Table of Contents

Abstract: This study proposes a fast 3D dynamic programming expansion to find a shortest surface in a 3D matrix. This algorithm can detect boundaries in an image sequence. Using phantom image studies with added uniform distributed noise from different SNRs, the unsigned error of this proposed method is investigated. Comparing the automated results to the gold standard, the best averaged relative unsigned error of the proposed method is 0.77% (SNR = 20 dB), and its corresponding parameter values are reported. We further apply this method to detect the boundary of the real superficial femoral artery (SFA) in MRI sequences without a contrast injection. The manual tracings on the SFA boundaries are performed by well-trained experts to be the gold standard. The comparisons between the manual tracings and automated results are made on 16 MRI sequences (800 total images). The average unsigned error rate is 2.4% (SD = 2.0%). The results demonstrate that the proposed method can perform qualitatively better than the 2D dynamic programming for vessel boundary detection on MRI sequences.

Abstract: This paper presents a microdevice for monitoring, control and management of electric loads at home. The key idea is to compact the electronic design as much as possible in order to install it inside a Schuko socket. Moreover, the electronic Schuko socket (electronic microdevice + Schuko socket) has the feature of communicating with a central unit and with other microdevices over the existing powerlines. Using the existing power lines, the proposed device can be installed in new buildings or in old ones. The main use of this device is to monitor, control and manage electric loads to save energy and prevent accidents produced by different kind of devices (e.g., iron) used in domestic tasks. The developed smart device is based on a single phase multifunction energy meter manufactured by Analog Devices (ADE7753) to measure the consumption of electrical energy and thento transmit it using a serial interface. To provide current measurement information to the ADE7753, an ultra flat SMD open loop integrated circuit current transducer based on the Hall effect principle manufactured by Lem (FHS-40P/SP600) has been used. Moreover, each smart device has a PL-3120 smart transceiver manufactured by LonWorks to execute the user’s program, to communicate with the ADE7753 via serial interface and to transmit information to the central unit via powerline communication. Experimental results show the exactitude of the measurements made using the developed smart device.

Abstract: High precision positioning technology for a kind of high speed maglev train with an electromagnetic suspension (EMS) system is studied. At first, the basic structure and functions of the position sensor are introduced and some key techniques to enhance the positioning precision are designed. Then, in order to further improve the positioning signal quality and the fault-tolerant ability of the sensor, a new kind of discrete-time tracking differentiator (TD) is proposed based on nonlinear optimal control theory. This new TD has good filtering and differentiating performances and a small calculation load. It is suitable for real-time signal processing. The stability, convergence property and frequency characteristics of the TD are studied and analyzed thoroughly. The delay constant of the TD is figured out and an effective time delay compensation algorithm is proposed. Based on the TD technology, a filtering process is introduced in to improve the positioning signal waveform when the sensor is under bad working conditions, and a two-sensor switching algorithm is designed to eliminate the positioning errors caused by the joint gaps of the long stator. The effectiveness and stability of the sensor and its signal processing algorithms are proved by the experiments on a test train during a long-term test run.

Abstract: In a biometric authentication system using protected templates, a pseudonymous identifier is the part of a protected template that can be directly compared. Each compared pair of pseudonymous identifiers results in a decision testing whether both identifiers are derived from the same biometric characteristic. Compared to an unprotected system, most existing biometric template protection methods cause to a certain extent degradation in biometric performance. Fusion is therefore a promising way to enhance the biometric performance in template-protected biometric systems. Compared to feature level fusion and score level fusion, decision level fusion has not only the least fusion complexity, but also the maximum interoperability across different biometric features, template protection and recognition algorithms, templates formats, and comparison score rules. However, performance improvement via decision level fusion is not obvious. It is influenced by both the dependency and the performance gap among the conducted tests for fusion. We investigate in this paper several fusion scenarios (multi-sample, multi-instance, multi-sensor, multi-algorithm, and their combinations) on the binary decision level, and evaluate their biometric performance and fusion efficiency on a multi-sensor fingerprint database with 71,994 samples.

Abstract: This paper presents the CONCERT framework, a push/filter information consumption paradigm, based on a rule-based semantic contextual information system for tourism. CONCERT suggests a specific insight of the notion of context from a human mobility perspective. It focuses on the particular characteristics and requirements of travellers and addresses the drawbacks found in other approaches. Additionally, CONCERT suggests the use of digital broadcasting as push communication technology, whereby tourism information is disseminated to mobile devices. This information is then automatically filtered by a network of ontologies and offered to tourists on the screen. The results obtained in the experiments carried out show evidence that the information disseminated through digital broadcasting can be manipulated by the network of ontologies, providing contextualizedinformation that produces user satisfaction.

Abstract: This paper presents OnRoute, a framework for developing and running ubiquitous software that provides information services to passengers of public transportation, including payment systems and on-route guidance services. To achieve a high level of interoperability, accessibility and context awareness, OnRoute uses the ubiquitous computing paradigm. To guarantee the quality of the software produced, the reliable software principles used in critical contexts, such as automotive systems, are also considered by the framework. The main components of its architecture (run-time, system services, software components and development discipline) and how they are deployed in the transportation network (stations and vehicles) are described in this paper. Finally, to illustrate the use of OnRoute, the development of a guidance service for travellers is explained.

Abstract: In this paper, we summarize the results of using dynamic models borrowed from tracking theory in describing the time evolution of the state vector to have an estimate of the angular motion in a gyro-free inertial measurement unit (GF-IMU). The GF-IMU is a special type inertial measurement unit (IMU) that uses only a set of accelerometers in inferring the angular motion. Using distributed accelerometers, we get an angular information vector (AIV) composed of angular acceleration and quadratic angular velocity terms. We use a Kalman filter approach to estimate the angular velocity vector since it is not expressed explicitly within the AIV. The bias parameters inherent in the accelerometers measurements’ produce a biased AIV and hence the AIV bias parameters are estimated within an augmented state vector. Using dynamic models, the appended bias parameters of the AIV become observable and hence we can have unbiased angular motion estimate. Moreover, a good model is required to extract the maximum amount of information from the observation. Observability analysis is done to determine the conditions for having an observable state space model. For higher grades of accelerometers and under relatively higher sampling frequency, the error of accelerometer measurements is dominated by the noise error. Consequently, simulations are conducted on two models, one has bias parameters appended in the state space model and the other is a reduced model without bias parameters.

Abstract: This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production.

Abstract: Slurry can be oxidized to eliminate undesirable emissions, including malodorous hydrogen sulfide (H₂S). However, it is difficult to assess the optimal amount of oxidizing agent required. In this study, one cow and one pig manure, each in three particle size ranges were oxidized with 0–350 mg ozone/L manure. Redox and H₂S concentration were measured continuously. During ozonation the manures gave equivalent redox potential curves. A relatively rapid rise in redox potential was observed within a range of −275 mV to −10 mV, with all manures changing as a minimum from −200 mV to −80 mV. The gaseous H₂S emissions were decreased by 99.5% during the redox increase (−200 mV to −80 mV). This is attributed to H₂S oxidation by ozone and oxygen, and is not due to H₂S deprotonation or gas flushing. By identifying the initiation of the final redox level following the rise, the amount of ozone required to remove H₂S from the manure samples was estimated to be in the range of 6–24 mg O₃/L manure, depending on the type of manure. Hence, continuous monitoring of redox potential (termination of the redox rise) during the oxidation treatment is a simple method of achieving cost-effective minimization of H₂S emissions from slurry.

Abstract: Activity monitoring of a person for a long-term would be helpful for controlling lifestyle associated diseases. Such diseases are often linked with the way a person lives. An unhealthy and irregular standard of living influences the risk of such diseases in the later part of one’s life. The symptoms and the initial signs of these diseases are common to the people with irregular lifestyle. In this paper, we propose a novel healthcare framework to manage lifestyle diseases using long-term activity monitoring. The framework recognizes the user’s activities with the help of the sensed data in runtime and reports the irregular and unhealthy activity patterns to a doctor and a caregiver. The proposed framework is a hierarchical structure that consists of three modules: activity recognition, activity pattern generation and lifestyle disease prediction. We show that it is possible to assess the possibility of lifestyle diseases from the sensor data. We also show the viability of the proposed framework.

Abstract: For the safety of prestressed structures, prestress loss is a critical issue that will increase with structural damage, so it is necessary to investigate prestress loss of prestressed structures under different damage scenarios. Unfortunately, to date, no qualified techniques are available due to difficulty for sensors to survive in harsh construction environments of long service life and large span. In this paper, a novel smart steel strand based on the Brillouin optical time domain analysis (BOTDA) sensing technique was designed and manufactured, and then series of tests were used to characterize properties of the smart steel strands. Based on prestress loss principle analysis of damaged structures, laboratory tests of two similar beams with different damages were used to verify the concept of full-scale prestress loss monitoring of damaged reinforced concrete (RC) beams by using the smart steel strands. The prestress losses obtained from the Brillouin sensors are compared with that from conventional sensors, which provided the evolution law of prestress losses of damaged RC beams. The monitoring results from the proposed smart strand can reveal both spatial distribution and time history of prestress losses of damaged RC beams.

Abstract: Fiber-optic sensors, especially fiber Bragg grating (FBG) sensors are very attractive due to their numerous advantages over traditional sensors, such as light weight, high sensitivity, cost-effectiveness, immunity to electromagnetic interference, ease of multiplexing and so on. Therefore, fiber-optic sensors have been intensively studied during the last several decades. Nowadays, with the development of novel fiber technology, more and more newly invented fiber technologies bring better and superior performance to fiber-optic sensing networks. In this paper, the applications of some advanced photonic technologies including fiber lasers and microwave photonic technologies for fiber sensing applications are reviewed. FBG interrogations based on several kinds of fiber lasers, especially the novel Fourier domain mode locking fiber laser, have been introduced; for the application of microwave photonic technology, examples of microwave photonic filtering utilized as a FBG sensing interrogator and microwave signal generation acting as a transversal loading sensor have been given. Both theoretical analysis and experimental demonstrations have been carried out. The comparison of these advanced photonic technologies for the applications of fiber sensing is carried out and important issues related to the applications have been addressed and the suitable and potential application examples have also been discussed in this paper.

Abstract: Fluorescence sensing of saccharides and glycoproteins using a boronic acid functionalized squarylium cyanine dye (“SQ-BA”) is characterized in terms of synthetic, fluorometric, thermodynamic and kinetic parameters. In our previous work, this newly synthesized dye was successfully applied to the separation and quantification of Gram-positive bacteria by capillary electrophoresis with laser-induced fluorescence detection (CE-LIF); however, the fundamental properties of the dye and its saccharide complexes still required elucidation, as presented in this paper. The dye itself forms nonemissive, soluble aggregates in aqueous solution. With the addition of a monosaccharide, the dye aggregate dissociates to form an emissive monomer accompanied by the formation of a cyclic cis-diol ester with long-wavelength emission (l_ex = 630 nm, l_em = 660 nm). A very large fluorescence enhancement factor of 18× was observed for the sensing dye as a fructose complex at pH 10, yielding a limit of detection of 10 mM fructose. The relative order of fluorescence enhancement of SQ-BA with other monosaccharides was found to be: fructose > ribose > arabinose ≈ galactose > xylose > mannose > rhamnose > fucose ≈ glucose; and apparent affinity constants of 10^2.80, 10^2.08 and 10^0.86 M⁻¹ were determined for fructose, ribose and glucose, respectively. Formation of the emissive complexes occurred within minutes, proving the kinetics of the sugar-dye interactions to be suitable for on-column labeling methods in CE-LIF. Furthermore, the sensing dye was successfully applied to glycoproteins, mucin type I–S and type III, which were detected with high sensitivity in batch aqueous solution as a result of the sugar-selective boronic acid-diol esterification as well as hydrophobic interactions.

Abstract: Virulence and adaptability of many Gram-negative bacterial species are associated with an N-acylhomoserine lactone (AHL) gene regulation mechanism called quorum sensing (QS). The arrangement of quorum sensing genes is variable throughout bacterial genomes, although there are unifying themes that are common among the various topological arrangements. A bioinformatics survey of 1,403 complete bacterial genomes revealed characteristic gene topologies in 152 genomes that could be classified into 16 topological groups. We developed a concise notation for the patterns and show that the sequences of LuxR regulators and LuxI autoinducer synthase proteins cluster according to the topological patterns. The annotated topologies are deposited online with links to sequences and genome annotations at http://bacteria.itk.ppke.hu/QStopologies/.

Abstract: An electrochemical microbiosensor for DNA has been fabricated based on new acrylic microspheres modified with reactive N-acryloxysuccinimide (NAS) functional groups. Hydrophobic poly(n-butylacrylate-N-acryloxysuccinimide) microspheres were synthesized in an emulsion form with a simple one-step photopolymerization technique. Aminated DNA probe was attached to the succinimde functional group of the acrylic microspheres via covalent bonding. The hybridization of the immobilized DNA probe with the complementary DNA was studied by differential pulse voltametry using anthraquninone-2-sulfonic acid monohydrate sodium salt (AQMS) as the electroactive hybridization label. The influences of many factors such as duration of DNA probe immobilization and hybridization, pH, type of ions, buffer concentrations, ionic strength, operational temperature and non-complementary DNA on the biosensor performance were evaluated. Under optimized conditions, the DNA microbiosensor demonstrated a linear response range to target DNA over a wide concentration range of 1.0 × 10⁻¹⁶ and 1.0 ´ 10⁻⁸ M with a lower limit of detection (LOD) of 9.46 ´ 10⁻¹⁷ M (R² = 0.97). This DNA microbiosensor showed good reproducibility with 2.84% RSD (relative standard deviation) (n = 3). Application of the NAS-modified acrylic microspheres in the construction of DNA microbiosensor had improved the overall analytical performance of the resultant DNA microbiosensor when compared with other reported DNA biosensors using other nano-materials for membranes and microspheres as DNA immobilization matrices.

Abstract: Quantum dots (QDs) are a new class of fluorescent labeling for biological and biomedical applications. In this study, we detected prostate stem cell antigen (PSCA) expression correlated with tumor grade and stage in human prostate cancer by QDs-based immunolabeling and conventional immunohistochemistry (IHC), and evaluated the sensitivity and stability of QDs-based immunolabeling in comparison with IHC. Our data revealed that increasing levels of PSCA expression accompanied advanced tumor grade (QDs labeling, r = 0.732, p < 0.001; IHC, r = 0.683, p < 0.001) and stage (QDs labeling, r = 0.514, p = 0.001; IHC, r = 0.432, p = 0.005), and the similar tendency was detected by the two methods. In addition, by comparison between the two methods, QDs labeling was consistent with IHC in detecting the expression of PSCA in human prostate tissue correlated with different pathological types (K = 0.845, p < 0.001). During the observation time, QDs exhibited superior stability. The intensity of QDs fluorescence remained stable for two weeks (p = 0.083) after conjugation to the PSCA protein, and nearly 93% of positive expression with their fluorescence still could be seen after four weeks.

Abstract: Over the past five years, Distributed Temperature Sensing (DTS) along fiber optic cables using Raman backscattering has become an important tool in the environmental sciences. Many environmental applications of DTS demand very accurate temperature measurements, with typical RMSE < 0.1 K. The aim of this paper is to describe and clarify the advantages and disadvantages of double-ended calibration to achieve such accuracy under field conditions. By measuring backscatter from both ends of the fiber optic cable, one can redress the effects of differential attenuation, as caused by bends, splices, and connectors. The methodological principles behind the double-ended calibration are presented, together with a set of practical considerations for field deployment. The results from a field experiment are presented, which show that with double-ended calibration good accuracies can be attained in the field.

Abstract: Localization is one of the most important issues associated with underwater acoustic sensor networks, especially when sensor nodes are randomly deployed. Given that it is difficult to deploy beacon nodes at predetermined locations, localization schemes with a mobile beacon on the sea surface or along the planned path are inherently convenient, accurate, and energy-efficient. In this paper, we propose a new range-free Localization with a Mobile Beacon (LoMoB). The mobile beacon periodically broadcasts a beacon message containing its location. Sensor nodes are individually localized by passively receiving the beacon messages without inter-node communications. For location estimation, a set of potential locations are obtained as candidates for a node’s location and then the node’s location is determined through the weighted mean of all the potential locations with the weights computed based on residuals.

Abstract: The concept of the information society is now a common one, as opposed to the industrial society that dominated the economy during the last years. It is assumed that all sectors should have access to information and reap its benefits. Elderly people are, in this respect, a major challenge, due to their lack of interest in technological progress and their lack of knowledge regarding the potential benefits that information society technologies might have on their lives. The Naviga Project (An Open and Adaptable Platform for the Elderly and Persons with Disability to Access the Information Society) is a European effort, whose main goal is to design and develop a technological platform allowing elder people and persons with disability to access the internet and the information society. Naviga also allows the creation of services targeted to social networks, mind training and personalized health care. In this paper we focus on the health care and information services designed on the project, the technological platform developed and details of two representative elements, the virtual reality hand rehabilitation and the health information intelligent system.

Abstract: Recently, the hydrogen gas sensing properties of semiconductor oxide (SMO) nanostructures have been widely investigated. In this article, we provide a comprehensive review of the research progress in the last five years concerning hydrogen gas sensors based on SMO thin film and one-dimensional (1D) nanostructures. The hydrogen sensing mechanism of SMO nanostructures and some critical issues are discussed. Doping, noble metal-decoration, heterojunctions and size reduction have been investigated and proved to be effective methods for improving the sensing performance of SMO thin films and 1D nanostructures. The effect on the hydrogen response of SMO thin films and 1D nanostructures of grain boundary and crystal orientation, as well as the sensor architecture, including electrode size and nanojunctions have also been studied. Finally, we also discuss some challenges for the future applications of SMO nanostructured hydrogen sensors.

Abstract: When extracting discriminative features from multimodal data, current methods rarely concern themselves with the data distribution. In this paper, we present an assumption that is consistent with the viewpoint of discrimination, that is, a person’s overall biometric data should be regarded as one class in the input space, and his different biometric data can form different Gaussians distributions, i.e., different subclasses. Hence, we propose a novel multimodal feature extraction and recognition approach based on subclass discriminant analysis (SDA). Specifically, one person’s different bio-data are treated as different subclasses of one class, and a transformed space is calculated, where the difference among subclasses belonging to different persons is maximized, and the difference within each subclass is minimized. Then, the obtained multimodal features are used for classification. Two solutions are presented to overcome the singularity problem encountered in calculation, which are using PCA preprocessing, and employing the generalized singular value decomposition (GSVD) technique, respectively. Further, we provide nonlinear extensions of SDA based multimodal feature extraction, that is, the feature fusion based on KPCA-SDA and KSDA-GSVD. In KPCA-SDA, we first apply Kernel PCA on each single modal before performing SDA. While in KSDA-GSVD, we directly perform Kernel SDA to fuse multimodal data by applying GSVD to avoid the singular problem. For simplicity two typical types of biometric data are considered in this paper, i.e., palmprint data and face data. Compared with several representative multimodal biometrics recognition methods, experimental results show that our approaches outperform related multimodal recognition methods and KSDA-GSVD achieves the best recognition performance.

Abstract: Non-invasive detection and monitoring of lethal diseases, such as cancer, are considered as effective factors in treatment and survival. We describe a new disease diagnostic approach, denoted “reactomics”, based upon reactions between blood sera and an array of vesicles comprising different lipids and polydiacetylene (PDA), a chromatic polymer. We show that reactions between sera and such a lipid/PDA vesicle array produce chromatic patterns which depend both upon the sera composition as well as the specific lipid constituents within the vesicles. The chromatic patterns were processed through machine-learning algorithms, and the bioinformatics analysis could distinguish both between cancer-bearing and healthy patients, respectively, as well between two types of cancers. Size-separation and enzymatic digestion experiments indicate that lipoproteins are the primary components in sera which react with the chromatic biomimetic vesicles. This colorimetric reactomics concept is highly generic, robust, and does not require a priori knowledge upon specific disease markers in sera. Therefore, it could be employed as complementary or alternative approach for disease diagnostics.

Abstract: It has been shown that a suppressive protein, acting as an immune suppressor, is generated in animals and humans under particular stresses. However, studies related to immunosuppressive factors in response to the stress resulting from acute exercise are limited. This study compares the effects of pre- and post-exercise human serum on concanavalin A stimulated lymphocyte proliferation of mice. In the present study, blood samples in eight male undergraduates (age 21 ± 0.7 years) were taken before and immediately after ten sets of exercise consisting of 15 free and 30 10-kg loaded squat jumps in each set. The suppression of lymphocyte proliferation was analysed with high pressure liquid chromatography. It was noted from the result of gel chromatography columns that the post-exercise values of the suppression of lymphocyte proliferation, in comparison to corresponding pre-exercise values, were generally greater with significant differences observed in 7.5th–9th min post-exercise eluates (P < 0.05). Such findings suggest that intense eccentric type exercise may lead to generation of immunosuppressive factor(s) in young males.

Abstract: In multiple sclerosis (MS) the gold standard for the diagnosis and prognosis is, up to now, the use of magnetic resonance imaging markers. No alternative simpler assays proven of use, except for cerebrospinal fluid analysis, have been provided in MS diagnosis. Therefore, there is a need to develop non-invasive, sensitive, simple new techniques for the clinical routine. Herein we present the evaluation of the feasibility of a glycopeptide-based biosensor to detect MS specific antibodies in sera using the surface plasmon resonance technology. The previously described glycopeptide antigen CSF114(Glc) has been immobilized on a gold sensor chip and the method has been optimized for real-time specific autoantibody detection directly in sera. A population of 60 healthy blood donors and 61 multiple sclerosis patients has been screened. The receiver operating characteristic (ROC)-based analysis has established the optimal diagnostic cut-off value for the method obtaining a sensitivity of 36% and a specificity of 95%. Sample sera have been also screened with a previously validated ELISA.

Abstract: Chemiresistors (conductometric sensor) were fabricated on the basis of novel nanomaterials—silica nanosprings ALD coated with ZnO. The effects of high temperature and UV illumination on the electronic and gas sensing properties of chemiresistors are reported. For the thermally activated chemiresistors, a discrimination mechanism was developed and an integrated sensor-array for simultaneous real-time resistance scans was built. The integrated sensor response was tested using linear discriminant analysis (LDA). The distinguished electronic signatures of various chemical vapors were obtained at ppm level. It was found that the recovery rate at high temperature drastically increases upon UV illumination. The feasibility study of the activation method by UV illumination at room temperature was conducted.

Abstract: Foreground detection has been used extensively in many applications such as people counting, traffic monitoring and face recognition. However, most of the existing detectors can only work under limited conditions. This happens because of the inability of the detector to distinguish foreground and background pixels, especially in complex situations. Our aim is to improve the robustness of foreground detection under sudden and gradual illumination change, colour similarity issue, moving background and shadow noise. Since it is hard to achieve robustness using a single model, we have combined several methods into an integrated system. The masked grey world algorithm is introduced to handle sudden illumination change. Colour co-occurrence modelling is then fused with the probabilistic edge-based background modelling. Colour co-occurrence modelling is good infiltering moving background and robust to gradual illumination change, while an edge-based modelling is used for solving a colour similarity problem. Finally, an extended conditional random field approach is used to filter out shadow and afterimage noise. Simulation results show that our algorithm performs better compared to the existing methods, which makes it suitable for higher-level applications.

Abstract: We have successfully demonstrated video-rate CMOS single-photon avalanche diode (SPAD)-based cameras for fluorescence lifetime imaging microscopy (FLIM) by applying innovative FLIM algorithms. We also review and compare several time-domain techniques and solid-state FLIM systems, and adapt the proposed algorithms for massive CMOS SPAD-based arrays and hardware implementations. The theoretical error equations are derived and their performances are demonstrated on the data obtained from 0.13 μm CMOS SPAD arrays and the multiple-decay data obtained from scanning PMT systems. In vivo two photon fluorescence lifetime imaging data of FITC-albumin labeled vasculature of a P22 rat carcinosarcoma (BD9 rat window chamber) are used to test how different algorithms perform on bi-decay data. The proposed techniques are capable of producing lifetime images with enough contrast.

Abstract: The presence of smoke is the first symptom of fire; therefore to achieve early fire detection, accurate and quick estimation of the presence of smoke is very important. In this paper we propose an algorithm to detect the presence of smoke using video sequences captured by Internet Protocol (IP) cameras, in which important features of smoke, such as color, motion and growth properties are employed. For an efficient smoke detection in the IP camera platform, a detection algorithm must operate directly in the Discrete Cosine Transform (DCT) domain to reduce computational cost, avoiding a complete decoding process required for algorithms that operate in spatial domain. In the proposed algorithm the DCT Inter-transformation technique is used to increase the detection accuracy without inverse DCT operation. In the proposed scheme, firstly the candidate smoke regions are estimated using motion and color smoke properties; next using morphological operations the noise is reduced. Finally the growth properties of the candidate smoke regions are furthermore analyzed through time using the connected component labeling technique. Evaluation results show that a feasible smoke detection method with false negative and false positive error rates approximately equal to 4% and 2%, respectively, is obtained.

Abstract: In this study, a camera to infrared diode (IRED) distance estimation problem was analyzed. The main objective was to define an alternative to measures depth only using the information extracted from pixel grey levels of the IRED image to estimate the distance between the camera and the IRED. In this paper, the standard deviation of the pixel grey level in the region of interest containing the IRED image is proposed as an empirical parameter to define a model for estimating camera to emitter distance. This model includes the camera exposure time, IRED radiant intensity and the distance between the camera and the IRED. An expression for the standard deviation model related to these magnitudes was also derived and calibrated using different images taken under different conditions. From this analysis, we determined the optimum parameters to ensure the best accuracy provided by this alternative. Once the model calibration had been carried out, a differential method to estimate the distance between the camera and the IRED was defined and applied, considering that the camera was aligned with the IRED. The results indicate that this method represents a useful alternative for determining the depth information.

Abstract: This paper is focused on the automatic construction of 3D basic-semantic models of inhabited interiors using laser scanners with the help of RFID technologies. This is an innovative approach, in whose field scarce publications exist. The general strategy consists of carrying out a selective and sequential segmentation from the cloud of points by means of different algorithms which depend on the information that the RFID tags provide. The identification of basic elements of the scene, such as walls, floor, ceiling, windows, doors, tables, chairs and cabinets, and the positioning of their corresponding models can then be calculated. The fusion of both technologies thus allows a simplified 3D semantic indoor model to be obtained. This method has been tested in real scenes under difficult clutter and occlusion conditions, and has yielded promising results.

Abstract: Various nanowire or nanotube-based devices have been demonstrated to fulfill the anticipated future demands on sensors. To fabricate such devices, electric field-based methods have demonstrated a great potential to integrate one-dimensional nanostructures into various forms. This review paper discusses theoretical and experimental aspects of the working principles, the assembled structures, and the unique functions associated with electric field-based assembly. The challenges and opportunities of the assembly methods are addressed in conjunction with future directions toward high performance sensors.

Abstract: The rearing of poultry for meat production (broilers) is an agricultural food industry with high relevance to the economy and development of some countries. Periodic episodes of extreme climatic conditions during the summer season can cause high mortality among birds, resulting in economic losses. In this context, ventilation systems within poultry houses play a critical role to ensure appropriate indoor climatic conditions. The objective of this study was to develop a multisensor system to evaluate the design of the ventilation system in broiler houses. A measurement system equipped with three types of sensors: air velocity, temperature and differential pressure was designed and built. The system consisted in a laptop, a data acquisition card, a multiplexor module and a set of 24 air temperature, 24 air velocity and two differential pressure sensors. The system was able to acquire up to a maximum of 128 signals simultaneously at 5 second intervals. The multisensor system was calibrated under laboratory conditions and it was then tested in field tests. Field tests were conducted in a commercial broiler farm under four different pressure and ventilation scenarios in two sections within the building. The calibration curves obtained under laboratory conditions showed similar regression coefficients among temperature, air velocity and pressure sensors and a high goodness fit (R² = 0.99) with the reference. Under field test conditions, the multisensor system showed a high number of input signals from different locations with minimum internal delay in acquiring signals. The variation among air velocity sensors was not significant. The developed multisensor system was able to integrate calibrated sensors of temperature, air velocity and differential pressure and operated succesfully under different conditions in a mechanically-ventilated broiler farm. This system can be used to obtain quasi-instantaneous fields of the air velocity and temperature, as well as differential pressure maps to assess the design and functioning of ventilation system and as a verification and validation (V&V) system of Computational Fluid Dynamics (CFD) simulations in poultry farms.

Abstract: An ultimate goal for Ubiquitous Computing is to enable people to interact with the surrounding electrical devices using their habitual body gestures as they communicate with each other. The feasibility of such an idea is demonstrated through a wearable gestural device named Magic Ring (MR), which is an original compact wireless sensing mote in a ring shape that can recognize various finger gestures. A scenario of wireless multiple appliances control is selected as a case study to evaluate the usability of such a gestural interface. Experiments comparing the MR and a Remote Controller (RC) were performed to evaluate the usability. From the results, only with 10 minutes practice, the proposed paradigm of gestural-based control can achieve a performance of completing about six tasks per minute, which is in the same level of the RC-based method.

Abstract: Determination of (in)activity periods when monitoring human body motion is a mandatory preprocessing step in all human inertial navigation and position analysis applications. Distinction of (in)activity needs to be established in order to allow the system to recompute the calibration parameters of the inertial sensors as well as the Zero Velocity Updates (ZUPT) of inertial navigation. The periodical recomputation of these parameters allows the application to maintain a constant degree of precision. This work presents a comparative study among different well known inertial magnitude-based detectors and proposes a new approach by applying spectrum-based detectors and memory-based detectors. A robust statistical comparison is carried out by the use of an accelerometer and angular rate signal synthesizer that mimics the output of accelerometers and gyroscopes when subjects are performing basic activities of daily life. Theoretical results are verified by testing the algorithms over signals gathered using an Inertial Measurement Unit (IMU). Detection accuracy rates of up to 97% are achieved.

Abstract: Failure detectors are one of the fundamental components for building a distributed system with high availability. In order to maintain the efficiency and scalability of failure detection in a complicated large-scale distributed system, accrual failure detectors that can adapt to multiple applications have been studied extensively. In this paper, an new accrual failure detector—LA-FD with low system overhead has been proposed specifically for current mobile network equipment on the Internet whose processing power, memory space and power supply are all constrained. It does not rely on the probability distribution of message transmission time, or on the maintenance of a history message window. By simple calculation, LA-FD provides adaptive failure detection service with high accuracy to multiple upper applications. The related experiments and results have also been presented.

Abstract: A novel measurement prototype based on a mobile vehicle that carries a laser scanning sensor is proposed. The prototype is intended for the automated measurement of the interior 3D geometry of large-diameter long-stepped pipes. The laser displacement sensor, which has a small measurement range, is mounted on an extended arm of known length. It is scanned to improve the measurement accuracy for large-sized pipes. A fixing mechanism based on two sections is designed to ensure that the stepped pipe is concentric with the axis of rotation of the system. Data are acquired in a cylindrical coordinate system and fitted in a circle to determine diameter. Systematic errors covering arm length, tilt, and offset errors are analyzed and calibrated. The proposed system is applied to sample parts and the results are discussed to verify its effectiveness. This technique measures a diameter of 600 mm with an uncertainty of 0.02 mm at a 95% confidence probability. A repeatability test is performed to examine precision, which is 1.1 µm. A laser tracker is used to verify the measurement accuracy of the system, which is evaluated as 9 µm within a diameter of 600 mm.

Abstract: This work presents a novel fiber-optic sensing system, capable of monitoring debris flows or other natural hazards that produce ground vibrations. The proposed sensing system comprises a demodulator (BraggSCOPE, FS5500), which includes a broadband light source and a data logger, a four-port coupler and four Fiber Bragg Grating (FBG) accelerometers. Based on field tests, the performance of the proposed fiber-optic sensing system is compared with that of a conventional sensing system that includes a geophone or a microphone. Following confirmation of the reliability of the proposed sensing system, the fiber-optic sensing systems are deployed along the Ai-Yu-Zi and Chu-Shui Creeks in Nautou County of central Taiwan for monitoring debris flows. Sensitivity test of the deployed fiber-optic sensing system along the creek banks is also performed. Analysis results of the seismic data recorded by the systems reveal in detail the frequency characteristics of the artificially generated ground vibrations. Results of this study demonstrate that the proposed fiber-optic sensing system is highly promising for use in monitoring natural disasters that generate ground vibrations.

Abstract: The data collection problem is one of the most important issues in Wireless Sensor Networks (WSNs). Constructing a tree from all sensor nodes to the sink node is the simplest way, but this raises the problem of energy unbalance since the sensors closer to the sink node would have much higher workloads from relaying data. To cope with the energy unbalance problem, a number of mobile-sink mechanisms have been proposed in recent years. This paper proposes an Energy-Balanced Data Collection mechanism, called EBDC, which determines the trajectory of a mobile data collector (or mobile sink) such that the data-relaying workloads of all sensors can be totally balanced. Theoretical analysis and performance evaluation reveal that the proposed EBDC mechanism outperforms the existing approaches in terms of network lifetime and the degree of energy balancing.

Abstract: In order to improve algorithm efficiency and performance, a technique for image fusion based on the Non-subsampled Contourlet Transform (NSCT) domain and an Accelerated Non-negative Matrix Factorization (ANMF)-based algorithm is proposed in this paper. Firstly, the registered source images are decomposed in multi-scale and multi-direction using the NSCT method. Then, the ANMF algorithm is executed on low-frequency sub-images to get the low-pass coefficients. The low frequency fused image can be generated faster in that the update rules for W and H are optimized and less iterations are needed. In addition, the Neighborhood Homogeneous Measurement (NHM) rule is performed on the high-frequency part to achieve the band-pass coefficients. Finally, the ultimate fused image is obtained by integrating all sub-images with the inverse NSCT. The simulated experiments prove that our method indeed promotes performance when compared to PCA, NSCT-based, NMF-based and weighted NMF-based algorithms.

Abstract: We propose and demonstrate a fiber Bragg grating (FBG) sensor network employing the code division multiple access (CDMA) technique to identify information from individual sensors. To detect information without considering time delays between sensors, a sliding correlation method is applied, in which two different signals with the same pseudo-random binary sequence (PRBS) pattern, but slightly different frequencies, are applied to the source and detector sides. Moreover, for time domain detection, a wavelength-to-time conversion technique using a wavelength dispersive medium is introduced. The experimental results show that the proposed sensor network has a wide strain dynamic range of 2,400 μe and a low crosstalk of 950:1.

Abstract: Homogeneous matrices of calcium oxide (CaO) were prepared by mixing this material with polyethylene glycol (PEG) acting as malleable inert support in order to obtain processable composites. Preliminary tests were carried out to assess the best concentration of CaO in the composite, individuated in the CaO/PEG weight ratio of 1/4. Experimental data highlighted that the composite was able to selectively detect carbon dioxide (CO₂) via a nanogravimetric method by performing the experiments inside an atmosphere-controlled chamber filled with CO₂. Furthermore, the composite material showed a linear absorption of CO₂ as a function of the gas concentration inside the atmosphere-controlled chamber, thus paving the way for the possible use of these matrices for applications in the field of sensor devices for long-term evaluation of accumulated environmental CO₂.

Abstract: Horizontal and vertical positions of points for the control assessment of crane rails are classically determined separately. The procedure is time consuming and causes non-homogenous accuracy of the horizontal and vertical position of control points. The proposed alternative approach is based on polar measurements using a high accuracy total station instrument and a special platform with two precise surveying prisms fixed on it. Measurements are carried out from a single station thus ensuring a common coordinate system and homogenous accuracy. The position of the characteristic point of a rail is derived from the measured positions of both prisms with known geometry of the platform. The influence of platform non-horizontality is defined, along with its elimination procedure. Accuracy assessment is ensured with redundant measurements. Result of the proposed procedure is a numerical and graphical presentation of characteristic points. The control parameters required in international Eurocode standards are easily determined from them.

Abstract: This study proposes a new condition diagnosis method for rotating machinery developed using least squares mapping (LSM) and a fuzzy neural network. The non-dimensional symptom parameters (NSPs) in the time domain are defined to reflect the features of the vibration signals measured in each state. A sensitive evaluation method for selecting good symptom parameters using detection index (DI) is also proposed for detecting and distinguishing faults in rotating machinery. In order to raise the diagnosis sensitivity of the symptom parameters the synthetic symptom parameters (SSPs) are obtained by LSM. Moreover, possibility theory and the Dempster & Shafer theory (DST) are used to process the ambiguous relationship between symptoms and fault types. Finally, a sequential diagnosis method, using sequential inference and a fuzzy neural network realized by the partially-linearized neural network (PLNN), is also proposed, by which the conditions of rotating machinery can be identified sequentially. Practical examples of fault diagnosis for a roller bearing are shown to verify that the method is effective.

Abstract: A fluorescent probe for glutathione (GSH) detection was developed. Our study indicates a possible mechanism which couples a conjugate addition and micelle-catalyzed large membered ring formation/elimination sequence. This method enables excellent selectivity towards GSH over other biological thiols such as cysteine (Cys) and homocysteine (Hcy). The proposed method is precise with a relative standard deviation (R.S.D) lower than 6% (n = 3) and has been successfully applied to determine GSH in human plasma with recoveries between 99.2% and 102.3%.

Abstract: Dielectrophoresis (DEP) is the phenomenon in which a particle, such as a living cell, is polarized and moved by electrical gravity in a non-uniform electric field. In the present study, the DEP force is utilized to act on the cells to induce spatial movement for investigating the correlation between the cell adhesion force and activation level of focal adhesion kinase (FAK). The DEP force produced by the non-uniform electric field was used to measure the cell adhesion force of ECV304 cells, on type 1 collagen (COL1)- and fibronectin (FN)-coated polydimethylsiloxane (PDMS) membranes. For COL1-coating, ECV304 cells revealed weak and variable adhesion force (0.343–0.760 nN) in the first eight hours of incubation. Interestingly, the cell adhesion force of ECV304 at two and five hours of cultivation was significantly high and matched their FAK activation level. In comparison, ECV304 on FN-coated membrane had higher and more stable cell adhesion force (0.577–2.053 nN). FN coating intensified the cell adhesion force of ECV304 with culture time and similar outcome was present on the activation level of FAK. Therefore, this study demonstrated a relationship between cell adhesion force and FAK activation level that was dependant on the choice of the extracellular matrix (ECM) component. Subsequently, two tyrosine kinase inhibitors (AG18 and genistein) and one PI3K inhibitor (LY294002) were applied to study the influence of protein phosphorylation on the cell adhesion force. FAK plays an important role on cell attachment and DEP force measurement is a useful technique for studying cell adhesion.

Abstract: A nanosensory membrane device was constructed for detecting liposome fusion through changes in an enzymatic activity. Inspired by a biological signal transduction system, the device design involved functionalized liposomal membranes prepared by self-assembly of the following molecular components: a synthetic peptide lipid and a phospholipid as matrix membrane components, a Schiff’s base of pyridoxal 5’-phosphate with phosphatidylethanolamine as a thermo-responsive artificial receptor, NADH-dependent L-lactate dehydrogenase as a signal amplifier, and Cu²⁺ ion as a signal mediator between the receptor and enzyme. The enzymatic activity of the membrane device was adjustable by changing the matrix lipid composition, reflecting the thermotropic phase transition behavior of the lipid membranes, which in turn controlled receptor binding affinity toward the enzyme-inhibiting mediator species. When an effective fusogen anionic polymer was added to these cationic liposomes, membrane fusion occurred, and the functionalized liposomal membranes responded with changes in enzymatic activity, thus serving as an effective nanosensory device for liposome fusion detection.

Abstract: Staphylococcus aureus is a major bacterial pathogen which causes clinical infections and food poisoning. This bacterium produces a group of twenty-one enterotoxins (SEs). These enterotoxins have two separate but related biological activities. They cause gastroenteritis and function as superantigens that activate large numbers of T cells. The current method for detection of enterotoxins activity is an in vivo monkey or kitten bioassay; however, this method is not practical to test on a large number of samples. Several immunological assays have been developed however, but these assays cannot distinguish between active toxin which causes food poisoning and inactive toxin, which can bind antibody, but shows no toxicity. The current study demonstrates that short term ex vivo exposure of primary naïve CD4⁺ T-cells or splenocytes to SEA induces differential expression and secretion of tumor necrosis factor (TNF) protein. We used immunomagnetic beads coated with anti-SEA antibody to specifically isolate SEA from food. After the eluted toxin was added to the cells SEA biological activity was measured by quantifying TNF protein expression or secretion.

Abstract: Cancer is a leading cause of death worldwide. New early tumor markers are needed to treat the disease at curable stages. In addition, new therapeutic targets are required to treat patients not responding to available treatments. Ion channels play major roles in health and disease, including cancer. Actually, several ion channels have been suggested as potential tumor markers and therapeutic targets for different types of malignancies. One of most studied ion channels in cancer is the voltage-gated potassium channel Eag1 (ether à go-go 1), which has a high potential to be used as a cancer biomarker. Eag1 is expressed in most human tumors, in contrast to its restricted distribution in healthy tissues. Several findings suggest Eag1 as a potential early marker for cervical, colon, and breast cancer. In addition, because Eag1 amplification/expression is associated with poor survival in leukemia, colon and ovarian cancer patients, it has also been proposed as a prognosis marker. Moreover, inhibition of either expression or activity of Eag1 leads to reduced proliferation of cancer cells, making Eag1 a potential anticancer target. Using Eag1 in cancer detection programs could help to reduce mortality from this disease.

Abstract: There has been an explosion of research into the physical and chemical properties of carbon-based nanomaterials, since the discovery of carbon nanotubes (CNTs) by Iijima in 1991. Carbon nanomaterials offer unique advantages in several areas, like high surface-volume ratio, high electrical conductivity, chemical stability and strong mechanical strength, and are thus frequently being incorporated into sensing elements. Carbon nanomaterial-based sensors generally have higher sensitivities and a lower detection limit than conventional ones. In this review, a brief history of glucose biosensors is firstly presented. The carbon nanotube and grapheme-based biosensors, are introduced in Sections 3 and 4, respectively, which cover synthesis methods, up-to-date sensing approaches and nonenzymatic hybrid sensors. Finally, we briefly outline the current status and future direction for carbon nanomaterials to be used in the sensing area.

Abstract: In recent years, there have been a number of reported studies on the use of non-destructive techniques to evaluate and determine mango maturity and ripeness levels. However, most of these reported works were conducted using single-modality sensing systems, either using an electronic nose, acoustics or other non-destructive measurements. This paper presents the work on the classification of mangoes (Magnifera Indica cv. Harumanis) maturity and ripeness levels using fusion of the data of an electronic nose and an acoustic sensor. Three groups of samples each from two different harvesting times (week 7 and week 8) were evaluated by the e-nose and then followed by the acoustic sensor. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to discriminate the mango harvested at week 7 and week 8 based solely on the aroma and volatile gases released from the mangoes. However, when six different groups of different maturity and ripeness levels were combined in one classification analysis, both PCA and LDA were unable to discriminate the age difference of the Harumanis mangoes. Instead of six different groups, only four were observed using the LDA, while PCA showed only two distinct groups. By applying a low level data fusion technique on the e-nose and acoustic data, the classification for maturity and ripeness levels using LDA was improved. However, no significant improvement was observed using PCA with data fusion technique. Further work using a hybrid LDA-Competitive Learning Neural Network was performed to validate the fusion technique and classify the samples. It was found that the LDA-CLNN was also improved significantly when data fusion was applied.

Abstract: Superconducting point contacts have been used for measuring magnetic polarizations, identifying magnetic impurities, electronic structures, and even the vibrational modes of small molecules. Due to intrinsically small energy scale in the subgap structures of the supercurrent determined by the size of the superconducting energy gap, superconductors provide ultrahigh sensitivities for high resolution spectroscopies. The so-called Andreev reflection process between normal metal and superconductor carries complex and rich information which can be utilized as powerful sensor when fully exploited. In this review, we would discuss recent experimental and theoretical developments in the supercurrent transport through superconducting point contacts and their relevance to sensing applications, and we would highlight their current issues and potentials. A true utilization of the method based on Andreev reflection analysis opens up possibilities for a new class of ultrasensitive sensors.

Abstract: Sometimes, one needs to control different emotional situations which can lead the person suffering them to dangerous situations, in both the medium and short term. There are studies which indicate that stress increases the risk of cardiac problems. In this study we have designed and built a stress sensor based on Galvanic Skin Response (GSR), and controlled by ZigBee. In order to check the device’s performance, we have used 16 adults (eight women and eight men) who completed different tests requiring a certain degree of effort, such as mathematical operations or breathing deeply. On completion, we appreciated that GSR is able to detect the different states of each user with a success rate of 76.56%. In the future, we plan to create an algorithm which is able to differentiate between each state.

Abstract: Self-selected walking speed is an important measure of ambulation ability used in various clinical gait experiments. Inertial sensors, i.e., accelerometers and gyroscopes, have been gradually introduced to estimate walking speed. This research area has attracted a lot of attention for the past two decades, and the trend is continuing due to the improvement of performance and decrease in cost of the miniature inertial sensors. With the intention of understanding the state of the art of current development in this area, a systematic review on the exiting methods was done in the following electronic engines/databases: PubMed, ISI Web of Knowledge, SportDiscus and IEEE Xplore. Sixteen journal articles and papers in proceedings focusing on inertial sensor based walking speed estimation were fully reviewed. The existing methods were categorized by sensor specification, sensor attachment location, experimental design, and walking speed estimation algorithm.

Abstract: Variable structure strategy is widely used for the control of sensor-actuator systems modeled by Euler-Lagrange equations. However, accurate knowledge on the model structure and model parameters are often required for the control design. In this paper, we consider model-free variable structure control of a class of sensor-actuator systems, where only the online input and output of the system are available while the mathematic model of the system is unknown. The problem is formulated from an optimal control perspective and the implicit form of the control law are analytically obtained by using the principle of optimality. The control law and the optimal cost function are explicitly solved iteratively. Simulations demonstrate the effectiveness and the efficiency of the proposed method.

Abstract: Credential-based authorization offers interesting advantages for ubiquitous scenarios involving limited devices such as sensors and personal mobile equipment: the verification can be done locally; it offers a more reduced computational cost than its competitors for issuing, storing, and verification; and it naturally supports rights delegation. The main drawback is the revocation of rights. Revocation requires handling potentially large revocation lists, or using protocols to check the revocation status, bringing extra communication costs not acceptable for sensors and other limited devices. Moreover, the effective revocation consent—considered as a privacy rule in sensitive scenarios—has not been fully addressed.This paper proposes an event-based mechanism empowering a new concept, the sleepyhead credentials, which allows to substitute time constraints and explicit revocation by activating and deactivating authorization rights according to events. Our approach is to integrate this concept in IdM systems in a hybrid model supporting delegation, which can be an interesting alternative for scenarios where revocation of consent and user privacy are critical. The delegation includes a SAML compliant protocol, which we have validated through a proof-of-concept implementation. This article also explains the mathematical model describing the event-based model and offers estimations of the overhead introduced by the system. The paper focus on health care scenarios, where we show the flexibility of the proposed event-based user consent revocation mechanism.

Abstract: The paper presents an indoor navigation solution by combining physical motion recognition with wireless positioning. Twenty-seven simple features are extracted from the built-in accelerometers and magnetometers in a smartphone. Eight common motion states used during indoor navigation are detected by a Least Square-Support Vector Machines (LS-SVM) classification algorithm, e.g., static, standing with hand swinging, normal walking while holding the phone in hand, normal walking with hand swinging, fast walking, U-turning, going up stairs, and going down stairs. The results indicate that the motion states are recognized with an accuracy of up to 95.53% for the test cases employed in this study. A motion recognition assisted wireless positioning approach is applied to determine the position of a mobile user. Field tests show a 1.22 m mean error in “Static Tests” and a 3.53 m in “Stop-Go Tests”.

Abstract: AI-2–mediated quorum sensing has been identified in various bacteria, including both Gram-negative and Gram-positive species, and numerous phenotypes have been reported to be regulated by this mechanism, using the luxS-mutant strain. But the AI-2 production process confused this regulatory function; some considered this regulation as the result of a metabolic change, which refers to an important metabolic cycle named activated methyl cycle (AMC), caused by luxS-mutant simultaneously with the defect of AI-2. Herein we hypothesized that the quorum sensing system—not the metabolic aspect—is responsible for such a regulatory function. In this study, we constructed plasmids infused with sahH and induced protein expression in the luxS-mutant strain to make the quorum-sensing system and metabolic system independent. The biofilm-related genes were investigated by real-time polymerase chain reaction (PCR), and the results demonstrated that the quorum-sensing completed strain restored the gene expression of the defective strain, but the metabolically completed one did not. This evidence supported our hypothesis that the autoinducer-2-mediated, quorum-sensing system, not the AMC, was responsible for luxS mutant regulation.

Abstract: A low-cost intensity-based polymer optical fiber (POF) sensor for fuel level measurements in paramotoring and powered paragliding is presented, exploiting the advantages of the optical fiber sensing technology. Experimental results demonstrate that the best option can be performed by stripping the fiber at the desired discrete points to measure the fuel level as well as with a gauge-shape fiber bending. The prototype has a good linearity, better than 4% full scale (F.S.), and sensitivity around 0.5 V per bend are obtained. Hysteresis due to residual fluid at the sensing points is found to be less than 9% F.S.

Abstract: The influence of anemometer rotor shape parameters, such as the cups’ front area or their center rotation radius on the anemometer’s performance was analyzed. This analysis was based on calibrations performed on two different anemometers (one based on magnet system output signal, and the other one based on an opto-electronic system output signal), tested with 21 different rotors. The results were compared to the ones resulting from classical analytical models. The results clearly showed a linear dependency of both calibration constants, the slope and the offset, on the cups’ center rotation radius, the influence of the front area of the cups also being observed. The analytical model of Kondo et al. was proved to be accurate if it is based on precise data related to the aerodynamic behavior of a rotor’s cup.

Abstract: Geo-collaboration is an emerging research area in computer sciences studying the way spatial, geographically referenced information and communication technologies can support collaborative activities. Scenarios in which information associated to its physical location are of paramount importance are often referred as Situated Knowledge Creation scenarios. To date there are few computer systems supporting knowledge creation that explicitly incorporate physical context as part of the knowledge being managed in mobile face-to-face scenarios. This work presents a collaborative software application supporting visually-geo-referenced knowledge creation in mobile working scenarios while the users are interacting face-to-face. The system allows to manage data information associated to specific physical locations for knowledge creation processes in the field, such as urban planning, identifying specific physical locations, territorial management, etc.; using Tablet-PCs and GPS in order to geo-reference data and information. It presents a model for developing mobile applications supporting situated knowledge creation in the field, introducing the requirements for such an application and the functionalities it should have in order to fulfill them. The paper also presents the results of utility and usability evaluations.

Abstract: This paper presents a novel hardware architecture for principal component analysis. The architecture is based on the Generalized Hebbian Algorithm (GHA) because of its simplicity and effectiveness. The architecture is separated into three portions: the weight vector updating unit, the principal computation unit and the memory unit. In the weight vector updating unit, the computation of different synaptic weight vectors shares the same circuit for reducing the area costs. To show the effectiveness of the circuit, a texture classification system based on the proposed architecture is physically implemented by Field Programmable Gate Array (FPGA). It is embedded in a System-On-Programmable-Chip (SOPC) platform for performance measurement. Experimental results show that the proposed architecture is an efficient design for attaining both high speed performance andlow area costs.

Abstract: We have developed a wireless biosensor system to continuously monitor L-lactic acid concentrations in fish. The blood L-lactic acid level of fish is a barometer of stress. The biosensor comprised Pt-Ir wire (φ0.178 mm) as the working electrode and Ag/AgCl paste as the reference electrode. Lactate oxidase was immobilized on the working electrode using glutaraldehyde. The sensor calibration was linear and good correlated with L-lactic acid levels (R = 0.9959) in the range of 0.04 to 6.0 mg·dL⁻¹. We used the eyeball interstitial sclera fluid (EISF) as the site of sensor implantation. The blood L-lactic acid levels correlated closely with the EISF L-lactic acid levels in the range of 3 to 13 mg·dL⁻¹ (R = 0.8173, n = 26). Wireless monitoring of L-lactic acid was performed using the sensor system in free-swimming fish in an aquarium. The sensor response was stable for over 60 h. Thus, our biosensor provided a rapid and convenient method for real-time monitoring of L-lactic acid levels in fish.

Abstract: The mainstream of research in Ambient Assisted Living (AAL) is devoted to developing intelligent systems for processing the data collected through artificial sensing. Besides, there are other elements that must be considered to foster the adoption of AAL solutions in real environments. In this paper we focus on the problem of designing interfaces among caregivers and AAL systems. We present an alert management tool that supports carers in their task of validating alarms raised by the system. It generates text-based explanations—obtained through an argumentation process—of the causes leading to alarm activation along with graphical sensor information and 3D models, thus offering complementary types of information. Moreover, a guideline to use the tool when validating alerts is also provided. Finally, the functionality of the proposed tool is demonstrated through two real cases of alert.

Abstract: Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively. Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is sound.

Abstract: With the rapid development of modern physics, atomic gyroscopes have been demonstrated in recent years. There are two types of atomic gyroscope. The Atomic Interferometer Gyroscope (AIG), which utilizes the atomic interferometer to sense rotation, is an ultra-high precision gyroscope; and the Atomic Spin Gyroscope (ASG), which utilizes atomic spin to sense rotation, features high precision, compact size and the possibility to make a chip-scale one. Recent developments in the atomic gyroscope field have created new ways to obtain high precision gyroscopes which were previously unavailable with mechanical or optical gyroscopes, but there are still lots of problems that need to be overcome to meet the requirements of inertial navigation systems. This paper reviews the basic principles of AIG and ASG, introduces the recent progress in this area, focusing on discussing their technical difficulties for inertial navigation applications, and suggests methods for developing high performance atomic gyroscopes in the near future.

Abstract: Digital surface models (DSMs) are widely used in forest science to model the forest canopy. Stereo pairs of very high resolution satellite and digital aerial images are relatively new and their absolute accuracy for DSM generation is largely unknown. For an assessment of these input data two DSMs based on a WorldView-2 stereo pair and a ADS80 DSM were generated with photogrammetric instruments. Rational polynomial coefficients (RPCs) are defining the orientation of the WorldView-2 satellite images, which can be enhanced with ground control points (GCPs). Thus two WorldView-2 DSMs were distinguished: a WorldView-2 RPCs-only DSM and a WorldView-2 GCP-enhanced RPCs DSM. The accuracy of the three DSMs was estimated with GPS measurements, manual stereo-measurements, and airborne laser scanning data (ALS). With GCP-enhanced RPCs the WorldView-2 image orientation could be optimised to a root mean square error (RMSE) of 0.56 m in planimetry and 0.32 m in height. This improvement in orientation allowed for a vertical median error of −0.24 m for the WorldView-2 GCP-enhanced RPCs DSM in flat terrain. Overall, the DSM based on ADS80 images showed the highest accuracy of the three models with a median error of 0.08 m over bare ground. As the accuracy of a DSM varies with land cover three classes were distinguished: herb and grass, forests, and artificial areas. The study suggested the ADS80 DSM to best model actual surface height in all three land cover classes, with median errors < 1.1 m. The WorldView-2 GCP-enhanced RPCs model achieved good accuracy, too, with median errors of −0.43 m for the herb and grass vegetation and −0.26 m for artificial areas. Forested areas emerged as the most difficult land cover type for height modelling; still, with median errors of −1.85 m for the WorldView-2 GCP-enhanced RPCs model and −1.12 m for the ADS80 model, the input data sets evaluated here are quite promising for forest canopy modelling.

Abstract: A novel nc-Si/c-Si heterojunction MOSFETs pressure sensor is proposed in this paper, with four p-MOSFETs with nc-Si/c-Si heterojunction as source and drain. The four p-MOSFETs are designed and fabricated on a square silicon membrane by CMOS process and MEMS technology where channel resistances of the four nc-Si/c-Si heterojunction MOSFETs form a Wheatstone bridge. When the additional pressure is P, the nc-Si/c-Si heterojunction MOSFETs pressure sensor can measure this additional pressure P. The experimental results show that when the supply voltage is 3 V, length-width (L:W) ratio is 2:1, and the silicon membrane thickness is 75 μm, the full scale output voltage of the pressure sensor is 15.50 mV at room temperature, and pressure sensitivity is 0.097 mV/kPa. When the supply voltage and L:W ratio are the same as the above, and the silicon membrane thickness is 45 μm, the full scale output voltage is 43.05 mV, and pressure sensitivity is 2.153 mV/kPa. Therefore, the sensor has higher sensitivity and good temperature characteristics compared to the traditional piezoresistive pressure sensor.

Abstract: Effective communication among first responders during response to natural and human-made large-scale catastrophes has increased tremendously during the last decade. However, most efforts to achieve a higher degree of effectiveness in communication lack synergy between the environment and the technology involved to support first responders operations. This article presents a natural and intuitive interface to support Stigmergy; or communication through the environment, based on intuitively marking and retrieving information from the environment with a pointer. A prototype of the system was built and tested in the field, however the pointing activity revealed challenges regarding accuracy due to limitations of the sensors used. The results obtained from these field tests were the basis for this research effort and will have the potential to enable communication through the environment for first responders operating in highly dynamical and inhospitable disaster relief environments.

Abstract: This paper presents recent development on magnetostrictive linear position sensors (MLPS). A new compensation coil structure improves the EMI suppression and accuracy considerably. Furthermore, experimental results indicate that the new structure can improve the accuracy to ±0.13 mm nearly double the ±0.2 mm obtained with traditional structures. As another design continuation after the differential waveguide structure, this new structure is a practical and reliable implementation technique for the commercialization of MLPS.

Abstract: A T-shaped fiber-optic phantom-dosimeter system was developed using square scintillating optical fibers, a lens system, and a CMOS image camera. Images of scintillating light were used to simultaneously measure the transverse and longitudinal distributions of absorbed dose of a 6 MV photon beam with field sizes of 1 × 1 and 3 × 3 cm². Each optical fiber has a very small sensitive volume and the sensitive material is water equivalent. This allows the measurements of cross-beam profile as well as the percentage depth dose of small field sizes. In the case of transverse dose distribution, the measured beam profiles were gradually become uneven and the beam edge had a gentle slope with increasing depth of the PMMA phantom. In addition, the maximum dose values of longitudinal dose distribution for 6 MV photon beam with field sizes of 1 × 1 and 3 × 3 cm² were found to be at a depth of approximately 15 mm and the percentage depth dose of both field sizes were nearly in agreement at the skin dose level. Based on the results of this study, it is anticipated that an all-in-one phantom-dosimeter can be developed to accurately measure beam profiles and dose distribution in a small irradiation fields prior to carrying out stereotactic radiosurgery.

Abstract: A road sign recognition system based on adaptive image pre-processing models using two fuzzy inference schemes has been proposed. The first fuzzy inference scheme is to check the changes of the light illumination and rich red color of a frame image by the checking areas. The other is to check the variance of vehicle’s speed and angle of steering wheel to select an adaptive size and position of the detection area. The Adaboost classifier was employed to detect the road sign candidates from an image and the support vector machine technique was employed to recognize the content of the road sign candidates. The prohibitory and warning road traffic signs are the processing targets in this research. The detection rate in the detection phase is 97.42%. In the recognition phase, the recognition rate is 93.04%. The total accuracy rate of the system is 92.47%. For video sequences, the best accuracy rate is 90.54%, and the average accuracy rate is 80.17%. The average computing time is 51.86 milliseconds per frame. The proposed system can not only overcome low illumination and rich red color around the road sign problems but also offer high detection rates and high computing performance.

Abstract: Temperature changes have a strong effect on Hemispherical Resonator Gyro (HRG) output; therefore, it is of vital importance to observe their influence and then make necessary compensations. In this paper, a temperature compensation model for HRG based on the natural frequency of the resonator is established and then temperature drift compensations are accomplished. To begin with, a math model of the relationship between the temperature and the natural frequency of HRG is set up. Then, the math model is written into a Taylor expansion expression and the expansion coefficients are calibrated through temperature experiments. The experimental results show that the frequency changes correspond to temperature changes and each temperature only corresponds to one natural frequency, so the output of HRG can be compensated through the natural frequency of the resonator instead of the temperature itself. As a result, compensations are made for the output drift of HRG based on natural frequency through a stepwise linear regression method. The compensation results show that temperature-frequency method is valid and suitable for the gyroscope drift compensation, which would ensure HRG’s application in a larger temperature range in the future.

Abstract: The long stator track for high speed maglev trains has a tooth-slot structure. The sensor obtains precise relative position information for the traction system by detecting the long stator tooth-slot structure based on nondestructive detection technology. The magnetic field modeling of the sensor is a typical three-dimensional (3-D) electromagnetic problem with complex boundary conditions, and is studied semi-analytically in this paper. A second-order vector potential (SOVP) is introduced to simplify the vector field problem to a scalar field one, the solution of which can be expressed in terms of series expansions according to Multipole Theory (MT) and the New Equivalent Source (NES) method. The coefficients of the expansions are determined by the least squares method based on the boundary conditions. Then, the solution is compared to the simulation result through Finite Element Analysis (FEA). The comparison results show that the semi-analytical solution agrees approximately with the numerical solution. Finally, based on electromagnetic modeling, a difference coil structure is designed to improve the sensitivity and accuracy of the sensor.

Abstract: The extensions of the environment with the integration of sensing systems in any space, in conjunction with ubiquitous computing are enabling the so-called Smart Space Sensor Networks. This new generation of networks are offering full connectivity with any object, through the Internet of Things (IoT) and/or the Web, i.e., the Web of Things. These connectivity capabilities are making it feasible to sense the behaviours of people at home and act accordingly. These sensing systems must be integrated within typical elements found at home such as furniture. For that reason, this work considers furniture as an interesting element for the transparent location of sensors. Furniture is a ubiquitous object, i.e., it can be found everywhere at home or the office, and it can integrate and hide the sensors of a network. This work addresses the lack of an exhaustive study of the effect of furniture on signal losses. In addition an easy-to-use tool for estimating the robustness of the communication channel among the sensor nodes and gateways is proposed. Specifically, the losses in a sensor network signal due to the materials found within the communication link are evaluated. Then, this work proposes a software tool that gathers the obtained results and is capable of evaluating the impact of a given set of materials on the communications. This tool also provides a mechanism to optimize the sensor network deployments during the definition of smart spaces. Specifically, it provides information such as: maximum distances between sensor nodes, most suitable type of furniture to integrate sensors, or battery life of sensor nodes. This tool has been validated empirically in the lab, and it is currently being used by several enterprise partners of the Technological Centre of Furniture and Wood in the southeast of Spain.

Abstract: Micromechanic resonators provide a small-volume and potentially high-throughput method to determine rheological properties of fluids. Here we explore the accuracy in measuring mass density and viscosity of ethanol-water and glycerol-water model solutions, using a simple and easily implemented model to deduce the hydrodynamic effects on resonating cantilevers of various length-to-width aspect ratios. We next show that these measurements can be extended to determine the alcohol percentage of both model solutions and commercial beverages such as beer, wine and liquor. This demonstrates how micromechanical resonators can be used for quality control of every-day drinks.

Abstract: An infrared hot-electron transistor (IHET) 5 × 8 array with a common base configuration that allows two-terminal readout integration was investigated and fabricated for the first time. The IHET structure provides a maximum factor of six in improvement in the photocurrent to dark current ratio compared to the basic quantum well infrared photodetector (QWIP), and hence it improved the array S/N ratio by the same factor. The study also showed for the first time that there is no electrical cross-talk among individual detectors, even though they share the same emitter and base contacts. Thus, the IHET structure is compatible with existing electronic readout circuits for photoconductors in producing sensitive focal plane arrays.

Abstract: We report on the electrochemical detection of anti-cancer drugs in human serum with sensitivity values in the range of 8–925 nA/µM. Multi-walled carbon nanotubes were functionalized with three different cytochrome P450 isoforms (CYP1A2, CYP2B6, and CYP3A4). A model used to effectively describe the cytochrome P450 deposition onto carbon nanotubes was confirmed by Monte Carlo simulations. Voltammetric measurements were performed in phosphate buffer saline (PBS) as well as in human serum, giving well-defined current responses upon addition of increasing concentrations of anti-cancer drugs. The results assert the capability to measure concentration of drugs in the pharmacological ranges in human serum. Another important result is the possibility to detect pairs of drugs present in the same sample, which is highly required in case of therapies with high side-effects risk and in anti-cancer pharmacological treatments based on mixtures of different drugs. Our technology holds potentials for inexpensive multi-panel drug-monitoring in personalized therapy.

Abstract: Technological advances for improving supply chain efficiency present three key challenges for managing goods: tracking, tracing and monitoring (TTM), in order to satisfy the requirements for products such as perishable goods where the European Legislations requires them to ship within a prescribed temperature range to ensure freshness and suitability for consumption. The proposed system integrates RFID for tracking and tracing through a distributed architecture developed for heavy goods vehicles, and the sensors embedded in the SunSPOT platform for monitoring the goods transported based on the concept of the Internet of Things. This paper presents how the Internet of Things is integrated for improving terrestrial logistics offering a comprehensive and flexible architecture, with high scalability, according to the specific needs for reaching an item-level continuous monitoring solution. The major contribution from this work is the optimization of the Embedded Web Services based on RESTful (Web of Things) for the access to TTM services at any time during the transportation of goods. Specifically, it has been extended the monitoring patterns such as observe and blockwise transfer for the requirements from the continuous conditional monitoring, and for the transfer of full inventories and partial ones based on conditional queries. In definitive, this work presents an evolution of the previous TTM solutions, which were limited to trailer identification and environment monitoring, to a solution which is able to provide an exhaustive item-level monitoring, required for several use cases. This exhaustive monitoring has required new communication capabilities through the Web of Things, which has been optimized with the use and improvement of a set of communications patterns.

Abstract: Electrolyte Cathode Discharge (ELCAD) spectrometry, a novel sensitive multielement direct analytical method for metal traces in aqueous solutions, was introduced in 1993 as a new sensing principle. Since then several works have tried to develop an operational mechanism for this exotic atmospheric glow plasma technique, however these attempts cannot be combined into a valid model description. In this review we summarize the conceptual and technical problems we found in this upcoming research field of direct sensors. The T_G gas temperature and the n_e electron density values published up to now for ELCAD are very confusing. These data were evaluated by three conditions. The first is the gas composition of the ELCAD plasma, since T_G was determined from the emitted intensity of the N₂ and OH bands. Secondly, since the ELCAD is an atmospheric glow discharge, thus, the obtained T_G has to be close to the T_e electron temperature. This can be used for the mutual validation of the received temperature data. Thirdly, as a consequence of the second condition, the values of T_G and n_e have to agree with the Engel-Brown approximation of the Saha-equation related to weakly ionized glow discharge plasmas. Application of non-adequate experimental methods and theoretical treatment leads to unreliable descriptions which cannot be used to optimize the detector performance.

Abstract: This paper describes a telematic system based on an intelligent van which is capable of tracing pharmaceutical drugs over delivery routes from a warehouse to pharmacies, without altering carriers’ daily conventional tasks. The intelligent van understands its environment, taking into account its location, the assets and the predefined delivery route; with the capability of reporting incidences to carriers in case of failure according to the established distribution plan. It is a non-intrusive solution which represents a successful experience of using smart environments and an optimized Radio Frequency Identification (RFID) embedded system in a viable way to resolve a real industrial need in the pharmaceutical industry. The combination of deterministic modeling of the indoor vehicle, the implementation of an ad-hoc radiating element and an agile software platform within an overall system architecture leads to a competitive, flexible and scalable solution.

Abstract: The increasing trends of electrical consumption within data centres are a growing concern for business owners as they are quickly becoming a large fraction of the total cost of ownership. Ultra small sensors could be deployed within a data centre to monitor environmental factors to lower the electrical costs and improve the energy efficiency. Since servers and air conditioners represent the top users of electrical power in the data centre, this research sets out to explore methods from each subsystem of the data centre as part of an overall energy efficient solution. In this paper, we investigate the current trends of Green IT awareness and how the deployment of small environmental sensors and Site Infrastructure equipment optimization techniques which can offer a solution to a global issue by reducing carbon emissions.

Abstract: In this paper we summarize the research activities at the Instituto de Telecomunicações—Pólo de Aveiro and University of Aveiro, in the field of fiber Bragg grating based sensors and their applications in dynamic measurements for Structural Health Monitoring of slender structures such as towers. In this work we describe the implementation of an optical biaxial accelerometer based on fiber Bragg gratings inscribed on optical fibers. The proof-of-concept was done with the dynamic monitoring of a reinforced concrete structure and a slender metallic telecommunication tower. Those structures were found to be suitable to demonstrate the feasibility of FBG accelerometers to obtain the structures’ natural frequencies, which are the key parameters in Structural Health Monitoring and in the calibration of numerical models used to simulate the structure behavior.

Abstract: The LuxS enzyme, an S-ribosyl-homocysteine lyase, catalyzes the production of the signal precursor for autoinducer-2 mediated quorum sensing (QS-2) in Vibrio. Its widespread occurrence among bacteria is often considered the evidence for a universal language for interspecies communication. Presence of the luxS gene and production of the autoinducer-2 (AI-2) signal have repeatedly been the only evidences presented to assign a functional QS-2 to the most diverse species. In fact, LuxS has a primary metabolic role as part of the activated methyl cycle. In this review we have analyzed the distribution of QS-2 related genes in Enterobacteriaceae by moving the focus of the investigation from AI-2 production to the detection of potential AI-2 receptors. The latter are common in pathogens or endosymbionts of animals, but were also found in a limited number of Enterobacteriaceae of the genera Enterobacter, Klebsiella, and Pantoea that live in close association with plants or fungi. Although a precise function of QS-2 in these species has not been identified, they all show an endophytic or endosymbiontic lifestyle that suggests a role of type-2 quorum sensing in the adaptation to closed ecosystems.

Abstract: The dynamic behaviors of an Atomic Force Microscope are of interest, and variously unpredictable phenomena are experimentally measured. In practical measurements, researchers have proposed many methods for avoiding these uncertainties. However, causes of these phenomena are still hard to demonstrate in simulation. To demonstrate these phenomena, this paper claims the tip-jump motion is a predictable process, and the jumping kinetic energy results in different nonlinear phenomena. It emphasizes the variation in the eigenvalues of an AFM with tip-sample distance. This requirement ensures the phase transformations from one associated with the oscillation mode to one associated with the tip-jump/sample-contact mode. Also, multi-modal analysis was utilized to ensure the modal transformation in varying tip-sample distances. In the presented model, oscillations with various tip-sample distances and with various excitation frequencies and amplitudes were compared. The results reveal that the tip-jump motion separates the oscillation orbit into two regions, and the jumping kinetic energy, comparing with the superficial potential energy, leads the oscillation to be bistable or intermittent. The sample-contact condition associates to bifurcation and chaos. Additionally, the jumping is a strong motion that occurrs before the tip-sample contacts, and this motion signal can replace the sample-contact-signal to avoid destroying the sample.

Abstract: We demonstrate novel graphite-on-paper piezoresistive devices. The graphite was used as sensing component. The fabrication process can be finished in a short time with simple tools (e.g., a scissor and a pencil). A small array of six paper-based piezoresistive devices is made. The whole device is flexible. The test results showed that the change of resistance was proportional to the applied force. A paper-based weighing balance was also made as an example of applications. This novel array of paper-based piezoresistive devices will open wide applications in force and acceleration sensing areas.

Abstract: The categorization of places in indoor environments is an important capability for service robots working and interacting with humans. In this paper we present a method to categorize different areas in indoor environments using a mobile robot equipped with a Kinect camera. Our approach transforms depth and grey scale images taken at each place into histograms of local binary patterns (LBPs) whose dimensionality is further reduced following a uniform criterion. The histograms are then combined into a single feature vector which is categorized using a supervised method. In this work we compare the performance of support vector machines and random forests as supervised classifiers. Finally, we apply our technique to distinguish five different place categories: corridors, laboratories, offices, kitchens, and study rooms. Experimental results show that we can categorize these places with high accuracy using our approach.

Abstract: The precision of star point location is significant to identify the star map and to acquire the aircraft attitude for star sensors. Under dynamic conditions, star images are not only corrupted by various noises, but also blurred due to the angular rate of the star sensor. According to different angular rates under dynamic conditions, a novel method is proposed in this article, which includes a denoising method based on adaptive wavelet threshold and a restoration method based on the large angular rate. The adaptive threshold is adopted for denoising the star image when the angular rate is in the dynamic range. Then, the mathematical model of motion blur is deduced so as to restore the blurred star map due to large angular rate. Simulation results validate the effectiveness of the proposed method, which is suitable for blurred star image processing and practical for attitude determination of satellites under dynamic conditions.

Abstract: In this paper, a variable threshold voice activity detector (VAD) is developed to control the operation of a two-sensor adaptive noise canceller (ANC). The VAD prohibits the reference input of the ANC from containing some strength of actual speech signal during adaptation periods. The novelty of this approach resides in using the residual output from the noise canceller to control the decisions made by the VAD. Thresholds of full-band energy and zero-crossing features are adjusted according to the residual output of the adaptive filter. Performance evaluation of the proposed approach is quoted in terms of signal to noise ratio improvements as well mean square error (MSE) convergence of the ANC. The new approach showed an improved noise cancellation performance when tested under several types of environmental noise. Furthermore, the computational power of the adaptive process is reduced since the output of the adaptive filter is efficiently calculated only during non-speech periods.

Abstract: The aim of this work was the determination of pH with a sensor array-based optical portable instrument. This sensor array consists of eleven membranes with selective colour changes at different pH intervals. The method for the pH calculation is based on the implementation of artificial neural networks that use the responses of the membranes to generate a final pH value. A multi-objective algorithm was used to select the minimum number of sensing elements required to achieve an accurate pH determination from the neural network, and also to minimise the network size. This helps to minimise instrument and array development costs and save on microprocessor energy consumption. A set of artificial neural networks that fulfils these requirements is proposed using different combinations of the membranes in the sensor array, and is evaluated in terms of accuracy and reliability. In the end, the network including the response of the eleven membranes in the sensor was selected for validation in the instrument prototype because of its high accuracy. The performance of the instrument was evaluated by measuring the pH of a large set of real samples, showing that high precision can be obtained in the full range.