Table of Contents

Abstract: This paper focuses on developing a novel technique based on machine vision for detection of foreign substances in injections. Mechanical control yields spin/stop movement of injections which helps to cause relative movement between foreign substances in liquid and an ampoule bottle. Foreign substances are classified into two categories: subsiding-slowly object and subsiding-fast object. A sequence of frames are captured by a camera and used to recognize foreign substances. After image preprocessing like noise reduction and motion detection, two different methods, Moving-object Clustering (MC) and Frame Difference, are proposed to detect the two categories respectively. MC is operated to cluster subsiding-slowly foreign substances, based on the invariant features of those objects. Frame Difference is defined to calculate the difference between two frames due to the change of subsiding-fast objects. 200 ampoule samples filled with injection are tested and the experimental result indicates that the approach can detect the visible foreign substances effectively.

Abstract: Over the past few years, Intelligent Spaces (ISs) have received the attention of many Wireless Sensor Network researchers. Recently, several studies have been devoted to identify their common capacities and to set up ISs over these networks. However, little attention has been paid to integrating Fuzzy Rule-Based Systems into collaborative Wireless Sensor Networks for the purpose of implementing ISs. This work presents a distributed architecture proposal for collaborative Fuzzy Rule-Based Systems embedded in Wireless Sensor Networks, which has been designed to optimize the implementation of ISs. This architecture includes the following: (a) an optimized design for the inference engine; (b) a visual interface; (c) a module to reduce the redundancy and complexity of the knowledge bases; (d) a module to evaluate the accuracy of the new knowledge base; (e) a module to adapt the format of the rules to the structure used by the inference engine; and (f) a communications protocol. As a real-world application of this architecture and the proposed methodologies, we show an application to the problem of modeling two plagues of the olive tree: prays (olive moth, Prays oleae Bern.) and repilo (caused by the fungus Spilocaea oleagina). The results show that the architecture presented in this paper significantly decreases the consumption of resources (memory, CPU and battery) without a substantial decrease in the accuracy of the inferred values.

Abstract: This paper presents a novel phase unwrapping architecture for accelerating the computational speed of digital holographic microscopy (DHM). A fast Fourier transform (FFT) based phase unwrapping algorithm providing a minimum squared error solution is adopted for hardware implementation because of its simplicity and robustness to noise. The proposed architecture is realized in a pipeline fashion to maximize through put of thecomputation. Moreover, the number of hardware multipliers and dividers are minimized to reduce the hardware costs. The proposed architecture is used as a custom user logic in a system on programmable chip (SOPC) for physical performance measurement. Experimental results reveal that the proposed architecture is effective for expediting the computational speed while consuming low hardware resources for designing an embedded DHM system.

Abstract: In this paper we present a quaternion-based Extended Kalman Filter (EKF) for estimating the three-dimensional orientation of a rigid body. The EKF exploits the measurements from an Inertial Measurement Unit (IMU) that is integrated with a tri-axial magnetic sensor. Magnetic disturbances and gyro bias errors are modeled and compensated by including them in the filter state vector. We employ the observability rank criterion based on Lie derivatives to verify the conditions under which the nonlinear system that describes the process of motion tracking by the IMU is observable, namely it may provide sufficient information for performing the estimation task with bounded estimation errors. The observability conditions are that the magnetic field, perturbed by first-order Gauss-Markov magnetic variations, and the gravity vector are not collinear and that the IMU is subject to some angular motions. Computer simulations and experimental testing are presented to evaluate the algorithm performance, including when the observability conditions are critical.

Abstract: Nanocrystalline SnO_x (x = 1–2) thin films were prepared on glass substrates by a simple chemical bath deposition method. Triethanolamine was used as complexing agent to decrease time and temperature of deposition and shift the pH of the solution to the noncorrosive region. The films were characterized for composition, surface morphology, structure and optical properties. X-ray diffraction analysis confirms that SnO_x thin films consist of a polycrystalline structure with an average grain size of 36 nm. Atomic force microscopy studies show a uniform grain distribution without pinholes. The elemental composition was evaluated by energy dispersive X-ray spectroscopy. The average O/Sn atomic percentage ratio is 1.72. Band gap energy and optical transition were determined from optical absorbance data. The film was found to exhibit direct and indirect transitions in the visible spectrum with band gap values of about 3.9 and 3.7 eV, respectively. The optical transmittance in the visible region is 82%. The SnO_x nanocrystals exhibit an ultraviolet emission band centered at 392 nm in the vicinity of the band edge, which is attributed to the well-known exciton transition in SnO_x. Photosensitivity was detected in the positive region under illumination with white light.

Abstract: This paper describes a novel design methodology using non-linear models for complex closed loop electro-mechanical sigma-delta modulators (EMΣΔM) that is based on genetic algorithms and statistical variation analysis. The proposed methodology is capable of quickly and efficiently designing high performance, high order, closed loop, near-optimal systems that are robust to sensor fabrication tolerances and electronic component variation. The use of full non-linear system models allows significant higher order non-ideal effects to be taken into account, improving accuracy and confidence in the results. To demonstrate the effectiveness of the approach, two design examples are presented including a 5th order low-pass EMΣΔM for a MEMS accelerometer, and a 6th order band-pass EMΣΔM for the sense mode of a MEMS gyroscope. Each example was designed using the system in less than one day, with very little manual intervention. The strength of the approach is verified by SNR performances of 109.2 dB and 92.4 dB for the low-pass and band-pass system respectively, coupled with excellent immunities to fabrication tolerances and parameter mismatch.

Abstract: Linewidth measurements of a distributed feedback (DFB) fibre laser are made using delayed self heterodyne interferometry (DHSI) with both Mach-Zehnder and Michelson interferometer configurations. Voigt fitting is used to extract and compare the Lorentzian and Gaussian linewidths and associated sources of noise. The respective measurements are w_L (MZI) = (1.6 ± 0.2) kHz and w_L (MI) = (1.4 ± 0.1) kHz. The Michelson with Faraday rotator mirrors gives a slightly narrower linewidth with significantly reduced error. This is explained by the unscrambling of polarisation drift using the Faraday rotator mirrors, confirmed by comparing with non-rotating standard gold coated fibre end mirrors.

Abstract: Radio frequency identification (RFID) tags are small electronic devices working in the radio frequency range. They use wireless radio communications to automatically identify objects or people without the need for line-of-sight or contact, and are widely used in inventory tracking, object location, environmental monitoring. This paper presents a design of a covert RFID tag network for target discovery and target information routing. In the design, a static or very slowly moving target in the field of RFID tags transmits a distinct pseudo-noise signal, and the RFID tags in the network collect the target information and route it to the command center. A map of each RFID tag’s location is saved at command center, which can determine where a RFID tag is located based on each RFID tag’s ID. We propose the target information collection method with target association and clustering, and we also propose the information routing algorithm within the RFID tag network. The design and operation of the proposed algorithms are illustrated through examples. Simulation results demonstrate the effectiveness of the design.

Abstract: The present work analyzes theoretically and verifies the advantage of utilizing ε-microcantilever assemblies in microsensing applications. The deflection profile of these innovative ε-assembly microcantilevers is compared with that of the rectangular microcantilever and modified triangular microcantlever. Various force-loading conditions are considered. The theorem of linear elasticity for thin beams is used to obtain the deflections. The obtained defections are validated against an accurate numerical solution utilizing finite element method with maximum deviation less than 10 percent. It is found that the ε-assembly produces larger deflections than the rectangular microcantilever under the same base surface stress and same extension length. In addition, the ε-microcantilever assembly is found to produce larger deflection than the modified triangular microcantilever. This deflection enhancement is found to increase as the ε-assembly’s free length decreases for various types of force loading conditions. Consequently, the ε-microcantilever is shown to be superior in microsensing applications as it provides favorable high detection capability with a reduced susceptibility to external noises. Finally, this work paves a way for experimentally testing the ε-assembly to show whether detective potential of microsensors can be increased.

Abstract: Over the last decade, wireless devices have decreased in size and power requirements. These devices generally use batteries as a power source but can employ additional means of power, such as solar, thermal or wind energy. However, sensor networks are often deployed in conditions of minimal lighting and thermal gradient such as densely wooded environments, where even normal wind energy harvesting is limited. In these cases a possible source of energy is from the motion of the trees themselves. We investigated the amount of energy and power available from the motion of a tree in a sheltered position, during Beaufort 4 winds. We measured the work performed by the tree to lift a mass, we measured horizontal acceleration of free movement, and we determined the angular deflection of the movement of the tree trunk, to determine the energy and power available to various types of harvesting devices. We found that the amount of power available from the tree, as demonstrated by lifting a mass, compares favourably with the power required to run a wireless sensor node.

Abstract: We report a conductometric nanoparticle biosensor array to address the significant variation of electrical property in nanomaterial biosensors due to the random network nature of nanoparticle thin-film. Indium oxide and silica nanoparticles (SNP) are assembled selectively on the multi-site channel area of the resistors using layer-by-layer self-assembly. To demonstrate enzymatic biosensing capability, glucose oxidase is immobilized on the SNP layer for glucose detection. The packaged sensor chip onto a ceramic pin grid array is tested using syringe pump driven feed and multi-channel I–V measurement system. It is successfully demonstrated that glucose is detected in many different sensing sites within a chip, leading to concentration dependent currents. The sensitivity has been found to be dependent on the channel length of the resistor, 4–12 nA/mM for channel lengths of 5–20 µm, while the apparent Michaelis-Menten constant is 20 mM. By using sensor array, analytical data could be obtained with a single step of sample solution feeding. This work sheds light on the applicability of the developed nanoparticle microsensor array to multi-analyte sensors, novel bioassay platforms, and sensing components in a lab-on-a-chip.

Abstract: The expected increase in the penetration of electric vehicles (EV) and plug-in hybrid electric vehicles (PHEV) will produce unbalanced conditions, reactive power consumption and current harmonics drawn by the battery charging equipment, causing a great impact on the power quality of the future smart grid. A single-phase semi-fast electric vehicle battery charger is proposed in this paper. This ac on-board charging equipment can operate in grid-to-vehicle (G2V) mode, and also in vehicle-to-grid (V2G) mode, transferring the battery energy to the grid when the vehicle is parked. The charger is controlled with a Perfect Harmonic Cancellation (PHC) strategy, contributing to improve the grid power quality, since the current demanded or injected has no harmonic content and a high power factor. Hall-effect current and voltage transducers have been used in the sensor stage to carry out this control strategy. Experimental results with a laboratory prototype are presented.

Abstract: The obstacle avoidance problem in geographic forwarding is an important issue for location-based routing in wireless sensor networks. The presence of an obstacle leads to several geographic routing problems such as excessive energy consumption and data congestion. Obstacles are hard to avoid in realistic environments. To bypass obstacles, most routing protocols tend to forward packets along the obstacle boundaries. This leads to a situation where the nodes at the boundaries exhaust their energy rapidly and the obstacle area is diffused. In this paper, we introduce a novel routing algorithm to solve the obstacle problem in wireless sensor networks based on a game-theory model. Our algorithm forms a concave region that cannot forward packets to achieve the aim of improving the transmission success rate and decreasing packet transmission delays. We consider the residual energy, out-degree and forwarding angle to determine the forwarding probability and payoff function of forwarding candidates. This achieves the aim of load balance and reduces network energy consumption. Simulation results show that based on the average delivery delay, energy consumption and packet delivery ratio performances our protocol is superior to other traditional schemes.

Abstract: The use of the enzyme alanine dehydrogenase (AlaDH) for the determination of ammonium ion (NH₄⁺) usually requires the addition of pyruvate substrate and reduced nicotinamide adenine dinucleotide (NADH) simultaneously to effect the reaction. This addition of reagents is inconvenient when an enzyme biosensor based on AlaDH is used. To resolve the problem, a novel reagentless amperometric biosensor using a stacked methacrylic membrane system coated onto a screen-printed carbon paste electrode (SPE) for NH₄⁺ ion determination is described. A mixture of pyruvate and NADH was immobilized in low molecular weight poly(2-hydroxyethyl methacrylate) (pHEMA) membrane, which was then deposited over a photocured pHEMA membrane (photoHEMA) containing alanine dehydrogenase (AlaDH) enzyme. Due to the enzymatic reaction of AlaDH and the pyruvate substrate, NH₄⁺ was consumed in the process and thus the signal from the electrocatalytic oxidation of NADH at an applied potential of +0.55 V was proportional to the NH₄⁺ ion concentration under optimal conditions. The stacked methacrylate membranes responded rapidly and linearly to changes in NH₄⁺ ion concentrations between 10–100 mM, with a detection limit of 0.18 mM NH₄⁺ ion. The reproducibility of the amperometrical NH₄⁺ biosensor yielded low relative standard deviations between 1.4–4.9%. The stacked membrane biosensor has been successfully applied to the determination of NH₄⁺ ion in spiked river water samples without pretreatment. A good correlation was found between the analytical results for NH₄⁺ obtained from the biosensor and the Nessler spectrophotometric method.

Abstract: Human interaction environments (HIE) must be understood as any place where people carry out their daily life, including their work, family life, leisure and social life, interacting with technology to enhance or facilitate the experience. The integration of technology in these environments has been achieved in a disorderly and incompatible way, with devices operating in isolated islands with artificial edges delimited by the manufacturers. In this paper we are presenting the UniDA framework, an integral solution for the development of systems that require the integration and interoperation of devices and technologies in HIEs. It provides developers and installers with a uniform conceptual framework capable of modelling an HIE, together with a set of libraries, tools and devices to build distributed instrumentation networks with support for transparent integration of other technologies. A series of use case examples and a comparison to many of the existing technologies in the field has been included in order to show the benefits of using UniDA.

Abstract: The localization of persons in indoor environments is nowadays an open problem. There are partial solutions based on the deployment of a network of sensors (Local Positioning Systems or LPS). Other solutions only require the installation of an inertial sensor on the person’s body (Pedestrian Dead-Reckoning or PDR). PDR solutions integrate the signals coming from an Inertial Measurement Unit (IMU), which usually contains 3 accelerometers and 3 gyroscopes. The main problem of PDR is the accumulation of positioning errors due to the drift caused by the noise in the sensors. This paper presents a PDR solution that incorporates a drift correction method based on detecting the access ramps usually found in buildings. The ramp correction method is implemented over a PDR framework that uses an Inertial Navigation algorithm (INS) and an IMU attached to the person’s foot. Unlike other approaches that use external sensors to correct the drift error, we only use one IMU on the foot. To detect a ramp, the slope of the terrain on which the user is walking, and the change in height sensed when moving forward, are estimated from the IMU. After detection, the ramp is checked for association with one of the existing in a database. For each associated ramp, a position correction is fed into the Kalman Filter in order to refine the INS-PDR solution. Drift-free localization is achieved with positioning errors below 2 meters for 1,000-meter-long routes in a building with a few ramps.

Abstract: This paper presents a new muscle contraction (MC) sensor. This MC sensor is based on a novel principle whereby muscle tension is measured during muscle contractions. During the measurement, the sensor is fixed on the skin surface above the muscle, while the sensor tip applies pressure and causes an indentation of the skin and intermediate layer directly above the muscle and muscle itself. The force on the sensor tip is then measured. This force is roughly proportional to the tension of the muscle. The measurement is non-invasive and selective. Selectivity of MC measurement refers to the specific muscle or part of the muscle that is being measured and is limited by the size of the sensor tip. The sensor is relatively small and light so that the measurements can be performed while the measured subject performs different activities. Test measurements with this MC sensor on the biceps brachii muscle under isometric conditions (elbow angle 90°) showed a high individual linear correlation between the isometric force and MC signal amplitudes (0.97 ≤ r ≤ 1). The measurements also revealed a strong correlation between the MC and electromyogram (EMG) signals as well as good dynamic behaviour by the MC sensor. We believe that this MC sensor, when fully tested, will be a useful device for muscle mechanic diagnostics and that it will be complementary to existing methods.

Abstract: We have developed an aptamer-based microarray for human thrombin detection exploiting two non-overlapping DNA thrombin aptamers recognizing different exosites of the target protein. The 15-mer aptamer (TBA1) binds the fibrinogen-binding site, whereas the 29-mer aptamer (TBA2) binds the heparin binding domain. Extensive analysis on the complex formation between human thrombin and modified aptamers was performed by Electrophoresis Mobility Shift Assay (EMSA), in order to verify in solution whether the chemical modifications introduced would affect aptamers/protein recognition. The validated system was then applied to the aptamer microarray, using the solid phase system devised by the solution studies. Finally, the best procedure for Sandwich Aptamer Microarray (SAM) and the specificity of the sandwich formation for the developed aptasensor for human thrombin were optimized.

Abstract: Separative extended gate field effect transistor (SEGFET) type devices have been used as an ion sensor or biosensor as an alternative to traditional ion sensitive field effect transistors (ISFETs) due to their robustness, ease of fabrication, low cost and possibility of FET isolation from the chemical environment. The layer-by-layer technique allows the combination of different materials with suitable properties for enzyme immobilization on simple platforms such as the extended gate of SEGFET devices enabling the fabrication of biosensors. Here, glucose biosensors based on dendrimers and metallophthalocyanines (MPcs) in the form of layer-by-layer (LbL) films, assembled on indium tin oxide (ITO) as separative extended gate material, has been produced. NH₃⁺ groups in the dendrimer allow electrostatic interactions or covalent bonds with the enzyme (glucose oxidase). Relevant parameters such as optimum pH, buffer concentration and presence of serum bovine albumin (BSA) in the immobilization process were analyzed. The relationship between the output voltage and glucose concentration shows that upon detection of a specific analyte, the sub-products of the enzymatic reaction change the pH locally, affecting the output signal of the FET transducer. In addition, dendritic layers offer a nanoporous environment, which may be permeable to H⁺ ions, improving the sensibility as modified electrodes for glucose biosensing.

Abstract: Antibacterials are among of the most important medications used in health care. However, their efficacy is increasingly impeded by a tremendous and globally spread bacterial resistance phenomenon. This bacterial resistance is accelerated by inadequate application of antibacterial drugs in humans, the widespread veterinary use of antibacterials, and antibacterial occurrence in the environment and food. Further, there is a lack of development of innovative novel drugs. Therefore, the search for novel antibacterials has to be intensified and the spread of antibacterials in the environment has to be restricted. Due to the fundamental progress in biosensor development and promising applications in the antibiotic field, this review gives for the first time an overview on the use and prospects of biosensor applications in that area. A number of reports have applied biosensors of different design and techniques to search for antibacterials in environmental and foodstuff matrices. These studies are discussed with respect to the analytical values and compared to conventional techniques. Furthermore, biosensor applications to elucidate the mode of action of antimicrobial drugs in vitro have been described. These studies were critically introduced referring to the informational value of those simulations. In summary, biosensors will be illustrated as an innovative and promising, although not yet comprehensively applied, technique in the antibacterial field.

Abstract: We report a noble optical sensing method to diagnose seed abnormalities using optical coherence tomography (OCT). Melon seeds infected with Cucumber green mottle mosaic virus (CGMMV) were scanned by OCT. The cross-sectional sensed area of the abnormal seeds showed an additional subsurface layer under the surface which is not found in normal seeds. The presence of CGMMV in the sample was examined by a blind test (n = 140) and compared by the reverse transcription-polymerase chain reaction. The abnormal layers (n = 40) were quantitatively investigated using A-scan sensing analysis and statistical method. By utilizing 3D OCT image reconstruction, we confirmed the distinctive layers on the whole seeds. These results show that OCT with the proposed data processing method can systemically pick up morphological modification induced by viral infection in seeds, and, furthermore, OCT can play an important role in automatic screening of viral infections in seeds.

Abstract: This article describes further development of a novel Non Destructive Evaluation (NDE) approach described in one of our previous papers. Here these sensors have been used for the first time as a Piecewise Continuous System (PCS), which means that they are not only capable of following the deformation pattern but can also detect distinctive fracture events. In order to characterize the simultaneous compression and traction response of these sensors, multilayer glass laminate composite samples were prepared for 3-point bending tests. The laminate sample consisted of five layers of plain woven glass fabrics placed one over another. The sensors were placed at two strategic locations during the lay-up process so as to follow traction and compression separately. The reinforcements were then impregnated in epoxy resin and later subjected to 3-point bending tests. An appropriate data treatment and recording device has also been developed and used for simultaneous data acquisition from the two sensors. The results obtained, under standard testing conditions have shown that our textile fibrous sensors can not only be used for simultaneous detection of compression and traction in composite parts for on-line structural health monitoring but their sensitivity and carefully chosen location inside the composite ensures that each fracture event is indicated in real time by the output signal of the sensor.

Abstract: An acoustic electronic scanning array for acquiring images from a person using a biometric application is developed. Based on pulse-echo techniques, multifrequency acoustic images are obtained for a set of positions of a person (front, front with arms outstretched, back and side). Two Uniform Linear Arrays (ULA) with 15 l/2-equispaced sensors have been employed, using different spatial apertures in order to reduce sidelobe levels. Working frequencies have been designed on the basis of the main lobe width, the grating lobe levels and the frequency responses of people and sensors. For a case-study with 10 people, the acoustic profiles, formed by all images acquired, are evaluated and compared in a mean square error sense. Finally, system performance, using False Match Rate (FMR)/False Non-Match Rate (FNMR) parameters and the Receiver Operating Characteristic (ROC) curve, is evaluated. On the basis of the obtained results, this system could be used for biometric applications.

Abstract: In this study, an anti-carbofuran monoclonal antibody (Ab) was immobilized on the surface of a glassy carbon electrode (GCE) using silica sol-gel (SiSG) technology. Thus, a sensitive, label-free electrochemical immunosensor for the direct determination of carbofuran was developed. The electrochemical performance of immunoreaction of antigen with the anti-carbofuran monoclonal antibody was investigated by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), in which phosphate buffer solution containing [Fe(CN)₆]^3−/4− was used as the base solution for test. Because the complex formed by the immunoreaction hindered the diffusion of [Fe(CN)₆]^3−/4− on the electrode surface, the redox peak current of the immunosensor in the CV obviously decreased with the increase of the carbofuran concentration. The pH of working solution, the concentration of Ab and the incubation time of carbofuran were studied to ensure the sensitivity and conductivity of the immunosensor. Under the optimal conditions, the linear range of the proposed immunosensor for the determination of carbofuran was from 1 ng/mL to 100 μg/mL and from 50 μg/mL to 200 μg/mL with a detection limit of 0.33 ng/mL (S/N = 3). The proposed immunosensor exhibited good high sensitivity and stability, and it was thus suitable for trace detection of carbofuran pesticide residues.

Abstract: Radio frequency identification (RFID) devices are currently used to quantify several traits of animal behaviour with potential applications for the study of marine organisms. To date, behavioural studies with marine organisms are rare because of the technical difficulty of propagating radio waves within the saltwater medium. We present a novel RFID tracking system to study the burrowing behaviour of a valuable fishery resource, the Norway lobster (Nephrops norvegicus L.). The system consists of a network of six controllers, each handling a group of seven antennas. That network was placed below a microcosm tank that recreated important features typical of Nephrops’ grounds, such as the presence of multiple burrows. The animals carried a passive transponder attached to their telson, operating at 13.56 MHz. The tracking system was implemented to concurrently report the behaviour of up to three individuals, in terms of their travelled distances in a specified unit of time and their preferential positioning within the antenna network. To do so, the controllers worked in parallel to send the antenna data to a computer via a USB connection. The tracking accuracy of the system was evaluated by concurrently recording the animals’ behaviour with automated video imaging. During the two experiments, each lasting approximately one week, two different groups of three animals each showed a variable burrow occupancy and a nocturnal displacement under a standard photoperiod regime (12 h light:12 h dark), measured using the RFID method. Similar results were obtained with the video imaging. Our implemented RFID system was therefore capable of efficiently tracking the tested organisms and has a good potential for use on a wide variety of other marine organisms of commercial, aquaculture, and ecological interest.

Abstract: A 2-channel embedded infrared fiber-optic temperature sensor was fabricated using two identical silver halide optical fibers for accurate thermometry without complicated calibration processes. In this study, we measured the output voltages of signal and reference probes according to temperature variation over a temperature range from 25 to 225 °C. To decide the temperature of the water, the difference between the amounts of infrared radiation emitted from the two temperature sensing probes was measured. The response time and the reproducibility of the fiber-optic temperature sensor were also obtained. Thermometry with the proposed sensor is immune to changes if parameters such as offset voltage, ambient temperature, and emissivity of any warm object. In particular, the temperature sensing probe with silver halide optical fibers can withstand a high temperature/pressure and water-chemistry environment. It is expected that the proposed sensor can be further developed to accurately monitor temperature in harsh environments.

Abstract: We combine suspended-core microstructured optical fibers with the photoinduced electron transfer (PET) effect to demonstrate a new type of fluorescent optical fiber-dip sensing platform for small volume ion detection. A sensor design based on a simple model PET-fluoroionophore system and small core microstructured optical fiber capable of detecting sodium ions is demonstrated. The performance of the dip sensor operating in a high sodium concentration regime (925 ppm Na⁺) and for lower sodium concentration environments (18.4 ppm Na⁺) is explored and future approaches to improving the sensor’s signal stability, sensitivity and selectivity are discussed.

Abstract: Facial expression recognition is an interesting and challenging subject. Considering the nonlinear manifold structure of facial images, a new kernel-based manifold learning method, called kernel discriminant isometric mapping (KDIsomap), is proposed. KDIsomap aims to nonlinearly extract the discriminant information by maximizing the interclass scatter while minimizing the intraclass scatter in a reproducing kernel Hilbert space. KDIsomap is used to perform nonlinear dimensionality reduction on the extracted local binary patterns (LBP) facial features, and produce low-dimensional discrimimant embedded data representations with striking performance improvement on facial expression recognition tasks. The nearest neighbor classifier with the Euclidean metric is used for facial expression classification. Facial expression recognition experiments are performed on two popular facial expression databases, i.e., the JAFFE database and the Cohn-Kanade database. Experimental results indicate that KDIsomap obtains the best accuracy of 81.59% on the JAFFE database, and 94.88% on the Cohn-Kanade database. KDIsomap outperforms the other used methods such as principal component analysis (PCA), linear discriminant analysis (LDA), kernel principal component analysis (KPCA), kernel linear discriminant analysis (KLDA) as well as kernel isometric mapping (KIsomap).

Abstract: The automated collection of data (e.g., through sensor networks) has led to a massive increase in the quantity of environmental and other data available. The sheer quantity of data and growing need for real-time ingestion of sensor data (e.g., alerts and forecasts from physical models) means that automated Quality Assurance/Quality Control (QA/QC) is necessary to ensure that the data collected is fit for purpose. Current automated QA/QC approaches provide assessments based upon hard classifications of the gathered data; often as a binary decision of good or bad data that fails to quantify our confidence in the data for use in different applications. We propose a novel framework for automated data quality assessments that uses Fuzzy Logic to provide a continuous scale of data quality. This continuous quality scale is then used to compute error bars upon the data, which quantify the data uncertainty and provide a more meaningful measure of the data’s fitness for purpose in a particular application compared with hard quality classifications. The design principles of the framework are presented and enable both data statistics and expert knowledge to be incorporated into the uncertainty assessment. We have implemented and tested the framework upon a real time platform of temperature and conductivity sensors that have been deployed to monitor the Derwent Estuary in Hobart, Australia. Results indicate that the error bars generated from the Fuzzy QA/QC implementation are in good agreement with the error bars manually encoded by a domain expert.

Abstract: Nine Sky Quality Meters (SQMs) have been intercompared during a night time measurement campaign held in the Netherlands in April 2011. Since then the nine SQMs have been distributed across the Netherlands and form the Dutch network for monitoring night sky brightness. The goal of the intercomparison was to infer mutual calibration factors and obtain insight into the variability of the SQMs under different meteorological situations. An ensemble average is built from the individual measurements and used as a reference to infer the mutual calibration factors. Data required additional synchronization prior to the calibration determination, because the effect of moving clouds combined with small misalignments emerges as time jitter in the measurements. Initial scatter of the individual instruments lies between ±14%. Individual night time sums range from −16% to +20%. Intercalibration reduces this to 0.5%, and −7% to +9%, respectively. During the campaign the smallest luminance measured was 0.657 ± 0.003 mcd/m² on 12 April, and the largest value was 5.94 ± 0.03 mcd/m² on 2 April. During both occurrences interfering circumstances like snow cover or moonlight were absent.

Abstract: This study demonstrates a novel cell manipulation microdevice for cell docking, culturing, cell-cell contact and interaction by microfluidic manipulation of heterogeneous cell suspensions. Heterogeneous cell suspensions include disparate blood cells of natural killer cells and leukemia cancer cells for immune cell transplantation therapy. However, NK cell alloreactivity from different healthy donors present various recovery response levels. Little is still known about the interactions and cytotoxicity effects between donor NK cells and recipient cancer cells. The cell-based micro device first showed the capability of cell docking, movement, contact and cell-cell interaction with respect to cell cytotoxicity of NK cells against cancer cells. With various flow tests for live cell loading, flow rates of 10 μL/h were chosen for injection in the central and side flows such that both types of suspension cells could be gently docked at the gap structure in a reaction zone. The trapping number of particles and cells was linearly proportional to the gap length. Finally, the cytotoxicity of around 40% was found to be similar in the case of dilute cells and a large cell population. As a result, the cell manipulation microdevice has been validated for live suspensions of natural killer and cancer cells, and exhibited the capability to measure the cytotoxicity of dilute cell suspensions.

Abstract: This paper presents a road distress detection system involving the phases needed to properly deal with fully automatic road distress assessment. A vehicle equipped with line scan cameras, laser illumination and acquisition HW-SW is used to storage the digital images that will be further processed to identify road cracks. Pre-processing is firstly carried out to both smooth the texture and enhance the linear features. Non-crack features detection is then applied to mask areas of the images with joints, sealed cracks and white painting, that usually generate false positive cracking. A seed-based approach is proposed to deal with road crack detection, combining Multiple Directional Non-Minimum Suppression (MDNMS) with a symmetry check. Seeds are linked by computing the paths with the lowest cost that meet the symmetry restrictions. The whole detection process involves the use of several parameters. A correct setting becomes essential to get optimal results without manual intervention. A fully automatic approach by means of a linear SVM-based classifier ensemble able to distinguish between up to 10 different types of pavement that appear in the Spanish roads is proposed. The optimal feature vector includes different texture-based features. The parameters are then tuned depending on the output provided by the classifier. Regarding non-crack features detection, results show that the introduction of such module reduces the impact of false positives due to non-crack features up to a factor of 2. In addition, the observed performance of the crack detection system is significantly boosted by adapting the parameters to the type of pavement.

Abstract: Finite element method analysis was applied to the characterization of the biomolecular interactions taking place in a microfluidic assisted microarray. Numerical simulations have been used for the optimization of geometrical and physical parameters of the sensing device. Different configurations have been analyzed and general considerations have been derived. We have shown that a parallel disposition of the sensing area allows the homogeneous formation of the target molecular complex in all the active zones of the microarray. Stationary and time dependent results have also been obtained.

Abstract: Förster resonance energy transfer (FRET) from luminescent terbium complexes (LTC) as donors to semiconductor quantum dots (QDs) as acceptors allows extraordinary large FRET efficiencies due to the long Förster distances afforded. Moreover, time-gated detection permits an efficient suppression of autofluorescent background leading to sub-picomolar detection limits even within multiplexed detection formats. These characteristics make FRET-systems with LTC and QDs excellent candidates for clinical diagnostics. So far, such proofs of principle for highly sensitive multiplexed biosensing have only been performed under optimized buffer conditions and interactions between real-life clinical media such as human serum or plasma and LTC-QD-FRET-systems have not yet been taken into account. Here we present an extensive spectroscopic analysis of absorption, excitation and emission spectra along with the luminescence decay times of both the single components as well as the assembled FRET-systems in TRIS-buffer, TRIS-buffer with 2% bovine serum albumin, and fresh human plasma. Moreover, we evaluated homogeneous LTC-QD FRET assays in QD conjugates assembled with either the well-known, specific biotin-streptavidin biological interaction or, alternatively, the metal-affinity coordination of histidine to zinc. In the case of conjugates assembled with biotin-streptavidin no significant interference with the optical and binding properties occurs whereas the histidine-zinc system appears to be affected by human plasma.

Abstract: Various ZnO nanostructures such as porous nanorods and two hierarchical structures consisting of porous nanosheets or crystalline nanorods were prepared by the reaction of mixtures of oleic-acid-dissolved ethanol solutions and aqueous dissolved Zn-precursor solutions in the presence of NaOH. All three ZnO nanostructures showed sensitive and selective detection of C₂H₅OH. In particular, ultra-high responses (R_a/R_g = ~1,200, R_a: resistance in air, R_g: resistance in gas) to 100 ppm C₂H₅OH was attained using porous nanorods and hierarchical structures assembled from porous nanosheets, which is one of the highest values reported in the literature. The gas response and linearity of gas sensors were discussed in relation to the size, surface area, and porosity of the nanostructures.

Abstract: We introduce both the coexistence zone within the WiMAX frame structure and a PS-Request protocol for the coexistence of WiFi and WiMAX systems sharing a frequency band. Because we know that the PS-Request protocol has drawbacks, we propose a revised PS-Request protocol to improve the performance. Two PS-Request protocols are based on the time division operation (TDO) of WiFi system and WiMAX system to avoid the mutual interference, and use the vestigial power management (PwrMgt) bit within the Frame Control field of the frames transmitted by a WiFi AP. The performance of the revised PS-Request protocol is evaluated by computer simulation, and compared to those of the cases without a coexistence protocol and to the original PS-Request protocol.

Abstract: With the widespread use of identification systems, establishing authenticity with sensors has become an important research issue. Among the schemes for making authenticity verification based on information security possible, reversible data hiding has attracted much attention during the past few years. With its characteristics of reversibility, the scheme is required to fulfill the goals from two aspects. On the one hand, at the encoder, the secret information needs to be embedded into the original image by some algorithms, such that the output image will resemble the input one as much as possible. On the other hand, at the decoder, both the secret information and the original image must be correctly extracted and recovered, and they should be identical to their embedding counterparts. Under the requirement of reversibility, for evaluating the performance of the data hiding algorithm, the output image quality, named imperceptibility, and the number of bits for embedding, called capacity, are the two key factors to access the effectiveness of the algorithm. Besides, the size of side information for making decoding possible should also be evaluated. Here we consider using the characteristics of original images for developing our method with better performance. In this paper, we propose an algorithm that has the ability to provide more capacity than conventional algorithms, with similar output image quality after embedding, and comparable side information produced. Simulation results demonstrate the applicability and better performance of our algorithm.

Abstract: Semiconductor quantum dots (QDs) have served as the basis for signal development in a variety of biosensing technologies and in applications using bioprobes. The use of QDs as physical platforms to develop biosensors and bioprobes has attracted considerable interest. This is largely due to the unique optical properties of QDs that make them excellent choices as donors in fluorescence resonance energy transfer (FRET) and well suited for optical multiplexing. The large majority of QD-based bioprobe and biosensing technologies that have been described operate in bulk solution environments, where selective binding events at the surface of QDs are often associated with relatively long periods to reach a steady-state signal. An alternative approach to the design of biosensor architectures may be provided by a microfluidic system (MFS). A MFS is able to integrate chemical and biological processes into a single platform and allows for manipulation of flow conditions to achieve, by sample transport and mixing, reaction rates that are not entirely diffusion controlled. Integrating assays in a MFS provides numerous additional advantages, which include the use of very small amounts of reagents and samples, possible sample processing before detection, ultra-high sensitivity, high throughput, short analysis time, and in situ monitoring. Herein, a comprehensive review is provided that addresses the key concepts and applications of QD-based microfluidic biosensors with an added emphasis on how this combination of technologies provides for innovations in bioassay designs. Examples from the literature are used to highlight the many advantages of biosensing in a MFS and illustrate the versatility that such a platform offers in the design strategy.

Abstract: Nowadays sun sensors are being more widely used in satellites to determine the sunray orientation, thus development of a new version of sun sensor with lighter mass, lower power consumption and smaller size it of considerable interest. This paper introduces such a novel digital sun sensor, which is composed of a micro-electro-mechanical system (MEMS) mask with an N-shaped slit as well as a single linear array charge-coupled device (CCD). The sun sensor can achieve the measurement of two-axis sunray angles according to the three sun spot images on the CCD formed by sun light illumination through the mask. Given the CCD glass layer, an iterative algorithm is established to correct the refraction error. Thus, system resolution, update rate and other characteristics are improved based on the model simulation and system design. The test of sun sensor prototype is carried out on a three-axis rotating platform with a sun simulator. The test results show that the field of view (FOV) is ±60° × ±60° and the accuracy is 0.08 degrees of arc (3σ) in the whole FOV. Since the power consumption of the prototype is only 300 mW and the update rate is 14 Hz, the novel digital sun sensor can be applied broadly in micro/nano-satellites, even pico-satellites.

Abstract: Position data of players and athletes are widely used in sports performance analysis for measuring the amounts of physical activities as well as for tactical assessments in game sports. However, positioning sensing systems are applied in sports as tools to gain objective information of sports behavior rather than as components of intelligent spaces (IS). The paper outlines the idea of IS for the sports context with special focus to game sports and how intelligent sports feedback systems can benefit from IS. Henceforth, the most common location sensing techniques used in sports and their practical application are reviewed, as location is among the most important enabling techniques for IS. Furthermore, the article exemplifies the idea of IS in sports on two applications.

Abstract: A high Q-factor (quality-factor) spiral inductor fabricated by the CMOS (complementary metal oxide semiconductor) process and a post-process was investigated. The spiral inductor is manufactured on a silicon substrate. A post-process is used to remove the underlying silicon substrate in order to reduce the substrate loss and to enhance the Q-factor of the inductor. The post-process adopts RIE (reactive ion etching) to etch the sacrificial oxide layer, and then TMAH (tetramethylammonium hydroxide) is employed to remove the silicon substrate for obtaining the suspended spiral inductor. The advantage of this post-processing method is its compatibility with the CMOS process. The performance of the spiral inductor is measured by an Agilent 8510C network analyzer and a Cascade probe station. Experimental results show that the Q-factor and inductance of the spiral inductor are 15 at 15 GHz and 1.8 nH at 1 GHz, respectively.

Abstract: A rocking mass gyroscope (RMG) is a kind of vibrating mass gyroscope with high sensitivity, whose driving mode and sensing mode are completely uniform. MEMS RMG devices are a research hotspot now because they have the potential to be used in space applications. Support loss is the dominant energy loss mechanism influencing their high sensitivity. An accurate analytical model of support loss for RMGs is presented to enhance their Q factors. The anchor type and support loss mechanism of an RMG are analyzed. Firstly, the support loads, powers flowing into support structure, and vibration energy of an RMG are all developed. Then the analytical model of support loss for the RMG is developed, and its sensitivities to the main structural parameters are also analyzed. High-Q design guidelines for rocking mass microgyroscopes are deduced. Finally, the analytical model is validated by the experimental data and the data from the existing literature. The thicknesses of the prototypes are reduced from 240 µm to 60 µm, while Q factors increase from less than 150 to more than 800. The derived model is general and applicable to various beam resonators, providing significant insight to the design of high-Q MEMS devices.

Abstract: The present work has developed a methodology for studying natural ventilation in Mediterranean greenhouses by means of sonic anemometry. In addition, specific calculation programmes have been designed to enable processing and analysis of the data recorded during the experiments. Sonic anemometry allows us to study the direction of the airflow at all the greenhouse vents. Knowing through which vents the air enters and leaves the greenhouse enables us to establish the airflow pattern of the greenhouse under natural ventilation conditions. In the greenhouse analysed in this work for Poniente wind (from the southwest), a roof vent designed to open towards the North (leeward) could allow a positive interaction between the wind and stack effects, improving the ventilation capacity of the greenhouse. The cooling effect produced by the mass of turbulent air oscillating between inside and outside the greenhouse at the side vents was limited to 2% (for high wind speed, u_o ≥ 4 m s⁻¹) reaching 36.3% when wind speed was lower (u_o = 2 m s⁻¹).

Abstract: Autonomous manipulation in semi-structured environments where human operators can interact is an increasingly common task in robotic applications. This paper describes an intelligent multi-sensorial approach that solves this issue by providing a multi-robotic platform with a high degree of autonomy and the capability to perform complex tasks. The proposed sensorial system is composed of a hybrid visual servo control to efficiently guide the robot towards the object to be manipulated, an inertial motion capture system and an indoor localization system to avoid possible collisions between human operators and robots working in the same workspace, and a tactile sensor algorithm to correctly manipulate the object. The proposed controller employs the whole multi-sensorial system and combines the measurements of each one of the used sensors during two different phases considered in the robot task: a first phase where the robot approaches the object to be grasped, and a second phase of manipulation of the object. In both phases, the unexpected presence of humans is taken into account. This paper also presents the successful results obtained in several experimental setups which verify the validity of the proposed approach.

Abstract: Radio frequency identification (RFID) systems are emerging as the primary object identification mechanism, especially in supply chain management. However, RFID naturally generates a large amount of duplicate readings. Removing these duplicates from the RFID data stream is paramount as it does not contribute new information to the system and wastes system resources. Existing approaches to deal with this problem cannot fulfill the real time demands to process the massive RFID data stream. We propose a data filtering approach that efficiently detects and removes duplicate readings from RFID data streams. Experimental results show that the proposed approach offers a significant improvement as compared to the existing approaches.

Abstract: A miniaturized taste sensor chip was designed for use in a portable-type taste sensing system. The fabricated sensor chip (40 mm × 26 mm × 2.2 mm) has multiple taste-sensing sites consisting of a poly(hydroxyethyl methacrylate) hydrogel with KCl as the electrolyte layer for stability of the membrane potential and artificial lipid membranes as the taste sensing elements. The sensor responses to the standard taste substances showed high accuracy and good reproducibility, which is comparable with the performance of the sensor probe of the commercialized taste sensing system. Thus, the fabricated taste sensor chip could be used as a key element for the realization of a portable-type taste sensing system.

Abstract: Cooperative communication in wireless sensor network (WSN) explores the energy efficient wireless communication schemes between multiple sensors and data gathering node (DGN) by exploiting multiple input multiple output (MIMO) and multiple input single output (MISO) configurations. In this paper, an energy efficient cooperative MIMO (C-MIMO) technique is proposed where low density parity check (LDPC) code is used as an error correcting code. The rate of LDPC code is varied by varying the length of message and parity bits. Simulation results show that the cooperative communication scheme outperforms SISO scheme in the presence of LDPC code. LDPC codes with different code rates are compared using bit error rate (BER) analysis. BER is also analyzed under different Nakagami fading scenario. Energy efficiencies are compared for different targeted probability of bit error p_b. It is observed that C-MIMO performs more efficiently when the targeted p_b is smaller. Also the lower encoding rate for LDPC code offers better error characteristics.

Abstract: Recent advances in integrated electronic devices motivated the use of Wireless Sensor Networks (WSNs) in many applications including domain surveillance and mobile target tracking, where a number of sensors are scattered within a sensitive region to detect the presence of intruders and forward related events to some analysis center(s). Obviously, sensor deployment should guarantee an optimal event detection rate and should reduce coverage holes. Most of the coverage control approaches proposed in the literature deal with two-dimensional zones and do not develop strategies to handle coverage in three-dimensional domains, which is becoming a requirement for many applications including water monitoring, indoor surveillance, and projectile tracking. This paper proposes efficient techniques to detect coverage holes in a 3D domain using a finite set of sensors, repair the holes, and track hostile targets. To this end, we use the concepts of Voronoi tessellation, Vietoris complex, and retract by deformation. We show in particular that, through a set of iterative transformations of the Vietoris complex corresponding to the deployed sensors, the number of coverage holes can be computed with a low complexity. Mobility strategies are also proposed to repair holes by moving appropriately sensors towards the uncovered zones. The tracking objective is to set a non-uniform WSN coverage within the monitored domain to allow detecting the target(s) by the set of sensors. We show, in particular, how the proposed algorithms adapt to cope with obstacles. Simulation experiments are carried out to analyze the efficiency of the proposed models. To our knowledge, repairing and tracking is addressed for the first time in 3D spaces with different sensor coverage schemes.

Abstract: Sensor fault diagnosis is necessary to ensure the normal operation of a gas turbine system. However, the existing methods require too many resources and this need can’t be satisfied in some occasions. Since the sensor readings are directly affected by sensor state, sensor fault diagnosis can be performed by extracting features of the measured signals. This paper proposes a novel fault diagnosis method for sensors based on wavelet entropy. Based on the wavelet theory, wavelet decomposition is utilized to decompose the signal in different scales. Then the instantaneous wavelet energy entropy (IWEE) and instantaneous wavelet singular entropy (IWSE) are defined based on the previous wavelet entropy theory. Subsequently, a fault diagnosis method for gas turbine sensors is proposed based on the results of a numerically simulated example. Then, experiments on this method are carried out on a real micro gas turbine engine. In the experiment, four types of faults with different magnitudes are presented. The experimental results show that the proposed method for sensor fault diagnosis is efficient.

Abstract: Lithium-ion secondary batteries are commonly used in electric vehicles, smart phones, personal digital assistants (PDA), notebooks and electric cars. These lithium-ion secondary batteries must charge and discharge rapidly, causing the interior temperature to rise quickly, raising a safety issue. Over-charging results in an unstable voltage and current, causing potential safety problems, such as thermal runaways and explosions. Thus, a micro flexible temperature sensor for the in in-situ monitoring of temperature inside a lithium-ion secondary battery must be developed. In this work, flexible micro temperature sensors were integrated into a lithium-ion secondary battery using the micro-electro-mechanical systems (MEMS) process for monitoring temperature in situ.

Abstract: In the present research, the concept of developing a novel system based on polymer-enzyme macromolecules was tested by coupling carboxylic acid functionalized poly(vinyl alcohol) (PVA-COOH) to glucose oxidase (GOx) followed by the bioconjugation with CdS quantum-dots (QD). The resulting organic-inorganic nanohybrids were characterized by UV-visible spectroscopy, infrared spectroscopy, Photoluminescence spectroscopy (PL) and transmission electron microscopy (TEM). The spectroscopy results have clearly shown that the polymer-enzyme macromolecules (PVA-COOH/GOx) were synthesized by the proposed zero-length linker route. Moreover, they have performed as successful capping agents for the nucleation and constrained growth of CdS quantum-dots via aqueous colloidal chemistry. The TEM images associated with the optical absorption results have indicated the formation of CdS nanocrystals with estimated diameters of about 3.0 nm. The “blue-shift” in the visible absorption spectra and the PL values have provided strong evidence that the fluorescent CdS nanoparticles were produced in the quantum-size confinement regime. Finally, the hybrid system was biochemically assayed by injecting the glucose substrate and detecting the formation of peroxide with the enzyme horseradish peroxidase (HRP). Thus, the polymer-enzyme-QD hybrid has behaved as a nanostructured sensor for glucose detecting.

Abstract: Developing soil sensors with the possibility of continuous online measurement is a major challenge in soil science. Terahertz (THz) electromagnetic radiation may provide the opportunity for the measurement of organic material density, water content and other soil parameters at different soil depths. Penetration depth and information content is important for a functional soil sensor. Therefore, we present initial research on the analysis of absorption coefficients of four different soil samples by means of THz transmission measurements. An optimized soil sample holder to determine absorption coefficients was used. This setup improves data acquisition because interface reflections can be neglected. Frequencies of 340 GHz to 360 GHz and 1.627 THz to 2.523 THz provided information about an existing frequency dependency. The results demonstrate the potential of this THz approach for both soil analysis and imaging of buried objects. Therefore, the THz approach allows different soil samples to be distinguished according to their different absorption properties so that relations among soil parameters may be established in future.

Abstract: Localization is an important research issue in Wireless Sensor Networks (WSNs). Though Global Positioning System (GPS) can be used to locate the position of the sensors, unfortunately it is limited to outdoor applications and is costly and power consuming. In order to find location of sensor nodes without help of GPS, collaboration among nodes is highly essential so that localization can be accomplished efficiently. In this paper, novel localization algorithms are proposed to find out possible location information of the normal nodes in a collaborative manner for an outdoor environment with help of few beacons and anchor nodes. In our localization scheme, at most three beacon nodes should be collaborated to find out the accurate location information of any normal node. Besides, analytical methods are designed to calculate and reduce the localization error using probability distribution function. Performance evaluation of our algorithm shows that there is a trade off betweendeployed number of beacon nodes and localization error, and average localization time of the network can be increased with increase in the number of normal nodes deployed over a region.