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Sensors, Volume 15, Issue 8 (August 2015), Pages 17827-20944

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Open AccessArticle A Self-Assessment Stereo Capture Model Applicable to the Internet of Things
Sensors 2015, 15(8), 20925-20944; https://doi.org/10.3390/s150820925
Received: 10 July 2015 / Revised: 7 August 2015 / Accepted: 14 August 2015 / Published: 21 August 2015
Cited by 148 | PDF Full-text (1648 KB) | HTML Full-text | XML Full-text
Abstract
The realization of the Internet of Things greatly depends on the information communication among physical terminal devices and informationalized platforms, such as smart sensors, embedded systems and intelligent networks. Playing an important role in information acquisition, sensors for stereo capture have gained extensive
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The realization of the Internet of Things greatly depends on the information communication among physical terminal devices and informationalized platforms, such as smart sensors, embedded systems and intelligent networks. Playing an important role in information acquisition, sensors for stereo capture have gained extensive attention in various fields. In this paper, we concentrate on promoting such sensors in an intelligent system with self-assessment capability to deal with the distortion and impairment in long-distance shooting applications. The core design is the establishment of the objective evaluation criteria that can reliably predict shooting quality with different camera configurations. Two types of stereo capture systems—toed-in camera configuration and parallel camera configuration—are taken into consideration respectively. The experimental results show that the proposed evaluation criteria can effectively predict the visual perception of stereo capture quality for long-distance shooting. Full article
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
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Open AccessArticle Reliable Fusion of Stereo Matching and Depth Sensor for High Quality Dense Depth Maps
Sensors 2015, 15(8), 20894-20924; https://doi.org/10.3390/s150820894
Received: 23 June 2015 / Revised: 7 August 2015 / Accepted: 17 August 2015 / Published: 21 August 2015
Cited by 5 | PDF Full-text (22352 KB) | HTML Full-text | XML Full-text
Abstract
Depth estimation is a classical problem in computer vision, which typically relies on either a depth sensor or stereo matching alone. The depth sensor provides real-time estimates in repetitive and textureless regions where stereo matching is not effective. However, stereo matching can obtain
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Depth estimation is a classical problem in computer vision, which typically relies on either a depth sensor or stereo matching alone. The depth sensor provides real-time estimates in repetitive and textureless regions where stereo matching is not effective. However, stereo matching can obtain more accurate results in rich texture regions and object boundaries where the depth sensor often fails. We fuse stereo matching and the depth sensor using their complementary characteristics to improve the depth estimation. Here, texture information is incorporated as a constraint to restrict the pixel’s scope of potential disparities and to reduce noise in repetitive and textureless regions. Furthermore, a novel pseudo-two-layer model is used to represent the relationship between disparities in different pixels and segments. It is more robust to luminance variation by treating information obtained from a depth sensor as prior knowledge. Segmentation is viewed as a soft constraint to reduce ambiguities caused by under- or over-segmentation. Compared to the average error rate 3.27% of the previous state-of-the-art methods, our method provides an average error rate of 2.61% on the Middlebury datasets, which shows that our method performs almost 20% better than other “fused” algorithms in the aspect of precision. Full article
(This article belongs to the Special Issue Imaging: Sensors and Technologies) Printed Edition available
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Open AccessArticle A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness
Sensors 2015, 15(8), 20873-20893; https://doi.org/10.3390/s150820873
Received: 6 July 2015 / Revised: 30 July 2015 / Accepted: 18 August 2015 / Published: 21 August 2015
Cited by 11 | PDF Full-text (1567 KB) | HTML Full-text | XML Full-text
Abstract
Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI) systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at
[...] Read more.
Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI) systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existing BMI systems. This study proposes a context-aware BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements. The proposed system is carefully designed for low-power consumption with on-chip feature extraction and low energy Bluetooth connection. Also, the proposed system is implemented using JAVA programming language as a mobile application for on-line analysis. In total, 266 datasets obtained from six subjects who participated in a one-hour monotonous driving simulation experiment were used to evaluate this system. According to a video-based reference, the proposed system obtained an overall detection accuracy of 82.71% for classifying alert and slightly drowsy events by using EEG data alone and 96.24% by using the hybrid data of head-movement and EEG. These results indicate that the combination of EEG data and head-movement contextual information constitutes a robust solution for the early detection of driver drowsiness. Full article
(This article belongs to the Special Issue Wearable Sensors)
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Open AccessArticle Lipid Multilayer Grating Arrays Integrated by Nanointaglio for Vapor Sensing by an Optical Nose
Sensors 2015, 15(8), 20863-20872; https://doi.org/10.3390/s150820863
Received: 3 July 2015 / Revised: 29 July 2015 / Accepted: 17 August 2015 / Published: 21 August 2015
Cited by 3 | PDF Full-text (722 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Lipid multilayer gratings are recently invented nanomechanical sensor elements that are capable of transducing molecular binding to fluid lipid multilayers into optical signals in a label free manner due to shape changes in the lipid nanostructures. Here, we show that nanointaglio is suitable
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Lipid multilayer gratings are recently invented nanomechanical sensor elements that are capable of transducing molecular binding to fluid lipid multilayers into optical signals in a label free manner due to shape changes in the lipid nanostructures. Here, we show that nanointaglio is suitable for the integration of chemically different lipid multilayer gratings into a sensor array capable of distinguishing vapors by means of an optical nose. Sensor arrays composed of six different lipid formulations are integrated onto a surface and their optical response to three different vapors (water, ethanol and acetone) in air as well as pH under water is monitored as a function of time. Principal component analysis of the array response results in distinct clustering indicating the suitability of the arrays for distinguishing these analytes. Importantly, the nanointaglio process used here is capable of producing lipid gratings out of different materials with sufficiently uniform heights for the fabrication of an optical nose. Full article
(This article belongs to the Special Issue Nanomechanics for Sensing and Spectrometry)
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Open AccessArticle Distance-Dependent Multimodal Image Registration for Agriculture Tasks
Sensors 2015, 15(8), 20845-20862; https://doi.org/10.3390/s150820845
Received: 1 May 2015 / Revised: 11 August 2015 / Accepted: 11 August 2015 / Published: 21 August 2015
Cited by 3 | PDF Full-text (6024 KB) | HTML Full-text | XML Full-text
Abstract
Image registration is the process of aligning two or more images of the same scene taken at different times; from different viewpoints; and/or by different sensors. This research focuses on developing a practical method for automatic image registration for agricultural systems that use
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Image registration is the process of aligning two or more images of the same scene taken at different times; from different viewpoints; and/or by different sensors. This research focuses on developing a practical method for automatic image registration for agricultural systems that use multimodal sensory systems and operate in natural environments. While not limited to any particular modalities; here we focus on systems with visual and thermal sensory inputs. Our approach is based on pre-calibrating a distance-dependent transformation matrix (DDTM) between the sensors; and representing it in a compact way by regressing the distance-dependent coefficients as distance-dependent functions. The DDTM is measured by calculating a projective transformation matrix for varying distances between the sensors and possible targets. To do so we designed a unique experimental setup including unique Artificial Control Points (ACPs) and their detection algorithms for the two sensors. We demonstrate the utility of our approach using different experiments and evaluation criteria. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Efficient Implementation of a Symbol Timing Estimator for Broadband PLC
Sensors 2015, 15(8), 20825-20844; https://doi.org/10.3390/s150820825
Received: 26 June 2015 / Revised: 27 July 2015 / Accepted: 14 August 2015 / Published: 21 August 2015
Cited by 3 | PDF Full-text (1718 KB) | HTML Full-text | XML Full-text
Abstract
Broadband Power Line Communications (PLC) have taken advantage of the research advances in multi-carrier modulations to mitigate frequency selective fading, and their adoption opens up a myriad of applications in the field of sensory and automation systems, multimedia connectivity or smart spaces. Nonetheless,
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Broadband Power Line Communications (PLC) have taken advantage of the research advances in multi-carrier modulations to mitigate frequency selective fading, and their adoption opens up a myriad of applications in the field of sensory and automation systems, multimedia connectivity or smart spaces. Nonetheless, the use of these multi-carrier modulations, such as Wavelet-OFDM, requires a highly accurate symbol timing estimation for reliably recovering of transmitted data. Furthermore, the PLC channel presents some particularities that prevent the direct use of previous synchronization algorithms proposed in wireless communication systems. Therefore more research effort should be involved in the design and implementation of novel and robust synchronization algorithms for PLC, thus enabling real-time synchronization. This paper proposes a symbol timing estimator for broadband PLC based on cross-correlation with multilevel complementary sequences or Zadoff-Chu sequences and its efficient implementation in a FPGA; the obtained results show a 90% of success rate in symbol timing estimation for a certain PLC channel model and a reduced resource consumption for its implementation in a Xilinx Kyntex FPGA. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Towards a Low-Cost Remote Memory Attestation for the Smart Grid
Sensors 2015, 15(8), 20799-20824; https://doi.org/10.3390/s150820799
Received: 27 June 2015 / Revised: 9 August 2015 / Accepted: 13 August 2015 / Published: 21 August 2015
Cited by 10 | PDF Full-text (500 KB) | HTML Full-text | XML Full-text
Abstract
In the smart grid, measurement devices may be compromised by adversaries, and their operations could be disrupted by attacks. A number of schemes to efficiently and accurately detect these compromised devices remotely have been proposed. Nonetheless, most of the existing schemes detecting compromised
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In the smart grid, measurement devices may be compromised by adversaries, and their operations could be disrupted by attacks. A number of schemes to efficiently and accurately detect these compromised devices remotely have been proposed. Nonetheless, most of the existing schemes detecting compromised devices depend on the incremental response time in the attestation process, which are sensitive to data transmission delay and lead to high computation and network overhead. To address the issue, in this paper, we propose a low-cost remote memory attestation scheme (LRMA), which can efficiently and accurately detect compromised smart meters considering real-time network delay and achieve low computation and network overhead. In LRMA, the impact of real-time network delay on detecting compromised nodes can be eliminated via investigating the time differences reported from relay nodes. Furthermore, the attestation frequency in LRMA is dynamically adjusted with the compromised probability of each node, and then, the total number of attestations could be reduced while low computation and network overhead can be achieved. Through a combination of extensive theoretical analysis and evaluations, our data demonstrate that our proposed scheme can achieve better detection capacity and lower computation and network overhead in comparison to existing schemes. Full article
(This article belongs to the Special Issue Identification, Information & Knowledge in the Internet of Things)
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Open AccessArticle GPS/DR Error Estimation for Autonomous Vehicle Localization
Sensors 2015, 15(8), 20779-20798; https://doi.org/10.3390/s150820779
Received: 16 June 2015 / Revised: 30 July 2015 / Accepted: 11 August 2015 / Published: 21 August 2015
Cited by 20 | PDF Full-text (1356 KB) | HTML Full-text | XML Full-text
Abstract
Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections
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Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level. Full article
(This article belongs to the Special Issue Sensors in New Road Vehicles)
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Open AccessArticle High-Performance Motion Estimation for Image Sensors with Video Compression
Sensors 2015, 15(8), 20752-20778; https://doi.org/10.3390/s150820752
Received: 29 June 2015 / Revised: 5 August 2015 / Accepted: 13 August 2015 / Published: 21 August 2015
Cited by 2 | PDF Full-text (949 KB) | HTML Full-text | XML Full-text
Abstract
It is important to reduce the time cost of video compression for image sensors in video sensor network. Motion estimation (ME) is the most time-consuming part in video compression. Previous work on ME exploited intra-frame data reuse in a reference frame to improve
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It is important to reduce the time cost of video compression for image sensors in video sensor network. Motion estimation (ME) is the most time-consuming part in video compression. Previous work on ME exploited intra-frame data reuse in a reference frame to improve the time efficiency but neglected inter-frame data reuse. We propose a novel inter-frame data reuse scheme which can exploit both intra-frame and inter-frame data reuse for ME in video compression (VC-ME). Pixels of reconstructed frames are kept on-chip until they are used by the next current frame to avoid off-chip memory access. On-chip buffers with smart schedules of data access are designed to perform the new data reuse scheme. Three levels of the proposed inter-frame data reuse scheme are presented and analyzed. They give different choices with tradeoff between off-chip bandwidth requirement and on-chip memory size. All three levels have better data reuse efficiency than their intra-frame counterparts, so off-chip memory traffic is reduced effectively. Comparing the new inter-frame data reuse scheme with the traditional intra-frame data reuse scheme, the memory traffic can be reduced by 50% for VC-ME. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle ECG Sensor Card with Evolving RBP Algorithms for Human Verification
Sensors 2015, 15(8), 20730-20751; https://doi.org/10.3390/s150820730
Received: 14 June 2015 / Revised: 28 July 2015 / Accepted: 6 August 2015 / Published: 21 August 2015
Cited by 2 | PDF Full-text (1077 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a
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It is known that cardiac and respiratory rhythms in electrocardiograms (ECGs) are highly nonlinear and non-stationary. As a result, most traditional time-domain algorithms are inadequate for characterizing the complex dynamics of the ECG. This paper proposes a new ECG sensor card and a statistical-based ECG algorithm, with the aid of a reduced binary pattern (RBP), with the aim of achieving faster ECG human identity recognition with high accuracy. The proposed algorithm has one advantage that previous ECG algorithms lack—the waveform complex information and de-noising preprocessing can be bypassed; therefore, it is more suitable for non-stationary ECG signals. Experimental results tested on two public ECG databases (MIT-BIH) from MIT University confirm that the proposed scheme is feasible with excellent accuracy, low complexity, and speedy processing. To be more specific, the advanced RBP algorithm achieves high accuracy in human identity recognition and is executed at least nine times faster than previous algorithms. Moreover, based on the test results from a long-term ECG database, the evolving RBP algorithm also demonstrates superior capability in handling long-term and non-stationary ECG signals. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Low Power Wireless Smoke Alarm System in Home Fires
Sensors 2015, 15(8), 20717-20729; https://doi.org/10.3390/s150820717
Received: 28 April 2015 / Revised: 24 July 2015 / Accepted: 17 August 2015 / Published: 21 August 2015
Cited by 7 | PDF Full-text (3034 KB) | HTML Full-text | XML Full-text
Abstract
A novel sensing device for fire detection in domestic environments is presented. The fire detector uses a combination of several sensors that not only detect smoke, but discriminate between different types of smoke. This feature avoids false alarms and warns of different situations.
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A novel sensing device for fire detection in domestic environments is presented. The fire detector uses a combination of several sensors that not only detect smoke, but discriminate between different types of smoke. This feature avoids false alarms and warns of different situations. Power consumption is optimized both in terms of hardware and software, providing a high degree of autonomy of almost five years. Data gathered from the device are transmitted through a wireless communication to a base station. The low cost and compact design provides wide application prospects. Full article
(This article belongs to the Special Issue Sensors for Fire Detection)
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Open AccessArticle Evaluation of the Fourier Frequency Spectrum Peaks of Milk Electrical Conductivity Signals as Indexes to Monitor the Dairy Goats’ Health Status by On-Line Sensors
Sensors 2015, 15(8), 20698-20716; https://doi.org/10.3390/s150820698
Received: 12 May 2015 / Revised: 27 July 2015 / Accepted: 17 August 2015 / Published: 21 August 2015
Cited by 6 | PDF Full-text (1382 KB) | HTML Full-text | XML Full-text
Abstract
The aim of this study is a further characterization of the electrical conductivity (EC) signal of goat milk, acquired on-line by EC sensors, to identify new indexes representative of the EC variations that can be observed during milking, when considering not healthy (NH)
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The aim of this study is a further characterization of the electrical conductivity (EC) signal of goat milk, acquired on-line by EC sensors, to identify new indexes representative of the EC variations that can be observed during milking, when considering not healthy (NH) glands. Two foremilk gland samples from 42 Saanen goats, were collected for three consecutive weeks and for three different lactation stages (LS: 0–60 Days In Milking (DIM); 61–120 DIM; 121–180 DIM), for a total amount of 1512 samples. Bacteriological analyses and somatic cells counts (SCC) were used to define the health status of the glands. With negative bacteriological analyses and SCC < 1,000,000 cells/mL, glands were classified as healthy. When bacteriological analyses were positive or showed a SCC > 1,000,000 cells/mL, glands were classified as NH. For each milk EC signal, acquired on-line and for each gland considered, the Fourier frequency spectrum of the signal was calculated and three representative frequency peaks were identified. To evaluate data acquired a MIXED procedure was used considering the HS, LS and LS × HS as explanatory variables in the statistical model.Results showed that the studied frequency peaks had a significant relationship with the gland’s health status. Results also explained how the milk EC signals’ pattern change in case of NH glands. In fact, it is characterized by slower fluctuations (due to the lower frequencies of the peaks) and by an irregular trend (due to the higher amplitudes of all the main frequency peaks). Therefore, these frequency peaks could be used as new indexes to improve the performances of algorithms based on multivariate models which evaluate the health status of dairy goats through the use of gland milk EC sensors. Full article
(This article belongs to the Section Biosensors)
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Open AccessArticle Research and Experiments on a Unipolar Capacitive Voltage Sensor
Sensors 2015, 15(8), 20678-20697; https://doi.org/10.3390/s150820678
Received: 9 June 2015 / Revised: 27 July 2015 / Accepted: 12 August 2015 / Published: 21 August 2015
Cited by 5 | PDF Full-text (2238 KB) | HTML Full-text | XML Full-text
Abstract
Voltage sensors are an important part of the electric system. In service, traditional voltage sensors need to directly contact a high-voltage charged body. Sensors involve a large volume, complex insulation structures, and high design costs. Typically an iron core structure is adopted. As
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Voltage sensors are an important part of the electric system. In service, traditional voltage sensors need to directly contact a high-voltage charged body. Sensors involve a large volume, complex insulation structures, and high design costs. Typically an iron core structure is adopted. As a result, ferromagnetic resonance can occur easily during practical application. Moreover, owing to the multilevel capacitor divider, the sensor cannot reflect the changes of measured voltage in time. Based on the electric field coupling principle, this paper designs a new voltage sensor; the unipolar structure design solves many problems of traditional voltage sensors like the great insulation design difficulty and high costs caused by grounding electrodes. A differential signal input structure is adopted for the detection circuit, which effectively restrains the influence of the common-mode interference signal. Through sensor modeling, simulation and calculations, the structural design of the sensor electrode was optimized, miniaturization of the sensor was realized, the voltage division ratio of the sensor was enhanced, and the phase difference of sensor measurement was weakened. The voltage sensor is applied to a single-phase voltage class line of 10 kV for testing. According to the test results, the designed sensor is able to meet the requirements of accurate and real-time measurement for voltage of the charged conductor as well as to provide a new method for electricity larceny prevention and on-line monitoring of the power grid in an electric system. Therefore, it can satisfy the development demands of the smart power grid. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle Ultrahigh-Temperature Regeneration of Long Period Gratings (LPGs) in Boron-Codoped Germanosilicate Optical Fibre
Sensors 2015, 15(8), 20659-20677; https://doi.org/10.3390/s150820659
Received: 11 June 2015 / Revised: 13 July 2015 / Accepted: 14 August 2015 / Published: 20 August 2015
Cited by 3 | PDF Full-text (671 KB) | HTML Full-text | XML Full-text
Abstract
The regeneration of UV-written long period gratings (LPG) in boron-codoped germanosilicate “W” fibre is demonstrated and studied. They survive temperatures over 1000 °C. Compared with regenerated FBGs fabricated in the same type of fibre, the evolution curves of LPGs during regeneration and post-annealing
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The regeneration of UV-written long period gratings (LPG) in boron-codoped germanosilicate “W” fibre is demonstrated and studied. They survive temperatures over 1000 °C. Compared with regenerated FBGs fabricated in the same type of fibre, the evolution curves of LPGs during regeneration and post-annealing reveal even more detail of glass relaxation. Piece-wise temperature dependence is observed, indicating the onset of a phase transition of glass in the core and inner cladding at ~500 °C and ~250 °C, and the melting of inner cladding between 860 °C and 900 °C. An asymmetric spectral response with increasing and decreasing annealing temperature points to the complex process dependent material system response. Resonant wavelength tuning by adjusting the dwell temperature at which regeneration is undertaken is demonstrated, showing a shorter resonant wavelength and shorter time for stabilisation with higher dwell temperatures. All the regenerated LPGs are nearly strain-insensitive and cannot be tuned by applying loads during annealing as done for regenerated FBGs. Full article
(This article belongs to the Special Issue Sensors for Harsh Environments)
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Open AccessArticle Highly Sensitive Electrochemical Determination of Alfatoxin B1 Using Quantum Dots-Assembled Amplification Labels
Sensors 2015, 15(8), 20648-20658; https://doi.org/10.3390/s150820648
Received: 24 June 2015 / Revised: 6 August 2015 / Accepted: 17 August 2015 / Published: 20 August 2015
Cited by 4 | PDF Full-text (1137 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
A competitive electrochemical immunoassay for highly sensitive detection of AFB1 is demonstrated using layer-by-layer (LBL) assembled quantum dots (QDs) as labels. To investigate the effects of the higher sensitivity of square wave voltammetric stripping (SWV) and of the LBL technique on the proposed
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A competitive electrochemical immunoassay for highly sensitive detection of AFB1 is demonstrated using layer-by-layer (LBL) assembled quantum dots (QDs) as labels. To investigate the effects of the higher sensitivity of square wave voltammetric stripping (SWV) and of the LBL technique on the proposed immunoassays, the proposed assay was compared to electrochemical (EC) and fluorescent immunoassays, which did not use LBL technology. Peanut samples were analyzed using the three immunoassays. The limits of detection (LODs) were 0.018, 0.046 and 0.212 ng/mL, respectively, while the sensitivities were 0.308, 1.011 and 4.594 ng/mL, respectively. The proposed electrochemical immunoassay displayed a significant improvement in sensitivity, thereby providing a simple and sensitive alternative strategy for determining AFB1 levels in peanut samples. Full article
(This article belongs to the Section Biosensors)
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