Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796268
Walid Elgenaidi, T. Newe, E. O’Connell, D. Toal, G. Dooly, Joseph Coleman
Handling the security in Wireless Sensor Networks (WSNs) requires cryptographic mechanisms to detect faulty and unstable nodes that lead to the inactivity of network during packet travelling. Although, cryptographic security mechanism operations demand a high calculation of computational time and memory resources, while the sensor nodes have low memory and low computation capability. Alternatively, trust management schemes are tools to address some main issues in WSNs including memory and storage space, key generation, and re-keying. In this work, we will present solution of memory resources consumption and key management processing issues for a secure maritime coastal monitoring system. This system is a symmetric security scheme with a dynamic update key based on a trusted node configuration, called a leader node, which works as a trusted third party.
{"title":"Memory storage administration of security encryption keys for line topology in maritime wireless sensor networks","authors":"Walid Elgenaidi, T. Newe, E. O’Connell, D. Toal, G. Dooly, Joseph Coleman","doi":"10.1109/ICSENST.2016.7796268","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796268","url":null,"abstract":"Handling the security in Wireless Sensor Networks (WSNs) requires cryptographic mechanisms to detect faulty and unstable nodes that lead to the inactivity of network during packet travelling. Although, cryptographic security mechanism operations demand a high calculation of computational time and memory resources, while the sensor nodes have low memory and low computation capability. Alternatively, trust management schemes are tools to address some main issues in WSNs including memory and storage space, key generation, and re-keying. In this work, we will present solution of memory resources consumption and key management processing issues for a secure maritime coastal monitoring system. This system is a symmetric security scheme with a dynamic update key based on a trusted node configuration, called a leader node, which works as a trusted third party.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130880203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796240
Nasrin Afsarimanesh, M. Alahi, S. Mukhopadhyay, M. Kruger, P. Yu
This paper presents a label-free and non-invasive technique for selective detection of C-terminal telopeptide type I collagen (CTx-I) by employing Electrochemical Impedance Spectroscopy to measure sample impedance. Molecular imprinted polymer, containing artificial recognition sites for CTx-was prepared by precipitation polymerization using CTx-I peptide as a template, methacrylic acid as a functional monomer and ethylene glycol methacrylate as the cross-linker. A high penetration depth planar interdigital sensor was functionalized by a self-assembled monolayer along with the synthesized MIP. Different concentrations of CTx-I sample solutions were tested using the proposed sensing system. High-Performance Liquid chromatography diode array system was used to validate the results.
{"title":"Development of molecular imprinted polymer interdigital sensor for C-terminal telopeptide of type I collagen","authors":"Nasrin Afsarimanesh, M. Alahi, S. Mukhopadhyay, M. Kruger, P. Yu","doi":"10.1109/ICSENST.2016.7796240","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796240","url":null,"abstract":"This paper presents a label-free and non-invasive technique for selective detection of C-terminal telopeptide type I collagen (CTx-I) by employing Electrochemical Impedance Spectroscopy to measure sample impedance. Molecular imprinted polymer, containing artificial recognition sites for CTx-was prepared by precipitation polymerization using CTx-I peptide as a template, methacrylic acid as a functional monomer and ethylene glycol methacrylate as the cross-linker. A high penetration depth planar interdigital sensor was functionalized by a self-assembled monolayer along with the synthesized MIP. Different concentrations of CTx-I sample solutions were tested using the proposed sensing system. High-Performance Liquid chromatography diode array system was used to validate the results.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126083673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796322
Malinda Dilhara, J. Samarawickrama, S. Elvitigala
We present a novel non-invasive current measuring platform that estimates the current through a bundled cable. The sensor platform contains eight three axis magnetometer breakout sensors. We develop a regression model to estimate the current flowing in the wire using captured data from the sensor platform. The model in the paper demonstrated accurate results for current estimation of two core wire (7.2 mm diameter) with mean absolute error as low as 0.03 A and root mean square error as low as 0.06 A. This work can be used to develop a plug and play instrument that can non-invasively measure current in a system without disturbing its behavior in operating environment.
{"title":"Sensor platform for non-invasive ubiquitous current sensing","authors":"Malinda Dilhara, J. Samarawickrama, S. Elvitigala","doi":"10.1109/ICSENST.2016.7796322","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796322","url":null,"abstract":"We present a novel non-invasive current measuring platform that estimates the current through a bundled cable. The sensor platform contains eight three axis magnetometer breakout sensors. We develop a regression model to estimate the current flowing in the wire using captured data from the sensor platform. The model in the paper demonstrated accurate results for current estimation of two core wire (7.2 mm diameter) with mean absolute error as low as 0.03 A and root mean square error as low as 0.06 A. This work can be used to develop a plug and play instrument that can non-invasively measure current in a system without disturbing its behavior in operating environment.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114277364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796313
Li Yuehua, Zhou Jingbo, Huang Fengshan, L. Lijian
Center extraction of structured light stripe is an essential problem for the development of line structured light sensors (LSLS). To obtain the sub-pixel center coordinates precisely, an improved gray weighted method (IGWM) is proposed with an adaptive sampling region. Firstly, the center of the stripe is computed using gray weighted method (GWM) for each pixel column. Then these center points are fitted using moving least squares algorithm to estimate the tangential vector, the normal vector and the radius of curvature. For each center point, a rectangular region is defined with two sides parallel with the normal vector. The other two sides that parallel with the tangential vector alter their length automatically according to the radius of curvature. After that, the center coordinate at this point is recalculated based on the GWM, but in the normal vector direction and only takes into account the pixels within the rectangular region. The experimental results show that this method is not only suited for the center extraction of smooth laser stripes, but also the ones with sharp corners. The noise can also be obviously suppressed than that of the traditional GWM.
{"title":"An improved gray weighted method for sub-pixel center extraction of structured light stripe","authors":"Li Yuehua, Zhou Jingbo, Huang Fengshan, L. Lijian","doi":"10.1109/ICSENST.2016.7796313","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796313","url":null,"abstract":"Center extraction of structured light stripe is an essential problem for the development of line structured light sensors (LSLS). To obtain the sub-pixel center coordinates precisely, an improved gray weighted method (IGWM) is proposed with an adaptive sampling region. Firstly, the center of the stripe is computed using gray weighted method (GWM) for each pixel column. Then these center points are fitted using moving least squares algorithm to estimate the tangential vector, the normal vector and the radius of curvature. For each center point, a rectangular region is defined with two sides parallel with the normal vector. The other two sides that parallel with the tangential vector alter their length automatically according to the radius of curvature. After that, the center coordinate at this point is recalculated based on the GWM, but in the normal vector direction and only takes into account the pixels within the rectangular region. The experimental results show that this method is not only suited for the center extraction of smooth laser stripes, but also the ones with sharp corners. The noise can also be obviously suppressed than that of the traditional GWM.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129169805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796321
Wenzhong Liu, Shiqiang Pi
Magnetic nanothermometry is of great promising in future biomedical and industrial applications. However, the diameters of the used thermosensitive materials, magnetic nanoparticles, are commonly nonuniform, which will impact the performance of the magnetic nanothermometry. To achieve future high performance magnetic nanothermometer, we study the influences of the particle size distribution of magnetic nanoparticles on the response signal and the temperature estimation error in this paper.
{"title":"AC magnetic nanothermometry: The influence of particle size distribution","authors":"Wenzhong Liu, Shiqiang Pi","doi":"10.1109/ICSENST.2016.7796321","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796321","url":null,"abstract":"Magnetic nanothermometry is of great promising in future biomedical and industrial applications. However, the diameters of the used thermosensitive materials, magnetic nanoparticles, are commonly nonuniform, which will impact the performance of the magnetic nanothermometry. To achieve future high performance magnetic nanothermometer, we study the influences of the particle size distribution of magnetic nanoparticles on the response signal and the temperature estimation error in this paper.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129072323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796232
Y. Qin, L. Mo, Jing Ye, Z. Du
Human activity recognition has been widely used in many fields, especially in video surveillance and virtual reality, etc. The paper investigates a general feature combination method for a relatively new 3D CNNs and LSTMs fusion model in human activity recognition. All the features used in this combination method are from human activity videos without manually extracting features or any prior knowledge, and the model has good generalization performance. Through extracting multi-channel features of the motion optical flow vector, grayscale and body edge, putting them to 3D convolutional neural network, and processing time characteristics within Long-Short Term Memory neural network, the recognition rate of the model rises greatly. The experiment selects KTH dataset as the data source. The model based on RGB is used to compare with the model based on multi-channel features. It shows that multi-channel features can improve recognition accuracy rate obviously, and have great robustness in different scenes, which proves that it is an efficient feature combination method fitted 3D CNNs and LSTMs.
{"title":"Multi-channel features fitted 3D CNNs and LSTMs for human activity recognition","authors":"Y. Qin, L. Mo, Jing Ye, Z. Du","doi":"10.1109/ICSENST.2016.7796232","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796232","url":null,"abstract":"Human activity recognition has been widely used in many fields, especially in video surveillance and virtual reality, etc. The paper investigates a general feature combination method for a relatively new 3D CNNs and LSTMs fusion model in human activity recognition. All the features used in this combination method are from human activity videos without manually extracting features or any prior knowledge, and the model has good generalization performance. Through extracting multi-channel features of the motion optical flow vector, grayscale and body edge, putting them to 3D convolutional neural network, and processing time characteristics within Long-Short Term Memory neural network, the recognition rate of the model rises greatly. The experiment selects KTH dataset as the data source. The model based on RGB is used to compare with the model based on multi-channel features. It shows that multi-channel features can improve recognition accuracy rate obviously, and have great robustness in different scenes, which proves that it is an efficient feature combination method fitted 3D CNNs and LSTMs.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116353791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796340
Xu Jun, Tang Ya-nan, Li Xin
In order to realize remote monitoring and centralized management of combustible gas. A monitoring system of high performance fuel gas based on RS485 bus communication mode was presented in this paper. The system was composed of center controller and unit controller. The hardware design of unit controller and center controller was introduced, and the software design scheme of the control and communication between each controller were given in this paper. The center controller used Modbus protocol to communicate with the unit controller, to realize the display, storage and query of alarm signal of combustible gas, and complete the automatic zero adjustment, calibration and fault detection of the sensor signal of the unit controller. The unit controller collected the concentration value and temperature value of the combustible gas in real time, but due to effect of temperature, so I used RBF neural network to solve the problem of measuring deviation. The experimental results show that the measurement error is less than 2% LEL, and the alarm error is less than 3% LEL. The presented system has advantages such as easiness of operation, real-time fixing, relativity low cost and a wide prospect of applications.
{"title":"High performance combustible gas monitoring system","authors":"Xu Jun, Tang Ya-nan, Li Xin","doi":"10.1109/ICSENST.2016.7796340","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796340","url":null,"abstract":"In order to realize remote monitoring and centralized management of combustible gas. A monitoring system of high performance fuel gas based on RS485 bus communication mode was presented in this paper. The system was composed of center controller and unit controller. The hardware design of unit controller and center controller was introduced, and the software design scheme of the control and communication between each controller were given in this paper. The center controller used Modbus protocol to communicate with the unit controller, to realize the display, storage and query of alarm signal of combustible gas, and complete the automatic zero adjustment, calibration and fault detection of the sensor signal of the unit controller. The unit controller collected the concentration value and temperature value of the combustible gas in real time, but due to effect of temperature, so I used RBF neural network to solve the problem of measuring deviation. The experimental results show that the measurement error is less than 2% LEL, and the alarm error is less than 3% LEL. The presented system has advantages such as easiness of operation, real-time fixing, relativity low cost and a wide prospect of applications.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115152604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796332
I. Platt, A. Tan, I. Woodhead, K. Eccleston
In this paper we derive a robust Markov Chain Monte Carlo formulation to determine the suitable driver amplitudes for a microwave antenna to generate a Bessel beam. We show that the resulting solutions provide a robust driver for a well collimated beam with high SNR over a region of 0.5-3 m, easily sufficient for close proximity sampling.
{"title":"A Monte Carlo approach to determining bessel beam source parameters","authors":"I. Platt, A. Tan, I. Woodhead, K. Eccleston","doi":"10.1109/ICSENST.2016.7796332","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796332","url":null,"abstract":"In this paper we derive a robust Markov Chain Monte Carlo formulation to determine the suitable driver amplitudes for a microwave antenna to generate a Bessel beam. We show that the resulting solutions provide a robust driver for a well collimated beam with high SNR over a region of 0.5-3 m, easily sufficient for close proximity sampling.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121733026","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796252
Lei Jiang, Yu Wang, Xin-hua Zhu, Yan Su
The major challenge of inertial navigation system (INS) is the rapid navigation error drift when aiding sensors are unavailable. However, if the dynamics of land vehicle can be detected, these errors can be corrected or restrained. A method based on support vector machine (SVM) using the outputs of MIMU is proposed here to identify the dynamics of land vehicle. This method computes part of the time-domain features and frequency-domain features. Then, a subset of these features is selected based on wrapper evaluation criteria. Afterwards, SVM is trained based on these selected features. Finally, the trained SVM is used in identification tests. The identification results show that this method can correctly identify the stationary, straight-line and cornering states.
{"title":"A novel vehicle dynamics identification method utilizing MIMU sensors based on support vector machine","authors":"Lei Jiang, Yu Wang, Xin-hua Zhu, Yan Su","doi":"10.1109/ICSENST.2016.7796252","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796252","url":null,"abstract":"The major challenge of inertial navigation system (INS) is the rapid navigation error drift when aiding sensors are unavailable. However, if the dynamics of land vehicle can be detected, these errors can be corrected or restrained. A method based on support vector machine (SVM) using the outputs of MIMU is proposed here to identify the dynamics of land vehicle. This method computes part of the time-domain features and frequency-domain features. Then, a subset of these features is selected based on wrapper evaluation criteria. Afterwards, SVM is trained based on these selected features. Finally, the trained SVM is used in identification tests. The identification results show that this method can correctly identify the stationary, straight-line and cornering states.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124666718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-11-01DOI: 10.1109/ICSENST.2016.7796274
Xu Jing, Wang Yutian, Zhang Lijuan, Zhao Xu, Wu Xijun, Pan Zhao
Fluorescence technique serves as a soft sensor with the ability to estimate the shape of emission and excitation spectrum and the information of concentrations of each fluorophore in multi-component fluorescent substances. Noise exist in each measurement inevitably. The impact of smoothing on parallel factor model of fluorescence emission excitation matrix is studied by compare nine methods. Smoothing can obtain more smooth resolved spectra, while the advantage of predication concentrations is not so obviously with the methods and processes used in this paper. Other more smoothing methods need to attempt to discover the obvious advantage of predication concentrations.
{"title":"A study of the impact of smoothing on parallel factor model of fluorescence emission excitation matrix","authors":"Xu Jing, Wang Yutian, Zhang Lijuan, Zhao Xu, Wu Xijun, Pan Zhao","doi":"10.1109/ICSENST.2016.7796274","DOIUrl":"https://doi.org/10.1109/ICSENST.2016.7796274","url":null,"abstract":"Fluorescence technique serves as a soft sensor with the ability to estimate the shape of emission and excitation spectrum and the information of concentrations of each fluorophore in multi-component fluorescent substances. Noise exist in each measurement inevitably. The impact of smoothing on parallel factor model of fluorescence emission excitation matrix is studied by compare nine methods. Smoothing can obtain more smooth resolved spectra, while the advantage of predication concentrations is not so obviously with the methods and processes used in this paper. Other more smoothing methods need to attempt to discover the obvious advantage of predication concentrations.","PeriodicalId":297617,"journal":{"name":"2016 10th International Conference on Sensing Technology (ICST)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133764561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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