Search results for: Wireless sensor network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3530

Search results for: Wireless sensor network

2510 Using of Latin Router for Routing Wavelength with Configuration Algorithm

Authors: A. Habiboghli, R. Mostafaei, M. R.Meybodi

Abstract:

Optical network uses a tool for routing which is called Latin router. These routers use particular algorithms for routing. In this paper, we present algorithm for configuration of optical network that is optimized regarding previous algorithm. We show that by decreasing the number of hops for source-destination in lightpath number of satisfied request is less. Also we had shown that more than single-hop lightpath relating single-hop lightpath is better.

Keywords: Latin Router, Constraint Satisfied, Wavelength, Optical Network

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2509 MCDM Spectrum Handover Models for Cognitive Wireless Networks

Authors: Cesar Hernández, Diego Giral, Fernando Santa

Abstract:

Spectrum handover is a significant topic in the cognitive radio networks to assure an efficient data transmission in the cognitive radio user’s communications. This paper proposes a comparison between three spectrum handover models: VIKOR, SAW and MEW. Four evaluation metrics are used. These metrics are, accumulative average of failed handover, accumulative average of handover performed, accumulative average of transmission bandwidth and, accumulative average of the transmission delay. As a difference with related work, the performance of the three spectrum handover models was validated with captured data of spectrum occupancy in experiments performed at the GSM frequency band (824 MHz - 849 MHz). These data represent the actual behavior of the licensed users for this wireless frequency band. The results of the comparison show that VIKOR Algorithm provides a 15.8% performance improvement compared to SAW Algorithm and, it is 12.1% better than the MEW Algorithm.

Keywords: Cognitive radio, decision making, MEW, SAW, spectrum handover, VIKOR.

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2508 Optimizing the Capacity of a Convolutional Neural Network for Image Segmentation and Pattern Recognition

Authors: Yalong Jiang, Zheru Chi

Abstract:

In this paper, we study the factors which determine the capacity of a Convolutional Neural Network (CNN) model and propose the ways to evaluate and adjust the capacity of a CNN model for best matching to a specific pattern recognition task. Firstly, a scheme is proposed to adjust the number of independent functional units within a CNN model to make it be better fitted to a task. Secondly, the number of independent functional units in the capsule network is adjusted to fit it to the training dataset. Thirdly, a method based on Bayesian GAN is proposed to enrich the variances in the current dataset to increase its complexity. Experimental results on the PASCAL VOC 2010 Person Part dataset and the MNIST dataset show that, in both conventional CNN models and capsule networks, the number of independent functional units is an important factor that determines the capacity of a network model. By adjusting the number of functional units, the capacity of a model can better match the complexity of a dataset.

Keywords: CNN, capsule network, capacity optimization, character recognition, data augmentation; semantic segmentation.

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2507 Diffusion Analysis of a Scalable Feistel Network

Authors: Subariah Ibrahim, Mohd Aizaini Maarof

Abstract:

A generalization of the concepts of Feistel Networks (FN), known as Extended Feistel Network (EFN) is examined. EFN splits the input blocks into n > 2 sub-blocks. Like conventional FN, EFN consists of a series of rounds whereby at least one sub-block is subjected to an F function. The function plays a key role in the diffusion process due to its completeness property. It is also important to note that in EFN the F-function is the most computationally expensive operation in a round. The aim of this paper is to determine a suitable type of EFN for a scalable cipher. This is done by analyzing the threshold number of rounds for different types of EFN to achieve the completeness property as well as the number of F-function required in the network. The work focuses on EFN-Type I, Type II and Type III only. In the analysis it is found that EFN-Type II and Type III diffuses at the same rate and both are faster than Type-I EFN. Since EFN-Type-II uses less F functions as compared to EFN-Type III, therefore Type II is the most suitable EFN for use in a scalable cipher.

Keywords: Cryptography, Extended Feistel Network, Diffusion Analysis.

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2506 Enhanced Traffic Light Detection Method Using Geometry Information

Authors: Changhwan Choi, Yongwan Park

Abstract:

In this paper, we propose a method that allows faster and more accurate detection of traffic lights by a vision sensor during driving, DGPS is used to obtain physical location of a traffic light, extract from the image information of the vision sensor only the traffic light area at this location and ascertain if the sign is in operation and determine its form. This method can solve the problem in existing research where low visibility at night or reflection under bright light makes it difficult to recognize the form of traffic light, thus making driving unstable. We compared our success rate of traffic light recognition in day and night road environments. Compared to previous researches, it showed similar performance during the day but 50% improvement at night.

Keywords: Traffic light, Intelligent vehicle, Night, Detection, DGPS (Differential Global Positioning System).

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2505 Tool Tracker: A Toolkit Ensembling Useful Online Networking Tools for Efficient Management and Operation of a Network

Authors: Onkar Bhat Kodical, Sridhar Srinivasan, N.K. Srinath

Abstract:

Tool Tracker is a client-server based application. It is essentially a catalogue of various network monitoring and management tools that are available online. There is a database maintained on the server side that contains the information about various tools. Several clients can access this information simultaneously and utilize this information. The various categories of tools considered are packet sniffers, port mappers, port scanners, encryption tools, and vulnerability scanners etc for the development of this application. This application provides a front end through which the user can invoke any tool from a central repository for the purpose of packet sniffing, port scanning, network analysis etc. Apart from the tool, its description and the help files associated with it would also be stored in the central repository. This facility will enable the user to view the documentation pertaining to the tool without having to download and install the tool. The application would update the central repository with the latest versions of the tools. The application would inform the user about the availability of a newer version of the tool currently being used and give the choice of installing the newer version to the user. Thus ToolTracker provides any network administrator that much needed abstraction and ease-ofuse with respect to the tools that he can use to efficiently monitor a network.

Keywords: Network monitoring, single platform, client/server application, version management.

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2504 A 5-V to 30-V Current-Mode Boost Converter with Integrated Current Sensor and Power-on Protection

Authors: Jun Yu, Yat-Hei Lam, Boris Grinberg, Kevin Chai Tshun Chuan

Abstract:

This paper presents a 5-V to 30-V current-mode boost converter for powering the drive circuit of a micro-electro-mechanical sensor. The design of a transconductance amplifier and an integrated current sensing circuit are presented. In addition, essential building blocks for power-on protection such as a soft-start and clamp block and supply and clock ready block are discussed in details. The chip is fabricated in a 0.18-μm CMOS process. Measurement results show that the soft-start and clamp block can effectively limit the inrush current during startup and protect the boost converter from startup failure.

Keywords: Boost Converter, Current Sensing, Power-on protection, Step-up Converter, Soft-start.

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2503 A Planning Model for Evacuation in Building

Authors: Hsin-Yun Lee, Hao-Hsi Tseng

Abstract:

Previous studies mass evacuation route network does not fully reflect the step-by-step behavior and evacuees make routing decisions. Therefore, they do not work as expected when applied to the evacuation route planning is valid. This article describes where evacuees may have to make a direction to select all areas were identified as guiding points to improve evacuation routes network. This improved route network can be used as a basis for the layout can be used to guide the signs indicate that provides the required evacuation direction. This article also describes that combines simulation and artificial bee colony algorithm to provide the proposed routing solutions, to plan an integrated routing mode. The improved network and the model used is the cinema as a case study to assess the floor. The effectiveness of guidance solution in the total evacuation time is significant by verification.

Keywords: Artificial bee colony, Evacuation, Simulation.

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2502 A Study of Recent Contribution on Simulation Tools for Network-on-Chip

Authors: Muthana Saleh Alalaki, Michael Opoku Agyeman

Abstract:

The growth in the number of Intellectual Properties (IPs) or the number of cores on the same chip becomes a critical issue in System-on-Chip (SoC) due to the intra-communication problem between the chip elements. As a result, Network-on-Chip (NoC) has emerged as a system architecture to overcome intra-communication issues. This paper presents a study of recent contributions on simulation tools for NoC. Furthermore, an overview of NoC is covered as well as a comparison between some NoC simulators to help facilitate research in on-chip communication.

Keywords: Network-on-Chip, System-on-Chip, embedded systems, computer architecture.

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2501 Study on Network-Based Technology for Detecting Potentially Malicious Websites

Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

Abstract:

Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat, Malware, Network Security, Network Packet, Exploit Kits.

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2500 Comparison of Different Neural Network Approaches for the Prediction of Kidney Dysfunction

Authors: Ali Hussian Ali AlTimemy, Fawzi M. Al Naima

Abstract:

This paper presents the prediction of kidney dysfunction using different neural network (NN) approaches. Self organization Maps (SOM), Probabilistic Neural Network (PNN) and Multi Layer Perceptron Neural Network (MLPNN) trained with Back Propagation Algorithm (BPA) are used in this study. Six hundred and sixty three sets of analytical laboratory tests have been collected from one of the private clinical laboratories in Baghdad. For each subject, Serum urea and Serum creatinin levels have been analyzed and tested by using clinical laboratory measurements. The collected urea and cretinine levels are then used as inputs to the three NN models in which the training process is done by different neural approaches. SOM which is a class of unsupervised network whereas PNN and BPNN are considered as class of supervised networks. These networks are used as a classifier to predict whether kidney is normal or it will have a dysfunction. The accuracy of prediction, sensitivity and specificity were found for each type of the proposed networks .We conclude that PNN gives faster and more accurate prediction of kidney dysfunction and it works as promising tool for predicting of routine kidney dysfunction from the clinical laboratory data.

Keywords: Kidney Dysfunction, Prediction, SOM, PNN, BPNN, Urea and Creatinine levels.

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2499 Paradigm of Digital Twin Application in Project Management in Architecture, Engineering and Construction

Authors: Kwok Tak Kit

Abstract:

With the growing trend of adoption of advanced technologies like, building information modeling, artificial intelligence, wireless network, the collaboration and integration of these technologies into digital twin become more prominent in architecture, engineering and construction (AEC) industry in view of the nature and scale of AEC industry which efficiently adopted the digital twin. Digital twin is provided to be effective for AEC professions for design and project management. The digital concept is continuously developing and it is vital for AEC professionals and other stakeholders to understand the digital twin concept and the adoption of various advanced building technologies related to the AEC industry. This paper is to review the application of digital twins application in project management in AEC industry and highlight the challenge of AEC partitioners faced by the revolution of technologies including digital twins and building information modelling (BIM) for further research and future study.

Keywords: Digital Twin, AEC, building information modeling, project management, internet of things.

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2498 BPNN Based Processing for End Effects of HHT

Authors: Chun-Yao Lee, Yao-chen Lee

Abstract:

This paper describes a method of signal process applied on an end effects of Hilbert-Huang transform (HHT) to provide an improvement in the reality of spectrum. The method is based on back-propagation network (BPN). To improve the effect, the end extension of the original signal is obtained by back-propagation network. A full waveform including origin and its extension is decomposed by using empirical mode decomposition (EMD) to obtain intrinsic mode functions (IMFs) of the waveform. Then, the Hilbert transform (HT) is applied to the IMFs to obtain the Hilbert spectrum of the waveform. As a result, the method is superiority of the processing of end effect of HHT to obtain the real frequency spectrum of signals.

Keywords: Neural network, back-propagation network, Hilbert-Huang transform

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2497 Cognitive Radio Spectrum Management

Authors: Swapnil Singhal, Santosh Kumar Singh

Abstract:

The emerging Cognitive Radio is combo of both the technologies i.e. Radio dynamics and software technology. It involve wireless system with efficient coding, designing, and making them artificial intelligent to take the decision according to the surrounding environment and adopt themselves accordingly, so as to deliver the best QoS. This is the breakthrough from fixed hardware and fixed utilization of the spectrum. This software-defined approach of research is centralized at user-definition and application driven model, various software method are used for the optimization of the wireless communication. This paper focused on the Spectrum allocation technique using genetic algorithm GA to evolve radio, represented by chromosomes. The chromosomes gene represents the adjustable parameters in given radio and by using GA, evolving over the generations, the optimized set of parameters are evolved, as per the requirement of user and availability of the spectrum, in our prototype the gene consist of 6 different parameters, and the best set of parameters are evolved according to the application need and availability of the spectrum holes and thus maintaining best QoS for user, simultaneously maintaining licensed user rights. The analyzing tool Matlab is used for the performance of the prototype.

Keywords: ASDR, Cognitive Radio, QoS, Spectrum.

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2496 Prioritizing Service Quality Dimensions:A Neural Network Approach

Authors: A. Golmohammadi, B. Jahandideh

Abstract:

One of the determinants of a firm-s prosperity is the customers- perceived service quality and satisfaction. While service quality is wide in scope, and consists of various dimensions, there may be differences in the relative importance of these dimensions in affecting customers- overall satisfaction of service quality. Identifying the relative rank of different dimensions of service quality is very important in that it can help managers to find out which service dimensions have a greater effect on customers- overall satisfaction. Such an insight will consequently lead to more effective resource allocation which will finally end in higher levels of customer satisfaction. This issue –despite its criticality- has not received enough attention so far. Therefore, using a sample of 240 bank customers in Iran, an artificial neural network is developed to address this gap in the literature. As customers- evaluation of service quality is a subjective process, artificial neural networks –as a brain metaphor- may appear to have a potentiality to model such a complicated process. Proposing a neural network which is able to predict the customers- overall satisfaction of service quality with a promising level of accuracy is the first contribution of this study. In addition, prioritizing the service quality dimensions in affecting customers- overall satisfaction –by using sensitivity analysis of neural network- is the second important finding of this paper.

Keywords: service quality, customer satisfaction, relativeimportance, artificial neural network.

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2495 The Relation between Social Capital and Trust with Social Network Analysis

Authors: Safak Baykal

Abstract:

The purpose of this study is analyzing the relationship between trust and social capital of people with using Social Network Analysis. In this study, two aspects of social capital will be focused: Bonding, homophilous social capital (BoSC), and Bridging, heterophilous social capital (BrSC). These two aspects diverge each other regarding to the social theories. The other concept of the study is Trust (Tr), namely interpersonal trust, willing to ascribe good intentions to and have confidence in the words and actions of other people. In this study, the sample group, 61 people, was selected from a private firm from the defense industry. The relation between BoSC/BrSC and Tr is shown by using Social Network Analysis (SNA) and statistical analysis with Likert type-questionnaire. The results of the analysis show the Cronbach’s alpha value is 0.756 and social capital values (BoSC/BrSC) is not correlated with Tr values of the people.

Keywords: Social capital, interpersonal trust, social network analysis (SNA).

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2494 A New Routing Algorithm: MIRAD

Authors: Amir Gholami Pastaki, Ali Reza Sahab, Seyed Mehdi Sadeghi

Abstract:

LSP routing is among the prominent issues in MPLS networks traffic engineering. The objective of this routing is to increase number of the accepted requests while guaranteeing the quality of service (QoS). Requested bandwidth is the most important QoS criterion that is considered in literatures, and a various number of heuristic algorithms have been presented with that regards. Many of these algorithms prevent flows through bottlenecks of the network in order to perform load balancing, which impedes optimum operation of the network. Here, a modern routing algorithm is proposed as MIRAD: having a little information of the network topology, links residual bandwidth, and any knowledge of the prospective requests it provides every request with a maximum bandwidth as well as minimum end-to-end delay via uniform load distribution across the network. Simulation results of the proposed algorithm show a better efficiency in comparison with similar algorithms.

Keywords: new generation networks, QoS, traffic engineering, MPLS, QoS based routing, LSP

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2493 Determination of Volatile Organic Compounds in Human Breath by Optical Fiber Sensing

Authors: C. I. L. Justino, L. I. B. Silva, K. Duarte, A. C. Freitas, T. A. P. Rocha-Santos, A. C. Duarte

Abstract:

This work proposes an optical fiber system (OF) for sensing various volatile organic compounds (VOCs) in human breath for the diagnosis of some metabolic disorders as a non-invasive methodology. The analyzed VOCs are alkanes (i.e., ethane, pentane, heptane, octane, and decane), and aromatic compounds (i.e., benzene, toluene, and styrene). The OF displays high analytical performance since it provides near real-time responses, rapid analysis, and low instrumentation costs, as well as it exhibits useful linear range and detection limits; the developed OF sensor is also comparable to a reference methodology (gas chromatography-mass spectrometry) for the eight tested VOCs.

Keywords: Breath analysis, gas chromatography-mass spectrometry, optical fiber sensor, volatile organic compounds

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2492 A Quantitative Analysis of GSM Air Interface Based on Radiating Columns and Prediction Model

Authors: K. M. Doraiswamy, Lakshminarayana Merugu, B. C. Jinaga

Abstract:

This paper explains the cause of nonlinearity in floor attenuation hither to left unexplained. The performance degradation occurring in air interface for GSM signals is quantitatively analysed using the concept of Radiating Columns of buildings. The signal levels were measured using Wireless Network Optimising Drive Test Tool (E6474A of Agilent Technologies). The measurements were taken in reflected signal environment under usual fading conditions on actual GSM signals radiated from base stations. A mathematical model is derived from the measurements to predict the GSM signal levels in different floors. It was applied on three buildings and found that the predicted signal levels deviated from the measured levels with in +/- 2 dB for all floors. It is more accurate than the prediction models based on Floor Attenuation Factor. It can be used for planning proper indoor coverage in multi storey buildings.

Keywords: GSM air interface, nonlinear attenuation, multistory building, radiating columns, ground conduction and floor attenuation factor.

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2491 Prediction of Compressive Strength of Self- Compacting Concrete with Fuzzy Logic

Authors: Paratibha Aggarwal, Yogesh Aggarwal

Abstract:

The paper presents the potential of fuzzy logic (FL-I) and neural network techniques (ANN-I) for predicting the compressive strength, for SCC mixtures. Six input parameters that is contents of cement, sand, coarse aggregate, fly ash, superplasticizer percentage and water-to-binder ratio and an output parameter i.e. 28- day compressive strength for ANN-I and FL-I are used for modeling. The fuzzy logic model showed better performance than neural network model.

Keywords: Self compacting concrete, compressive strength, prediction, neural network, Fuzzy logic.

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2490 Quality Properties of Fermented Mugworts and Rapid Pattern Analysis of Their Volatile Flavor Components by Electric Nose Based On SAW (Surface Acoustic Wave) Sensor in GC System

Authors: Hyo-Nam Song

Abstract:

The changes in quality properties and nutritional components in two fermented mugworts (Artemisia capillaries Thumberg, Artemisiaeasiaticae Nakai) were characterized followed by the rapid pattern analysis of volatile flavor compounds by Electric Nose based on SAW(Surface Acoustic Wave) sensor in GC system. There were remarkable decreases in the pH and small changes in the total soluble solids after fermentation. The L (lightness) and b (yellowness) values in Hunter's color system were shown to be decreased, whilst the a (redness) value was increased by fermentation. The HPLC analysis demonstrated that total amino acids were increased in quantity and the essential amino acids were contained higher in A. asiaticaeNakai than in A. capillaries Thumberg. While the total polyphenol contents were not affected by fermentation, the total sugar contents were dramatically decreased. Scopoletinwere highly abundant in A. capillarisThumberg, however, it was not detected in A. asiaticaeNakai. Volatile flavor compounds by Electric Nose showed that the intensity of several peaks were increased much and seven additional flavor peaks were newly produced after fermentation. The flavor differences of two mugworts were clearly distinguished from the image patterns of VaporPrintTM which indicate that the fermentation enables the two mugworts to have subtle flavor differences.

Keywords: Mugwort, Fermentation, Electric Nose, SAW sensor, Flavor.

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2489 Planning the Building Evacuation Routes by a Spatial Network

Authors: Hsin-Yun Lee

Abstract:

The previous proposed evacuation routing approaches usually divide the space into multiple interlinked zones. However, it may be harder to clearly and objectively define the margins of each zone. This paper proposes an approach that connects locations of necessary guidance into a spatial network. In doing so, evacuation routes can be constructed based on the links between starting points, turning nodes, and terminal points. This approach more conforms to the real-life evacuation behavior. The feasibility of the proposed approach is evaluated through a case of one floor in a hospital building. Results indicate that the proposed approach provides valuable suggestions for evacuation planning.

Keywords: Evacuation, spatial network, simulation.

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2488 Two Wheels Balancing Robot with Line Following Capability

Authors: Nor Maniha Abdul Ghani, Faradila Naim, Tan Piow Yon

Abstract:

This project focuses on the development of a line follower algorithm for a Two Wheels Balancing Robot. In this project, ATMEGA32 is chosen as the brain board controller to react towards the data received from Balance Processor Chip on the balance board to monitor the changes of the environment through two infra-red distance sensor to solve the inclination angle problem. Hence, the system will immediately restore to the set point (balance position) through the implementation of internal PID algorithms at the balance board. Application of infra-red light sensors with the PID control is vital, in order to develop a smooth line follower robot. As a result of combination between line follower program and internal self balancing algorithms, we are able to develop a dynamically stabilized balancing robot with line follower function.

Keywords: infra-red sensor, PID algorithms, line followerBalancing robot

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2487 Fiber Braggs Grating Sensor Based Instrumentation to Evaluate Postural Balance and Stability on an Unstable Platform

Authors: Chethana K., Guru Prasad A. S., Vikranth H. N., Varun H., Omkar S. N., Asokan S.

Abstract:

This paper describes a novel application of Fiber Braggs Grating (FBG) sensors in the assessment of human postural stability and balance on an unstable platform. In this work, FBG sensor Stability Analyzing Device (FBGSAD) is developed for measurement of plantar strain to assess the postural stability of subjects on unstable platforms during different stances in eyes open and eyes closed conditions on a rocker board. The studies are validated by comparing the Centre of Gravity (CG) variations measured on the lumbar vertebra of subjects using a commercial accelerometer. The results obtained from the developed FBGSAD depict qualitative similarities with the data recorded by commercial accelerometer. The advantage of the FBGSAD is that it measures simultaneously plantar strain distribution and postural stability of the subject along with its inherent benefits like non-requirement of energizing voltage to the sensor, electromagnetic immunity and simple design which suits its applicability in biomechanical applications. The developed FBGSAD can serve as a tool/yardstick to mitigate space motion sickness, identify individuals who are susceptible to falls and to qualify subjects for balance and stability, which are important factors in the selection of certain unique professionals such as aircraft pilots, astronauts, cosmonauts etc.

Keywords: Biomechanics, Fiber Bragg Gratings, Plantar Strain Measurement, Postural Stability Analysis.

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2486 Innovation and Analysis of Vibrating Fork Level Switch

Authors: Kuen-Ming Shu, Cheng-Yu Chen

Abstract:

A vibrating-fork sensor can measure the level height of solids and liquids and operates according to the principle that vibrations created by piezoelectric ceramics are transmitted to the vibrating fork, which produces resonance. When the vibrating fork touches an object, its resonance frequency changes and produces a signal that returns to a controller for immediate adjustment, so as to effectively monitor raw material loading. The design of the vibrating fork in a vibrating-fork material sensor is crucial. In this paper, ANSYS finite element analysis software is used to perform modal analysis on the vibrations of the vibrating fork. In addition, to design and produce a superior vibrating fork, the dimensions and welding shape of the vibrating fork are compared in a simulation performed using the Taguchi method.

Keywords: Vibrating fork, piezoelectric ceramics, sound wave, ANSYS, Taguchi method, modal analysis.

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2485 X-Ray Intensity Measurement Using Frequency Output Sensor for Computed Tomography

Authors: R. M. Siddiqui, D. Z. Moghaddam, T. R. Turlapati, S. H. Khan, I. Ul Ahad

Abstract:

Quality of 2D and 3D cross-sectional images produce by Computed Tomography primarily depend upon the degree of precision of primary and secondary X-Ray intensity detection. Traditional method of primary intensity detection is apt to errors. Recently the X-Ray intensity measurement system along with smart X-Ray sensors is developed by our group which is able to detect primary X-Ray intensity unerringly. In this study a new smart X-Ray sensor is developed using Light-to-Frequency converter TSL230 from Texas Instruments which has numerous advantages in terms of noiseless data acquisition and transmission. TSL230 construction is based on a silicon photodiode which converts incoming X-Ray radiation into the proportional current signal. A current to frequency converter is attached to this photodiode on a single monolithic CMOS integrated circuit which provides proportional frequency count to incoming current signal in the form of the pulse train. The frequency count is delivered to the center of PICDEM FS USB board with PIC18F4550 microcontroller mounted on it. With highly compact electronic hardware, this Demo Board efficiently read the smart sensor output data. The frequency output approaches overcome nonlinear behavior of sensors with analog output thus un-attenuated X-Ray intensities could be measured precisely and better normalization could be acquired in order to attain high resolution.

Keywords: Computed tomography, detector technology, X-Ray intensity measurement

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2484 Reliable Line-of-Sight and Non-Line-of-Sight Propagation Channel Identification in Ultra-Wideband Wireless Networks

Authors: Mohamed Adnan Landolsi, Ali F. Almutairi

Abstract:

The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultra-wideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response (CIR) using parameters related to the “skewness” of the CIR and its root mean square (RMS) delay spread. A log-normal fit is presented for the probability densities of the CIR parameters. Simulation results show that different environments (residential, office, outdoor, etc.) have measurable differences in their CIR parameters’ statistics, which is then exploited in determining the nature of the propagation channels. Correct LOS/NLOS channel identification rates exceeding 90% are shown to be achievable for most types of environments. Additional improvement is also obtained by combining both CIR skewness and RMS delay statistics.

Keywords: Ultra-wideband, propagation, line-of-sight, non-line-of-sight, identification.

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2483 Software Architecture and Support for Patient Tracking Systems in Critical Scenarios

Authors: Gianluca Cornetta, Abdellah Touhafi, David J. Santos, Jose Manuel Vazquez

Abstract:

In this work a new platform for mobile-health systems is presented. System target application is providing decision support to rescue corps or military medical personnel in combat areas. Software architecture relies on a distributed client-server system that manages a wireless ad-hoc networks hierarchy in which several different types of client operate. Each client is characterized for different hardware and software requirements. Lower hierarchy levels rely in a network of completely custom devices that store clinical information and patient status and are designed to form an ad-hoc network operating in the 2.4 GHz ISM band and complying with the IEEE 802.15.4 standard (ZigBee). Medical personnel may interact with such devices, that are called MICs (Medical Information Carriers), by means of a PDA (Personal Digital Assistant) or a MDA (Medical Digital Assistant), and transmit the information stored in their local databases as well as issue a service request to the upper hierarchy levels by using IEEE 802.11 a/b/g standard (WiFi). The server acts as a repository that stores both medical evacuation forms and associated events (e.g., a teleconsulting request). All the actors participating in the diagnostic or evacuation process may access asynchronously to such repository and update its content or generate new events. The designed system pretends to optimise and improve information spreading and flow among all the system components with the aim of improving both diagnostic quality and evacuation process.

Keywords: IEEE 802.15.4 (ZigBee), IEEE 802.11 a/b/g (WiFi), distributed client-server systems, embedded databases, issue trackers, ad-hoc networks.

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2482 Tool Wear and Surface Roughness Prediction using an Artificial Neural Network (ANN) in Turning Steel under Minimum Quantity Lubrication (MQL)

Authors: S. M. Ali, N. R. Dhar

Abstract:

Tool wear and surface roughness prediction plays a significant role in machining industry for proper planning and control of machining parameters and optimization of cutting conditions. This paper deals with developing an artificial neural network (ANN) model as a function of cutting parameters in turning steel under minimum quantity lubrication (MQL). A feed-forward backpropagation network with twenty five hidden neurons has been selected as the optimum network. The co-efficient of determination (R2) between model predictions and experimental values are 0.9915, 0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra respectively. The results imply that the model can be used easily to forecast tool wear and surface roughness in response to cutting parameters.

Keywords: ANN, MQL, Surface Roughness, Tool Wear.

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2481 Online Pose Estimation and Tracking Approach with Siamese Region Proposal Network

Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

Abstract:

Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: Computer vision, Siamese network, pose estimation, pose tracking.

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