Search results for: monitoring data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7926

Search results for: monitoring data

7656 The Rail Traffic Management with Usage of C-OTDR Monitoring Systems

Authors: Andrey V. Timofeev, Dmitry V. Egorov, Viktor M. Denisov

Abstract:

This paper presents development results of usage of C-OTDR monitoring systems for rail traffic management. The COTDR method is based on vibrosensitive properties of optical fibers. Analysis of Rayleigh backscattering radiation parameters changes which take place due to microscopic seismoacoustic impacts on the optical fiber allows to determine seismoacoustic emission source positions and to identify their types. This approach proved successful for rail traffic management (moving block system, weigh- in-motion system etc.).

Keywords: C-OTDR systems, moving block-sections, rail traffic management, Rayleigh backscattering, weigh-in-motion.

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7655 Soil Moisture Content in Hill-Filed Side Slope

Authors: A. Aboufayed

Abstract:

The soil moisture content is an important property of the soil. The results of mean weekly gravimetric soil moisture content, measured for the three soil layers within the A horizon, showed that it was higher for the top 5 cm over the whole period of monitoring (15/7/2004 up to 10/11/05) with the variation becoming greater during winter time. This reflects the pattern of rainfall in Ireland which is spread over the whole year and shows that light rainfall events during summer time were compensated by loss through evapotranspiration, but only in the top 5 cm of soil. This layer had the highest porosity and highest moisture holding capacity due to the high content of organic matter. The gravimetric soil moisture contents of the top 5 cm and the underlying 5-15 and 15-25 cm layers show that bottom site of the Hill Field had higher soil moisture content than the middle and top sites during the whole period of monitoring.

Keywords: Soil, Soil moisture, Gravimetric soil moisture content.

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7654 Mining Big Data in Telecommunications Industry: Challenges, Techniques, and Revenue Opportunity

Authors: Hoda A. Abdel Hafez

Abstract:

Mining big data represents a big challenge nowadays. Many types of research are concerned with mining massive amounts of data and big data streams. Mining big data faces a lot of challenges including scalability, speed, heterogeneity, accuracy, provenance and privacy. In telecommunication industry, mining big data is like a mining for gold; it represents a big opportunity and maximizing the revenue streams in this industry. This paper discusses the characteristics of big data (volume, variety, velocity and veracity), data mining techniques and tools for handling very large data sets, mining big data in telecommunication and the benefits and opportunities gained from them.

Keywords: Mining Big Data, Big Data, Machine learning, Data Streams, Telecommunication.

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7653 Balanced Scorecard in SMEs – A Proposal for Small Gas Stations in Portugal

Authors: Ana Paula Monte, Christiane Fontenete

Abstract:

As current business environment is demanding a constant adaptation of companies, the planning and strategic management should be an ongoing and natural process in all kind of organizations. The use of management and monitoring strategic performance tools such as the Balanced Scorecard (BSC) have been popular; even to Small and Medium-sized Enterprises. This paper aims to investigate whether the BSC is being used in monitoring the performance of small businesses, particularly in small fuel retailers companies, which are competing in co-branding; and if not, it aims to identify its strategic orientation in order to recommend a possible strategy map for those managers that are willing to adopt this model as an alternative to traditional ones for organizational performance evaluation, which often focus only on evaluation of the organizational financial performance.

Keywords: Balanced Scorecard, Performance Management and Evaluation, SMEs, Strategy Maps

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7652 Adverse Drug Reactions Monitoring in the Northern Region of Zambia

Authors: Ponshano Kaselekela, Simooya O. Oscar, Lunshano Boyd

Abstract:

The Copperbelt University Health Services (CBUHS) was designated by the Zambia Medicines Regulatory Authority (ZAMRA), formally the Pharmaceutical Regulatory Authority (PRA) as a regional pharmacovigilance centre to carryout activities of drug safety monitoring in four provinces in Zambia. CBUHS’s mandate included stimulating the reporting of adverse drug reactions (ADRs), as well as collecting and collating ADR reports from health institutions in the four provinces. This report covers the researchers’ experiences from May 2008 to September, 2016. The main objectives are 1) to monitor ADRs in the Zambian population, 2) to disseminate information to all health professionals in the region advising that the CBU health was a centre for reporting ADRs in the region, 3) to monitor polypharmacy as well as the benefit-risk profile of medicines, 4) to generate independent, evidence based recommendations on the safety of medicines, 5) to support ZAMRA in formulating safety related regulatory decisions for medicines, and 6) to communicate findings with all key stakeholders. The methodology involved monthly visits, beginning in early May 2008 to September, 2016, by the CBUHS to health institutions in the programme areas. Activities included holding discussions with health workers, distribution of ADR forms and collection of ADRs reports. These reports, once collected, were documented and assessed at the CBUHS. A report was then prepared for ZAMRA on quarterly basis. At ZAMRA, serious ADRs were noted and recommendations made to the Ministry of Health of the Republic of Zambia. The results show that 2,600 ADRs reports were received at the pharmacovigilance regional centre. Most of the ADRs reports that received were due to antiretroviral drugs, as well as a few from anti-malarial drugs like Artemether/Lumefantrine – Coartem®. Three hundred and twelve ADRs were entered in the Uppsala Monitoring Centre WHO Vigiflow for further analysis. It was concluded that in general, 2008-16 were exciting years for the pharmacovigilance group at CBUHS. From a very tentative beginning, a lot of strides were made and contacts established with healthcare facilities in the region. The researchers were encouraged by the support received from the Copperbelt University management, the motivation provided by ZAMRA and most importantly the enthusiasm of health workers in all the health care facilities visited. As a centre for drug safety in Zambia, the results show it achieves its objectives for monitoring ADRs, Pharmacovigilance (drug safety monitoring), and activities of monitoring ADRs as well as preventing them. However, the centre faces critical challenges caused by erratic funding that prevents the smooth running of the programme.

Keywords: Assessments, evaluation, monitoring, pharmacovigilance.

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7651 Characterisation and Classification of Natural Transients

Authors: Ernst D. Schmitter

Abstract:

Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automisation of the detection and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for analysis and characterisation of transients and as input into a radial basis function network that is trained to discriminate transients from pulse like to wave like.

Keywords: transient signals, statistics, wavelets, neural networks

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7650 Implementation of a Motion Detection System

Authors: Asif Ansari, T.C.Manjunath, C. Ardil

Abstract:

In today-s competitive environment, the security concerns have grown tremendously. In the modern world, possession is known to be 9/10-ths of the law. Hence, it is imperative for one to be able to safeguard one-s property from worldly harms such as thefts, destruction of property, people with malicious intent etc. Due to the advent of technology in the modern world, the methodologies used by thieves and robbers for stealing have been improving exponentially. Therefore, it is necessary for the surveillance techniques to also improve with the changing world. With the improvement in mass media and various forms of communication, it is now possible to monitor and control the environment to the advantage of the owners of the property. The latest technologies used in the fight against thefts and destruction are the video surveillance and monitoring. By using the technologies, it is possible to monitor and capture every inch and second of the area in interest. However, so far the technologies used are passive in nature, i.e., the monitoring systems only help in detecting the crime but do not actively participate in stopping or curbing the crime while it takes place. Therefore, we have developed a methodology to detect the motion in a video stream environment and this is an idea to ensure that the monitoring systems not only actively participate in stopping the crime, but do so while the crime is taking place. Hence, a system is used to detect any motion in a live streaming video and once motion has been detected in the live stream, the software will activate a warning system and capture the live streaming video.

Keywords: Motion, Detection, System, Video, Crime, Matlab, Surveillance.

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7649 Fault Detection and Diagnosis of Broken Bar Problem in Induction Motors Base Wavelet Analysis and EMD Method: Case Study of Mobarakeh Steel Company in Iran

Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

Abstract:

Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: Broken bar, condition monitoring, diagnostics, empirical mode decomposition, Fourier transform, wavelet transform.

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7648 A Comparison of Signal Processing Techniques for the Extraction of Breathing Rate from the Photoplethysmogram

Authors: Susannah G. Fleming Lionel Tarassenko

Abstract:

The photoplethysmogram (PPG) is the pulsatile waveform produced by the pulse oximeter, which is widely used for monitoring arterial oxygen saturation in patients. Various methods for extracting the breathing rate from the PPG waveform have been compared using a consistent data set, and a novel technique using autoregressive modelling is presented. This novel technique is shown to outperform the existing techniques, with a mean error in breathing rate of 0.04 breaths per minute.

Keywords: Autoregressive modelling, breathing rate, photoplethysmogram, pulse oximetry.

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7647 MIMO Radar-Based System for Structural Health Monitoring and Geophysical Applications

Authors: Davide D’Aria, Paolo Falcone, Luigi Maggi, Aldo Cero, Giovanni Amoroso

Abstract:

The paper presents a methodology for real-time structural health monitoring and geophysical applications. The key elements of the system are a high performance MIMO RADAR sensor, an optical camera and a dedicated set of software algorithms encompassing interferometry, tomography and photogrammetry. The MIMO Radar sensor proposed in this work, provides an extremely high sensitivity to displacements making the system able to react to tiny deformations (up to tens of microns) with a time scale which spans from milliseconds to hours. The MIMO feature of the system makes the system capable of providing a set of two-dimensional images of the observed scene, each mapped on the azimuth-range directions with noticeably resolution in both the dimensions and with an outstanding repetition rate. The back-scattered energy, which is distributed in the 3D space, is projected on a 2D plane, where each pixel has as coordinates the Line-Of-Sight distance and the cross-range azimuthal angle. At the same time, the high performing processing unit allows to sense the observed scene with remarkable refresh periods (up to milliseconds), thus opening the way for combined static and dynamic structural health monitoring. Thanks to the smart TX/RX antenna array layout, the MIMO data can be processed through a tomographic approach to reconstruct the three-dimensional map of the observed scene. This 3D point cloud is then accurately mapped on a 2D digital optical image through photogrammetric techniques, allowing for easy and straightforward interpretations of the measurements. Once the three-dimensional image is reconstructed, a 'repeat-pass' interferometric approach is exploited to provide the user of the system with high frequency three-dimensional motion/vibration estimation of each point of the reconstructed image. At this stage, the methodology leverages consolidated atmospheric correction algorithms to provide reliable displacement and vibration measurements.

Keywords: Interferometry, MIMO RADAR, SAR, tomography.

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7646 Rule Insertion Technique for Dynamic Cell Structure Neural Network

Authors: Osama Elsarrar, Marjorie Darrah, Richard Devin

Abstract:

This paper discusses the idea of capturing an expert’s knowledge in the form of human understandable rules and then inserting these rules into a dynamic cell structure (DCS) neural network. The DCS is a form of self-organizing map that can be used for many purposes, including classification and prediction. This particular neural network is considered to be a topology preserving network that starts with no pre-structure, but assumes a structure once trained. The DCS has been used in mission and safety-critical applications, including adaptive flight control and health-monitoring in aerial vehicles. The approach is to insert expert knowledge into the DCS before training. Rules are translated into a pre-structure and then training data are presented. This idea has been demonstrated using the well-known Iris data set and it has been shown that inserting the pre-structure results in better accuracy with the same training.

Keywords: Neural network, rule extraction, rule insertion, self-organizing map.

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7645 Assessment of Solid Insulating Material Using Partial Discharge Characteristics

Authors: Qasim Khan, Furkan Ahmad, Asfar A. Khan, M. Saad Alam, Faiz Ahmad

Abstract:

In this paper, partial discharge analysis is performed in cavities artificially created in insulation. The setup is according with Cigre-II Method. Circular Samples created from Perspex Sheet with different configuration with changing number of cavities. Assessment of insulation health can be performed by Partial Discharge measurement as this has been found to be important means of condition monitoring. The experiments are done using MPD 540, which is a modern partial discharge measurement system. By analyzing the PD activity obtained for various voids/cavities, it is observed that the PD voltages show variation for cavity’s diameter, depth even for its ratios. This can be employed for scrutiny of insulation system.

Keywords: Partial discharges, condition monitoring, MPD 540, cavities/defects, degradation and corrosion, PMMA.

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7644 Analysis of the Key Indicators of Sustainable Tourism: A Case Study in Lagoa da Confusão, Brazil

Authors: Veruska C. Dutra, Lucio F. M. Adorno, Mary L. G. S. Senna

Abstract:

From the start, the importance of having a plan to sustain tourism was acknowledged. The correct methods to monitor that type of tourism have been researched. Thus, we propose in this work to analyze the applicability of a monitoring and assistance method on the understanding of the tourism sustainability in a small size destiny or getaway. In this study, the subject is Lagoa da Confusão, in the state of Tocantins and the analysis was carried out through the efficiency of the local indicators, according to the WOT approach. We concluded that the sustainable tourism key points that were analyzed demonstrated to be important evaluation and quantification tools for the proposed tasks to be developed in the mentioned destiny. This is a study of an interdisciplinary character and the deductive method was chosen as the guiding line.

Keywords: Indicators, Lagoa da Confusão, Tocantins, Brazil, monitoring, sustainability.

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7643 Using High Performance Computing for Online Flood Monitoring and Prediction

Authors: Stepan Kuchar, Martin Golasowski, Radim Vavrik, Michal Podhoranyi, Boris Sir, Jan Martinovic

Abstract:

The main goal of this article is to describe the online flood monitoring and prediction system Floreon+ primarily developed for the Moravian-Silesian region in the Czech Republic and the basic process it uses for running automatic rainfall-runoff and hydrodynamic simulations along with their calibration and uncertainty modeling. It takes a long time to execute such process sequentially, which is not acceptable in the online scenario, so the use of a high performance computing environment is proposed for all parts of the process to shorten their duration. Finally, a case study on the Ostravice River catchment is presented that shows actual durations and their gain from the parallel implementation.

Keywords: Flood prediction process, High performance computing, Online flood prediction system, Parallelization.

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7642 Entropy based Expeditive Methodology for Rating Curves Assessment

Authors: D. Mirauda, M. Greco, P. Moscarelli

Abstract:

The river flow forecasting represents a crucial point to employ for improving a management policy addressed to the right use of water resources as well as for conjugating prevention and defense actions against environmental degradation. The difficulties occurring during the field activities encourage the development and implementation of operative computation and measuring methods addressed to time reduction for data acquisition and processing maintaining a good level of accuracy. Therefore, the aim of the present work is to test a new entropy based expeditive methodology for the evaluation of the rating curves on three gauged sections with different geometric and morphological characteristics. The methodology requires the choice of only three verticals along the measure section and the sampling of only the maximum velocity. The results underline how in most conditions the rating curves drawn can replace those built with classic methodologies, simplifying thus the procedures of data monitoring and calculation.

Keywords: gauged station, entropic approach, expeditive methodology, rating curves.

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7641 Kalman Filter Design in Structural Identification with Unknown Excitation

Authors: Z. Masoumi, B. Moaveni

Abstract:

This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.

Keywords: Structural health monitoring, Kalman filter, Least square estimation, structural system identification.

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7640 Comparative Analysis of Diverse Collection of Big Data Analytics Tools

Authors: S. Vidhya, S. Sarumathi, N. Shanthi

Abstract:

Over the past era, there have been a lot of efforts and studies are carried out in growing proficient tools for performing various tasks in big data. Recently big data have gotten a lot of publicity for their good reasons. Due to the large and complex collection of datasets it is difficult to process on traditional data processing applications. This concern turns to be further mandatory for producing various tools in big data. Moreover, the main aim of big data analytics is to utilize the advanced analytic techniques besides very huge, different datasets which contain diverse sizes from terabytes to zettabytes and diverse types such as structured or unstructured and batch or streaming. Big data is useful for data sets where their size or type is away from the capability of traditional relational databases for capturing, managing and processing the data with low-latency. Thus the out coming challenges tend to the occurrence of powerful big data tools. In this survey, a various collection of big data tools are illustrated and also compared with the salient features.

Keywords: Big data, Big data analytics, Business analytics, Data analysis, Data visualization, Data discovery.

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7639 The Impact of Fish Cages on Water Quality in One Fish Farm in Croatia

Authors: G. Jelic Mrcelic, M. Sliskovic

Abstract:

In Croatia, the majority of cultured marine fish species are reared in net cages. The intensive production of the fish in net cages may generate the considerable amount of bio waste and change water quality especially in enclosed and semi-enclosed coastal areas. The aim of this paper is to assess the potential impact of sea bass (Dicentrarchus labrax L.) cage farm on water quality. The weak relationship between food supply and water quality parameters (nutrient content and phytoplankton biomass) was found, but significant changes in oxygen saturation was observed in the cages during the warmer period of a year especially in the morning (occasionally it dropped below 70 %). Despite of, satisfactory results of water quality parameters, it is necessary to establish comprehensive monitoring process, especially to include quality assessment of fouling communities.

Keywords: Mariculture, monitoring, fish cages, water quality parameters.

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7638 Towards an Analysis of Rhetoric of Digital Arabic Discourse

Authors: Gameel Abdelmageed

Abstract:

Arabs have a rhetorical heritage which has greatly contributed to the monitoring and analyzing of the rhetoric of the Holy Quran, Hadith, and Arabic texts on poetry and oratory. But Arab scholars - as far as the researcher knows – have not contributed to monitoring and analyzing the rhetoric of digital Arabic discourse although it has prominence, particularly in social media and has strong effectiveness in the political and social life of Arab society. This discourse has made its impact by using very new rhetorical techniques in language, voice, image, painting and video clips which are known as “Multimedia” and belong to “Digital Rhetoric”. This study suggests that it is time to draw the attention of Arab scholars and invite them to monitor and analyze the rhetoric of digital Arabic discourse.

Keywords: Digital discourse, digital rhetoric, social media, Facebook.

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7637 An Improved k Nearest Neighbor Classifier Using Interestingness Measures for Medical Image Mining

Authors: J. Alamelu Mangai, Satej Wagle, V. Santhosh Kumar

Abstract:

The exponential increase in the volume of medical image database has imposed new challenges to clinical routine in maintaining patient history, diagnosis, treatment and monitoring. With the advent of data mining and machine learning techniques it is possible to automate and/or assist physicians in clinical diagnosis. In this research a medical image classification framework using data mining techniques is proposed. It involves feature extraction, feature selection, feature discretization and classification. In the classification phase, the performance of the traditional kNN k nearest neighbor classifier is improved using a feature weighting scheme and a distance weighted voting instead of simple majority voting. Feature weights are calculated using the interestingness measures used in association rule mining. Experiments on the retinal fundus images show that the proposed framework improves the classification accuracy of traditional kNN from 78.57 % to 92.85 %.

Keywords: Medical Image Mining, Data Mining, Feature Weighting, Association Rule Mining, k nearest neighbor classifier.

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7636 Neural Network Monitoring Strategy of Cutting Tool Wear of Horizontal High Speed Milling

Authors: Kious Mecheri, Hadjadj Abdechafik, Ameur Aissa

Abstract:

The wear of cutting tool degrades the quality of the product in the manufacturing processes. The on line monitoring of the cutting tool wear level is very necessary to prevent the deterioration of the quality of machining. Unfortunately there is not a direct manner to measure the cutting tool wear on line. Consequently we must adopt an indirect method where wear will be estimated from the measurement of one or more physical parameters appearing during the machining process such as the cutting force, the vibrations, or the acoustic emission etc…. In this work, a neural network system is elaborated in order to estimate the flank wear from the cutting force measurement and the cutting conditions.

Keywords: Flank wear, cutting forces, high speed milling, signal processing, neural network.

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7635 Online Structural Health Monitoring of Ball Bearings

Authors: Matta S. N. S. Kiran, Manikantadhar Maheswaram, Akshat Upadhyay, Rohit Mishra, Bhagat Singh

Abstract:

A bearing is a very common and useful component of mechanical systems in order to transfer power from one end to another. Therefore, to ensure the accountability and robustness of the rotating mechanical systems, the bearing part's health condition must be checked at regular intervals, also known as preventive maintenance. This condition may lead to unnecessary higher maintenance costs and later result in higher production costs. These costs can be minimized by diagnosing the faulty bearing in its incipient stage. This paper describes an approach to detect rolling bearing defects based on Empirical Mode Decomposition. The novelty of the proposed methodology is validated experimentally using Case Western Reserve University bearing's data sets. The selected data sets comprise the two vibration signals, i.e., inner race and outer, for healthy and faulty conditions.

Keywords: Ball bearing, denoising, signal processing, statistical indicators.

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7634 Multi-labeled Data Expressed by a Set of Labels

Authors: Tetsuya Furukawa, Masahiro Kuzunishi

Abstract:

Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders.

Keywords: Classification Hierarchies, Multi-labeled Data, Multiple Classificaiton, Orders of Sets of Labels

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7633 Real Time Multi-Sensory Force Sensing Mat for Sports Biomechanics and Human Gait Analysis

Authors: D. Gouwanda, S. M. N. A. Senanayake

Abstract:

This paper presents a real time force sensing instrument that is designed for human gait analysis purposes. It is capable of recording and monitoring ground reaction forces exerted by human foot during various activities such as walking, running and jumping in real time. In overall, force sensing mat mainly consists of three elements: the force sensing mat, signal conditioning circuit and data acquisition device. Force sensing mat is the mat that contains an array of force sensing elements. To control and process the incoming signal from the force sensing mat, Force-Logger and Force-Reloader are developed using National Instrument Labview. This paper describes the architecture of the force sensing mat, signal conditioning circuit and the real time streaming of the incoming data from the force sensing mat. Additionally, a preliminary experiment dataset is presented in this paper.

Keywords: Force platform, force sensing resistor, human gait analysis.

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7632 Eye Location Based on Structure Feature for Driver Fatigue Monitoring

Authors: Qiong Wang

Abstract:

One of the most important problems to solve is eye location for a driver fatigue monitoring system. This paper presents an efficient method to achieve fast and accurate eye location in grey level images obtained in the real-word driving conditions. The structure of eye region is used as a robust cue to find possible eye pairs. Candidates of eye pair at different scales are selected by finding regions which roughly match with the binary eye pair template. To obtain real one, all the eye pair candidates are then verified by using support vector machines. Finally, eyes are precisely located by using binary vertical projection and eye classifier in eye pair images. The proposed method is robust to deal with illumination changes, moderate rotations, glasses wearing and different eye states. Experimental results demonstrate its effectiveness.

Keywords: eye location, structure feature, driver fatiguemonitoring

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7631 Designing Transcutaneous Inductive Powering Links for Implanted Micro-System Device

Authors: Saad Mutashar Abbas, M. A. Hannan, S. A. Samad, A. Hussain

Abstract:

This paper presented a proposed design for transcutaneous inductive powering links. The design used to transfer power and data to the implanted devices such as implanted Microsystems to stimulate and monitoring the nerves and muscles. The system operated with low band frequency 13.56 MHZ according to industrial- scientific – medical (ISM) band to avoid the tissue heating. For external part, the modulation index is 13 % and the modulation rate 7.3% with data rate 1 Mbit/s assuming Tbit=1us. The system has been designed using 0.35-μm fabricated CMOS technology. The mathematical model is given and the design is simulated using OrCAD P Spice 16.2 software tool and for real-time simulation the electronic workbench MULISIM 11 has been used. The novel circular plane (pancake) coils was simulated using ANSOFT- HFss software.

Keywords: Implanted devices, ASK techniques, Class-E power amplifier, Inductive powering and low-frequency ISM band.

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7630 A Simple User Administration View of Computing Clusters

Authors: Valeria M. Bastos, Myrian A. Costa, Matheus Ambrozio, Nelson F. F. Ebecken

Abstract:

In this paper a very simple and effective user administration view of computing clusters systems is implemented in order of friendly provide the configuration and monitoring of distributed application executions. The user view, the administrator view, and an internal control module create an illusionary management environment for better system usability. The architecture, properties, performance, and the comparison with others software for cluster management are briefly commented.

Keywords: Big data, computing clusters, administration view, user view.

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7629 Chemical Species Concentration Measurement via Wireless Sensors

Authors: Jer Hayes, Stephen Beirne, Breda M. Kiernan, Conor Slater, King-Tong Lau, Dermot Diamond

Abstract:

This paper describes studies carried out to investigate the viability of using wireless cameras as a tool in monitoring changes in air quality. A camera is used to monitor the change in colour of a chemically responsive polymer within view of the camera as it is exposed to varying chemical species concentration levels. The camera captures this image and the colour change is analyzed by averaging the RGB values present. This novel chemical sensing approach is compared with an established chemical sensing method using the same chemically responsive polymer coated onto LEDs. In this way, the concentration levels of acetic acid in the air can be tracked using both approaches. These approaches to chemical plume tracking have many applications for air quality monitoring.

Keywords: Environmental sensing, chemical sensors, wirelesssensor networks.

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7628 Context Aware Lightweight Energy Efficient Framework

Authors: D. Sathan, A. Meetoo, R. K. Subramaniam

Abstract:

Context awareness is a capability whereby mobile computing devices can sense their physical environment and adapt their behavior accordingly. The term context-awareness, in ubiquitous computing, was introduced by Schilit in 1994 and has become one of the most exciting concepts in early 21st-century computing, fueled by recent developments in pervasive computing (i.e. mobile and ubiquitous computing). These include computing devices worn by users, embedded devices, smart appliances, sensors surrounding users and a variety of wireless networking technologies. Context-aware applications use context information to adapt interfaces, tailor the set of application-relevant data, increase the precision of information retrieval, discover services, make the user interaction implicit, or build smart environments. For example: A context aware mobile phone will know that the user is currently in a meeting room, and reject any unimportant calls. One of the major challenges in providing users with context-aware services lies in continuously monitoring their contexts based on numerous sensors connected to the context aware system through wireless communication. A number of context aware frameworks based on sensors have been proposed, but many of them have neglected the fact that monitoring with sensors imposes heavy workloads on ubiquitous devices with limited computing power and battery. In this paper, we present CALEEF, a lightweight and energy efficient context aware framework for resource limited ubiquitous devices.

Keywords: Context-Aware, Energy-Efficient, Lightweight, Ubiquitous Devices.

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7627 Self-Sensing Concrete Nanocomposites for Smart Structures

Authors: A. D'Alessandro, F. Ubertini, A. L. Materazzi

Abstract:

In the field of civil engineering, Structural Health Monitoring is a topic of growing interest. Effective monitoring instruments permit the control of the working conditions of structures and infrastructures, through the identification of behavioral anomalies due to incipient damages, especially in areas of high environmental hazards as earthquakes. While traditional sensors can be applied only in a limited number of points, providing a partial information for a structural diagnosis, novel transducers may allow a diffuse sensing. Thanks to the new tools and materials provided by nanotechnology, new types of multifunctional sensors are developing in the scientific panorama. In particular, cement-matrix composite materials capable of diagnosing their own state of strain and tension, could be originated by the addition of specific conductive nanofillers. Because of the nature of the material they are made of, these new cementitious nano-modified transducers can be inserted within the concrete elements, transforming the same structures in sets of widespread sensors. This paper is aimed at presenting the results of a research about a new self-sensing nanocomposite and about the implementation of smart sensors for Structural Health Monitoring. The developed nanocomposite has been obtained by inserting multi walled carbon nanotubes within a cementitious matrix. The insertion of such conductive carbon nanofillers provides the base material with piezoresistive characteristics and peculiar sensitivity to mechanical modifications. The self-sensing ability is achieved by correlating the variation of the external stress or strain with the variation of some electrical properties, such as the electrical resistance or conductivity. Through the measurement of such electrical characteristics, the performance and the working conditions of an element or a structure can be monitored. Among conductive carbon nanofillers, carbon nanotubes seem to be particularly promising for the realization of self-sensing cement-matrix materials. Some issues related to the nanofiller dispersion or to the influence of the nano-inclusions amount in the cement matrix need to be carefully investigated: the strain sensitivity of the resulting sensors is influenced by such factors. This work analyzes the dispersion of the carbon nanofillers, the physical properties of the fresh dough, the electrical properties of the hardened composites and the sensing properties of the realized sensors. The experimental campaign focuses specifically on their dynamic characterization and their applicability to the monitoring of full-scale elements. The results of the electromechanical tests with both slow varying and dynamic loads show that the developed nanocomposite sensors can be effectively used for the health monitoring of structures.

Keywords: Carbon nanotubes, self-sensing nanocomposites, smart cement-matrix sensors, structural health monitoring.

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