Search results for: Maximum likelihood detection (MLD).
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3144

Search results for: Maximum likelihood detection (MLD).

384 An Archetype to Sustain Knowledge Management Systems through Intranet

Authors: B. T. Sayed, Nafaâ Jabeur, M. Aref

Abstract:

Creation and maintenance of knowledge management systems has been recognized as an important research area. Consecutively lack of accurate results from knowledge management systems limits the organization to apply their knowledge management processes. This leads to a failure in getting the right information to the right people at the right time thus followed by a deficiency in decision making processes. An Intranet offers a powerful tool for communication and collaboration, presenting data and information, and the means that creates and shares knowledge, all in one easily accessible place. This paper proposes an archetype describing how a knowledge management system, with the support of intranet capabilities, could very much increase the accuracy of capturing, storing and retrieving knowledge based processes thereby increasing the efficiency of the system. This system will expect a critical mass of usage, by the users, for intranet to function as knowledge management systems. This prototype would lead to a design of an application that would impose creation and maintenance of an effective knowledge management system through intranet. The aim of this paper is to introduce an effective system to handle capture, store and distribute knowledge management in a form that may not lead to any failure which exists in most of the systems. The methodology used in the system would require all the employees, in the organization, to contribute the maximum to deliver the system to a successful arena. The system is still in its initial mode and thereby the authors are under the process to practically implement the ideas, as mentioned in the system, to produce satisfactory results.

Keywords: Knowledge Management Systems, Intranet, Methodology.

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383 Leachate Generation from Landfill Lysimeter using Different Types of Soil Cover

Authors: S. Karnchanawong, P. Yongpisalpop

Abstract:

The objectives of this study are to determine the effects of soil cover type on characteristics of leachates generated from landfill lysimeters. Four lysimeters with diameter and height of 0.15 and 3.00 m, respectively, were prepared. Three lysimeters were filled with municipal waste and three different cover soil types i.e. sandy loam soil, silty loam soil and clay soil while another lysimeter was filled solely with municipal waste. The study was conducted in the rainy season. Leachate quantities were measured every day and leachate characteristics were determined once a week. The cumulative leachate quantity from the lysimeter filled solely with municipal waste was found to be around 27% higher than the lysimeters using cover soils. There were no any differences of the cumulative leachate amounts generated from the lysimeters using three types of soils. The comparison of the total mass of pollutants generated from all lysimeters showed that the lysimeter filled solely with municipal waste generated the maximum quantities of pollutants. Among the lysimeters using different types of soils, the lysimeter using sandy loam soil generated the lowest amount of most of pollutants, compared with the lysimeters using silty loam and clay soils. It can be concluded that in term of pollutant attenuation in the leachate, a sandy loam is the most suitable soil to be used as a cover soil in the landfill.

Keywords: cover soil, leachate, sandy loam soil, silty loam soil, clay soil.

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382 Accurate Positioning Method of Indoor Plastering Robot Based on Line Laser

Authors: Guanqiao Wang, Hongyang Yu

Abstract:

There is a lot of repetitive work in the traditional construction industry. These repetitive tasks can significantly improve production efficiency by replacing manual tasks with robots. Therefore, robots appear more and more frequently in the construction industry. Navigation and positioning is a very important task for construction robots, and the requirements for accuracy of positioning are very high. Traditional indoor robots mainly use radio frequency or vision methods for positioning. Compared with ordinary robots, the indoor plastering robot needs to be positioned closer to the wall for wall plastering, so the requirements for construction positioning accuracy are higher, and the traditional navigation positioning method has a large error, which will cause the robot to move. Without the exact position, the wall cannot be plastered or the error of plastering the wall is large. A positioning method is proposed, which is assisted by line lasers and uses image processing-based positioning to perform more accurate positioning on the traditional positioning work. In actual work, filter, edge detection, Hough transform and other operations are performed on the images captured by the camera. Each time the position of the laser line is found, it is compared with the standard value, and the position of the robot is moved or rotated to complete the positioning work. The experimental results show that the actual positioning error is reduced to less than 0.5 mm by this accurate positioning method.

Keywords: Indoor plastering robot, navigation, precise positioning, line laser, image processing.

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381 The Effects of Whole-Body Vibration Training on Jump Performance in Handball Athletes

Authors: Yen-Ting Wang, Shou-Jing Guo, Hsiu-Kuang Chang, Kenny Wen-Chyuan Chen, Alex J.Y. Lee

Abstract:

This study examined the effects of eight weeks of whole-body vibration training (WBVT) on vertical and decuple jump performance in handball athletes. Sixteen collegiate Level I handball athletes volunteered for this study. They were divided equally as control group and experimental group (EG). During the period of the study, all athletes underwent the same handball specific training, but the EG received additional WBVT (amplitude: 2 mm, frequency: 20 - 40 Hz) three time per week for eight consecutive weeks. The vertical jump performance was evaluated according to the maximum height of squat jump (SJ) and countermovement jump (CMJ). Single factor ANCOVA was used to examine the differences in each parameter between the groups after training with the pretest values as a covariate. The statistic significance was set at p < .05. After 8 weeks WBVT, the EG had significantly improved the maximal height of SJ (40.92 ± 2.96 cm vs. 48.40 ± 4.70 cm, F = 5.14, p < .05) and the maximal height CMJ (47.25 ± 7.48 cm vs. 52.20 ± 6.25 cm, F = 5.31, p < .05). 8 weeks of additional WBVT could improve the vertical and decuple jump performance in handball athletes. Enhanced motor unit synchronization and firing rates, facilitated muscular contraction stretch-shortening cycle, and improved lower extremity neuromuscular coordination could account for these enhancements.

Keywords: Muscle strength, explosive power, squat jump, and countermovement jump.

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380 Featured based Segmentation of Color Textured Images using GLCM and Markov Random Field Model

Authors: Dipti Patra, Mridula J

Abstract:

In this paper, we propose a new image segmentation approach for colour textured images. The proposed method for image segmentation consists of two stages. In the first stage, textural features using gray level co-occurrence matrix(GLCM) are computed for regions of interest (ROI) considered for each class. ROI acts as ground truth for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Statistical mean feature at certain inter pixel distance (IPD) of I2 component was considered to be the optimized textural feature for further segmentation. In the second stage, the feature matrix obtained is assumed to be the degraded version of the image labels and modeled as Markov Random Field (MRF) model to model the unknown image labels. The labels are estimated through maximum a posteriori (MAP) estimation criterion using ICM algorithm. The performance of the proposed approach is compared with that of the existing schemes, JSEG and another scheme which uses GLCM and MRF in RGB colour space. The proposed method is found to be outperforming the existing ones in terms of segmentation accuracy with acceptable rate of convergence. The results are validated with synthetic and real textured images.

Keywords: Texture Image Segmentation, Gray Level Cooccurrence Matrix, Markov Random Field Model, Ohta colour space, ICM algorithm.

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379 Assessment of Health and Safety Item on Construction Sites in Ondo State

Authors: Ikumapayi Catherine Mayowa

Abstract:

The well been of human beings on construction site is very important, many man power had been lost through accidents which kills or make workers physically unfit to carry out construction activities, these in turn have multiple effects on the whole economy. Thus it is necessary to put all safety items and regulations in place before construction activities can commence. This study was carried out in Ondo state of Nigeria to known and analyse the state of health and safety of construction workers in the state. The study was done using first hand observation method, 50 construction project sites were visited in 10 major towns of Ondo state, questionnaires were distributed and the results were analysed. The result show that construction workers are being exposed to a lot of construction site hazards due to lack of inadequate safety programmes and nonprovision of appropriate safety materials for workers on site. From the data gotten for each site visited and the statistical analysis, it can be concluded that occurrence of accident on construction sites depends significantly on the available safety facilities on the sites. The result of the regression statistics show that the level of significant of the dependence of occurrence of accident on the availability of safety items on site is 0.0362 which is less than 0.05 maximum significant level required. Therefore a vital way of sustaining our building strategy is by given a detail attention to provision of adequate health and safety items on construction sites which will reduce the occurrence of accident, loss of man power and death of skilled workers among others.

Keywords: Construction sites, health, safety, welfare.

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378 Modelling Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) Outbreak Using Poisson and Negative Binomial Model

Authors: W. Y. Wan Fairos, W. H. Wan Azaki, L. Mohamad Alias, Y. Bee Wah

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Dengue fever has become a major concern for health authorities all over the world particularly in the tropical countries. These countries, in particular are experiencing the most worrying outbreak of dengue fever (DF) and dengue haemorrhagic fever (DHF). The DF and DHF epidemics, thus, have become the main causes of hospital admissions and deaths in Malaysia. This paper, therefore, attempts to examine the environmental factors that may influence the recent dengue outbreak. The aim of this study is twofold, firstly is to establish a statistical model to describe the relationship between the number of dengue cases and a range of explanatory variables and secondly, to identify the lag operator for explanatory variables which affect the dengue incidence the most. The explanatory variables involved include the level of cloud cover, percentage of relative humidity, amount of rainfall, maximum temperature, minimum temperature and wind speed. The Poisson and Negative Binomial regression analyses were used in this study. The results of the analyses on the 915 observations (daily data taken from July 2006 to Dec 2008), reveal that the climatic factors comprising of daily temperature and wind speed were found to significantly influence the incidence of dengue fever after 2 and 3 weeks of their occurrences. The effect of humidity, on the other hand, appears to be significant only after 2 weeks.

Keywords: Dengue Fever, Dengue Hemorrhagic Fever, Negative Binomial Regression model, Poisson Regression model.

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377 Removal of Boron from Waste Waters by Ion- Exchange in a Batch System

Authors: Pelin Demirçivi, Gülhayat Nasün-Saygılı

Abstract:

Boron minerals are very useful for various industrial activities, such as glass industry and detergent industry, due to its mechanical and chemical properties. During the production of boron compounds, many of these are introduced into the environment in the form of waste. Boron is also an important micro nutrient for the plants to vegetate but if it exists in high concentrations, it could have toxic effects. The maximum boron level in drinking water for human health is given as 0.3 mg/L in World Health Organization (WHO) standards. The toxic effects of boron should be noted especially for dry regions, thus, in recent years, increasing attention has been paid to remove the boron from waste waters. In this study, boron removal is implemented by ion exchange process using Amberlite IRA-743 resin. Amberlite IRA-743 resin is a boron specific resin and it belongs to the polymerizate sorbent group within the aminopolyol functional group. Batch studies were performed to investigate the effects of various experimental parameters, such as adsorbent dose, initial concentration and pH, on the removal of boron. It is found that, when the adsorbent dose increases removal of boron from the liquid phase increases. However, an increase in the initial concentration decreases the removal of boron. The effective pH values for removal of boron are determined between 8.5 and 9. Equilibrium isotherms were also analyzed by Langmuir and Freundlich isotherm models. The Langmuir isotherm is obeyed better than the Freundlich isotherm.

Keywords: Amberlite resin, boron removal, ion exchange, isotherm models.

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376 MPPT Operation for PV Grid-connected System using RBFNN and Fuzzy Classification

Authors: A. Chaouachi, R. M. Kamel, K. Nagasaka

Abstract:

This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.

Keywords: MPPT, neuro-fuzzy, RBFN, grid-connected, photovoltaic.

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375 Performance Comparison of Resource Allocation without Feedback in Wireless Body Area Networks by Various Pseudo Orthogonal Sequences

Authors: Ojin Kwon, Yong-Jin Yoon, Liu Xin, Zhang Hongbao

Abstract:

Wireless Body Area Network (WBAN) is a short-range wireless communication around human body for various applications such as wearable devices, entertainment, military, and especially medical devices. WBAN attracts the attention of continuous health monitoring system including diagnostic procedure, early detection of abnormal conditions, and prevention of emergency situations. Compared to cellular network, WBAN system is more difficult to control inter- and inner-cell interference due to the limited power, limited calculation capability, mobility of patient, and non-cooperation among WBANs. In this paper, we compare the performance of resource allocation scheme based on several Pseudo Orthogonal Codewords (POCs) to mitigate inter-WBAN interference. Previously, the POCs are widely exploited for a protocol sequence and optical orthogonal code. Each POCs have different properties of auto- and cross-correlation and spectral efficiency according to its construction of POCs. To identify different WBANs, several different pseudo orthogonal patterns based on POCs exploits for resource allocation of WBANs. By simulating these pseudo orthogonal resource allocations of WBANs on MATLAB, we obtain the performance of WBANs according to different POCs and can analyze and evaluate the suitability of POCs for the resource allocation in the WBANs system.

Keywords: Wireless body area network, body sensor network, resource allocation without feedback, interference mitigation, pseudo orthogonal pattern.

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374 An Investigation on the Accuracy of Nonlinear Static Procedures for Seismic Evaluation of Buckling-restrained Braced Frames

Authors: An Hong Nguyen, Chatpan Chintanapakdee, Toshiro Hayashikawa

Abstract:

Presented herein is an assessment of current nonlinear static procedures (NSPs) for seismic evaluation of bucklingrestrained braced frames (BRBFs) which have become a favorable lateral-force resisting system for earthquake resistant buildings. The bias and accuracy of modal, improved modal pushover analysis (MPA, IMPA) and mass proportional pushover (MPP) procedures are comparatively investigated when they are applied to BRBF buildings subjected to two sets of strong ground motions. The assessment is based on a comparison of seismic displacement demands such as target roof displacements, peak floor/roof displacements and inter-story drifts. The NSP estimates are compared to 'exact' results from nonlinear response history analysis (NLRHA). The response statistics presented show that the MPP procedure tends to significantly overestimate seismic demands of lower stories of tall buildings considered in this study while MPA and IMPA procedures provide reasonably accurate results in estimating maximum inter-story drift over all stories of studied BRBF systems.

Keywords: Buckling-restrained braced frames, nonlinearresponse history analysis, nonlinear static procedure, seismicdemands.

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373 Modeling and Analysis for Effective Capacity of a Cross-Layer Optimized Wireless Networks

Authors: Reham A. El-mayet, Hesham M. El-Badawy, Salwa H. Elramly

Abstract:

New generation mobile communication networks have the ability of supporting triple play. In order that, Orthogonal Frequency Division Multiplexing (OFDM) access techniques have been chosen to enlarge the system ability for high data rates networks. Many of cross-layer modeling and optimization schemes for Quality of Service (QoS) and capacity of downlink multiuser OFDM system were proposed. In this paper, the Maximum Weighted Capacity (MWC) based resource allocation at the Physical (PHY) layer is used. This resource allocation scheme provides a much better QoS than the previous resource allocation schemes, while maintaining the highest or nearly highest capacity and costing similar complexity. In addition, the Delay Satisfaction (DS) scheduling at the Medium Access Control (MAC) layer, which allows more than one connection to be served in each slot is used. This scheduling technique is more efficient than conventional scheduling to investigate both of the number of users as well as the number of subcarriers against system capacity. The system will be optimized for different operational environments: the outdoor deployment scenarios as well as the indoor deployment scenarios are investigated and also for different channel models. In addition, effective capacity approach [1] is used not only for providing QoS for different mobile users, but also to increase the total wireless network's throughput.

Keywords: Cross-layer, effective capacity, LTE, OFDM, QoS, resource allocation, wireless networks.

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372 Robust Face Recognition using AAM and Gabor Features

Authors: Sanghoon Kim, Sun-Tae Chung, Souhwan Jung, Seoungseon Jeon, Jaemin Kim, Seongwon Cho

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In this paper, we propose a face recognition algorithm using AAM and Gabor features. Gabor feature vectors which are well known to be robust with respect to small variations of shape, scaling, rotation, distortion, illumination and poses in images are popularly employed for feature vectors for many object detection and recognition algorithms. EBGM, which is prominent among face recognition algorithms employing Gabor feature vectors, requires localization of facial feature points where Gabor feature vectors are extracted. However, localization method employed in EBGM is based on Gabor jet similarity and is sensitive to initial values. Wrong localization of facial feature points affects face recognition rate. AAM is known to be successfully applied to localization of facial feature points. In this paper, we devise a facial feature point localization method which first roughly estimate facial feature points using AAM and refine facial feature points using Gabor jet similarity-based facial feature localization method with initial points set by the rough facial feature points obtained from AAM, and propose a face recognition algorithm using the devised localization method for facial feature localization and Gabor feature vectors. It is observed through experiments that such a cascaded localization method based on both AAM and Gabor jet similarity is more robust than the localization method based on only Gabor jet similarity. Also, it is shown that the proposed face recognition algorithm using this devised localization method and Gabor feature vectors performs better than the conventional face recognition algorithm using Gabor jet similarity-based localization method and Gabor feature vectors like EBGM.

Keywords: Face Recognition, AAM, Gabor features, EBGM.

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371 Bridge Health Monitoring: A Review

Authors: Mohammad Bakhshandeh

Abstract:

Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: Structural health monitoring, bridge health monitoring, sensor-based methods, machine-learning algorithms, model-based techniques, sensor placement, data acquisition, data analysis.

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370 Utilization of Agro-Industrial Byproducts for Bacteriocin Production Using Newly Isolated Enterococcus faecium BS13

Authors: Vandana Bali, Manab B. Bera, Parmjit S. Panesar

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Microbial production of antimicrobials as biopreservatives is the major area of focus nowadays due to increased interest of consumers towards natural and safe preservation of ready to eat food products. The agro-industrial byproduct based medium and optimized process conditions can contribute in economical production of bacteriocins. Keeping this in view, the present investigation was carried out on agro-industrial byproducts utilization for the production of bacteriocin using Enterococcus faecium BS13 isolated from local fermented food. Different agro-industrial byproduct based carbon sources (whey, potato starch liquor, kinnow peel, deoiledrice bran and molasses), nitrogen sources (soya okra, pea pod and corn steep liquor), metal ions and surfactants were tested for optimal bacteriocin production. The effect of various process parameters such as pH, temperature, inoculum level, agitation and time were also tested on bacteriocin production. The optimized medium containing whey, supplemented with 4%corn steep liquor and polysorbate-80 displayed maximum bacteriocin activity with 2% inoculum, at pH 6.5, temperature 40oC under shaking conditions (100 rpm).

Keywords: Bacteriocin, biopreservation, corn steep liquor, Enterococcus faecium, waste utilization, whey.

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369 Instant Location Detection of Objects Moving at High-Speedin C-OTDR Monitoring Systems

Authors: Andrey V. Timofeev

Abstract:

The practical efficient approach is suggested to estimate the high-speed objects instant bounds in C-OTDR monitoring systems. In case of super-dynamic objects (trains, cars) is difficult to obtain the adequate estimate of the instantaneous object localization because of estimation lag. In other words, reliable estimation coordinates of monitored object requires taking some time for data observation collection by means of C-OTDR system, and only if the required sample volume will be collected the final decision could be issued. But it is contrary to requirements of many real applications. For example, in rail traffic management systems we need to get data of the dynamic objects localization in real time. The way to solve this problem is to use the set of statistical independent parameters of C-OTDR signals for obtaining the most reliable solution in real time. The parameters of this type we can call as «signaling parameters» (SP). There are several the SP’s which carry information about dynamic objects instant localization for each of COTDR channels. The problem is that some of these parameters are very sensitive to dynamics of seismoacoustic emission sources, but are non-stable. On the other hand, in case the SP is very stable it becomes insensitive as rule. This report contains describing of the method for SP’s co-processing which is designed to get the most effective dynamic objects localization estimates in the C-OTDR monitoring system framework.

Keywords: C-OTDR-system, co-processing of signaling parameters, high-speed objects localization, multichannel monitoring systems.

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368 Broadband PowerLine Communications: Performance Analysis

Authors: Justinian Anatory, Nelson Theethayi, M. M. Kissaka, N. H. Mvungi

Abstract:

Power line channel is proposed as an alternative for broadband data transmission especially in developing countries like Tanzania [1]. However the channel is affected by stochastic attenuation and deep notches which can lead to the limitation of channel capacity and achievable data rate. Various studies have characterized the channel without giving exactly the maximum performance and limitation in data transfer rate may be this is due to complexity of channel modeling being used. In this paper the channel performance of medium voltage, low voltage and indoor power line channel is presented. In the investigations orthogonal frequency division multiplexing (OFDM) with phase shift keying (PSK) as carrier modulation schemes is considered, for indoor, medium and low voltage channels with typical ten branches and also Golay coding is applied for medium voltage channel. From channels, frequency response deep notches are observed in various frequencies which can lead to reduce the achievable data rate. However, is observed that data rate up to 240Mbps is realized for a signal to noise ratio of about 50dB for indoor and low voltage channels, however for medium voltage a typical link with ten branches is affected by strong multipath and coding is required for feasible broadband data transfer.

Keywords: Powerline Communications, branched network, channel model, modulation, channel performance, OFDM.

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367 Preliminary Geophysical Assessment of Soil Contaminants around Wacot Rice Factory Argungu, North-Western Nigeria

Authors: A. I. Augie, Y. Alhassan, U. Z. Magawata

Abstract:

Geophysical investigation was carried out at wacot rice factory Argungu north-western Nigeria, using the 2D electrical resistivity method. The area falls between latitude 12˚44′23ʺN to 12˚44′50ʺN and longitude 4032′18′′E to 4032′39′′E covering a total area of about 1.85 km. Two profiles were carried out with Wenner configuration using resistivity meter (Ohmega). The data obtained from the study area were modeled using RES2DIVN software which gave an automatic interpretation of the apparent resistivity data. The inverse resistivity models of the profiles show the high resistivity values ranging from 208 Ωm to 651 Ωm. These high resistivity values in the overburden were due to dryness and compactness of the strata that lead to consolidation, which is an indication that the area is free from leachate contaminations. However, from the inverse model, there are regions of low resistivity values (1 Ωm to 18 Ωm), these zones were observed and identified as clayey and the most contaminated zones. The regions of low resistivity thereby indicated the leachate plume or the highly leachate concentrated zones due to similar resistivity values in both clayey and leachate. The regions of leachate are mainly from the factory into the surrounding area and its groundwater. The maximum leachate infiltration was found at depths 1 m to 15.9 m (P1) and 6 m to 15.9 m (P2) vertically, as well as distance along the profiles from 67 m to 75 m (P1), 155 m to 180 m (P1), and 115 m to 192 m (P2) laterally.

Keywords: Contaminant, leachate, soil, groundwater, 2D, electrical, resistivity, Argungu.

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366 Embedding a Large Amount of Information Using High Secure Neural Based Steganography Algorithm

Authors: Nameer N. EL-Emam

Abstract:

In this paper, we construct and implement a new Steganography algorithm based on learning system to hide a large amount of information into color BMP image. We have used adaptive image filtering and adaptive non-uniform image segmentation with bits replacement on the appropriate pixels. These pixels are selected randomly rather than sequentially by using new concept defined by main cases with sub cases for each byte in one pixel. According to the steps of design, we have been concluded 16 main cases with their sub cases that covere all aspects of the input information into color bitmap image. High security layers have been proposed through four layers of security to make it difficult to break the encryption of the input information and confuse steganalysis too. Learning system has been introduces at the fourth layer of security through neural network. This layer is used to increase the difficulties of the statistical attacks. Our results against statistical and visual attacks are discussed before and after using the learning system and we make comparison with the previous Steganography algorithm. We show that our algorithm can embed efficiently a large amount of information that has been reached to 75% of the image size (replace 18 bits for each pixel as a maximum) with high quality of the output.

Keywords: Adaptive image segmentation, hiding with high capacity, hiding with high security, neural networks, Steganography.

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365 Cross Signal Identification for PSG Applications

Authors: Carmen Grigoraş, Victor Grigoraş, Daniela Boişteanu

Abstract:

The standard investigational method for obstructive sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG), which consists of a simultaneous, usually overnight recording of multiple electro-physiological signals related to sleep and wakefulness. This is an expensive, encumbering and not a readily repeated protocol, and therefore there is need for simpler and easily implemented screening and detection techniques. Identification of apnea/hypopnea events in the screening recordings is the key factor for the diagnosis of OSAS. The analysis of a solely single-lead electrocardiographic (ECG) signal for OSAS diagnosis, which may be done with portable devices, at patient-s home, is the challenge of the last years. A novel artificial neural network (ANN) based approach for feature extraction and automatic identification of respiratory events in ECG signals is presented in this paper. A nonlinear principal component analysis (NLPCA) method was considered for feature extraction and support vector machine for classification/recognition. An alternative representation of the respiratory events by means of Kohonen type neural network is discussed. Our prospective study was based on OSAS patients of the Clinical Hospital of Pneumology from Iaşi, Romania, males and females, as well as on non-OSAS investigated human subjects. Our computed analysis includes a learning phase based on cross signal PSG annotation.

Keywords: Artificial neural networks, feature extraction, obstructive sleep apnea syndrome, pattern recognition, signalprocessing.

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364 Effect of Ambient Oxygen Content and Lifting Frequency on the Participant’s Lifting Capabilities, Muscle Activities, and Perceived Exertion

Authors: Atef M. Ghaleb, Mohamed Z. Ramadan, Khalid Saad Aljaloud

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The aim of this study is to assesses the lifting capabilities of persons experiencing hypoxia. It also examines the behavior of the physiological response induced through the lifting process related to changing in the hypoxia and lifting frequency variables. For this purpose, the study performed two consecutive tests by using; (1) training and acclimatization; and (2) an actual collection of data. A total of 10 male students from King Saud University, Kingdom of Saudi Arabia, were recruited in the study. A two-way repeated measures design, with two independent variables (ambient oxygen (15%, 18% and 21%)) and lifting frequency (1 lift/min and 4 lifts/min) and four dependent variables i.e., maximum acceptable weight of lift (MAWL), Electromyography (EMG) of four muscle groups (anterior deltoid, trapezius, biceps brachii, and erector spinae), rating of perceived exertion (RPE), and rating of oxygen feeling (ROF) were used in this study. The results show that lifting frequency has significantly impacted the MAWL and muscles’ activities. The oxygen content had a significant effect on the RPE and ROE. The study has revealed that acclimatization and training sessions significantly reduce the effect of the hypoxia on the human physiological parameters during the manual materials handling tasks.

Keywords: Lifting capabilities, muscle activities (sEMG), oxygen content, perceived exertion.

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363 Vacuum Membrane Distillation for Desalination of Ground Water by using Flat Sheet Membrane

Authors: Bhausaheb L. Pangarkar, M.G. Sane, Saroj B. Parjane, Mahendra Guddad

Abstract:

The possibility of producing drinking water from brackish ground water using Vacuum membrane distillation (VMD) process was studied. It is a rising technology for seawater or brine desalination process. The process simply consists of a flat sheet hydrophobic micro porous PTFE membrane and diaphragm vacuum pump without a condenser for the water recovery or trap. In this work, VMD performance was investigated for aqueous NaCl solution and natural ground water. The influence of operational parameters such as feed flow rate (30 to 55 l/h), feed temperature (313 to 333 K), feed salt concentration (5000 to 7000 mg/l) and permeate pressure (1.5 to 6 kPa) on the membrane distillation (MD) permeation flux have been investigated. The maximum flux reached to 28.34 kg/m2 h at feed temperature, 333 K; vacuum pressure, 1.5 kPa; feed flow rate, 55 l/h and feed salt concentration, 7000 mg/l. The negligible effects in the reduction of permeate flux found over 150 h experimental run for salt water. But for the natural ground water application over 75 h, scale deposits observed on the membrane surface and 29% reduction in the permeate flux over 75 h. This reduction can be eliminated by acidification of feed water. Hence, promote the research attention in apply of VMD for the ground water purification over today-s conventional RO operation.

Keywords: VMD, hydrophobic PTFE flat membrane, desalination, ground water

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362 Study of Human Upper Arm Girth during Elbow Isokinetic Contractions Based on a Smart Circumferential Measuring System

Authors: Xi Wang, Xiaoming Tao, Raymond C. H. So

Abstract:

As one of the convenient and noninvasive sensing approaches, the automatic limb girth measurement has been applied to detect intention behind human motion from muscle deformation. The sensing validity has been elaborated by preliminary researches but still need more fundamental studies, especially on kinetic contraction modes. Based on the novel fabric strain sensors, a soft and smart limb girth measurement system was developed by the authors’ group, which can measure the limb girth in-motion. Experiments were carried out on elbow isometric flexion and elbow isokinetic flexion (biceps’ isokinetic contractions) of 90°/s, 60°/s, and 120°/s for 10 subjects (2 canoeists and 8 ordinary people). After removal of natural circumferential increments due to elbow position, the joint torque is found not uniformly sensitive to the limb circumferential strains, but declining as elbow joint angle rises, regardless of the angular speed. Moreover, the maximum joint torque was found as an exponential function of the joint’s angular speed. This research highly contributes to the application of the automatic limb girth measuring during kinetic contractions, and it is useful to predict the contraction level of voluntary skeletal muscles.

Keywords: Fabric strain sensor, muscle deformation, isokinetic contraction, joint torque, limb girth strain.

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361 ANN based Multi Classifier System for Prediction of High Energy Shower Primary Energy and Core Location

Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

Abstract:

Cosmic showers, during the transit through space, produce sub - products as a result of interactions with the intergalactic or interstellar medium which after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of High Energy Particle Showers involve a plethora of theoretical and experimental works with a host of constraints resulting in inaccuracies in measurements. Therefore, there exist a necessity to develop a readily available system based on soft-computational approaches which can be used for EAS analysis. This is due to the fact that soft computational tools such as Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making in many situations for which Multiple Classifier System (MCS) are preferred to enhance the ability of the system to make decisions adjusting to finer variations. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) with data inputs from correlation mapping Self Organizing Map (SOM) blocks and the output optimized by another SOM. The results show that the setup can be adopted for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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360 Implementation of a “DIVA“ Concept withspecific Elisa Kits; When Subunit H5 Avian Influenza Vaccine is used

Authors: Robles F, Uribe A, Guadarrama A , Castellanos L, González C.

Abstract:

The main objective of this study was to demonstrate that differentiation of infected and vaccinated animals (DIVA) strategy using different ELISA tests is possible when a subunit vaccine (Haemagglutinin protein) is used to prevent Avian influenza. Special emphasis was placed on the differentiation in the serological response to different components of the AIV (Nucleoprotein, Neuraminidase, Haemagglutinin, Nucleocapsid) between chickens that were vaccinated with a whole virus kill vaccine and recombinant vaccine. Furthermore, the potential use of this DIVA strategy using ELISA assays to detect Neuraminidase 1 (N1) was analyzed as strategy in countries where the field virus is H5N1 and the vaccine used is formulated with H5N2. Detection of AIV-s antibodies to any component in serum was negative for all animals on the study days 0-13. At study day 14 the titers of antibodies against Nucleoprotein (NP) and Nucleocapsid (NC) rose in the experimental groups vaccinated with Volvac® AI KV and were negatives during all the trial in the experimental groups vaccinated with a subunit H5; significant statistically differences were observed between these groups (p < 0.05). The seroconversion either Haemagglutinin or Neuraminidase was evident after 21 days post-vaccination in the experimental groups vaccinated with the respective viral fraction. Regarding the main aim of this study and according with the results that were obtained, use a combination of different ELISA test as a DIVA strategy is feasible when the vaccination is carry out with a subunit H5 vaccine. Also is possible to use the ELISA kit to detect Neuraminidase (either N1 or N2) as a DIVA concept in countries where H5N1 is present and the vaccination programs are done with H5N2 vaccine.

Keywords: Avian Influenza Virus, "DIVA concept", ELISAassay, subunit H5 vaccine.

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359 Finite Element Analysis of Connecting Rod

Authors: Mohammed Mohsin Ali H., Mohamed Haneef

Abstract:

The connecting rod transmits the piston load to the crank causing the latter to turn, thus converting the reciprocating motion of the piston into a rotary motion of the crankshaft. Connecting rods are subjected to forces generated by mass and fuel combustion. This study investigates and compares the fatigue behavior of forged steel, powder forged and ASTM a 514 steel cold quenched connecting rods. The objective is to suggest for a new material with reduced weight and cost with the increased fatigue life. This has entailed performing a detailed load analysis. Therefore, this study has dealt with two subjects: first, dynamic load and stress analysis of the connecting rod, and second, optimization for material, weight and cost. In the first part of the study, the loads acting on the connecting rod as a function of time were obtained. Based on the observations of the dynamic FEA, static FEA, and the load analysis results, the load for the optimization study was selected. It is the conclusion of this study that the connecting rod can be designed and optimized under a load range comprising tensile load and compressive load. Tensile load corresponds to 360o crank angle at the maximum engine speed. The compressive load is corresponding to the peak gas pressure. Furthermore, the existing connecting rod can be replaced with a new connecting rod made of ASTM a 514 steel cold quenched that is 12% lighter and 28% cheaper.

Keywords: Connecting rod, ASTM a514 cold quenched steel, static analysis, fatigue analysis, stress life approach.

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358 Embodiment Design of an Azimuth-Altitude Solar Tracker

Authors: M. Culman, O. Lengerke

Abstract:

To provide an efficient solar generation system, the embodiment design of a two axis solar tracker for an array of photovoltaic (PV) panels destiny to supply the power demand on off-the-grid areas was developed. Photovoltaic cells have high costs in relation to t low efficiency; and while a lot of research and investment has been made to increases its efficiency a few points, there is a profitable solution that increases by 30-40% the annual power production: two axis solar trackers. A solar tracker is a device that supports a load in a perpendicular position toward the sun during daylight. Mounted on solar trackers, the solar panels remain perpendicular to the incoming sunlight at day and seasons so the maximum amount of energy is outputted. Through a preview research done it was justified why the generation of solar energy through photovoltaic panels mounted on dual axis structures is an attractive solution to bring electricity to remote off-the-grid areas. The work results are the embodiment design of an azimuth-altitude solar tracker to guide an array of photovoltaic panels based on a specific design methodology. The designed solar tracker is mounted on a pedestal that uses two slewing drives‚ with a nominal torque of 1950 Nm‚ to move a solar array that provides 3720 W from 12 PV panels.

Keywords: Azimuth-altitude sun tracker, dual-axis solar tracker, photovoltaic system, solar energy, stand-alone power system.

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357 A 10 Giga VPN Accelerator Board for Trust Channel Security System

Authors: Ki Hyun Kim, Jang-Hee Yoo, Kyo Il Chung

Abstract:

This paper proposes a VPN Accelerator Board (VPN-AB), a virtual private network (VPN) protocol designed for trust channel security system (TCSS). TCSS supports safety communication channel between security nodes in internet. It furnishes authentication, confidentiality, integrity, and access control to security node to transmit data packets with IPsec protocol. TCSS consists of internet key exchange block, security association block, and IPsec engine block. The internet key exchange block negotiates crypto algorithm and key used in IPsec engine block. Security Association blocks setting-up and manages security association information. IPsec engine block treats IPsec packets and consists of networking functions for communication. The IPsec engine block should be embodied by H/W and in-line mode transaction for high speed IPsec processing. Our VPN-AB is implemented with high speed security processor that supports many cryptographic algorithms and in-line mode. We evaluate a small TCSS communication environment, and measure a performance of VPN-AB in the environment. The experiment results show that VPN-AB gets a performance throughput of maximum 15.645Gbps when we set the IPsec protocol with 3DES-HMAC-MD5 tunnel mode.

Keywords: TCSS(Trust Channel Security System), VPN(VirtualPrivate Network), IPsec, SSL, Security Processor, Securitycommunication.

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356 Influence of Driving Strategy on Power and Fuel Consumption of Lightweight PEM Fuel Cell Vehicle Powertrain

Authors: Suhadiyana Hanapi, Alhassan Salami Tijani, W. A. N Wan Mohamed

Abstract:

In this paper, a prototype PEM fuel cell vehicle integrated with a 1 kW air-blowing proton exchange membrane fuel cell (PEMFC) stack as a main power sources has been developed for a lightweight cruising vehicle. The test vehicle is equipped with a PEM fuel cell system that provides electric power to a brushed DC motor. This vehicle was designed to compete with industrial lightweight vehicle with the target of consuming least amount of energy and high performance. Individual variations in driving style have a significant impact on vehicle energy efficiency and it is well established from the literature. The primary aim of this study was to assesses the power and fuel consumption of a hydrogen fuel cell vehicle operating at three difference driving technique (i.e. 25 km/h constant speed, 22-28 km/h speed range, 20-30 km/h speed range). The goal is to develop the best driving strategy to maximize performance and minimize fuel consumption for the vehicle system. The relationship between power demand and hydrogen consumption has also been discussed. All the techniques can be evaluated and compared on broadly similar terms. Automatic intelligent controller for driving prototype fuel cell vehicle on different obstacle while maintaining all systems at maximum efficiency was used. The result showed that 25 km/h constant speed was identified for optimal driving with less fuel consumption.

Keywords: Prototype fuel cell electric vehicles, energy efficient, control/driving technique, fuel economy.

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355 Phenolic Compounds and Antimicrobial Properties of Pomegranate (Punica granatum) Peel Extracts

Authors: P. Rahnemoon, M. Sarabi Jamab, M. Javanmard Dakheli, A. Bostan

Abstract:

In recent years, tendency to use of natural antimicrobial agents in food industry has increased. Pomegranate peels containing phenolic compounds and anti-microbial agents, are counted as valuable source for extraction of these compounds. In this study, the extraction of pomegranate peel extract was carried out at different ethanol/water ratios (40:60, 60:40, and 80:20), temperatures (25, 40, and 55 ˚C), and time durations (20, 24, and 28 h). The extraction yield, phenolic compounds, flavonoids, and anthocyanins were measured. ‎Antimicrobial activity of pomegranate peel extracts were determined against some food-borne ‎microorganisms such as Salmonella enteritidis, Escherichia coli, Listeria monocytogenes, ‎‎Staphylococcus aureus, Aspergillus niger, and Saccharomyces cerevisiae by agar diffusion and MIC methods. Results showed that at ethanol/water ratio 60:40, 25 ˚C and 24 h maximum amount of phenolic compounds ‎(‎‎349.518‎‏ ‏mg gallic acid‏/‏g dried extract), ‎flavonoids (250.124 mg rutin‏/‏g dried extract), anthocyanins (252.047 ‎‏‏mg ‎cyanidin‎3‎glucoside‏/‏‎100 g dried extract), and the strongest antimicrobial activity were obtained. ‎All extracts’ antimicrobial activities were demonstrated against every tested ‎‎microorganisms.‎Staphylococcus aureus showed the highest sensitivity among the tested ‎‎‎microorganisms.

Keywords: Antimicrobial agents, phenolic compounds, pomegranate peel, solvent extraction.

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