Search results for: body area network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16375

Search results for: body area network

14455 Simulation of Nonlinear Behavior of Reinforced Concrete Slabs Using Rigid Body-Spring Discrete Element Method

Authors: Felix Jr. Garde, Eric Augustus Tingatinga

Abstract:

Most analysis procedures of reinforced concrete (RC) slabs are based on elastic theory. When subjected to large forces, however, slabs deform beyond elastic range and the study of their behavior and performance require nonlinear analysis. This paper presents a numerical model to simulate nonlinear behavior of RC slabs using rigid body-spring discrete element method. The proposed slab model composed of rigid plate elements and nonlinear springs is based on the yield line theory which assumes that the nonlinear behavior of the RC slab subjected to transverse loads is contained in plastic or yield-lines. In this model, the displacement of the slab is completely described by the rigid elements and the deformation energy is concentrated in the flexural springs uniformly distributed at the potential yield lines. The spring parameters are determined from comparison of transverse displacements and stresses developed in the slab obtained using FEM and the proposed model with assumed homogeneous material. Numerical models of typical RC slabs with varying geometry, reinforcement, support conditions, and loading conditions, show reasonable agreement with available experimental data. The model was also shown to be useful in investigating dynamic behavior of slabs.

Keywords: RC slab, nonlinear behavior, yield line theory, rigid body-spring discrete element method

Procedia PDF Downloads 319
14454 Enhanced Cluster Based Connectivity Maintenance in Vehicular Ad Hoc Network

Authors: Manverpreet Kaur, Amarpreet Singh

Abstract:

The demand of Vehicular ad hoc networks is increasing day by day, due to offering the various applications and marvelous benefits to VANET users. Clustering in VANETs is most important to overcome the connectivity problems of VANETs. In this paper, we proposed a new clustering technique Enhanced cluster based connectivity maintenance in vehicular ad hoc network. Our objective is to form long living clusters. The proposed approach is grouping the vehicles, on the basis of the longest list of neighbors to form clusters. The cluster formation and cluster head selection process done by the RSU that may results it reduces the chances of overhead on to the network. The cluster head selection procedure is the vehicle which has closest speed to average speed will elect as a cluster Head by the RSU and if two vehicles have same speed which is closest to average speed then they will be calculate by one of the new parameter i.e. distance to their respective destination. The vehicle which has largest distance to their destination will be choosing as a cluster Head by the RSU. Our simulation outcomes show that our technique performs better than the existing technique.

Keywords: VANETs, clustering, connectivity, cluster head, intelligent transportation system (ITS)

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14453 Optimal Number and Placement of Vertical Links in 3D Network-On-Chip

Authors: Nesrine Toubaline, Djamel Bennouar, Ali Mahdoum

Abstract:

3D technology can lead to a significant reduction in power and average hop-count in Networks on Chip (NoCs). It offers short and fast vertical links which copes with the long wire problem in 2D NoCs. This work proposes heuristic-based method to optimize number and placement of vertical links to achieve specified performance goals. Experiments show that significant improvement can be achieved by using a specific number of vertical interconnect.

Keywords: interconnect optimization, monolithic inter-tier vias, network on chip, system on chip, through silicon vias, three dimensional integration circuits

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14452 Photo-Fenton Decolorization of Methylene Blue Adsolubilized on Co2+ -Embedded Alumina Surface: Comparison of Process Modeling through Response Surface Methodology and Artificial Neural Network

Authors: Prateeksha Mahamallik, Anjali Pal

Abstract:

In the present study, Co(II)-adsolubilized surfactant modified alumina (SMA) was prepared, and methylene blue (MB) degradation was carried out on Co-SMA surface by visible light photo-Fenton process. The entire reaction proceeded on solid surface as MB was embedded on Co-SMA surface. The reaction followed zero order kinetics. Response surface methodology (RSM) and artificial neural network (ANN) were used for modeling the decolorization of MB by photo-Fenton process as a function of dose of Co-SMA (10, 20 and 30 g/L), initial concentration of MB (10, 20 and 30 mg/L), concentration of H2O2 (174.4, 348.8 and 523.2 mM) and reaction time (30, 45 and 60 min). The prediction capabilities of both the methodologies (RSM and ANN) were compared on the basis of correlation coefficient (R2), root mean square error (RMSE), standard error of prediction (SEP), relative percent deviation (RPD). Due to lower value of RMSE (1.27), SEP (2.06) and RPD (1.17) and higher value of R2 (0.9966), ANN was proved to be more accurate than RSM in order to predict decolorization efficiency.

Keywords: adsolubilization, artificial neural network, methylene blue, photo-fenton process, response surface methodology

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14451 Human Motion Capture: New Innovations in the Field of Computer Vision

Authors: Najm Alotaibi

Abstract:

Human motion capture has become one of the major area of interest in the field of computer vision. Some of the major application areas that have been rapidly evolving include the advanced human interfaces, virtual reality and security/surveillance systems. This study provides a brief overview of the techniques and applications used for the markerless human motion capture, which deals with analyzing the human motion in the form of mathematical formulations. The major contribution of this research is that it classifies the computer vision based techniques of human motion capture based on the taxonomy, and then breaks its down into four systematically different categories of tracking, initialization, pose estimation and recognition. The detailed descriptions and the relationships descriptions are given for the techniques of tracking and pose estimation. The subcategories of each process are further described. Various hypotheses have been used by the researchers in this domain are surveyed and the evolution of these techniques have been explained. It has been concluded in the survey that most researchers have focused on using the mathematical body models for the markerless motion capture.

Keywords: human motion capture, computer vision, vision-based, tracking

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14450 Sunflower Oil as a Nutritional Strategy to Reduce the Impacts of Heat Stress on Meat Quality and Dirtiness Pigs Score

Authors: Angela Cristina Da F. De Oliveira, Salma E. Asmar, Norbert P. Battlori, Yaz Vera, Uriel R. Valencia, Tâmara D. Borges, Antoni D. Bueno, Leandro B. Costa

Abstract:

The present study aimed to evaluate the replacement of 5% of starch per 5% of sunflower oil (SO) on meat quality and animal welfare of growing and finishing pigs (Iberic x Duroc), exposed to a heat stress environment. The experiment lasted 90 days, and it was carried out in a randomized block design, in a 2 x 2 factorial, composed of two diets (starch or sunflower oil (with or without) and two feed intake management (ad libitum and restriction). Seventy-two crossbred males (51± 6,29 kg body weight - BW) were housed in climate-controlled rooms, in collective pens and exposed to heat stress environment (32°C; 35% to 50% humidity). The treatments studies were: 1) control diet (5% starch x 0% SO) with ad libitum intake (n = 18); 2) SO diet (replacement of 5% of starch per 5% of SO) with ad libitum intake (n = 18); 3) control diet with restriction feed intake (n = 18); or 4) SO diet with restriction feed intake (n = 18). Feed were provided in two phases, 50-100 Kg BW for growing and 100-140 Kg BW for finishing, respectively. Within welfare evaluations, dirtiness score was evaluated all morning during ninety days of the experiment. The presence of manure was individually measured based on one side of the pig´s body and scored according to: 0 (less than 20% of the body surface); 1 (more than 20% but less than 50% of the body surface); 2 (over 50% of the body surface). After the experimental period, when animals reach 130-140 kg BW, they were slaughtered using carbon dioxide (CO2) stunning. Carcass weight, leanness and fat content, measured at the last rib, were recorded within 20 min post-mortem (PM). At 24h PM, pH, electrical conductivity and color measures (L, a*, b*) were recorded in the Longissimus thoracis and Semimembranosus muscles. Data shown no interaction between diet (control x SO) and management feed intake (ad libitum x restriction) on the meat quality parameters. Animals in ad libitum management presented an increase (p < 0.05) on BW, carcass weight (CW), back fat thickness (BT), and intramuscular fat content (IM) when compared with animals in restriction management. In contrast, animals in restriction management showing a higher (p < 0.05) carcass yield, percentage of lean and loin thickness. To welfare evaluations, the interaction between diet and management feed intake did not influence the degree of dirtiness. Although, the animals that received SO diet, independently of the management, were cleaner than animals in control group (p < 0,05), which, for pigs, demonstrate an important strategy to reduce body temperature. Based in our results, the diet and management feed intake had a significant influence on meat quality and animal welfare being considered efficient nutritional strategies to reduce heat stress and improved meat quality.

Keywords: dirtiness, environment, meat, pig

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14449 Evaluation and Proposal for Improvement of the Flow Measurement Equipment in the Bellavista Drinking Water System of the City of Azogues

Authors: David Quevedo, Diana Coronel

Abstract:

The present article carries out an evaluation of the drinking water system in the Bellavista sector of the city of Azogues, with the purpose of determining the appropriate equipment to record the actual consumption flows of the inhabitants in said sector. Taking into account that the study area is located in a rural and economically disadvantaged area, there is an urgent need to establish a control system for the consumption of drinking water in order to conserve and manage the vital resource in the best possible way, considering that the water source supplying this sector is approximately 9km away. The research began with the collection of cartographic, demographic, and statistical data of the sector, determining the coverage area, population projection, and a provision that guarantees the supply of drinking water to meet the water needs of the sector's inhabitants. By using hydraulic modeling through the United States Environmental Protection Agency Application for Modeling Drinking Water Distribution Systems EPANET 2.0 software, theoretical hydraulic data were obtained, which were used to design and justify the most suitable measuring equipment for the Bellavista drinking water system. Taking into account a minimum service life of the drinking water system of 30 years, future flow rates were calculated for the design of the macro-measuring device. After analyzing the network, it was evident that the Bellavista sector has an average consumption of 102.87 liters per person per day, but considering that Ecuadorian regulations recommend a provision of 180 liters per person per day for the geographical conditions of the sector, this value was used for the analysis. With all the collected and calculated information, the conclusion was reached that the Bellavista drinking water system needs to have a 125mm electromagnetic macro-measuring device for the first three quinquenniums of its service life and a 150mm diameter device for the following three quinquenniums. The importance of having equipment that provides real and reliable data will allow for the control of water consumption by the population of the sector, measured through micro-measuring devices installed at the entrance of each household, which should match the readings of the macro-measuring device placed after the water storage tank outlet, in order to control losses that may occur due to leaks in the drinking water system or illegal connections.

Keywords: macrometer, hydraulics, endowment, water

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14448 Design and Development of an 'Optimisation Controller' and a SCADA Based Monitoring System for Renewable Energy Management in Telecom Towers

Authors: M. Sundaram, H. R. Sanath Kumar, A. Ramprakash

Abstract:

Energy saving is a key sustainability focus area for the Indian telecom industry today. This is especially true in rural India where energy consumption contributes to 70 % of the total network operating cost. In urban areas, the energy cost for network operation ranges between 15-30 %. This expenditure on energy as a result of the lack of grid power availability highlights a potential barrier to telecom industry growth. As a result of this, telecom tower companies switch to diesel generators, making them the second largest consumer of diesel in India, consuming over 2.5 billion litres per annum. The growing cost of energy due to increasing diesel prices and concerns over rising greenhouse emissions have caused these companies to look at other renewable energy options. Even the TRAI (Telecom Regulation Authority of India) has issued a number of guidelines to implement Renewable Energy Technologies (RETs) in the telecom towers as part of its ‘Implementation of Green Technologies in Telecom Sector’ initiative. Our proposal suggests the implementation of a Programmable Logic Controller (PLC) based ‘optimisation controller’ that can not only efficiently utilize the energy from RETs but also help to conserve the power used in the telecom towers. When there are multiple RETs available to supply energy, this controller will pick the optimum amount of energy from each RET based on the availability and feasibility at that point of time, reducing the dependence on diesel generators. For effective maintenance of the towers, we are planing to implement a SCADA based monitoring system along with the ‘optimization controller’.

Keywords: operation costs, consumption of fuel and carbon footprint, implementation of a programmable logic controller (PLC) based ‘optimisation controller’, efficient SCADA based monitoring system

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14447 Classifying Turbomachinery Blade Mode Shapes Using Artificial Neural Networks

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

Abstract:

Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

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14446 Effect of Diazepam on Internal Organs of Chrysomya megacephala Using Micro-Computed Tomograph

Authors: Sangkhao M., Butcher B. A.

Abstract:

Diazepam (known as valium) is a medication for calming effect. Many reports on committed suicide cases shown that diazepam is frequently used for this purpose. This research aims to study effect of diazepam on the development of forensically important blowflies, Chrysomya megacephala (Diptera: Calliphoridae) using micro-computed tomography (micro CT). In this study, four rabbits were treated with three different lethal doses of diazepam and one control (LD₀, LD₅₀, LD₁₀₀ and LC). The rabbit’s livers were removed for rearing the blowflies. Pupae were sampled for two series (ages; S1: 24h and S2: 120h) of development. After preparing the specimens, all samples were performed Micro CT using Skyscan 1172. The results shown the effect of diazepam on internal organs and tissues such as brain, cavity of the body, gas bubble, meconium and especially fat body. In the control group, in series 1 (LCS1), fat body was equally dispersed in the head, thorax, and abdomen, development of internal organs were not completed, however, brain, thoracic muscle, wings, legs and rectum were able to observe at 24h after developing into the pupal stage. Development of each organ in the control group in the series two was completed. In the treatment groups, LD₀, LD₅₀, LD₁₀₀ (Series 1 and Series 2), tissues are different, such as gas bubble in LD₀S1, was observed due to rapidity morphological changes during the metamorphosis of blowfly’s pupa in this treatment. Meconium was observed in LD₅₀S2 group because excretion of metabolic waste was not completed. All of the samples in the treatment groups had differentiation of fat bodies because metabolic activities were not completed and these changes affected on functions of every internal system. Discovering of differentiated fat bodies are important results because fat bodies of insect functions as liver in human, therefore it is shown that toxin eliminates from blowfly’s body and homeostatic maintenance of the hemolymph proteins, lipid and carbohydrates in each treatment group are abnormal.

Keywords: forensic toxicology, forensic entomology, diptera, diazepam

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14445 Black Bodies Matter: The Contemporary Manifestation of Saartjie Baartman

Authors: Rokeshia Renné Ashley

Abstract:

The purpose of this study is to understand the perception of historical figure Saartjie 'Sara/Sarah' Baartman from a cross cultural perspective of black women in the United States and black women in South Africa. Semi-structured interviews (n = 30) uncover that many women in both countries did not have an accurate representation, recollection, or have been exposed to the story of Baartman. Nonetheless, those who were familiar with Baartman’s story, those participants compared her to modern examples of black women who are showcased in a contemporary familiarity. The women are described by participants as women who reveal their bodies in a sexualized manner and have the curves that are similar to Baartman’s historic figure. This comparison emphasized a connection to popular images of black women who represent the curvaceous ideal. Findings contribute to social comparison theory by providing a lens for examining black women’s body image.

Keywords: black women, body modification, media, South Africa

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14444 Micromechanics Modeling of 3D Network Smart Orthotropic Structures

Authors: E. M. Hassan, A. L. Kalamkarov

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Two micromechanical models for 3D smart composite with embedded periodic or nearly periodic network of generally orthotropic reinforcements and actuators are developed and applied to cubic structures with unidirectional orientation of constituents. Analytical formulas for the effective piezothermoelastic coefficients are derived using the Asymptotic Homogenization Method (AHM). Finite Element Analysis (FEA) is subsequently developed and used to examine the aforementioned periodic 3D network reinforced smart structures. The deformation responses from the FE simulations are used to extract effective coefficients. The results from both techniques are compared. This work considers piezoelectric materials that respond linearly to changes in electric field, electric displacement, mechanical stress and strain and thermal effects. This combination of electric fields and thermo-mechanical response in smart composite structures is characterized by piezoelectric and thermal expansion coefficients. The problem is represented by unit-cell and the models are developed using the AHM and the FEA to determine the effective piezoelectric and thermal expansion coefficients. Each unit cell contains a number of orthotropic inclusions in the form of structural reinforcements and actuators. Using matrix representation of the coupled response of the unit cell, the effective piezoelectric and thermal expansion coefficients are calculated and compared with results of the asymptotic homogenization method. A very good agreement is shown between these two approaches.

Keywords: asymptotic homogenization method, finite element analysis, effective piezothermoelastic coefficients, 3D smart network composite structures

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14443 Management of Autoimmune Diseases with Ayurveda

Authors: Simmi Chopra

Abstract:

In the last few years, there has been a surge of Autoimmune diseases that have become more like an epidemic all over the world. The reasons vary from stress, insufficient sleep, smoking, genetics, environmental pollution, adulterated foods, and a diet full of “the deadly white,” which is white sugar and white flour. Most of the people diagnosed with these diseases are given steroids, opioids, supplements, or elimination diets to manage their lives, but most of them continue suffering to varying degrees. On the other hand, Ayurveda can help manage autoimmune problems effectively. Ayurveda is a 5000 years old holistic medical system from India that has an individualistic approach where health problems are looked at from the lens of balancing body and mind and by targeting the root cause of the problem. A combination of diet and lifestyle according to Ayurvedic principles, Ayurvedic herbal formulations and Ayurvedic therapies can help in the management of autoimmune and other chronic diseases. Panchkarma, which is an intense six weeks detox method, helps balance our body and mind, and has been very effective in managing autoimmune problems. The paper will introduce the basic concepts of Ayurveda and describe the terminologies- doshas, agni and ama. The paper will discuss the importance of diet and lifestyle according to the individual’s imbalance in the three functional parameters - doshas, which govern every aspect of our body and mind, our cells and tissues. The significance of agni, which can be correlated to digestive strength and ama, which can be correlated to toxins that are formed in our body leading to health problems, will be outlined. The Ayurvedic pathophysiology of autoimmune diseases will be discussed with emphasis on Rheumatoid arthritis, Multiple sclerosis and Psoriasis. Ayurvedic management will be discussed for these autoimmune conditions. As Ayurveda is an individualistic system, one protocol will not work for everyone. Therefore, case studies with Ayurvedic protocols for the above autoimmune disease will be presented. Conclusion: Ayurveda can help in managing as well as arresting the progression of autoimmune problems. Ayurveda is an ancient medical system, is much more needed today than ever. It is a tried and tested holistic system which has been practiced for the past many generations in India.

Keywords: ayurveda, autoimmune, diseases, nutrition

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14442 Bio-Equivalence of Doxycycline in Two Preparations in Broiler Chickens

Authors: Abdelrazzag Elmajdoub

Abstract:

The present study was designed to investigate the bio-equivalence of doxycycline in Dolistin® and Colidox® at a dose rate of 10 mg doxycycline/kg of body weight in 48 clinically normal broiler chickens. After oral administration, plasma levels of doxycycline peaked after 2 hours post-dosing without significant differences between the two products and it could be detected therapeutically and exceeded the minimum inhibitory concentration (MIC) for most micro-organisms sensitive to doxycycline for 12 hours. The disposition kinetics of doxycycline in the two products following oral administration revealed that the maximum plasma concentrations (Cmax.) were 22.65 and 21.80 µg/ml and attained at (Tmax.) 2.10 and 2.20 hours, respectively. Doxycycline in both of the products was eliminated with half- lives (t0.5α) equal to 7.70 and 6.93 hours, respectively. The mean systemic bio availabilities of doxycycline in both of the products after oral administration in chickens were 80.60 and 79.70%, respectively. It was concluded that doxycycline in the form of Dolistin® and Colidox® needs a dose equivalent to 20 mg doxycycline/kg of body weight a day is better to keep the plasma concentration higher than the MIC.

Keywords: tetracyclines, doxycycline, bioavailability, broilers, chickens

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14441 Text Localization in Fixed-Layout Documents Using Convolutional Networks in a Coarse-to-Fine Manner

Authors: Beier Zhu, Rui Zhang, Qi Song

Abstract:

Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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14440 Optimisation of Energy Harvesting for a Composite Aircraft Wing Structure Bonded with Discrete Macro Fibre Composite Sensors

Authors: Ali H. Daraji, Ye Jianqiao

Abstract:

The micro electrical devices of the wireless sensor network are continuously developed and become very small and compact with low electric power requirements using limited period life conventional batteries. The low power requirement for these devices, cost of conventional batteries and its replacement have encouraged researcher to find alternative power supply represented by energy harvesting system to provide an electric power supply with infinite period life. In the last few years, the investigation of energy harvesting for structure health monitoring has increased to powering wireless sensor network by converting waste mechanical vibration into electricity using piezoelectric sensors. Optimisation of energy harvesting is an important research topic to ensure a flowing of efficient electric power from structural vibration. The harvesting power is mainly based on the properties of piezoelectric material, dimensions of piezoelectric sensor, its position on a structure and value of an external electric load connected between sensor electrodes. Larger surface area of sensor is not granted larger power harvesting when the sensor area is covered positive and negative mechanical strain at the same time. Thus lead to reduction or cancellation of piezoelectric output power. Optimisation of energy harvesting is achieved by locating these sensors precisely and efficiently on the structure. Limited published work has investigated the energy harvesting for aircraft wing. However, most of the published studies have simplified the aircraft wing structure by a cantilever flat plate or beam. In these studies, the optimisation of energy harvesting was investigated by determination optimal value of an external electric load connected between sensor electrode terminals or by an external electric circuit or by randomly splitting piezoelectric sensor to two segments. However, the aircraft wing structures are complex than beam or flat plate and mostly constructed from flat and curved skins stiffened by stringers and ribs with more complex mechanical strain induced on the wing surfaces. This aircraft wing structure bonded with discrete macro fibre composite sensors was modelled using multiphysics finite element to optimise the energy harvesting by determination of the optimal number of sensors, location and the output resistance load. The optimal number and location of macro fibre sensors were determined based on the maximization of the open and close loop sensor output voltage using frequency response analysis. It was found different optimal distribution, locations and number of sensors bounded on the top and the bottom surfaces of the aircraft wing.

Keywords: energy harvesting, optimisation, sensor, wing

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14439 Evaluation of Toxic Elements in Thai Rice Samples

Authors: W. Srinuttrakul, V. Permnamtip

Abstract:

Toxic elements in rice samples are great concern in Thailand because rice (Oryza sativa) is a staple food for Thai people. Furthermore, rice is an economic crop of Thailand for export. In this study, the concentrations of arsenic (As), cadmium (Cd) and lead (Pb) in rice samples collected from the paddy fields in the northern, northeastern and southern regions of Thailand were determined by inductively coupled plasma mass spectrometry. The mean concentrations of As, Cd and Pb in 55 rice samples were 0.112±0.056, 0.029±0.037 and 0.031±0.033 mg kg-1, respectively. All rice samples showed As, Cd and Pb lower than the limit data of Codex. The estimated daily intakes (EDIs) of As, Cd, and Pb from rice consumption were 0.026±0.013, 0.007±0.009 and 0.007±0.008 mg day-1, respectively. The percentage contribution to Provisional Tolerable Weekly Intake (PTWI) values of As, Cd and Pb for Thai male (body weight of 69 kg) was 17.6%, 9.7%, and 2.9%, respectively, and for Thai female (body weight of 57 kg) was 21.3%, 11.7% and 3.5%, respectively. The findings indicated that all studied rice samples are safe for consumption.

Keywords: arsenic, cadmium, ICP-MS, lead, rice

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14438 Presenting a Model for Predicting the State of Being Accident-Prone of Passages According to Neural Network and Spatial Data Analysis

Authors: Hamd Rezaeifar, Hamid Reza Sahriari

Abstract:

Accidents are considered to be one of the challenges of modern life. Due to the fact that the victims of this problem and also internal transportations are getting increased day by day in Iran, studying effective factors of accidents and identifying suitable models and parameters about this issue are absolutely essential. The main purpose of this research has been studying the factors and spatial data affecting accidents of Mashhad during 2007- 2008. In this paper it has been attempted to – through matching spatial layers on each other and finally by elaborating them with the place of accident – at the first step by adding landmarks of the accident and through adding especial fields regarding the existence or non-existence of effective phenomenon on accident, existing information banks of the accidents be completed and in the next step by means of data mining tools and analyzing by neural network, the relationship between these data be evaluated and a logical model be designed for predicting accident-prone spots with minimum error. The model of this article has a very accurate prediction in low-accident spots; yet it has more errors in accident-prone regions due to lack of primary data.

Keywords: accident, data mining, neural network, GIS

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14437 A Neural Network Based Clustering Approach for Imputing Multivariate Values in Big Data

Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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14436 Comparative Scanning Electron Microscopic Observations of Anthelminthic Effect of Trigonella foenum-graecum on Paramphistomum cervi in Buffalo

Authors: Kiran Roat, Bhanupriya Sanger, Gayatri Swarnakar

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Amphistomiasis disease is the main health problem throughout of the world and responsible for great economic losses to cattle industries, mostly to poor cattle farmers in developing countries. Among the rumen parasites, the Paramphistomum cervi were collected from the rumen of freshly slaughtered buffalo for the further treatment process. Trigonella foenum-graecum is commonly known as methi and fenugreek and their seeds are known for their therapeutic value. The present study was considered to evaluate in vitro efficacy of aqueous extract of Trigonella foenum-graecum on P. cervi. 130 mg/ml concentration of aqueous extract shows total mortality of P. cervi at 5 hours. The ultrastructural surface topography of untreated animal was compared with a treated animal by scanning electron microscope (SEM). The body of untreated P. cervi in conical shape, tegumental surface is highly ridged with transverse folds and present abundance number of papillaes. Observations demonstrated that the body of treated P. cervi become shrunken & elongated. Treated parasite shows the deep breakage in tegument and the disappearance of tegumental folds & papillae. Severe blebs formations have been found. Above findings, it can be concluded that the seeds of Trigonella foenum-graecum can be used as an anthelminthic agent to eliminate P. cervi from the body of buffalo.

Keywords: Paramphistomum cervi, Trigonella foenum-graecum, scanning electron microscope, buffalo

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14435 Examining the Relevance of Electoral Commission in Fostering Democratic Governance in Nigeria

Authors: Ahmed Usman

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This paper attempts to examine the relevance of an Electoral Commission in the democratic process of governance in Nigeria. However, democratic system and governance present a clear indication of responsive and responsible governments. The idea of a government being responsive and responsible is based on the premise of conventional principles of democracy such as freedom of political, economic and social rights of and individual. More so, upholding of the Rule of Law based on the ground of constitutionalism is a clear manifestation of the democratic governance. The burdens of ascertaining theses democratic ethos rely solely on the constituted election management body known as Independent National Electoral Commission (INEC) for the case of Nigeria. This body is however, saddled with the responsibility of organizing and conducting periodic regular credible election known as free and fair election. The body also, is expected to be neutral, and independent to ensure fair treatment to all. It is on the basis of this fair treatment that credible leaders emerged. To this end, the paper examines the powers, functions and features of Independent National Electoral Commission. More so, the concepts of election and democracy have been operationalized. It is obvious that electoral process in Nigeria is marred with series of problems of which the paper identified and solutions were proffered towards credible, free and fair elections for sustainable democratic governance. In order to succinctly discuss and analyze the issues at stake, Structural Functional Analysis theory is adopted as a theoretical frame work for the paper.

Keywords: election, electoral commission, democracy, governance

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14434 Human Microbiome Hidden Association with Chronic and Autoimmune Diseases

Authors: Elmira Davasaz Tabrizi, Müşteba Sevil, Ercan Arican

Abstract:

In recent decades, there has been a sharp increase in the prevalence of several unrelated chronic diseases. The use of long-term antibiotics for chronic illnesses is increasing. The antibiotic resistance occurrence and its relationship with host microbiomes are still unclear. Properties of the identifying antibodies have been the focus of chronic disease research, such as prostatitis or autoimmune. The immune system is made up of a complicated but well-organized network of cell types that constantly monitor and maintain their surroundings. The regulated homeostatic interaction between immune system cells and their surrounding environment shapes the microbial flora. Researchers believe that the disappearance of special bacterial species from our ancestral microbiota might have altered the body flora that can cause a rise in disease during the human life span. This unpleasant pattern demonstrates the importance of focusing on discovering and revealing the root causes behind the disappearance or alteration of our microbiota. In this review, we gathered the results of some studies that reveal changes in the diversity and quantity of microorganisms that may affect chronic and autoimmune diseases. Additionally, a Ph.D. thesis that is still in process as Metagenomic studies in chronic prostatitis samples is mentioned.

Keywords: metagenomic, autoimmune, prostatitis, microbiome

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14433 Network Traffic Classification Scheme for Internet Network Based on Application Categorization for Ipv6

Authors: Yaser Miaji, Mohammed Aloryani

Abstract:

The rise of recent applications in everyday implementation like videoconferencing, online recreation and voice speech communication leads to pressing the need for novel mechanism and policy to serve this steep improvement within the application itself and users‟ wants. This diversity in web traffics needs some classification and prioritization of the traffics since some traffics merit abundant attention with less delay and loss, than others. This research is intended to reinforce the mechanism by analysing the performance in application according to the proposed mechanism implemented. The mechanism used is quite direct and analytical. The mechanism is implemented by modifying the queue limit in the algorithm.

Keywords: traffic classification, IPv6, internet, application categorization

Procedia PDF Downloads 559
14432 The On-Board Critical Message Transmission Design for Navigation Satellite Delay/Disruption Tolerant Network

Authors: Ji-yang Yu, Dan Huang, Guo-ping Feng, Xin Li, Lu-yuan Wang

Abstract:

The navigation satellite network, especially the Beidou MEO Constellation, can relay data effectively with wide coverage and is applied in navigation, detection, and position widely. But the constellation has not been completed, and the amount of satellites on-board is not enough to cover the earth, which makes the data-relay disrupted or delayed in the transition process. The data-relay function needs to tolerant the delay or disruption in some extension, which make the Beidou MEO Constellation a delay/disruption-tolerant network (DTN). The traditional DTN designs mainly employ the relay table as the basic of data path schedule computing. But in practical application, especially in critical condition, such as the war-time or the infliction heavy losses on the constellation, parts of the nodes may become invalid, then the traditional DTN design could be useless. Furthermore, when transmitting the critical message in the navigation system, the maximum priority strategy is used, but the nodes still inquiry the relay table to design the path, which makes the delay more than minutes. Under this circumstances, it needs a function which could compute the optimum data path on-board in real-time according to the constellation states. The on-board critical message transmission design for navigation satellite delay/disruption-tolerant network (DTN) is proposed, according to the characteristics of navigation satellite network. With the real-time computation of parameters in the network link, the least-delay transition path is deduced to retransmit the critical message in urgent conditions. First, the DTN model for constellation is established based on the time-varying matrix (TVM) instead of the time-varying graph (TVG); then, the least transition delay data path is deduced with the parameters of the current node; at last, the critical message transits to the next best node. For the on-board real-time computing, the time delay and misjudges of constellation states in ground stations are eliminated, and the residual information channel for each node can be used flexibly. Compare with the minute’s delay of traditional DTN; the proposed transmits the critical message in seconds, which improves the re-transition efficiency. The hardware is implemented in FPGA based on the proposed model, and the tests prove the validity.

Keywords: critical message, DTN, navigation satellite, on-board, real-time

Procedia PDF Downloads 338
14431 The Effect of Restaurant Residuals on Performance of Japanese Quail

Authors: A. A. Saki, Y. Karimi, H. J. Najafabadi, P. Zamani, Z. Mostafaie

Abstract:

The restaurant residuals reasons such as competition between human and animal consumption of cereals, increasing environmental pollution and the high cost of production of livestock products is important. Therefore, in this restaurant residuals have a high nutritional value (protein and high energy) that it is possible can replace some of the poultry diets are especially Japanese quail. Today, the challenges of processing and consumption of these lesions occurring in modern industry would be confronting. Increasing costs, pressures, and problems associated with waste excretion, the need for re-evaluation and utilization of waste to livestock and poultry feed fortifies. This study aimed to investigate the effects of different levels of restaurant residuals on performance of 300 layer Japanese quails. This experiment included 5 treatments, 4 replicates, and 15 quails in each from 10 to 18 weeks age in a completely randomized design (CRD). The treatments consist of basal diet including corn and soybean meal (without residual restaurants), and treatments 2, 3, 4 and 5, includes a basal diet containing 5, 10, 15 and 20% of restaurant residuals, respectively. There were no significant effect of restaurant residuals levels on body weight (BW), feed conversion ratio (FCR), percentage of egg production (EP), egg mass (EM) between treatments (P > 0/05). However, feed intake (FI) of 5% restaurant residual was significantly higher than 20% treatment (P < 0/05). Egg weight (EW) was also higher by receiving 20% restaurant residuals compared with 10% in this respect (P < 0/05). Yolk weight (YW) of treatments containing 10 and 20% of the residual restaurant were significantly higher than control (P < 0/05). Eggs white weight (EWW) of 20 and 5% restaurants residual treatments were significantly increased compared by 10% (P < 0/05). Furthermore, EW, egg weight to shell surface area and egg surface area in 20% treatment were significantly higher than control and 10% treatment (P < 0/05). The overall results of this study have shown that restaurant residuals for laying quail diets in levels of 10 and 15 percent could be replaced with a part of the quail ration without any adverse effect.

Keywords: by-product, laying quail, performance, restaurant residuals

Procedia PDF Downloads 162
14430 The Findings EEG-LORETA about Epilepsy

Authors: Leila Maleki, Ahmad Esmali Kooraneh, Hossein Taghi Derakhshi

Abstract:

Neural activity in the human brain starts from the early stages of prenatal development. This activity or signals generated by the brain are electrical in nature and represent not only the brain function but also the status of the whole body. At the present moment, three methods can record functional and physiological changes within the brain with high temporal resolution of neuronal interactions at the network level: the electroencephalogram (EEG), the magnet oencephalogram (MEG), and functional magnetic resonance imaging (fMRI); each of these has advantages and shortcomings. EEG recording with a large number of electrodes is now feasible in clinical practice. Multichannel EEG recorded from the scalp surface provides a very valuable but indirect information about the source distribution. However, deep electrode measurements yield more reliable information about the source locations، Intracranial recordings and scalp EEG are used with the source imaging techniques to determine the locations and strengths of the epileptic activity. As a source localization method, Low Resolution Electro-Magnetic Tomography (LORETA) is solved for the realistic geometry based on both forward methods, the Boundary Element Method (BEM) and the Finite Difference Method (FDM). In this paper, we review The findings EEG- LORETA about epilepsy.

Keywords: epilepsy, EEG, EEG-LORETA

Procedia PDF Downloads 539
14429 Study of Variation in Linear Growth and Other Parameters of Male Albino Rats on Exposure to Chronic Multiple Stress after Birth

Authors: Potaliya Pushpa, Kataria Sushma, D. S. Chowdhary, Dadhich Abhilasha

Abstract:

Introduction: Stress is a nonspecific response of the body to a stressor or triggering stimulus. Chronic stress exposure contributes to various remarkable alterations o growth and development. Collective effects of stressors lead to several changes which are physical, physiological and behavioral in nature. Objective: To understand on an animal model how various chronic stress affect the somatic body growth as it can be useful for effective stress treatment and prevention of stress related illnesses. Material and Method: By selective fostering only male pup colonies were made and 102 male albino rats were studied. They were divided two groups as Control and Stressed. The experimental groups were exposed to four major types of stress as maternal deprivation, Restraint stress, electric foot shock and noise stress for affecting emotional, physical and physiological activities. Exposure was from birth to 17 week of life. Roentgenographs were taken in two planes as Dorso-ventral and Lateral and then measured for each rat. Various parameters were observed at specific intervals. Parameters recorded were Body weight and for linear growth it was summation of Cranial length, Head rump length and tail length. Behavior changes were also observed. Result: Multiple chronic stresses resulted in loss of approx. 25% of mean body weight. Maximal difference was found on 119th day (i.e. 87.81 gm) between the control and stressed group. Linear growth showed retardation which was found to be significant in stressed group on statistical analysis. Cranial Length and Head-rump Length showed maximum difference after maternal deprivation stress. After maternal deprivation (Day 21) and electric foot shock (Day 101) maximum difference i.e. 0.39 cm and 0.47 cm were found in cranial length of two groups. Electric foot shock had considerable impact on tail length. Noise Stress affected moreover behavior as compact to physical growth. Conclusion: Collective study showed that chronic stress not only resulted in reduced body weight in albino rats but also total linear size of rat thus affecting whole growth and development.

Keywords: stress, microscopic anatomy, macroscopic anatomy, chronic multiple stress, birth

Procedia PDF Downloads 263
14428 Intrusion Detection System Using Linear Discriminant Analysis

Authors: Zyad Elkhadir, Khalid Chougdali, Mohammed Benattou

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Most of the existing intrusion detection systems works on quantitative network traffic data with many irrelevant and redundant features, which makes detection process more time’s consuming and inaccurate. A several feature extraction methods, such as linear discriminant analysis (LDA), have been proposed. However, LDA suffers from the small sample size (SSS) problem which occurs when the number of the training samples is small compared with the samples dimension. Hence, classical LDA cannot be applied directly for high dimensional data such as network traffic data. In this paper, we propose two solutions to solve SSS problem for LDA and apply them to a network IDS. The first method, reduce the original dimension data using principal component analysis (PCA) and then apply LDA. In the second solution, we propose to use the pseudo inverse to avoid singularity of within-class scatter matrix due to SSS problem. After that, the KNN algorithm is used for classification process. We have chosen two known datasets KDDcup99 and NSLKDD for testing the proposed approaches. Results showed that the classification accuracy of (PCA+LDA) method outperforms clearly the pseudo inverse LDA method when we have large training data.

Keywords: LDA, Pseudoinverse, PCA, IDS, NSL-KDD, KDDcup99

Procedia PDF Downloads 223
14427 Characterization of Complex Electromagnetic Environment Created by Multiple Sources of Electromagnetic Radiation

Authors: Clement Temaneh-Nyah, Josiah Makiche, Josephine Nujoma

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This paper considers the characterisation of a complex electromagnetic environment due to multiple sources of electromagnetic radiation as a five-dimensional surface which can be described by a set of several surface sections including: instant EM field intensity distribution maps at a given frequency and altitude, instantaneous spectrum at a given location in space and the time evolution of the electromagnetic field spectrum at a given point in space. This characterization if done over time can enable the exposure levels of Radio Frequency Radiation at every point in the analysis area to be determined and results interpreted based on comparison of the determined RFR exposure level with the safe guidelines for general public exposure given by recognised body such as the International commission on non-ionising radiation protection (ICNIRP), Institute of Electrical and Electronic Engineers (IEEE), the National Radiation Protection Authority (NRPA).

Keywords: complex electromagnetic environment, electric field strength, mathematical models, multiple sources

Procedia PDF Downloads 365
14426 Short Term Distribution Load Forecasting Using Wavelet Transform and Artificial Neural Networks

Authors: S. Neelima, P. S. Subramanyam

Abstract:

The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

Procedia PDF Downloads 433