Search results for: Electric Field Strength

Authors: Bhekisipho Twala, Mantepu Masetshaba, Ramapulana Nkoana

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Multiple classifier systems combine several individual classifiers to deliver a final classification decision. However, an increasingly controversial question is whether such systems can outperform the single best classifier, and if so, what form of multiple classifiers system yields the most significant benefit. Also, multi-target tracking detection using multiple sensors is an important research field in mobile techniques and military applications. In this paper, several multiple classifiers systems are evaluated in terms of their ability to predict a system’s failure or success for multi-sensor target tracking tasks. The Bristol Eden project dataset is utilised for this task. Experimental and simulation results show that the human activity identification system can fulfil requirements of target tracking due to improved sensors classification performances with multiple classifier systems constructed using boosting achieving higher accuracy rates.

Keywords: Single classifier, machine learning, ensemble learning, multi-sensor target tracking.

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Authors: R. Mohan, V. Jadhav, A. Ahmed, J. Rivas, A. Kelkar

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Cementitious materials are an excellent example of a composite material with complex hierarchical features and random features that range from nanometer (nm) to millimeter (mm) scale. Multi-scale modeling of complex material systems requires starting from fundamental building blocks to capture the scale relevant features through associated computational models. In this paper, molecular dynamics (MD) modeling is employed to predict the effect of plasticizer additive on the mechanical properties of key hydrated cement constituent calcium-silicate-hydrate (CSH) at the molecular, nanometer scale level. Due to complexity, still unknown molecular configuration of CSH, a representative configuration widely accepted in the field of mineral Jennite is employed. The effectiveness of the Molecular Dynamics modeling to understand the predictive influence of material chemistry changes based on molecular / nanoscale models is demonstrated.

Keywords: Cement composite, Mechanical Properties, Molecular Dynamics, Plasticizer additives.

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Authors: Carlos H. Cuadra

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The present report describes the characteristics of damages and behavior of reinforced concrete buildings during the tsunami action. The discussion is based on the field damage survey in selected cities located on the coast of the zone affected by the Great East Japan Earthquake on March 11, 2011. This earthquake is the most powerful know earthquake that has hit Japan with a magnitude 9.0 and with epicenter located at 129 km of Sendai city (off the coast). The earthquake triggered a destructive tsunami with run up height of up to 40 meters that mainly affect cities located on the Pacific Ocean coast of the Tohoku region (north-east region of Japan). Reinforced concrete buildings in general resist the tsunami without collapse however the non-structural elements like panels and ceilings were severely damaged. The analysis of damages has permitted to understand the behavior of RC buildings under tsunami attack, and has also permitted to establish recommendations for their use to take refuge from tsunami in places where natural topography makes impossible to reach hilltops or other safer places.

Keywords: tsunami, RC buildings, East Japan Earthquake, seismic damage

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Authors: Jayson G. Balansag

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An integrated biology and chemistry (iBC) course for freshmen college students was developed in University of Delaware. This course will prepare students to (1) become interdisciplinary thinkers in the field of biology and (2) collaboratively work with others from multiple disciplines in the future. This paper documents and describes the implementation of the course. The information gathered from reading literature, classroom observations, and interviews were used to carry out the purpose of this paper. The major goal of the iBC course is to align the concepts between Biology and Chemistry, so that students can draw science concepts from both disciplines which they can apply in their interdisciplinary researches. This course is offered every fall and spring semesters of each school year. Students enrolled in Biology are also enrolled in Chemistry during the same semester. The iBC is composed of lectures, laboratories, studio sessions, and workshops and is taught by the faculty from the biology and chemistry departments. In addition, the preceptors, graduate teaching assistants, and studio fellows facilitate the laboratory and studio sessions. These roles are interdependent with each other. The iBC can be used as a model for higher education institutions who wish to implement an integrated biology course.

Keywords: Integrated biology and chemistry, integration, interdisciplinary research, new biology, undergraduate science education.

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Authors: Nazim Mir-Nasiri, Hudyjaya Siswoyo Jo

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The paper describes conceptual design, control strategies, and partial simulation for a new fully autonomous lower limb wearable exoskeleton system for human motion enhancement that can support its weight and increase strength and endurance. Various problems still remain to be solved where the most important is the creation of a power and cost efficient system that will allow an exoskeleton to operate for extended period without batteries being frequently recharged. The designed exoskeleton is enabling to decouple the weight/mass carrying function of the system from the forward motion function which reduces the power and size of propulsion motors and thus the overall weight, cost of the system. The decoupling takes place by blocking the motion at knee joint by placing passive air cylinder across the joint. The cylinder is actuated when the knee angle has reached the minimum allowed value to bend. The value of the minimum bending angle depends on usual walk style of the subject. The mechanism of the exoskeleton features a seat to rest the subject’s body weight at the moment of blocking the knee joint motion. The mechanical structure of each leg has six degrees of freedom: four at the hip, one at the knee, and one at the ankle. Exoskeleton legs are attached to subject legs by using flexible cuffs. The operation of all actuators depends on the amount of pressure felt by the feet pressure sensors and knee angle sensor. The sensor readings depend on actual posture of the subject and can be classified in three distinct cases: subject stands on one leg, subject stands still on both legs and subject stands on both legs but transit its weight from one leg to other. This exoskeleton is power efficient because electrical motors are smaller in size and did not participate in supporting the weight like in all other existing exoskeleton designs.

Keywords: Energy efficient system, exoskeleton, motion enhancement, robotics.

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Authors: Yuwaraj M. Ghugal, Ajay G. Dahake

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A trigonometric shear deformation theory for flexure of thick beams, taking into account transverse shear deformation effects, is developed. The number of variables in the present theory is same as that in the first order shear deformation theory. The sinusoidal function is used in displacement field in terms of thickness coordinate to represent the shear deformation effects. The noteworthy feature of this theory is that the transverse shear stresses can be obtained directly from the use of constitutive relations with excellent accuracy, satisfying the shear stress free conditions on the top and bottom surfaces of the beam. Hence, the theory obviates the need of shear correction factor. Governing differential equations and boundary conditions are obtained by using the principle of virtual work. The thick cantilever isotropic beams are considered for the numerical studies to demonstrate the efficiency of the. Results obtained are discussed critically with those of other theories.

Keywords: Trigonometric shear deformation, thick beam, flexure, principle of virtual work, equilibrium equations, stress.

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Authors: Shahzad Hassan, Kamran Saeed

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People are always in search of Wi-Fi hotspots because Internet is a major demand nowadays. But like all other technologies, there is still room for improvement in the Wi-Fi technology with regards to the speed and quality of connectivity. In order to address these aspects, Harald Haas, a professor at the University of Edinburgh, proposed what we know as the Li-Fi (Light Fidelity). Li-Fi is a new technology in the field of wireless communication to provide connectivity within a network environment. It is a two-way mode of wireless communication using light. Basically, the data is transmitted through Light Emitting Diodes which can vary the intensity of light very fast, even faster than the blink of an eye. From the research and experiments conducted so far, it can be said that Li-Fi can increase the speed and reliability of the transfer of data. This paper pays particular attention on the assessment of the performance of this technology. In other words, it is a 5G technology which uses LED as the medium of data transfer. For coverage within the buildings, Wi-Fi is good but Li-Fi can be considered favorable in situations where large amounts of data are to be transferred in areas with electromagnetic interferences. It brings a lot of data related qualities such as efficiency, security as well as large throughputs to the table of wireless communication. All in all, it can be said that Li-Fi is going to be a future phenomenon where the presence of light will mean access to the Internet as well as speedy data transfer.

Keywords: Communication, LED, Li-Fi, Wi-Fi.

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Authors: Elias O. Tembe, Hussain A. Al-Salamin

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There is decagram of strategic decisions of operations and production/service management (POSM) within operational research (OR) which must collate, namely: design, inventory, quality, location, process and capacity, layout, scheduling, maintain ace, and supply chain. This paper presents an architectural configuration conceptual framework of a decagram of sets decisions in a form of mathematical complete graph and abelian graph. Mathematically, a complete graph is undirected (UDG), and directed (DG) a relationship where every pair of vertices is connected, collated, confluent, and holomorphic. There has not been any study conducted which, however, prioritizes the holomorphic sets which of POMS within OR field of study. The study utilizes OR structured technique known as The Analytic Hierarchy Process (AHP) analysis for organizing, sorting and prioritizing(ranking) the sets within the decagram of POMS according to their attribution (propensity), and provides an analysis how the prioritization has real-world application within the 21st century.

Keywords: AHP analysis, Decagram, Decagon, Holomorphic.

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Authors: Sedigheh Zarei

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The aim of this research is to identify the key factors in shipping company’s port selection in order to providing their requirement. To identify and rank factors that play the main role in selecting port for providing the ship requirement, at the first step, data were collected via Semi-structured interviews, the aim was to generate knowledge on how shipping company select the port and suppliers for providing their needs. 37 port selection factors were chosen from the previous researches and field interviews and have been categorized into two groups of port's factor and the factors of services of suppliers companies. The current study adopts a questionnaire survey to the main shipping companies' operators in Iran. Their responses reveal that level of services of supplying companies and customs rules play the important role in selecting the ports. Our findings could affect decisions made by port authorities to consider that supporting the privet sections for ship chandelling business could have the best result in attracting ships.

Keywords: Port selection, ship supplier, ship chandler, provision.

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Authors: Bhavneet Sidhu, Hardeep Singh

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Cellular networks provide voice and data services to the users with mobility. To deliver services to the mobile users, the cellular network is capable of tracking the locations of the users, and allowing user movement during the conversations. These capabilities are achieved by the location management. Location management in mobile communication systems is concerned with those network functions necessary to allow the users to be reached wherever they are in the network coverage area. In a cellular network, a service coverage area is divided into smaller areas of hexagonal shape, referred to as cells. The cellular concept was introduced to reuse the radio frequency. Continued expansion of cellular networks, coupled with an increasingly restricted mobile spectrum, has established the reduction of communication overhead as a highly important issue. Much of this traffic is used in determining the precise location of individual users when relaying calls, with the field of location management aiming to reduce this overhead through prediction of user location. This paper describes and compares various location management schemes in the cellular networks.

Keywords: Cellular Networks, Location Area, MobilityManagement, Paging.

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Authors: Ranjit Chatterjee, P. K. Paul

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The influence of organic amendments and inorganic fertilizers on cabbage head was investigated to determine their effect on storage behavior and organoleptic quality. Field cabbage was raised by combining fourteen different treatments comprising of organic amendments and inorganic fertilizers at different levels. The result showed that nutrient schedule of the crop significantly influenced the physiological loss in weight (PLW) and organoleptic quality of cabbage head and judicious selection of nutrient combination can extend the storage life and reduce the post harvest detoriaration of head. The nutrient schedule comprising of higher level of FYM (16 t ha^-1) along with 75% of recommended inorganic fertilizers in conjugation with seedling inoculation of biofertilizer emerged as potential nutrient source for improving storage life, marketability and maintaining nutritional and organoleptic quality under ambient storage condition.

Keywords: Cabbage head, Organic amendments, Organoleptic quality, Physiological loss in weight (PLW).

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Authors: Gonzalo Rubio, Eusebio Valero, Sven Lanzan

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The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations. As a results of this, Computational Fluid Dynamic (CFD) solvers are widely used in the aeronautical field. These solvers require the correct selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on the proper choice of these parameters. In this paper we create an expert system capable of making an accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver. Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time required for the convergence of a CFD solver.

Keywords: Artificial Neural Network, Computational Fluid Dynamics, Optimization

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Authors: D. Singh, R. Yousefi, M. Boroushaki

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Intelligent deep-drawing is an instrumental research field in sheet metal forming. A set of 28 different experimental data have been employed in this paper, investigating the roles of die radius, punch radius, friction coefficients and drawing ratios for axisymmetric workpieces deep drawing. This paper focuses an evolutionary neural network, specifically, error back propagation in collaboration with genetic algorithm. The neural network encompasses a number of different functional nodes defined through the established principles. The input parameters, i.e., punch radii, die radii, friction coefficients and drawing ratios are set to the network; thereafter, the material outputs at two critical points are accurately calculated. The output of the network is used to establish the best parameters leading to the most uniform thickness in the product via the genetic algorithm. This research achieved satisfactory results based on demonstration of neural networks.

Keywords: Deep-drawing, Neural network, Genetic algorithm, Sheet metal forming.

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Authors: Jinsiang Shaw, Ray Pan, Yin-Chieh Chang

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In this paper, an magnetorheological (MR) mount with fuzzy sliding mode controller (FSMC) is studied for vibration suppression when the system is subject to base excitations. In recent years, magnetorheological fluids are becoming a popular material in the field of the semi-active control. However, the dynamic equation of an MR mount is highly nonlinear and it is difficult to identify. FSMC provides a simple method to achieve vibration attenuation of the nonlinear system with uncertain disturbances. This method is capable of handling the chattering problem of sliding mode control effectively and the fuzzy control rules are obtained by using the Lyapunov stability theory. The numerical simulations using one-dimension and two-dimension FSMC show effectiveness of the proposed controller for vibration suppression. Further, the well-known skyhook control scheme and an adaptive sliding mode controller are also included in the simulation for comparison with the proposed FSMC.

Keywords: adaptive sliding mode controller, fuzzy sliding modecontroller, magnetorheological mount, skyhook control.

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Authors: Ethar H. Khalil, Bahaa I. Kazem

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In this work a software simulation model has been proposed for two driven wheels mobile robot path planning; that can navigate in dynamic environment with static distributed obstacles. The work involves utilizing Bezier curve method in a proposed N order matrix form; for engineering the mobile robot path. The Bezier curve drawbacks in this field have been diagnosed. Two directions: Up and Right function has been proposed; Probability Recursive Function (PRF) to overcome those drawbacks. PRF functionality has been developed through a proposed; obstacle detection function, optimization function which has the capability of prediction the optimum path without comparison between all feasible paths, and N order Bezier curve function that ensures the drawing of the obtained path. The simulation results that have been taken showed; the mobile robot travels successfully from starting point and reaching its goal point. All obstacles that are located in its way have been avoided. This navigation is being done successfully using the proposed PRF techniques.

Keywords: Mobile robot, path planning, Bezier curve.

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Authors: Arun Goel

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Prediction of maximum local scour is necessary for the safety and economical design of the bridges. A number of equations have been developed over the years to predict local scour depth using laboratory data and a few pier equations have also been proposed using field data. Most of these equations are empirical in nature as indicated by the past publications. In this paper attempts have been made to compute local depth of scour around bridge pier in dimensional and non-dimensional form by using linear regression, simple regression and SVM (Poly & Rbf) techniques along with few conventional empirical equations. The outcome of this study suggests that the SVM (Poly & Rbf) based modeling can be employed as an alternate to linear regression, simple regression and the conventional empirical equations in predicting scour depth of bridge piers. The results of present study on the basis of non-dimensional form of bridge pier scour indicate the improvement in the performance of SVM (Poly & Rbf) in comparison to dimensional form of scour.

Keywords: Modeling, pier scour, regression, prediction, SVM (Poly & Rbf kernels).

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Authors: Maria Luskova, Maria Hudakova, Katarina Buganova

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Established objective and subjective preconditions for entrepreneurship, forming the business organically related whole, are the necessary condition of successful entrepreneurial activities. Objective preconditions for entrepreneurship are developed by market economy that should stimulate entrepreneurship by allowing the use of economic opportunities for all those who want to do business in respective field while providing guarantees to all owners and creating a stable business environment for entrepreneurs. Subjective preconditions of entrepreneurship are formed primarily by personal characteristics of the entrepreneur. These are his properties, abilities, skills, physiological and psychological preconditions which may be inherited, inborn or sequentially developed and obtained during his life on the basis of education and influences of surrounding environment. The paper is dealing with issues of objective and subjective preconditions for entrepreneurship and provides their analysis in view of the current situation in Slovakia. It presents risks of the business environment in Slovakia that the Slovak managers considered the most significant in 2014 and defines the dominant attributes of the entrepreneur in the current business environment in Slovakia.

Keywords: Entrepreneurship, innovations, opportunity, risk, uncertainty.

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Authors: S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha

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Machine learning is a new and exciting area of artificial intelligence nowadays. Machine learning is the most valuable, time, supervised, and cost-effective approach. It is not a narrow learning approach; it also includes a wide range of methods and techniques that can be applied to a wide range of complex realworld problems and time domains. Biological image classification, adaptive testing, computer vision, natural language processing, object detection, cancer detection, face recognition, handwriting recognition, speech recognition, and many other applications of machine learning are widely used in research, industry, and government. Every day, more data are generated, and conventional machine learning techniques are becoming obsolete as users move to distributed and real-time operations. By providing fundamental knowledge of machine learning tools and research opportunities in the field, the aim of this article is to serve as both a comprehensive overview and a guide. A diverse set of machine learning resources is demonstrated and contrasted with the key features in this survey.

Keywords: Artificial intelligence, machine learning, deep learning, machine learning algorithms, machine learning tools.

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Authors: Magdi M. E. Zumrawi

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Crossing culverts are essential element of rural roads. The paper aims to investigate failures of recently constructed wadi-crossing pipe culverts in Sennar state and provide necessary remedial measures. The investigation is conducted to provide an extensive diagnosis study in order to find out the main structural and hydrological weaknesses of the culverts. Literature of steel pipe culverts related to construction practices and common types of culvert failures and their appropriate mitigation measures were reviewed. A detailed field survey was conducted to detect failures and defects appeared on the existing culverts. The results revealed that seepage of water through the embankment and foundation of the culverts leads to excessive erosion and scouring causing sever failures and damages. The design mistakes and poor construction were detected as the main causes of culverts failures. For sustainability of the culverts, various remedial measures are recommended to be considered in urgent rehabilitation of the existing crossings.

Keywords: Culvert, erosion, failure, sustainability.

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Authors: V. Karamzadeh, J. Adhvaryu, A. Chandrasekaran, M. Packirisamy

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In Bulk Acoustic Wave (BAW) microfluidics, the throughput of particle sorting is dependent on the complex interplay between the geometric configuration of the channel, the size of the particles, and the properties of the fluid medium, which therefore calls for a detailed modeling and understanding of the fluid-particle interaction dynamics under an acoustic field, prior to designing the system. In this work, we propose a simplified Bulk acoustophoretic system that can be used for size dependent particle sorting. A Finite Element Method (FEM) based analytical model has been developed to study the dependence of particle sizes on channel parameters, and the sorting efficiency in a given fluid medium. Based on the results, the microfluidic system has been designed to take into account all the variables involved with the underlying physics, and has been fabricated using an additive manufacturing technique employing a commercial 3D printer, to generate a simple, cost-effective system that can be used for size sensitive particle sorting.

Keywords: 3D printing, 3D microfluidic chip, acoustophoresis, cell separation, MEMS, microfluidics.

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Authors: M.R. Mustafa, M.H. Isa, R.B. Rezaur

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Prediction of highly non linear behavior of suspended sediment flow in rivers has prime importance in the field of water resources engineering. In this study the predictive performance of two Artificial Neural Networks (ANNs) namely, the Radial Basis Function (RBF) Network and the Multi Layer Feed Forward (MLFF) Network have been compared. Time series data of daily suspended sediment discharge and water discharge at Pari River was used for training and testing the networks. A number of statistical parameters i.e. root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and coefficient of determination (R2) were used for performance evaluation of the models. Both the models produced satisfactory results and showed a good agreement between the predicted and observed data. The RBF network model provided slightly better results than the MLFF network model in predicting suspended sediment discharge.

Keywords: ANN, discharge, modeling, prediction, suspendedsediment,

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Authors: Cyrille Lambert, Tatiana Kalganova, Emanuele Stomeo

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Since 1992, year where Hugo de Garis has published the first paper on Evolvable Hardware (EHW), a period of intense creativity has followed. It has been actively researched, developed and applied to various problems. Different approaches have been proposed that created three main classifications: extrinsic, mixtrinsic and intrinsic EHW. Each of these solutions has a real interest. Nevertheless, although the extrinsic evolution generates some excellent results, the intrinsic systems are not so advanced. This paper suggests 3 possible solutions to implement the run-time configuration intrinsic EHW system: FPGA-based Run-Time Configuration system, JBits-based Run-Time Configuration system and Multi-board functional-level Run-Time Configuration system. The main characteristic of the proposed architectures is that they are implemented on Field Programmable Gate Array. A comparison of proposed solutions demonstrates that multi-board functional-level run-time configuration is superior in terms of scalability, flexibility and the implementation easiness.

Keywords: Evolvable hardware, evolutionary computation, FPGA systems.

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Authors: V. G. Sangam, Balasaheb M. Patre

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In this paper we have proposed a methodology to develop an amperometric biosensor for the analysis of glucose concentration using a simple microcontroller based data acquisition system. The work involves the development of Detachable Membrane Unit (enzyme based biomembrane) with immobilized glucose oxidase on the membrane and interfacing the same to the signal conditioning system. The current generated by the biosensor for different glucose concentrations was signal conditioned, then acquired and computed by a simple AT89C51-microcontroller. The optimum operating parameters for the better performance were found and reported. The detailed performance evaluation of the biosensor has been carried out. The proposed microcontroller based biosensor system has the sensitivity of 0.04V/g/dl, with a resolution of 50mg/dl. It has exhibited very good inter day stability observed up to 30 days. Comparing to the reference method such as HPLC, the accuracy of the proposed biosensor system is well within ± 1.5%. The system can be used for real time analysis of glucose concentration in the field such as, food and fermentation and clinical (In-Vitro) applications.

Keywords: Biosensor, DMU, Glucose oxidase andMicrocontroller.

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Authors: M. Keshavarzi

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Grasslands of Iran are encountered with a vast desertification and destruction. Some legumes are plants of forage importance with high palatability. Studied legumes in this project are Onobrychis, Medicago sativa (alfalfa) and Trifolium repens. Seeds were cultivated in research field of Kaboutarabad (33 km East of Isfahan, Iran) with an average 80 mm. annual rainfall. Plants were cultivated in a split plot design with 3 replicate and two water treatments (weekly irrigation, and under stress with same amount per 15 days interval). Water entrance to each plots were measured by Partial flow. This project lasted 20 weeks. Destructive samplings (1m2 each time) were done weekly. At each sampling plants were gathered and weighed separately for each vegetative parts. An Area Meter (Vista) was used to measure root surface and leaf area. Total shoot and root fresh and dry weight, leaf area index and soil coverage were evaluated too. Dry weight was achieved in 750c oven after 24 hours. Statgraphic and Harvard Graphic software were used to formulate and demonstrate the parameters curves due to time. Our results show that Trifolium repens has affected 60 % and Medicago sativa 18% by water stress. Onobrychis total fresh weight was reduced 45%. Dry weight or Biomass in alfalfa is not so affected by water shortage. This means that in alfalfa fields we can decrease the irrigation amount and have some how same amount of Biomass. Onobrychis show a drastic decrease in Biomass. The increases in total dry matter due to time in studied plants are formulated. For Trifolium repens if removal or cattle entrance to meadows do not occurred at perfect time, it will decrease the palatability and water content of the shoots. Water stress in a short period could develop the root system in Trifolium repens, but if it last more than this other ecological and soil factors will affect the growth of this plant. Low level of soil water is not so important for studied legume forges. But water shortage affect palatability and water content of aerial parts. Leaf area due to time in studied legumes is formulated. In fact leaf area is decreased by shortage in available water. Higher leaf area means higher forage and biomass production. Medicago and Onobrychis reach to the maximum leaf area sooner than Trifolium and are able to produce an optimum soil cover and inhibit the transpiration of soil water of meadows. Correlation of root surface to Total biomass in studied plants is formulated. Medicago under water stress show a 40% decrease in crown cover while at optimum condition this amount reach to 100%. In order to produce forage in areas without soil erosion Medicago is the best choice even with a shortage in water resources. It is tried to represent the growth simulation of three famous Forage Legumes. By growth simulation farmers and range managers could better decide to choose best plant adapted to water availability without designing different time and labor consuming field experiments.

Keywords: Ecological parameters, Medicago, Onobrychis, Trifolium.

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Authors: Jeong-Min Jo, Young-Jae Han, Chang-Young Lee

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Attracting ferromagnetic forces between magnet and reaction rail provide the supporting force in Electromagnetic Suspension. Miniature maglev using permanent magnets and electromagnets is based on the idea to generate the nominal magnetic force by permanent magnets and superimpose the variable magnetic field required for stabilization by currents flowing through control windings in electromagnets. Permanent magnets with a high energy density have lower power losses with regard to supporting force and magnet weight. So the advantage of the maglev using electromagnets and permanent magnets is partially reduced by the power required to feed the remaining onboard supply system so that the overall onboard power is diminished as compared to that of the electromagnet. In this paper we proposed the how to design and control the miniature maglev and confirmed the feasibility of the levitation system using electromagnets and permanent magnets through the manufacturing the miniature maglev

Keywords: Magnetic Levitation system, Maglev, Permanent Magnets, Hybrid Magnet.

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Authors: Supriyo Goswami, Debabrata Mazumder

Abstract:

Chrome tannery wastewater causes serious environmental hazard due to its high pollution potential. As a result, rigorous treatment is necessary for abatement of pollution from this type of wastewater. There are many research studies on chrome tannery wastewater treatment in the field of physical, chemical, and biological methods. In general, biological treatment process is found ineffective for direct application because of adverse effects by toxic chromium, sulphide, chloride etc. However, biological methods were employed mainly for a few sub processes generating significant amount of organic matter and without chromium, chlorides etc. In this context the present paper reviews the characteristics feature and pollution potential of wastewater generated from chrome tannery units and treatment of the same. The different biological processes used earlier and their chronological development for treatment of the chrome tannery wastewater are thoroughly reviewed in this paper. In this regard, the scope of hybrid bioreactor - an advanced technology option has also been explored, as this kind of treatment is well suited for the wastewater having inhibitory substances. 

Keywords: Composite tannery wastewater, biological treatment, Hybrid bioreactor, Organic removal

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Authors: Thanh Nguyen, Andrei Doncescu, Pierre Siegel

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Classification is an important data mining technique and could be used as data filtering in artificial intelligence. The broad application of classification for all kind of data leads to be used in nearly every field of our modern life. Classification helps us to put together different items according to the feature items decided as interesting and useful. In this paper, we compare two classification methods Naïve Bayes and ADTree use to detect spam e-mail. This choice is motivated by the fact that Naive Bayes algorithm is based on probability calculus while ADTree algorithm is based on decision tree. The parameter settings of the above classifiers use the maximization of true positive rate and minimization of false positive rate. The experiment results present classification accuracy and cost analysis in view of optimal classifier choice for Spam Detection. It is point out the number of attributes to obtain a tradeoff between number of them and the classification accuracy.

Keywords: Classification, data mining, spam filtering, naive Bayes, decision tree.

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Authors: Nur Atiqah Rochin Demong, Jie Lu, Farookh Khadeer Hussain

Abstract:

Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert-s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts- experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.

Keywords: Uncertainty factors, data mining, multidimensional data model, risk analysis.

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Authors: Iqbalur Rahman, Miftahur Rahman, Abul L Haque, Mostafizur Rahman,

Abstract:

In this paper, RSA encryption algorithm and its hardware implementation in Xilinx-s Virtex Field Programmable Gate Arrays (FPGA) is analyzed. The issues of scalability, flexible performance, and silicon efficiency for the hardware acceleration of public key crypto systems are being explored in the present work. Using techniques based on the interleaved math for exponentiation, the proposed RSA calculation architecture is compared to existing FPGA-based solutions for speed, FPGA utilization, and scalability. The paper covers the RSA encryption algorithm, interleaved multiplication, Miller Rabin algorithm for primality test, extended Euclidean math, basic FPGA technology, and the implementation details of the proposed RSA calculation architecture. Performance of several alternative hardware architectures is discussed and compared. Finally, conclusion is drawn, highlighting the advantages of a fully flexible & parameterized design.

Keywords: Crypto Accelerator, FPGA, Public Key Cryptography, RSA.

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Authors: Shweta Singh, Dipali Bansal, Rashima Mahajan

Abstract:

Psychoacoustics has become a potential area of research due to the growing interest of both laypersons and medical and mental health professionals. Non invasive brain computer interface like Electroencephalography (EEG) is widely being used in this field. An attempt has been made in this paper to examine the response of EEG signals to acoustic stimuli further analyzing the brain electrical activity. The real time EEG is acquired for 6 participants using a cost effective and portable EMOTIV EEG neuro headset. EEG data analysis is further done using EMOTIV test bench, EDF browser and EEGLAB (MATLAB Tool) application software platforms. Spectral analysis of acquired neural signals (AF3 channel) using these software platforms are clearly indicative of increased brain activity in various bands. The inferences drawn from such an analysis have significant correlation with subject’s subjective reporting of the experiences. The results suggest that the methodology adopted can further be used to assist patients with sleeping and depressive disorders.

Keywords: OM’ chant, Spectral analysis, EDF Browser, EEGLAB, EMOTIV, Real time Acquisition.

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