Search results for: Pattern Search.

Authors: Wael M Albadri, Hassnen M Jafer, Ehab H Sfoog

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Relationship between undrained shear strength (Su) and over consolidation ratio (OCR) of clay soil (marine clay) is very important in the field of geotechnical engineering to estimate the settlement behaviour of clay and to prepare a small scale physical modelling test. In this study, a relationship between shear strength and OCR parameters was determined using the laboratory vane shear apparatus and the fully automatic consolidated apparatus. The main objective was to establish non-linear correlation formula between shear strength and OCR and comparing it with previous studies. Therefore, in order to achieve this objective, three points were chosen to obtain 18 undisturbed samples which were collected with an increasing depth of 1.0 m to 3.5 m each 0.5 m. Clay samples were prepared under undrained condition for both tests. It was found that the OCR and shear strength are inversely proportional at similar depth and at same undrained conditions. However, a good correlation was obtained from the relationships where the R2 values were very close to 1.0 using polynomial equations. The comparison between the experimental result and previous equation from other researchers produced a non-linear correlation which has a similar pattern with this study.

Keywords: Shear strength, over-consolidation ratio, vane shear test, clayey soil.

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: Pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction.

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Authors: Pradyumna Kumar Sahoo, Prasanta Kumar Satpathy

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This paper aims at finding a suitable neural network for monitoring congestion level in electrical power systems. In this paper, the input data has been framed properly to meet the target objective through supervised learning mechanism by defining normal and abnormal operating conditions for the system under study. The congestion level, expressed as line congestion index (LCI), is evaluated for each operating condition and is presented to the NN along with the bus voltages to represent the input and target data. Once, the training goes successful, the NN learns how to deal with a set of newly presented data through validation and testing mechanism. The crux of the results presented in this paper rests on performance comparison of a multi-layered feed forward neural network with eleven types of back propagation techniques so as to evolve the best training criteria. The proposed methodology has been tested on the standard IEEE-14 bus test system with the support of MATLAB based NN toolbox. The results presented in this paper signify that the Levenberg-Marquardt backpropagation algorithm gives best training performance of all the eleven cases considered in this paper, thus validating the proposed methodology.

Keywords: Line congestion index, critical bus, contingency, neural network.

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Authors: Maria C. Proença, Marco Aniceto, Pedro N. Santos, José C. Freitas

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A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Keywords: Automatic detection, wavelets, defects, fracture lines.

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Authors: M. Tehranizadeh, E. Shoushtari Rezvani

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Seismic performance of steel moment-resisting frame structures is investigated considering nonlinear soil-structure interaction (SSI) effects. 10-, 15-, and 20-story planar building frames with aspect ratio of 3 are designed in accordance with current building codes. Inelastic seismic demands of the superstructure are considered using concentrated plasticity model. The raft foundation system is designed for different soil types. Beam-on-nonlinear Winkler foundation (BNWF) is used to represent dynamic impedance of the underlying soil. Two sets of pulse-like as well as no-pulse near-fault earthquakes are used as input ground motions. The results show that the reduction in drift demands due to nonlinear SSI is characterized by a more uniform distribution pattern along the height when compared to the fixed-base and linear SSI condition. It is also concluded that beneficial effects of nonlinear SSI on displacement demands is more significant in case of pulse-like ground motions and performance level of the steel moment-resisting frames can be enhanced.

Keywords: Soil-structure interaction, uplifting, soil plasticity, near-fault earthquake, tall building.

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Authors: Rezaul Azim, A. Toaha Mobashsher, M. Tariqul Islam

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In this paper a novel ultra-wideband (UWB) slot antenna with band notch characteristics for world interoperability for microwave access (WiMAX) is proposed. The designed antenna consists of a rectangular radiating patch and a ground plane with tapered shape slot. To realize a notch band, a curved parasitic element has been etched out along with the radiating patch. It is observed that by adjusting the length, thickness and position of the parasitic element, the proposed antenna can achieved an impedance bandwidth of 8.01GHz (2.84 to 10.85GHz) with a notched band of 3.28-3.85GHz. Compared to the recently reported band notch antennas, the proposed antenna has a simple configuration to realize band notch characteristics in order to mitigate the potential interference between WiMAX and UWB system. Furthermore, a stable radiation pattern and moderate gain except at the notched band makes the proposed antenna suitable for various UWB applications. 

Keywords: Band notch, Filter element, Ultra-wideband (UWB), WiMAX.

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Authors: Rao M. V., Joshi S. C., Balaji M.

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Coastal zone combines terrestrial, marine and atmospheric factors and gives rise to unique landforms that play an important role in long-term sustainability of the hinterland and economy of maritime nations. World over, efforts have been put forth to understand plants of the seacoasts. In India also, plants of several geographical entities have been well documented, but works devoted to plant communities of the vast tropical coast of India and its States are still insufficient. Therefore, an inventory of plants flourishing in a stretch of ~450km of the Coastal Regulatory Zone I encompassing a total of 84 villages in 6 revenue Districts of northern Andhra Pradesh (15o42’06”N, 80^o51’03”E to 19o05’51”N, 84^o47’44”E) along Bay of Bengal was carried out. The study revealed presence of a total of 364 species belonging to 225 genera under 71 families. In addition to inventory, zonation pattern, ethnobotany, and certain interesting ecological facts are included.

Keywords: Ecology, Ethnobotany, Inventory, Tropical coast, Zonation.

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Authors: Petra Wächter

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A comprehensive discussion of feasible strategies for sustainable energy supply is urgently needed to achieve a turnaround of the current energy situation. The necessary fundamentals required for the development of a long term energy vision are lacking to a great extent due to the absence of reasonable long term scenarios that fulfill the requirements of climate protection and sustainable energy use. The contribution of the study is based on a search for sustainable energy paths in the long run for Austria. The analysis makes use of secondary data predominantly. The measures developed to avoid CO2 emissions and other ecological risk factors vary to a great extent among all economic sectors. This is shown by the calculation of CO2 cost of abatement curves. In this study it is demonstrated that the most effective technical measures with the lowest CO2 abatement costs yield solutions to the current energy problems. Various scenarios are presented concerning the question how the technological and environmental options for a sustainable energy system for Austria could look like in the long run. It is shown how sustainable energy can be supplied even with today-s technological knowledge and options available. The scenarios developed include an evaluation of the economic costs and ecological impacts. The results are not only applicable to Austria but demonstrate feasible and cost efficient ways towards a sustainable future.

Keywords: Cost of CO2 Abatement, Energy Economics, Energy Efficiency, Renewable Energy Technologies, Sustainable Energy and Development.

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Authors: Thomas Kerstein, Martin Laurowski, Philipp Klein, Michael Weyrich, Hubert Roth, Jürgen Wahrburg

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Optical 3D measurement of objects is meaningful in numerous industrial applications. In various cases shape acquisition of weak textured objects is essential. Examples are repetition parts made of plastic or ceramic such as housing parts or ceramic bottles as well as agricultural products like tubers. These parts are often conveyed in a wobbling way during the automated optical inspection. Thus, conventional 3D shape acquisition methods like laser scanning might fail. In this paper, a novel approach for acquiring 3D shape of weak textured and moving objects is presented. To facilitate such measurements an active stereo vision system with structured light is proposed. The system consists of multiple camera pairs and auxiliary laser pattern generators. It performs the shape acquisition within one shot and is beneficial for rapid inspection tasks. An experimental setup including hardware and software has been developed and implemented.

Keywords: automated optical inspection, depth from structured light, stereo vision, surface reconstruction

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Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

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This paper presents modeling and optimization of two NP-hard problems in flexible manufacturing system (FMS), part type selection problem and loading problem. Due to the complexity and extent of the problems, the paper was split into two parts. The first part of the papers has discussed the modeling of the problems and showed how the real coded genetic algorithms (RCGA) can be applied to solve the problems. This second part discusses the effectiveness of the RCGA which uses an array of real numbers as chromosome representation. The novel proposed chromosome representation produces only feasible solutions which minimize a computational time needed by GA to push its population toward feasible search space or repair infeasible chromosomes. The proposed RCGA improves the FMS performance by considering two objectives, maximizing system throughput and maintaining the balance of the system (minimizing system unbalance). The resulted objective values are compared to the optimum values produced by branch-and-bound method. The experiments show that the proposed RCGA could reach near optimum solutions in a reasonable amount of time.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm

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Authors: F. Farzin

Abstract:

Research has shown that techno-entrepreneurship is economically significant. Therefore, it is suggested that teaching techno-entrepreneurship may be important because such programmes would prepare current and future generations of learners to recognise and act on high-technology opportunities. Education in technoentrepreneurship may increase the knowledge of how to start one’s own enterprise and recognise the technological opportunities for commercialisation to improve decision-making about starting a new venture; also it influence decisions about capturing the business opportunities and turning them into successful ventures. Universities can play a main role in connecting and networking technoentrepreneurship students towards a cooperative attitude with real business practice and industry knowledge. To investigate and answer whether education for techno-entrepreneurs really helps, this paper choses a comparison of literature reviews as its method of research. After reviewing literature related to the impact of technoentrepreneurship education on self-employment 6 studies which had similar aim and objective to this paper were. These particular papers were selected based on a keywords search and as their aim, objectives, and gaps were close to the current research. In addition, they were all based on the influence of techno-entrepreneurship education in self-employment and intention of students to start new ventures. The findings showed that teaching techno-entrepreneurship education may have an influence on students’ intention and their future self-employment, but which courses should be covered and the duration of programmes, needs further investigation.

Keywords: Techno-entrepreneurship education, training, higher education, intention, self-employment.

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Authors: Maumita Bhattacharya

Abstract:

Optimization is often a critical issue for most system design problems. Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, finding optimal solution to complex high dimensional, multimodal problems often require highly computationally expensive function evaluations and hence are practically prohibitive. The Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model presented in our earlier work [14] reduced computation time by controlled use of meta-models to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the meta-model are generated from a single uniform model. Situations like model formation involving variable input dimensions and noisy data certainly can not be covered by this assumption. In this paper we present an enhanced version of DAFHEA that incorporates a multiple-model based learning approach for the SVM approximator. DAFHEA-II (the enhanced version of the DAFHEA framework) also overcomes the high computational expense involved with additional clustering requirements of the original DAFHEA framework. The proposed framework has been tested on several benchmark functions and the empirical results illustrate the advantages of the proposed technique.

Keywords: Evolutionary algorithm, Fitness function, Optimization, Meta-model, Stochastic method.

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

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Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: Pollen recognition, logistic model tree, expectation-maximization, local binary pattern.

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Authors: Wayan F. Mahmudy, Romeo M. Marian, Lee H. S. Luong

Abstract:

 This paper deals with modeling and optimization of two NP-hard problems in production planning of flexible manufacturing system (FMS), part type selection problem and loading problem. The part type selection problem and the loading problem are strongly related and heavily influence the system’s efficiency and productivity. These problems have been modeled and solved simultaneously by using real coded genetic algorithms (RCGA) which uses an array of real numbers as chromosome representation. The novel proposed chromosome representation produces only feasible solutions which minimize a computational time needed by GA to push its population toward feasible search space or repair infeasible chromosomes. The proposed RCGA improves the FMS performance by considering two objectives, maximizing system throughput and maintaining the balance of the system (minimizing system unbalance). The resulted objective values are compared to the optimum values produced by branch-and-bound method. The experiments show that the proposed RCGA could reach near optimum solutions in a reasonable amount of time.

Keywords: Flexible manufacturing system, production planning, part type selection problem, loading problem, real-coded genetic algorithm.

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Authors: K. Akilandeswari, G. M. Nasira

Abstract:

Brain-Computer Interfaces (BCIs) measure brain signals activity, intentionally and unintentionally induced by users, and provides a communication channel without depending on the brain’s normal peripheral nerves and muscles output pathway. Feature Selection (FS) is a global optimization machine learning problem that reduces features, removes irrelevant and noisy data resulting in acceptable recognition accuracy. It is a vital step affecting pattern recognition system performance. This study presents a new Binary Particle Swarm Optimization (BPSO) based feature selection algorithm. Multi-layer Perceptron Neural Network (MLPNN) classifier with backpropagation training algorithm and Levenberg-Marquardt training algorithm classify selected features.

Keywords: Brain-Computer Interfaces (BCI), Feature Selection (FS), Walsh–Hadamard Transform (WHT), Binary Particle Swarm Optimization (BPSO), Multi-Layer Perceptron (MLP), Levenberg–Marquardt algorithm.

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Authors: Yi-Cheng Huang, Yan-Chen Shin

Abstract:

This paper proposes method of diagnosing ball screw preload loss through the Hilbert-Huang Transform （HHT） and Multiscale entropy （MSE） process. The proposed method can diagnose ball screw preload loss through vibration signals when the machine tool is in operation. Maximum dynamic preload of 2 %, 4 %, and 6 % ball screws were predesigned, manufactured, and tested experimentally. Signal patterns are discussed and revealed using Empirical Mode Decomposition（EMD）with the Hilbert Spectrum. Different preload features are extracted and discriminated using HHT. The irregularity development of a ball screw with preload loss is determined and abstracted using MSE based on complexity perception. Experiment results show that the proposed method can predict the status of ball screw preload loss. Smart sensing for the health of the ball screw is also possible based on a comparative evaluation of MSE by the signal processing and pattern matching of EMD/HHT. This diagnosis method realizes the purposes of prognostic effectiveness on knowing the preload loss and utilizing convenience.

Keywords: Empirical Mode Decomposition, Hilbert-Huang Transform, Multi-scale Entropy, Preload Loss, Single-nut Ball Screw

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Authors: Sharath Kumar T., S.Vinodh

Abstract:

Over the course of the past century, the global automotive industry-s stance towards safety has evolved from one of contempt to one nearing reverence. A suspension system that provides safe handling and cornering capabilities can, with the help of an efficient braking system, improve safety to a large extent. The aim of this research is to propose a new automotive brake rotor design and to compare it with automotive vented disk rotor. Static structural and transient thermal analysis have been carried out on the vented disk rotor and proposed rotor designs to evaluate and compare their performance. Finite element analysis was employed for both static structural and transient thermal analysis. Structural analysis was carried out to study the stress and deformation pattern of the rotors under extreme loads. Time varying temperature load was applied on the rotors and the temperature distribution was analysed considering cooling parameters (convection and radiation). This dissertation illustrates the use of Finite Element Methods to examine models, concluding with a comparative study of the proposed rotor design and the conventional vented disk rotor for structural stability and thermal efficiency.

Keywords: Disk brakes, CAD model, rotor design, structural and thermal analysis

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Authors: Mohamed Dbouk, Ihab Sbeity

Abstract:

Spatial and mobile computing evolves. This paper describes a smart modeling platform called “GeoSEMA". This approach tends to model multidimensional GeoSpatial Evolutionary and Mobile Agents. Instead of 3D and location-based issues, there are some other dimensions that may characterize spatial agents, e.g. discrete-continuous time, agent behaviors. GeoSEMA is seen as a devoted design pattern motivating temporal geographic-based applications; it is a firm foundation for multipurpose and multidimensional special-based applications. It deals with multipurpose smart objects (buildings, shapes, missiles, etc.) by stimulating geospatial agents. Formally, GeoSEMA refers to geospatial, spatio-evolutive and mobile space constituents where a conceptual geospatial space model is given in this paper. In addition to modeling and categorizing geospatial agents, the model incorporates the concept of inter-agents event-based protocols. Finally, a rapid software-architecture prototyping GeoSEMA platform is also given. It will be implemented/ validated in the next phase of our work.

Keywords: Location-Trajectory management, GIS, Mobile- Moving Objects/Agents, Multipurpose/Spatiotemporal data, Multi- Agent Systems.

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Authors: Suwimon Saneewong Na Ayuttaya, Chainarong Chaktranond, Phadungsak Rattanadecho

Abstract:

This study numerically investigates the effects of Electrohydrodynamic on flow patterns and heat transfer enhancement within a cavity which is on the lower wall of channel. In this simulation, effects of using ground wire and ground plate on the flow patterns are compared. Moreover, the positions of electrode wire respecting with ground are tested in the range of angles θ = 0 - 180^o. High electrical voltage exposes to air is 20 kV. Bulk mean velocity and temperature of inlet air are controlled at 0.1 m/s and 60 ^OC, respectively. The result shows when electric field is applied, swirling flow is appeared in the channel. In addition, swirling flow patterns in the main flow of using ground plate are widely spreader than that of using ground wire. Moreover, direction of swirling flow also affects the flow pattern and heat transfer in a cavity. These cause the using ground wire to give the maximum temperature and heat transfer higher than using ground plate. Furthermore, when the angle is at θ = 60^o, high shear flow effect is obtained. This results show high strength of swirling flow and effective heat transfer enhancement.

Keywords: Swirling Flow, Heat Transfer, Electrohydrodynamic, Numerical Analysis.

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Authors: Jayendra Krishna, Laxmi Srivastava

Abstract:

Power flow (PF) study, which is performed to determine the power system static states (voltage magnitudes and voltage angles) at each bus to find the steady state operating condition of a system, is very important and is the most frequently carried out study by power utilities for power system planning, operation and control. In this paper, a counterpropagation neural network (CPNN) is proposed to solve power flow problem under different loading/contingency conditions for computing bus voltage magnitudes and angles of the power system. The counterpropagation network uses a different mapping strategy namely counterpropagation and provides a practical approach for implementing a pattern mapping task, since learning is fast in this network. The composition of the input variables for the proposed neural network has been selected to emulate the solution process of a conventional power flow program. The effectiveness of the proposed CPNN based approach for solving power flow is demonstrated by computation of bus voltage magnitudes and voltage angles for different loading conditions and single line-outage contingencies in IEEE 14-bus system.

Keywords: Admittance matrix, counterpropagation neural network, line outage contingency, power flow

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Authors: Kalyan Deepak Kolla, Ketan Paua, Rajkumar Bhagate

Abstract:

Transmission dynamics occupy major role in customer perception of the product in both senses of touch and quality of sound. The quantity and quality of sound perceived is more concerned with the whine noise of the gears engaged. Whine noise is tonal in nature and tonal noises cause fatigue and irritation to customers, which in turn affect the quality of the product. Transmission error is the usual suspect for whine noise, which can be caused due to misalignments, tolerances, manufacturing variabilities. In-cabin noise is also more sensitive to the gear design. As the details of the gear tooth design and manufacturing are in microns, anything out of the tolerance zone, either in design or manufacturing, will cause a whine noise. This will also cause high variation in stress and deformation due to change in the load and leads to the fatigue failure of the gears. Hence gear design and development take priority in the transmission development process. This paper aims to study such variability by considering five pairs of helical spur gears and their effect on the transmission error, contact pattern and vibration level on the transmission.

Keywords: Gears, whine noise, manufacturing variability, mount vibration variability.

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Authors: Yu-Chuan Chang, Chen Shi-Kai

Abstract:

A water reuse system in wetland paddy was simulated to supply water for industrial in this paper. A two-tank model was employed to represent the return flow of the wetland paddy.Historical data were performed for parameter estimation and model verification. With parameters estimated from the data, the model was then used to simulate a reasonable return flow rate from the wetland paddy. The simulation results show that the return flow ratio was 11.56% in the first crop season and 35.66% in the second crop season individually; the difference may result from the heavy rainfall in the second crop season. Under the existent pond with surplus active capacity, the water reuse ratio was 17.14%, and the water supplementary ratio was 21.56%. However, the pattern of rainfall, the active capacity of the pond, and the rate of water treatment limit the volume of reuse water. Increasing the irrigation water, dredging the depth of pond before rainy season and enlarging the scale of module are help to develop water reuse system to support for the industrial water use around wetland paddy.

Keywords: Return flow, water reuse, wetland paddy, return flow ratio (RR), water reuse ratio (WRR), water supplementary ratio(WSR)

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Authors: Pongsatorn Tantrabundit, Lersak Phothong, Ong-art Chanprasitchai

Abstract:

Due to the emergence of the Internet, it has extended the traditional Word-of-Mouth (WOM) to a new form called “Electronic Word-of-Mouth (eWOM).” Unlike traditional WOM, eWOM is able to present information in various ways by applying different components. Each eWOM component generates different effects on online consumer behavior. This research investigates the effects of Webcare (responding message) from product/ service providers on negative eWOM by applying two types of products (search and experience). The proposed conceptual model was developed based on the combination of the stages in consumer decision-making process, theory of reasoned action (TRA), theory of planned behavior (TPB), the technology acceptance model (TAM), the information integration theory and the elaboration likelihood model. The methodology techniques used in this study included multivariate analysis of variance (MANOVA) and multiple regression analysis. The results suggest that Webcare does slightly increase Thai online consumer’s perceptions on perceived eWOM trustworthiness, information diagnosticity and quality. For negative eWOM, we also found that perceived eWOM Trustworthiness, perceived eWOM diagnosticity and quality have a positive relationship with eWOM influence whereas perceived valence has a negative relationship with eWOM influence in Thai online consumers.

Keywords:

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Authors: S. M. Kamruzzaman, Md. Monirul Islam

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Although backpropagation ANNs generally predict better than decision trees do for pattern classification problems, they are often regarded as black boxes, i.e., their predictions cannot be explained as those of decision trees. In many applications, it is desirable to extract knowledge from trained ANNs for the users to gain a better understanding of how the networks solve the problems. A new rule extraction algorithm, called rule extraction from artificial neural networks (REANN) is proposed and implemented to extract symbolic rules from ANNs. A standard three-layer feedforward ANN is the basis of the algorithm. A four-phase training algorithm is proposed for backpropagation learning. Explicitness of the extracted rules is supported by comparing them to the symbolic rules generated by other methods. Extracted rules are comparable with other methods in terms of number of rules, average number of conditions for a rule, and predictive accuracy. Extensive experimental studies on several benchmarks classification problems, such as breast cancer, iris, diabetes, and season classification problems, demonstrate the effectiveness of the proposed approach with good generalization ability.

Keywords: Backpropagation, clustering algorithm, constructivealgorithm, continuous activation function, pruning algorithm, ruleextraction algorithm, symbolic rules.

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Authors: O. Boe, S-T. Kristiansen, R. Wold

Abstract:

In this article we explore how computer assisted exercises may allow for bridging the traditional gap between theory and practice in professional education. To educate officers able to master the complexity of the battlefield the Norwegian Military Academy needs to develop a learning environment that allows for creating viable connections between the educational environment and the field of practice. In response to this challenge we explore the conditions necessary to make computer assisted training systems (CATS) a useful tool to create structural similarities between an educational context and the field of military practice. Although, CATS may facilitate work procedures close to real life situations, this case do demonstrate how professional competence also must build on viable learning theories and environments. This paper explores the conditions that allow for using simulators to facilitate professional competence from within an educational setting. We develop a generic didactic model that ascribes learning to participation in iterative cycles of action and reflection. The development of this model is motivated by the need to develop an interdisciplinary professional education rooted in the pattern of military practice.

Keywords: Development in higher education, experiential learning, professional education, simulation.

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Authors: Elif Derya UBEYLI, Inan GULER

Abstract:

A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.

Keywords: Chaotic signal, Electroencephalogram (EEG) signals, Feature extraction/selection, Lyapunov exponents

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Authors: Tushar Vasant Salunkhe, Sariput M. Nawghare, Maheboobsab B. Nadaf, Sushovan Dutta, J. N. Mandal

Abstract:

The model tests were conducted in the laboratory without and with Plastic recycled polymer in fly ash steep slopes overlaying soft foundation soils like fly ash and powai soil in order to check the stability of steep slope. In this experiment, fly ash is used as a filling material and Plastic Recycled Polymers of diameter = 3mm and length = 4mm were made from waste plastic product (lower grade plastic product). The properties of fly ash and Plastic recycled polymers are determined. From the experiments, load and settlement have measured. From these data, load –settlement curves have reported. It has been observed from test results that load carrying capacity of mixture fly ash with Plastic Recycled Polymers slope is more than that of fly ash slope. The deformation of Plastic Recycled Polymers slope is slightly more than that of fly ash slope. A Finite Element Method (F.E.M.) was also evaluated using PLAXIS 3D version. The failure pattern, deformations and factor of safety are reported based on analytical programme. The results from experimental data and analytical programme are compared and reported.

Keywords: Fly ash, Plastic recycled polymer, Factor of safety, Finite element method (FEM), Bishop’s simplified method.

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Authors: Hazem M. El-Bakry

Abstract:

In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.

Keywords: Boolean Functions, Simplification, KarnoughMap, Implementation of Logic Functions, Modular NeuralNetworks.

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Authors: Leila Vafajoo, Farhad Khorasheh, Mehrnoosh Hamzezadeh Nakhjavani, Moslem Fattahi

Abstract:

In the present study, a procedure was developed to determine the optimum reaction rate constants in generalized Arrhenius form and optimized through the Nelder-Mead method. For this purpose, a comprehensive mathematical model of a fixed bed reactor for dehydrogenation of heavy paraffins over Pt–Sn/Al2O3 catalyst was developed. Utilizing appropriate kinetic rate expressions for the main dehydrogenation reaction as well as side reactions and catalyst deactivation, a detailed model for the radial flow reactor was obtained. The reactor model composed of a set of partial differential equations (PDE), ordinary differential equations (ODE) as well as algebraic equations all of which were solved numerically to determine variations in components- concentrations in term of mole percents as a function of time and reactor radius. It was demonstrated that most significant variations observed at the entrance of the bed and the initial olefin production obtained was rather high. The aforementioned method utilized a direct-search optimization algorithm along with the numerical solution of the governing differential equations. The usefulness and validity of the method was demonstrated by comparing the predicted values of the kinetic constants using the proposed method with a series of experimental values reported in the literature for different systems.

Keywords: Dehydrogenation, Pt-Sn/Al2O3 Catalyst, Modeling, Nelder-Mead, Optimization

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Authors: Lee Suan Chua

Abstract:

This study investigated the effects of thermal treatment on Tualang honey sample in terms of honey colour and heat-induced small metabolites. The heating process was carried out in a temperature controlled water batch at 90oC for 4 hours. The honey samples were put in cylinder tubes with the dimension of 1 cm diameter and 10 cm length for homogenous heat transfer. The results found that the thermal treatment produced not only hydroxylmethylfurfural, but also other harmful substances such as phthalic anhydride and radiolytic byproducts. The degradation of honey protein was due to the detection of free amino acids such as cysteine and phenylalanine in heat-treated honey samples. Sugar dehydration was also occurred because fragmented di-galactose was identified based on the presence of characteristic ions in the mass fragmentation pattern. The honey colour was found getting darker as the heating duration was increased up to 4 hours. Approximately, 60 mm PFund of increment was noticed for the honey colour with the colour change rate of 14.8 mm PFund per hour. Based on the principal component analysis, the score plot clearly shows that the chemical profile of Tualang honey was significantly altered after 2 hours of heating at 90oC.

Keywords: Honey colour, hydroxylmethylfurfural, thermal treatment, Tualang honey.

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