Search results for: image based FE modelling

Authors: Abdullah A. Wardak

Abstract:

This paper describes an interfacing of C and the TMS320C6713 assembly language which is crucially important for many real-time applications. Similarly, interfacing of C with the assembly language of a conventional microprocessor such as MC68000 is presented for comparison. However, it should be noted that the way the C compiler passes arguments among various functions in the TMS320C6713-based environment is totally different from the way the C compiler passes arguments in a conventional microprocessor such as MC68000. Therefore, it is very important for a user of the TMS320C6713-based system to properly understand and follow the register conventions when interfacing C with the TMS320C6713 assembly language subroutine. It should be also noted that in some cases (examples 6-9) the endian-mode of the board needs to be taken into consideration. In this paper, one method is presented in great detail. Other methods will be presented in the future.

Keywords: Assembly language, high level language, interfacing, stack, arguments.

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Authors: Majlinda Fetaji, Alajdin Abazi, Zamir Dika, Bekim Fetaji

Abstract:

The assessment of the efficacy of devised Mobile- Assisted Instructional Modes in Mobile Learning was the focus of this research. The study adopted pre-test, post-test, control group quasi-experimental design. Research instruments were developed, validated and used for collecting data. Findings revealed that the students exposed to Mobile Task Based Learning Mode (MTBLM) in using Mobile-Assisted Instruction (MAI) performed significantly better. The implication of these findings is that, the Audio tutorial and Practice Mode (ATPM) (Stimulus instruments) of MAI had been found better over the other modes used in the study.

Keywords: Mobile-Assisted instructions, Mobile learning, learning instructions, task based learning.

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Authors: Neha Khanduja

Abstract:

This paper presents a comparative analysis of continuously stirred tank reactor (CSTR) control based on adaptive control and optimal tuning of PID control based on particle swarm optimization. In the design of adaptive control, Model reference adaptive control (MRAC) scheme is used, in which the adaptation law have been developed by MIT rule & Lyapunov’s rule. In PSO control parameters of PID controller is tuned by using the concept of particle swarm optimization to get optimized operating point for minimum integral square error (ISE) condition. The results show the adjustment of PID parameters converting into the optimal operating point and the good control response can be obtained by the PSO technique.

Keywords: Model reference adaptive control (MRAC), optimal control, particle swarm optimization (PSO).

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Authors: Yong Wang, Wang Ling Goh, Jung Hyup Lee, Kevin T. C. Chai, Minkyu Je

Abstract:

This paper presents a resonant-based read-out circuit for capacitive pressure sensors. The proposed read-out circuit consists of an LC oscillator and a counter. The circuit detects the capacitance changes of a capacitive pressure sensor by means of frequency shifts from its nominal operation frequency. The proposed circuit is designed in 0.18m CMOS with an estimated power consumption of 43.1mW. Simulation results show that the circuit has a capacitive resolution of 8.06kHz/fF, which enables it for high resolution pressure detection.

Keywords: Capacitance-to-frequency converter, Capacitive pressure sensor, Digital counter, LC oscillator.

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Authors: B.S. Al-Tulaian, M. J. Al-Shannag, A.M. Al-Hozaimy

Abstract:

The development of new construction materials using  recycled plastic is important to both the construction and the plastic  recycling industries. Manufacturing of fibers from industrial or  postconsumer plastic waste is an attractive approach with such  benefits as concrete performance enhancement, and reduced needs  for land filling. The main objective of this study is to investigate the  effect of Plastic fibers obtained locally from recycled waste on plastic  shrinkage cracking of ordinary cement based mortar. Parameters  investigated include: fiber length ranging from 20 to 50mm, and fiber  volume fraction ranging from 0% to 1.5% by volume. The test results  showed significant improvement in crack arresting mechanism and  substantial reduction in the surface area of cracks for the mortar  reinforced with recycled plastic fibers compared to plain mortar.  Furthermore, test results indicated that there was a slight decrease in  compressive strength of mortar reinforced with different lengths and  contents of recycled fibers compared to plain mortar. This study  suggests that adding more than 1% of RP fibers to mortar, can be  used effectively for controlling plastic shrinkage cracking of cement  based mortar, and thus results in waste reduction and resources  conservation.

 

Keywords: Mortar, plastic, shrinkage cracking, compressive strength, RF recycled fibers.

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Authors: Qiaozhen Song

Abstract:

Based on the feature of model disturbances and uncertainty being compensated dynamically in auto – disturbances-rejection-controller (ADRC), a new method using ADRC is proposed for the decoupling control of dispenser longitudinal movement in big flight envelope. Developed from nonlinear model directly, ADRC is especially suitable for dynamic model that has big disturbances. Furthermore, without changing the structure and parameters of the controller in big flight envelope, this scheme can simplify the design of flight control system. The simulation results in big flight envelope show that the system achieves high dynamic performance, steady state performance and the controller has strong robustness.

Keywords: ADRC, ESO, nonlinear system

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Authors: R. Uporn, P. Luangpaiboon

Abstract:

This paper presents a comparative study of statistical methods for the multi-response surface optimization of a cryogenic freezing process. Taguchi design and analysis and steepest ascent methods based on the desirability function were conducted to ascertain the influential factors of a cryogenic freezing process and their optimal levels. The more preferable levels of the set point, exhaust fan speed, retention time and flow direction are set at -90oC, 20 Hz, 18 minutes and Counter Current, respectively. The overall desirability level is 0.7044.

Keywords: Cryogenic Freezing Process, Taguchi Design and Analysis, Response Surface Method, Steepest Ascent Method and Desirability Function Approach.

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Authors: A. Zanj, F. He

Abstract:

In the current paper, a domain independent conduction model compatible for multi-physical system dynamic investigations is suggested. By means of a port-based approach, a classical nonlinear conduction model containing physical states is first represented. A compatible discrete configuration of the thermal domain in line with the elastic domain is then generated through the enhancement of the configuration of the conventional thermal element. The presented simulation results of a sample structure indicate that the suggested conductive model can cover a wide range of dynamic behavior of the thermal domain.

Keywords: Multi-physical domain, conduction model, port-based modeling, dynamic interaction, physical modeling.

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Authors: H. Omrani, P. Gerber

Abstract:

Success is a European project that will implement several clean transport offers in three European cities and evaluate the environmental impacts. The goal of these measures is to improve urban mobility or the displacement of residents inside cities. For e.g. park and ride, electric vehicles, hybrid bus and bike sharing etc. A list of 28 criteria and 60 measures has been established for evaluation of these transport projects. The evaluation criteria can be grouped into: Transport, environment, social, economic and fuel consumption. This article proposes a decision support system based that encapsulates a hybrid approach based on fuzzy logic, multicriteria analysis and belief theory for the evaluation of impacts of urban mobility solutions. A web-based tool called DeSSIA (Decision Support System for Impacts Assessment) has been developed that treats complex data. The tool has several functionalities starting from data integration (import of data), evaluation of projects and finishes by graphical display of results. The tool development is based on the concept of MVC (Model, View, and Controller). The MVC is a conception model adapted to the creation of software's which impose separation between data, their treatment and presentation. Effort is laid on the ergonomic aspects of the application. It has codes compatible with the latest norms (XHTML, CSS) and has been validated by W3C (World Wide Web Consortium). The main ergonomic aspect focuses on the usability of the application, ease of learning and adoption. By the usage of technologies such as AJAX (XML and Java Script asynchrones), the application is more rapid and convivial. The positive points of our approach are that it treats heterogeneous data (qualitative, quantitative) from various information sources (human experts, survey, sensors, model etc.).

Keywords: Decision support tool, hybrid approach, urban mobility.

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Authors: Mousmita Sarma, Krishna Dutta, Kandarpa Kumar Sarma

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Speech corpus is one of the major components in a Speech Processing System where one of the primary requirements is to recognize an input sample. The quality and details captured in speech corpus directly affects the precision of recognition. The current work proposes a platform for speech corpus generation using an adaptive LMS filter and LPC cepstrum, as a part of an ANN based Speech Recognition System which is exclusively designed to recognize isolated numerals of Assamese language- a major language in the North Eastern part of India. The work focuses on designing an optimal feature extraction block and a few ANN based cooperative architectures so that the performance of the Speech Recognition System can be improved.

Keywords: Filter, Feature, LMS, LPC, Cepstrum, ANN.

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Authors: Ahmed Bensenouci

Abstract:

This paper provides the design steps of a robust Linear Matrix Inequality (LMI) based iterative multivariable PID controller whose duty is to drive a sample power system that comprises a synchronous generator connected to a large network via a step-up transformer and a transmission line. The generator is equipped with two control-loops, namely, the speed/power (governor) and voltage (exciter). Both loops are lumped in one where the error in the terminal voltage and output active power represent the controller inputs and the generator-exciter voltage and governor-valve position represent its outputs. Multivariable PID is considered here because of its wide use in the industry, simple structure and easy implementation. It is also preferred in plants of higher order that cannot be reduced to lower ones. To improve its robustness to variation in the controlled variables, H∞-norm of the system transfer function is used. To show the effectiveness of the controller, divers tests, namely, step/tracking in the controlled variables, and variation in plant parameters, are applied. A comparative study between the proposed controller and a robust H∞ LMI-based output feedback is given by its robustness to disturbance rejection. From the simulation results, the iterative multivariable PID shows superiority.

Keywords: Linear matrix inequality, power system, robust iterative PID, robust output feedback control

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

Abstract:

Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: Decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle.

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

Abstract:

Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: Feature selection, mass spectrometry, biomarker discovery, cancer.

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Authors: W. I. Wan Rosli, M. S. Aishah

Abstract:

The grey oyster mushroom, Pleurotus sajor-caju (PSC), is a common edible mushroom and is now grown commercially around the world for food. This fungus has been broadly used as food or food ingredients in various food products for a long time. To enhance the nutritional quality and sensory attributes of bakery-based products, PSC powder is used in the present study to partially replace wheat flour in baked product formulations. The nutrient content and sensory properties of rice-porridge and unleavened bread (paratha) incorporated with various levels of PSC powder were studied. These food items were formulated with either 0%, 2%, 4% or 6% of PSC powder. Results show PSC powder recorded β-glucan at 3.57g/100g. In sensory evaluation, consumers gave higher score to both rice-porridge and paratha bread containing 2-4% PSC compared to those that are not added with PSC powder. The paratha containing 4% PSC powder can be formulated with the intention in improving overall acceptability of paratha bread. Meanwhile, for rice-porridge, consumers prefer the formulated product added with 4% PSC powder. In conclusion, the addition of PSC powder to partially wheat flour can be recommended for the purpose of enhancing nutritional composition and maintaining the acceptability of carbohydrate-based products.

Keywords: Pleurotus sajor-caju (PSC), nutrient contents, sensory evaluation

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Authors: Mohammad Hadi Jalali, Behrooz Shahriari, Mostafa Ghayour, Saeed Ziaei-Rad, Shahram Yousefi

Abstract:

Most flexible rotors can be considered as beam-like structures. In many cases, rotors are modeled as one-dimensional bodies, made basically of beam-like shafts with rigid bodies attached to them. This approach is typical of rotor dynamics, both analytical and numerical, and several rotor dynamic codes, based on the finite element method, follow this trend. In this paper, a finite element model based on Timoshenko beam elements is utilized to analyze the lateral dynamic behavior of a certain rotor-bearing system in operating conditions.

Keywords: Finite element method, Operational deflection shape, Timoshenko beam elements, Unbalance response.

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Authors: W. Phanwanich, O. Kumdee, P. Ritthipravat, Y. Wongsawat

Abstract:

In order to alleviate the mental and physical problems of persons with disabilities, animal-assisted therapy (AAT) is one of the possible modalities that employs the merit of the human-animal interaction. Nevertheless, to achieve the purpose of AAT for persons with severe disabilities (e.g. spinal cord injury, stroke, and amyotrophic lateral sclerosis), real-time animal language interpretation is desirable. Since canine behaviors can be visually notable from its tail, this paper proposes the automatic real-time interpretation of canine tail language for human-canine interaction in the case of persons with severe disabilities. Canine tail language is captured via two 3-axis accelerometers. Directions and frequencies are selected as our features of interests. The novel fuzzy rules based on Gaussian-Trapezoidal model and center of gravity (COG)-based defuzzification method are proposed in order to interpret the features into four canine emotional behaviors, i.e., agitate, happy, scare and neutral as well as its blended emotional behaviors. The emotional behavior model is performed in the simulated dog and has also been evaluated in the real dog with the perfect recognition rate.

Keywords: Animal-assisted therapy (AAT), Persons with disabilities, Canine tail language, Fuzzy emotional behavior model

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Authors: Norisma Idris, Sapiyan Baba, Rukaini Abdullah

Abstract:

Summarizing skills have been introduced to English syllabus in secondary school in Malaysia to evaluate student-s comprehension for a given text where it requires students to employ several strategies to produce the summary. This paper reports on our effort to develop a computer-based summarization assessment system that detects the strategies used by the students in producing their summaries. Sentence decomposition of expert-written summaries is used to analyze how experts produce their summary sentences. From the analysis, we identified seven summarizing strategies and their rules which are then transformed into a set of heuristic rules on how to determine the summarizing strategies. We developed an algorithm based on the heuristic rules and performed some experiments to evaluate and support the technique proposed.

Keywords: Summarizing strategies, heuristic rules, sentencedecomposition.

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Authors: Y. Harold Robinson, M. Rajaram, E. Golden Julie, S. Balaji

Abstract:

In wireless sensor networks, locality and positioning information can be captured using Global Positioning System (GPS). This message can be congregated initially from spot to identify the system. Users can retrieve information of interest from a wireless sensor network (WSN) by injecting queries and gathering results from the mobile sink nodes. Routing is the progression of choosing optimal path in a mobile network. Intermediate node employs permutation of device nodes into teams and generating cluster heads that gather the data from entity cluster’s node and encourage the collective data to base station. WSNs are widely used for gathering data. Since sensors are power-constrained devices, it is quite vital for them to reduce the power utilization. A tree-based data fusion clustering routing algorithm (TBDFC) is used to reduce energy consumption in wireless device networks. Here, the nodes in a tree use the cluster formation, whereas the elevation of the tree is decided based on the distance of the member nodes to the cluster-head. Network simulation shows that this scheme improves the power utilization by the nodes, and thus considerably improves the lifetime.

Keywords: WSN, TBDFC, LEACH, PEGASIS, TREEPSI.

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Authors: Maumita Bhattacharya

Abstract:

Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, many real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function evaluations. Use of evolutionary algorithms in such problem domains is thus practically prohibitive. An attractive alternative is to build meta models or use an approximation of the actual fitness functions to be evaluated. These meta models are order of magnitude cheaper to evaluate compared to the actual function evaluation. Many regression and interpolation tools are available to build such meta models. This paper briefly discusses the architectures and use of such meta-modeling tools in an evolutionary optimization context. We further present two evolutionary algorithm frameworks which involve use of meta models for fitness function evaluation. The first framework, namely the Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model [14] reduces computation time by controlled use of meta-models (in this case approximate model generated by Support Vector Machine regression) to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the metamodel are generated from a single uniform model. This does not take into account uncertain scenarios involving noisy fitness functions. The second model, DAFHEA-II, an enhanced version of the original DAFHEA framework, incorporates a multiple-model based learning approach for the support vector machine approximator to handle noisy functions [15]. Empirical results obtained by evaluating the frameworks using several benchmark functions demonstrate their efficiency

Keywords: Meta model, Evolutionary algorithm, Stochastictechnique, Fitness function, Optimization, Support vector machine.

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Authors: Mohamed A. Mahfouz, M. A. Ismail

Abstract:

This paper introduces new algorithms (Fuzzy relative of the CLARANS algorithm FCLARANS and Fuzzy c Medoids based on randomized search FCMRANS) for fuzzy clustering of relational data. Unlike existing fuzzy c-medoids algorithm (FCMdd) in which the within cluster dissimilarity of each cluster is minimized in each iteration by recomputing new medoids given current memberships, FCLARANS minimizes the same objective function minimized by FCMdd by changing current medoids in such away that that the sum of the within cluster dissimilarities is minimized. Computing new medoids may be effected by noise because outliers may join the computation of medoids while the choice of medoids in FCLARANS is dictated by the location of a predominant fraction of points inside a cluster and, therefore, it is less sensitive to the presence of outliers. In FCMRANS the step of computing new medoids in FCMdd is modified to be based on randomized search. Furthermore, a new initialization procedure is developed that add randomness to the initialization procedure used with FCMdd. Both FCLARANS and FCMRANS are compared with the robust and linearized version of fuzzy c-medoids (RFCMdd). Experimental results with different samples of the Reuter-21578, Newsgroups (20NG) and generated datasets with noise show that FCLARANS is more robust than both RFCMdd and FCMRANS. Finally, both FCMRANS and FCLARANS are more efficient and their outputs are almost the same as that of RFCMdd in terms of classification rate.

Keywords: Data Mining, Fuzzy Clustering, Relational Clustering, Medoid-Based Clustering, Cluster Analysis, Unsupervised Learning.

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Authors: K. Dimitropoulos, N. Grammalidis, I. Gragopoulos, H. Gao, Th. Heuer, M. Weinmann, S. Voit, C. Stockhammer, U. Hartmann, N. Pavlidou

Abstract:

Existing ground movement surveillance technologies at airports are subjected to limitations due to shadowing effects or multiple reflections. Therefore, there is a strong demand for a new sensing technology, which will be cost effective and will provide detection of non-cooperative targets under any weather conditions. This paper aims to present a new intelligent system, developed within the framework of the EC-funded ISMAEL project, which is based on a new magnetic sensing technology and provides detection, tracking and automatic classification of targets moving on the airport surface. The system is currently being installed at two European airports. Initial experimental results under real airport traffic demonstrate the great potential of the proposed system.

Keywords: Air traffic management, magnetic sensors, multitracking, A-SMGCS.

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Authors: Prateek Maheshwari, Nitin Seth, Anoop Kumar Gupta

Abstract:

The objective of present research paper is to highlight the importance of measuring advertisement effectiveness in print media and to develop a conceptual model for advertisement effectiveness. The developed model is based on dimensions on which advertisement effectiveness depends and on the dimensions which are used to measure the effectiveness. An in-depth and extensive literature review is carried out to understand the concept of advertisement effectiveness and its various determinants in context of print media. Based on the insights gained, a conceptual framework for advertisement effectiveness is presented. The model is an attempt to uncover the relatively less explored area of advertisement effectiveness in Indian advertising scenario. It is believed that present work will encourage scholars and academicians to further explore the area and will offer conceptual assistance and a fresh direction in the domain of advertisement effectiveness.

Keywords: Advertisement Effectiveness, Conceptual Model, Effectiveness Dimensions, Print Media.

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Authors: Eric Jiang

Abstract:

As a popular rank-reduced vector space approach, Latent Semantic Indexing (LSI) has been used in information retrieval and other applications. In this paper, an LSI-based content vector model for text classification is presented, which constructs multiple augmented category LSI spaces and classifies text by their content. The model integrates the class discriminative information from the training data and is equipped with several pertinent feature selection and text classification algorithms. The proposed classifier has been applied to email classification and its experiments on a benchmark spam testing corpus (PU1) have shown that the approach represents a competitive alternative to other email classifiers based on the well-known SVM and naïve Bayes algorithms.

Keywords: Feature Selection, Latent Semantic Indexing, Text Classification, Vector Space Model.

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Authors: Shigeaki Sakurai, Ryohei Orihara

Abstract:

This paper proposes a new method for analyzing textual data. The method deals with items of textual data, where each item is described based on various viewpoints. The method acquires 2- class classification models of the viewpoints by applying an inductive learning method to items with multiple viewpoints. The method infers whether the viewpoints are assigned to the new items or not by using the models. The method extracts expressions from the new items classified into the viewpoints and extracts characteristic expressions corresponding to the viewpoints by comparing the frequency of expressions among the viewpoints. This paper also applies the method to questionnaire data given by guests at a hotel and verifies its effect through numerical experiments.

Keywords: Text mining, Multiple viewpoints, Differential analysis, Questionnaire data

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Authors: Smrity Dwivedi

Abstract:

The present paper has revealed the effect of double substrates over a bandwidth performance for planar antennas. The used material has its own importance to get minimum return loss and improved directivity. The author has taken double substrates to enhance the efficiency in terms of gain of antenna. Metamaterial based antenna has its own specific structure which increased the performance of antenna. Improved return loss is -20 dB, and the voltage standing wave ratio (VSWR) is 1.2, which is better than single substrate having return loss of -15 dB and VSWR of 1.4. Complete results are obtained using commercial software CST microwave studio.

Keywords: Metamaterials, return loss, standing wave ratio, directivity, CST microwave studio.

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Authors: Sujoy Das, M. M. Ghosh

Abstract:

The thermal conductivity of a fluid can be significantly enhanced by dispersing nano-sized particles in it, and the resultant fluid is termed as "nanofluid". A theoretical model for estimating the thermal conductivity of a nanofluid has been proposed here. It is based on the mechanism that evenly dispersed nanoparticles within a nanofluid undergo Brownian motion in course of which the nanoparticles repeatedly collide with the heat source. During each collision a rapid heat transfer occurs owing to the solidsolid contact. Molecular dynamics (MD) simulation of the collision of nanoparticles with the heat source has shown that there is a pulselike pick up of heat by the nanoparticles within 20-100 ps, the extent of which depends not only on thermal conductivity of the nanoparticles, but also on the elastic and other physical properties of the nanoparticle. After the collision the nanoparticles undergo Brownian motion in the base fluid and release the excess heat to the surrounding base fluid within 2-10 ms. The Brownian motion and associated temperature variation of the nanoparticles have been modeled by stochastic analysis. Repeated occurrence of these events by the suspended nanoparticles significantly contributes to the characteristic thermal conductivity of the nanofluids, which has been estimated by the present model for a ethylene glycol based nanofluid containing Cu-nanoparticles of size ranging from 8 to 20 nm, with Gaussian size distribution. The prediction of the present model has shown a reasonable agreement with the experimental data available in literature.

Keywords: Brownian dynamics, Molecular dynamics, Nanofluid, Thermal conductivity.

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Authors: Sanjoy Das, Akash Arya, Rishi Pal Singh

Abstract:

Vehicular Ad hoc Network is basically the solution of several problems associated while vehicles are plying on the road. In this paper, we have focused on the detection of imposter node while it has stolen the ID's of the authenticated vehicle in the network. The purpose is to harm the network through imposter messages. Here, we have proposed a protocol namely Imposter Detection based on Location (IDBL), which will store the location coordinate of the each vehicle as the key of the authenticity of the message so that imposter node can be detected. The imposter nodes send messages from a stolen ID and show that it is from an authentic node ID. So, to detect this anomaly, the first location is checked and observed different from original vehicle location. This node is known as imposter node. We have implemented the algorithm through JAVA and tested various types of node distribution and observed the detection probability of imposter node.

Keywords: Authentication, detection, IDBL protocol, imposter node, node detection.

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

Abstract:

Document Analysis is an important research field that aims to gather the information by analyzing the data in documents. As one of the important targets for many fields is to understand what people actually want, sentimental analysis field has been one of the vital fields that are tightly related to the document analysis. This research focuses on analyzing text documents to classify each document according to its opinion. The aim of this research is to detect the emotions from text documents based on enriching the lexicon with adapting their content based on semantic patterns extraction. The proposed approach has been presented, and different experiments are applied by different perspectives to reveal the positive impact of the proposed approach on the classification results.

Keywords: Document analysis, sentimental analysis, emotion detection, WEKA tool, NRC Lexicon.

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Authors: Shonal Singh, Bibhya Sharma, Jito Vanualailai

Abstract:

This paper considers the design of a motion planner that will simultaneously accomplish control and motion planning of a n-link nonholonomic mobile manipulator, wherein, a n-link holonomic manipulator is coupled with a nonholonomic mobile platform, within an obstacle-ridden environment. This planner, derived from the Lyapunov-based control scheme, generates collision-free trajectories from an initial configuration to a final configuration in a constrained environment cluttered with stationary solid objects of different shapes and sizes. We demonstrate the efficiency of the control scheme and the resulting acceleration controllers of the mobile manipulator with results through computer simulations of an interesting scenario.

Keywords: Artificial potential fields, Lyapunov-based control scheme, Lyapunov stability, nonholonomic manipulator, minimum distance technique, kinodynamic constraints.

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Authors: Ali Nourollah, Mohsen Movahedinejad

Abstract:

In this paper a new algorithm to generate random simple polygons from a given set of points in a two dimensional plane is designed. The proposed algorithm uses a genetic algorithm to generate polygons with few vertices. A new merge algorithm is presented which converts any two polygons into a simple polygon. This algorithm at first changes two polygons into a polygonal chain and then the polygonal chain is converted into a simple polygon. The process of converting a polygonal chain into a simple polygon is based on the removal of intersecting edges. The experiments results show that the proposed algorithm has the ability to generate a great number of different simple polygons and has better performance in comparison to celebrated algorithms such as space partitioning and steady growth.

Keywords: Divide and conquer, genetic algorithm, merge polygons, Random simple polygon generation.

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