Search results for: experimental data

Authors: Davide Pierattoni, Ivan Macor, Pier Luca Montessoro

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In the recent years multimedia traffic and in particular VoIP services are growing dramatically. We present a new algorithm to control the resource utilization and to optimize the voice codec selection during SIP call setup on behalf of the traffic condition estimated on the network path. The most suitable methodologies and the tools that perform realtime evaluation of the available bandwidth on a network path have been integrated with our proposed algorithm: this selects the best codec for a VoIP call in function of the instantaneous available bandwidth on the path. The algorithm does not require any explicit feedback from the network, and this makes it easily deployable over the Internet. We have also performed intensive tests on real network scenarios with a software prototype, verifying the algorithm efficiency with different network topologies and traffic patterns between two SIP PBXs. The promising results obtained during the experimental validation of the algorithm are now the basis for the extension towards a larger set of multimedia services and the integration of our methodology with existing PBX appliances.

Keywords: Integrated voice-data communication, computernetwork performance, resource optimization.

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: Analysis of optimization, artificial intelligence-based optimization, optimization for learning and data analysis, global optimization.

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Authors: Shiuh-Jer Huang, Ming-Tien Su

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Since the driving speed and control accuracy of commercial optical disk are increasing significantly, it needs an efficient controller to monitor the track seeking and following operations of the servo system for achieving the desired data extracting response. The nonlinear behaviors of the actuator and servo system of the optical disk drive will influence the laser spot positioning. Here, the model-free fuzzy control scheme is employed to design the track seeking servo controller for a d.c. motor driving optical disk drive system. In addition, the sliding model control strategy is introduced into the fuzzy control structure to construct a 1-D adaptive fuzzy rule intelligent controller for simplifying the implementation problem and improving the control performance. The experimental results show that the steady state error of the track seeking by using this fuzzy controller can maintain within the track width (1.6 μm ). It can be used in the track seeking and track following servo control operations.

Keywords: Fuzzy control, gain tuning and optical disk drive.

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Authors: M. Govindarajan, R. M.Chandrasekaran

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Text data mining is a process of exploratory data analysis. Classification maps data into predefined groups or classes. It is often referred to as supervised learning because the classes are determined before examining the data. This paper describes proposed radial basis function Classifier that performs comparative crossvalidation for existing radial basis function Classifier. The feasibility and the benefits of the proposed approach are demonstrated by means of data mining problem: direct Marketing. Direct marketing has become an important application field of data mining. Comparative Cross-validation involves estimation of accuracy by either stratified k-fold cross-validation or equivalent repeated random subsampling. While the proposed method may have high bias; its performance (accuracy estimation in our case) may be poor due to high variance. Thus the accuracy with proposed radial basis function Classifier was less than with the existing radial basis function Classifier. However there is smaller the improvement in runtime and larger improvement in precision and recall. In the proposed method Classification accuracy and prediction accuracy are determined where the prediction accuracy is comparatively high.

Keywords: Text Data Mining, Comparative Cross-validation, Radial Basis Function, runtime, accuracy.

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Authors: S. Šupić, M. Malešev, V. Radonjanin, M. Radeka, M. Laban

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The production of low cost and environmentally friendly products represents an important step for developing countries. Biomass is one of the largest renewable energy sources, and Serbia is among the top European countries in terms of the amount of available and unused biomass. Substituting cement with the ashes obtained by the combustion of biomass would reduce the negative impact of concrete industry on the environment and would provide a waste valorization by the reuse of this type of by-product in mortars and concretes manufacture. The study contains data on physical properties, chemical characteristics and pozzolanic properties of obtained biomass ashes: wheat straw ash and mixture of wheat and soya straw ash in Serbia, which were, later, used as supplementary cementitious materials in preparation of mortars. Experimental research of influence of biomass ashes on physical and mechanical properties of cement mortars was conducted. The results indicate that the biomass ashes can be successfully used in mortars as substitutes of cement without compromising their physical and mechanical performances.

Keywords: Biomass, ash, cementitious material, mortar.

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Authors: Setareh Shekarsaraei, Marjan Moridi, Nasser L. Hadipour

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In this study, nuclear magnetic resonance spectroscopy and nuclear quadrupole resonance spectroscopy parameters of 14N (Nitrogen in imidazole ring) in N–H…O hydrogen bonding for Histidine hydrochloride monohydrate were calculated via density functional theory. We considered a five-molecule model system of Histidine hydrochloride monohydrate. Also we examined the trends of environmental effect on hydrogen bonds as well as cooperativity. The functional used in this research is M06-2X which is a good functional and the obtained results has shown good agreement with experimental data. This functional was applied to calculate the NMR and NQR parameters. Some correlations among NBO parameters, NMR and NQR parameters have been studied which have shown the existence of strong correlations among them. Furthermore, the geometry optimization has been performed using M062X/6-31++G(d,p) method. In addition, in order to study cooperativity and changes in structural parameters, along with increase in cluster size, natural bond orbitals have been employed.

Keywords: Hydrogen bonding, Density Functional Theory (DFT), Natural bond Orbitals (NBO), cooperativity effects.

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Authors: Ginhsuan Li, Chiuyun Hung, Desheng Chen, Yiwen Wang

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Application-Specific Instruction (ASI ) set Processors (ASIP) have become an important design choice for embedded systems due to runtime flexibility, which cannot be provided by custom ASIC solutions. One major bottleneck in maximizing ASIP performance is the limitation on the data bandwidth between the General Purpose Register File (GPRF) and ASIs. This paper presents the Implicit Registers (IRs) to provide the desirable data bandwidth. An ASI Input/Output model is proposed to formulate the overheads of the additional data transfer between the GPRF and IRs, therefore, an IRs allocation algorithm is used to achieve the better performance by minimizing the number of extra data transfer instructions. The experiment results show an up to 3.33x speedup compared to the results without using IRs.

Keywords: Application-Specific Instruction-set Processors, data bandwidth, configurable processor, implicit register.

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Authors: Hiroyuki Ohsaki, Makoto Imase

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In Grid computing, a data transfer protocol called GridFTP has been widely used for efficiently transferring a large volume of data. Currently, two versions of GridFTP protocols, GridFTP version 1 (GridFTP v1) and GridFTP version 2 (GridFTP v2), have been proposed in the GGF. GridFTP v2 supports several advanced features such as data streaming, dynamic resource allocation, and checksum transfer, by defining a transfer mode called X-block mode. However, in the literature, effectiveness of GridFTP v2 has not been fully investigated. In this paper, we therefore quantitatively evaluate performance of GridFTP v1 and GridFTP v2 using mathematical analysis and simulation experiments. We reveal the performance limitation of GridFTP v1, and quantitatively show effectiveness of GridFTP v2. Through several numerical examples, we show that by utilizing the data streaming feature, the average file transfer time of GridFTP v2 is significantly smaller than that of GridFTP v1.

Keywords: Grid Computing, GridFTP, Performance Evaluation, Queuing Theory.

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Authors: K. Indra Gandhi

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Wireless Sensor Networks (WSNs) have always been characterized for application-specific sensing, relaying and collection of information for further analysis. However, software development was not considered as a separate entity in this process of data collection which has posed severe limitations on the software development for WSN. Software development for WSN is a complex process since the components involved are data-driven, network-driven and application-driven in nature. This implies that there is a tremendous need for the separation of concern from the software development perspective. A layered approach for developing data acquisition design based on Model Driven Development (MDD) has been proposed as the sensed data collection process itself varies depending upon the application taken into consideration. This work focuses on the layered view of the data acquisition process so as to ease the software point of development. A metamodel has been proposed that enables reusability and realization of the software development as an adaptable component for WSN systems. Further, observing users perception indicates that proposed model helps in improving the programmer's productivity by realizing the collaborative system involved.

Keywords: Model-driven development, wireless sensor networks, data acquisition, separation of concern, layered design.

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Authors: G. Santamato, M. Solazzi, A. Frisoli

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Systems for detection of damages in railway pantographs effectively reduce the cost of maintenance and improve time scheduling. In this paper, we present an approach to design a monitoring tool fitting strong customer requirements such as portability and ease of use. Pantograph has been modeled to estimate its dynamical properties, since no data are available. With the aim to focus on suspensions health, a two Degrees of Freedom (DOF) scheme has been adopted. Parameters have been calculated by means of analytical dynamics. A Finite Element Method (FEM) modal analysis verified the former model with an acceptable error. The detection strategy seeks phase-plots topology alteration, induced by defects. In order to test the suitability of the method, leakage in the dashpot was simulated on the lumped model. Results are interesting because changes in phase plots are more appreciable than frequency-shift. Further calculations as well as experimental tests will support future developments of this smart strategy.

Keywords: Pantograph models, phase-plots, structural health monitoring, vibration-based condition monitoring.

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Authors: Yeo Kyeong Lee, Hae Won Min, Ji Yeon Kang, Hee Sun Kim, Yeong Soo Shin

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In recent years, fire accidents have been steadily increased and the amount of property damage caused by the accidents has gradually raised. Damaging building structure, fire incidents bring about not only such property damage but also strength degradation and member deformation. As a result, the building structure undermines its structural ability. Examining the degradation and the deformation is very important because reusing the building is more economical than reconstruction. Therefore, engineers need to investigate the strength degradation and member deformation well, and make sure that they apply right rehabilitation methods. This study aims at evaluating deformation characteristics of fire damaged and rehabilitated normal strength concrete beams through both experiments and finite element analyses. For the experiments, control beams, fire damaged beams and rehabilitated beams are tested to examine deformation characteristics. Ten test beam specimens with compressive strength of 21MPa are fabricated and main test variables are selected as cover thickness of 40mm and 50mm and fire exposure time of 1 hour or 2 hours. After heating, fire damaged beams are air-recurred for 2 months and rehabilitated beams are repaired with polymeric cement mortar after being removed the fire damaged concrete cover. All beam specimens are tested under four points loading. FE analyses are executed to investigate the effects of main parameters applied to experimental study. Test results show that both maximum load and stiffness of the rehabilitated beams are higher than those of the fire damaged beams. In addition, predicted structural behaviors from the analyses also show good rehabilitation effect and the predicted load-deflection curves are similar to the experimental results. For the further, the proposed analytical method can be used to predict deformation characteristics of fire damaged and rehabilitated concrete beams without suffering from time and cost consuming of experimental process.

Keywords: Fire, Normal strength concrete, Rehabilitation, Reinforced concrete beam.

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Authors: Roza Dastres, Mohsen Soori

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In order to electronically exchange information between network users in the web of data, different software such as outlook is presented. So, the traffic of users on a site or even the floors of a building can be decreased as a result of applying a secure and reliable data sharing software. It is essential to provide a fast, secure and reliable network system in the data sharing webs to create an advanced communication systems in the users of network. In the present research work, different encoding methods and algorithms in data sharing systems is studied in order to increase security of data sharing systems by preventing the access of hackers to the transferred data. To increase security in the networks, the possibility of textual conversation between customers of a local network is studied. Application of the encryption and decryption algorithms is studied in order to increase security in networks by preventing hackers from infiltrating. As a result, a reliable and secure communication system between members of a network can be provided by preventing additional traffic in the website environment in order to increase speed, accuracy and security in the network and web systems of data sharing.

Keywords: Secure Socket Layer, Security of networks.

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Authors: Abeer K. Jameel, Harry Evdorides

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Iraq is a middle income country where the road safety issue is considered one of the leading causes of deaths. To control the road risk issue, the Iraqi Ministry of Planning, General Statistical Organization started to organise a collection system of traffic accidents data with details related to their causes and severity. These data are published as an annual report. In this paper, a review of the available crash data in Iraq will be presented. The available data represent the rate of accidents in aggregated level and classified according to their types, road users’ details, and crash severity, type of vehicles, causes and number of causalities. The review is according to the types of models used in road safety studies and research, and according to the required road safety data in the road constructions tasks. The available data are also compared with the road safety dataset published in the United Kingdom as an example of developed country. It is concluded that the data in Iraq are suitable for descriptive and exploratory models, aggregated level comparison analysis, and evaluation and monitoring the progress of the overall traffic safety performance. However, important traffic safety studies require disaggregated level of data and details related to the factors of the likelihood of traffic crashes. Some studies require spatial geographic details such as the location of the accidents which is essential in ranking the roads according to their level of safety, and name the most dangerous roads in Iraq which requires tactic plan to control this issue. Global Road safety agencies interested in solve this problem in low and middle-income countries have designed road safety assessment methodologies which are basing on the road attributes data only. Therefore, in this research it is recommended to use one of these methodologies.

Keywords: Data availability, Iraq, road safety.

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Authors: Keqin Li

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Given a parallel program to be executed on a heterogeneous computing system, the overall execution time of the program is determined by a schedule. In this paper, we analyze the worst-case performance of the list scheduling algorithm for scheduling tasks of a parallel program in a mixed-machine heterogeneous computing system such that the total execution time of the program is minimized. We prove tight lower and upper bounds for the worst-case performance ratio of the list scheduling algorithm. We also examine the average-case performance of the list scheduling algorithm. Our experimental data reveal that the average-case performance of the list scheduling algorithm is much better than the worst-case performance and is very close to optimal, except for large systems with large heterogeneity. Thus, the list scheduling algorithm is very useful in real applications.

Keywords: Average-case performance, list scheduling algorithm, mixed-machine heterogeneous computing system, worst-case performance.

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Authors: A. Lauvray, F. Poulhaon, P. Michaud, P. Joyot, E. Duc

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Additive Friction Stir Manufacturing, or AFSM, is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. There is still a lack in understanding of the physical phenomena taking place during the process. This research aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system due to pure friction. An analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable, due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes through a numerical modeling followed by an experimental validation to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, frictional heat generation, process

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Authors: Yazhi Huang, Jing Yang, Dingge Ying, Yan Zhang, Vorasuk Shotelersuk, Nattiya Hirankarn, Pak Chung Sham, Yu Lung Lau, Wanling Yang

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Human leukocyte antigen (HLA) typing from next generation sequencing (NGS) data has the potential for applications in clinical laboratories and population genetic studies. Here we introduce a novel technique for HLA typing from NGS data based on read-mapping using a comprehensive reference panel containing all known HLA alleles and de novo assembly of the gene-specific short reads. An accurate HLA typing at high-digit resolution was achieved when it was tested on publicly available NGS data, outperforming other newly-developed tools such as HLAminer and PHLAT.

Keywords: Human leukocyte antigens, next generation sequencing, whole exome sequencing, HLA typing.

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Authors: Renáta Iváncsy, Sándor Juhász

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Web usage mining has become a popular research area, as a huge amount of data is available online. These data can be used for several purposes, such as web personalization, web structure enhancement, web navigation prediction etc. However, the raw log files are not directly usable; they have to be preprocessed in order to transform them into a suitable format for different data mining tasks. One of the key issues in the preprocessing phase is to identify web users. Identifying users based on web log files is not a straightforward problem, thus various methods have been developed. There are several difficulties that have to be overcome, such as client side caching, changing and shared IP addresses and so on. This paper presents three different methods for identifying web users. Two of them are the most commonly used methods in web log mining systems, whereas the third on is our novel approach that uses a complex cookie-based method to identify web users. Furthermore we also take steps towards identifying the individuals behind the impersonal web users. To demonstrate the efficiency of the new method we developed an implementation called Web Activity Tracking (WAT) system that aims at a more precise distinction of web users based on log data. We present some statistical analysis created by the WAT on real data about the behavior of the Hungarian web users and a comprehensive analysis and comparison of the three methods

Keywords: Data preparation, Tracking individuals, Web useridentification, Web usage mining

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Authors: N. Moghadam, H. Sadeghi

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In this paper a novel scheme for watermarking digital audio during its compression to MPEG-1 Layer III format is proposed. For this purpose we slightly modify some of the selected MDCT coefficients, which are used during MPEG audio compression procedure. Due to the possibility of modifying different MDCT coefficients, there will be different choices for embedding the watermark into audio data, considering robustness and transparency factors. Our proposed method uses a genetic algorithm to select the best coefficients to embed the watermark. This genetic selection is done according to the parameters that are extracted from the perceptual content of the audio to optimize the robustness and transparency of the watermark. On the other hand the watermark security is increased due to the random nature of the genetic selection. The information of the selected MDCT coefficients that carry the watermark bits, are saves in a database for future extraction of the watermark. The proposed method is suitable for online MP3 stores to pursue illegal copies of musical artworks. Experimental results show that the detection ratio of the watermarks at the bitrate of 128kbps remains above 90% while the inaudibility of the watermark is preserved.

Keywords: Content-Based Audio Watermarking, Genetic AudioWatermarking.

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Authors: Mohd K. Yunus, Murni M. Ahmad, Abrar Inayat, Suzana Yusup

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Due to the environmental and price issues of current energy crisis, scientists and technologists around the globe are intensively searching for new environmentally less-impact form of clean energy that will reduce the high dependency on fossil fuel. Particularly hydrogen can be produced from biomass via thermochemical processes including pyrolysis and gasification due to the economic advantage and can be further enhanced through in-situ carbon dioxide removal using calcium oxide. This work focuses on the synthesis and development of the flowsheet for the enhanced biomass gasification process in PETRONAS-s iCON process simulation software. This hydrogen prediction model is conducted at operating temperature between 600 to 1000oC at atmospheric pressure. Effects of temperature, steam-to-biomass ratio and adsorbent-to-biomass ratio were studied and 0.85 mol fraction of hydrogen is predicted in the product gas. Comparisons of the results are also made with experimental data from literature. The preliminary economic potential of developed system is RM 12.57 x 106 which equivalent to USD 3.77 x 106 annually shows economic viability of this process.

Keywords: Biomass, Gasification, Hydrogen, iCON.

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Authors: Mohammadreza Amini, Omid Moradtalab, Ebadollah Zohrevandi

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In real-time networks a large number of application programs are relying on video data and heterogeneous data transmission techniques. The aim of this research is presenting a method for end-to-end vouch quality service in surface applicationlayer for sending video data in comparison form in wireless heterogeneous networks. This method tries to improve the video sending over the wireless heterogeneous networks with used techniques in surface layer, link and application. The offered method is showing a considerable improvement in quality observing by user. In addition to this, other specifications such as shortage of data load that had require to resending and limited the relation period length to require time for second data sending, help to be used the offered method in the wireless devices that have a limited energy. The presented method and the achieved improvement is simulated and presented in the NS-2 software.

Keywords: Heterogeneous wireless networks, adaptation mechanism, multi-level, Handoff, stop mechanism, graceful degrades, application layer.

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Authors: Jinsuk Yang, Choongjae Joo, Kyoungsu Oh

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Existing methods in which the animation data of all frames are stored and reproduced as with vertex animation cannot be used in mobile device environments because these methods use large amounts of the memory. So 3D animation data reduction methods aimed at solving this problem have been extensively studied thus far and we propose a new method as follows. First, we find and remove frames in which motion changes are small out of all animation frames and store only the animation data of remaining frames (involving large motion changes). When playing the animation, the removed frame areas are reconstructed using the interpolation of the remaining frames. Our key contribution is to calculate the accelerations of the joints of individual frames and the standard deviations of the accelerations using the information of joint locations in the relevant 3D model in order to find and delete frames in which motion changes are small. Our methods can reduce data sizes by approximately 50% or more while providing quality which is not much lower compared to original animations. Therefore, our method is expected to be usefully used in mobile device environments or other environments in which memory sizes are limited.

Keywords: Data Reduction, Interpolation, Vertex Animation, 3D Animation.

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Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other.

As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO.

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Authors: P.S. Prakash, S. Selvan

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IP networks are evolving from data communication infrastructure into many real-time applications such as video conferencing, IP telephony and require stringent Quality of Service (QoS) requirements. A rudimentary issue in QoS routing is to find a path between a source-destination pair that satisfies two or more endto- end constraints and termed to be NP hard or complete. In this context, we present an algorithm Multi Constraint Path Problem Version 3 (MCPv3), where all constraints are approximated and return a feasible path in much quicker time. We present another algorithm namely Delay Coerced Multi Constrained Routing (DCMCR) where coerce one constraint and approximate the remaining constraints. Our algorithm returns a feasible path, if exists, in polynomial time between a source-destination pair whose first weight satisfied by the first constraint and every other weight is bounded by remaining constraints by a predefined approximation factor (a). We present our experimental results with different topologies and network conditions.

Keywords: Routing, Quality-of-Service (QoS), additive constraints, shortest path, delay coercion.

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Authors: Sabah I. Wais, Raghad Y. Mohammed, Sedki O. Yousif

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The influence of axial magnetic field (B=0.48 T) on the variation of ionization efficiency coefficient h and secondary electron emission coefficient g with respect to reduced electric field E/P is studied at a new range of plane-parallel electrode spacing (0< d< 20 cm) and different nitrogen working pressure between 0.5-20 Pa. The axial magnetic field is produced from an inductive copper coil of radius 5.6 cm. The experimental data of breakdown voltage is adopted to estimate the mean Paschen curves at different working features. The secondary electron emission coefficient is calculated from the mean Paschen curve and used to determine the minimum breakdown voltage. A reduction of discharge voltage of about 25% is investigated by the applied of axial magnetic field. At high interelectrode spacing, the effect of axial magnetic field becomes more significant for the obtained values of h but it was less for the values of g.

Keywords: Paschen curve, Townsend coefficient, Secondaryelectron emission, Magnetic field, Minimum breakdown voltage.

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Authors: Myung-Won Lee, Keun-Chang Kwak

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation.

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Authors: Fan Ye

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Adverse weather conditions, particularly those with low visibility, are critical to the driving tasks. However, the direct relationship between visibility distances and traffic flow/roadway safety is uncertain due to the limitation of visibility data availability. The recent growth of deployment of Road Weather Information Systems (RWIS) makes segment-specific visibility information available which can be integrated with other Intelligent Transportation System, such as automated warning system and variable speed limit, to improve mobility and safety. Before applying the RWIS visibility measurements in traffic study and operations, it is critical to validate the data. Therefore, an attempt was made in the paper to examine the validity and viability of RWIS visibility data by comparing visibility measurements among RWIS, airport weather stations, and weather information recorded by police in crash reports, based on Ohio data. The results indicated that RWIS visibility measurements were significantly different from airport visibility data in Ohio, but no conclusion regarding the reliability of RWIS visibility could be drawn in the consideration of no verified ground truth in the comparisons. It was suggested that more objective methods are needed to validate the RWIS visibility measurements, such as continuous in-field measurements associated with various weather events using calibrated visibility sensors.

Keywords: Low visibility, RWIS, traffic safety, visibility.

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Authors: K. Bensafia, A. Mansour, G. Le Maillot, B. Clement, O. Reynet, P. Ariès, S. Haddab

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This paper presents a system designed for wireless acquisition, the recording of electrocardiogram (ECG) signals and the monitoring of the heart’s health during surgery. This wireless recording system allows us to visualize and monitor the state of the heart’s health during a surgery, even if the patient is moved from the operating theater to post anesthesia care unit. The acquired signal is transmitted via a Bluetooth unit to a PC where the data are displayed, stored and processed. To test the reliability of our system, a comparison between ECG signals processed by a conventional ECG monitoring system (Datex-Ohmeda) and by our wireless system is made. The comparison is based on the shape of the ECG signal, the duration of the QRS complex, the P and T waves, as well as the position of the ST segments with respect to the isoelectric line. The proposed system is presented and discussed. The results have confirmed that the use of Bluetooth during surgery does not affect the devices used and vice versa. Pre- and post-processing steps are briefly discussed. Experimental results are also provided.

Keywords: Electrocardiography, monitoring, surgery, wireless system.

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Authors: T. Suresh Kumar, M. Arthanari, N. Shanthi

Abstract:

Nowadays, the Web has become one of the most pervasive platforms for information change and retrieval. It collects the suitable and perfectly fitting information from websites that one requires. Data mining is the form of extracting data’s available in the internet. Web mining is one of the elements of data mining Technique, which relates to various research communities such as information recovery, folder managing system and simulated intellects. In this Paper we have discussed the concepts of Web mining. We contain generally focused on one of the categories of Web mining, specifically the Web Content Mining and its various farm duties. The mining tools are imperative to scanning the many images, text, and HTML documents and then, the result is used by the various search engines. We conclude by presenting a comparative table of these tools based on some pertinent criteria.

Keywords: Data Mining, Web Mining, Web Content Mining, Mining Tools, Information retrieval.

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Authors: Ping Du, Masaki Sagehashi, Akihiko Terada, Masaaki Hosomi

Abstract:

Prediction of benzene transport in soil and volatilization from soil to the atmosphere is important for the preservation of human health and management of contaminated soils. The adequacy of a simple numerical model, assuming two-phase diffusion and equilibrium of liquid/solid adsorption, was investigated by experimental data of benzene concentration in a flux chamber (with headspace) where Andosol and sand were filled. Adsorption experiment for liquid phase was performed to determine an adsorption coefficient. Furthermore, adequacy of vapor phase adsorption was also studied through two runs of experiment using sand with different water content. The results show that the model adequately predicted benzene transport and volatilization from Andosol and sand with water content of 14.0%. In addition, the experiment additionally revealed that vapor phase adsorption should be considered in diffusion model for sand with very low water content.

Keywords: Benzene; Transport Model, Adsorption, Soil Contaminant.

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Authors: Myint Myint Yi, Khin Sandar Linn, Marlar Kyaw

Abstract:

This paper proposed a novel model for short term load forecast (STLF) in the electricity market. The prior electricity demand data are treated as time series. The model is composed of several neural networks whose data are processed using a wavelet technique. The model is created in the form of a simulation program written with MATLAB. The load data are treated as time series data. They are decomposed into several wavelet coefficient series using the wavelet transform technique known as Non-decimated Wavelet Transform (NWT). The reason for using this technique is the belief in the possibility of extracting hidden patterns from the time series data. The wavelet coefficient series are used to train the neural networks (NNs) and used as the inputs to the NNs for electricity load prediction. The Scale Conjugate Gradient (SCG) algorithm is used as the learning algorithm for the NNs. To get the final forecast data, the outputs from the NNs are recombined using the same wavelet technique. The model was evaluated with the electricity load data of Electronic Engineering Department in Mandalay Technological University in Myanmar. The simulation results showed that the model was capable of producing a reasonable forecasting accuracy in STLF.

Keywords: Neural network, Load forecast, Time series, wavelettransform.

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