Search results for: Fully fuzzy linear system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10397

Search results for: Fully fuzzy linear system

3167 Simulation Tools for Fixed Point DSP Algorithms and Architectures

Authors: K. B. Cullen, G. C. M. Silvestre, N. J. Hurley

Abstract:

This paper presents software tools that convert the C/Cµ floating point source code for a DSP algorithm into a fixedpoint simulation model that can be used to evaluate the numericalperformance of the algorithm on several different fixed pointplatforms including microprocessors, DSPs and FPGAs. The tools use a novel system for maintaining binary point informationso that the conversion from floating point to fixed point isautomated and the resulting fixed point algorithm achieves maximum possible precision. A configurable architecture is used during the simulation phase so that the algorithm can produce a bit-exact output for several different target devices.

Keywords: DSP devices, DSP algorithm, simulation model, software

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3166 Genetic Mining: Using Genetic Algorithm for Topic based on Concept Distribution

Authors: S. M. Khalessizadeh, R. Zaefarian, S.H. Nasseri, E. Ardil

Abstract:

Today, Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to text classification, summarization and information retrieval system in text mining process. This researches show a better performance due to the nature of Genetic Algorithm. In this paper a new algorithm for using Genetic Algorithm in concept weighting and topic identification, based on concept standard deviation will be explored.

Keywords: Genetic Algorithm, Text Mining, Term Weighting, Concept Extraction, Concept Distribution.

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3165 TheAnalyzer: Clustering-Based System for Improving Business Productivity by Analyzing User Profiles to Enhance Human-Computer Interaction

Authors: D. S. A. Nanayakkara, K. J. P. G. Perera

Abstract:

E-commerce platforms have revolutionized the shopping experience, offering convenient ways for consumers to make purchases. To improve interactions with customers and optimize marketing strategies, it is essential for businesses to understand user behavior, preferences, and needs on these platforms. This paper focuses on recommending businesses to customize interactions with users based on their behavioral patterns, leveraging data-driven analysis and machine learning techniques. Businesses can improve engagement and boost the adoption of e-commerce platforms by aligning behavioral patterns with user goals of usability and satisfaction. We propose TheAnalyzer, a clustering-based system designed to enhance business productivity by analyzing user-profiles and improving human-computer interaction. TheAnalyzer seamlessly integrates with business applications, collecting relevant data points based on users' natural interactions without additional burdens such as questionnaires or surveys. It defines five key user analytics as features for its dataset, which are easily captured through users' interactions with e-commerce platforms. This research presents a study demonstrating the successful distinction of users into specific groups based on the five key analytics considered by TheAnalyzer. With the assistance of domain experts, customized business rules can be attached to each group, enabling TheAnalyzer to influence business applications and provide an enhanced personalized user experience. The outcomes are evaluated quantitatively and qualitatively, demonstrating that utilizing TheAnalyzer’s capabilities can optimize business outcomes, enhance customer satisfaction, and drive sustainable growth. The findings of this research contribute to the advancement of personalized interactions in e-commerce platforms. By leveraging user behavioral patterns and analyzing both new and existing users, businesses can effectively tailor their interactions to improve customer satisfaction, loyalty and ultimately drive sales.

Keywords: Data clustering, data standardization, dimensionality reduction, human-computer interaction, user profiling.

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3164 A Descriptive Study on Syrian Entrepreneurs in Turkey

Authors: Rudainah Alkhazam, Özlem Yaşar Uğurlu

Abstract:

Immigrant entrepreneurship arises from the start of entrepreneurial activity by immigrants in the country they relocate to. The future prosperity and stability of the refugee-hosting countries depends on the mutual social and economic benefits between the residents and the refugees. Syrian refugees and workers in host countries necessitate efforts to assist their residents and refugees in meeting their daily needs, contributing lawfully to local and possibly regional economies through trade, and instilling hope in their future. This study investigates the effects of Syrian refugee entrepreneurs on host communities' business sectors, focusing on Turkey. Specifically, we examine entrepreneurship in general and its role in the country's economy. Because Turkey is the most popular resettlement destination for Syrian refugees, this study will shed light on the challenges of successful migrant entrepreneurship in Turkey and their role in the business sector. The research relies on a mixed-method approach which helps identify recurring themes, favorable results, and conflicting results across methods, allowing us to draw accurate conclusions. The study will adopt a quantitative method in collecting numerical data from Syrian refugees in Turkey. The self-administered survey would be translated into Arabic to ensure that the respondents understood the questions and possible replies. The research will use survey questionnaires to gather the majority of the data. These surveys would have closed-ended questions with nominal ratio and Likert scales. The data will be analyzed using linear regression and the Statistical Package for Social Sciences (SPSS) to ascertain the role of Syrian entrepreneurs in the business sectors of Turkey. The research will use the findings to make future recommendations. Syrian entrepreneurs, among the migrant entrepreneurs, contribute to the labor market, the majority of whom are young people. This research noted the significant participation of Syrian immigrant women in the entrepreneurship sector. The previous experience of Syrians in the field of trade and running their own business plays a vital role in the success of their business in the host countries. The study shows that Syrian entrepreneurs could integrate effectively into the various Turkish business sectors and could rely on themselves, open and manage their projects, and market them in the Turkish market. Syrian entrepreneurs consider that the investment and labor laws, commercial arrangements, and facilities for obtaining financial resources in Turkey need to be more flexible and available to immigrant entrepreneurs.

Keywords: Entrepreneurship, immigration, Syrian, Turkey, refugees, investors, socio-economic benefits, unemployment.

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3163 Assessing Water Quality Using GIS: The Case of Northern Lebanon Miocene Aquifer

Authors: M. Saba, A. Iaaly, E. Carlier, N. Georges

Abstract:

This research focuses on assessing the ground water quality of Northern Lebanon affected by saline water intrusion. The chemical, physical and microbiological parameters were collected in various seasons spanning over the period of two years. Results were assessed using Geographic Information System (GIS) due to its visual capabilities in presenting the pollution extent in the studied region. Future projections of the excessive pumping were also simulated using GIS in order to assess the extent of the problem of saline intrusion in the near future.

Keywords: GIS, saline water, quality control, drinkable water quality standards, pumping.

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3162 A Multimodal Approach for Biometric Authentication with Multiple Classifiers

Authors: Sorin Soviany, Cristina Soviany, Mariana Jurian

Abstract:

The paper presents a multimodal approach for biometric authentication, based on multiple classifiers. The proposed solution uses a post-classification biometric fusion method in which the biometric data classifiers outputs are combined in order to improve the overall biometric system performance by decreasing the classification error rates. The paper shows also the biometric recognition task improvement by means of a carefully feature selection, as much as not all of the feature vectors components support the accuracy improvement.

Keywords: biometric fusion, multiple classifiers

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3161 Development of a Secured Telemedical System Using Biometric Feature

Authors: O. Iyare, A. H. Afolayan, O. T. Oluwadare, B. K. Alese

Abstract:

Access to advanced medical services has been one of the medical challenges faced by our present society especially in distant geographical locations which may be inaccessible. Then the need for telemedicine arises through which live videos of a doctor can be streamed to a patient located anywhere in the world at any time. Patients’ medical records contain very sensitive information which should not be made accessible to unauthorized people in order to protect privacy, integrity and confidentiality. This research work focuses on a more robust security measure which is biometric (fingerprint) as a form of access control to data of patients by the medical specialist/practitioner.

Keywords: Biometrics, telemedicine, privacy, patient information.

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3160 Treatment of Wool Scouring Waste Using Anaerobic Digestion with and without Chemicals Addition

Authors: M. Z. Othman

Abstract:

The aim of this study was to investigate the effectiveness of anaerobic digestion for the treatment of wool scouring wastes. The experiments design comprised three ratios of waste (W) to seed(S) (W:S) of 25:75, 50:50 and 75:25, corresponding to 1.9. 1.7 and 1.5g tCOD/g TS, respectively, with or without chemicals addition. NH4Cl was added to the reactors as a source for nitrogen to achieve C:N:P of 420:14:3. A cationic flocculent was added at 0.5 and 0.75% to enhance flocculation of sludge. The results showed that the reactors that received W:S at a ratio of 25:75 produced the largest volume of biogas. The final soluble COD (sCOD) was below the limits for discharge to the sewer system.

Keywords: Anaerobic digestion, wool processing waste, organicloading, biogas.

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3159 Minimum Energy of a Prismatic Joint with out: Actuator: Application on RRP Robot

Authors: Tawiwat V., Tosapolporn P., Kedit J.

Abstract:

This research proposes the state of art on how to control or find the trajectory paths of the RRP robot when the prismatic joint is malfunction. According to this situation, the minimum energy of the dynamic optimization is applied. The RRP robot or similar systems have been used in many areas such as fire fighter truck, laboratory equipment and military truck for example a rocket launcher. In order to keep on task that assigned, the trajectory paths must be computed. Here, the open loop control is applied and the result of an example show the reasonable solution which can be applied to the controllable system.

Keywords: RRP robot, Optimal Control, Minimum Energy and Under Actuator.

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3158 Non-Polynomial Spline Solution of Fourth-Order Obstacle Boundary-Value Problems

Authors: Jalil Rashidinia, Reza Jalilian

Abstract:

In this paper we use quintic non-polynomial spline functions to develop numerical methods for approximation to the solution of a system of fourth-order boundaryvalue problems associated with obstacle, unilateral and contact problems. The convergence analysis of the methods has been discussed and shown that the given approximations are better than collocation and finite difference methods. Numerical examples are presented to illustrate the applications of these methods, and to compare the computed results with other known methods.

Keywords: Quintic non-polynomial spline, Boundary formula, Convergence, Obstacle problems.

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3157 Method of Moments Applied to a Cuboidal Cavity Resonator: Effect of Gravitational Field Produced by a Black Hole

Authors: Arti Vaish, Harish Parthasarathy

Abstract:

This paper deals with the formulation of Maxwell-s equations in a cavity resonator in the presence of the gravitational field produced by a blackhole. The metric of space-time due to the blackhole is the Schwarzchild metric. Conventionally, this is expressed in spherical polar coordinates. In order to adapt this metric to our problem, we have considered this metric in a small region close to the blackhole and expressed this metric in a cartesian system locally.

Keywords: Method of moments, General theory of relativity, Electromagnetism, Metric tensor, schwarzchild metric, Wave Equation.

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3156 Using Automatic Ontology Learning Methods in Human Plausible Reasoning Based Systems

Authors: A. R. Vazifedoost, M. Rahgozar, F. Oroumchian

Abstract:

Knowledge discovery from text and ontology learning are relatively new fields. However their usage is extended in many fields like Information Retrieval (IR) and its related domains. Human Plausible Reasoning based (HPR) IR systems for example need a knowledge base as their underlying system which is currently made by hand. In this paper we propose an architecture based on ontology learning methods to automatically generate the needed HPR knowledge base.

Keywords: Ontology Learning, Human Plausible Reasoning, knowledge extraction, knowledge representation.

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3155 An Approach to Adaptive Load Balancing for RFID Middlewares

Authors: Heung Seok Chae, Jaegeol Park

Abstract:

Recently, there have been an increasing interest in RFID system and RFID systems have been applied to various applications. Load balancing is a fundamental technique for providing scalability of systems by moving workload from overloaded nodes to under-loaded nodes. This paper presents an approach to adaptive load balancing for RFID middlewares. Workloads of RFID middlewares can have a considerable variation according to the location of the connected RFID readers and can abruptly change at a particular instance. The proposed approach considers those characteristics of RFID middle- wares to provide an efficient load balancing.

Keywords: RFID middleware, Adaptive load balancing.

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3154 ICF Neutron Detection Techniques Based on Doped ZnO Crystal

Authors: L. Chen, X. P. Ouyang, Z. B. Zhang, J. F. Zhang, J. L. Liu

Abstract:

Ultrafast doped zinc oxide crystal promised us a good opportunity to build new instruments for ICF fusion neutron measurement. Two pulsed neutron detectors based on ZnO crystal wafer have been conceptually designed, the superfast ZnO timing detector and the scintillation recoil proton neutron detection system. The structure of these detectors was presented, and some characters were studied as well. The new detectors could be much faster than existing systems, and would be more competent for ICF neutron diagnostics.

Keywords: ICF fusion neutron detection, proton recoil telescope, superfast timing, ZnO crystal

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3153 Design of a Novel CPW Fed Fractal Antenna for UWB

Authors: A. El Hamdouni, J. Zbitou, A. Tajmouati, L. El Abdellaoui, A. Errkik, A. Tribak, M. Latrach

Abstract:

This paper presents a novel fractal antenna structure proposed for UWB (Ultra – Wideband) applications. The frequency band 3.1-10.6GHz released by FCC (Federal Communication Commission) as the commercial operation of UWB has been chosen as frequency range for this antenna based on coplanar waveguide (CPW) feed and circular shapes fulfilled according to fractal geometry. The proposed antenna is validated and designed by using an FR4 substrate with overall area of 34x43 mm2. The simulated results performed by CST-Microwave Studio and compared by ADS (Advanced Design System) show good matching input impedance with return loss less than -10dB between 2.9 GHz and 11 GHz.

Keywords: Fractal antenna, Fractal Geometry, CPW Feed, UWB, FCC.

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3152 Incorporation of Safety into Design by Safety Cube

Authors: Mohammad Rajabalinejad

Abstract:

Safety is often seen as a requirement or a performance indicator through the design process, and this does not always result in optimally safe products or systems. This paper suggests integrating the best safety practices with the design process to enrich the exploration experience for designers and add extra values for customers. For this purpose, the commonly practiced safety standards and design methods have been reviewed and their common blocks have been merged forming Safety Cube. Safety Cube combines common blocks for design, hazard identification, risk assessment and risk reduction through an integral approach. An example application presents the use of Safety Cube for design of machinery.

Keywords: Safety, safety cube, design, product, system, machinery.

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3151 A Simulation Study of Direct Injection Compressed Natural Gas Spark Ignition Engine Performance Utilizing Turbulent Jet Ignition with Controlled Air Charge

Authors: Siyamak Ziyaei, Siti Khalijah Mazlan, Petros Lappas

Abstract:

Compressed natural gas (CNG) is primarily composed of methane (CH4), and has a lower carbon to hydrogen ratio than other hydrocarbon fuels such as gasoline (C8H18) and diesel (C12H23). Consequently, it has the potential to reduce CO2 emissions compared to conventional fuels. Although Natural Gas (NG) has environmental advantages compared to other hydrocarbon fuels, its main component, CH4, burns at a slower rate compared to the conventional fuels. A higher pressure and leaner cylinder environment will unravel the slow burn characteristic of CH4. Lean combustion and high compression ratios are well-known methods for increasing the efficiency of internal combustion engines. In order to achieve successful a CNG lean combustion in Spark Ignition (SI) engines, a strong ignition system is essential to avoid engine misfires, especially in ultra-lean conditions. Turbulent Jet Ignition (TJI) is an ignition system that employs a pre-combustion chamber to ignite the lean fuel mixture in the main combustion chamber using a fraction of the total fuel per cycle. TJI enables ultra-lean combustion by providing distributed ignition sites through orifices. The fast burn rate provided by TJI enables the ordinary SI engine to be comparable to other combustion systems such as Homogeneous Charge Compression Ignition (HCCI) or Controlled Auto-Ignition (CAI) in terms of thermal efficiency, through the increased levels of dilution without the need of sophisticated control systems. Due to the physical geometry of TJI, which contains small orifices that connect the pre-chamber to the main chamber, providing the right mixture of fuel and air has been identified as a key challenge due to the insufficient amount of air that is pushed into the pre-chamber during each compression stroke. There is also the problem of scavenging which contributed to the factors that reduces the TJI performance. Combustion residual gases such as CO2, CO and NOx from the previous combustion cycle dilute the pre-chamber fuel-air mixture preventing rapid combustion in the pre-chamber. An air-controlled active TJI is presented in this paper in order to address these issues. By supplying air into the pre-chamber at a sufficient pressure, residual gases are exhausted, and the air-fuel ratio is controlled within the pre-chamber, thereby improving the quality of the combustion. An investigation of the 3D combustion characteristics of a CNG-fueled SI engine using a direct injection fuelling strategy employing an air channel in the prechamber is presented in this paper. Experiments and simulations were performed at the Worldwide Mapping Point (WWMP) at 1500 revolutions per minute (rpm), 3.3 bar Indicated Mean Effective Pressure (IMEP), using only conventional spark plugs as a baseline. With a validated baseline engine simulation, the settings were set for all simulation scenarios at λ=1. Following that, the pre-chambers with and without an auxiliary fuel supply were simulated. In the study of (DI-CNG) SI engine, active TJI was observed to perform better than passive TJI and conventional  spark plug ignition. In conclusion, the active pre-chamber with an air channel demonstrated an improved thermal efficiency (ηth) over other counterparts and conventional spark ignition systems.

Keywords: Turbulent Jet Ignition, Active Air Control Turbulent Jet Ignition, Pre-chamber ignition system, Active and Passive Pre-chamber, thermal efficiency, methane combustion, internal combustion engine combustion emissions.

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3150 Cryptocurrency-Based Mobile Payments with Near-Field Communication-Enabled Devices

Authors: Marko Niinimaki

Abstract:

Cryptocurrencies are getting increasingly popular, but very few of them can be conveniently used in daily mobile phone purchases. To solve this problem, we demonstrate how to build a functional prototype of a mobile cryptocurrency-based e-commerce application the communicates with Near-Field Communication (NFC) tags. Using the system, users are able to purchase physical items with an NFC tag that contains an e-commerce URL. The payment is done simply by touching the tag with a mobile device and accepting the payment. Our method is constructive: we describe the design and technologies used in the implementation and evaluate the security and performance of the solution. Our main finding is that the analysis and measurements show that our solution is feasible for e-commerce.

Keywords: Cryptocurrency, e-commerce, NFC, mobile devices.

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3149 Towards a Simulation Model to Ensure the Availability of Machines in Maintenance Activities

Authors: Maryam Gallab, Hafida Bouloiz, Youness Chater, Mohamed Tkiouat

Abstract:

The aim of this paper is to present a model based on multi-agent systems in order to manage the maintenance activities and to ensure the reliability and availability of machines just with the required resources (operators, tools). The interest of the simulation is to solve the complexity of the system and to find results without cost or wasting time. An implementation of the model is carried out on the AnyLogic platform to display the defined performance indicators.

Keywords: Maintenance, complexity, simulation, multi-agent systems, AnyLogic platform.

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3148 Machine Learning Techniques for Short-Term Rain Forecasting System in the Northeastern Part of Thailand

Authors: Lily Ingsrisawang, Supawadee Ingsriswang, Saisuda Somchit, Prasert Aungsuratana, Warawut Khantiyanan

Abstract:

This paper presents the methodology from machine learning approaches for short-term rain forecasting system. Decision Tree, Artificial Neural Network (ANN), and Support Vector Machine (SVM) were applied to develop classification and prediction models for rainfall forecasts. The goals of this presentation are to demonstrate (1) how feature selection can be used to identify the relationships between rainfall occurrences and other weather conditions and (2) what models can be developed and deployed for predicting the accurate rainfall estimates to support the decisions to launch the cloud seeding operations in the northeastern part of Thailand. Datasets collected during 2004-2006 from the Chalermprakiat Royal Rain Making Research Center at Hua Hin, Prachuap Khiri khan, the Chalermprakiat Royal Rain Making Research Center at Pimai, Nakhon Ratchasima and Thai Meteorological Department (TMD). A total of 179 records with 57 features was merged and matched by unique date. There are three main parts in this work. Firstly, a decision tree induction algorithm (C4.5) was used to classify the rain status into either rain or no-rain. The overall accuracy of classification tree achieves 94.41% with the five-fold cross validation. The C4.5 algorithm was also used to classify the rain amount into three classes as no-rain (0-0.1 mm.), few-rain (0.1- 10 mm.), and moderate-rain (>10 mm.) and the overall accuracy of classification tree achieves 62.57%. Secondly, an ANN was applied to predict the rainfall amount and the root mean square error (RMSE) were used to measure the training and testing errors of the ANN. It is found that the ANN yields a lower RMSE at 0.171 for daily rainfall estimates, when compared to next-day and next-2-day estimation. Thirdly, the ANN and SVM techniques were also used to classify the rain amount into three classes as no-rain, few-rain, and moderate-rain as above. The results achieved in 68.15% and 69.10% of overall accuracy of same-day prediction for the ANN and SVM models, respectively. The obtained results illustrated the comparison of the predictive power of different methods for rainfall estimation.

Keywords: Machine learning, decision tree, artificial neural network, support vector machine, root mean square error.

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3147 Fast Extraction of Edge Histogram in DCT Domain based on MPEG7

Authors: Minyoung Eom, Yoonsik Choe

Abstract:

In these days, multimedia data is transmitted and processed in compressed format. Due to the decoding procedure and filtering for edge detection, the feature extraction process of MPEG-7 Edge Histogram Descriptor is time-consuming as well as computationally expensive. To improve efficiency of compressed image retrieval, we propose a new edge histogram generation algorithm in DCT domain in this paper. Using the edge information provided by only two AC coefficients of DCT coefficients, we can get edge directions and strengths directly in DCT domain. The experimental results demonstrate that our system has good performance in terms of retrieval efficiency and effectiveness.

Keywords: DCT, Descriptor, EHD, MPEG7.

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3146 Electronic Voting System using Mobile Terminal

Authors: Keonwoo Kim, Dowon Hong

Abstract:

Electronic voting (E-voting) using an internet has been recently performed in some nations and regions. There is no spatial restriction which a voter directly has to visit the polling place, but an e-voting using an internet has to go together the computer in which the internet connection is possible. Also, this voting requires an access code for the e-voting through the beforehand report of a voter. To minimize these disadvantages, we propose a method in which a voter, who has the wireless certificate issued in advance, uses its own cellular phone for an e-voting without the special registration for a vote. Our proposal allows a voter to cast his vote in a simple and convenient way without the limit of time and location, thereby increasing the voting rate, and also ensuring confidentiality and anonymity.

Keywords: Voting, mobile terminal, confidentiality, anonymity.

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3145 Analysis of DNA from Fired Cartridge Casings

Authors: S. Mawlood, L. Dennany, N. Watson, B. Pickard

Abstract:

DNA analysis has been widely accepted as providing valuable evidence concerning the identity of the source of biological traces. Our work has showed that DNA samples can survive on cartridges even after firing. The study also raised the possibility of determining other information such as the age of the donor. Such information may be invaluable in certain cases where spent cartridges from automatic weapons are left behind at the scene of a crime. In spite of the nature of touch evidence and exposure to high chamber temperatures during shooting, we were still capable to retrieve enough DNA for profile typing. In order to estimate age of contributor, DNA methylation levels were analyzed using EpiTect system for retrieved DNA. However, results were not conclusive, due to low amount of input DNA.

Keywords: Age prediction, Fired cartridge, Trace DNA sample.

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3144 Asymptotic Properties of a Stochastic Predator-Prey Model with Bedding-DeAngelis Functional Response

Authors: Xianqing Liu, Shouming Zhong, Lijiang Xiang

Abstract:

In this paper, a stochastic predator-prey system with Bedding-DeAngelis functional response is studied. By constructing a suitable Lyapunov founction, sufficient conditions for species to be stochastically permanent is established. Meanwhile, we show that the species will become extinct with probability one if the noise is sufficiently large.

Keywords: Stochastically permanent, extinct, white noise, Bedding-DeAngelis functional response.

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3143 Numerical Calculation of the Ionization Energy of Donors in a Cubic Quantum well and Wire

Authors: Sara Sedaghat, Mahmood Barati, Iraj Kazeminezhad

Abstract:

The ionization energy in semiconductor systems in nano scale was investigated by using effective mass approximation. By introducing the Hamiltonian of the system, the variational technique was employed to calculate the ground state and the ionization energy of a donor at the center and in the case that the impurities are randomly distributed inside a cubic quantum well. The numerical results for GaAs/GaAlAs show that the ionization energy strongly depends on the well width for both cases and it decreases as the well width increases. The ionization energy of a quantum wire was also calculated and compared with the results for the well.

Keywords: quantum well, quantum wire, quantum dot, impuritystate

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3142 Affine Projection Adaptive Filter with Variable Regularization

Authors: Young-Seok Choi

Abstract:

We propose two affine projection algorithms (APA) with variable regularization parameter. The proposed algorithms dynamically update the regularization parameter that is fixed in the conventional regularized APA (R-APA) using a gradient descent based approach. By introducing the normalized gradient, the proposed algorithms give birth to an efficient and a robust update scheme for the regularization parameter. Through experiments we demonstrate that the proposed algorithms outperform conventional R-APA in terms of the convergence rate and the misadjustment error.

Keywords: Affine projection, regularization, gradient descent, system identification.

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3141 VoIP Networks Performance Analysis with Encryption Systems

Authors: Edward Paul Guillen, Diego Alejandro Chacon

Abstract:

The VoIP networks as alternative method to traditional PSTN system has been implemented in a wide variety of structures with multiple protocols, codecs, software and hardware–based distributions. The use of cryptographic techniques let the users to have a secure communication, but the calculate throughput as well as the QoS parameters are affected according to the used algorithm. This paper analyzes the VoIP throughput and the QoS parameters with different commercial encryption methods. The measurement–based approach uses lab scenarios to simulate LAN and WAN environments. Security mechanisms such as TLS, SIAX2, SRTP, IPSEC and ZRTP are analyzed with μ-LAW and GSM codecs.

Keywords: VoIP, Secure VoIP, Throughput Analysis, VoIP QoS evaluation

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3140 Numerical Simulation of a Solar Photovoltaic Panel Cooled by a Forced Air System

Authors: D. Nebbali, R. Nebbali, A. Ouibrahim

Abstract:

This study focuses on the cooling of a photovoltaic panel (PV). Indeed, the cooling improves the conversion capacity of this one and maintains, under extreme conditions of air temperature, the panel temperature at an appreciable level which avoids the altering. To do this, a fan provides forced circulation of air. Because the fan is supplied by the panel, it is necessary to determine the optimum operating point that unites efficiency of the PV with the consumption of the fan. For this matter, numerical simulations are performed at varying mass flow rates of air, under two extreme air temperatures (50°C, 25°C) and a fixed solar radiation (1000W.m2) in a case of no wind.

Keywords: Energy conversion, efficiency, balance energy, solar cell.

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3139 Proposition of an Ontology of Diseases and Their Signs from Medical Ontologies Integration

Authors: Adama Sow, Abdoulaye Guiss´e, Oumar Niang

Abstract:

To assist medical diagnosis, we propose a federation of several existing and open medical ontologies and terminologies. The goal is to merge the strengths of all these resources to provide clinicians the access to a variety of shared knowledges that can facilitate identification and association of human diseases and all of their available characteristic signs such as symptoms and clinical signs. This work results to an integration model loaded from target known ontologies of the bioportal platform such as DOID, MESH, and SNOMED for diseases selection, SYMP, and CSSO for all existing signs.

Keywords: Medical decision, medical ontologies, ontologies integration, linked data, knowledge ingeneering, e-health system.

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3138 Analysis of Combined Use of NN and MFCC for Speech Recognition

Authors: Safdar Tanweer, Abdul Mobin, Afshar Alam

Abstract:

The performance and analysis of speech recognition system is illustrated in this paper. An approach to recognize the English word corresponding to digit (0-9) spoken by 2 different speakers is captured in noise free environment. For feature extraction, speech Mel frequency cepstral coefficients (MFCC) has been used which gives a set of feature vectors from recorded speech samples. Neural network model is used to enhance the recognition performance. Feed forward neural network with back propagation algorithm model is used. However other speech recognition techniques such as HMM, DTW exist. All experiments are carried out on Matlab.

Keywords: Speech Recognition, MFCC, Neural Network, classifier.

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