Search results for: network security protocols.

Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

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For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: High-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network.

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Authors: Ghulam Haider Haidaree, Nsenda Lukumwena

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Most developing nations face energy production and supply problems. This is also the case of Afghanistan whose generating capacity does not meet its energy demand. This is due in part to high security and risk caused by war which deters foreign investments and insufficient internal revenue. To address the issue above, this paper would like to suggest an alternative and affordable way to deal with the energy problem. That is by converting Solid Waste to energy. As a result, this approach tackles the municipal solid waste issue (potential cause of several diseases), contributes to the improvement of the quality of life, local economy, and so on. While addressing the solid waste problem in general, this paper samples specifically one municipality which is District-12, one of the 22 districts of Kabul city. Using geographic information system (GIS) technology, District-12 is divided into nine different zones whose municipal solid waste is respectively collected, processed, and converted into electricity and distributed to the closest area. It is important to mention that GIS has been used to estimate the amount of electricity to be distributed and to optimally position the production plant.

Keywords: Energy problem, estimation of electricity, GIS zones, solid waste management system.

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Authors: Zixin Liu, Shu Lü, Shouming Zhong, Mao Ye

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The problem of exponential stability and periodicity for a class of cellular neural networks (DCNNs) with time-varying delays is investigated. By dividing the network state variables into subgroups according to the characters of the neural networks, some sufficient conditions for exponential stability and periodicity are derived via the methods of variation parameters and inequality techniques. These conditions are represented by some blocks of the interconnection matrices. Compared with some previous methods, the method used in this paper does not resort to any Lyapunov function, and the results derived in this paper improve and generalize some earlier criteria established in the literature cited therein. Two examples are discussed to illustrate the main results.

Keywords: Cellular neural networks, exponential stability, time varying delays, partitioned matrices, periodic solution.

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Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis

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An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.

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Authors: S. Sendhil Kumar, M. Senthil Kumar

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Maintenance and design engineers have great concern for the functioning of rotating machineries due to the vibration phenomenon. Improper functioning in rotating machinery originates from the damage to rolling element bearings. The status of rolling element bearings require advanced technologies to monitor their health status efficiently and effectively. Avoiding vibration during machine running conditions is a complicated process. Vibration simulation should be carried out using suitable sensors/ transducers to recognize the level of damage on bearing during machine operating conditions. Various issues arising in rotating systems are interlinked with bearing faults. This paper presents an approach for fault diagnosis of bearings using neural networks and time/frequencydomain vibration analysis.

Keywords: Bearing vibration, Condition monitoring, Fault diagnosis, Frequency domain.

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Authors: Oluseye Adeniyi Adeleke, Mohd Fadzli Salleh

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Cooperative communication provides transmit diversity, even when, due to size constraints, mobile units cannot accommodate multiple antennas. A versatile cooperation method called coded cooperation has been developed, in which cooperation is implemented through channel coding with a view to controlling the errors inherent in wireless communication. In this work we evaluate the performance of coded cooperation in flat Rayleigh fading environment using a concept known as the pair wise error probability (PEP). We derive the PEP for a flat fading scenario in coded cooperation and then compare with the signal-to-noise ratio of the users in the network. Results show that an increase in the SNR leads to a decrease in the PEP. We also carried out simulations to validate the result.

Keywords: Channel state information, coded cooperation, cooperative systems, pairwise-error-probability, Reed-Solomon codes.

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Authors: M. N. Moschakis, V. V. Dafopoulos, I. G. Andritsos, E. S. Karapidakis, J. M. Prousalidis

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This paper deals with the effect of a power transformer’s vector group on the basic voltage sag characteristics during unbalanced faults at a meshed or radial power network. Specifically, the propagation of voltage sags through a power transformer is studied with advanced short-circuit analysis. A smart method to incorporate this effect on analytical mathematical expressions is proposed. Based on this methodology, the positive effect of transformers of certain vector groups on the mitigation of the expected number of voltage sags per year (sag frequency) at the terminals of critical industrial customers can be estimated.

Keywords: Balanced and unbalanced faults, industrial design, phase shift, power quality, power systems, voltage sags (or dips).

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Authors: Orawan Boriban, Phatthanan Chaiyabut

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The purpose of this research is to study motivation factors and also to study factors relation to job performance to compare motivation factors under the personal factor classification such as gender, age, income, educational level, marital status, and working duration; and to study the relationship between Motivation Factors and Job Performance with job satisfactions. The sample groups utilized in this research were 400 Suan Sunandha Rajabhat University employees. This research is a quantitative research using questionnaires as research instrument. The statistics applied for data analysis including percentage, mean, and standard deviation. In addition, the difference analysis was conducted by t value computing, one-way analysis of variance and Pearson’s correlation coefficient computing. The findings of the study results were as follows the findings showed that the aspects of job promotion and salary were at the moderate levels. Additionally, the findings also showed that the motivations that affected the revenue branch chiefs’ job performance were job security, job accomplishment, policy and management, job promotion, and interpersonal relation.

Keywords: Motivation Factors, Job Performance, Suan Sunandha Rajabhat University Employee.

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Authors: Shuen-Tai Wang, Ying-Chuan Chen, Hsi-Ya Chang

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The rapid improvement of the microprocessor and network has made it possible for the PC cluster to compete with conventional supercomputers. Lots of high throughput type of applications can be satisfied by using the current desktop PCs, especially for those in PC classrooms, and leave the supercomputers for the demands from large scale high performance parallel computations. This paper presents our development on enabling an automated deployment mechanism for cluster computing to utilize the computing power of PCs such as reside in PC classroom. After well deployment, these PCs can be transformed into a pre-configured cluster computing resource immediately without touching the existing education/training environment installed on these PCs. Thus, the training activities will not be affected by this additional activity to harvest idle computing cycles. The time and manpower required to build and manage a computing platform in geographically distributed PC classrooms also can be reduced by this development.

Keywords: PC cluster, automated deployment, cluster computing, PC classroom.

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Authors: Reza Fazeli, Vitor Leal, Jorge Pinho de Sousa

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Planning the transition period for the adoption of alternative fuel-technology powertrains is a challenging task that requires sophisticated analysis tools. In this study, a system dynamic approach was applied to analyze the bi-directional interaction between the development of the refueling station network and vehicle sales. Besides, the developed model was used to estimate the transition cost to reach a predefined target (share of alternative fuel vehicles) in different scenarios. Several scenarios have been analyzed to investigate the effectiveness and cost of incentives on the initial price of vehicles, and on the evolution of fuel and refueling stations. Obtained results show that a combined set of incentives will be more effective than just a single specific type of incentives.

Keywords: adoption of Alternative Fuel Vehicles, System Dynamic Analysis, Plug-in Hybrid Vehicles

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Authors: Ahmed Al-Adaileh, Souheil Khaddaj

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Outcomes of exhaustion of natural resources started influencing each spirit on this planet. Energy is an essential factor in this aspect. To restore the circumstance to the appropriate track, all attempts must focus on two fundamental branches: producing electricity from clean and renewable reserves and decreasing the overall unnecessary consumption of energy. The focal point of this paper will be on lessening the power consumption in the household's segment. This paper is an attempt to give a clear understanding of a framework called Reduction of Energy Consumption in Household Sector (RECHS) and how it should help householders to reduce their power consumption by substituting their household appliances, turning-off the appliances when stand-by modus is detected, and scheduling their appliances operation periods. Technically, the framework depends on utilizing Z-Wave compatible plug-ins which will be connected to the usual house devices to gauge and control them remotely and semi-automatically. The suggested framework underpins numerous quality characteristics, for example, integrability, scalability, security and adaptability.

Keywords: Smart energy management systems, internet of things, wireless mesh networks, microservices, cloud computing, big data.

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Authors: Alec Wells, Aminu Bello Usman, Justin McKeown

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The growing usage of smart speakers raises many privacy and trust concerns compared to other technologies such as smart phones and computers. In this study, a proxy measure of trust is used to gauge users’ opinions on three different technologies based on an empirical study, and to understand which technology most people are most likely to trust. The collected data were analysed using the Kruskal-Wallis H test to determine the statistical differences between the users’ trust level of the three technologies: smart speaker, computer and smart phone. The findings of the study revealed that despite the wide acceptance, ease of use and reputation of smart speakers, people find it difficult to trust smart speakers with their sensitive information via the Direct Voice Input (DVI) and would prefer to use a keyboard or touchscreen offered by computers and smart phones. Findings from this study can inform future work on users’ trust in technology based on perceived ease of use, reputation, perceived credibility and risk of using technologies via DVI.

Keywords: Direct voice input, risk, security, technology and trust.

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Authors: Elham Rastegari, Amirmasood Rahmani, Saeed Setayeshi

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The hospital and the health-care center of a community, as a place for people-s life-care and health-care settings, must provide more and better services for patients or residents. After Establishing Electronic Medical Record (EMR) system -which is a necessity- in the hospital, providing pervasive services is a further step. Our objective in this paper is to use pervasive computing in a case study of healthcare, based on EMR database that coordinates application services over network to form a service environment for medical and health-care. Our method also categorizes the hospital spaces into 3 spaces: Public spaces, Private spaces and Isolated spaces. Although, there are many projects about using pervasive computing in healthcare, but all of them concentrate on the disease recognition, designing smart cloths, or provide services only for patient. The proposed method is implemented in a hospital. The obtained results show that it is suitable for our purpose.

Keywords: Pervasive computing, RFID, Health-care.

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Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil

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Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.

Keywords: Backpropagation algorithm, conjugacy condition, line search, matrix perturbation

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Authors: Tulika Bhattacharjee, A. K.Chakraborty

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Due to the deregulation of the Electric Supply Industry and the resulting emergence of electricity market, the volumes of power purchases are on the rise all over the world. In a bid to meet the customer-s demand in a reliable and yet economic manner, utilities purchase power from the energy market over and above its own production. This paper aims at developing an optimal power purchase model with two objectives viz economy and environment ,taking various functional operating constraints such as branch flow limits, load bus voltage magnitudes limits, unit capacity constraints and security constraints into consideration.The price of purchased power being an uncertain variable is modeled using fuzzy logic. DEMO (Differential Evolution For Multi-objective Optimization) is used to obtain the pareto-optimal solution set of the multi-objective problem formulated. Fuzzy set theory has been employed to extract the best compromise non-dominated solution. The results obtained on IEEE 30 bus system are presented and compared with that of NSGAII.

Keywords: Deregulation, Differential Evolution, Multi objective Optimization, Pareto Optimal Set, Optimal Power Flow

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Authors: M. S. Anton Merkulov

Abstract:

This article discusses the questions concerning of creating small packet networks for energy companies with application of high voltage power line carrier equipment (PLC) with functionality of IP traffic transmission. The main idea is to create converged PLC links between substations and dispatching centers where packet data and voice are transmitted in one data flow. The article contents description of basic conception of the network, evaluation of voice traffic transmission parameters, and discussion of header compression techniques in relation to PLC links. The results of exploration show us, that convergent packet PLC links can be very useful in the construction of small packet networks between substations in remote locations, such as deposits or low populated areas.

Keywords: packet PLC, VoIP, time delay, packet traffic, overhead compression

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Authors: B. Leela Devi, A. Sankar

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The web’s increased popularity has included a huge amount of information, due to which automated web page classification systems are essential to improve search engines’ performance. Web pages have many features like HTML or XML tags, hyperlinks, URLs and text contents which can be considered during an automated classification process. It is known that Webpage classification is enhanced by hyperlinks as it reflects Web page linkages. The aim of this study is to reduce the number of features to be used to improve the accuracy of the classification of web pages. In this paper, a novel feature selection method using an improved Particle Swarm Optimization (PSO) using principle of evolution is proposed. The extracted features were tested on the WebKB dataset using a parallel Neural Network to reduce the computational cost.

Keywords: Web page classification, WebKB Dataset, Term Frequency-Inverse Document Frequency (TF-IDF), Particle Swarm Optimization (PSO).

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Authors: Arafat A. A. Shabaneh

Abstract:

Harsh environments require developed detection by an optical communication system to ensure a high level of security and safety. Fiber Bragg gratings (FBGs) are emerging sensing instruments that respond to variations in strain and temperature by varying wavelengths. In this study, a cascaded uniform FBG is designed as a strain sensor for 6 km length at 1550 nm wavelength with 30 °C temperature by analyzing dynamic strain and wavelength shifts. The FBG is placed in a small segment of an optical fiber that reflects light with a specific wavelength and passes on the remaining wavelengths. Consequently, periodic alteration occurs in the refractive index in the fiber core. The alteration in the modal index of the fiber is produced by strain effects on a Bragg wavelength. When the developed sensor is exposed to the strain (0.01) of the cascaded uniform FBG, the wavelength shifts by 0.0000144383 μm. The sensing accuracy of the developed sensor is 0.0012. Simulation results show the reliability and effectiveness of the strain monitoring sensor for remote sensing application.

Keywords: Remote sensing, cascaded fiber Bragg grating, strain sensor, wavelength shift.

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Authors: Chien-Wei Hung, Fu-Hau Hsu, Chuan-Sheng Wang, Chia-Hao Lee

Abstract:

Nowadays, the abuse of keyloggers is one of the most widespread approaches to steal sensitive information. In this paper, we propose an On-Screen Prompts Approach to Keyloggers (OSPAK) and its analysis, which is installed in public computers. OSPAK utilizes a canvas to cue users when their keystrokes are going to be logged or ignored by OSPAK. This approach can protect computers against recoding sensitive inputs, which obfuscates keyloggers with letters inserted among users' keystrokes. It adds a canvas below each password field in a webpage and consists of three parts: two background areas, a hit area and a moving foreground object. Letters at different valid time intervals are combined in accordance with their time interval orders, and valid time intervals are interleaved with invalid time intervals. It utilizes animation to visualize valid time intervals and invalid time intervals, which can be integrated in a webpage as a browser extension. We have tested it against a series of known keyloggers and also performed a study with 95 users to evaluate how easily the tool is used. Experimental results made by volunteers show that OSPAK is a simple approach.

Keywords: Authentication, computer security, keylogger, privacy, information leakage.

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Authors: A. Roukouni, S. Basbas, M. Giannopoulou

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Transport and land use are two systems that are mutually influenced. Their interaction is a complex process associated with continuous feedback. The paper examines the existing land use around an under construction metro station of the new metro network of Thessaloniki, Greece, through the use of field investigations, around the station-s predefined location. Moreover, except from the analytical land use recording, a sampling questionnaire survey is addressed to several selected enterprises of the study area. The survey aims to specify the characteristics of the enterprises, the trip patterns of their employees and clients, as well as the stated preferences towards the changes the new metro station is considered to bring to the area. The interpretation of the interrelationships among selected data from the questionnaire survey takes place using the method of Principal Components Analysis for Categorical Data. The followed methodology and the survey-s results contribute to the enrichment of the relevant bibliography concerning the way the creation of a new metro station can have an impact on the land use pattern of an area, by examining the situation before the operation of the station.

Keywords: land use, metro station, questionnaire survey

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Authors: P. Sankar, P. James Daniel Paul, Siddhant Sahu

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A brief review of the empirical studies on the methodology of the stock market decision support would indicate that they are at a threshold of validating the accuracy of the traditional and the fuzzy, artificial neural network and the decision trees. Many researchers have been attempting to compare these models using various data sets worldwide. However, the research community is on the way to the conclusive confidence in the emerged models. This paper attempts to use the automotive sector stock prices from National Stock Exchange (NSE), India and analyze them for the intra-sectorial support for stock market decisions. The study identifies the significant variables and their lags which affect the price of the stocks using OLS analysis and decision tree classifiers.

Keywords: Indian Automotive Sector, Stock Market Decisions, Equity Portfolio Analysis, Decision Tree Classifiers, Statistical Data Analysis.

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Authors: Yu-Kyung Kang, Suk-Hyung Hwang, Kyoung-Mo Yang

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The tagging data of (users, tags and resources) constitutes a folksonomy that is the user-driven and bottom-up approach to organizing and classifying information on the Web. Tagging data stored in the folksonomy include a lot of very useful information and knowledge. However, appropriate approach for analyzing tagging data and discovering hidden knowledge from them still remains one of the main problems on the folksonomy mining researches. In this paper, we have proposed a folksonomy data mining approach based on FCA for discovering hidden knowledge easily from folksonomy. Also we have demonstrated how our proposed approach can be applied in the collaborative tagging system through our experiment. Our proposed approach can be applied to some interesting areas such as social network analysis, semantic web mining and so on.

Keywords: Folksonomy data mining, formal concept analysis, collaborative tagging, conceptual knowledge discovery, classification.

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Authors: Magdy B. Eteiba, Wael Ismael Wahba, Shimaa Barakat

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This paper presents a fault identification, classification and fault location estimation method based on Discrete Wavelet Transform and Adaptive Network Fuzzy Inference System (ANFIS) for medium voltage cable in the distribution system.

Different faults and locations are simulated by ATP/EMTP, and then certain selected features of the wavelet transformed signals are used as an input for a training process on the ANFIS. Then an accurate fault classifier and locator algorithm was designed, trained and tested using current samples only. The results obtained from ANFIS output were compared with the real output. From the results, it was found that the percentage error between ANFIS output and real output is less than three percent. Hence, it can be concluded that the proposed technique is able to offer high accuracy in both of the fault classification and fault location.

Keywords: ANFIS, Fault location, Underground Cable, Wavelet Transform.

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Authors: H. Shahabi

Abstract:

since in natural accidents, facilities that relate to this vita element are underground so, it is difficult to find quickly some right, exact and definite information about water utilities. There fore, this article has done operationally in Boukan city in Western Azarbaijan of Iran and it tries to represent operation and capabilities of Geographical Information system (GIS) in urban water management at the time of natural accidents. Structure of this article is that firstly it has established a comprehensive data base related to water utilities by collecting, entering, saving and data management, then by modeling water utilities we have practically considered its operational aspects related to water utility problems in urban regions.

Keywords: Natural Disaster, Geographical Information system (GIS), Modeling and network analysis, Boukan city in Western Azerbaijan, Iran

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Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. However, accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER benefiting from deep learning, especially CNN and VGG16. First, the data are pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning.

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Authors: Semih Demir, Anil Celebi

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Circuit switched networks widely used until the end of the 20^th century have been transformed into packages switched networks. Time Division Multiplexing over Internet Protocol (TDMoIP) is a system that enables Time Division Multiplexing (TDM) traffic to be carried over packet switched networks (PSN). In TDMoIP systems, devices that send TDM data to the PSN and receive it from the network must operate with the same clock frequency. In this study, it was aimed to implement clock synchronization process in Field Programmable Gate Array (FPGA) chips using time information attached to the packages received from PSN. The designed hardware is verified using the datasets obtained for the different carrier types and comparing the results with the software model. Field tests are also performed by using the real time TDMoIP system.

Keywords: Clock recovery on TDMoIP, FPGA, MATLAB reference model, clock synchronization.

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Authors: R. Geetha, G. Umarani Srikanth, S. Prabhu

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Wireless sensor networks are resource constrained networks, where energy is the major resource in such networks. Therefore, energy conservation is major aspect in the deployment of Wireless Sensor Network. This work makes use of an extended Greedy Perimeter Stateless Routing (eGPSR) protocol that mainly focuses on energy efficient data transmission. This data transmission is based on the fact that the message that is sent to a distant node consumes more energy than the message that is sent to a short range transmission. Every cluster contains a head set that consists of many virtual cluster heads. Routing is decided by head set members. The energy level of the received signal is the major constraint to choose head set from its members. The experimental result shows that the use of eGPSR in routing has improved throughput with comparatively less delay.

Keywords: eGPSR, energy efficiency, routing, wireless sensor networks, WSN.

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Authors: Achuthsankar S. Nair, J. S. Jayasudha

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The ever increasing use of World Wide Web in the existing network, results in poor performance. Several techniques have been developed for reducing web traffic by compressing the size of the file, saving the web pages at the client side, changing the burst nature of traffic into constant rate etc. No single method was adequate enough to access the document instantly through the Internet. In this paper, adaptive hybrid algorithms are developed for reducing web traffic. Intelligent agents are used for monitoring the web traffic. Depending upon the bandwidth usage, user-s preferences, server and browser capabilities, intelligent agents use the best techniques to achieve maximum traffic reduction. Web caching, compression, filtering, optimization of HTML tags, and traffic dispersion are incorporated into this adaptive selection. Using this new hybrid technique, latency is reduced to 20 – 60 % and cache hit ratio is increased 40 – 82 %.

Keywords: Bandwidth, Congestion, Intelligent Agents, Prefetching, Web Caching.

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Authors: Santosh Kumar Singh, Krishna Chandra Roy, Vibhakar Pathak

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Spectrum is a scarce commodity, and considering the spectrum scarcity faced by the wireless-based service providers led to high congestion levels. Technical inefficiencies from pooled, since all networks share a common pool of channels, exhausting the available channels will force networks to block the services. Researchers found that cognitive radio (CR) technology may resolve the spectrum scarcity. A CR is a self-configuring entity in a wireless networking that senses its environment, tracks changes, and frequently exchanges information with their networks. However, CRN facing challenges and condition become worst while tracks changes i.e. reallocation of another under-utilized channels while primary network user arrives. In this paper, channels or resource reallocation technique based on DNA-inspired computing algorithm for CRN has been proposed.

Keywords: Ad hoc networks, channels reallocation, cognitive radio, DNA local sequence alignment.

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Authors: Metehan Makinacı

Abstract:

The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.

Keywords: Computer-aided diagnosis, support vector machines, Gauss-Markov random fields, texture classification.

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