Search results for: case pile wave analysis

Authors: Jatinderkumar R. Saini, Apurva A. Desai

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In recent times, the problem of Unsolicited Bulk Email (UBE) or commonly known as Spam Email, has increased at a tremendous growth rate. We present an analysis of survey based on classifications of UBE in various research works. There are many research instances for classification between spam and non-spam emails but very few research instances are available for classification of spam emails, per se. This paper does not intend to assert some UBE classification to be better than the others nor does it propose any new classification but it bemoans the lack of harmony on number and definition of categories proposed by different researchers. The paper also elaborates on factors like intent of spammer, content of UBE and ambiguity in different categories as proposed in related research works of classifications of UBE.

Keywords: E-mail, Scams, Spam Email, Unsolicited Bulk Email(UBE)

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Authors: Jacqueline R. T. Alipo-on, Francesca I. F. Escobar, Myles J. T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Electrocardiogram (ECG) signal analysis and processing are crucial in the diagnosis of cardiovascular diseases which are considered as one of the leading causes of mortality worldwide. However, the traditional rule-based analysis of large volumes of ECG data is time-consuming, labor-intensive, and prone to human errors. With the advancement of the programming paradigm, algorithms such as machine learning have been increasingly used to perform an analysis on the ECG signals. In this paper, various deep learning algorithms were adapted to classify five classes of heart beat types. The dataset used in this work is the synthetic MIT-Beth Israel Hospital (MIT-BIH) Arrhythmia dataset produced from generative adversarial networks (GANs). Various deep learning models such as ResNet-50 convolutional neural network (CNN), 1-D CNN, and long short-term memory (LSTM) were evaluated and compared. ResNet-50 was found to outperform other models in terms of recall and F1 score using a five-fold average score of 98.88% and 98.87%, respectively. 1-D CNN, on the other hand, was found to have the highest average precision of 98.93%.

Keywords: Heartbeat classification, convolutional neural network, electrocardiogram signals, ECG signals, generative adversarial networks, long short-term memory, LSTM, ResNet-50.

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Authors: H. López-Moreno, A. Rodríguez-Sánchez, C. Viñas-Arrebola, C. Porras-Amores

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The ventilated façade has great advantages when compared to traditional façades as it reduces the air conditioning thermal loads due to the stack effect induced by solar radiation in the air chamber. Optimizing energy consumption by using a ventilated façade can be used not only in newly built buildings but also it can be implemented in existing buildings, opening the field of implementation to energy building retrofitting works. In this sense, the following three prototypes of façade where designed, built and further analyzed in this research: non-ventilated façade (NVF); slightly ventilated façade (SLVF) and strongly ventilated façade (STVF). The construction characteristics of the three facades are based on the Spanish regulation of building construction “Technical Building Code”. The façades have been monitored by type-k thermocouples in a representative day of the summer season in Madrid (Spain). Moreover, an analysis of variance (ANOVA) with repeated measures, studying the thermal lag in the ventilated and no-ventilated façades has been designed. Results show that STVF façade presents higher levels of thermal inertia as the thermal lag reduces up to 17% (daily mean) compared to the non-ventilated façade. In addition, the statistical analysis proves that an increase of the ventilation holes size in STVF façades can improve the thermal lag significantly (p >0.05) when compared to the SLVF façade.

Keywords: Energy efficiency, experimental study, statistical analysis, thermal behavior, ventilated façade.

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Authors: J.-C. Créput, A. Koukam, A. Hajjam

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We present a non standard Euclidean vehicle routing problem adding a level of clustering, and we revisit the use of self-organizing maps as a tool which naturally handles such problems. We present how they can be used as a main operator into an evolutionary algorithm to address two conflicting objectives of route length and distance from customers to bus stops minimization and to deal with capacity constraints. We apply the approach to a real-life case of combined clustering and vehicle routing for the transportation of the 780 employees of an enterprise. Basing upon a geographic information system we discuss the influence of road infrastructures on the solutions generated.

Keywords: Evolutionary algorithm, self-organizing map, clustering and vehicle routing.

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Authors: Ming-Wen Hsu, Yaw-Kuang Chen, Che-Ming Chiang, Shin-Ku Lee

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This research explores visitor-s expectations of service quality in intelligent living space showroom – Living 3.0 in Taiwan. Based on the five dimensions of PZB service quality, a specialist questionnaire is utilized to establish a complete service quality evaluation framework for Living 3.0. In this research, analysis hierarchy process (AHP) is applied to find the relative weights among the criteria. Finally, the service quality evaluation framework and evaluation results can be used as a guide for Living 3.0 proprietors to review, improve, and enhance service planning and service qualities in the future.

Keywords: Analysis Hierarchy Process (AHP), Service quality, Intelligent living space.

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Authors: Abhishek Soni, Bhagat Singh

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Perfect restoration of fractured distal femur has been a challenging task for the medical practitioners. In the present study, model of a fractured bone has been created using the scan data of the damaged bone. Thereafter, customized implant of Stainless Steel (SS-316L) for this fractured femur bone is modeled using the reverse engineering approach. Clinical set-up is prepared by assembling all the models together. Stress and deformation analysis of this clinical set-up has been performed in order to check the load bearing capacity and intactness of the joint. From this analysis, it has been inferred that the stresses and deformation developed due to the static load of the person is within the permissible limits.

Keywords: Biomechanical evaluations, customized implant, reverse engineering, stainless steel alloy.

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Authors: N. Akhavan, Sh. Tavousi Tafreshi, A. Ghasemi

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Seismic behavior of irregular structures through the past decades indicate that the stated buildings do not have appropriate performance. Among these subjects, the current paper has investigated the behavior of special steel moment frame with different configuration of soft storey vertically. The analyzing procedure has been evaluated with respect to incremental dynamic analysis (IDA), and numeric process was carried out by OpenSees finite element analysis package. To this end, nine 2D steel frames, with different numbers of stories and irregularity positions, which were subjected to seven pairs of ground motion records orthogonally with respect to Ibarra-Krawinkler deterioration model, have been investigated. This paper aims at evaluating the response of two-dimensional buildings incorporating soft storey which subjected to bi-directional seismic excitation. The IDAs were implemented for different stages of PGA with various ground motion records, in order to determine maximum inter-storey drift ratio. According to statistical elements and fracture range (standard deviation), the vulnerability or exceedance from above-mentioned cases has been examined. For this reason, fragility curves for different placement of soft storey in the first, middle and the last floor for 4, 8, and 16 storey buildings have been generated and compared properly.

Keywords: Special steel moment frame, soft storey, incremental dynamic analysis, fragility curve.

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Authors: Gi-Ryun Park, Gye-Wan Moon, Dong-Hoon Yang

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This study aims to explore the positive effects of self-leadership and innovative behavior that'd been proven in the existing researches proactively and understand the regulation effects of smartphone addiction which has recently become an issue in Korea. This study conducted a convenient sampling of college students attending the four colleges located at Daegu. A total of 210 questionnaires in 5-point Likert scale were distributed to college students. Among which, a total of 200 questionnaires were collected for our final analysis data. Both correlation analysis and regression analysis were carried out to verify those questionnaires through SPSS 20.0. As a result, college students' self-leadership had a significantly positive impact on innovative behavior (B= .210, P= .003). In addition, it is found that the relationship between self-leadership and innovative behavior can be adjusted depending on the degree of smartphone addiction in college students (B= .264, P= .000). This study could first understand the negative effects of smartphone addiction and find that if students' self-leadership is improved in terms of self-management and unnecessary use of smartphone is controlled properly, innovative behavior can be improved. In addition, this study is significant in that it attempts to identify a new impact of smartphone addiction with the recent environmental changes, unlike the existing researches that'd been carried out from the perspective of organizational behavior theory.

Keywords: Innovative Behavior, Revolutionary Behavior, Self-leadership, Smartphone Addiction.

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Authors: Gitanjali Devi, Kandarpa Kumar Sarma, Pranayee Datta, Anjana Kakoti Mahanta

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Cosmic showers, from their places of origin in space, after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of EAS and similar High Energy Particle Showers involve a plethora of experimental setups with certain constraints for which soft-computational tools like Artificial Neural Network (ANN)s can be adopted. The optimality of ANN classifiers can be enhanced further by the use of Multiple Classifier System (MCS) and certain data - dimension reduction techniques. This work describes the performance of certain data dimension reduction techniques like Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Self Organizing Map (SOM) approximators for application with an MCS formed using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN). The data inputs are obtained from an array of detectors placed in a circular arrangement resembling a practical detector grid which have a higher dimension and greater correlation among themselves. The PCA, ICA and SOM blocks reduce the correlation and generate a form suitable for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Keywords: EAS, Shower, Core, ANN, Location.

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Authors: W. EL Khoumsi, A. Hammani, M. Kuper, A. Bouaziz

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Oases are complex and fragile agro-ecosystems. They have always existed in environments characterized by an arid climate, scarcity of rainfall, high temperatures and high evaporation. These palms have grown up despite the severity of the physical characteristics thanks to the water's existence and irrigation practice. The oases are generally spread along non-perennial rivers (wadis), shallow water table or deep artesian groundwater. However, the sustainability of oasis system is threatened by water scarcity and declining of water table levels particularly in arid areas. Located in the southern east area of Morocco, Tafilalet plain encompasses one of the largest palm groves in the kingdom. In recent years, this area has become increasingly threatened by water shortage and has seen a sharp deterioration under the effect of several combined anthropogenic and climatic factors. The Bayoud disease, successive years of drought, Hassan Addakhil dam construction etc are all factors that have affected both water and phoenicicole heritage of the area. The objective of this study is to understand the interaction between qualitative and quantitative degradation of groundwater resources, and the palm grove dynamics, while reviewing the assumption that groundwater resources contribute in a direct way to the conservation of this oasis agroecosystem. A historical analysis tracing both the oasis dynamics and the groundwater evolution has been established. Data were collected from satellite images, surveys with different actors (farmers, Regional Office for Agricultural Development, Basin agency...). They were complemented by a synthesis of numerous technical reports in the area. The results showed that within 40 years, the thickness of the groundwater table has dropped in 50 %. Along with this, there has been a downsizing of date palm by 50 %. Areas with higher groundwater level were the least affected by the downsizing. So we can say that the shallow groundwater contribute significantly and directly to the water supply of date palm through its root system, and largely ensures the oasis ecosystem sustainability.

Keywords: Oasis dynamics, Arid environments, Groundwater deterioration, Date palm.

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Authors: Norsakinah Mohammad Osman, Ali Etemad, Patimah Ismail

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Type 2 diabetes mellitus (T2DM) is a complex metabolic disorder that characterized by the presence of high glucose in blood that cause from insulin resistance and insufficiency due to deterioration β-cell Langerhans functions. T2DM is commonly caused by the combination of inherited genetic variations as well as our own lifestyle. Metallothionein (MT) is a known cysteine-rich protein responsible in helping zinc homeostasis which is important in insulin signaling and secretion as well as protection our body from reactive oxygen species (ROS). MT scavenged ROS and free radicals in our body happen to be one of the reasons of T2DM and its complications. The objective of this study was to investigate the association of MT1A and MT2A polymorphisms between T2DM and control subjects among Malay populations. This study involved 150 T2DM and 120 Healthy individuals of Malay ethnic with mixed genders. The genomic DNA was extracted from buccal cells and amplified for MT1A and MT2A loci; the 347bp and 238bp banding patterns were respectively produced by mean of the Polymerase Chain Reaction (PCR). The PCR products were digested with Mlucl and Tsp451 restriction enzymes respectively and producing fragments lengths of (158/189/347bp) and (103/135/238bp) respectively. The ANOVA test was conducted and it shown that there was a significant difference between diabetic and control subjects for age, BMI, WHR, SBP, FPG, HBA1C, LDL, TG, TC and family history with (P<0.05). While the HDL, CVD risk ratio and DBP does not show any significant difference with (P>0.05). The genotype frequency for AA, AG and GG of MT1A polymorphisms was 72.7%, 22.7% and 4.7% in cases and 15%, 55% and 30% in control respectively. As for MT2A, genotype frequency of GG, GC and CC was 42.7%, 27.3% and 30% in case and 5%, 40% and 55% for control respectively. Both polymorphisms show significant difference between two investigated groups with (P=0.000). The Post hoc test was conducted and shows a significant difference between the genotypes within each polymorphism (P=0. 000). The MT1A and MT2A polymorphisms were believed to be the reliable molecular markers to distinguish the T2DM subjects from healthy individuals in Malay populations.

Keywords: Type 2 Diabetes Mellitus (T2DM), Metallothionein (MT), MT1A (rs11076161), MT2A (rs10636), Malay, Genetic Polymorphism.

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Authors: Minsoo Lee, Yun-mi Kim, Yearn Jeong Kim, Yoon-kyung Lee, Hyejung Yoon

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Biological data has several characteristics that strongly differentiate it from typical business data. It is much more complex, usually large in size, and continuously changes. Until recently business data has been the main target for discovering trends, patterns or future expectations. However, with the recent rise in biotechnology, the powerful technology that was used for analyzing business data is now being applied to biological data. With the advanced technology at hand, the main trend in biological research is rapidly changing from structural DNA analysis to understanding cellular functions of the DNA sequences. DNA chips are now being used to perform experiments and DNA analysis processes are being used by researchers. Clustering is one of the important processes used for grouping together similar entities. There are many clustering algorithms such as hierarchical clustering, self-organizing maps, K-means clustering and so on. In this paper, we propose a clustering algorithm that imitates the ecosystem taking into account the features of biological data. We implemented the system using an Ant-Colony clustering algorithm. The system decides the number of clusters automatically. The system processes the input biological data, runs the Ant-Colony algorithm, draws the Topic Map, assigns clusters to the genes and displays the output. We tested the algorithm with a test data of 100 to1000 genes and 24 samples and show promising results for applying this algorithm to clustering DNA chip data.

Keywords: Ant colony system, biological data, clustering, DNA chip.

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Authors: A. Danbaba

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Samurai Sudoku consists of five Sudoku square designs each having nine treatments in each row (column or sub-block) only once such the five Sudoku designs overlaps. Two or more Samurai designs can be joint together to give an extended Samurai design. In addition, two Samurai designs, each containing five Sudoku square designs, are mutually orthogonal (Graeco). If we superimpose two Samurai designs and obtained a pair of Latin and Greek letters in each row (column or sub-block) of the five Sudoku designs only once, then we have Graeco Samurai design. In this paper, simple method of constructing Samurai designs and mutually orthogonal Samurai design are proposed. In addition, linear models and methods of data analysis for the designs are proposed.

Keywords: Samurai design, Graeco samurai design, sudoku design, row or column swap.

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Authors: Chih-Hao Chen, Hsing-Chung Lee, Qingdong Ling, Hsiao-Jung Chen, Sun-Chong Wang, Li-Ching Wu, H.C. Lee

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Segmentation, filtering out of measurement errors and identification of breakpoints are integral parts of any analysis of microarray data for the detection of copy number variation (CNV). Existing algorithms designed for these tasks have had some successes in the past, but they tend to be O(N2) in either computation time or memory requirement, or both, and the rapid advance of microarray resolution has practically rendered such algorithms useless. Here we propose an algorithm, SAD, that is much faster and much less thirsty for memory – O(N) in both computation time and memory requirement -- and offers higher accuracy. The two key ingredients of SAD are the fundamental assumption in statistics that measurement errors are normally distributed and the mathematical relation that the product of two Gaussians is another Gaussian (function). We have produced a computer program for analyzing CNV based on SAD. In addition to being fast and small it offers two important features: quantitative statistics for predictions and, with only two user-decided parameters, ease of use. Its speed shows little dependence on genomic profile. Running on an average modern computer, it completes CNV analyses for a 262 thousand-probe array in ~1 second and a 1.8 million-probe array in 9 seconds

Keywords: Cancer, pathogenesis, chromosomal aberration, copy number variation, segmentation analysis.

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Authors: Jelena Zagorska, Inga Ciprovica

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the obligatory step during immunoglobulin and lysozyme concentration process is thermal treatment. The combination of temperature and time used in processing can affect the structure of the proteins and involve unfolding and aggregation. The aim of the present study was to evaluate the heat stability of total Igs, the particular immunoglobulin classes and lysozyme in milk. Milk samples were obtained from conventional dairy herd in Latvia. Raw milk samples were pasteurized in different regimes: 63 °C 30 min, 72 °C 15-20 s, 78 °C 15-20 s, 85 °C 15-20 s, 95 °C 15-20 s. The concentrations of Igs (IgA, IgG, IgM) and lysozyme were determined by turbodimetric method. During research was established, that activity of antimicrobial proteins decreases differently. Less concentration reduce was established in a case of lysozyme.

Keywords: immunoglobulins, lysozyme, milk, pasteurization

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Authors: Smajo Bisanovic, Mensur Hajro, Muris Dlakic

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This paper presents one comprehensive modelling approach for maintenance scheduling problem of thermal power units in competitive market. This problem is formulated as a 0/1 mixedinteger linear programming model. Model incorporates long-term bilateral contracts with defined profiles of power and price, and weekly forecasted market prices for market auction. The effectiveness of the proposed model is demonstrated through case study with detailed discussion.

Keywords: Maintenance scheduling, bilateral contracts, market prices, profit.

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Authors: Elsayed A. Habib Elamir

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In social network analysis the mean nodal degree and density of the graph can be considered as a measure of the activity of all actors in the network and this is an important property of a graph and for making comparisons among networks. Since subjects in a family or organization are subject to common environment factors, it is prime interest to study the association between responses. Therefore, we study the distribution of the mean nodal degree and density of the graph under correlated binary units. The cross product ratio is used to capture the intra-units association among subjects. Computer program and an application are given to show the benefits of the method.

Keywords: Correlated Binary data, cross product ratio, densityof the graph, multiplicative binomial distribution.

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Authors: Batel Noureddine, Mehenni Mohamed, Dekar Lies

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In biomedical implant field, a new formula is given for the study of Radio Frequency power attenuation by simultaneous effects of side and angular misalignment of the supply/data transfer coils. A confrontation with the practical measurements done into a Faraday cage, allowed a checking of the obtained theoretical results. The DC supply systems without material connection and the data transmitters used in the case of biomedical implants, can be well dimensioned by taking into account the possibility of power attenuation by misalignment of transfer coils

Keywords: Biomedical implant field, misalignment coils, powerattenuation, transmitter and receiver coils.

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Authors: Sobir T. Navruzov

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The problem of complex use of water resources in Central Asia by taking into consideration the sovereignty of the states and increasing demand on use of water for economic aspects are considered. Complex program with appropriate mathematical software intended for calculation of possible variants of using the Amudarya up-stream water resources according to satisfaction of incompatible requirements of the national economics in irrigation and energy generation is proposed.

Keywords: water resources, national economics, irrigation, transboundry, energy generation, optimal solution, program complex, up-stream, down-stream, compensating services.

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: Machine learning, stock market trading, logistic principal component analysis, automated stock investment system.

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Authors: I. Erins, J. Erina

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The aim of this article is to assess the existing business models used by the banks operating in the CEE countries in the time period from 2006 till 2011. In order to obtain research results, the authors performed qualitative analysis of the scientific literature on bank business models, which have been grouped into clusters that consist of such components as: 1) capital and reserves; 2) assets; 3) deposits, and 4) loans. In their turn, bank business models have been developed based on the types of core activities of the banks, and have been divided into four groups: Wholesale, Investment, Retail and Universal Banks. Descriptive statistics have been used to analyse the models, determining mean, minimal and maximal values of constituent cluster components, as well as standard deviation. The analysis of the data is based on such bank variable indices as Return on Assets (ROA) and Return on Equity (ROE).

Keywords: Banks, Business model, CEE, ROA, ROE.

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Authors: Shankar Kambhampaty, Venkata Srinivas Modali

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When architecting an application, key nonfunctional requirements such as performance, scalability, availability and security, which influence the architecture of the system, are some times not adequately addressed. Performance of the application may not be looked at until there is a concern. There are several problems with this reactive approach. If the system does not meet its performance objectives, the application is unlikely to be accepted by the stakeholders. This paper suggests an approach for performance modeling for web based J2EE and .Net applications to address performance issues early in the development life cycle. It also includes a Performance Modeling Case Study, with Proof-of-Concept (PoC) and implementation details for .NET and J2EE platforms.

Keywords: Performance Measures, Performance Modeling, Performance Testing, Resource Utilization, Response Time, Throughput.

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Authors: Hossein Mohammadpour, Rahman Dashti

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Power transformers are among the most important and expensive equipments in the electric power systems. Consequently the transformer protection is an essential part of the system protection. This paper presents a new method for locating transformer winding faults such as turn-to-turn, turn-to-core, turn-totransformer body, turn-to-earth, and high voltage winding to low voltage winding. In this study the current and voltage signals of input and output terminals of the transformer are measured, which the Fourier transform of measured signals and harmonic analysis determine the fault's location.

Keywords: turn-to-turn faults, short circuit, Fourier transform, harmonic analysis.

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Authors: Aditya Pratap Singh, Pradeep Tomar

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Software reusability is an essential characteristic of Component-Based Software (CBS). The component reusability is an important assess for the effective reuse of components in CBS. The attributes of reusability proposed by various researchers are studied and four of them are identified as potential factors affecting reusability. This paper proposes metric for reusability estimation of black-box software component along with metrics for Interface Complexity, Understandability, Customizability and Reliability. An experiment is performed for estimation of reusability through a case study on a sample web application using a real world component.

Keywords: Component-based software, component reusability, customizability, interface complexity, reliability, understandability.

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Authors: Fatimah Almah Saaid, Darfiana Nur, Robert King

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This paper presents a procedure for estimating VAR using Sequential Discounting VAR (SDVAR) algorithm for online model learning to detect fraudulent acts using the telecommunications call detailed records (CDR). The volatility of the VAR is observed allowing for non-linearity, outliers and change points based on the works of [1]. This paper extends their procedure from univariate to multivariate time series. A simulation and a case study for detecting telecommunications fraud using CDR illustrate the use of the algorithm in the bivariate setting.

Keywords: Telecommunications Fraud, SDVAR Algorithm, Multivariate time series, Vector Autoregressive, Change points.

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Authors: Miaomiao Yang, Shouming Zhong

Abstract:

This paper studies the problem of exponential stability analysis for uncertain neural networks with discrete and distributed time-varying delays. Together with a suitable augmented Lyapunov Krasovskii function, zero equalities, reciprocally convex approach and a novel sufficient condition to guarantee the exponential stability of the considered system. The several exponential stability criterion proposed in this paper is simpler and effective. Finally,numerical examples are provided to demonstrate the feasibility and effectiveness of our results.

Keywords: Exponential stability, Uncertain Neural networks, LMI approach, Lyapunov-Krasovskii function, Time-varying.

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Authors: Serkan Narli

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This study aims to specify to what extent students understand topology during the lesson and to determine possible misconceptions. 14 teacher trainees registered at Secondary School Mathematics education department were observed in the topology lessons throughout a semester and data collected at the first topology lesson is presented here. Students- knowledge was evaluated using a written test right before and after the topology lesson. Thus, what the students learnt in terms of the definition and examples of topologic space were specified as well as possible misconceptions. The findings indicated that students did not fully comprehend the topic and misunderstandings were due to insufficient pre-requisite knowledge of abstract mathematical topics and mathematical notation.

Keywords: Mathematics Education, Teacher Education, Topology.

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Authors: Daniel C. S. Lim, Eric Y. M. Yeo, W. Y. Tan

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This paper presents an overview of how calcium interacts with the various essential nutrients within an environment of cellular and hormonal interactions for the purpose of increasing bioavailability to the human body. One example of such interactions can be illustrated with calcium homeostasis. This paper gives an in-depth discussion on the possible interactive permutations with various nutrients and factors leading to the promotion of calcium bioavailability to the body. The review hopes to provide further insights into how calcium supplement formulations can be improved to better influence its bioavailability in the human body.

Keywords: Bioavailability, environment of cellular and hormonal interactions, combinative nutrition, nutrient synergy.

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Authors: V. C. Sathish Gandhi, R. Kumaravelan, S. Ramesh, M. Venkatesan, M. Ponraj

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Each year nearly nine hundred persons die in head injuries and over fifty thousand persons are severely injured due to non wearing of helmets. In motor cycle accidents, the human head is exposed to heavy impact loading against natural protection. In this work, an attempt has been made for analyzing the helmet with all the standard data. The simulation software ‘ANSYS’ is used to analyze the helmet with different conditions such as bottom fixed-load on top surface, bottom fixed -load on top line, side fixed –load on opposite surface, side fixed-load on opposite line and dynamic analysis. The maximum force of 19.5 kN is applied on the helmet to study the model in static and dynamic conditions. The simulation has been carried out for the static condition for the parameters like total deformation, strain energy, von-Mises stress for different cases. The dynamic analysis has been performed for the parameter like total deformation and equivalent elastic strain. The result shows that these values are concentrated in the retention portion of the helmet. These results have been compared with the standard experimental data proposed by the BIS and well within the acceptable limit.

Keywords: Helmet, Deformation, Strain energy, Equivalent elastic strain.

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Authors: Mahmud Fotuhi-Firuzabad, Saeed Afshar

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This paper presents the results of a preventive maintenance application-based study and modeling of failure rates in breakers of electrical distribution systems. This is a critical issue in the reliability assessment of a system. In the analysis conducted in this paper, the impacts of failure rate variations caused by a preventive maintenance are examined. This is considered as a part of a Reliability Centered Maintenance (RCM) application program. A number of load point reliability indices is derived using the mathematical model of the failure rate, which is established using the observed data in a distribution system.

Keywords: Reliability-Centered Maintenance (RCM), failure rate, preventive maintenance (PM), Distribution System Reliability.

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