Search results for: genomic data analysis

Authors: Nisar Ahmed Memon

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Embedding and extraction of a secret information as well as the restoration of the original un-watermarked image is highly desirable in sensitive applications like military, medical, and law enforcement imaging. This paper presents a novel reversible data-hiding method for digital images using integer to integer wavelet transform and companding technique which can embed and recover the secret information as well as can restore the image to its pristine state. The novel method takes advantage of block based watermarking and iterative optimization of threshold for companding which avoids histogram pre and post-processing. Consequently, it reduces the associated overhead usually required in most of the reversible watermarking techniques. As a result, it keeps the distortion small between the marked and the original images. Experimental results show that the proposed method outperforms the existing reversible data hiding schemes reported in the literature.

Keywords: Adaptive Thresholding, Companding Technique, Integer Wavelet Transform, Reversible Watermarking

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Authors: Abdulnasir Hossen, Ulrich Heute

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In 1990 [1] the subband-DFT (SB-DFT) technique was proposed. This technique used the Hadamard filters in the decomposition step to split the input sequence into low- and highpass sequences. In the next step, either two DFTs are needed on both bands to compute the full-band DFT or one DFT on one of the two bands to compute an approximate DFT. A combination network with correction factors was to be applied after the DFTs. Another approach was proposed in 1997 [2] for using a special discrete wavelet transform (DWT) to compute the discrete Fourier transform (DFT). In the first step of the algorithm, the input sequence is decomposed in a similar manner to the SB-DFT into two sequences using wavelet decomposition with Haar filters. The second step is to perform DFTs on both bands to obtain the full-band DFT or to obtain a fast approximate DFT by implementing pruning at both input and output sides. In this paper, the wavelet-based DFT (W-DFT) with Haar filters is interpreted as SB-DFT with Hadamard filters. The only difference is in a constant factor in the combination network. This result is very important to complete the analysis of the W-DFT, since all the results concerning the accuracy and approximation errors in the SB-DFT are applicable. An application example in spectral analysis is given for both SB-DFT and W-DFT (with different filters). The adaptive capability of the SB-DFT is included in the W-DFT algorithm to select the band of most energy as the band to be computed. Finally, the W-DFT is extended to the two-dimensional case. An application in image transformation is given using two different types of wavelet filters.

Keywords: Image Transform, Spectral Analysis, Sub-Band DFT, Wavelet DFT.

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Authors: Okechukwu Odinaka Ajaegbu

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In the recent past, discussing about sex among children and youths was frowned at by traditional norms and as such sexual discussions and behavior were approached with great respect. Things are actually falling apart with the increasing number of young people that engage in premarital sex. Due to lack of experience and sex education, many young people are becoming increasingly exposed to the risk of HIV infection. In the light of the above, this study discussed premarital sex, HIV, and use of condom among youths in Nigeria. Data for this study came from 2013 Nigeria Demographic and Health Survey and other secondary data. The survey revealed that only 18.5 percent of young women that had sex in the 12 months preceding the survey used condom. Out of 3306 never-married sexually active men and women, 1728 representing 52 percent live in urban areas and 43 percent of them did not use condom during sexual intercourse in the 12 months preceding the survey. This study concludes that for there to be reduction in prevalence of HIV/AIDS among Nigerian youths, there is need for concerted effort to be made towards educating youths on the expedient of the use of condom during sexual intercourse.

Keywords: Condom, HIV, Nigeria, Premarital sex, Youths.

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Authors: Rahil Garnavi, Mohammad Aldeen, M. Emre Celebi, Alauddin Bhuiyan, Constantinos Dolianitis, George Varigos

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Automatic segmentation of skin lesions is the first step towards development of a computer-aided diagnosis of melanoma. Although numerous segmentation methods have been developed, few studies have focused on determining the most discriminative and effective color space for melanoma application. This paper proposes a novel automatic segmentation algorithm using color space analysis and clustering-based histogram thresholding, which is able to determine the optimal color channel for segmentation of skin lesions. To demonstrate the validity of the algorithm, it is tested on a set of 30 high resolution dermoscopy images and a comprehensive evaluation of the results is provided, where borders manually drawn by four dermatologists, are compared to automated borders detected by the proposed algorithm. The evaluation is carried out by applying three previously used metrics of accuracy, sensitivity, and specificity and a new metric of similarity. Through ROC analysis and ranking the metrics, it is shown that the best results are obtained with the X and XoYoR color channels which results in an accuracy of approximately 97%. The proposed method is also compared with two state-ofthe- art skin lesion segmentation methods, which demonstrates the effectiveness and superiority of the proposed segmentation method.

Keywords: Border detection, Color space analysis, Dermoscopy, Histogram thresholding, Melanoma, Segmentation.

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Authors: Sanae Attioui, Said Najah

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The Earth's surface is constantly changing through forces of nature and human activities. Reliable, accurate, and timely change detection is critical to environmental monitoring, resource management, and planning activities. Recently, interest in deep learning algorithms, especially convolutional neural networks, has increased in the field of image change detection due to their powerful ability to extract multi-level image features automatically. However, these networks are prone to drawbacks that limit their applications, which reside in their inability to capture spatial relationships between image instances, as this necessitates a large amount of training data. As an alternative, Capsule Network has been proposed to overcome these shortcomings. Although its effectiveness in remote sensing image analysis has been experimentally verified, its application in change detection tasks remains very sparse. Motivated by its greater robustness towards improved hierarchical object representation, this study aims to apply a capsule network for PolSAR image Change Detection. The experimental results demonstrate that the proposed change detection method can yield a significantly higher detection rate compared to methods based on convolutional neural networks.

Keywords: Change detection, capsule network, deep network, Convolutional Neural Networks, polarimetric synthetic aperture radar images, PolSAR images.

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Authors: D. H. Park, Y. H. Tak, H. H. Kwon, G. J. Kwon, H. G. Kim

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The purpose of this study is to develop a forging process of automotive parts that satisfies the deformation characteristics. The analyses of temperature variation and deformation behavior of the material are important to obtain the optimal forging products. The hot compression test was carried out to know formability at high temperature. In order to define the optimum forging conditions including material temperature, strain and forging load, the commercial finite element analysis code was used to simulate the forging procedure of engine mounting parts. Experimental results were compared with the simulation results by finite element analysis. Test results were in good agreement with the simulations.

Keywords: Cold forging, hot forging, engine mounting, automotive parts, optimization.

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Authors: Cindy Wang-Cowham, Judy Ningyu Tang

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The paper contributes towards the development of scarce literature on HR knowledge management. Drawing literature from knowledge management, the authors define the meaning of HR knowledge and propose that there are social mechanisms in organizations that facilitate the management and sharing of HR knowledge. Instead of investigating the subject in large multinational corporations, the present paper examines it in a large Chinese privately owned enterprise, which has an international standing. The main finding of the case analysis is that communication and feedback plays a pivotal role when managing HR knowledge. Social mechanisms can stimulate the communication and feedback between employees, thus facilitate knowledge exchange.

Keywords: HR knowledge, knowledge management, large privately owned enterprises, China.

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Authors: N. Kazantseva, P. Krakhmalev, I. Yadroitsev, A. Fefelov, N. Vinogradova, I. Ezhov, T. Kurennykh

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Martensitic texture-phase transition in Selective Laser Melting (SLM) Ti-6Al-4V (ELI) alloys was found. Electron Backscatter Diffraction (EBSD) analysis showed the initial cubic beta < 100 > (001) BCC texture. Such kind of texture is observed in BCC metals with flat rolling texture when axis is in the direction of rolling and the texture plane coincides with the plane of rolling. It was found that the texture of the parent BCC beta-phase determined the texture of low-temperature HCP alpha-phase limited the choice of its orientation variants. The {10-12} < -1011 > twinning system in titanium alloys after SLM was determined. Analysis of the oxygen contamination in SLM alloys was done. Comparison of the obtained results with the conventional titanium alloys is also provided.

Keywords: Additive technology, texture, Ti-6Al-4V, twins, oxygen content.

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Authors: Nuridayanti Che Khalib, Kaliyaperumal Thanigaimani, Suhana Arshad, Ibrahim Abdul Razak

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The 1:1 cocrystal of 2-amino-4-chloro-6- methylpyrimidine (2A4C6MP) with 4-methylbenzoic acid (4MBA) (I) has been prepared by slow evaporation method in methanol, which was crystallized in monoclinic C2/c space group, Z = 8, and a = 28.431 (2) Å, b = 7.3098 (5) Å, c = 14.2622 (10) Å and β = 109.618 (3)°. The presence of unionized –COOH functional group in cocrystal I was identified both by spectral methods (1H and 13C NMR, FTIR) and X-ray diffraction structural analysis. The 2A4C6MP molecule interact with the carboxylic group of the respective 4MBA molecule through N—H⋯O and O—H⋯N hydrogen bonds, forming a cyclic hydrogen–bonded motif R2 2(8). The crystal structure was stabilized by Npyrimidine—H⋯O=C and C=O—H⋯Npyrimidine types hydrogen bonding interactions. Theoretical investigations have been computed by HF and density function (B3LYP) method with 6–311+G (d,p)basis set. The vibrational frequencies together with 1H and 13C NMR chemical shifts have been calculated on the fully optimized geometry of cocrystal I. Theoretical calculations are in good agreement with the experimental results. Solvent–free formation of this cocrystal I is confirmed by powder X-ray diffraction analysis.

Keywords: Supramolecular Cocrystal, 2-amino-4-chloro-6- methylpyrimidine, Hartree-Fock and DFT Studies, Spectroscopic Analysis.

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Authors: Yose Rizal, Maria Endo Mahata, Mira Andriani, Guoyao Wu

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An experiment was conducted with 80 unsexed broilers of the Arbor Acress strain to determine the capability of a carrot and fruit juice wastes mixture (carrot, apple, manggo, avocado, orange, melon and Dutch egg plant) in the same proportion for replacing corn in broiler diet. This study involved a completely randomized design (CRD) with 5 treatments (0, 5, 10, 15, and 20% of juice wastes mixture in diets) and 4 replicates per treatment. Diets were isonitrogenous (22% crude protein) and isocaloric (3000 kcal/kg diet). Measured variables were feed consumption, average daily gain, feed conversion, as well as percentages of abdominal fat pad, carcass, digestive organs (liver, pancreas and gizzard), and heart. Data were analyzed by analysis of variance for CRD. Increasing juice wastes mixture levels in diets increased feed consumption (P<0.05) and average daily gain (P<0.01), while improving feed utilization efficiency (P<0.05). These treatments also affected (P<0.05) abdominal fat pad percentage but had no effect (P>0.05) on carcass, liver, pancreas, gizzard or heart percentages. In conclusion, up to 20% of juice wastes mixture could be included for the broiler diet to effectively replace up to 40% corn in the diet.

Keywords: average daily gain, feed consumption, feedconversion, juice waste mixture

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Authors: Samad Jafarmadar, Amin Habibzadeh, Mohammad Mehdi Rashidi, Sayed Sina Rezaei, Abbas Aghagoli

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In this paper, the ejector-absorption refrigeration cycle is presented. This article deals with the thermodynamic simulation and the first and second law analysis of an ammonia-water. The effects of parameters such as condenser, absorber, generator, and evaporator temperatures have been investigated. The influence of the various operating parameters on the performance coefficient and exergy efficiency of this cycle has been studied. The results show that when the temperature of different parts increases, the performance coefficient and the exergy efficiency of the cycle decrease, except for evaporator and generator, that causes an increase in coefficient of performance (COP). According to the results, absorber and ejector have the highest exergy losses in the studied conditions.

Keywords: Absorption refrigeration, COP, ejector, exergy efficiency.

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Authors: Sorayya Malek, Mogeeb Mosleh, Sharifah M. Syed

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In this study, Support Vector Machine (SVM) technique was applied to predict the dichotomized value of Dissolved oxygen (DO) from two freshwater lakes namely Chini and Bera Lake (Malaysia). Data sample contained 11 parameters for water quality features from year 2005 until 2009. All data parameters were used to predicate the dissolved oxygen concentration which was dichotomized into 3 different levels (High, Medium, and Low). The input parameters were ranked, and forward selection method was applied to determine the optimum parameters that yield the lowest errors, and highest accuracy. Initial results showed that pH, Water Temperature, and Conductivity are the most important parameters that significantly affect the predication of DO. Then, SVM model was applied using the Anova kernel with those parameters yielded 74% accuracy rate. We concluded that using SVM models to predicate the DO is feasible, and using dichotomized value of DO yields higher prediction accuracy than using precise DO value.

Keywords: Dissolved oxygen, Water quality, predication DO, Support Vector Machine.

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Authors: Ayşe Coban, Orhan Coban, Haldun Soydal, Sükrü Sürücü

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While health is a source of prosperity for individuals, it is also one of the most important determinants of economic growth for a country. Health, by increasing the productivity of labor, contributes to economic growth. Therefore, countries should give the necessary emphasis to health services. The primary aim of this study is to analyze the changes occurring in health services in Turkey by examining the developments in the sector. In this scope, the second aim of the study is to reveal the place of health expenditures in the Turkish economy. As a result of the analysis in the dataset, in which the 1999-2013 periods is considered, it was determined that some increase in health expenditures took place and that the increase in the share of health expenditures in GDP was too small. Furthermore, analysis of the results points out that in financing health expenditures, the public sector is prominent compared to the private sector.

Keywords: Healthcare, health service, health expenditures, Turkey.

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Authors: Jijimon Alakkalam Joseph

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The UN 2030 Agenda for Sustainable Development claims to be a comprehensive and integrated plan of action for prosperity for people and the planet, including almost all dimensions of human existence. Nevertheless, the religious dimension of human existence has been kept away from development discussions. Care for the earth is one of the vital aspects of sustainable development. Farmers all over the world contribute much to environmental protection. Most farmers are religious believers and religious ideologies influence their agricultural practices. This nexus between faith and agriculture has forced policymakers to include religion in development discussions. This paper delves deeper into this religion and sustainable development connection. Buddhism and Christianity have contributed much to environmental protection in Taiwan. However, interviews conducted among 40 Taiwanese farmers (10 male and female farmers from Buddhism and Christianity) show that their faith experiences make them relate to the natural environment differently. Most of the Buddhist farmers interviewed admitted that they chose their religious adherence, while most of the Christian farmers inherited their faith. The in-depth analysis of the interview data collected underlines the close relationship between religion and sustainable development. More importantly, concerning their intention to care for the earth, farmers whose religious adherence is ‘chosen’ are self-motivated and more robust compared to those whose religious adherence is ‘inherited’.

Keywords: Buddhism, Christianity, environmental protection, sustainable development.

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluates the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: lexical semantics, feature representation, semantic decision, convolutional neural network, electronic medical record

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Authors: Emre Ipekci Cetin, Ebru Tarcan Icigen

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Personnel selection process is considered as one of the most important and most difficult issues in human resources management. At the stage of personnel selection, the applicants are handled according to certain criteria, the candidates are dealt with, and efforts are made to select the most appropriate candidate. However, this process can be more complicated in terms of the managers who will carry out the staff selection process. Candidates should be evaluated according to different criteria such as work experience, education, foreign language level etc. It is crucial that a rational selection process is carried out by considering all the criteria in an integrated structure. In this study, the problem of choosing the front office manager of a 5 star accommodation enterprise operating in Antalya is addressed by using multi-criteria decision-making methods. In this context, SWARA (Step-wise weight assessment ratio analysis) and MOORA (Multi-Objective Optimization on the basis of ratio analysis) methods, which have relatively few applications when compared with other methods, have been used together. Firstly SWARA method was used to calculate the weights of the criteria and subcriteria that were determined by the business. After the weights of the criteria were obtained, the MOORA method was used to rank the candidates using the ratio system and the reference point approach. Recruitment processes differ from sector to sector, from operation to operation. There are a number of criteria that must be taken into consideration by businesses in accordance with the structure of each sector. It is of utmost importance that all candidates are evaluated objectively in the framework of these criteria, after these criteria have been carefully selected in the selection of suitable candidates for employment. In the study, staff selection process was handled by using SWARA and MOORA methods together.

Keywords: Accommodation establishments, human resource management, MOORA, multi criteria decision making, SWARA.

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Authors: Nuzlinda Abdul Rahman, Syerrina Zakaria

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Deprivation indices are widely used in public health study. These indices are also referred as the index of inequalities or disadvantage. Even though, there are many indices that have been built before, it is believed to be less appropriate to use the existing indices to be applied in other countries or areas which had different socio-economic conditions and different geographical characteristics. The objective of this study is to construct the index based on the geographical and socio-economic factors in Peninsular Malaysia which is defined as the weighted household-based deprivation index. This study has employed the variables based on household items, household facilities, school attendance and education level obtained from Malaysia 2000 census report. The factor analysis is used to extract the latent variables from indicators, or reducing the observable variable into smaller amount of components or factor. Based on the factor analysis, two extracted factors were selected, known as Basic Household Amenities and Middle-Class Household Item factor. It is observed that the district with a lower index values are located in the less developed states like Kelantan, Terengganu and Kedah. Meanwhile, the areas with high index values are located in developed states such as Pulau Pinang, W.P. Kuala Lumpur and Selangor.

Keywords: Factor Analysis, Basic Household Amenities, Middle-Class Household Item, Socio-economic Index

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Authors: [email protected]

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data need a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM), ensemble learning with hyper parameters optimization, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: Machine learning, Deep learning, cancer prediction, breast cancer, LSTM, Score-Level Fusion.

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Authors: Jatinderkumar R. Saini, Apurva A. Desai

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e-mail has become an important means of electronic communication but the viability of its usage is marred by Unsolicited Bulk e-mail (UBE) messages. UBE consists of many types like pornographic, virus infected and 'cry-for-help' messages as well as fake and fraudulent offers for jobs, winnings and medicines. UBE poses technical and socio-economic challenges to usage of e-mails. To meet this challenge and combat this menace, we need to understand UBE. Towards this end, the current paper presents a content-based textual analysis of more than 2700 body enhancement medicinal UBE. Technically, this is an application of Text Parsing and Tokenization for an un-structured textual document and we approach it using Bag Of Words (BOW) and Vector Space Document Model techniques. We have attempted to identify the most frequently occurring lexis in the UBE documents that advertise various products for body enhancement. The analysis of such top 100 lexis is also presented. We exhibit the relationship between occurrence of a word from the identified lexis-set in the given UBE and the probability that the given UBE will be the one advertising for fake medicinal product. To the best of our knowledge and survey of related literature, this is the first formal attempt for identification of most frequently occurring lexis in such UBE by its textual analysis. Finally, this is a sincere attempt to bring about alertness against and mitigate the threat of such luring but fake UBE.

Keywords: Body Enhancement, Lexis, Medicinal, Unsolicited Bulk e-mail (UBE), Vector Space Document Model, Viagra

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Authors: B. Tomczyk, R. Mania

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Thin linear-elastic cylindrical circular shells having a micro-periodic structure along two directions tangent to the shell midsurface (biperiodic shells) are object of considerations. The aim of this paper is twofold. First, we formulate an averaged nonasymptotic model for the analysis of parametric vibrations or dynamical stability of periodic shells under consideration, which has constant coefficients and takes into account the effect of a cell size on the overall shell behavior (a length-scale effect). This model is derived employing the tolerance modeling procedure. Second we apply the obtained model to derivation of frequency equation being a starting point in the analysis of parametric vibrations. The effect of the microstructure length oh this frequency equation is discussed.

Keywords: Micro-periodic shells, mathematical modeling, length-scale effect, parametric vibrations

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Authors: Aline Zeitunlian, Ramzi A. Haraty

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Caching was suggested as a solution for reducing bandwidth utilization and minimizing query latency in mobile environments. Over the years, different caching approaches have been proposed, some relying on the server to broadcast reports periodically informing of the updated data while others allowed the clients to request for the data whenever needed. Until recently a hybrid cache consistency scheme Scalable Asynchronous Cache Consistency Scheme SACCS was proposed, which combined the two different approaches benefits- and is proved to be more efficient and scalable. Nevertheless, caching has its limitations too, due to the limited cache size and the limited bandwidth, which makes the implementation of cache replacement strategy an important aspect for improving the cache consistency algorithms. In this thesis, we proposed a new cache replacement strategy, the Least Unified Value strategy (LUV) to replace the Least Recently Used (LRU) that SACCS was based on. This paper studies the advantages and the drawbacks of the new proposed strategy, comparing it with different categories of cache replacement strategies.

Keywords: Cache consistency, hybrid algorithm, and mobileenvironments

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Authors: Payam Haghparast, Mikhail V. Sorin, Hakim Nesreddine

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The complex oblique shock phenomenon can be simply assumed as a normal shock at the constant area section to simulate a sharp pressure increase and velocity decrease in 1-D thermodynamic models. The assumed normal shock location is one of the greatest sources of error in ejector thermodynamic models. Most researchers consider an arbitrary location without justifying it. Our study compares the effect of normal shock place on ejector dimensions in 1-D models. To this aim, two different ejector experimental test benches, a constant area-mixing ejector (CAM) and a constant pressure-mixing (CPM) are considered, with different known geometries, operating conditions and working fluids (R245fa, R141b). In the first step, in order to evaluate the real value of the efficiencies in the different ejector parts and critical back pressure, a CFD model was built and validated by experimental data for two types of ejectors. These reference data are then used as input to the 1D model to calculate the lengths and the diameters of the ejectors. Afterwards, the design output geometry calculated by the 1D model is compared directly with the corresponding experimental geometry. It was found that there is a good agreement between the ejector dimensions obtained by the 1D model, for both CAM and CPM, with experimental ejector data. Furthermore, it is shown that normal shock place affects only the constant area length as it is proven that the inlet normal shock assumption results in more accurate length. Taking into account previous 1D models, the results suggest the use of the assumed normal shock location at the inlet of the constant area duct to design the supersonic ejectors.

Keywords: 1D model, constant area-mixing, constant pressure-mixing, normal shock location, ejector dimensions.

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Authors: A. M. Tahsini

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Solid fuel transient burning behavior under oxidizer gas flow is numerically investigated. It is done using analysis of the regression rate responses to the imposed sudden and oscillatory variation at inflow properties. The conjugate problem is considered by simultaneous solution of flow and solid phase governing equations to compute the fuel regression rate. The advection upstream splitting method is used as flow computational scheme in finite volume method. The ignition phase is completely simulated to obtain the exact initial condition for response analysis. The results show that the transient burning effects which lead to the combustion instabilities and intermittent extinctions could be observed in solid fuels as the solid propellants.

Keywords: Extinction, Oscillation, Regression rate, Response, Transient burning.

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Authors: Z. Ishak, S. Jamaluddin, F.P Chew

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This paper examines the students’ self-concept among 16- and 17- year- old adolescents in Malaysian secondary schools. Previous studies have shown that positive self-concept played an important role in student adjustment and academic performance during schooling. This study attempts to investigate the factors influencing students’ perceptions toward their own self-concept. A total of 1168 students participated in the survey. This study utilized the CoPs (UM) instrument to measure self-concept. Principal Component Analysis (PCA) revealed three factors: academic selfconcept, physical self-concept and social self-concept. This study confirmed that students perceived certain internal context factors, and revealed that external context factor also have an impact on their self-concept.

Keywords: Academic self-concept, physical self-concept, Principal Component Analysis (PCA), social self-concept.

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Authors: Bo Wun Huang, Pu Ping Yu, Jao-Hwa Kuang

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For smaller mechatronic device, especially for micro Electronic system, a micro machining is a must. However, most investigations on vibration of a mill have been limited to the traditional type mill. In this article, vibration and dynamic characteristics of a micro mill were investigated in this study. The trend towards higher precision manufacturing technology requires producing miniaturized components. To improve micro-milled product quality, obtain a higher production rate and avoid milling breakage, the dynamic characteristics of micro milling must be studied. A stepped pre-twisted mill is used to simulate the micro mill. The finite element analysis is employed in this work. The flute length and diameter effects of the micro mill are considered. It is clear that the effects of micro mill shape parameters on vibration in a micro mill are significant.

Keywords: micro system, micro mill, vibration.

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Authors: Dyi-Cheng Chen, Wen-Hsuan Ku, Ming-Ren Chen

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The current of professional bicycle pedal-s manufacturing model mostly used casting, forging, die-casting processing methods, so the paper used 7075 aluminum alloy which is to produce the bicycle parts most commonly, and employs the rigid-plastic finite element (FE) DEFORMTM 3D software to simulate and to analyze the professional bicycle pedal design. First we use Solid works 2010 3D graphics software to design the professional bicycle pedal of the mold and appearance, then import finite element (FE) DEFORMTM 3D software for analysis. The paper used rigid-plastic model analytical methods, and assuming mode to be rigid body. A series of simulation analyses in which the variables depend on different temperature of forging billet, friction factors, forging speed, mold temperature are reveal to effective stress, effective strain, damage and die radial load distribution for forging bicycle pedal. The analysis results hope to provide professional bicycle pedal forming mold references to identified whether suit with the finite element results for high-strength design suitability of aluminum alloy.

Keywords: Bicycle pedal, finite element analysis, 7075 aluminum alloy, Taguchi method

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Authors: Souvik Bhattacharyya, Gautam Sanyal

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Recent years have witnessed the rapid development of the Internet and telecommunication techniques. Information security is becoming more and more important. Applications such as covert communication, copyright protection, etc, stimulate the research of information hiding techniques. Traditionally, encryption is used to realize the communication security. However, important information is not protected once decoded. Steganography is the art and science of communicating in a way which hides the existence of the communication. Important information is firstly hidden in a host data, such as digital image, video or audio, etc, and then transmitted secretly to the receiver.In this paper a data hiding model with high security features combining both cryptography using finite state sequential machine and image based steganography technique for communicating information more securely between two locations is proposed. The authors incorporated the idea of secret key for authentication at both ends in order to achieve high level of security. Before the embedding operation the secret information has been encrypted with the help of finite-state sequential machine and segmented in different parts. The cover image is also segmented in different objects through normalized cut.Each part of the encoded secret information has been embedded with the help of a novel image steganographic method (PMM) on different cuts of the cover image to form different stego objects. Finally stego image is formed by combining different stego objects and transmit to the receiver side. At the receiving end different opposite processes should run to get the back the original secret message.

Keywords: Cover Image, Finite state sequential machine, Melaymachine, Pixel Mapping Method (PMM), Stego Image, NCUT.

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Authors: Nor Fadzillah Mohd Mokhtar, Norihan Md Arifin, Roslinda Nazar, Fudziah Ismail, MohamedSuleiman

Abstract:

The stability analysis of Marangoni convection in porous media with a deformable upper free surface is investigated. The linear stability theory and the normal mode analysis are applied and the resulting eigenvalue problem is solved exactly. The Darcy law and the Brinkman model are used to describe the flow in the porous medium heated from below. The effect of the Crispation number, Bond number and the Biot number are analyzed for the stability of the system. It is found that a decrease in the Crispation number and an increase in the Bond number delay the onset of convection in porous media. In addition, the system becomes more stable when the Biot number is increases and the Daeff number is decreases.

Keywords: Deformable, Marangoni, Porous, Stability.

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Authors: Kamaldeep Kaur, Arvinder Kaur, Ruchika Malhotra

Abstract:

The aim of this paper is to rank the impact of Object Oriented(OO) metrics in fault prediction modeling using Artificial Neural Networks(ANNs). Past studies on empirical validation of object oriented metrics as fault predictors using ANNs have focused on the predictive quality of neural networks versus standard statistical techniques. In this empirical study we turn our attention to the capability of ANNs in ranking the impact of these explanatory metrics on fault proneness. In ANNs data analysis approach, there is no clear method of ranking the impact of individual metrics. Five ANN based techniques are studied which rank object oriented metrics in predicting fault proneness of classes. These techniques are i) overall connection weights method ii) Garson-s method iii) The partial derivatives methods iv) The Input Perturb method v) the classical stepwise methods. We develop and evaluate different prediction models based on the ranking of the metrics by the individual techniques. The models based on overall connection weights and partial derivatives methods have been found to be most accurate.

Keywords: Artificial Neural Networks (ANNS), Backpropagation, Fault Prediction Modeling.

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Authors: A. Rajagopal, S. Somasundaram, B. Sowmya, T. Suguna

Abstract:

Wireless Sensor Networks (WSNs) enable new applications and need non-conventional paradigms for the protocol because of energy and bandwidth constraints, In WSN, sensor node’s life is a critical parameter. Research on life extension is based on Low-Energy Adaptive Clustering Hierarchy (LEACH) scheme, which rotates Cluster Head (CH) among sensor nodes to distribute energy consumption over all network nodes. CH selection in WSN affects network energy efficiency greatly. This study proposes an improved CH selection for efficient data aggregation in sensor networks. This new algorithm is based on Bacterial Foraging Optimization (BFO) incorporated in LEACH.

Keywords: Bacterial Foraging Optimization (BFO), Cluster Head (CH), Data-aggregation protocols, Low-Energy Adaptive Clustering Hierarchy (LEACH).

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