Search results for: principal component regression

Authors: Slim Yacoub, Kosai Raoof

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The aim of this study was to remove the two principal noises which disturb the surface electromyography signal (Diaphragm). These signals are the electrocardiogram ECG artefact and the power line interference artefact. The algorithm proposed focuses on a new Lean Mean Square (LMS) Widrow adaptive structure. These structures require a reference signal that is correlated with the noise contaminating the signal. The noise references are then extracted : first with a noise reference mathematically constructed using two different cosine functions; 50Hz (the fundamental) function and 150Hz (the first harmonic) function for the power line interference and second with a matching pursuit technique combined to an LMS structure for the ECG artefact estimation. The two removal procedures are attained without the use of supplementary electrodes. These techniques of filtering are validated on real records of surface diaphragm electromyography signal. The performance of the proposed methods was compared with already conducted research results.

Keywords: Surface EMG, Adaptive, Matching Pursuit, Powerline interference.

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Authors: V. Churkin, M. Lopatin

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The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second – 95,3%.

Keywords: Bass model, generalized Bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States.

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Authors: Humberto N. Teixeira, Isabel S. Lopes, Sérgio D. Sousa

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This article proposes a new methodology to be used by SMEs (Small and Medium enterprises) to characterize their performance in quality, highlighting weaknesses and area for improvement. The methodology aims to identify the principal causes of quality problems and help to prioritize improvement initiatives. This is a self-assessment methodology that intends to be easy to implement by companies with low maturity level in quality. The methodology is organized in six different steps which includes gathering information about predetermined processes and subprocesses of quality management, defined based on the well-known Juran-s trilogy for quality management (Quality planning, quality control and quality improvement) and, predetermined results categories, defined based on quality concept. A set of tools for data collecting and analysis, such as interviews, flowcharts, process analysis diagrams and Failure Mode and effects Analysis (FMEA) are used. The article also presents the conclusions obtained in the application of the methodology in two cases studies.

Keywords: Continuous improvement, Diagnosis, Quality Management, Self-assessment, SMEs

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Authors: Lai-Fen Yang

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In this increasingly visual world, how can we best decipher and understand the many ways that our everyday lives are organized around looking practices and the many images we encounter each day? Indeed, how we interact with and interpret visual images is a basic component of human life. Today, however, we are living in one of the most artificial visual and image-saturated cultures in human history, which makes understanding the complex construction and multiple social functions of visual imagery more important than ever before. Themes regarding our experience of a visually pervasive mediated culture, here, termed visual spectacle.

Keywords: Visual culture, contemporary, visual spectacle.

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Authors: K. K. Kaldybay, T. K. Abdrassilov, G. K. Abdygalieva, P. M. Suleymenov, M. O. Nassimov

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People have always needed to believe in some supernatural power, which could explain nature phenomena. Different kinds of religions like Christianity, Hinduism, Islam, Buddhism have thought believers in all world, how to behave themselves. We think the most important role of religion in modern society most important role of religion in modern society is safety of the People. World and traditional religion played a prominent role in the socio-cultural progress, and in the development of man as a spiritual being. At the heart of religious morals the belief in god and responsibility before it lies and specifies religious and ethical values and categories . The religion is based on ethical standards historically developed by society, requirements and concepts, but it puts all social and moral relations of the person in dependence on religious values. For everything that the believer makes on a debt or a duty, he bears moral responsibility before conscience, people and god. The concept of value of religious morals takes the central place because the religion from all forms of public consciousness most values is painted as it is urged to answer vital questions. Any religion not only considers questions of creation of the world, sense of human existence, relationship of god and the person, but also offers the ethical concept, develops rules of behavior of people. The religion a long time dominated in the history of culture, and during this time created a set of cultural and material values. The identity of Kazakh culture can be defined as a Cultural identity traditional ,national identity and the identity values developed by Kazakh people in process of cultural-historical development, promoting formation of Kazakh culture identity on public consciousness. Identity is the historical process but always the tradition exists in it as a component of stability, as a component of self that what this identity formed .

Keywords: Philosophy, religion, education, culture, human, national value, security, religious value.

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Authors: M. R. Naghavi, S. Rashidi Monfared, A. H. Ahkami, M. A. Ombidbakhsh

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Knowledge of patterns of genetic diversity enhances the efficiency of germplasm conservation and improvement. In this study 96 Iranian landraces of Triticum turgidum originating from different geographical areas of Iran, along with 18 durum cultivars from ten countries were evaluated for variation in morphological and high molecular weight glutenin subunit (HMW-GS) composition. The first two principal components clearly separated the Iranian landraces from cultivars. Three alleles were present at the Glu-A1 locus and 11 alleles at Glu-B1. In both cultivars and landraces of durum wheat, the null allele (Glu-A1c) was observed more frequently than the Glu-A1a and Glu-A1b alleles. Two alleles, namely Glu-B1a (subunit 7) and Glu-B1e (subunit 20) represented the more frequent alleles at Glu-B1 locus. The results showed that the evaluated Iranian landraces formed an interesting source of favourable glutenin subunits that might be very desirable in breeding activities for improving pasta-making quality.

Keywords: Triticum turgidum var. durum, glutenin subunits, morphological characters.

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Authors: Jörg Linde, Ekaterina Buyko, Robert Altwasser, Udo Hahn, Reinhard Guthke

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Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.

Keywords: Pathogen, network inference, text-mining, Candida albicans, LASSO, mutual information, reverse engineering, linear regression, modelling.

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Authors: S. Sarumathi, N. Shanthi, P. Ranjetha

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Data mining is the procedure of determining interesting patterns from the huge amount of data. With the intention of accessing the data faster the most supporting processes needed is clustering. Clustering is the process of identifying similarity between data according to the individuality present in the data and grouping associated data objects into clusters. Cluster ensemble is the technique to combine various runs of different clustering algorithms to obtain a general partition of the original dataset, aiming for consolidation of outcomes from a collection of individual clustering outcomes. The performances of clustering ensembles are mainly affecting by two principal factors such as diversity and quality. This paper presents the overview about the different cluster ensemble algorithm along with their methods used in cluster ensemble to improve the diversity and quality in the several cluster ensemble related papers and shows the comparative analysis of different cluster ensemble also summarize various cluster ensemble methods. Henceforth this clear analysis will be very useful for the world of clustering experts and also helps in deciding the most appropriate one to determine the problem in hand.

Keywords: Cluster Ensemble, Consensus Function, CSPA, Diversity, HGPA, MCLA.

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Authors: David E. Culler, Noah D. Anderson

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Integrated systems for product design, manufacturing, and lifecycle management are difficult to implement and customize. Commercial software vendors, including CAD/CAM and third party PDM/PLM developers, create user interfaces and functionality that allow their products to be applied across many industries. The result is that systems become overloaded with functionality, difficult to navigate, and use terminology that is unfamiliar to engineers and production personnel. For example, manufacturers of automotive, aeronautical, electronics, and household products use similar but distinct methods and processes. Furthermore, each company tends to have their own preferred tools and programs for controlling work and information flow and that connect design, planning, and manufacturing processes to business applications. This paper presents a methodology and a case study that addresses these issues and suggests that in the future more companies will develop personalized applications that fit to the natural way that their business operates. A functioning system has been implemented at a highly competitive U.S. aerospace tooling and component supplier that works with many prominent airline manufacturers around the world including The Boeing Company, Airbus, Embraer, and Bombardier Aerospace. During the last three years, the program has produced significant benefits such as the automatic creation and management of component and assembly designs (parametric models and drawings), the extensive use of lightweight 3D data, and changes to the way projects are executed from beginning to end. CATIA (CAD/CAE/CAM) and a variety of programs developed in C#, VB.Net, HTML, and SQL make up the current system. The web-based platform is facilitating collaborative work across multiple sites around the world and improving communications with customers and suppliers. This work demonstrates that the creative use of Application Programming Interface (API) utilities, libraries, and methods is a key to automating many time-consuming tasks and linking applications together.

Keywords: CAD/CAM, CAPP, PDM, PLM, Scalable Systems.

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Authors: Haythem Yahyaoui, Samir Moalla, Mounir Bouden, Skander Ghorbel

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Nowadays, cloud environments are becoming a need for companies, this new technology gives the opportunities to access to the data anywhere and anytime. It also provides an optimized and secured access to the resources and gives more security for the data which is stored in the platform. However, some companies do not trust Cloud providers, they think that providers can access and modify some confidential data such as bank accounts. Many works have been done in this context, they conclude that encryption methods realized by providers ensure the confidentiality, but, they forgot that Cloud providers can decrypt the confidential resources. The best solution here is to apply some operations on the data before sending them to the provider Cloud in the objective to make them unreadable. The principal idea is to allow user how it can protect his data with his own methods. In this paper, we are going to demonstrate our approach and prove that is more efficient in term of execution time than some existing methods. This work aims at enhancing the quality of service of providers and ensuring the trust of the customers. 

Keywords: Confidentiality, cryptography, security issues, trust issues.

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion detection system (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw dataset for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle component analysis (PCA), Linear Discriminant Analysis (LDA) and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. This optimal feature subset is used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) are used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle component analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP).

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Authors: T. Özdal, N. Şahin Yeşilcubuk

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Bisphenol-A (BPA) is one of the highest volume chemicals produced worldwide in the plastic industry. This compound is mostly used in producing polycarbonate plastics that are often used for food and beverage storage, and BPA is also a component of epoxy resins that are used to line food and beverage containers. Studies performed in this area indicated that BPA could be extracted from such products while they are in contact with food.  Therefore, BPA exposure is presumed. In this paper, the chemical structure of BPA, factors affecting BPA migration to food and beverages, effects on health, and recent regulations will be reviewed.

Keywords: BPA, health, regulations, toxicity.

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: Artificial Neural Networks, ANNs, classifier algorithms, credit risk assessment, logistic regression, machine learning, support vector machines.

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Authors: Hanifeh Imanian, Morteza Kolahdoozan

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The purpose of this study is to present a mathematical phrase for calculating the dispersion rate of spilled oil in water column under non-breaking waves. In this regard, a multiphase numerical model is applied for which waves and oil phase were computed concurrently, and accuracy of its hydraulic calculations have been proven. More than 200 various scenarios of oil spilling in wave waters were simulated using the multiphase numerical model and its outcome were collected in a database. The recorded results were investigated to identify the major parameters affected vertical oil dispersion and finally 6 parameters were identified as main independent factors. Furthermore, some statistical tests were conducted to identify any relationship between the dependent variable (dispersed oil mass in the water column) and independent variables (water wave specifications containing height, length and wave period and spilled oil characteristics including density, viscosity and spilled oil mass). Finally, a mathematical-statistical relationship is proposed to predict dispersed oil in marine waters. To verify the proposed relationship, a laboratory example available in the literature was selected. Oil mass rate penetrated in water body computed by statistical regression was in accordance with experimental data was predicted. On this occasion, it was necessary to verify the proposed mathematical phrase. In a selected laboratory case available in the literature, mass oil rate penetrated in water body computed by suggested regression. Results showed good agreement with experimental data. The validated mathematical-statistical phrase is a useful tool for oil dispersion prediction in oil spill events in marine areas.

Keywords: Dispersion, marine environment, mathematical-statistical relationship, oil spill.

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Authors: Joe Walsh, Mike Climstein, Ian Timothy Heazlewood, Stephen Burke, Jyrki Kettunen, Kent Adams, Mark DeBeliso

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Thousands of masters athletes participate quadrennially in the World Masters Games (WMG), yet this cohort of athletes remains proportionately under-investigated. Due to a growing global obesity pandemic in context of benefits of physical activity across the lifespan, the BMI trends for this unique population was of particular interest. The nexus between health, physical activity and aging is complex and has raised much interest in recent times due to the realization that a multifaceted approach is necessary in order to counteract the obesity pandemic. By investigating age based trends within a population adhering to competitive sport at older ages, further insight might be gleaned to assist in understanding one of many factors influencing this relationship.BMI was derived using data gathered on a total of 6,071 masters athletes (51.9% male, 48.1% female) aged 25 to 91 years ( =51.5, s =±9.7), competing at the Sydney World Masters Games (2009). Using linear and loess regression it was demonstrated that the usual tendency for prevalence of higher BMI increasing with age was reversed in the sample. This trend in reversal was repeated for both male and female only sub-sets of the sample participants, indicating the possibility of improved prevalence of BMI with increasing age for both the sample as a whole and these individual sub-groups.This evidence of improved classification in one index of health (reduced BMI) for masters athletes (when compared to the general population) implies there are either improved levels of this index of health with aging due to adherence to sport or possibly the reduced BMI is advantageous and contributes to this cohort adhering (or being attracted) to masters sport at older ages.

Keywords: Aging, masters athlete, Quetelet Index, sport

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Authors: Peyman Shadman Heidari, Mohammad Khorasani

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The principal purpose of this article is to present a new method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) to generate additional artificial earthquake accelerograms from presented data, which are compatible with specified response spectra. The proposed method uses the learning abilities of ANFIS to develop the knowledge of the inverse mapping from response spectrum to earthquake records. In addition, wavelet packet transform is used to decompose specified earthquake records and then ANFISs are trained to relate the response spectrum of records to their wavelet packet coefficients. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to demonstrate the effectiveness of the proposed method.

Keywords: Adaptive Neural Network Fuzzy Inference System, Wavelet Packet Transform, Response Spectrum.

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Authors: Gavin J. Baxter, Mark H. Stansfield

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This paper reviews the internal use of blogs and their potential effectiveness as organisational learning tools. Since the emergence of the concept of ‘Enterprise 2.0’ there remains a lack of empirical evidence associated with how organisations are applying social media tools and whether they are effective towards supporting organisational learning. Surprisingly, blogs, one of the more traditional social media tools, still remains under-researched in the context of ‘Enterprise 2.0’ and organisational learning. The aim of this paper is to identify the theoretical linkage between blogs and organisational learning in addition to reviewing prior research on organisational blogging exploring why this area remains underresearched. Through a literature review, one of the principal findings of this paper is that organisational blogs have a mutual compatibility with the interpretivist aspect of organisational learning. This paper further advocates that further empirical work in this subject area is required to substantiate this theoretical assumption.

Keywords: Blogs, Enterprise 2.0, Organisational Learning, Social Media Tools.

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Authors: L. Dahmani, M.Kouane

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In this paper are illustrated the principal aspects connected with the numerical evaluation of thermal stress induced by high gradient temperature in the concrete beam. The reinforced concrete beam has many advantages over steel beam, such as high resistance to high temperature, high resistance to thermal shock, Better resistance to fatigue and buckling, strong resistance against, fire, explosion, etc. The main drawback of the reinforced concrete beam is its poor resistance to tensile stresses. In order to investigate the thermal induced tensile stresses, a numerical model of a transient thermal analysis is presented for the evaluation of thermo-mechanical response of concrete beam to the high temperature, taking into account the temperature dependence of the thermo physical properties of the concrete like thermal conductivity and specific heat.

Keywords: Cracking, Gradient Temperature, Reinforced Concrete beam, Thermo-mechanical analysis.

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Authors: Görkem Arslan Kılınç

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Due to the high construction, operation, and maintenance costs of tall buildings, quantification of the area in the plan layout which provides a financial return is an important design criterion. The area of the “core and the structural system elements” does not provide financial return but must exist in the plan layout. Some characteristic items of tall office buildings affect the size of these areas. From this point of view, 15 tall office buildings were systematically investigated. The typical office floor plans of these buildings were re-produced digitally. The area of the “core and the structural system elements” in each building and the characteristic items of each building were calculated. These characteristic items are the size of the long and short plan edge, plan length/width ratio, size of the core long and short edge, core length/width ratio, core area, slenderness, building height, number of floors, and floor height. These items were analyzed by correlation and regression analyses. Results of this paper put forward that; characteristic items which affect the area of "core and structural system elements" are plan long and short edge size, core short edge size, building height, and the number of floors. A one-unit increase in plan short side size increases the area of the "core and structural system elements" in the plan by 12,378 m2. An increase in core short edge size increases the area of the core and structural system elements in the plan by 25,650 m2. Subsequent studies can be conducted by expanding the sample of the study and considering the geographical location of the building.

Keywords: Core area, correlation analysis, floor area, regression analysis, space efficiency, tall office buildings.

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Authors: Ramya Rathan, Miral N. F. Salama

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The variations in the arteries have been drawing attention of anatomists for a long time because of their clinical significance. The brachial artery is the principal artery of the arm which is the continuation of the axillary artery from the lower border of the Teres Major. It terminates into the radial and ulnar arteries below the elbow joint at the neck radius. The present study aims at exploring the clinical significance of the high termination of the brachial artery. During the routine cadaveric dissection of the arm, for the undergraduate students of medicine at our university, we observed a high bifurcation of the radial and the ulnar artery at the midshaft of the humerus. The median nerve was seen passing between these two junctions. Further, the course and the relations of this artery were studied. The accurate knowledge regarding these kinds of variation in the blood vessels is mandatory for planning of designing. General physicians, surgeons and radiologists should keep in mind the variations in the branching pattern of the arteries in their daily medical, diagnostic and therapeutic procedures to avoid complications in diagnostic and surgical procedures.

Keywords: Brachial artery, high termination, radial artery, ulnar artery.

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Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and Validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) where in the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation & Control design team. This paper discusses about the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), Steady State, Transient State.

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Authors: Khodamorad Nabaki, Jianhu Shen, Xiaodong Huang

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This paper develops a method for considering the critical fatigue stress as a constraint in the Bi-directional Evolutionary Structural Optimization (BESO) method. Our aim is to reach an optimal design in which high cycle fatigue failure does not occur for a specific life time. The critical fatigue stress is calculated based on modified Goodman criteria and used as a stress constraint in our topology optimization problem. Since fatigue generally does not occur for compressive stresses, we use the p-norm approach of the stress measurement that considers the highest tensile principal stress in each point as stress measure to calculate the sensitivity numbers. The BESO method has been extended to minimize volume an object subjected to the critical fatigue stress constraint. The optimization results are compared with the results from the compliance minimization problem which shows clearly the merits of our newly developed approach.

Keywords: Topology optimization, BESO method, p-norm, fatigue constraint.

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Authors: A. Farsiani, M. E. Ghobadi

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To study on effect of PEG and NaCl stress on germination and early seedling stages on two cultivar of corn, two separated experiment were laid out at physiology laboratory, faculty of Agriculture, Razi University, Kermanshah, Iran in 2009. This investigation was performed as factorial experiment under Complete Randomized Design (CRD) with three replications. Cultivar factor contains of two varieties (sweet corn SC403 and Flint corn SC704) and five levels of stress (0, -2, -4, -6 and -8 bar). The principal aim of current study was to compare the two varieties of maize in relative to the stress conditions. Results indicated that significant decrease was observed in percentage of germination, germination rate, length of radicle and plumule and radicle and plumule dry matter. On the basis of the results, NaCl as compared with PEG had more effect on germination and early seedling stage and sweet corn had more resistant than flint corn in both stress conditions.

Keywords: Corn, Early Seedling Stage, Germination, PEG andNaCl Stress.

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Authors: Haj Najafi Leila, Tehranizadeh Mohsen

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Dependencies between diverse factors involved in probabilistic seismic loss evaluation are recognized to be an imperative issue in acquiring accurate loss estimates. Dependencies among component damage costs could be taken into account considering two partial distinct states of independent or perfectly-dependent for component damage states; however, in our best knowledge, there is no available procedure to take account of loss dependencies in story level. This paper attempts to present a method called "modal cost superposition method" for decoupling story damage costs subjected to earthquake ground motions dealt with closed form differential equations between damage cost and engineering demand parameters which should be solved in complex system considering all stories' cost equations by the means of the introduced "substituted matrixes of mass and stiffness". Costs are treated as probabilistic variables with definite statistic factors of median and standard deviation amounts and a presumed probability distribution. To supplement the proposed procedure and also to display straightforwardness of its application, one benchmark study has been conducted. Acceptable compatibility has been proven for the estimated damage costs evaluated by the new proposed modal and also frequently used stochastic approaches for entire building; however, in story level, insufficiency of employing modification factor for incorporating occurrence probability dependencies between stories has been revealed due to discrepant amounts of dependency between damage costs of different stories. Also, more dependency contribution in occurrence probability of loss could be concluded regarding more compatibility of loss results in higher stories than the lower ones, whereas reduction in incorporation portion of cost modes provides acceptable level of accuracy and gets away from time consuming calculations including some limited number of cost modes in high mode situation.

Keywords: Dependency, story-cost, cost modes, engineering demand parameter.

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Authors: T. Penkova, A. Korobko, V. Nicheporchuk., L. Nozhenkova, A. Metus

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This paper presents an approach of on-line control of the state of technosphere and environment objects based on the integration of Data Warehouse, OLAP and Expert systems technologies. It looks at the structure and content of data warehouse that provides consolidation and storage of monitoring data. There is a description of OLAP-models that provide a multidimensional analysis of monitoring data and dynamic analysis of principal parameters of controlled objects. The authors suggest some criteria of emergency risk assessment using expert knowledge about danger levels. It is demonstrated now some of the proposed solutions could be adopted in territorial decision making support systems. Operational control allows authorities to detect threat, prevent natural and anthropogenic emergencies and ensure a comprehensive safety of territory.

Keywords: Decision making support systems, Emergency risk assessment, Natural and anthropogenic safety, On-line control, Territory.

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Authors: Maumita Bhattacharya

Abstract:

Evolutionary Algorithms are population-based, stochastic search techniques, widely used as efficient global optimizers. However, many real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function evaluations. Use of evolutionary algorithms in such problem domains is thus practically prohibitive. An attractive alternative is to build meta models or use an approximation of the actual fitness functions to be evaluated. These meta models are order of magnitude cheaper to evaluate compared to the actual function evaluation. Many regression and interpolation tools are available to build such meta models. This paper briefly discusses the architectures and use of such meta-modeling tools in an evolutionary optimization context. We further present two evolutionary algorithm frameworks which involve use of meta models for fitness function evaluation. The first framework, namely the Dynamic Approximate Fitness based Hybrid EA (DAFHEA) model [14] reduces computation time by controlled use of meta-models (in this case approximate model generated by Support Vector Machine regression) to partially replace the actual function evaluation by approximate function evaluation. However, the underlying assumption in DAFHEA is that the training samples for the metamodel are generated from a single uniform model. This does not take into account uncertain scenarios involving noisy fitness functions. The second model, DAFHEA-II, an enhanced version of the original DAFHEA framework, incorporates a multiple-model based learning approach for the support vector machine approximator to handle noisy functions [15]. Empirical results obtained by evaluating the frameworks using several benchmark functions demonstrate their efficiency

Keywords: Meta model, Evolutionary algorithm, Stochastictechnique, Fitness function, Optimization, Support vector machine.

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Authors: L. McAllister, A. Dudau

Abstract:

This paper explores gender related barriers to interagency collaboration in statutory children safeguard partnerships against a theoretical framework that considers individuals, professions and organisations interacting as part of a complex adaptive system. We argue that gender-framed obstacles to effective communication between culturally discrepant agencies can ultimately impact on the effectiveness of policy delivery,. We focused our research on three partnership structures in Sefton Metropolitan Borough in order to observe how interactions occur, whether the agencies involved perceive their occupational environment as being gender affected and whether they believe this can hinder effective collaboration with other biased organisations. Our principal empirical findings indicate that there is a general awareness amongst professionals of the role that gender plays in each of the agencies reviewed, that gender may well constitute a barrier to effective communication, but there is a sense in which there is little scope for change in the short term. We aim to signal here, however, the need to change against the risk of service failure.

Keywords: Children's safeguard, gender, gendered professions, inter-agency collaboration, partnerships.

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Authors: Shireen Simon

Abstract:

Cyberbullying among schoolchildren and teenagers became a hot issue discussed by Malaysian society. Cyberbullying is a new age of bullying because it uses the modern digital technology intentionally to hurt and degrade someone in the cyber world. Cyberbullying is a problem affecting many teenagers as they embrace online communication and interaction whereby virtual world with no borders. By adopting a qualitative approach, this study has captured 8 cyberbullied victims’ school experience. Even years after leaving school, these 8 cyberbullied victims remember how it feels to be bullied in the cyber world. The principal investigator also tries to identify the possibility factors that contribute to cyberbullying among these 8 victims. The result shows that these victims were bullied differently in cyber world. This study not just primarily focuses on cyberbullying issues among schoolchildren and teenagers; it also addresses the motives and causes of cyberbullying. Lastly, this article will be served as guidance for school teachers, parents and teenagers to prepare to tackle cyberbullying together. Cyberbullying is no laughing matter in our community, and it is time to spread the seeds of peace inspires others to do the same.

Keywords: Cyberbullying, cyber victimization, internet, school experience, teenagers.

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Authors: Ammar Redza Ahmad Rizal, Shahrina Md Nordin, Mohd Shamsuri Saad, Kamariah Ismail

Abstract:

Communication is becoming a significant tool to engage stakeholders since half of the century ago. In the recent years, there has been rapid growth of new technology developments. In tandem with such developments, there has been growing emphasis in communication strategies and management especially in determining the level of influence and management strategies among the said stakeholders on particular field. This paper presents a research conceptual framework focusing on stakeholder theories, communication and management strategies to be implied on the engagement of stakeholders of new technology developments of fertilizer industry in Malaysia. Framework espoused in this paper will provide insights into the various stakeholder theories and engagement strategies from different principal necessary for a successful introduction of new technology development in the above stated industry. The proposed framework has theoretical significance in filling the gap of the body of knowledge in the implementation of communication strategies in Malaysian fertilizer industry.

Keywords: Communication Strategies, Fertilizer Industry, New Technology Development, Stakeholders Management.

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Authors: Dmitriy Yu. Korulkin, Raissa A. Muzychkina

Abstract:

The article represents the results of isolation and component chromatographic analysis of essential oils of Polygonum L. plants growing in Kazakhstan in commercial reserves at the territory of Kazakhstan. The results of research of antibacterial and antifungal activity of isolated compounds have been represented.

Keywords: Antibacterial, antifungal, bioactive substances, essential oils, isolation, Polygonum L.

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