Search results for: distributed MIMO

Authors: Nurul ‘Ulyani Mohd Najib, Nor’ Aini Yusof, Zulkifli Osman

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Debates on residential satisfaction topic have been vigorously discussed in family house setting. Nonetheless, less or lack of attention was given to survey on student residential satisfaction in the campus house setting. This study, however, tried to fill in the gap by focusing more on the relationship between students- socio-economic backgrounds and student residential satisfaction with their on-campus student housing facilities. Two-stage cluster sampling method was employed to classify the respondents. Then, self-administered questionnaires were distributed face-to-face to the students. In general, it was confirmed that the students- socioeconomic backgrounds have significantly influence the students- satisfaction with their on-campus student housing facilities. The main influential factors were revealed as the economic status, sense of sharing, and the ethnicity of roommates. Likewise, this study could also provide some useful feedback for the universities administration in order to improve their student housing facilities.

Keywords: Malaysia, Socio-economic, Student housing, Studentresidential satisfaction

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Authors: Sahbi Farhani

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This study investigates the relationship between external debt and military spending in case of India over the period of 1970–2012. In doing so, we have applied the structural break unit root tests to examine stationarity properties of the variables. The Auto-Regressive Distributed Lag (ARDL) bounds testing approach is used to test whether cointegration exists in presence of structural breaks stemming in the series. Our results indicate the cointegration among external debt, military spending, debt servicing, and economic growth. Moreover, military spending and debt servicing add in external debt. Economic growth helps in lowering external debt. The Vector Error Correction Model (VECM) analysis and Granger causality test reveal that military spending and economic growth cause external debt. The feedback effect also exists between external debt and debt servicing in case of India.

Keywords: External debt, military spending, ARDL approach, structural breaks, India.

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Authors: Sandesh Achar

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The cloud computing industry has set new goals for better service delivery and deployment, so anyone can access services such as computation, application, and storage anytime. Cloud computing promises new possibilities for approaching sustainable solutions to deploy and advance their services in this distributed environment. This work explores energy-efficient approaches and how cloud-based architecture can reduce energy consumption levels amongst enterprises leveraging cloud computing services. Adopting cloud-based networking, database, and server machines provide a comprehensive means of achieving the potential gains in energy efficiency that cloud computing offers. In energy-efficient cloud computing, virtualization is one aspect that can integrate several technologies to achieve consolidation and better resource utilization. Moreover, the Green Cloud Architecture for cloud data centers is discussed in terms of cost, performance, and energy consumption, and appropriate solutions for various application areas are provided.

Keywords: Greener Cloud, cloud computing, energy efficiency, energy consumption, metadata tags, Green Cloud Advisor.

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Authors: N. Mpofu, M. Sears

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In this paper, we propose a novel algorithm for delineating the endocardial wall from a human heart ultrasound scan. We assume that the gray levels in the ultrasound images are independent and identically distributed random variables with different Rician Inverse Gaussian (RiIG) distributions. Both synthetic and real clinical data will be used for testing the algorithm. Algorithm performance will be evaluated using the expert radiologist evaluation of a soft copy of an ultrasound scan during the scanning process and secondly, doctor’s conclusion after going through a printed copy of the same scan. Successful implementation of this algorithm should make it possible to differentiate normal from abnormal soft tissue and help disease identification, what stage the disease is in and how best to treat the patient. We hope that an automated system that uses this algorithm will be useful in public hospitals especially in Third World countries where problems such as shortage of skilled radiologists and shortage of ultrasound machines are common. These public hospitals are usually the first and last stop for most patients in these countries.

Keywords: Endorcardial Wall, Rician Inverse Distributions, Segmentation, Ultrasound Images.

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Authors: Aimeng Wang, Dejun Ma, Hui Wang

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The paper presents a detailed calculation of characteristic of five different topology permanent magnet machines for high performance traction including hybrid -electric vehicles using finite element analysis (FEA) method. These machines include V-shape single layer interior PM, W-shape single-layer interior PM, Segment interior PM and surface PM on the rotor and with distributed winding on the stator. The performance characteristics which include the back-emf voltage and its harmonic, magnet mass, iron loss and ripple torque are compared and analyzed. One of a 7.5kW IPM prototype was tested and verified finite-element analysis results. The aim of the paper is given some guidance and reference for machine designer which are interested in IPM machine selection for high performance traction application.

Keywords: Interior permanent magnet machine, finite-element analysis (FEA), five topologies, electric vehicle.

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Authors: Zaki Ahmad Khan, Jamshed Siddiqui, Abdus Samad

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The Scheduling and mapping of tasks on a set of processors is considered as a critical problem in parallel and distributed computing system. This paper deals with the problem of dynamic scheduling on a special type of multiprocessor architecture known as Linear Crossed Cube (LCQ) network. This proposed multiprocessor is a hybrid network which combines the features of both linear types of architectures as well as cube based architectures. Two standard dynamic scheduling schemes namely Minimum Distance Scheduling (MDS) and Two Round Scheduling (TRS) schemes are implemented on the LCQ network. Parallel tasks are mapped and the imbalance of load is evaluated on different set of processors in LCQ network. The simulations results are evaluated and effort is made by means of through analysis of the results to obtain the best solution for the given network in term of load imbalance left and execution time. The other performance matrices like speedup and efficiency are also evaluated with the given dynamic algorithms.

Keywords: Dynamic algorithm, Load imbalance, Mapping, Task scheduling.

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Authors: B. Arun Kumar, T. Ravichandran

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Workflow scheduling is an important part of cloud computing and based on different criteria it decides cost, execution time, and performances. A cloud workflow system is a platform service facilitating automation of distributed applications based on new cloud infrastructure. An aspect which differentiates cloud workflow system from others is market-oriented business model, an innovation which challenges conventional workflow scheduling strategies. Time and Cost optimization algorithm for scheduling Hybrid Clouds (TCHC) algorithm decides which resource should be chartered from public providers is combined with a new De-De algorithm considering that every instance of single and multiple workflows work without deadlocks. To offset this, two new concepts - De-De Dodging Algorithm and Priority Based Decisive Algorithm - combine with conventional deadlock avoidance issues by proposing one algorithm that maximizes active (not just allocated) resource use and reduces Makespan.

Keywords: Workflow Scheduling, cloud workflow, TCHC algorithm, De-De Dodging Algorithm, Priority Based Decisive Algorithm (PBD), Makespan.

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Authors: Mubarak Saif Mohsen, Zurinahni Zainol, Rosalina Abdul Salam, Wahidah Husain

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One of the major problems in genomic field is to perform sequence comparison on DNA and protein sequences. Executing sequence comparison on the DNA and protein data is a computationally intensive task. Sequence comparison is the basic step for all algorithms in protein sequences similarity. Parallel computing is an attractive solution to provide the computational power needed to speedup the lengthy process of the sequence comparison. Our main research is to enhance the protein sequence algorithm using dynamic programming method. In our approach, we parallelize the dynamic programming algorithm using multithreaded program to perform the sequence comparison and also developed a distributed protein database among many PCs using Remote Method Interface (RMI). As a result, we showed how different sizes of protein sequences data and computation of scoring matrix of these protein sequence on different number of processors affected the processing time and speed, as oppose to sequential processing.

Keywords: Protein sequence algorithm, dynamic programming algorithm, multithread

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Authors: Azam Beg, P. W. Chandana Prasad, S.M.N.A Senenayake

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When binary decision diagrams are formed from uniformly distributed Monte Carlo data for a large number of variables, the complexity of the decision diagrams exhibits a predictable relationship to the number of variables and minterms. In the present work, a neural network model has been used to analyze the pattern of shortest path length for larger number of Monte Carlo data points. The neural model shows a strong descriptive power for the ISCAS benchmark data with an RMS error of 0.102 for the shortest path length complexity. Therefore, the model can be considered as a method of predicting path length complexities; this is expected to lead to minimum time complexity of very large-scale integrated circuitries and related computer-aided design tools that use binary decision diagrams.

Keywords: Monte Carlo circuit simulation data, binary decision diagrams, neural network modeling, shortest path length estimation

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Authors: Joel Arrais, João E. Pereira, João Fernandes, José Luís Oliveira

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The scientific achievements coming from molecular biology depend greatly on the capability of computational applications to analyze the laboratorial results. A comprehensive analysis of an experiment requires typically the simultaneous study of the obtained dataset with data that is available in several distinct public databases. Nevertheless, developing a centralized access to these distributed databases rises up a set of challenges such as: what is the best integration strategy, how to solve nomenclature clashes, how to solve database overlapping data and how to deal with huge datasets. In this paper we present GeNS, a system that uses a simple and yet innovative approach to address several biological data integration issues. Compared with existing systems, the main advantages of GeNS are related to its maintenance simplicity and to its coverage and scalability, in terms of number of supported databases and data types. To support our claims we present the current use of GeNS in two concrete applications. GeNS currently contains more than 140 million of biological relations and it can be publicly downloaded or remotely access through SOAP web services.

Keywords: Data integration, biological databases

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Authors: Vaishali P. Joshi, Pallav Joshi

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The objective of this study is to examine the differences fashion innovators and non-fashion innovators in their fashion consumption behavior in terms of their pre-purchase behavior, purchase behavior and post purchase behavior. The questionnaire was distributed to a female college student for data collection for achieving the objective of the first part of the study. Question-related to fashion innovativeness and fashion consumption behavior was asked. The sample was comprised of 81 college females ages 18 through 30 who were attending Business Management degree. A series of attitude questions was used to categorize respondents on the Innovativeness Scale. 32 respondents with a score of 21 and above were designated as Fashion innovators and the remainder (49) as Non-fashion innovators. Findings showed that there exist significant differences between innovators and non-innovators in their fashion consumption behavior. Data was analyzed through frequency distribution table. Many differences were found in the behavior of innovators and non-innovators in terms of their pre-purchase, actual purchase, and post-purchase behavior.

Keywords: Consumption behavior, fashion, innovativeness, frequency distribution table.

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Authors: Mahmood Reza Shakarami, Reza Sedaghati

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Recently, distributed generation technologies have received much attention for the potential energy savings and reliability assurances that might be achieved as a result of their widespread adoption. The distribution feeder reconfiguration (DFR) is one of the most important control schemes in the distribution networks, which can be affected by DGs. This paper presents a new approach to DFR at the distribution networks considering wind turbines. The main objective of the DFR is to minimize the deviation of the bus voltage. Since the DFR is a nonlinear optimization problem, we apply the Adaptive Modified Firefly Optimization (AMFO) approach to solve it. As a result of the conflicting behavior of the single- objective function, a fuzzy based clustering technique is employed to reach the set of optimal solutions called Pareto solutions. The approach is tested on the IEEE 32-bus standard test system.

Keywords: Adaptive Modified Firefly Optimization (AMFO), Pareto solutions, feeder reconfiguration, wind turbines, bus voltage.

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Authors: Saleh Komies, Mona Alharbi, Razan Alhayyani, Mozah Almulhim, Roseanne Khawaja, Ahmed Alradhi

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One of the proposed solutions that face some challenges is encouraging sustainable energy consumption across Saudi Arabia through crowdfunding platforms. To address these challenges, we need to determine the level of awareness of crowdfunding and green projects, as well as the preferences and willingness of Saudis to utilize crowdfunding as an alternative funding source for green projects in Saudi Arabia. In this study, we aim to determine the influence of environmental awareness and concern on the propensity to crowdfund green projects. The survey is being conducted as part of environmental initiatives to assess public perceptions and opinions on crowdfunding green projects in Saudi Arabia. A total of 450 responses to an online questionnaire distributed via convenience and snowball sampling were utilized for data analysis. The survey reveals that Saudis have a low understanding of crowdfunding concepts and a relatively high understanding of implementing green projects. The public is interested in crowdfunding green projects if there is a return on investment.

Keywords: Crowdfunding, green projects, renewable energy, Saudi Arabia, solar farms, wind resources.

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Authors: Guguloth Ramesh, T. K. Sunil Kumar

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This paper presents congestion management in deregulated power systems. In a deregulated environment, every buyer wants to buy power from the cheapest generator available, irrespective of relative geographical location of buyer and seller. As a consequence of this, the transmission corridors evacuating the power of cheaper generators would get overloaded if all such transactions are approved. Congestion management is a mechanism to prioritize the transactions and commit to such a schedule which would not overload the network. The congestions in the transmission lines are determined by Optimal Power Flow (OPF) solution, which is carried by primal liner programming method. Congestion in the transmission lines are alleviated by connected Distributed Generation (DG) of micro grid at load bus. A method to determine the optimal location of DG unit has been suggested based on transmission line relief sensitivity based approach. The effectiveness of proposed method has been demonstrated on modified IEEE-14 and 30 bus test systems.

Keywords: Congestion management, Distribution Generation (DG), Transmission Line Relief (TLR) sensitivity index, OPF.

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Authors: Md Abdullah Al Faruque, Ram Balachandar

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The present study was carried out to understand the extent of effect of roughness and Reynolds number in open channel flow (OCF). To this extent, four different types of bed surface conditions consisting smooth, distributed roughness, continuous roughness, natural sand bed and two different Reynolds number for each bed surfaces were adopted in this study. Particular attention was given on mean velocity, turbulence intensity, Reynolds shear stress, correlation, higher order moments and quadrant analysis. Further, the extent of influence of roughness and Reynolds number in the depth-wise direction also studied. Increasing Reynolds shear stress near rough beds are noticed due to arrays of discrete roughness elements and flow over these elements generating a series of wakes which contributes to the generation of significantly higher Reynolds shear stress.

Keywords: Bed roughness, ejection, sweep, open channel flow, Reynolds Shear Stress, turbulent boundary layer, velocity triple product.

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Authors: Md. Mahbubur Rahim

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B2E portals represent a new class of web-based information technologies which many organisations are introducing in recent years to stay in touch with their distributed workforces and enable them to perform value added activities for organisations. However, actual usage of these emerging systems (measured using suitable instruments) has not been reported in the contemporary scholarly literature. We argue that many of the instruments to measure usage of various types of IT-enabled information systems are not directly applicable for B2E portals because they were developed for the context of traditional mainframe and PC-based information systems. It is therefore important to develop a new instrument for web-based portal technologies aimed at employees. In this article, we report on the development and initial qualitative evaluation of an instrument that seeks to operationaise a set of independent factors affecting the usage of portals by employees. The proposed instrument is useful to IT/e-commerce researchers and practitioners alike as it enhances their confidence in predicting employee usage of portals in organisations.

Keywords: Portal, business-to-employees, instrument, evaluation, qualitative research.

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Authors: Sae-Rom Pak, Seung Hwan Park, Jeong Ho Cho, Daewoong An, Cheong-Sool Park, Jun Seok Kim, Jun-Geol Baek

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It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.

Keywords: Yield Prediction, Semiconductor Test Process, Support Vector Machine, Under Sampling

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Authors: Ethar H. Khalil, Bahaa I. Kazem

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In this work a software simulation model has been proposed for two driven wheels mobile robot path planning; that can navigate in dynamic environment with static distributed obstacles. The work involves utilizing Bezier curve method in a proposed N order matrix form; for engineering the mobile robot path. The Bezier curve drawbacks in this field have been diagnosed. Two directions: Up and Right function has been proposed; Probability Recursive Function (PRF) to overcome those drawbacks. PRF functionality has been developed through a proposed; obstacle detection function, optimization function which has the capability of prediction the optimum path without comparison between all feasible paths, and N order Bezier curve function that ensures the drawing of the obtained path. The simulation results that have been taken showed; the mobile robot travels successfully from starting point and reaching its goal point. All obstacles that are located in its way have been avoided. This navigation is being done successfully using the proposed PRF techniques.

Keywords: Mobile robot, path planning, Bezier curve.

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Authors: Emelia Akashah P.A, Sharifah Nadiah S.A

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Knowledge sharing enables the information or knowledge to be transmitted from one source to another. This paper demonstrates the needs of having the online book catalogue which can be used to facilitate disseminating information on textbook used in the university. This project is aimed to give access to the students and lecturers to the list of books in the bookstore and at the same time to allow book reviewing without having to visit the bookstore physically. Research is carried out according to the boundaries which accounts to current process of new book purchasing, current system used by the bookstore and current process the lecturers go through for reviewing textbooks. The questionnaire is used to gather the requirements and it is distributed to 100 students and 40 lecturers. This project has enabled the improvement of a manual process to be carried out automatically, through a web based platform. It is shown based on the user acceptance survey carried out that target groups found that this web service is feasible to be implemented in Universiti Teknologi PETRONAS (UTP), and they have shown positive signs of interest in utilizing it in the future.

Keywords: bookstore, knowledge sharing, online bookcatalogue, textbook

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Authors: M. M. Bashandy, A. R. Ahmed, M. El-Gaffary, Sahar S. Abd El-Rahman

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This study evaluated the acute toxicity and tissue distribution of intravenously administered gold nanoparticles (AuNPs) in male rabbits. Rabbits were exposed to single dose of AuNPs (300 μg/ kg). Toxic effects were assessed via general behavior, hematological parameters, serum biochemical parameters, and histopathological examination of various rabbits’ organs. Inductively coupled plasma–mass spectrometry (ICP-MS) was used to determine gold concentrations in tissue samples collected at predetermined time intervals. After one week, AuNPs exerted no obvious acute toxicity in rabbits. However, inflammatory reactions were observed in liver, lungs and kidneys accompanied with mild absolute neutrophilia and significant monocytosis. The highest gold levels were found in the spleen and liver followed by lungs, and kidneys. These results indicated that AuNPs could be distributed extensively to various tissues in the body, but primarily in the spleen and liver.

Keywords: Gold nanoparticles, toxicity, pathology, hematology, liver function, kidney function.

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Authors: S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha

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Machine learning is a new and exciting area of artificial intelligence nowadays. Machine learning is the most valuable, time, supervised, and cost-effective approach. It is not a narrow learning approach; it also includes a wide range of methods and techniques that can be applied to a wide range of complex realworld problems and time domains. Biological image classification, adaptive testing, computer vision, natural language processing, object detection, cancer detection, face recognition, handwriting recognition, speech recognition, and many other applications of machine learning are widely used in research, industry, and government. Every day, more data are generated, and conventional machine learning techniques are becoming obsolete as users move to distributed and real-time operations. By providing fundamental knowledge of machine learning tools and research opportunities in the field, the aim of this article is to serve as both a comprehensive overview and a guide. A diverse set of machine learning resources is demonstrated and contrasted with the key features in this survey.

Keywords: Artificial intelligence, machine learning, deep learning, machine learning algorithms, machine learning tools.

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Authors: Gabriela Lindemann, Danilo Schmidt, Thomas Schrader, Dietmar Keune

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The amount and heterogeneity of data in biomedical research, notably in interdisciplinary fields, requires new methods for the collection, presentation and analysis of information. Important data from laboratory experiments as well as patient trials are available but come out of distributed resources. The Charité - University Hospital Berlin has established together with the German Research Foundation (DFG) a new information service centre for kidney diseases and transplantation (Open European Nephrology Science Centre - OpEN.SC). Beside a collaborative aspect to create new research groups every single partner or institution of this science information centre making his own data available is allowed to search the whole data pool of the various involved centres. A core task is the implementation of a non-restricting open data structure for the various different data sources. We decided to use a modern RDF model and in a first phase transformed original data coming from the web-based Electronic Patient Record database TBase©.

Keywords: Medical databases, Resource Description Framework (RDF), metadata repository.

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Authors: Siti Juryiah Mohd Khalid, Norazlina Dol

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Academic libraries in Malaysia are still not prepared for disaster even though several occasions have been reported. The study sets out to assess the current status of preparedness in disaster management among Malaysian academic libraries in the State of Selangor and the Federal Territory of Kuala Lumpur. To obtain a base level of knowledge on disaster preparedness of current practices, a questionnaire was distributed to chief librarians or their assignees in charge of disaster or emergency preparedness at 40 academic libraries and 34 responses were received. The study revolved around the current status of preparedness, on various issues including existence of disaster preparedness plan among academic libraries in Malaysia, disaster experiences by the academic libraries, funding, risk assessment activities and involvement of library staff in disaster management. Frequency and percentage tables were used in the analysis of the data collected. Some of the academic libraries under study have experienced one form of disaster or the other. Most of the academic libraries do not have a written disaster preparedness plan. The risk assessments and staff involvement in disaster preparedness by these libraries were generally adequate.

Keywords: Academic libraries, disaster preparedness plan, disaster management, emergency plan.

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Authors: Ayad Sleibi Mustafa, Ahmed Abdulkadhim Mohsin, Layth Noori Ali

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The deterioration of solid waste management in Baghdad city is considered as a great challenge in terms of human health and environment. Baghdad city is divided into thirteen districts which are distributed on both Tigris River banks. The west bank is Al-Karkh and the east bank is Al-Rusafa. Municipal Solid Waste Management is one of the most complicated problems facing the environment in Iraq. Population growth led to increase waste production and more load of the waste to the limited capacity infrastructure. The problems of municipal solid waste become more serious after the war in 2003. More waste is disposed in underground landfills in Baghdad with little or no concern for both human health and environment. The results showed that the total annually predicted solid waste is increasing for the period 2015-2030. Municipal solid waste in 2030 will be 6,427,773 tons in Baghdad city according to the population growth rate of 2.4%. This increase is estimated to be approximately 30%.

Keywords: Municipal solid waste, solid waste composition and characteristics, Baghdad city, environment, human health.

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Authors: M. Hakak Khadem, S. Hossainpour, M. Shams

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A numerical simulation of micro Poiseuille flow has performed for rarefied and compressible flow at slip flow regimes. The wall roughness is simulated in two cases with triangular microelements and random micro peaks distributed on wall surfaces to study the effects of roughness shape and distribution on flow field. Two values of Mach and Knudsen numbers have used to investigate the effects of rarefaction as well as compressibility. The numerical results have also checked with available theoretical and experimental relations and good agreements has achieved. High influence of roughness shape can be seen for both compressible and incompressible rarefied flows. In addition it is found that rarefaction has more significant effect on flow field in microchannels with higher relative roughness. It is also found that compressibility has more significant effects on Poiseuille number when relative roughness increases.

Keywords: Relative roughness, slip flow, Poiseuille number, roughness distribution.

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Authors: Bogdan Il. Bogdanov, Plamen S. Pashev, Yancho H. Hristov, Dimitar P.Georgiev, Irena G. Markovska

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The crystallization kinetics and phase transformation of SiO2.Al2O3.0,56P2O5.1,8CaO.0,56CaF2 glass have been investigated using differential thermal analysis (DTA), x-ray diffraction (XRD), and scanning electron microscopy (SEM). Glass samples were obtained by melting the glass mixture at 14500С/120 min. in platinum crucibles. The mixture were prepared from chemically pure reagents: SiO2, Al(OH)3, H3PO4, CaCO3 and CaF2. The non-isothermal kinetics of crystallization was studied by applying the DTA measurements carried out at various heating rates. The activation energies of crystallization and viscous flow were measured as 348,4 kJ.mol–1 and 479,7 kJ.mol–1 respectively. Value of Avrami parameter n ≈ 3 correspond to a three dimensional of crystal growth mechanism. The major crystalline phase determined by XRD analysis was fluorapatite (Ca(PO4)3F) and as the minor phases – fluormargarite (CaAl2(Al2SiO2)10F2) and vitlokite (Ca9P6O24). The resulting glass-ceramic has a homogeneous microstructure, composed of prismatic crystals, evenly distributed in glass phase.

Keywords: glass-ceramic, crystallization, non-isothermalkinetics, Avrami parameter

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Authors: Beata Horníckova, Sona Lorencova

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The study deals with the presentation of the results of quantitatively oriented research. The research was conducted as part of a questionnaire survey with the aim to find out what are the attitudes of parents to compulsory preschool education in the Czech Republic. This research presents results from the area of importance of compulsory pre-school education from the parents’ perspective. The research method was a questionnaire, which was distributed to respondents through an online platform. The research involved 107 parents, who answered a total of 36 questions that found out their attitudes to last year’s compulsory preschool attendance. The results show that compulsory pre-school attendance has increased the importance of pre-school education. However, the results also show that the compulsory last year of preschool education is not more important according to parents than in previous years. Most participants consider compulsory pre-school attendance to be important and are happy that their child attends it. The results reveal the fact that the introduction of compulsory pre-school attendance has contributed to the importance of parents’ perceptions of pre-primary education.

Keywords: compulsory pre-school education, education of preschool children, kindergarten, parents

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Authors: Sutisa Khempaka, Supattra Okrathok, Laddawan Hokking, Buntita Thukhanon, Wittawat Molee

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This study was conducted to investigate the optimum levels of glutamine (Gln) supplementation in broiler diets. A total of 32 one-day-old male chicks with initial body weight 41.5 g were segregated into 4 groups (8 chicks per group) and subsequently distributed to individual cages. Feed and water were provided ad libitum for 21 days. Four dietary treatments were as follows: control and supplemented Gln at 1, 2 and 3%, respectively. The results found that the addition Gln had no negative effects on dry matter, organic matter, ash digestibility or nitrogen retention. Birds fed with 1% Gln had significantly higher villi wide and villi height : crypt depth ratio in duodenum than the control chicks and 2 and 3% Gln chicks. It is suggested that the addition of Gln at 1% indicated a beneficial effect on improving small intestinal morphology, in addition Gln may stimulate immune organ development of broiler chickens.

Keywords: broiler chicken, digestibility, gastrointestinal tract glutamine, glutamine

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Authors: Samar Raffoul, Martin Heywood, Dimitrios Moutaftsis, Michael Rowell

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This paper comprises an experimental investigation into the structural performance of cold formed steel (CFS) and timber board composite floor systems. The tests include a series of small-scale pushout tests and full-scale bending tests carried out using a refined loading system to simulate uniformly distributed constant load. The influence of connection details (screw spacing and adhesives) on floor performance was investigated. The results are then compared to predictions from relevant existing models for composite floor systems. The results of this research demonstrate the significant benefits of considering the composite action of the boards in floor design. Depending on connection detail, an increase in flexural stiffness of up to 40% was observed in the floor system, when compared to designing joists individually.

Keywords: Cold formed steel joists, composite action, flooring systems, shear connection.

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: Distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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