Search results for: Initial value problem.

Authors: Vera Pujani, Alfitman, Refdinal Nazir

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E-travel is travel agency-s companies employing internet and website as e-commerce context. This study presents numerous initial key factors of electronic travel model based on small travel agencies perspectives. Browsing previous studies related to website travel activities are conducted. Five small travel agencies in Indonesia has been deeply interviewed in case studies. The finding of this research is identifying numerous characteristics and dimension factors and travel website operations including ownermanager roles, business experiences, characteristically business, and technological aspects. This study is the preliminary research related to travel website adoption in Indonesia. The further study would be conducted in questionnaires of the quantitative research in Indonesia contexts as a developing country.

Keywords: Tourism, travel agency, e-commerce, website, developing country, small business, case study.

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Authors: V. D. Thi, M. Li, M. Khelifa, M. El Ganaoui, Y. Rogaume

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This paper presents a two-dimensional model to study the heat and moisture transfer through porous building materials. Dynamic and static coupled models of heat and moisture transfer in porous material under low temperature are presented and the coupled models together with variable initial and boundary conditions have been considered in an analytical way and using the finite element method. The resulting coupled model is converted to two nonlinear partial differential equations, which is then numerically solved by an implicit iterative scheme. The numerical results of temperature and moisture potential changes are compared with the experimental measurements available in the literature. Predicted results demonstrate validation of the theoretical model and effectiveness of the developed numerical algorithms. It is expected to provide useful information for the porous building material design based on heat and moisture transfer model.

Keywords: Finite element method, heat transfer, moisture transfer, porous materials, wood.

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Authors: Shuen-Tai Wang, Chin-Hung Li, Ying-Chuan Chen

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In recent years there has been renewal of interest in the relation between Green IT and Cloud Computing. The growing use of computers in cloud platform has caused marked energy consumption, putting negative pressure on electricity cost of cloud data center. This paper proposes an effective mechanism to reduce energy utilization in cloud computing environments. We present initial work on the integration of resource and power management that aims at reducing power consumption. Our mechanism relies on recalling virtualization services dynamically according to user-s virtualization request and temporarily shutting down the physical machines after finish in order to conserve energy. Given the estimated energy consumption, this proposed effort has the potential to positively impact power consumption. The results from the experiment concluded that energy indeed can be saved by powering off the idling physical machines in cloud platforms.

Keywords: Green IT, Cloud Computing, virtualization, power consumption.

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Authors: Nerijus Remeikis, Ignas Skucas, Vida Melninkaite

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Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.

Keywords: Text categorization, decision trees, neural networks, machine learning.

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Authors: Munther I. Kandah, Fahmi A. Abu Al-Rub, Lucy Bawarish, Mira Bawarish, Hiba Al-Tamimi, Reem Khalil, Raja'a Sa, ada

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In this project cadmium ions were adsorbed from aqueous solutions onto either date pits; a cheap agricultural and nontoxic material, or chemically activated carbon prepared from date pits using phosphoric acid. A series of experiments were conducted in a batch adsorption technique to assess the feasibility of using the prepared adsorbents. The effects of the process variables such as initial cadmium ions concentration, contact time, solution pH and adsorbent dose on the adsorption capacity of both adsorbents were studied. The experimental data were tested using different isotherm models such as Langmuir, Freundlich, Tempkin and Dubinin- Radushkevich. The results showed that although the equilibrium data could be described by all models used, Langmuir model gave slightly better results when using activated carbon while Freundlich model, gave better results with date pits.

Keywords: Adsorption, Cadmium, Chemical Activation, DatePits.

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Authors: Joonas Pääkkönen

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In sports, individuals and teams are typically interested in final rankings. Final results, such as times or distances, dictate these rankings, also known as places. Places can be further associated with ordered random variables, commonly referred to as order statistics. In this work, we introduce a simple, yet accurate order statistical ordinal regression function that predicts relay race places with changeover-times. We call this function the Fenton-Wilkinson Order Statistics model. This model is built on the following educated assumption: individual leg-times follow log-normal distributions. Moreover, our key idea is to utilize Fenton-Wilkinson approximations of changeover-times alongside an estimator for the total number of teams as in the notorious German tank problem. This original place regression function is sigmoidal and thus correctly predicts the existence of a small number of elite teams that significantly outperform the rest of the teams. Our model also describes how place increases linearly with changeover-time at the inflection point of the log-normal distribution function. With real-world data from Jukola 2019, a massive orienteering relay race, the model is shown to be highly accurate even when the size of the training set is only 5% of the whole data set. Numerical results also show that our model exhibits smaller place prediction root-mean-square-errors than linear regression, mord regression and Gaussian process regression.

Keywords: Fenton-Wilkinson approximation, German tank problem, log-normal distribution, order statistics, ordinal regression, orienteering, sports analytics, sports modeling.

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Authors: Emi Govorčin Bajsić, Vesna Ocelić Bulatović, Miroslav Slouf, Ana Šitum

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Composites based on a biodegradable polycaprolactone (PCL) containing 0.5, 1.0 and 2.0 wt % of titanium dioxide (TiO₂) micro and nanoparticles were prepared by melt mixing and the effect of filler type and contents on the thermal properties, dynamic-mechanical behaviour and morphology were investigated. Measurements of storage modulus and loss modulus by dynamic mechanical analysis (DMA) showed better results for microfilled PCL/TiO₂ composites than nanofilled composites, with the same filler content. DSC analysis showed that the T_g and T_c of micro and nanocomposites were slightly lower than those of neat PCL. The crystallinity of the PCL increased with the addition of TiO₂ micro and nanoparticles; however, the c_c for the PCL was unchanged with micro TiO₂ content. The thermal stability of PCL/TiO₂ composites were characterized using thermogravimetric analysis (TGA). The initial weight loss (5 wt %) occurs at slightly higher temperature with micro and nano TiO₂ addition and with increasing TiO₂ content.

Keywords: Morphology, polycaprolactone, thermal properties, titanium dioxide.

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Authors: Mehdi Tatari

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Finding the interpolation function of a given set of nodes is an important problem in scientific computing. In this work a kind of localization is introduced using the radial basis functions which finds a sufficiently smooth solution without consuming large amount of time and computer memory. Some examples will be presented to show the efficiency of the new method.

Keywords: Radial basis functions, local interpolation method, closed form solution.

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Authors: Colette Malyack, Pius Egbelu

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Business-to-Customer (B2C) delivery options have improved to meet increased demand in recent years. The change in end users has forced logistics networks to focus on customer service and sentiment that would have previously been the priority of the company or organization of origin. This has led to increased pressure on logistics companies to extend traditional B2B networks into a B2C solution while accommodating additional costs, roadblocks, and customer sentiment; the result has been the creation of the omnichannel delivery network encompassing a number of traditional and modern methods of package delivery. In this paper the many solutions within the omnichannel delivery network are defined and discussed. It can be seen through this analysis that the omnichannel delivery network can be applied to reduce the complexity of package delivery and provide customers with more options. Applied correctly the result is a reduction in cost to the logistics company over time, even with an initial increase in cost to obtain the technology.

Keywords: Network planning, Last Mile Delivery, LMD, omnichannel delivery network, omnichannel logistics.

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Authors: Mayowa A. Sofowora, Seraphim D. Eyono Obono

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The use of information and communication technologies such as computers, mobile phones and the Internet is becoming prevalent in today’s world; and it is facilitating access to a vast amount of data, services and applications for the improvement of people’s lives. However, this prevalence of ICTs is hampered by the problem of low income levels in developing countries to the point where people cannot timeously replace or repair their ICT devices when damaged or lost; and this problem serves as a motivation for this study whose aim is to examine the perceptions of teachers on the reliability of cellphones when used for teaching and learning purposes. The research objectives unfolding this aim are of two types: Objectives on the selection and design of theories and models, and objectives on the empirical testing of these theories and models. The first type of objectives is achieved using content analysis in an extensive literature survey: and the second type of objectives is achieved through a survey of high school teachers from the ILembe and UMgungundlovu districts in the KwaZulu-Natal province of South Africa. Data collected from this questionnaire based survey is analysed in SPSS using descriptive statistics and Pearson correlations after checking the reliability and validity of the questionnaires. The main hypothesis driving this study is that there is a relationship between the demographics and the attribution identity of teachers on one hand, and their perceptions on the reliability of cellphones on the other hand, as suggested by existing literature; except that attribution identities are considered in this study under three angles: intention, knowledge and ability, and action. The results of this study confirm that the perceptions of teachers on the reliability of cellphones for teaching and learning are affected by the school location of these teachers, and by their perceptions on learners’ cellphones usage intentions and actual use.

Keywords: Attribution, Cellphones, E-learning, Reliability

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Authors: S. V. Kasmir Raja, P. Herbert Raj

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The overlay approach has been widely used by many service providers for Traffic Engineering (TE) in large Internet backbones. In the overlay approach, logical connections are set up between edge nodes to form a full mesh virtual network on top of the physical topology. IP routing is then run over the virtual network. Traffic engineering objectives are achieved through carefully routing logical connections over the physical links. Although the overlay approach has been implemented in many operational networks, it has a number of well-known scaling issues. This paper proposes a new approach to achieve traffic engineering without full-mesh overlaying with the help of integrated approach and equal subset split method. Traffic engineering needs to determine the optimal routing of traffic over the existing network infrastructure by efficiently allocating resource in order to optimize traffic performance on an IP network. Even though constraint-based routing [1] of Multi-Protocol Label Switching (MPLS) is developed to address this need, since it is not widely tested or debugged, Internet Service Providers (ISPs) resort to TE methods under Open Shortest Path First (OSPF), which is the most commonly used intra-domain routing protocol. Determining OSPF link weights for optimal network performance is an NP-hard problem. As it is not possible to solve this problem, we present a subset split method to improve the efficiency and performance by minimizing the maximum link utilization in the network via a small number of link weight modifications. The results of this method are compared against results of MPLS architecture [9] and other heuristic methods.

Keywords: Constraint based routing, Link Utilization, Subsetsplit method and Traffic Engineering.

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Authors: Shahrazed Medeghri, Saad Hamzaoui, Mokhtar Zerdali

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The metallurgical grade silicon (MG-Si) is obtained from the reduction of silica (SiO₂) in an induction furnace or an electric arc furnace. Impurities inherent in reduction process also depend on the quality of the raw material used. Among the applications of the silicon, it is used as a substrate for the photovoltaic conversion of solar energy and this conversion is wider as the purity of the substrate is important. Research is being done where the purpose is looking for new methods of manufacturing and purification of silicon, as well as new materials that can be used as substrates for the photovoltaic conversion of light energy. In this research, the technique of production of silicon in an induction furnace, using a high vacuum for fusion. Diatomaceous Silica (SiO2) used is 99 mass% initial purities, the carbon used is 6N of purity and the particle size of 63μm as starting materials. The final achieved purity of the material was above 50% by mass. These results demonstrate that this method is a technically reliable, and allows obtaining a better return on the amount 50% of silicon.

Keywords: Induction, amorphous silica, carbon microstructure, silicon.

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Authors: Eric Kojo Wu Aikins

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This paper examines the relationships between and among the various drivers of climate change that have both climatic and ecological consequences for vegetation and land cover change in arctic areas, particularly in arctic Alaska. It discusses the various processes that have created spatial and climatic structures that have facilitated observable vegetation and land cover changes in the Arctic. Also, it indicates that the drivers of both climatic and ecological changes in the Arctic are multi-faceted and operate in a system with both positive and negative feedbacks that largely results in further increases or decreases of the initial drivers of climatic and vegetation change mainly at the local and regional scales. It demonstrates that the impact of arctic warming on land cover change and the Arctic ecosystems is not unidirectional and one dimensional in nature but it represents a multi-directional and multi-dimensional forces operating in a feedback system.

Keywords: Arctic Vegetation Change, Climate Change, Feedback System, Spatial Process and Structure.

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Authors: Carlos Machado, José A. Mendes

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Home Automation is a field that, among other subjects, is concerned with the comfort, security and energy requirements of private homes. The configuration of automatic functions in this type of houses is not always simple to its inhabitants requiring the initial setup and regular adjustments. In this work, the ubiquitous computing system vision is used, where the users- action patterns are captured, recorded and used to create the contextawareness that allows the self-configuration of the home automation system. The system will try to free the users from setup adjustments as the home tries to adapt to its inhabitants- real habits. In this paper it is described a completely automated process to determine the light state and act on them, taking in account the users- daily habits. Artificial Neural Network (ANN) is used as a pattern recognition method, classifying for each moment the light state. The work presented uses data from a real house where a family is actually living.

Keywords: ANN, Home Automation, Neural Systems, PatternRecognition, Ubiquitous Computing.

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Authors: Ε. Giovanis

Abstract:

In this paper we present an autoregressive model with neural networks modeling and standard error backpropagation algorithm training optimization in order to predict the gross domestic product (GDP) growth rate of four countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer after the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model in the out-of-sample period. The idea behind this approach is to propose a parametric regression with weighted variables in order to test for the statistical significance and the magnitude of the estimated autoregressive coefficients and simultaneously to estimate the forecasts.

Keywords: Autoregressive model, Error back-propagation Feed-Forward neural networks, , Gross Domestic Product

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Authors: Khaireyah Kh. Al-Hamad, V. Nassehi, A. R. Khan

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Air pollution is a major environmental health problem, affecting developed and developing countries around the world. Increasing amounts of potentially harmful gases and particulate matter are being emitted into the atmosphere on a global scale, resulting in damage to human health and the environment. Petroleum-related air pollutants can have a wide variety of adverse environmental impacts. In the crude oil production sectors, there is a strong need for a thorough knowledge of gaseous emissions resulting from the flaring of associated gas of known composition on daily basis through combustion activities under several operating conditions. This can help in the control of gaseous emission from flares and thus in the protection of their immediate and distant surrounding against environmental degradation. The impacts of methane and non-methane hydrocarbons emissions from flaring activities at oil production facilities at Kuwait Oilfields have been assessed through a screening study using records of flaring operations taken at the gas and oil production sites, and by analyzing available meteorological and air quality data measured at stations located near anthropogenic sources. In the present study the Industrial Source Complex (ISCST3) Dispersion Model is used to calculate the ground level concentrations of methane and nonmethane hydrocarbons emitted due to flaring in all over Kuwait Oilfields. The simulation of real hourly air quality in and around oil production facilities in the State of Kuwait for the year 2006, inserting the respective source emission data into the ISCST3 software indicates that the levels of non-methane hydrocarbons from the flaring activities exceed the allowable ambient air standard set by Kuwait EPA. So, there is a strong need to address this acute problem to minimize the impact of methane and non-methane hydrocarbons released from flaring activities over the urban area of Kuwait.

Keywords: Kuwait Oilfields, ISCST3 model, flaring, Airpollution, Methane and Non-methane.

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Authors: E. Giovanis

Abstract:

In this paper we present a Feed-Foward Neural Networks Autoregressive (FFNN-AR) model with genetic algorithms training optimization in order to predict the gross domestic product growth of six countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer of the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model. Moreover this technique can be used in Autoregressive-Moving Average models, with and without exogenous inputs, as also the training process with genetics algorithms optimization can be replaced by the error back-propagation algorithm.

Keywords: Autoregressive model, Feed-Forward neuralnetworks, Genetic Algorithms, Gross Domestic Product

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Authors: M. B. Kime, J. Ntambwe, J. Mwamba

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Froth flotation remains to date as one of the most used metallurgical processes for concentrating metal-bearing minerals in ores. Oxide ores are relatively less amenable to froth flotation and require a judicious choice of reagents for the recovery of metals to be optimised. Laboratory batch flotation tests were conducted to determine the effect of two types of gasoil-rinkalore mixtures on the flotation response of a copper cobalt oxide ore sample. The head assay conducted on the initial ore sample showed that it contained about 2.90% of Cu, 0.12% of Co. Upon the flotation test work, the results obtained indicated that the concentrate obtained with use of the mixture gazoil-rinkalore RX yielded 8.24% Cu and 0.22% Co concentrate grades with recoveries of 76.0% Cu and 78.0% Co respectively. But, the concentrate obtained by use of the mixture gazoil-rinkalore RX3 yielded relatively bad results with 5.92% Cu and 0.18% Cu concentrate grades with recoveries of 70.3% Cu and 65.3% Co respectively.

Keywords: Cobalt, copper, froth flotation, Rinkalore RX, Rinkalore RX3, Shangolowe.

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Authors: A. Mojtaba Aghajani, B. Leila Shavakhi

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Energy intensity(energy consumption intensity) is a global index which computes the required energy for producing a specific value of goods and services in each country. It is computed in terms of initial energy supply or final energy consumption. In this study (research) Divisia method is used to decompose energy consumption and energy intensity. This method decomposes consumption and energy intensity to production effects, structural and net intensity and could be done as time series or two-periodical. This study analytically investigates consumption changes and energy intensity on economical sectors of Iran and more specific on road transportation(rail road and road).Our results show that the contribution of structural effect (change in economical activities combination) is very low and the effect of net energy consumption has the higher contribution in consumption changes and energy intensity. In other words, the high consumption of energy is due to Intensity of energy consumption and is not to structural effect of transportation sector.

Keywords: Divisia Method, Energy Intensity, Net IntensityEffect, Road Transportation , Structural Effect.

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Authors: Razib M. Othman, Safaai Deris, Rosli M. Illias

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Annotation of a protein sequence is pivotal for the understanding of its function. Accuracy of manual annotation provided by curators is still questionable by having lesser evidence strength and yet a hard task and time consuming. A number of computational methods including tools have been developed to tackle this challenging task. However, they require high-cost hardware, are difficult to be setup by the bioscientists, or depend on time intensive and blind sequence similarity search like Basic Local Alignment Search Tool. This paper introduces a new method of assigning highly correlated Gene Ontology terms of annotated protein sequences to partially annotated or newly discovered protein sequences. This method is fully based on Gene Ontology data and annotations. Two problems had been identified to achieve this method. The first problem relates to splitting the single monolithic Gene Ontology RDF/XML file into a set of smaller files that can be easy to assess and process. Thus, these files can be enriched with protein sequences and Inferred from Electronic Annotation evidence associations. The second problem involves searching for a set of semantically similar Gene Ontology terms to a given query. The details of macro and micro problems involved and their solutions including objective of this study are described. This paper also describes the protein sequence annotation and the Gene Ontology. The methodology of this study and Gene Ontology based protein sequence annotation tool namely extended UTMGO is presented. Furthermore, its basic version which is a Gene Ontology browser that is based on semantic similarity search is also introduced.

Keywords: automatic clustering, bioinformatics tool, gene ontology, protein sequence annotation, semantic similarity search

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Authors: Aparajita Goswami, Mihir K Purkait

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In the present study Schwertmannite (an iron oxide hydroxide) is selected as an adsorbent for defluoridation of water. The adsorbent was prepared by wet chemical process and was characterized by SEM, XRD and BET. The fluoride adsorption efficiency of the prepared adsorbent was determined with respect to contact time, initial fluoride concentration, adsorbent dose and pH of the solution. The batch adsorption data revealed that the fluoride adsorption efficiency was highly influenced by the studied factors. Equilibrium was attained within one hour of contact time indicating fast kinetics and the adsorption data followed pseudo second order kinetic model. Equilibrium isotherm data fitted to both Langmuir and Freundlich isotherm models for a concentration range of 5-30 mg/L. The adsorption system followed Langmuir isotherm model with maximum adsorption capacity of 11.3 mg/g. The high adsorption capacity of Schwertmannite points towards the potential of this adsorbent for fluoride removal from aqueous medium.

Keywords: Adsorption, fluoride, isotherm study, kinetics, schwertmannite.

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Authors: Mediha B. Sılaydın Aydın, Emine D. Kahraman

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One of the important impacts of climate change is the sea level rise. Turkey is a peninsula, so the coastal areas of the country are threatened by the problem of sea level rise. Therefore, the urbanized coastal areas are highly vulnerable to climate change. At the aim of enhancing spatial resilience of urbanized areas, this question arises: What should be the priority intervention subject in the urban planning process for a given city. To answer this question, by focusing on the problem of sea level rise, this study aims to determine spatial vulnerability typologies and levels of Turkey coastal cities based on morphological, physical and social characteristics. As a method, spatial vulnerability of coastal cities is determined by two steps as level and type. Firstly, physical structure, morphological structure and social structure were examined in determining spatial vulnerability levels. By determining these levels, most vulnerable areas were revealed as a priority in adaptation studies. Secondly, all parameters are also used to determine spatial typologies. Typologies are determined for coastal cities in order to use as a base for urban planning studies. Adaptation to climate change is crucial for developing countries like Turkey so, this methodology and created typologies could be a guide for urban planners as spatial directors and an example for other developing countries in the context of adaptation to climate change. The results demonstrate that the urban settlements located on the coasts of the Marmara Sea, the Aegean Sea and the Mediterranean respectively, are more vulnerable than the cities located on the Black Sea’s coasts to sea level rise.

Keywords: Climate change, coastal cities, sea level rise, urban land use planning, vulnerability.

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Authors: Xin-Lei Feng, Ting-Zhu Huang

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Allowing diagonalizability of sign pattern is still an open problem. In this paper, we make a carefully discussion about allowing unitary diagonalizability of two sign pattern. Some sufficient and necessary conditions of allowing unitary diagonalizability are also obtained.

Keywords: Sign pattern, unitary diagonalizability, eigenvalue, allowing diagonalizability.

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Authors: Yepeng Cheng, Yasuhiko Morimoto

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Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.

Keywords: Customer value, Huff's Gravity Model, POS, retailer.

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Authors: Vipin Saxena, Deepa Raj

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Unified Modeling language (UML) is one of the important modeling languages used for the visual representation of the research problem. In the present paper, UML model is designed for the Instruction pipeline which is used for the evaluation of the instructions of software programs. The class and sequence diagrams are designed & performance is evaluated for instructions of a sample program through a case study.

Keywords: UML, Instruction Pipeline, Class Diagram &Sequence Diagram.

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Authors: Amin Eslami, Jafar Bolouri Bazaz

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Excavation and retaining walls are of challenging issues in civil engineering. In this study, the behavior of one important type of supporting systems called Contiguous Bored Pile (CBP) retaining wall is investigated using a physical model. Besides, a comparison is made between two modes of free end piles (soft bed) and fixed end piles (stiff bed). Also a back calculation of effective length (the real free length of pile) is done by measuring lateral deflection of piles in different stages of excavation in both aforementioned cases. Based on observed results, for the fixed end mode, the effective length to free length ratio (Leff/L0) is equal to unity in initial stages of excavation and less than 1 in its final stages in a decreasing manner. While this ratio for free end mode, remains constant during all stages of excavation and is always less than unity.

Keywords: Contiguous Bored Pile Wall, Effective Length, Fixed End, Free End, Free Length.

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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: Mustafa Engin Basoğlu, Bekir Çakır

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The most important component affecting the efficiency of photovoltaic power systems are solar panels. In other words, efficiency of these systems are significantly affected due to the being low efficiency of solar panel. Thus, solar panels should be operated under maximum power point conditions through a power converter. In this study, design of boost converter has been carried out with maximum power point tracking (MPPT) algorithm which is incremental conductance (Inc-Cond). By using this algorithm, importance of power converter in MPPT hardware design, impacts of MPPT operation have been shown. It is worth noting that initial operation point is the main criteria for determining the MPPT performance. In addition, it is shown that if value of load resistance is lower than critical value, failure operation is realized. For these analyzes, direct duty control is used for simplifying the control.

Keywords: Boost converter, Incremental Conductance (Inc- Cond), MPPT, Solar panel.

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Authors: P. Gomathi Priya, M. E. Thenmozhi

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Iron nanoparticles were used to cleanup effluents. This paper involves synthesis of iron nanoparticles chemically by sodium borohydride reduction of ammonium ferrous sulfate solution (FAS). Iron oxide nanoparticles have lesser efficiency of adsorption than Zero Valent Iron nanoparticles (nZVI). Glucosamine acts as a stabilizing agent and chelating agent to prevent Iron nanoparticles from oxidation. nZVI particles were characterized using Scanning Electron Microscopy (SEM). Thus, the synthesized nZVI was subjected to entrapment in biopolymer, viz. barium (Ba)-alginate beads. The beads were characterized using SEM. Batch dye degradation studies were conducted using Reactive black Water soluble Nontoxic Natural substances (WNN) dye which is one of the most hazardous dyes used in textile industries. Effect of contact time, effect of pH, initial dye concentration, adsorbent dosage, isotherm and kinetic studies were carried out.

Keywords: Ammonium ferrous sulfate solution, barium (Ba)- alginate beads, reactive black WNN dye, zero valent iron nanoparticles.

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Authors: Saidu Ibrahim, Winston M. W. Shakantu

Abstract:

The problem of construction material waste remains unresolved, as a significant percentage of the materials delivered to some project sites end up as waste which might result in additional project cost. Cost overrun is a problem which affects 90% of the completed projects in the world. The argument on how to eliminate it has been on-going for the past 70 years, but there is neither substantial improvement nor significant solution for mitigating its detrimental effects. Research evidence has proposed various construction cost overruns and material-waste management approaches; nonetheless, these studies failed to give a clear indication on the framework and the equation for managing construction material waste and cost overruns. Hence, this research aims to develop a conceptual framework and a mathematical equation for managing material waste and cost overrun in the construction industry. The paper adopts the desktop methodological approach. This involves comparing the causes of material waste and those of cost overruns from the literature to determine the possible relationship. The review revealed a relationship between material waste and cost overrun that; increase in material waste would result to a corresponding increase in the amount of cost overrun at both the pre-contract and the post contract stages of a project. It was found from the equation that achieving an effective construction material waste management must ensure a “Good Quality-of-Planning, Estimating, and Design Management” and a “Good Quality- of-Construction, Procurement and Site Management”; a decrease in “Design Complexity” which would reduce “Material Waste” and subsequently reduce the amount of cost overrun by 86.74%. The conceptual framework and the mathematical equation developed in this study are recommended to the professionals of the construction industry.

Keywords: Conceptual framework, cost overrun, material waste, project stags.

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