Search results for: Support Vector Machine

Authors: Henning Bjornlund, Alec Zuo, Sarah Wheeler, Rob de Loë

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There is currently intensive debate in Alberta, Canada, regarding rural to urban water reallocation. This paper explores the demographic and attitudinal influences that are associated with the acceptance of water reallocation policies and whether such acceptance differs between urban and rural residents. We investigate three policy orientations in regards to water policies: i) government intervention; ii) environmental protection; and iii) protecting irrigators- water rights. We find that urban dwellers are more likely to favour government intervention while rural dwellers are more likely to support policies that aim at protecting irrigators- water rights. While urban dwellers are also more likely to favour environmental protection, the difference is not statistically significant. We also find that other factors have a significant impact on policy choice irrespective of residence such as demographic and socioeconomic factors as well as the values people hold toward water and the environment.

Keywords: Canada, rural, urban, water transfers.

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Authors: Li Xu, Huanbao Jiang, Zhenfei Huang, Lailai Zhang

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In recent years, as global warming, the sea-ice extent of North Arctic undergoes an evident decrease and Arctic channel has attracted the attention of shipping industry. Ice crystals existing in the seawater of Arctic channel which enter the seawater system of the ship with the seawater were found blocking the seawater pipe. The appearance of cooler paralysis, auxiliary machine error and even ship power system paralysis may be happened if seriously. In order to reduce the effect of high temperature in auxiliary equipment, seawater system will use external ice-water to participate in the cooling cycle and achieve the state of its flow. The distribution of ice crystals in seawater pipe can be achieved. As the ice slurry system is solid liquid two-phase system, the flow process of ice-water mixture is very complex and diverse. In this paper, the flow process in seawater pipe of ice slurry is simulated with fluid dynamics simulation software based on k-ε turbulence model. As the ice packing fraction is a key factor effecting the distribution of ice crystals, the influence of ice packing fraction on the flowing process of ice slurry is analyzed. In this work, the simulation results show that as the ice packing fraction is relatively large, the distribution of ice crystals is uneven in the flowing process of the seawater which has such disadvantage as increase the possibility of blocking, that will provide scientific forecasting methods for the forming of ice block in seawater piping system. It has important significance for the reliability of the operating of polar ships in the future.

Keywords: Ice slurry, seawater pipe, ice packing fraction, numerical simulation.

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Authors: Redha M. Elhuni

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The critical key success factors, which have to be targeted with appropriate change management, are the user acceptance and support of a new Enterprise Resource Planning (ERP) system at the early implementation stages. This becomes even more important in Arab context where national and organisational culture with a different value and belief system, resulting in different management styles, might not complement with Western business culture embedded in the predefined standard business processes of existing ERP packages. This study explains and critically evaluates research into national and organizational culture and the influence of different national cultures on the implementation and reengineering process of ERP packages in an Arab context. Using a case study, realized through a quantitative survey testing five of Martinsons’s and Davison’s propositions in a Libyan sample company, confirmed the expected results from the literature review that culture has an impact on the implementation process and that employee empowerment is an unavoidable consequence of an ERP implementation.

Keywords: Enterprise resource planning, ERP systems, organisational culture, Arab context.

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Authors: Zhongjie Wang, Xiaofei Xu, Dechen Zhan

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With deep development of software reuse, componentrelated technologies have been widely applied in the development of large-scale complex applications. Component identification (CI) is one of the primary research problems in software reuse, by analyzing domain business models to get a set of business components with high reuse value and good reuse performance to support effective reuse. Based on the concept and classification of CI, its technical stack is briefly discussed from four views, i.e., form of input business models, identification goals, identification strategies, and identification process. Then various CI methods presented in literatures are classified into four types, i.e., domain analysis based methods, cohesion-coupling based clustering methods, CRUD matrix based methods, and other methods, with the comparisons between these methods for their advantages and disadvantages. Additionally, some insufficiencies of study on CI are discussed, and the causes are explained subsequently. Finally, it is concluded with some significantly promising tendency about research on this problem.

Keywords: Business component, component granularity, component identification, reuse performance.

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Authors: Fazıl Gökgöz, Fahrettin Filiz

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Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: Deep learning, artificial neural networks, energy price forecasting, Turkey.

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Authors: Rao Fu, Jie Chen, Shutian Zeng, Yiping Zhuang, Agus Sudjianto

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Generative Adversarial Net (GAN) has proved to be a powerful machine learning tool in image data analysis and generation. In this paper, we propose to use Conditional Generative Adversarial Net (CGAN) to learn and simulate time series data. The conditions include both categorical and continuous variables with different auxiliary information. Our simulation studies show that CGAN has the capability to learn different types of normal and heavy-tailed distributions, as well as dependent structures of different time series. It also has the capability to generate conditional predictive distributions consistent with training data distributions. We also provide an in-depth discussion on the rationale behind GAN and the neural networks as hierarchical splines to establish a clear connection with existing statistical methods of distribution generation. In practice, CGAN has a wide range of applications in market risk and counterparty risk analysis: it can be applied to learn historical data and generate scenarios for the calculation of Value-at-Risk (VaR) and Expected Shortfall (ES), and it can also predict the movement of the market risk factors. We present a real data analysis including a backtesting to demonstrate that CGAN can outperform Historical Simulation (HS), a popular method in market risk analysis to calculate VaR. CGAN can also be applied in economic time series modeling and forecasting. In this regard, we have included an example of hypothetical shock analysis for economic models and the generation of potential CCAR scenarios by CGAN at the end of the paper.

Keywords: Conditional Generative Adversarial Net, market and credit risk management, neural network, time series.

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Authors: Ibrahim Naeimifar, Omid Naeemifar

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Evaluation of the excavation-induced ground movements is an important design aspect of support systems in urban areas. Geological and geotechnical conditions of an excavation area have significant effects on excavation-induced ground movements and the related damage. This paper is aimed at studying the performance of excavation walls supported by nails in jointed rock medium. The performance of nailed walls is investigated based on evaluating the excavation-induced ground movements. For this purpose, a set of calibrated 2D finite element models are developed by taking into account the nail-rock-structure interactions, the anisotropic properties of jointed rock, and the staged construction process. The results of this paper highlight effects of different parameters such as joint inclinations, anisotropy of rocks and nail inclinations on deformation parameters of excavation wall supported by nails.

Keywords: Finite element, jointed rock, nailing, performance.

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Authors: Juergen Rossmann, Andre Kupetz, Roland Wischnewski

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Mobile robots are used in a large field of scenarios, like exploring contaminated areas, repairing oil rigs under water, finding survivors in collapsed buildings, etc. Currently, there is no unified intuitive user interface (UI) to control such complex mobile robots. As a consequence, some scenarios are done without the exploitation of experience and intuition of human teleoperators. A novel framework has been developed to embed a flexible and modular UI into a complete 3-D virtual reality simulation system. This new approach wants to access maximum benefits of human operators. Sensor information received from the robot is prepared for an intuitive visualization. Virtual reality metaphors support the operator in his decisions. These metaphors are integrated into a real time stereo video stream. This approach is not restricted to any specific type of mobile robot and allows for the operation of different robot types with a consistent concept and user interface.

Keywords: 3-D simulation system, augmented reality, teleoperation of mobile robots, user interface.

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Authors: U. Sakthi, R. Hemalatha, R. S. Bhuvaneswaran

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In Virtual organization, Knowledge Discovery (KD) service contains distributed data resources and computing grid nodes. Computational grid is integrated with data grid to form Knowledge Grid, which implements Apriori algorithm for mining association rule on grid network. This paper describes development of parallel and distributed version of Apriori algorithm on Globus Toolkit using Message Passing Interface extended with Grid Services (MPICHG2). The creation of Knowledge Grid on top of data and computational grid is to support decision making in real time applications. In this paper, the case study describes design and implementation of local and global mining of frequent item sets. The experiments were conducted on different configurations of grid network and computation time was recorded for each operation. We analyzed our result with various grid configurations and it shows speedup of computation time is almost superlinear.

Keywords: Association rule, Grid computing, Knowledge grid, Mobility prediction.

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Authors: Valarie A. Williams

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This paper is a nonempirical analysis of existing literature on virtual leadership, transformational leadership, and remote work cultures. This paper will provide insight into how virtual workplaces can utilize transformational leadership styles to overcome challenges that have become a reality due to the COVID-19 Pandemic. Many organizations were forced into remote work to remain viable. It investigates the obstacles of working from home and the challenges leaders face in coaching and development. Employees lack face-to-face interactions and begin to feel isolated. Leaders cannot have in-person meetings and conversations and struggle to engage and encourage employees. In acknowledging the different dynamics of virtual work environments, organizations can make the necessary adjustments to best support employees. This paper reviews prior research studies and applies what is known to assist with current obstacles. This paper addresses how transformational leadership will assist in overcoming challenges within virtual work environments.

Keywords: Challenges in remote work, transformational leadership, virtual leadership, virtual work environments.

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Authors: Kanda Runapongsa Saikaew, Patcharaporn Jiranuwattanawong, Patinya Taearak

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Currently, there is excessively growing information about places on Facebook, which is the largest social network but such information is not explicitly organized and ranked. Therefore users cannot exploit such data to recommend places conveniently and quickly. This paper proposes a Facebook application and an Android application that recommend places based on the number of check-ins of those places, the distance of those places from the current location, the number of people who like Facebook page of those places, and the number of talking about of those places. Related Facebook data is gathered via Facebook API requests. The experimental results of the developed applications show that the applications can recommend places and rank interesting places from the most to the least. We have found that the average satisfied score of the proposed Facebook application is 4.8 out of 5. The users’ satisfaction can increase by adding the app features that support personalization in terms of interests and preferences.

Keywords: Mobile computing, location-based services, recommendation system, social network analysis.

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Authors: Igor Shardakov, Anton Bykov, Alexey Shestakov, Irina Glot

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This article focuses on the cycle of experimental studies of the formation of cracks and debondings in the concrete reinforced with carbon fiber. This research was carried out in Perm National Research Polytechnic University. A series of CFRP-strengthened RC beams was tested to investigate the influence of preload and crack repairing factors on CFRP debonding. IRT was applied to detect the early stage of IC debonding during the laboratory bending tests. It was found that for the beams strengthened under load after crack injecting, СFRP debonding strain is 4-65% lower than for the preliminary strengthened beams. The beams strengthened under the load had a relative area of debonding of 2 times higher than preliminary strengthened beams. The СFRP debonding strain is weakly dependent on the strength of the concrete substrate. For beams with a transverse wrapping anchorage in support sections FRP debonding is not a failure mode.

Keywords: FRP, RC beams, strengthening, IC debonding, infrared thermography, quality control, non-destructive testing methods.

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Authors: Tadayuki Kyoutani, Shigeyuki Haruyama, Ken Kaminishi, Zefry Darmawan

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Japan’s semiconductor industries have developed greatly in recent years. Many were started from a Small and Medium-sized Enterprises (SMEs) that found at a good circumstance and now become the prosperous industries in the world. Sustainable growth factors that support the creation of spirit value inside the Japanese company were strongly embedded through performance. Those factors were not clearly defined among each company. A series of literature research conducted to explore quantitative text mining about the definition of sustainable growth factors. Sustainable criteria were developed from previous research to verify the definition of the factors. A typical frame work was proposed as a systematical approach to develop sustainable growth factor in a specific company. Result of approach was review in certain period shows that factors influenced in sustainable growth was importance for the company to achieve the goal.

Keywords: SME, manufacture, sustainable, growth factor.

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Authors: P. Ruttanee, K-N. Areerak, K-L. Areerak

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Dynamic models of power converters are normally time-varying because of their switching actions. Several approaches are applied to analyze the power converters to achieve the timeinvariant models suitable for system analysis and design via the classical control theory. The paper presents how to derive dynamic models of the power system consisting of a three-phase controlled rectifier feeding an uncontrolled buck converter by using the combination between the well known techniques called the DQ and the generalized state-space averaging methods. The intensive timedomain simulations of the exact topology model are used to support the accuracies of the reported model. The results show that the proposed model can provide good accuracies in both transient and steady-state responses.

Keywords: DQ method, Generalized state-space averaging method, Three-phase controlled rectifier, Uncontrolled buck converter, Averaging model, Modeling, Simulation.

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Authors: Pawalai Kraipeerapun, Chun Che Fung, Kok Wai Wong

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This paper proposes a novel approach to the question of lithofacies classification based on an assessment of the uncertainty in the classification results. The proposed approach has multiple neural networks (NN), and interval neutrosophic sets (INS) are used to classify the input well log data into outputs of multiple classes of lithofacies. A pair of n-class neural networks are used to predict n-degree of truth memberships and n-degree of false memberships. Indeterminacy memberships or uncertainties in the predictions are estimated using a multidimensional interpolation method. These three memberships form the INS used to support the confidence in results of multiclass classification. Based on the experimental data, our approach improves the classification performance as compared to an existing technique applied only to the truth membership. In addition, our approach has the capability to provide a measure of uncertainty in the problem of multiclass classification.

Keywords: Multiclass classification, feed-forward backpropagation neural network, interval neutrosophic sets, uncertainty.

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Authors: Nazmona Mat Ali, Kecheng Liu

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Knowledge is a key asset for any organisation to sustain competitive advantages, but it is difficult to identify and represent knowledge which is needed to perform activities in business processes. The effective knowledge management and support for relevant business activities definitely gives a huge impact to the performance of the organisation as a whole. This is because that knowledge have the functions of directing, coordinating and controlling actions within business processes. The study has introduced organisational morphology, a norm-based approach by applying semiotic theories which emphasise on the representation of knowledge in norms. This approach is concerned with the identification of activities into three categories: substantive, communication and control activities. All activities are directed by norms; hence three types of norms exist; each is associated to a category of activities. The paper describes the approach briefly and illustrates the application of this approach through a case study of academic activities in higher education institutions. The result of the study shows that the approach provides an effective way to profile business knowledge and the profile enables the understanding and specification of business requirements of an organisation.

Keywords: Business knowledge, Business process, Norms, Semiotics, Organisational morphology

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Authors: Abdelbasit Gadour

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A great number of children in mainstream schools across Libya is currently living with emotional, behavioural difficulties. This study aims to explore teachers’ perceptions of children’s emotional and behavioural difficulties (EBD) and their attributions of the causes of EBD. The relevance of this area of study to current educational practice is illustrated in the fact that primary school teachers in Libya find classroom behaviour problems one of the major difficulties they face. The information presented in this study was gathered from 182 teachers that responded back to the survey, of whom, 27 teachers were later interviewed. In general, teachers’ perceptions of EBD reflect personal experience, training, and attitudes. Teachers appear from this study to use words such as indifferent, frightened, withdrawn, aggressive, disobedient, hyperactive, less ambitious, lacking concentration, and academically weak to describe pupils with EBD. The implications of this study are envisaged as being extremely important to support teachers addressing children’s EBD and shed light on the contributing factors to EBD for a successful teaching-learning process in Libyan primary schools.

Keywords: Teachers, children, learning, emotional and behaviour difficulties.

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Authors: Bruno Škrinjarić

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Rapid technological developments and increase in organizations’ interdependence on international scale are changing the traditional workplace paradigm. A key feature of knowledge based economy is that employers are looking for individuals that possess both specific academic skills and knowledge, and also capability to be proactive and respond to problems creatively and autonomously. The focus of this paper is workers with Economics and Business background and its goals are threefold: (1) to explore wide range of competences and identify which are the most important to employers; (2) to investigate the existence and magnitude of gap between required and possessed level of a certain competency; and (3) to inquire how this gap is connected with performance of a company. A study was conducted on a representative sample of Croatian enterprises during the spring of 2016. Results show that generic, rather than specific, competences are more important to employers and the gap between the relative importance of certain competence and its current representation in existing workforce is greater for generic competences than for specific. Finally, results do not support the hypothesis that this gap is correlated with firms’ performance.

Keywords: Competency gap, competency matching, key competences, firm performance.

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Authors: Somdech Rungsrisawat

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The purposes of this research are to investigate Thai teens’ attitude toward prostitution on the internet, to discover the causes of teenage prostitution and to study the relationship between teenage promiscuity and the causes of teenage prostitution. This study is a mixed research which utilized both qualitative and quantitative approach. The population of this study included teenagers and early adults between 14-21 years old who were studying in high schools, colleges, or universities. A total of 600 respondents was sampled for interviews using a questionnaire, and 48 samples were chosen for an in-depth interview.

The findings revealed that the majority of respondents recognized that teenage prostitution on line was real. The reasons for choosing the internet to contact with customers included easy, convenient, safe, and anonymous. Moreover, the internet allowed teen prostitutes to contact customers anywhere and anytime. The correlation showed that promiscuity was related to the trend of teen prostitution. Other factors that contributed to increasing widespread teen prostitution online included their need for quick money to buy luxurious products and to support their extravagant behavior.

Keywords: Internet, Prostitutes, Online, Thai teens.

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Authors: P. Selva, B. Lorrain, J. Alexis, A. Seror, A. Longuet, C. Mary, F. Denard

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Over the past four decades, the fatigue behavior of nickel-based alloys has been widely studied. However, in recent years, significant advances in the fabrication process leading to grain size reduction have been made in order to improve fatigue properties of aircraft turbine discs. Indeed, a change in particle size affects the initiation mode of fatigue cracks as well as the fatigue life of the material. The present study aims to investigate the fatigue behavior of a newly developed nickel-based superalloy under biaxial-planar loading. Low Cycle Fatigue (LCF) tests are performed at different stress ratios so as to study the influence of the multiaxial stress state on the fatigue life of the material. Full-field displacement and strain measurements as well as crack initiation detection are obtained using Digital Image Correlation (DIC) techniques. The aim of this presentation is first to provide an in-depth description of both the experimental set-up and protocol: the multiaxial testing machine, the specific design of the cruciform specimen and performances of the DIC code are introduced. Second, results for sixteen specimens related to different load ratios are presented. Crack detection, strain amplitude and number of cycles to crack initiation vs. triaxial stress ratio for each loading case are given. Third, from fractographic investigations by scanning electron microscopy it is found that the mechanism of fatigue crack initiation does not depend on the triaxial stress ratio and that most fatigue cracks initiate from subsurface carbides.

Keywords: Cruciform specimen, multiaxial fatigue, Nickelbased superalloy.

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Authors: Achmad Zamroni, Masahiro Yamao

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Seaweed farming is emerging as a viable alternative activity in the Indonesian fisheries sector. This paper aims to investigate people-s perceptions of seaweed farming, to analyze its social and economic impacts and to identify the problems and obstacles hindering its continued development. Structured and semi-structured questionnaires were prepared to obtain qualitative data, and interviews were conducted with fishermen who also plant seaweed. The findings showed that fishermen in the Laikang Bay were enthusiastic about cultivating seaweeds and that seaweed plays a major role in supporting the household economy of fishermen. However, current seaweed drying technologies cannot support increased seaweed production on a farm or plot, especially in the rainy season. Additionally, variable monsoon seasons and long marketing channels are still major constraints on the development of the industry. Finally, capture fisheries, the primary economic livelihood of fishermen of older generations, is being slowly replaced by seaweed farming.

Keywords: Coastal management, perception, seaweed development and livelihood diversification

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Authors: Zuraini Hanim Zaini, Wan Fatimah Wan Ahmad

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Multimedia courseware has been accepted as a tool that can support teaching and learning process. 'Li2D' courseware was developed to assist student-s visualization on the topic of Loci in Two Dimension. This paper describes an evaluation on the effectiveness and usability of a 'Li2D' courseware. The quasi experiment was used for the effectiveness evaluation. Usability evaluation was accomplished based on four constructs of usability, namely: efficiency, learnability, screen design and satisfaction. An evaluation on the multimedia elements was also conducted. A total of 63 students of Form Two are involved in the study. The students are divided into two groups: control and experimental. The experimental group had to interact with 'Li2D' courseware as part of the learning activities while the control group used the conventional learning methods. The results indicate that the experimental group performed better than the control group in understanding the Loci in Two Dimensions topic. In terms of usability, the results showed that the students agreed on the usability in multimedia elements in the 'Li2D' courseware.

Keywords: Effectiveness, usability and multimedia elements, Loci in Two Dimensions.

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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: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

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Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: Convolutional neural network, lithology, prediction of reservoir lithology, seismic attributes.

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Authors: D Sudheer Reddy, N Gopal Reddy, P V Radhadevi, J Saibaba, Geeta Varadan

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Smoothing or filtering of data is first preprocessing step for noise suppression in many applications involving data analysis. Moving average is the most popular method of smoothing the data, generalization of this led to the development of Savitzky-Golay filter. Many window smoothing methods were developed by convolving the data with different window functions for different applications; most widely used window functions are Gaussian or Kaiser. Function approximation of the data by polynomial regression or Fourier expansion or wavelet expansion also gives a smoothed data. Wavelets also smooth the data to great extent by thresholding the wavelet coefficients. Almost all smoothing methods destroys the peaks and flatten them when the support of the window is increased. In certain applications it is desirable to retain peaks while smoothing the data as much as possible. In this paper we present a methodology called as peak-wise smoothing that will smooth the data to any desired level without losing the major peak features.

Keywords: smoothing, moving average, peakwise smoothing, spatialdensity models, planar shape models, wavelets.

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Authors: Sang-Hun Lee, Bum-Soo Kim, Yang-Sae Moon, Jinho Kim

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In this paper we present a photo mosaic smartphone application in client-server based large-scale image databases. Photo mosaic is not a new concept, but there are very few smartphone applications especially for a huge number of images in the client-server environment. To support large-scale image databases, we first propose an overall framework working as a client-server model. We then present a concept of image-PAA features to efficiently handle a huge number of images and discuss its lower bounding property. We also present a best-match algorithm that exploits the lower bounding property of image-PAA. We finally implement an efficient Android-based application and demonstrate its feasibility.

Keywords: smartphone applications; photo mosaic; similarity search; data mining; large-scale image databases.

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Authors: Md Shohidul Islam, Jongmyon Kim, Ui-pil Chong

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Medical image is an integral part of e-health care and e-diagnosis system. Medical image watermarking is widely used to protect patients’ information from malicious alteration and manipulation. The watermarked medical images are transmitted over the internet among patients, primary and referred physicians. The images are highly prone to corruption in the wireless transmission medium due to various noises, deflection, and refractions. Distortion in the received images leads to faulty watermark detection and inappropriate disease diagnosis. To address the issue, this paper utilizes error correction code (ECC) with (8, 4) Hamming code in an existing watermarking system. In addition, we implement the high complex ECC on a graphics processing units (GPU) to accelerate and support real-time requirement. Experimental results show that GPU achieves considerable speedup over the sequential CPU implementation, while maintaining 100% ECC efficiency.

Keywords: Medical Image Watermarking (MIW), e-health system, error correction, Hamming code, GPU.

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Authors: Minwoo Son, Seung-Hun Lee, Dongkyoo Shin, Dongil Shin

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The next stage of the home networking environment is supposed to be ubiquitous, where each piece of material is equipped with an RFID (Radio Frequency Identification) tag. To fully support the ubiquitous environment, home networking middleware should be able to recommend home services based on a user-s interests and efficiently manage information on service usage profiles for the users. Therefore, USN (Ubiquitous Sensor Network) technology, which recognizes and manages a appliance-s state-information (location, capabilities, and so on) by connecting RFID tags is considered. The Intelligent Multi-Agent Middleware (IMAM) architecture was proposed to intelligently manage the mobile RFID-based home networking and to automatically supply information about home services that match a user-s interests. Evaluation results for personalization services for IMAM using Bayesian-Net and Decision Trees are presented.

Keywords: Intelligent Agents, Home Network, Mobile RFID, Intelligent Middleware.

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Authors: J. Gazzola, I. M. Dal Fabbro, J. Soriano, M. V. G. Silva, S. Rodrigues

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Application of wood in rural construction is diffused all around the world since remote times. However, its inclusion in structural design deserves strong support from broad knowledge of material properties. The pertinent literature reveals the application of optical methods in determining the complete field displacement on bodies exhibiting regular as well as irregular surfaces. The use of moiré techniques in experimental mechanics consists in analyzing the patterns generated on the body surface before and after deformation. The objective of this research work is to study the qualitative deformation behavior of wooden testing specimens under specific loading situations. The experiment setup follows the literature description of shadow moiré methods. Results indicate strong anisotropy influence of the generated displacement field. Important qualitative as well as quantitative stress and strain distribution were obtained wooden members which are applicable to rural constructions.

Keywords: Moiré methods, wooden structural material, rural constructions.

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Authors: Q. Han, W. Schaefer, R. van den Berg

Abstract:

This paper deals with stakeholders’ decisions within energy neutral urban redevelopment processes. The decisions of these stakeholders during the process will make or break energy neutral ambitions. An extensive form of game theory model gave insight in the behavioral differences of stakeholders regarding energy neutral ambitions and the effects of the changing legislation. The results show that new legislation regarding spatial planning slightly influences the behavior of stakeholders. An active behavior of the municipality will still result in the best outcome. Nevertheless, the municipality becomes more powerful when acting passively and can make the use of planning tools to provide governance towards energy neutral urban redevelopment. Moreover, organizational support, recognizing the necessity for energy neutrality, keeping focused and collaboration among stakeholders are crucial elements to achieve the objective of an energy neutral urban (re)development.

Keywords: Energy neutrality urban (re)development, stakeholder behavior, legislation, game theory.

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