Search results for: technology acceptance model (TAM)

Authors: A. Azadeh, Z. Raoofi

Abstract:

Natural gas, as one of the most important sources of energy for many of the industrial and domestic users all over the world, has a complex, huge supply chain which is in need of heavy investments in all the phases of exploration, extraction, production, transportation, storage and distribution. The main purpose of supply chain is to meet customers’ need efficiently and with minimum cost. In this study, with the aim of minimizing economic costs, different levels of natural gas supply chain in the form of a multi-echelon, multi-period fuzzy linear programming have been modeled. In this model, different constraints including constraints on demand satisfaction, capacity, input/output balance and presence/absence of a path have been defined. The obtained results suggest efficiency of the recommended model in optimal allocation and reduction of supply chain costs.

Keywords: Cost Approach, Fuzzy Theory, Linear Programming, Natural Gas Supply Chain.

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Authors: Barenten Suciu

Abstract:

In this work, by replacing the traditional solid spokes with colloidal spokes, a vehicle wheel with a built-in suspension structure is proposed. Following the background and description of the wheel system, firstly, a vibration model of the wheel equipped with colloidal spokes is proposed, and based on such model the equivalent damping coefficients and spring constants are identified. Then, a modified model of a quarter-vehicle moving on a rough pavement is proposed in order to estimate the transmissibility of vibration from the road roughness to vehicle body. In the end, the optimal design of the colloidal spokes and the optimum number of colloidal spokes are decided in order to minimize the transmissibility of vibration, i.e., to maximize the ride comfort of the vehicle.

Keywords: Built-in suspension, colloidal spoke, intrinsic spring, vibration analysis, wheel.

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Authors: E. Guercio, A. Marcengo, A. Rapp

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This paper draws a methodological framework adopted within an internal Telecomitalia project aimed to identify, on a user centred base, the potential interest towards a technological scenario aimed to extend on a personal bubble the typical communication and media fruition home environment. The problem is that involving user in the early stage of the development of such disruptive technology scenario asking users opinions on something that users actually do not manage even in a rough manner could lead to wrong or distorted results. For that reason we chose an approach that indirectly aim to understand users hidden needs in order to obtain a meaningful picture of the possible interest for a technological proposition non yet easily understandable.

Keywords: Personas, focus groups, scenarios, extended home environment, telecommunication, media.

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Authors: Xiangbin Zhu

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Advances in computing applications in recent years have prompted the demand for more flexible scheduling models for QoS demand. Moreover, in practical applications, partly violated temporal constraints can be tolerated if the violation meets certain distribution. So we need extend the traditional Liu and Lanland model to adapt to these circumstances. There are two extensions, which are the (m, k)-firm model and Window-Constrained model. This paper researches on weakly hard real-time constraints and their combination to support QoS. The fact that a practical application can tolerate some violations of temporal constraint under certain distribution is employed to support adaptive QoS on the open real-time system. The experiment results show these approaches are effective compared to traditional scheduling algorithms.

Keywords: Weakly Hard Real-Time, Real-Time, Scheduling, Quality of Service.

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Authors: Mircea Ivanescu, Nirvana Popescu, Decebal Popescu, Dorin Popescu

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This paper addresses the control problem of a class of hyper-redundant arms. In order to avoid discrepancy between the mathematical model and the actual dynamics, the dynamic model with uncertain parameters of this class of manipulators is inferred. A procedure to design a feedback controller which stabilizes the uncertain system has been proposed. A PD boundary control algorithm is used in order to control the desired position of the manipulator. This controller is easy to implement from the point of view of measuring techniques and actuation. Numerical simulations verify the effectiveness of the presented methods. In order to verify the suitability of the control algorithm, a platform with a 3D flexible manipulator has been employed for testing. Experimental tests on this platform illustrate the applications of the techniques developed in the paper.

Keywords: Distributed model, flexible manipulator, observer, robot control.

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Authors: Alessio Plebe

Abstract:

One astonishing capability of humans is to recognize thousands of different objects visually, and to learn the semantic association between those objects and words referring to them. This work is an attempt to build a computational model of such capacity,simulating the process by which infants learn how to recognize objects and words through exposure to visual stimuli and vocal sounds.One of the main fact shaping the brain of a newborn is that lights and colors come from entities of the world. Gradually the visual system learn which light sensations belong to same entities, despite large changes in appearance. This experience is common between humans and several other mammals, like non-human primates. But humans only can recognize a huge variety of objects, most manufactured by himself, and make use of sounds to identify and categorize them. The aim of this model is to reproduce these processes in a biologically plausible way, by reconstructing the essential hierarchy of cortical circuits on the visual and auditory neural paths.

Keywords: Auditory cortex, object recognition, self-organizingmaps

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Authors: Kunchit Pirapake

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Application of Geo-Informatic technology in land tenure and land use on the economic crop area, to create sustainable land, access to the area, and produce sustainable food for the demand of its people in the community. The research objectives are to 1) apply Geo-Informatic Technology on land ownership and agricultural land use (cash crops) in the research area, 2) create GIS database on land ownership and land use, 3) create database of an online Geoinformation system on land tenure and land use. The results of this study reveal that, first; the study area is on high slope, mountains and valleys. The land is mainly in the forest zone which was included in the Forest Act 1941 and National Conserved Forest 1964. Residents gained the rights to exploit the land passed down from their ancestors. The practice was recognized by communities. The land was suitable for cultivating a wide variety of economic crops that was the main income of the family. At present the local residents keep expanding the land to grow cash crops. Second; creating a database of the geographic information system consisted of the area range, announcement from the Interior Ministry, interpretation of satellite images, transportation routes, waterways, plots of land with a title deed available at the provincial land office. Most pieces of land without a title deed are located in the forest and national reserve areas. Data were created from a field study and a land zone determined by a GPS. Last; an online Geo-Informatic System can show the information of land tenure and land use of each economic crop. Satellite data with high resolution which could be updated and checked on the online Geo-Informatic System simultaneously.

Keywords: Geo-Informatic Technology, Land Tenure, Online Geo-Informatic System, Land Use of cash crops.

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Authors: Yasuo Obikane

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The frequency dependence of the phase field model(PFM) is studied. A simple PFM is proposed, and is tested in a laminar boundary layer. The Blasius-s laminar boundary layer solution on a flat plate is used for the flow pattern, and several frequencies are imposed on the PFM, and the decay times of the interfaces are obtained. The computations were conducted for three cases: 1) no-flow, and 2) a half ball on the laminar boundary layer, 3) a line of mass sources in the laminar boundary layer. The computations show the decay time becomes shorter as the frequency goes larger, and also show that it is sensitive to both background disturbances and surface tension parameters. It is concluded that the proposed simple PFM can describe the properties of decay process, and could give the fundamentals for the decay of the interface in turbulent flows.

Keywords: Phase field model, two phase flows, Laminarboundary Layer

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Authors: Rafal Maciag

Abstract:

Due to the development of the current civilization, one must create suitable models of its pervasive massive phenomena. Such a phenomenon is the digital transformation, which has a substantial number of disciplined, methodical interpretations forming the diversified reflection. This reflection could be understood pragmatically as the current temporal, a local differential state of knowledge. The model of the discursive space is proposed as a model for the analysis and description of this knowledge. Discursive space is understood as an autonomous multidimensional space where separate discourses traverse specific trajectories of what can be presented in multidimensional parallel coordinate system. Discursive space built on the world of facts preserves the complex character of that world. Digital transformation as a discursive space has a relativistic character that means that at the same time, it is created by the dynamic discourses and these discourses are molded by the shape of this space.

Keywords: Knowledge, digital transformation, discourse, discursive space, complexity.

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Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom

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The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. Previous work established that the Ward-style artificial neural network (ANN) is a suitable tool for developing such models. The current research focused on developing ANN models with reduced average prediction error by increasing the number of distinct observations used in training, adding additional input terms that describe the date of an observation, increasing the duration of prior weather data included in each observation, and reexamining the number of hidden nodes used in the network. Models were created to predict air temperature at hourly intervals from one to 12 hours ahead. Each ANN model, consisting of a network architecture and set of associated parameters, was evaluated by instantiating and training 30 networks and calculating the mean absolute error (MAE) of the resulting networks for some set of input patterns. The inclusion of seasonal input terms, up to 24 hours of prior weather information, and a larger number of processing nodes were some of the improvements that reduced average prediction error compared to previous research across all horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or 12.5%, less than the previous model. Prediction MAEs eight and 12 hours ahead improved by 0.17°C and 0.16°C, respectively, improvements of 7.4% and 5.9% over the existing model at these horizons. Networks instantiating the same model but with different initial random weights often led to different prediction errors. These results strongly suggest that ANN model developers should consider instantiating and training multiple networks with different initial weights to establish preferred model parameters.

Keywords: Decision support systems, frost protection, fruit, time-series prediction, weather modeling

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Authors: Yakin Hajlaoui, Richard Labib, Jean-Franc¸ois Plante, Michel Gamache

Abstract:

This study presents the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs’ processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW’s ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. We employ gradient descent and backpropagation to train ML-IDW. The performance of the proposed model is compared against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. Our results highlight the efficacy of ML-IDW, particularly in handling complex spatial dataset, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: Deep Learning, Multi-Layer Neural Networks, Gradient Descent, Spatial Interpolation, Inverse Distance Weighting.

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Authors: Christopher Deekia Nwimae, Nigel Simms, Liyun Lao

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Erosion in a pipe bends caused by particles is a major concern in the oil and gas fields and might cause breakdown to production equipment. This work investigates the effect of sand particle transport in an elbow using computational fluid dynamics (CFD) approach. Two-way coupled Euler-Lagrange and discrete phase model is employed to calculate the air/solid particle flow in the elbow. Generic erosion model in Ansys fluent and three particle rebound models are used to predict the erosion rate on the 90° elbows. The model result is compared with experimental data from the open literature validating the CFD-based predictions which reveals that due to the sand particles impinging on the wall of the elbow at high velocity, a point on the pipe elbow were observed to have started turning red due to velocity increase and the maximum erosion locations occur at 48°.

Keywords: Erosion, prediction, elbow, computational fluid dynamics, CFD.

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Authors: P. G. Siddheshwar, B. N. Veena

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Rayleigh-B´enard convection of a nanoliquid in shallow, square and tall enclosures is studied using the Khanafer-Vafai-Lightstone single-phase model. The thermophysical properties of water, copper, copper-oxide, alumina, silver and titania at 3000 K under stagnant conditions that are collected from literature are used in calculating thermophysical properties of water-based nanoliquids. Phenomenological laws and mixture theory are used for calculating thermophysical properties. Free-free, rigid-rigid and rigid-free boundary conditions are considered in the study. Intractable Lorenz model for each boundary combination is derived and then reduced to the tractable Ginzburg-Landau model. The amplitude thus obtained is used to quantify the heat transport in terms of Nusselt number. Addition of nanoparticles is shown not to alter the influence of the nature of boundaries on the onset of convection as well as on heat transport. Amongst the three enclosures considered, it is found that tall and shallow enclosures transport maximum and minimum energy respectively. Enhancement of heat transport due to nanoparticles in the three enclosures is found to be in the range 3% - 11%. Comparison of results in the case of rigid-rigid boundaries is made with those of an earlier work and good agreement is found. The study has limitations in the sense that thermophysical properties are calculated by using various quantities modelled for static condition.

Keywords: Enclosures, free-free, rigid-rigid and rigid-free boundaries, Ginzburg-Landau model, Lorenz model.

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Authors: Kambiz Tahvildari, Shakila ila Motamedi

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Presently and in line with the United Nations (EPA), human thinking system has shifted towards clean fuels so as to maintain a cleaner environment and to save our planet earth. One of the most successful studies in order to achieve new energies includes the use of animal wastes and their organic residues, and the result of these researches has been represented in the form of very simple and cheap methods called biogas technology. Biogas technology has developed a lot in the recent decades; its reason is the high cost of fossil fuels and the greater attention of countries to the environmental pollutions due to the consumption of this kind of fuels. IRAN is ready for the optimized application of renewable energies, having much enriched resources of this kind of energies; so a special place could be considered for it when making programs. The purpose of biogas technology is the recovery of energy and finally the protection of the environment, which is much appropriate for the third world farmers with respect to their technical abilities and economic potentials. Studies show that the production and consumption of biogas is appropriate and economic in IRAN, because of the high amount of waste in the agriculture sector, the significant amount of animal and human excrement production, the great volume of garbage produced and the most important the specific social, climatic and agricultural conditions in IRAN, in order to proceed towards the reduction of pollution due to the use of fossil fuels.

Keywords: Agriculture, Biogas, Energy, Environment.

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Authors: M. S. Alam, M. R. Alam, Nusrat Jahan Imu

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This paper presents a computer simulation model based on system dynamics methodology for analyzing the dynamic characteristics of input energy structure in agriculture and Bangladesh is used here as a case study for model validation. The model provides an input energy structure linking the major energy flows with human energy and draft energy from cattle as well as tractors and/or power tillers, irrigation, chemical fertilizer and pesticide. The evaluation is made in terms of different energy dependent indicators. During the simulation period, the energy input to agriculture increased from 6.1 to 19.15 GJ/ha i.e. 2.14 fold corresponding to energy output in terms of food, fodder and fuel increase from 71.55 to 163.58 GJ/ha i.e. 1.28 fold from the base year. This result indicates that the energy input in Bangladeshi agricultural production is increasing faster than the energy output. Problems such as global warming, nutrient loading and pesticide pollution can associate with this increasing input. For an assessment, a comparative statement of input energy use in agriculture of developed countries (DCs) and least developed countries (LDCs) including Bangladesh has been made. The performance of the model is found satisfactory to analyze the agricultural energy system for LDCs

Keywords: Agriculture, energy indicator, system dynamics, energy flows.

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Authors: Shilpi Lavania

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As the frequency of operation has attained a range of GHz and signal rise time continues to increase interconnect technology is suffering due to various high frequency effects as well as ground bounce problem. In some recent studies a high frequency effect i.e. skin effect has been modeled and its drawbacks have been discussed. This paper strives to make an impression on the advantage side of modeling skin effect for interconnect line. The proposed method has considered a CMOS with RC interconnect. Delay and noise considering ground bounce problem and with skin effect are discussed. The simulation results reveal an advantage of considering skin effect for minimization of ground bounce problem during the working of the model. Noise and delay variations with temperature are also presented.

Keywords: Interconnect, Skin effect, Ground Bounce, Delay, Noise.

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Authors: Mounira Rouaïnia, Mohamed Salah Medjram, Noureddine Doghmane

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In Multiple Sclerosis, pathological changes in the brain results in deviations in signal intensity on Magnetic Resonance Images (MRI). Quantitative analysis of these changes and their correlation with clinical finding provides important information for diagnosis. This constitutes the objective of our work. A new approach is developed. After the enhancement of images contrast and the brain extraction by mathematical morphology algorithm, we proceed to the brain segmentation. Our approach is based on building statistical model from data itself, for normal brain MRI and including clustering tissue type. Then we detect signal abnormalities (MS lesions) as a rejection class containing voxels that are not explained by the built model. We validate the method on MR images of Multiple Sclerosis patients by comparing its results with those of human expert segmentation.

Keywords: EM algorithm, Magnetic Resonance Imaging, Mathematical morphology, Markov random model.

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Authors: Nhon Do, Hien Nguyen

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Nowadays there are many methods for representing knowledge such as semantic network, neural network, and conceptual graphs. Nonetheless, these methods are not sufficiently efficient when applied to perform and deduce on knowledge domains about supporting in general education such as algebra, analysis or plane geometry. This leads to the introduction of computational network which is a useful tool for representation knowledge base, especially for computational knowledge, especially knowledge domain about general education. However, when dealing with a practical problem, we often do not immediately find a new solution, but we search related problems which have been solved before and then proposing an appropriate solution for the problem. Besides that, when finding related problems, we have to determine whether the result of them can be used to solve the practical problem or not. In this paper, the extension model of computational network has been presented. In this model, Sample Problems, which are related problems, will be used like the experience of human about practical problem, simulate the way of human thinking, and give the good solution for the practical problem faster and more effectively. This extension model is applied to construct an automatic system for solving algebraic problems in middle school.

Keywords: educational software, artificial intelligence, knowledge base system, knowledge representation.

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Authors: S. M. Ali, N. R. Dhar

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Tool wear and surface roughness prediction plays a significant role in machining industry for proper planning and control of machining parameters and optimization of cutting conditions. This paper deals with developing an artificial neural network (ANN) model as a function of cutting parameters in turning steel under minimum quantity lubrication (MQL). A feed-forward backpropagation network with twenty five hidden neurons has been selected as the optimum network. The co-efficient of determination (R2) between model predictions and experimental values are 0.9915, 0.9906, 0.9761 and 0.9627 in terms of VB, VM, VS and Ra respectively. The results imply that the model can be used easily to forecast tool wear and surface roughness in response to cutting parameters.

Keywords: ANN, MQL, Surface Roughness, Tool Wear.

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Authors: Hao Min Chuah, Tatsuya Yamazaki, Ryosui Iwasawa, Tatsumi Suto

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In recent years, with the advancement of digital technology, the movement to introduce so-called ICT (Information and Communication Technology), such as computer technology and network technology, to civil engineering construction sites and construction sites is accelerating. As part of this movement, attempts are being made in various situations to reproduce actual sites inside computers and use them for designing and construction planning, as well as for training inexperienced engineers. The installation of wave-dissipating blocks on coasts, etc., is a type of work that has been carried out by skilled workers based on their years of experience and is one of the tasks that is difficult for inexperienced workers to carry out on site. Wave-dissipating blocks are structures that are designed to protect coasts, beaches, and so on from erosion by reducing the energy of ocean waves. Wave-dissipating blocks usually weigh more than 1 t and are installed by being suspended by a crane, so it would be time-consuming and costly for inexperienced workers to train on-site. In this paper, therefore, a block installation simulator is developed based on Unity 3D, a game development engine. The simulator computes porosity. Porosity is defined as the ratio of the total volume of the wave breaker blocks inside the structure to the final shape of the ideal structure. Using the evaluation of porosity, the simulator can determine how well the user is able to install the blocks. The voxelization technique is used to calculate the porosity of the structure, simplifying the calculations. Other techniques, such as raycasting and box overlapping, are employed for accurate simulation. In the near future, the simulator will install an automatic block installation algorithm based on combinatorial optimization solutions and compare the user-demonstrated block installation and the appropriate installation solved by the algorithm.

Keywords: 3D simulator, porosity, user interface, voxelization, wave-dissipating blocks.

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Authors: Toshitaka Higashino, Naoki Wakamiya

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Human beings perform a task by perceiving information from outside, recognizing them, and responding them. There have been various attempts to analyze and understand internal processes behind the reaction to a given stimulus by conducting psychological experiments and analysis from multiple perspectives. Among these, we focused on Model Human Processor (MHP). However, it was built based on psychological experiments and thus the relation with brain activity was unclear so far. To verify the validity of the MHP and propose our model from a viewpoint of neuroscience, EEG (Electroencephalography) measurements are performed during experiments in this study. More specifically, first, experiments were conducted where Latin alphabet characters were used as visual stimuli. In addition to response time, ERPs (event-related potentials) such as N100 and P300 were measured by using EEG. By comparing cycle time predicted by the MHP and latency of ERPs, it was found that N100, related to perception of stimuli, appeared at the end of the perceptual processor. Furthermore, by conducting an additional experiment, it was revealed that P300, related to decision making, appeared during the response decision process, not at the end. Second, by experiments using Japanese Hiragana characters, i.e. Japan's own phonetic symbols, those findings were confirmed. Finally, Japanese Kanji characters were used as more complicated visual stimuli. A Kanji character usually has several readings and several meanings. Despite the difference, a reading-related task and a meaning-related task exhibited similar results, meaning that they involved similar information processing processes of the brain. Based on those results, our model was proposed which reflects response time and ERP latency. It consists of three processors: the perception processor from an input of a stimulus to appearance of N100, the cognitive processor from N100 to P300, and the decision-action processor from P300 to response. Using our model, an application system which reflects brain activity can be established.

Keywords: Brain activity, EEG, information processing model, model human processor.

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: Classification algorithms; data mining; tourism; knowledge discovery.

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Authors: Jianlin Li, Jizhen Li

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Transnational corporations (TNCs) are playing a major role in global R&D, not only through activities in their home countries but also increasingly abroad. However, the process of R&D offshoring is not yet discussed thoroughly. Based on in-depth case study on Agilent China Communications Operation, this paper presents a stage model for theorizing the R&D offshoring process. This stage model outlines 5 maturity levels of organization and the offshoring process: Subsidiary team, Mirror team, Independent team, Mirror sector and the Independent sector (from software engineering point of view, it is similar to the local team's capability level of maturity model). Moreover, the paper gives a detailed discussion on the relevant characteristics, as well as the ability/responsibility of transfer, priorities and the corresponding organization structure. It also gives the characteristics and key points of different level-s R&D offshoring implementation using actual team practice.

Keywords: Internationalization of R&D, R&D offshoring process, Multinational Corporations, Organization Level.

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Authors: Tlou J. Ramabu

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Programming is one of the challenging subjects in the field of computing. In the higher education sphere, some programming novices’ performance, retention rate, and success rate are not improving. Most of the time, the problem is caused by the slow pace of learning, difficulty in grasping the syntax of the programming language and poor logical skills. More importantly, programming forms part of major subjects within the field of computing. As a result, specialized pedagogical methods and innovation are highly recommended. Little research has been done on the potential productivity of the WhatsApp platform as part of a blended learning model. In this article, the authors discuss the WhatsApp group as a part of blended learning model incorporated for a group of programming novices. We discuss possible administrative activities for productive utilisation of the WhatsApp group on the blended learning overview. The aim is to take advantage of the popularity of WhatsApp and the time students spend on it for their educational purpose. We believe that blended learning featuring a WhatsApp group may ease novices’ cognitive load and strengthen their foundational programming knowledge and skills. This is a work in progress as the proposed blended learning model with WhatsApp incorporated is yet to be implemented.

Keywords: Blended learning, higher education, WhatsApp, programming, novices, lecturers.

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Authors: Raymond K. Jonkers

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The present study investigated approaches and techniques to enhance strategic management governance and decision making within the framework of a performance-based balanced scorecard. The review of best practices from strategic, program, process, and systems engineering management provided for a holistic approach toward effective outcome-based capability management. One technique, based on factorial experimental design methods, was used to develop an empirical model. This model predicted the degree of capability effectiveness and is dependent on controlled system input variables and their weightings. These variables represent business performance measures, captured within a strategic balanced scorecard. The weighting of these measures enhances the ability to quantify causal relationships within balanced scorecard strategy maps. The focus in this study was on the performance of tangible assets within the scorecard rather than the traditional approach of assessing performance of intangible assets such as knowledge and technology. Tangible assets are represented in this study as physical systems, which may be thought of as being aboard a ship or within a production facility. The measures assigned to these systems include project funding for upgrades against demand, system certifications achieved against those required, preventive maintenance to corrective maintenance ratios, and material support personnel capacity against that required for supporting respective systems. The resultant scorecard is viewed as complimentary to the traditional balanced scorecard for program and performance management. The benefits from these scorecards are realized through the quantified state of operational capabilities or outcomes. These capabilities are also weighted in terms of priority for each distinct system measure and aggregated and visualized in terms of overall state of capabilities achieved. This study proposes the use of interactive controls within the scorecard as a technique to enhance development of alternative solutions in decision making. These interactive controls include those for assigning capability priorities and for adjusting system performance measures, thus providing for what-if scenarios and options in strategic decision-making. In this holistic approach to capability management, several cross functional processes were highlighted as relevant amongst the different management disciplines. In terms of assessing an organization’s ability to adopt this approach, consideration was given to the P3M3 management maturity model.

Keywords: Outcome based management, performance management, lifecycle costs, balanced scorecard.

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Authors: F. Urem, K. Fertalj, I. Livaja

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Constant upgrading of Enterprise Resource Planning (ERP) systems is necessary, but can cause new defects. This paper attempts to model the likelihood of defects after completed upgrades with Weibull defect probability density function (PDF). A case study is presented analyzing data of recorded defects obtained for one ERP subsystem. The trends are observed for the value of the parameters relevant to the proposed statistical Weibull distribution for a given one year period. As a result, the ability to predict the appearance of defects after the next upgrade is described.

Keywords: ERP, upgrade, reliability, Weibull model

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Authors: Alireza Noorpoor, Akbar Abvabi, Mehdi Saeed Kiasat

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Development, calibration and validation of a threedimensional model of the Legform impactor for pedestrian crash with bumper are presented. Lower limb injury is becoming an increasingly important concern in vehicle safety for both occupants and pedestrians. In order to prevent lower extremity injuries to a pedestrian when struck by a car, it is important to elucidate the loadings from car front structures on the lower extremities and the injury mechanism caused by these loadings. An impact test procedure with a legform addressing lower limb injuries in car pedestrian accidents has been proposed by EEVC/WG17. In this study a modified legform impactor is introduced and validated against EEVC/WG17 criteria. The finite element model of this legform is developed using LS-DYNA software. Total mass of legform impactor is 13.4 kg.Technical specifications including the mass and location of the center of gravity and moment of inertia about a horizontal axis through the respective centre of gravity in femur and tibia are determined. The obtained results of legform impactor static and dynamic tests are as specified in the EEVC/WG17.

Keywords: Legform impactor, Pedestrian safety, Finite element model, Knee joint, EEVC/WG17.

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Authors: Fariba Azizi, Firoozeh Haghighi, Viliam Makis

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In this paper, we propose a method to model the relationship between failure time and degradation for a simple step stress test where underlying degradation path is linear and different causes of failure are possible. It is assumed that the intensity function depends only on the degradation value. No assumptions are made about the distribution of the failure times. A simple step-stress test is used to shorten failure time of products and a tampered failure rate (TFR) model is proposed to describe the effect of the changing stress on the intensities. We assume that some of the products that fail during the test have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the maximum likelihood estimates (MLEs) of the model parameters are obtained through an expectation-maximization (EM) algorithm by treating the causes of failure as missing values. The effect of incomplete information on the estimation of parameters is studied through a Monte-Carlo simulation. Finally, a real example is analyzed to illustrate the application of the proposed methods.

Keywords: Expectation-maximization (EM) algorithm, cause of failure, intensity, linear degradation path, masked data, reliability function.

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Authors: J. X. Dong, C. J. An, Z. Chen, E. H. Owens, M. C. Boufadel, E. Taylor, K. Lee

Abstract:

Shorelines are vulnerable to significant environmental impacts from oil spills. Stranded oil can cause potential short- to long-term detrimental effects along beaches that include injuries to ecosystem, socio-economic and cultural resources. In this study, a three-dimensional (3D) numerical modeling approach is developed to evaluate the fate and transport of spilled oil for hypothetical oiled shoreline cases under various combinations of beach geomorphology and environmental conditions. The developed model estimates the spatial and temporal distribution of spilled oil for the various test conditions, using the finite volume method and considering the physical transport (dispersion and advection), sinks, and sorption processes. The model includes a user-friendly interface for data input on variables such as beach properties, environmental conditions, and physical-chemical properties of spilled oil. An experimental meso-scale tank design was used to test the developed model for dissolved petroleum hydrocarbon within shorelines. The simulated results for effects of different sediment substrates, oil types, and shoreline features for the transport of spilled oil are comparable to that obtained with a commercially available model. Results show that the properties of substrates and the oil removal by shoreline effects have significant impacts on oil transport in the beach area. Sensitivity analysis, through the application of the one-step-at-a-time method (OAT), for the 3D model identified hydraulic conductivity as the most sensitive parameter. The 3D numerical model allows users to examine the behavior of oil on and within beaches, assess potential environmental impacts, and provide technical support for decisions related to shoreline clean-up operations.

Keywords: dissolved petroleum hydrocarbons, environmental multimedia model, finite volume method, FVM, sensitivity analysis, total petroleum hydrocarbons, TPH

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Authors: V. Churkin, M. Lopatin

Abstract:

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

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

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