Search results for: real–time information

Authors: Anass Rahouti, Guillaume Salze, Ruggiero Lovreglio, Sélim Datoussaïd

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In healthcare facilities, training the staff for firefighting and evacuation in real buildings is very challenging due to the presence of a vulnerable population in such an environment. In a standard environment, traditional approaches, such as fire drills, are often used to train the occupants and provide them with information about fire safety procedures. However, those traditional approaches may be inappropriate for a vulnerable population and can be inefficient from an educational viewpoint as it is impossible to expose the occupants to scenarios similar to a real emergency. Immersive serious games could be used as an alternative to traditional approaches to overcome their limitations. Serious games are already being used in different safety domains such as fires, earthquakes and terror attacks for several building types (e.g., office buildings, train stations, tunnels, etc.). In this study, we developed an immersive serious game to improve the fire safety skills of staff in healthcare facilities. An accurate representation of the healthcare environment was built in Unity3D by including visual and audio stimuli inspired from those employed in commercial action games. The serious game is organised in three levels. In each of them, the trainee is presented with a specific fire emergency and s/he can perform protective actions (e.g., firefighting, helping non-ambulant occupants, etc.) or s/he can ignore the opportunity for action and continue the evacuation. In this paper, we describe all the steps required to develop such a prototype, as well as the key questions that need to be answered, to develop a serious game for firefighting and evacuation in healthcare facilities.

Keywords: Fire Safety, healthcare, serious game, training.

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Authors: Doraid Dalalah

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A topologically oriented neural network is very efficient for real-time path planning for a mobile robot in changing environments. When using a recurrent neural network for this purpose and with the combination of the partial differential equation of heat transfer and the distributed potential concept of the network, the problem of obstacle avoidance of trajectory planning for a moving robot can be efficiently solved. The related dimensional network represents the state variables and the topology of the robot's working space. In this paper two approaches to problem solution are proposed. The first approach relies on the potential distribution of attraction distributed around the moving target, acting as a unique local extreme in the net, with the gradient of the state variables directing the current flow toward the source of the potential heat. The second approach considers two attractive and repulsive potential sources to decrease the time of potential distribution. Computer simulations have been carried out to interrogate the performance of the proposed approaches.

Keywords: Mobile robot, Path Planning, Mesh, Potential field.

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Authors: Amir Azizi, Amir Yazid b. Ali, Loh Wei Ping, Mohsen Mohammadzadeh

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Uncertainties of a serial production line affect on the production throughput. The uncertainties cannot be prevented in a real production line. However the uncertain conditions can be controlled by a robust prediction model. Thus, a hybrid model including autoregressive integrated moving average (ARIMA) and multiple polynomial regression, is proposed to model the nonlinear relationship of production uncertainties with throughput. The uncertainties under consideration of this study are demand, breaktime, scrap, and lead-time. The nonlinear relationship of production uncertainties with throughput are examined in the form of quadratic and cubic regression models, where the adjusted R-squared for quadratic and cubic regressions was 98.3% and 98.2%. We optimized the multiple quadratic regression (MQR) by considering the time series trend of the uncertainties using ARIMA model. Finally the hybrid model of ARIMA and MQR is formulated by better adjusted R-squared, which is 98.9%.

Keywords: ARIMA, multiple polynomial regression, production throughput, uncertainties

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Authors: Adam Niewiadomski

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The research objective of the project and article “The Linguistic and Legal Term "Real Estate" in the Polish Law and Literature” is characteristic of legal regulations in contemporary countries is the abundance of legal definitions, which are, in fact, formulated separately for the needs of each legal act. This situation does not create favourable conditions for comprehensibility and effectiveness of the law created. The definition mess leads to various interpretations of the same legal circumstances and does not support normal business trading. It needs to be pointed out that using numerous references within a legal act and to other legal acts results in new legal definitions being created for the needs of a given decision by the authority which issues the decision in question. Such interpretation freedom may lead to the law being misused, not to mention being instrumentalised.

Keywords: Real estate, linguistic, legal term.

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Authors: Kamal Amarouche, Houda Benbrahim, Ismail Kassou

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Nowadays, e-commerce shopping websites have experienced noticeable growth. These websites have gained consumers’ trust. After purchasing a product, many consumers share comments where opinions are usually embedded about the given product. Research on the automatic management of opinions that gives suggestions to potential consumers and portrays an image of the product to manufactures has been growing recently. After launching the product in the market, the reviews generated around it do not usually contain helpful information or generic opinions about this product (e.g. telephone: great phone...); in the sense that the product is still in the launching phase in the market. Within time, the product becomes old. Therefore, consumers perceive the advantages/ disadvantages about each specific product feature. Therefore, they will generate comments that contain their sentiments about these features. In this paper, we present an unsupervised method to extract different product features hidden in the opinions which influence its purchase, and that combines Time Weighting (TW) which depends on the time opinions were expressed with Term Frequency-Inverse Document Frequency (TF-IDF). We conduct several experiments using two different datasets about cell phones and hotels. The results show the effectiveness of our automatic feature extraction, as well as its domain independent characteristic.

Keywords: Opinion mining, product feature extraction, sentiment analysis, SentiWordNet.

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Authors: Dimitris Balios, Stefanos Tantos

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Economic growth and social evolution are connected to trust relationships in a society. The quality of the accounting information, the tax information system and the tax audit mechanism evolve multiple benefits in an economy. Tax evasion, the illegal practice where people and companies do not pay taxes, is a crime because of the negative effect in economy and society. In this paper, we describe a theoretical framework on the characteristics of a fair and efficient tax auditing information system which could be a tool against tax evasion, a tool for an economy to grow, especially in countries that face fluctuations in economic activity. We conclude that a fair and efficient tax auditing information system increases the reliability of tax administration, improves taxpayers’ tax compliance and causes a developmental trajectory for the economy.

Keywords: Auditing information system, auditing mechanism, tax evasion, taxation, quality of accounting information.

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Authors: Silvia Santano Guillén, Luigi Lo Iacono, Christian Meder

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One of the main aims of current social robotic research is to improve the robots’ abilities to interact with humans. In order to achieve an interaction similar to that among humans, robots should be able to communicate in an intuitive and natural way and appropriately interpret human affects during social interactions. Similarly to how humans are able to recognize emotions in other humans, machines are capable of extracting information from the various ways humans convey emotions—including facial expression, speech, gesture or text—and using this information for improved human computer interaction. This can be described as Affective Computing, an interdisciplinary field that expands into otherwise unrelated fields like psychology and cognitive science and involves the research and development of systems that can recognize and interpret human affects. To leverage these emotional capabilities by embedding them in humanoid robots is the foundation of the concept Affective Robots, which has the objective of making robots capable of sensing the user’s current mood and personality traits and adapt their behavior in the most appropriate manner based on that. In this paper, the emotion recognition capabilities of the humanoid robot Pepper are experimentally explored, based on the facial expressions for the so-called basic emotions, as well as how it performs in contrast to other state-of-the-art approaches with both expression databases compiled in academic environments and real subjects showing posed expressions as well as spontaneous emotional reactions. The experiments’ results show that the detection accuracy amongst the evaluated approaches differs substantially. The introduced experiments offer a general structure and approach for conducting such experimental evaluations. The paper further suggests that the most meaningful results are obtained by conducting experiments with real subjects expressing the emotions as spontaneous reactions.

Keywords: Affective computing, emotion recognition, humanoid robot, Human-Robot-Interaction (HRI), social robots.

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Authors: Usha Sridhar, Sridhar Mandyam

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We propose a multi-agent based utilitarian approach to model and understand information flows in social networks that lead to Pareto optimal informational exchanges. We model the individual expected utility function of the agents to reflect the net value of information received. We show how this model, adapted from a theorem by Karl Borch dealing with an actuarial Risk Exchange concept in the Insurance industry, can be used for social network analysis. We develop a utilitarian framework that allows us to interpret Pareto optimal exchanges of value as potential information flows, while achieving a maximization of a sum of expected utilities of information of the group of agents. We examine some interesting conditions on the utility function under which the flows are optimal. We illustrate the promise of this new approach to attach economic value to information in networks with a synthetic example.

Keywords: Borch's Theorem , Economic value of information, Information Exchange, Pareto Optimal Solution, Social Networks, Utility Functions

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Authors: L. Mirtskhulava, M. Khunjgurua, N. Lomineishvili, K. Bakuria

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Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: Exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability.

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Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

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Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: Multiclass classification, convolution neural network, OpenCV, Data Augmentation.

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Authors: Simon Huston, Ebraheim Lahbash, Ali Parsa

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The development of the United Arab Emirates (UAE) into a regional trade, tourism, finance and logistics hub has transformed its real estate markets. However, speculative activity and price volatility remain concerns. UAE residential market values (MV) are exposed to fluctuations in capital flows and migration which, in turn, are affected by geopolitical uncertainty, oil price volatility and global investment market sentiment. Internally, a complex interplay between administrative boundaries, land tenure, building quality and evolving location characteristics fragments UAE residential property markets. In short, the UAE Residential Valuation System (UAE-RVS) confronts multiple challenges to collect, filter and analyze relevant information in complex and dynamic spatial and capital markets. A robust (RVS) can mitigate the risk of unhelpful volatility, speculative excess or investment mistakes. The research outlines the institutional, ontological, dynamic and epistemological issues at play. We highlight the importance of system capabilities, valuation standard salience and stakeholders trust.

Keywords: Valuation, property rights, information, institutions, trust, salience.

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Authors: Linda, Sau-ling Lai

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This paper provides new ways to explore the old problem of failure of information systems development in an organisation. Based on the theory of cognitive dissonance, information systems (IS) failure is defined as a gap between what the users expect from an information system and how well these expectations are met by the perceived performance of the delivered system. Bridging the expectation-perception gap requires that IS professionals make a radical change from being the proprietor of information systems and products to being service providers. In order to deliver systems and services that IS users perceive as valuable, IS people must become expert in determining and assessing users- expectations and perceptions. It is also suggested that the IS community, in general, has given relatively little attention to the front-end process of requirements specification for IS development. There is a simplistic belief that requirements are obtainable from users, they are then translatable into a formal specification. The process of information needs analysis is problematic and worthy of investigation.

Keywords: Information Systems Development, Cognitive Dissonance, Expectation-Perception Gap, Requirements Analysis.

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Authors: Hamidreza Hoshyarmanesh, Hosein Madieh, Sanju Lama, Yaser Maddahi, Garnette R. Sutherland, Kourosh Zareinia

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This paper illustrates the concept of an algorithm to register specified markers on the neuroArm surgical manipulators, an image-guided MR-compatible tele-operated robot for microsurgery and stereotaxy. Two range-finding algorithms, namely time-of-flight and phase-shift, are evaluated for registration and supervisory control. The time-of-flight approach is implemented in a semi-field experiment to determine the precise position of a tiny retro-reflective moving object. The moving object simulates a surgical tool tip. The tool is a target that would be connected to the neuroArm end-effector during surgery inside the magnet bore of the MR imaging system. In order to apply flight approach, a 905-nm pulsed laser diode and an avalanche photodiode are utilized as the transmitter and receiver, respectively. For the experiment, a high frequency time to digital converter was designed using a field-programmable gate arrays. In the phase-shift approach, a continuous green laser beam with a wavelength of 530 nm was used as the transmitter. Results showed that a positioning error of 0.1 mm occurred when the scanner-target point distance was set in the range of 2.5 to 3 meters. The effectiveness of this non-contact approach exhibited that the method could be employed as an alternative for conventional mechanical registration arm. Furthermore, the approach is not limited by physical contact and extension of joint angles.

Keywords: 3D laser scanner, intraoperative MR imaging, neuroArm, real time registration, robot-assisted surgery, supervisory control.

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Authors: Rekha V. Dundur , M.V.Latte, S.Y. Kulkarni, M.K.Venkatesha

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The advent of multi-million gate Field Programmable Gate Arrays (FPGAs) with hardware support for multiplication opens an opportunity to recreate a significant portion of the front end of a human cochlea using this technology. In this paper we describe the implementation of the cochlear filter and show that it is entirely suited to a single device XC3S500 FPGA implementation .The filter gave a good fit to real time data with efficiency of hardware usage.

Keywords: Cochlea, FPGA, IIR (Infinite Impulse Response), Multiplier.

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Authors: Lihui Ma, Kunlun Xin, Suiqing Liu

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Modern managements of water distribution system (WDS) need water quality models that are able to accurately predict the dynamics of water quality variations within the distribution system environment. Before water quality models can be applied to solve system problems, they should be calibrated. Although former researchers use GA solver to calibrate relative parameters, it is difficult to apply on the large-scale or medium-scale real system for long computational time. In this paper a new method is designed which combines both macro and detailed model to optimize the water quality parameters. This new combinational algorithm uses radial basis function (RBF) metamodeling as a surrogate to be optimized for the purpose of decreasing the times of time-consuming water quality simulation and can realize rapidly the calibration of pipe wall reaction coefficients of chlorine model of large-scaled WDS. After two cases study this method is testified to be more efficient and promising, and deserve to generalize in the future.

Keywords: Metamodeling, model calibration, radial basisfunction, water distribution system, water quality model.

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Authors: L. C. Moreira, M. Kauffman

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This paper outlines the results of an experimental research on deploying an emerging augmented reality (AR) system for real-time task assistance (or work instructions) of highly customised and high-risk manual operations. The focus is on human operators’ training effectiveness and performance and the aim is to test if such technologies can support enhancing the knowledge retention levels and accuracy of task execution to improve health and safety (H&S). An AR enhanced assembly method is proposed and experimentally tested using a real industrial process as case study for electric vehicles’ (EV) battery module assembly. The experimental results revealed that the proposed method improved the training practices and performance through increases in the knowledge retention levels from 40% to 84%, and accuracy of task execution from 20% to 71%, when compared to the traditional paper-based method. The results of this research validate and demonstrate how emerging technologies are advancing the choice for manual, hybrid or fully automated processes by promoting the XR-assisted processes, and the connected worker (a vision for Industry 4 and 5.0), and supporting manufacturing become more resilient in times of constant market changes.

Keywords: Augmented reality, extended reality, connected worker, XR-assisted operator, manual assembly 4.0, industry 5.0, smart training, battery assembly.

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Authors: J. A. López, C.I. López, J.E. Olguín, C. Camargo, J. M. López

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The institutions seek to improve their performance and quality of service, so that their patients are satisfied. This research project aims, conduct a time study program in the area of gynecological surgery, to determine the current level of capacity and optimize the programming time in order to adequately respond to demand. The system is analyzed by waiting lines and uses the simulation using ARENA to evaluate proposals for improvement and optimization programming time each of the surgeries.

Keywords: Time study, waiting lines, reducing time, simulation.

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Authors: Abdullah Y. Al-Hossain

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This paper considers inference under progressive type II censoring with a compound Rayleigh failure time distribution. The maximum likelihood (ML), and Bayes methods are used for estimating the unknown parameters as well as some lifetime parameters, namely reliability and hazard functions. We obtained Bayes estimators using the conjugate priors for two shape and scale parameters. When the two parameters are unknown, the closed-form expressions of the Bayes estimators cannot be obtained. We use Lindley.s approximation to compute the Bayes estimates. Another Bayes estimator has been obtained based on continuous-discrete joint prior for the unknown parameters. An example with the real data is discussed to illustrate the proposed method. Finally, we made comparisons between these estimators and the maximum likelihood estimators using a Monte Carlo simulation study.

Keywords: Progressive type II censoring, compound Rayleigh failure time distribution, maximum likelihood estimation, Bayes estimation, Lindley's approximation method, Monte Carlo simulation.

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Authors: Siriwan Saksiriruthai

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This paper develops models to analyze the relationship between leisure time and wage change. Using Thailand-s Time Use Survey and Labor Force Survey data, the estimation of wage changes in response to leisure time change indicates that media receiving, personal care and social participation and volunteer activities are the ones that significantly raise hourly wages. Thus, the finding suggests the stimulation in time use for media access to enhance knowledge and productivity, personal care for attractiveness and healthiness in order to raise productivity, and social activities to develop connections for possible future opportunities including wage increase. These activities should be promoted for productive leisure time and for welfare improvement.

Keywords: Leisure, wage, time use, Thailand.

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Authors: Valeri A. Makarov, Nazareth P. Castellanos, Manuel G. Velarde

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In order to answer the general question: “What does a simple agent with a limited life-time require for constructing a useful representation of the environment?" we propose a robot platform including the simplest probabilistic sensory and motor layers. Then we use the platform as a test-bed for evaluation of the navigational capabilities of the robot with different “brains". We claim that a protocognitive behavior is not a consequence of highly sophisticated sensory–motor organs but instead emerges through an increment of the internal complexity and reutilization of the minimal sensory information. We show that the most fundamental robot element, the short-time memory, is essential in obstacle avoidance. However, in the simplest conditions of no obstacles the straightforward memoryless robot is usually superior. We also demonstrate how a low level action planning, involving essentially nonlinear dynamics, provides a considerable gain to the robot performance dynamically changing the robot strategy. Still, however, for very short life time the brainless robot is superior. Accordingly we suggest that small organisms (or agents) with short life-time does not require complex brains and even can benefit from simple brain-like (reflex) structures. To some extend this may mean that controlling blocks of modern robots are too complicated comparative to their life-time and mechanical abilities.

Keywords: Neural network, probabilistic control, robot navigation.

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Authors: Vinko Vidučić, Ljiljana Vidučić, Damir Boras

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The goals of the research include the determination of the characteristics of SMEs finance in Croatia, as well as the determination of indirect growth rates of the information model of the entrepreneurs` perception of business environment. The research results show that cost of finance and access to finance are most important constraining factor in setting up and running the business of small entrepreneurs in Croatia. Furthermore, small entrepreneurs in Croatia are significantly dissatisfied with the administrative barriers although relatively to a lesser extent than was the case in the pre crisis time. High collateral requirement represents the main characteristic of bank lending concerning SMEs followed by long credit elaboration process. Formulated information model has defined the individual impact of indirect growth rates of the remaining variables on the model’s specific variable.

Keywords: Business environment, information model, indirect growth rates, SME finance.

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Authors: T. Wuttipornpun, U. Wangrakdiskul, W. Songserm

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This paper aims to develop an algorithm of finite capacity material requirement planning (FCMRP) system for a multistage assembly flow shop. The developed FCMRP system has two main stages. The first stage is to allocate operations to the first and second priority work centers and also determine the sequence of the operations on each work center. The second stage is to determine the optimal start time of each operation by using a linear programming model. Real data from a factory is used to analyze and evaluate the effectiveness of the proposed FCMRP system and also to guarantee a practical solution to the user. There are five performance measures, namely, the total tardiness, the number of tardy orders, the total earliness, the number of early orders, and the average flow-time. The proposed FCMRP system offers an adjustable solution which is a compromised solution among the conflicting performance measures. The user can adjust the weight of each performance measure to obtain the desired performance. The result shows that the combination of FCMRP NP3 and EDD outperforms other combinations in term of overall performance index. The calculation time for the proposed FCMRP system is about 10 minutes which is practical for the planners of the factory.

Keywords: Material requirement planning, Finite capacity, Linear programming, Permutation, Application in industry.

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Authors: Celso A. G. Santos, Paula K. M. M. Freire

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The urban centers within northeastern Brazil are mainly influenced by the intense rainfalls, which can occur after long periods of drought, when flood events can be observed during such events. Thus, this paper aims to study the rainfall frequencies in such region through the wavelet transform. An application of wavelet analysis is done with long time series of the total monthly rainfall amount at the capital cities of northeastern Brazil. The main frequency components in the time series are studied by the global wavelet spectrum and the modulation in separated periodicity bands were done in order to extract additional information, e.g., the 8 and 16 months band was examined by an average of all scales, giving a measure of the average annual variance versus time, where the periods with low or high variance could be identified. The important increases were identified in the average variance for some periods, e.g. 1947 to 1952 at Teresina city, which can be considered as high wet periods. Although, the precipitation in those sites showed similar global wavelet spectra, the wavelet spectra revealed particular features. This study can be considered an important tool for time series analysis, which can help the studies concerning flood control, mainly when they are applied together with rainfall-runoff simulations.

Keywords: rainfall data, urban center, wavelet transform.

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Authors: Mohammadreza Amini, Omid Moradtalab, Ebadollah Zohrevandi

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In real-time networks a large number of application programs are relying on video data and heterogeneous data transmission techniques. The aim of this research is presenting a method for end-to-end vouch quality service in surface applicationlayer for sending video data in comparison form in wireless heterogeneous networks. This method tries to improve the video sending over the wireless heterogeneous networks with used techniques in surface layer, link and application. The offered method is showing a considerable improvement in quality observing by user. In addition to this, other specifications such as shortage of data load that had require to resending and limited the relation period length to require time for second data sending, help to be used the offered method in the wireless devices that have a limited energy. The presented method and the achieved improvement is simulated and presented in the NS-2 software.

Keywords: Heterogeneous wireless networks, adaptation mechanism, multi-level, Handoff, stop mechanism, graceful degrades, application layer.

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Authors: Bangbo Hu

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This paper discusses applications of a revolutionary information technology, Geographic Information Systems (GIS), in the field of the history of cartography by examples, including assessing accuracy of early maps, establishing a database of places and historical administrative units in history, integrating early maps in GIS or digital images, and analyzing social, political, and economic information related to production of early maps. GIS provides a new mean to evaluate the accuracy of early maps. Four basic steps using GIS for this type of study are discussed. In addition, several historical geographical information systems are introduced. These include China Historical Geographic Information Systems (CHGIS), the United States National Historical Geographic Information System (NHGIS), and the Great Britain Historical Geographical Information System. GIS also provides digital means to display and analyze the spatial information on the early maps or to layer them with modern spatial data. How GIS relational data structure may be used to analyze social, political, and economic information related to production of early maps is also discussed in this paper. Through discussion on these examples, this paper reveals value of GIS applications in this field.

Keywords: Cartography, GIS, history, maps.

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Authors: Laila Yasir Al-Harthy, Ali H. Al-Badi

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As an emerging business model, cloud computing has been initiated to satisfy the need of organizations and to push Information Technology as a utility. The shift to the cloud has changed the way Information Technology departments are managed traditionally and has raised many concerns for both, public and private sectors.

The purpose of this study is to investigate the possibility of cloud computing services replacing services provided traditionally by IT departments. Therefore, it aims to 1) explore whether organizations in Oman are ready to move to the cloud; 2) identify the deciding factors leading to the adoption or rejection of cloud computing services in Oman; and 3) provide two case studies, one for a successful Cloud provider and another for a successful adopter.

This paper is based on multiple research methods including conducting a set of interviews with cloud service providers and current cloud users in Oman; and collecting data using questionnaires from experts in the field and potential users of cloud services.

Despite the limitation of bandwidth capacity and Internet coverage offered in Oman that create a challenge in adopting the cloud, it was found that many information technology professionals are encouraged to move to the cloud while few are resistant to change.

The recent launch of a new Omani cloud service provider and the entrance of other international cloud service providers in the Omani market make this research extremely valuable as it aims to provide real-life experience as well as two case studies on the successful provision of cloud services and the successful adoption of these services.

Keywords: Cloud computing, cloud deployment models, cloud service models and deciding factors.

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Authors: R. Usubamatov, M. Z. Abdulmuin

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Automated production lines with so called 'hard structures' are widely used in manufacturing. Designers segmented these lines into sections by placing a buffer between the series of machine tools to increase productivity. In real production condition the capacity of a buffer system is limited and real production line can compensate only some part of the productivity losses of an automated line. The productivity of such production lines cannot be readily determined. This paper presents mathematical approach to solving the structure of section-based automated production lines by criterion of maximum productivity.

Keywords: optimization production line, productivity, sections

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Authors: Rohiza Ahmad, Rozana Kasbon, Eliza Mazmee Mazlan, Aliza Sarlan

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Due to the mobility of users, many information systems are now developed with the capability of supporting retrieval of information from both static and mobile users. Hence, the amount, content and format of the information retrieved will need to be tailored according to the device and the user who requested for it. Thus, this paper presents a framework for the design and implementation of such a system, which is to be developed for communicating final examination related information to the academic community at one university in Malaysia. The concept of personalization will be implemented in the system so that only highly relevant information will be delivered to the users. The personalization concept used will be based on user profiling as well as context. The system in its final state will be accessible through cell phones as well as intranet connected personal computers.

Keywords: System framework, personalization, informationcommunicating system, multi-device.

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Authors: Amir Azizi, Amir Yazid B. Ali, Loh Wei Ping

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Throughput is an important measure of performance of production system. Analyzing and modeling of production throughput is complex in today-s dynamic production systems due to uncertainties of production system. The main reasons are that uncertainties are materialized when the production line faces changes in setup time, machinery break down, lead time of manufacturing, and scraps. Besides, demand changes are fluctuating from time to time for each product type. These uncertainties affect the production performance. This paper proposes Bayesian inference for throughput modeling under five production uncertainties. Bayesian model utilized prior distributions related to previous information about the uncertainties where likelihood distributions are associated to the observed data. Gibbs sampling algorithm as the robust procedure of Monte Carlo Markov chain was employed for sampling unknown parameters and estimating the posterior mean of uncertainties. The Bayesian model was validated with respect to convergence and efficiency of its outputs. The results presented that the proposed Bayesian models were capable to predict the production throughput with accuracy of 98.3%.

Keywords: Bayesian inference, Uncertainty modeling, Monte Carlo Markov chain, Gibbs sampling, Production throughput

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Authors: So Jeong Nam, Seung Woo Lee, Jai-Kyung Lee

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With the globalized production and logistics environment, the need for reducing the product development interval and lead time, having a faster response to orders, conforming to quality standards, fair tracking, and boosting information exchanging activities with customers and partners, and coping with changes in the management environment, manufacturers are in dire need of an information management system in their manufacturing environments. There are lots of information systems that have been designed to manage the condition or operation of equipment in the field but existing systems have a decentralized architecture, which is not unified. Also, these systems cannot effectively handle the status data extraction process upon encountering a problem related to protocols or changes in the equipment or the setting. In this regard, this paper will introduce a system for processing and saving the status info of production equipment, which uses standard representation formats, to enable flexible responses to and support for variables in the field equipment. This system can be used for a variety of manufacturing and equipment settings and is capable of interacting with higher-tier systems such as MES.

Keywords: DAS, Equipment Status, Regular Expression

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