Search results for: real time data.

Authors: A. Amar, N. Burtebayev, Kerimkulov Zhambul, Sh. Hamada, N. Amangeldi

Abstract:

the elastic scattering of protons, deuterons and 3He on 6Li at different incident energies have been analyzed in the framework of the optical model using ECIS88 as well as SPI GENOA codes. The potential parameters were extracted in the phenomenological treatment of measured by us angular distributions and literature data. A good agreement between theoretical and experimental differential cross sections was obtained in whole angular range. Parameters for real part of potential have been also calculated microscopically with singleand double-folding model for the p and d, 3He scattering, respectively, using DFPOT code. For best agreement with experiment the normalization factor N for the potential depth is obtained in the range of 0.7-0.9.

Keywords: Elastic scattering, Esis88 Code single and doublefolding model, phenomenological, DWBA.

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Authors: Maha Jazouli

Abstract:

Suicide is one of the leading causes of death among prisoners, both in Canada and internationally. In recent years, rates of attempts of suicide and self-harm suicide have increased, with hangings being the most frequently used method. The objective of this article is to propose a method to automatically detect suicidal behaviors in real time. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Tests show that the proposed system gives satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: Suicide detection, Kinect Azure, RGB-D camera, SVM, gesture recognition.

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Authors: Takahiro Nishigaki, Katsumi Nitta, Takashi Onoda

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In this paper, we present a method of applying Independent Topic Analysis (ITA) to increasing the number of document data. The number of document data has been increasing since the spread of the Internet. ITA was presented as one method to analyze the document data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis (ICA). ICA is a technique in the signal processing; however, it is difficult to apply the ITA to increasing number of document data. Because ITA must use the all document data so temporal and spatial cost is very high. Therefore, we present Incremental ITA which extracts the independent topics from increasing number of document data. Incremental ITA is a method of updating the independent topics when the document data is added after extracted the independent topics from a just previous the data. In addition, Incremental ITA updates the independent topics when the document data is added. And we show the result applied Incremental ITA to benchmark datasets.

Keywords: Text mining, topic extraction, independent, incremental, independent component analysis.

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Authors: Ruibiao J. Guo, Brad Cain, Pierre Meunier

Abstract:

The Integrated Performance Modelling Environment (IPME) is a powerful simulation engine for task simulation and performance analysis. However, it has no high level cognition such as memory and reasoning for complex simulation. This article introduces a knowledge representation and reasoning scheme that can accommodate uncertainty in simulations of military personnel with IPME. This approach demonstrates how advanced reasoning models that support similarity-based associative process, rule-based abstract process, multiple reasoning methods and real-time interaction can be integrated with conventional task network modelling to provide greater functionality and flexibility when modelling operator performance.

Keywords: Computer-Generated Forces, Human Behaviour Representation, IPME, Modelling and Simulation, Uncertainty Reasoning

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Authors: Cheon Sik Min, Hyeong Wook Song, Sook Yeon Shim, Hoon Chang

Abstract:

The purpose of this study was to analyze the correlation between permitted building areas and housing distribution ratios and their fluctuation, and test a distribution model during 3 successive governments in 5 cities including Bucheon in reference to the time series administrative data, and thereby, interpret the results of the analysis in association with the policies pursued by the successive governments to examine the structural fluctuation of permitted building areas and housing distribution ratios. In order to analyze the fluctuation of permitted building areas and housing distribution ratios during 3 successive governments and examine the cycles of the time series data, the spectral analysis was performed, and in order to analyze the correlation between permitted building areas and housing distribution ratios, the tabulation was performed to describe the correlations statistically, and in order to explain about differences of fluctuation distribution of permitted building areas and housing distribution ratios among 3 governments, the goodness of fit test was conducted.

Keywords: The Permitted Building Areas, Housing Distribution Ratios, the Structural Fluctuation.

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Authors: Ritu Ahlawat

Abstract:

Among all geo-hydrological relationships, rainfallrunoff relationship is of utmost importance in any hydrological investigation and water resource planning. Spatial variation, lag time involved in obtaining areal estimates for the basin as a whole can affect the parameterization in design stage as well as in planning stage. In conventional hydrological processing of data, spatial aspect is either ignored or interpolated at sub-basin level. Temporal variation when analysed for different stages can provide clues for its spatial effectiveness. The interplay of space-time variation at pixel level can provide better understanding of basin parameters. Sustenance of design structures for different return periods and their spatial auto-correlations should be studied at different geographical scales for better management and planning of water resources. In order to understand the relative effect of spatio-temporal variation in hydrological data network, a detailed geo-hydrological analysis of Betwa river catchment falling in Lower Yamuna Basin is presented in this paper. Moreover, the exact estimates about the availability of water in the Betwa river catchment, especially in the wake of recent Betwa-Ken linkage project, need thorough scientific investigation for better planning. Therefore, an attempt in this direction is made here to analyse the existing hydrological and meteorological data with the help of SPSS, GIS and MS-EXCEL software. A comparison of spatial and temporal correlations at subcatchment level in case of upper Betwa reaches has been made to demonstrate the representativeness of rain gauges. First, flows at different locations are used to derive correlation and regression coefficients. Then, long-term normal water yield estimates based on pixel-wise regression coefficients of rainfall-runoff relationship have been mapped. The areal values obtained from these maps can definitely improve upon estimates based on point-based extrapolations or areal interpolations.

Keywords: Catchment's runoff estimates, influence area regional regression coefficients, runoff yield series,

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Authors: Christopher Paterson, Richard Curry, Alan Purvis, Simon Johnson

Abstract:

Emerging Bio-engineering fields such as Brain Computer Interfaces, neuroprothesis devices and modeling and simulation of neural networks have led to increased research activity in algorithms for the detection, isolation and classification of Action Potentials (AP) from noisy data trains. Current techniques in the field of 'unsupervised no-prior knowledge' biosignal processing include energy operators, wavelet detection and adaptive thresholding. These tend to bias towards larger AP waveforms, AP may be missed due to deviations in spike shape and frequency and correlated noise spectrums can cause false detection. Also, such algorithms tend to suffer from large computational expense. A new signal detection technique based upon the ideas of phasespace diagrams and trajectories is proposed based upon the use of a delayed copy of the AP to highlight discontinuities relative to background noise. This idea has been used to create algorithms that are computationally inexpensive and address the above problems. Distinct AP have been picked out and manually classified from real physiological data recorded from a cockroach. To facilitate testing of the new technique, an Auto Regressive Moving Average (ARMA) noise model has been constructed bases upon background noise of the recordings. Along with the AP classification means this model enables generation of realistic neuronal data sets at arbitrary signal to noise ratio (SNR).

Keywords: Action potential detection, Low SNR, Phase spacediagrams/trajectories, Unsupervised/no-prior knowledge.

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Authors: Bernat-Carles Serdà Ferrer, Arantza Del Valle Gómez

Abstract:

The Quality of Life (QoL) paradigm is multidimensional, dynamic and modular and its definition differs across the cancer continuum. The challenge in the interpretation of QoL data in clinical research is that QoL is influenced by psychological phenomena such as adaptation to illness. This research aims to obtain a valid and sensitive assessment of QoL change over the continuum disease, and to evaluate a rehabilitation programme aimed at inverting the observed decrease in QoL when patients return to daily living activities. The sample comprised 66 men. Patients were first assessed to establish a baseline (P1-diagnosis). This was followed by a post-test (P2-discharge) and a then-test measurement (P3-retrospective evaluation) and after returning home patients were randomized in experimental and control groups. The experimental group attended a rehabilitation programme over 24 weeks (P4). Results show that from baseline to post-test, QoL decreased significantly. The recalibration then-test confirmed a low QoL in all periods evaluated. Significant differences between the experimental and control groups prove the positive effect of the Exercise Rehabilitation Programme (ERP) on QoL. Understanding the real dynamic of QoL over time would help to adapt rehabilitation programmes by improving sensitivity and efficacy and provide professionals with a more accurate perception of the impact of treatment and side effects on patients’ QoL. Our results underline the importance of changing the approach adopted by health professionals towards one of watchful waiting on patients’ QoL until their complete recovery in daily life.

Keywords: Prostate cancer, quality of life, rehabilitation programme, response shift.

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Authors: J. P. Dubois

Abstract:

This paper reports the feasibility of the ARMA model to describe a bursty video source transmitting over a AAL5 ATM link (VBR traffic). The traffic represents the activity of the action movie "Lethal Weapon 3" transmitted over the ATM network using the Fore System AVA-200 ATM video codec with a peak rate of 100 Mbps and a frame rate of 25. The model parameters were estimated for a single video source and independently multiplexed video sources. It was found that the model ARMA (2, 4) is well-suited for the real data in terms of average rate traffic profile, probability density function, autocorrelation function, burstiness measure, and the pole-zero distribution of the filter model.

Keywords: ARMA, ATM networks, burstiness, multimediatraffic, VBR video.

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Authors: Yendiyarov Sergei, Zobnin Boris, Petrushenko Sergei

Abstract:

Usually, the solid-fuel flow of an iron ore sinter plant consists of different types of the solid-fuels, which differ from each other. Information about the composition of the solid-fuel flow usually comes every 8-24 hours. It can be clearly seen that this information cannot be used to control the sintering process in real time. Due to this, we propose an expert system which uses indirect measurements from the process in order to obtain the composition of the solid-fuel flow by solving an optimization task. Then this information can be used to control the sintering process. The proposed technique can be successfully used to improve sinter quality and reduce the amount of solid-fuel used by the process.

Keywords: sintering process, particle swarm optimization, optimal control, expert system, solid-fuel

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Authors: Kanittha Kanokkanjana, Savitri Garivait

Abstract:

This study focuses on emission of black carbon (BC) from field open burning of corn residues. Real-time BC concentration was measured by Micro Aethalometer from field burning and simulated open burning in a chamber (SOC) experiments. The average concentration of BC was 1.18±0.47 mg/m3 in the field and 0.89±0.63 mg/m3 in the SOC. The deduced emission factor from field experiments was 0.50±0.20 gBC/kgdm, and 0.56±0.33 gBC/kgdm from SOC experiment, which are in good agreement with other studies. In 2007, the total burned area of corn crop was 8,000 ha, resulting in an emission load of BC 20 ton corresponding to 44.5 million kg CO2 equivalent. Therefore, the control of open burning in corn field represents a significant global warming reduction option.

Keywords: Black carbon, corn field residues, global warming, mitigation option

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Authors: H. Baazaoui Zghal, S. Faiz, H. Ben Ghezala

Abstract:

Data mining is an extraordinarily demanding field referring to extraction of implicit knowledge and relationships, which are not explicitly stored in databases. A wide variety of methods of data mining have been introduced (classification, characterization, generalization...). Each one of these methods includes more than algorithm. A system of data mining implies different user categories,, which mean that the user-s behavior must be a component of the system. The problem at this level is to know which algorithm of which method to employ for an exploratory end, which one for a decisional end, and how can they collaborate and communicate. Agent paradigm presents a new way of conception and realizing of data mining system. The purpose is to combine different algorithms of data mining to prepare elements for decision-makers, benefiting from the possibilities offered by the multi-agent systems. In this paper the agent framework for data mining is introduced, and its overall architecture and functionality are presented. The validation is made on spatial data. Principal results will be presented.

Keywords: Databases, data mining, multi-agent, spatial datamart.

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Authors: Ivan Živanović, Žužana Vaštag, Senka Popović, Ljiljana Popović, Draginja Peričin

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The present work represents an investigation of the hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein isolate (PuOC PI) by pepsin. To examine the effectiveness and suitability of pepsin towards PuOC PI the kinetic parameters for pepsin on PuOC PI were determined and then, the hydrolysis process was studied using Response Surface Methodology (RSM). The hydrolysis was carried out at temperature of 30°C and pH 3.00. Time and initial enzyme/substrate ratio (E/S) at three levels were selected as the independent parameters. The degree of hydrolysis, DH, was mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3 mA/mg proteins. Since the proposed second-order polynomial model showed good fit with the experimental data (R2 = 0.9822), the obtained mathematical model could be used for monitoring the hydrolysis of PuOC PI by pepsin, under studied experimental conditions, varying the time and initial E/S. To achieve the highest value of DH (39.13 %), the obtained optimum conditions for time and initial E/S were 30 min and 1.024 mA/mg proteins.

Keywords: Enzymatic hydrolysis, Pepsin, Pumpkin (CucurbitaPepo L.) oil cake protein isolate, Response surface methodology.

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Authors: Jian-hua Yeh, Shi-yi Kuo

Abstract:

This paper discusses the classification process for medical data. In this paper, we use the data from ACM KDDCup 2008 to demonstrate our classification process based on latent topic discovery. In this data set, the target set and outliers are quite different in their nature: target set is only 0.6% size in total, while the outliers consist of 99.4% of the data set. We use this data set as an example to show how we dealt with this extremely biased data set with latent topic discovery and noise reduction techniques. Our experiment faces two major challenge: (1) extremely distributed outliers, and (2) positive samples are far smaller than negative ones. We try to propose a suitable process flow to deal with these issues and get a best AUC result of 0.98.

Keywords: classification, latent topics, outlier adjustment, feature scaling

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Authors: Tim Wollert, Fabian Behrendt

Abstract:

Value Stream Management (VSM) is a widely used methodology in the context of Lean Management for improving end-to-end material and information flows from a supplier to a customer from a company’s perspective. Whereas the design principles, e.g. Pull, value-adding, customer-orientation and further ones are still valid against the background of an increasing digitalized and dynamic environment, the methodology itself for mapping a value stream is characterized as time- and resource-intensive due to the high degree of manual activities. The digitalization of processes in the context of Industry 4.0 enables new opportunities to reduce these manual efforts and make the VSM approach more agile. The paper at hand aims at providing a modular data and calculation framework, utilizing the available business data, provided by information and communication technologies for automizing the value stream mapping process with focus on the manufacturing process.

Keywords: Industry 4.0, lean management 4.0, value stream management 4.0, value stream mapping.

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Authors: F. Raja, M.Rahgozar, N. Razavi, M. Siadaty

Abstract:

Main Memory Database systems (MMDB) store their data in main physical memory and provide very high-speed access. Conventional database systems are optimized for the particular characteristics of disk storage mechanisms. Memory resident systems, on the other hand, use different optimizations to structure and organize data, as well as to make it reliable. This paper provides a brief overview on MMDBs and one of the memory resident systems named FastDB and compares the processing time of this system with a typical disc resident database based on the results of the implementation of TPC benchmarks environment on both.

Keywords: Disk-Resident Database, FastDB, Main MemoryDatabase.

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Authors: Xinhui Wang, Xiuyong Ding

Abstract:

This paper addresses the controller synthesis problem of discrete-time switched positive systems with bounded time-varying delays. Based on the switched copositive Lyapunov function approach, some necessary and sufficient conditions for the existence of state-feedback controller are presented as a set of linear programming and linear matrix inequality problems, hence easy to be verified. Another advantage is that the state-feedback law is independent on time-varying delays and initial conditions. A numerical example is provided to illustrate the effectiveness and feasibility of the developed controller.

Keywords: Switched copositive Lyapunov functions, positive linear systems, switched systems, time-varying delays, stabilization.

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Authors: Nouha Mhimdi, Wahiba Ben Abdessalem Karaa, Henda Ben Ghezala

Abstract:

Many methods are used to collect data like questionnaires, surveys, focus group interviews. Or the collection of poor-quality data resulting, for example, from poorly designed questionnaires, the absence of good translators or interpreters, and the incorrect recording of data allow conclusions to be drawn that are not supported by the data or to focus only on the average effect of the program or policy. There are several solutions to avoid or minimize the most frequent errors, including obtaining expert advice on the design or adaptation of data collection instruments; or use technologies allowing better "anonymity" in the responses. In this context, and to overcome the aforementioned problems, we suggest in this paper an approach to achieve the collection of relevant data, by carrying out a large-scale questionnaire-based survey. We have been able to collect good quality, consistent and practical data on hospital emergencies to improve emergency services in hospitals, especially in the case of epidemics or pandemics.

Keywords: Data collection, survey, database, data analysis, hospital emergencies.

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Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti

Abstract:

Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.

Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety.

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Authors: Devanjan Bhattacharya, Jitka Komarkova

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The research describes the implementation of a novel and stand-alone system for dynamic hazard warning. The system uses all existing infrastructure already in place like mobile networks, a laptop/PC and the small installation software. The geospatial dataset are the maps of a region which are again frugal. Hence there is no need to invest and it reaches everyone with a mobile. A novel architecture of hazard assessment and warning introduced where major technologies in ICT interfaced to give a unique WebGIS based dynamic real time geohazard warning communication system. A never before architecture introduced for integrating WebGIS with telecommunication technology. Existing technologies interfaced in a novel architectural design to address a neglected domain in a way never done before – through dynamically updatable WebGIS based warning communication. The work publishes new architecture and novelty in addressing hazard warning techniques in sustainable way and user friendly manner. Coupling of hazard zonation and hazard warning procedures into a single system has been shown. Generalized architecture for deciphering a range of geo-hazards has been developed. Hence the developmental work presented here can be summarized as the development of internet-SMS based automated geo-hazard warning communication system; integrating a warning communication system with a hazard evaluation system; interfacing different open-source technologies towards design and development of a warning system; modularization of different technologies towards development of a warning communication system; automated data creation, transformation and dissemination over different interfaces. The architecture of the developed warning system has been functionally automated as well as generalized enough that can be used for any hazard and setup requirement has been kept to a minimum.

Keywords: Geospatial, web-based GIS, geohazard, warning system.

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Authors: Hang Yu

Abstract:

The visualization of geographic information on mobile devices has become popular as the widespread use of mobile Internet. The mobility of these devices brings about much convenience to people-s life. By the add-on location-based services of the devices, people can have an access to timely information relevant to their tasks. However, visual analysis of geographic data on mobile devices presents several challenges due to the small display and restricted computing resources. These limitations on the screen size and resources may impair the usability aspects of the visualization applications. In this paper, a variable-scale visualization method is proposed to handle the challenge of small mobile display. By merging multiple scales of information into a single image, the viewer is able to focus on the interesting region, while having a good grasp of the surrounding context. This is essentially visualizing the map through a fisheye lens. However, the fisheye lens induces undesirable geometric distortion in the peripheral, which renders the information meaningless. The proposed solution is to apply map generalization that removes excessive information around the peripheral and an automatic smoothing process to correct the distortion while keeping the local topology consistent. The proposed method is applied on both artificial and real geographical data for evaluation.

Keywords: Map simplification, visualization, mobile devices.

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Authors: Mengzhuo Luo, Shouming Zhong

Abstract:

This paper investigates the problem of exponential stability for a class of uncertain discrete-time stochastic neural network with time-varying delays. By constructing a suitable Lyapunov-Krasovskii functional, combining the stochastic stability theory, the free-weighting matrix method, a delay-dependent exponential stability criteria is obtained in term of LMIs. Compared with some previous results, the new conditions obtain in this paper are less conservative. Finally, two numerical examples are exploited to show the usefulness of the results derived.

Keywords: Delay-dependent stability, Neural networks, Time varying delay, Linear matrix inequality (LMI).

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Authors: Insung Jung, Gi-Nam Wang

Abstract:

The objective of this paper is to a design of pattern classification model based on the back-propagation (BP) algorithm for decision support system. Standard BP model has done full connection of each node in the layers from input to output layers. Therefore, it takes a lot of computing time and iteration computing for good performance and less accepted error rate when we are doing some pattern generation or training the network. However, this model is using exclusive connection in between hidden layer nodes and output nodes. The advantage of this model is less number of iteration and better performance compare with standard back-propagation model. We simulated some cases of classification data and different setting of network factors (e.g. hidden layer number and nodes, number of classification and iteration). During our simulation, we found that most of simulations cases were satisfied by BP based using exclusive connection network model compared to standard BP. We expect that this algorithm can be available to identification of user face, analysis of data, mapping data in between environment data and information.

Keywords: Neural network, Back-propagation, classification.

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Authors: J. D. D. Daniel, K. N. Goh, S. M. Yusop

Abstract:

Trends in business intelligence, e-commerce and remote access make it necessary and practical to store data in different ways on multiple systems with different operating systems. As business evolve and grow, they require efficient computerized solution to perform data update and to access data from diverse enterprise business applications. The objective of this paper is to demonstrate the capability of DTS [1] as a database solution for automatic data transfer and update in solving business problem. This DTS package is developed for the sales of variety of plants and eventually expanded into commercial supply and landscaping business. Dimension data modeling is used in DTS package to extract, transform and load data from heterogeneous database systems such as MySQL, Microsoft Access and Oracle that consolidates into a Data Mart residing in SQL Server. Hence, the data transfer from various databases is scheduled to run automatically every quarter of the year to review the efficient sales analysis. Therefore, DTS is absolutely an attractive solution for automatic data transfer and update which meeting today-s business needs.

Keywords: Data Transformation Services (DTS), ObjectLinking and Embedding Database (OLEDB), Data Mart, OnlineAnalytical Processing (OLAP), Online Transactional Processing(OLTP).

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Authors: P. S. Hiremath, Siddu P. Algur

Abstract:

With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, tools for the mining of data regions, data records and data items need to be developed in order to provide value-added services. Currently available automatic techniques to mine data regions from web pages are still unsatisfactory because of their poor performance and tag-dependence. In this paper a novel method to extract data items from the web pages automatically is proposed. It comprises of two steps: (1) Identification and Extraction of the data regions based on visual clues information. (2) Identification of data records and extraction of data items from a data region. For step1, a novel and more effective method is proposed based on visual clues, which finds the data regions formed by all types of tags using visual clues. For step2 a more effective method namely, Extraction of Data Items from web Pages (EDIP), is adopted to mine data items. The EDIP technique is a list-based approach in which the list is a linear data structure. The proposed technique is able to mine the non-contiguous data records and can correctly identify data regions, irrespective of the type of tag in which it is bound. Our experimental results show that the proposed technique performs better than the existing techniques.

Keywords: Web data records, web data regions, web mining.

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Authors: Akash Rathee, Harish Parthasarathy

Abstract:

In this paper, a frequency-variation based method has been proposed for transistor parameter estimation in a commonemitter transistor amplifier circuit. We design an algorithm to estimate the transistor parameters, based on noisy measurements of the output voltage when the input voltage is a sine wave of variable frequency and constant amplitude. The common emitter amplifier circuit has been modelled using the transistor Ebers-Moll equations and the perturbation technique has been used for separating the linear and nonlinear parts of the Ebers-Moll equations. This model of the amplifier has been used to determine the amplitude of the output sinusoid as a function of the frequency and the parameter vector. Then, applying the proposed method to the frequency components, the transistor parameters have been estimated. As compared to the conventional time-domain least squares method, the proposed method requires much less data storage and it results in more accurate parameter estimation, as it exploits the information in the time and frequency domain, simultaneously. The proposed method can be utilized for parameter estimation of an analog device in its operating range of frequencies, as it uses data collected from different frequencies output signals for parameter estimation.

Keywords: Perturbation Technique, Parameter estimation, frequency-variation based method.

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Authors: P. Azimi, B. Behtoiy

Abstract:

One of the most famous techniques which affect the efficiency of a production line is the assembly line balancing (ALB) technique. This paper examines the balancing effect of a whole production line of a real auto glass manufacturer in three steps. In the first step, processing time of each activity in the workstations is generated according to a practical approach. In the second step, the whole production process is simulated and the bottleneck stations have been identified, and finally in the third step, several improvement scenarios are generated to optimize the system throughput, and the best one is proposed. The main contribution of the current research is the proposed framework which combines two famous approaches including Assembly Line Balancing and Optimization via Simulation technique (OvS). The results show that the proposed framework could be applied in practical environments, easily.

Keywords: Assembly line balancing problem, optimization via simulation, production planning.

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Authors: H. Ahmad, S. Kermanshahani, A. Simonet, M. Simonet

Abstract:

The data exchanged on the Web are of different nature from those treated by the classical database management systems; these data are called semi-structured data since they do not have a regular and static structure like data found in a relational database; their schema is dynamic and may contain missing data or types. Therefore, the needs for developing further techniques and algorithms to exploit and integrate such data, and extract relevant information for the user have been raised. In this paper we present the system OSIX (Osiris based System for Integration of XML Sources). This system has a Data Warehouse model designed for the integration of semi-structured data and more precisely for the integration of XML documents. The architecture of OSIX relies on the Osiris system, a DL-based model designed for the representation and management of databases and knowledge bases. Osiris is a viewbased data model whose indexing system supports semantic query optimization. We show that the problem of query processing on a XML source is optimized by the indexing approach proposed by Osiris.

Keywords: Data integration, semi-structured data, views, XML.

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Authors: Yingguo Li

Abstract:

In this paper, we consider a discrete Gompertz model with time delay. Firstly, the stability of the equilibrium of the system is investigated by analyzing the characteristic equation. By choosing the time delay as a bifurcation parameter, we prove that Neimark- Sacker bifurcations occur when the delay passes a sequence of critical values. The direction and stability of the Neimark-Sacker are determined by using normal forms and centre manifold theory. Finally, some numerical simulations are given to verify the theoretical analysis.

Keywords: Gompertz system, Neimark-Sacker bifurcation, stability, time delay.

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Authors: Jin A Ryu, Ga Ye Kim, Hee Sun Kim

Abstract:

As the number of fire accidents is gradually raising, many studies have been reported on evacuation. Previous studies have mostly focused on evaluating the safety of evacuation and the risk of fire in particular buildings. However, studies on effects of various parameters on evacuation have not been nearly done. Therefore, this paper aims at observing evacuation time under the effect of fire initiated location. In this study, evacuation simulations are performed on a 5-floor building located in Seoul, South Korea using the commercial program, Fire Dynamics Simulator with Evacuation (FDS+EVAC). Only the fourth and fifth floors are modeled with an assumption that fire starts in a room located on the fourth floor. The parameter for evacuation simulations is location of fire initiation to observe the evacuation time and safety. Results show that the location of fire initiation is closer to exit, the more time is taken to evacuate. The case having the nearest location of fire initiation to exit has the lowest ratio of successful occupants to the total occupants. In addition, for safety evaluation, the evacuation time calculated from computer simulation model is compared with the tolerable evacuation time according to code in Japan. As a result, all cases are completed within the tolerable evacuation time. This study allows predicting evacuation time under various conditions of fire and can be used to evaluate evacuation appropriateness and fire safety of building.

Keywords: Evacuation safety, Evacuation simulation, FDS+Evac, Time.

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