Search results for: data validation

Authors: Mehdi Emadi, Masoud Rahgozar, Adel Ardalan, Alireza Kazerani, Mohammad Mahdi Ariyan

Abstract:

The volume of XML data exchange is explosively increasing, and the need for efficient mechanisms of XML data management is vital. Many XML storage models have been proposed for storing XML DTD-independent documents in relational database systems. Benchmarking is the best way to highlight pros and cons of different approaches. In this study, we use a common benchmarking scheme, known as XMark to compare the most cited and newly proposed DTD-independent methods in terms of logical reads, physical I/O, CPU time and duration. We show the effect of Label Path, extracting values and storing in another table and type of join needed for each method's query answering.

Keywords: XML Data Management, XPath, DTD-IndependentXML Data

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Authors: Mehdi Emadi, Masoud Rahgozar, Adel Ardalan, Alireza Kazerani, Mohammad Mahdi Ariyan

Abstract:

The volume of XML data exchange is explosively increasing, and the need for efficient mechanisms of XML data management is vital. Many XML storage models have been proposed for storing XML DTD-independent documents in relational database systems. Benchmarking is the best way to highlight pros and cons of different approaches. In this study, we use a common benchmarking scheme, known as XMark to compare the most cited and newly proposed DTD-independent methods in terms of logical reads, physical I/O, CPU time and duration. We show the effect of Label Path, extracting values and storing in another table and type of join needed for each method-s query answering.

Keywords: XML Data Management, XPath, DTD-Independent XML Data.

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Authors: Yuyun Wabula, B. J. Dewancker

Abstract:

In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.

Keywords: Geolocation, Twitter, distribution analysis, human mobility.

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Authors: Ágoston Winkler, Sándor Juhász, Zoltán Benedek

Abstract:

The vehicle fleet of public transportation companies is often equipped with intelligent on-board passenger information systems. A frequently used but time and labor-intensive way for keeping the on-board controllers up-to-date is the manual update using different memory cards (e.g. flash cards) or portable computers. This paper describes a compression algorithm that enables data transmission using low bandwidth wireless radio networks (e.g. GPRS) by minimizing the amount of data traffic. In typical cases it reaches a compression rate of an order of magnitude better than that of the general purpose compressors. Compressed data can be easily expanded by the low-performance controllers, too.

Keywords: Data analysis, data compression, differentialencoding, run-length encoding, vehicle control.

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Authors: S. Balaji, M. Rajaram

Abstract:

The method of introducing the proxy interpretation for sending and receiving requests increase the capability of the server and our approach UDIV (User-Data Identity Security) to solve the data and user authentication without extending size of the data makes better than hybrid IDS (Intrusion Detection System). And at the same time all the security stages we have framed have to pass through less through that minimize the response time of the request. Even though an anomaly detected, before rejecting it the proxy extracts its identity to prevent it to enter into system. In case of false anomalies, the request will be reshaped and transformed into legitimate request for further response. Finally we are holding the normal and abnormal requests in two different queues with own priorities.

Keywords: IDS, Data & User authentication, UDIS.

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Authors: K. S. Neelukumari, K. B. Jayanthi

Abstract:

In this paper genetic based test data compression is targeted for improving the compression ratio and for reducing the computation time. The genetic algorithm is based on extended pattern run-length coding. The test set contains a large number of X value that can be effectively exploited to improve the test data compression. In this coding method, a reference pattern is set and its compatibility is checked. For this process, a genetic algorithm is proposed to reduce the computation time of encoding algorithm. This coding technique encodes the 2n compatible pattern or the inversely compatible pattern into a single test data segment or multiple test data segment. The experimental result shows that the compression ratio and computation time is reduced.

Keywords: Backtracking, test data compression (TDC), x-filling, x-propagating and genetic algorithm.

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Authors: Nagi Mekhiel

Abstract:

Many applications use vector operations by applying single instruction to multiple data that map to different locations in conventional memory. Transferring data from memory is limited by access latency and bandwidth affecting the performance gain of vector processing. We present a memory system that makes all of its content available to processors in time so that processors need not to access the memory, we force each location to be available to all processors at a specific time. The data move in different orbits to become available to other processors in higher orbits at different time. We use this memory to apply parallel vector operations to data streams at first orbit level. Data processed in the first level move to upper orbit one data element at a time, allowing a processor in that orbit to apply another vector operation to deal with serial code limitations inherited in all parallel applications and interleaved it with lower level vector operations.

Keywords: Memory organization, parallel processors, serial code, vector processing.

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Authors: Essa Alenazi, Zulfikar Adamu

Abstract:

The Kingdom of Saudi Arabia (KSA) is not an exception in relying on the growth of its construction industry to support rapid population growth. However, its need for infrastructure development is constrained by low productivity levels and cost overruns caused by factors such as delays to project completion. Delays in delivering a construction project are a global issue and while theories such as Optimism Bias have been used to explain such delays, in KSA, client-related causes of delays are also significant. The objective of this paper is to develop a framework-based approach to explore how the country’s construction industry can manage and reduce delays in construction projects through building information modelling (BIM) in order to mitigate the cost consequences of such delays.  It comprehensively and systematically reviewed the global literature on the subject and identified gaps, critical delay factors and the specific benefits that BIM can deliver for the delay management.  A case study comprising of nine hospital projects that have experienced delay and cost overruns was also carried out. Five critical delay factors related to the clients were identified as candidates that can be mitigated through BIM’s benefits. These factors are: Ineffective planning and scheduling of the project; changes during construction by the client; delay in progress payment; slowness in decision making by the client; and poor communication between clients and other stakeholders. In addition, data from the case study projects strongly suggest that optimism bias is present in many of the hospital projects. Further validation via key stakeholder interviews and documentations are planned.

Keywords: BIM, client perspective, delay management, optimism bias, public sector projects.

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Authors: J. McCullagh, T. Whitfort

Abstract:

Artificial Neural Networks (ANNs) have been used successfully in many scientific, industrial and business domains as a method for extracting knowledge from vast amounts of data. However the use of ANN techniques in the sporting domain has been limited. In professional sport, data is stored on many aspects of teams, games, training and players. Sporting organisations have begun to realise that there is a wealth of untapped knowledge contained in the data and there is great interest in techniques to utilise this data. This study will use player data from the elite Australian Football League (AFL) competition to train and test ANNs with the aim to predict the onset of injuries. The results demonstrate that an accuracy of 82.9% was achieved by the ANNs’ predictions across all examples with 94.5% of all injuries correctly predicted. These initial findings suggest that ANNs may have the potential to assist sporting clubs in the prediction of injuries.

Keywords: Artificial Neural Networks, data, injuries, sport

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Authors: Masoud Mohammadpour, Blair Carlson, Radovan Kovacevic

Abstract:

The quality of laser welded-brazed (LWB) joints were strongly dependent on the main process parameters, therefore the effect of laser power (3.2–4 kW), welding speed (60–80 mm/s) and wire feed rate (70–90 mm/s) on mechanical strength and surface roughness were investigated in this study. The comprehensive optimization process by means of response surface methodology (RSM) and desirability function was used for multi-criteria optimization. The experiments were planned based on Box– Behnken design implementing linear and quadratic polynomial equations for predicting the desired output properties. Finally, validation experiments were conducted on an optimized process condition which exhibited good agreement between the predicted and experimental results. AlSi3Mn1 was selected as the filler material for joining aluminum alloy 6022 and hot-dip galvanized steel in coach peel configuration. The high scanning speed could control the thickness of IMC as thin as 5 µm. The thermal simulations of joining process were conducted by the Finite Element Method (FEM), and results were validated through experimental data. The Fe/Al interfacial thermal history evidenced that the duration of critical temperature range (700–900 °C) in this high scanning speed process was less than 1 s. This short interaction time leads to the formation of reaction-control IMC layer instead of diffusion-control mechanisms.

Keywords: Laser welding-brazing, finite element, response surface methodology, multi-response optimization, cross-beam laser.

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Authors: Anamika Gupta, Naveen Kumar, Vasudha Bhatnagar

Abstract:

This paper focuses on analyzing medical diagnostic data using classification rules in data mining and context reduction in formal concept analysis. It helps in finding redundancies among the various medical examination tests used in diagnosis of a disease. Classification rules have been derived from positive and negative association rules using the Concept lattice structure of the Formal Concept Analysis. Context reduction technique given in Formal Concept Analysis along with classification rules has been used to find redundancies among the various medical examination tests. Also it finds out whether expensive medical tests can be replaced by some cheaper tests.

Keywords: Data Mining, Formal Concept Analysis, Medical Data, Negative Classification Rules.

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Authors: Sui Xin, Li Chunsheng, Tian Di

Abstract:

Short message integrated distributed monitoring systems (SM-DMS) are growing rapidly in wireless communication applications in various areas, such as electromagnetic field (EMF) management, wastewater monitoring, and air pollution supervision, etc. However, delay in short messages often makes the data embedded in SM-DMS transmit unreliably. Moreover, there are few regulations dealing with this problem in SMS transmission protocols. In this study, based on the analysis of the command and data requirements in the SM-DMS, we developed a processing model for the control center to solve the delay problem in data transmission. Three components of the model: the data transmission protocol, the receiving buffer pool method, and the timer mechanism were described in detail. Discussions on adjusting the threshold parameter in the timer mechanism were presented for the adaptive performance during the runtime of the SM-DMS. This model optimized the data transmission reliability in SM-DMS, and provided a supplement to the data transmission reliability protocols at the application level.

Keywords: Delay, SMS, reliability, distributed monitoringsystem (DMS), wireless communication.

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Authors: H. Bouhamed, A. Rebai, T. Lecroq, M. Jaoua

Abstract:

The objective of our work is to develop a new approach for discovering knowledge from a large mass of data, the result of applying this approach will be an expert system that will serve as diagnostic tools of a phenomenon related to a huge information system. We first recall the general problem of learning Bayesian network structure from data and suggest a solution for optimizing the complexity by using organizational and optimization methods of data. Afterward we proposed a new heuristic of learning a Multi-Entities Bayesian Networks structures. We have applied our approach to biological facts concerning hereditary complex illnesses where the literatures in biology identify the responsible variables for those diseases. Finally we conclude on the limits arched by this work.

Keywords: Data-organization, data-optimization, automatic knowledge discovery, Multi-Entities Bayesian networks, score merging.

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Authors: Dhinu Johnson, Gurdip Singh

Abstract:

Sensor network applications are often data centric and involve collecting data from a set of sensor nodes to be delivered to various consumers. Typically, nodes in a sensor network are resource-constrained, and hence the algorithms operating in these networks must be efficient. There may be several algorithms available implementing the same service, and efficient considerations may require a sensor application to choose the best suited algorithm. In this paper, we present a systematic evaluation of a set of algorithms implementing the data gathering service. We propose a modular infrastructure for implementing such algorithms in TOSSIM with separate configurable modules for various tasks such as interest propagation, data propagation, aggregation, and path maintenance. By appropriately configuring these modules, we propose a number of data gathering algorithms, each of which incorporates a different set of heuristics for optimizing performance. We have performed comprehensive experiments to evaluate the effectiveness of these heuristics, and we present results from our experimentation efforts.

Keywords: Data Centric Protocols, Shortest Paths, Sensor networks, Message passing systems.

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Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

Abstract:

This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, Traffic, Weigh-in-Motion, Axle load Distribution.

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Authors: Prakash G L, Thejaswini M, S H Manjula, K R Venugopal, L M Patnaik

Abstract:

The Sensor Network consists of densely deployed sensor nodes. Energy optimization is one of the most important aspects of sensor application design. Data acquisition and aggregation techniques for processing data in-network should be energy efficient. Due to the cross-layer design, resource-limited and noisy nature of Wireless Sensor Networks(WSNs), it is challenging to study the performance of these systems in a realistic setting. In this paper, we propose optimizing queries by aggregation of data and data redundancy to reduce energy consumption without requiring all sensed data and directed diffusion communication paradigm to achieve power savings, robust communication and processing data in-network. To estimate the per-node power consumption POWERTossim mica2 energy model is used, which provides scalable and accurate results. The performance analysis shows that the proposed methods overcomes the existing methods in the aspects of energy consumption in wireless sensor networks.

Keywords: Data Aggregation, Directed Diffusion, Partial Aggregation, Packet Merging, Query Plan.

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Authors: Xiaoshu Lu, Tao Lu, Matias Remes, Martti Viljanen

Abstract:

As the data-driven economy is growing faster than ever and the demand for energy is being spurred, we are facing unprecedented challenges of improving energy efficiency in data centers. Effectively maximizing energy efficiency or minimising the cooling energy demand is becoming pervasive for data centers. This paper investigates overall energy consumption and the energy efficiency of cooling system for a data center in Finland as a case study. The power, cooling and energy consumption characteristics and operation condition of facilities are examined and analysed. Potential energy and cooling saving opportunities are identified and further suggestions for improving the performance of cooling system are put forward. Results are presented as a comprehensive evaluation of both the energy performance and good practices of energy efficient cooling operations for the data center. Utilization of an energy recovery concept for cooling system is proposed. The conclusion we can draw is that even though the analysed data center demonstrated relatively high energy efficiency, based on its power usage effectiveness value, there is still a significant potential for energy saving from its cooling systems.

Keywords: Data center, case study, cooling system, energyefficiency.

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Authors: Urska Cvek, Marjan Trutschl, Randolph Stone II, Zanobia Syed, John L. Clifford, Anita L. Sabichi

Abstract:

Expression data analysis is based mostly on the statistical approaches that are indispensable for the study of biological systems. Large amounts of multidimensional data resulting from the high-throughput technologies are not completely served by biostatistical techniques and are usually complemented with visual, knowledge discovery and other computational tools. In many cases, in biological systems we only speculate on the processes that are causing the changes, and it is the visual explorative analysis of data during which a hypothesis is formed. We would like to show the usability of multidimensional visualization tools and promote their use in life sciences. We survey and show some of the multidimensional visualization tools in the process of data exploration, such as parallel coordinates and radviz and we extend them by combining them with the self-organizing map algorithm. We use a time course data set of transitional cell carcinoma of the bladder in our examples. Analysis of data with these tools has the potential to uncover additional relationships and non-trivial structures.

Keywords: microarrays, visualization, parallel coordinates, radviz, self-organizing maps.

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Authors: L. Torchane

Abstract:

The study is devoted to define the optimal conditions for the nitriding of pure iron at atmospheric pressure by using NH3- Ar-C3H8 gas mixtures. After studying the mechanisms of phase formation and mass transfer at the gas-solid interface, a mathematical model is developed in order to predict the nitrogen transfer rate in the solid, the ε-carbonitride layer growth rate and the nitrogen and carbon concentration profiles. In order to validate the model and to show its possibilities, it is compared with thermogravimetric experiments, analyses and metallurgical observations (X-ray diffraction, optical microscopy and electron microprobe analysis). Results obtained allow us to demonstrate the sound correlation between the experimental results and the theoretical predictions.

Keywords: Gaseous Nitrocarburizing, Kinetic Model, Diffusion, Layer Growth Kinetic.

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Authors: Kamal Ali Albashiri, Khaled Ahmed Kadouh

Abstract:

A generic and extendible Multi-Agent Data Mining (MADM) framework, MADMF (the Multi-Agent Data Mining Framework) is described. The central feature of the framework is that it avoids the use of agreed meta-language formats by supporting a framework of wrappers. The advantage offered is that the framework is easily extendible, so that further data agents and mining agents can simply be added to the framework. A demonstration MADMF framework is currently available. The paper includes details of the MADMF architecture and the wrapper principle incorporated into it. A full description and evaluation of the framework-s operation is provided by considering two MADM scenarios.

Keywords: Multi-Agent Data Mining (MADM), Frequent Itemsets, Meta ARM, Association Rule Mining, Classifier generator.

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Authors: Petr Šimek, Kamil Kostruk

Abstract:

This paper deals with the problem of testing the Electronic Control Unit (ECU) for the specified function validation. Modern ECUs have many functions which need to be tested. This process requires tracking between the test and the specification. The technique discussed in this paper explores the system for automating this process. The paper focuses on the introduction to the problem in general, then it describes the proposed test system concept and its principle. It looks at how the process of the ECU interface specification file for automated interface testing and test tracking works. In the end, the future possible development of the project is discussed.

Keywords: Electronic control unit testing, embedded system, test generate, test automation, process automation, CAN bus, Ethernet.

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Authors: Nevena Stolba, A Min Tjoa

Abstract:

Evidence-based medicine is a new direction in modern healthcare. Its task is to prevent, diagnose and medicate diseases using medical evidence. Medical data about a large patient population is analyzed to perform healthcare management and medical research. In order to obtain the best evidence for a given disease, external clinical expertise as well as internal clinical experience must be available to the healthcare practitioners at right time and in the right manner. External evidence-based knowledge can not be applied directly to the patient without adjusting it to the patient-s health condition. We propose a data warehouse based approach as a suitable solution for the integration of external evidence-based data sources into the existing clinical information system and data mining techniques for finding appropriate therapy for a given patient and a given disease. Through integration of data warehousing, OLAP and data mining techniques in the healthcare area, an easy to use decision support platform, which supports decision making process of care givers and clinical managers, is built. We present three case studies, which show, that a clinical data warehouse that facilitates evidence-based medicine is a reliable, powerful and user-friendly platform for strategic decision making, which has a great relevance for the practice and acceptance of evidence-based medicine.

Keywords: data mining, data warehousing, decision-support systems, evidence-based medicine.

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Authors: F. Stazi, C. Di Perna, C. Filiaci, A. Stazi

Abstract:

Passive systems were born with the purpose of the greatest exploitation of solar energy in cold climates and high altitudes. They spread themselves until the 80-s all over the world without any attention to the specific climate and the summer behavior; this caused the deactivation of the systems due to a series of problems connected to the summer overheating, the complex management and the rising of the dust. Until today the European regulation limits only the winter consumptions without any attention to the summer behavior but, the recent European EN 15251 underlines the relevance of the indoor comfort, and the necessity of the analytic studies validation by monitoring case studies. In the porpose paper we demonstrate that the solar wall is an efficient system both from thermal comfort and energy saving point of view and it is the most suitable for our temperate climates because it can be used as a passive cooling sistem too. In particular the paper present an experimental and numerical analisys carried out on a case study with nine different solar passive systems in Ancona, Italy. We carried out a detailed study of the lodging provided by the solar wall by the monitoring and the evaluation of the indoor conditions. Analyzing the monitored data, on the base of recognized models of comfort (ISO, ASHRAE, Givoni-s BBCC), is emerged that the solar wall has an optimal behavior in the middle seasons. In winter phase this passive system gives more advantages in terms of energy consumptions than the other systems, because it gives greater heat gain and therefore smaller consumptions. In summer, when outside air temperature return in the mean seasonal value, the indoor comfort is optimal thanks to an efficient transversal ventilation activated from the same wall.

Keywords: Building envelope, energy saving, passive solarwall, thermal comfort.

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

Abstract:

In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: Time series, fluctuation in statistical characteristics, optimal learning.

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Authors: Shaun Cox, Michael Oakes, Stefan Wermter, Maurice Hawthorne

Abstract:

We report on the results of a pilot study in which a data-mining tool was developed for mining audiology records. The records were heterogeneous in that they contained numeric, category and textual data. The tools developed are designed to observe associations between any field in the records and any other field. The techniques employed were the statistical chi-squared test, and the use of self-organizing maps, an unsupervised neural learning approach.

Keywords: Audiology, data mining, chi-squared, self-organizing maps

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Authors: Mansoor Momeni, Mahmoud Dehghan Nayeri, Ali Faal Ghayoumi, Hoda Ghorbani

Abstract:

This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.

Keywords: Financial data analysis, Influential data, Outliers, Robust regression.

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Authors: Rahma Souli-Jbali, Minyar Sassi Hidri, Rahma Ben Ayed

Abstract:

Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks.

Keywords: Data grids, fault tolerance, chandy-lamport, clustering.

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Authors: Ahmad Habibizad Navin, Mehdi Naghian Fesharaki, Mohamad Teshnelab, Ehsan Shahamatnia

Abstract:

The anti-lock braking systems installed on vehicles for safe and effective braking, are high-order nonlinear and timevariant. Using fuzzy logic controllers increase efficiency of such systems, but impose a high computational complexity as well. The main concept introduced by this paper is reducing computational complexity of fuzzy controllers by deploying problem-solution data structure. Unlike conventional methods that are based on calculations, this approach is based on data oriented modeling.

Keywords: ABS, Fuzzy controller, PSDS, Time-Memory tradeoff, Data oriented modeling.

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Authors: Quratulain N. Rajput, Sajjad Haider

Abstract:

This paper applies Bayesian Networks to support information extraction from unstructured, ungrammatical, and incoherent data sources for semantic annotation. A tool has been developed that combines ontologies, machine learning, and information extraction and probabilistic reasoning techniques to support the extraction process. Data acquisition is performed with the aid of knowledge specified in the form of ontology. Due to the variable size of information available on different data sources, it is often the case that the extracted data contains missing values for certain variables of interest. It is desirable in such situations to predict the missing values. The methodology, presented in this paper, first learns a Bayesian network from the training data and then uses it to predict missing data and to resolve conflicts. Experiments have been conducted to analyze the performance of the presented methodology. The results look promising as the methodology achieves high degree of precision and recall for information extraction and reasonably good accuracy for predicting missing values.

Keywords: Information Extraction, Bayesian Network, ontology, Machine Learning

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Authors: Keonwoo Kim, Dowon Hong, Kyoil Chung, Jae-Cheol Ryou

Abstract:

Cell phone forensics to acquire and analyze data in the cellular phone is nowadays being used in a national investigation organization and a private company. In order to collect cellular phone flash memory data, we have two methods. Firstly, it is a logical method which acquires files and directories from the file system of the cell phone flash memory. Secondly, we can get all data from bit-by-bit copy of entire physical memory using a low level access method. In this paper, we describe a forensic tool to acquire cell phone flash memory data using a logical level approach. By our tool, we can get EFS file system and peek memory data with an arbitrary region from Korea CDMA cell phone.

Keywords: Forensics, logical method, acquisition, cell phone, flash memory.

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