Search results for: Text Data Mining
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7939

Search results for: Text Data Mining

7129 The New Method of Concealed Data Aggregation in Wireless Sensor: A Case Study

Authors: M. Abbasi Dezfouli, S. Mazraeh, M. H. Yektaie

Abstract:

Wireless sensor networks (WSN) consists of many sensor nodes that are placed on unattended environments such as military sites in order to collect important information. Implementing a secure protocol that can prevent forwarding forged data and modifying content of aggregated data and has low delay and overhead of communication, computing and storage is very important. This paper presents a new protocol for concealed data aggregation (CDA). In this protocol, the network is divided to virtual cells, nodes within each cell produce a shared key to send and receive of concealed data with each other. Considering to data aggregation in each cell is locally and implementing a secure authentication mechanism, data aggregation delay is very low and producing false data in the network by malicious nodes is not possible. To evaluate the performance of our proposed protocol, we have presented computational models that show the performance and low overhead in our protocol.

Keywords: Wireless Sensor Networks, Security, Concealed Data Aggregation.

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7128 Peakwise Smoothing of Data Models using Wavelets

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

Abstract:

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

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

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7127 A New Precautionary Method for Measurement and Improvement the Data Quality

Authors: Seyed Mohammad Hossein Moossavizadeh, Mehran Mohsenzadeh, Nasrin Arshadi

Abstract:

the data quality is a kind of complex and unstructured concept, which is concerned by information systems managers. The reason of this attention is the high amount of Expenses for maintenance and cleaning of the inefficient data. Such a data more than its expenses of lack of quality, cause wrong statistics, analysis and decisions in organizations. Therefor the managers intend to improve the quality of their information systems' data. One of the basic subjects of quality improvement is the evaluation of the amount of it. In this paper, we present a precautionary method, which with its application the data of information systems would have a better quality. Our method would cover different dimensions of data quality; therefor it has necessary integrity. The presented method has tested on three dimensions of accuracy, value-added and believability and the results confirm the improvement and integrity of this method.

Keywords: Data quality, precaution, information system, measurement, improvement.

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7126 Contingent Presences in Architecture: Vitruvian Theory as a Beginning

Authors: Zelal Çinar

Abstract:

This paper claims that architecture is a contingent discipline, despite the fact that its contingency has long been denied through a retreat to Vitruvian writing. It is evident that contingency is rejected not only by architecture but also by modernity as a whole. Vitruvius attempted to cover the entire field of architecture in a systematic form in order to bring the whole body of this great discipline to a complete order. The legacy of his theory hitherto lasted not only that it is the only major work on the architecture of Classical Antiquity to have survived, but also that its conformity with the project of modernity. In the scope of the paper, it will be argued that contingency should be taken into account rather than avoided as a potential threat. 

Keywords: Architecture, contingency, modernity, Vitruvius.

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7125 Weigh-in-Motion Data Analysis Software for Developing Traffic Data for Mechanistic Empirical Pavement Design

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

Abstract:

Currently, there are few user friendly Weigh-in- Motion (WIM) data analysis softwares available which can produce traffic input data for the recently developed AASHTOWare pavement Mechanistic-Empirical (ME) design software. However, these softwares have only rudimentary Quality Control (QC) processes. Therefore, they cannot properly deal with erroneous WIM data. As the pavement performance is highly sensible to the quality of WIM data, it is highly recommended to use more refined QC process on raw WIM data to get a good result. This study develops a userfriendly software, which can produce traffic input for the ME design software. This software takes the raw data (Class and Weight data) collected from the WIM station and processes it with a sophisticated QC procedure. Traffic data such as traffic volume, traffic distribution, axle load spectra, etc. can be obtained from this software; which can directly be used in the ME design software.

Keywords: Weigh-in-motion, software, axle load spectra, traffic distribution, AASHTOWare.

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7124 Author's Approach to the Problem of Correctional Speech Therapy with Children Suffering from Alalia

Authors: Е. V. Kutsina, S. A. Tarasova

Abstract:

In this article we present a methodology which enables preschool and primary school unlanguaged children to remember words, phrases and texts with the help of graphic signs - letters, syllables and words. Reading for a child becomes a support for speech development. Teaching is based on the principle "from simple to complex", "a letter - a syllable - a word - a proposal - a text." Availability of multi-level texts allows using this methodology for working with children who have different levels of speech development.

Keywords: Alalia, analytic-synthetic method, development of coherent speech, formation of vocabulary, learning to read, , sentence formation, three-level stories, unlanguaged children.

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7123 Human Growth Curve Estimation through a Combination of Longitudinal and Cross-sectional Data

Authors: Sedigheh Mirzaei S., Debasis Sengupta

Abstract:

Parametric models have been quite popular for studying human growth, particularly in relation to biological parameters such as peak size velocity and age at peak size velocity. Longitudinal data are generally considered to be vital for fittinga parametric model to individual-specific data, and for studying the distribution of these biological parameters in a human population. However, cross-sectional data are easier to obtain than longitudinal data. In this paper, we present a method of combining longitudinal and cross-sectional data for the purpose of estimating the distribution of the biological parameters. We demonstrate, through simulations in the special case ofthePreece Baines model, how estimates based on longitudinal data can be improved upon by harnessing the information contained in cross-sectional data.We study the extent of improvement for different mixes of the two types of data, and finally illustrate the use of the method through data collected by the Indian Statistical Institute.

Keywords: Preece-Baines growth model, MCMC method, Mixed effect model

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7122 Semantic Support for Hypothesis-Based Research from Smart Environment Monitoring and Analysis Technologies

Authors: T. S. Myers, J. Trevathan

Abstract:

Improvements in the data fusion and data analysis phase of research are imperative due to the exponential growth of sensed data. Currently, there are developments in the Semantic Sensor Web community to explore efficient methods for reuse, correlation and integration of web-based data sets and live data streams. This paper describes the integration of remotely sensed data with web-available static data for use in observational hypothesis testing and the analysis phase of research. The Semantic Reef system combines semantic technologies (e.g., well-defined ontologies and logic systems) with scientific workflows to enable hypothesis-based research. A framework is presented for how the data fusion concepts from the Semantic Reef architecture map to the Smart Environment Monitoring and Analysis Technologies (SEMAT) intelligent sensor network initiative. The data collected via SEMAT and the inferred knowledge from the Semantic Reef system are ingested to the Tropical Data Hub for data discovery, reuse, curation and publication.

Keywords: Information architecture, Semantic technologies Sensor networks, Ontologies.

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7121 Data Migration between Document-Oriented and Relational Databases

Authors: Bogdan Walek, Cyril Klimes

Abstract:

Current tools for data migration between documentoriented and relational databases have several disadvantages. We propose a new approach for data migration between documentoriented and relational databases. During data migration the relational schema of the target (relational database) is automatically created from collection of XML documents. Proposed approach is verified on data migration between document-oriented database IBM Lotus/ Notes Domino and relational database implemented in relational database management system (RDBMS) MySQL.

Keywords: data migration, database, document-oriented database, XML, relational schema

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7120 Identity Verification Using k-NN Classifiers and Autistic Genetic Data

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: Biometrics, identity verification, genetic data, k-nearest neighbor.

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7119 A Robotic Cube to Preschool Children for Acquiring the Mathematical and Colours Concepts

Authors: Ahmed Amin Mousa, Tamer M. Ismail, M. Abd El Salam

Abstract:

This work presents a robot called Conceptual Robotic Cube, CR-Cube. The robot can be used as an educational tool for children from the age of three. It has a cube shape attached with a camera colours sensor. In addition, it contains four wheels to move smoothly. The researchers prepared a questionnaire to measure the efficiency of the robot. The design and the questionnaire was presented to 11 experts who agreed that the robot is appropriate for learning numbering and colours for preschool children.

Keywords: CR-Cube, robotic cube, conceptual robot, conceptual cube, colour concept, early childhood education.

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7118 Power Saving System in Green Data Center

Authors: Joon-young Jung, Dong-oh Kang, Chang-seok Bae

Abstract:

Power consumption is rapidly increased in data centers because the number of data center is increased and more the scale of data center become larger. Therefore, it is one of key research items to reduce power consumption in data center. The peak power of a typical server is around 250 watts. When a server is idle, it continues to use around 60% of the power consumed when in use, though vendors are putting effort into reducing this “idle" power load. Servers tend to work at only around a 5% to 20% utilization rate, partly because of response time concerns. An average of 10% of servers in their data centers was unused. In those reason, we propose dynamic power management system to reduce power consumption in green data center. Experiment result shows that about 55% power consumption is reduced at idle time.

Keywords: Data Center, Green IT, Management Server, Power Saving.

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7117 Dynamic Inverted Index Maintenance

Authors: Leo Galambos

Abstract:

The majority of today's IR systems base the IR task on two main processes: indexing and searching. There exists a special group of dynamic IR systems where both processes (indexing and searching) happen simultaneously; such a system discards obsolete information, simultaneously dealing with the insertion of new in¬formation, while still answering user queries. In these dynamic, time critical text document databases, it is often important to modify index structures quickly, as documents arrive. This paper presents a method for dynamization which may be used for this task. Experimental results show that the dynamization process is possible and that it guarantees the response time for the query operation and index actualization.

Keywords: Search engine, inverted file, index management.

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7116 Spatial Econometric Approaches for Count Data: An Overview and New Directions

Authors: Paula Simões, Isabel Natário

Abstract:

This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: Spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data.

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7115 Increased Capacity of Information Hiding in LSB-s Method for Text and Image

Authors: H.B.Kekre, Archana Athawale, Pallavi N.Halarnkar

Abstract:

Steganography, derived from Greek, literally means “covered writing". It includes a vast array of secret communications methods that conceal the message-s very existence. These methods include invisible inks, microdots, character arrangement, digital signatures, covert channels, and spread spectrum communications. This paper proposes a new improved version of Least Significant Bit (LSB) method. The approach proposed is simple for implementation when compared to Pixel value Differencing (PVD) method and yet achieves a High embedding capacity and imperceptibility. The proposed method can also be applied to 24 bit color images and achieve embedding capacity much higher than PVD.

Keywords: Information Hiding, LSB Matching, PVD Steganography.

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7114 Shopping Cart System: Load Balancing and Fault Tolerance in the OSGi Service Platform

Authors: Irina Astrova, Arne Koschel, Thole Schneider, Johannes Westhuis, Jürgen Westerkamp

Abstract:

The main purpose of this paper was to find a simple solution for load balancing and fault tolerance in OSGi. The challenge was to implement a highly available web application such as a shopping cart system with load balancing and fault tolerance, without having to change the core of OSGi.

Keywords: Fault tolerance, load balancing, OSGi, shopping cart system.

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7113 Image Classification and Accuracy Assessment Using the Confusion Matrix, Contingency Matrix, and Kappa Coefficient

Authors: F. F. Howard, C. B. Boye, I. Yakubu, J. S. Y. Kuma

Abstract:

One of the ways that could be used for the production of land use and land cover maps by a procedure known as image classification is the use of the remote sensing technique. Numerous elements ought to be taken into consideration, including the availability of highly satisfactory Landsat imagery, secondary data and a precise classification process. The goal of this study was to classify and map the land use and land cover of the study area using remote sensing and Geospatial Information System (GIS) analysis. The classification was done using Landsat 8 satellite images acquired in December 2020 covering the study area. The Landsat image was downloaded from the USGS. The Landsat image with 30 m resolution was geo-referenced to the WGS_84 datum and Universal Transverse Mercator (UTM) Zone 30N coordinate projection system. A radiometric correction was applied to the image to reduce the noise in the image. This study consists of two sections: the Land Use/Land Cover (LULC) and Accuracy Assessments using the confusion and contingency matrix and the Kappa coefficient. The LULC classifications were vegetation (agriculture) (67.87%), water bodies (0.01%), mining areas (5.24%), forest (26.02%), and settlement (0.88%). The overall accuracy of 97.87% and the kappa coefficient (K) of 97.3% were obtained for the confusion matrix. While an overall accuracy of 95.7% and a Kappa coefficient of 0.947 were obtained for the contingency matrix, the kappa coefficients were rated as substantial; hence, the classified image is fit for further research.

Keywords: Confusion Matrix, contingency matrix, kappa coefficient, land used/ land cover, accuracy assessment.

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7112 Principal Component Analysis using Singular Value Decomposition of Microarray Data

Authors: Dong Hoon Lim

Abstract:

A series of microarray experiments produces observations of differential expression for thousands of genes across multiple conditions. Principal component analysis(PCA) has been widely used in multivariate data analysis to reduce the dimensionality of the data in order to simplify subsequent analysis and allow for summarization of the data in a parsimonious manner. PCA, which can be implemented via a singular value decomposition(SVD), is useful for analysis of microarray data. For application of PCA using SVD we use the DNA microarray data for the small round blue cell tumors(SRBCT) of childhood by Khan et al.(2001). To decide the number of components which account for sufficient amount of information we draw scree plot. Biplot, a graphic display associated with PCA, reveals important features that exhibit relationship between variables and also the relationship of variables with observations.

Keywords: Principal component analysis, singular value decomposition, microarray data, SRBCT

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7111 Clustering Mixed Data Using Non-normal Regression Tree for Process Monitoring

Authors: Youngji Yoo, Cheong-Sool Park, Jun Seok Kim, Young-Hak Lee, Sung-Shick Kim, Jun-Geol Baek

Abstract:

In the semiconductor manufacturing process, large amounts of data are collected from various sensors of multiple facilities. The collected data from sensors have several different characteristics due to variables such as types of products, former processes and recipes. In general, Statistical Quality Control (SQC) methods assume the normality of the data to detect out-of-control states of processes. Although the collected data have different characteristics, using the data as inputs of SQC will increase variations of data, require wide control limits, and decrease performance to detect outof- control. Therefore, it is necessary to separate similar data groups from mixed data for more accurate process control. In the paper, we propose a regression tree using split algorithm based on Pearson distribution to handle non-normal distribution in parametric method. The regression tree finds similar properties of data from different variables. The experiments using real semiconductor manufacturing process data show improved performance in fault detecting ability.

Keywords: Semiconductor, non-normal mixed process data, clustering, Statistical Quality Control (SQC), regression tree, Pearson distribution system.

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7110 Royal Mound “Baygetobe“ from the Burial Ground Shilikty

Authors: Abdesh Toleubayev, Rinat Zhumatayev, Kulzhazira Toleubayeva

Abstract:

Mounds are one of the most valuable sources of information on various aspects of life, household skills, rituals and beliefs of the ancient peoples of Kazakhstan. Moreover, the objects associated with the cult of the burial of the dead are the most informative, and often the only source of knowledge about past eras. The present study is devoted to some results of the excavations carried out on the mound "Baygetobe" of Shilikti burial ground. The purpose of the work is associated with certain categories of grave goods and reading "Fine Text" of Shilikti graves, whose structure is the same for burials of nobles and ordinary graves. The safety of a royal burial mounds, the integrity and completeness of the source are of particular value for studying.

Keywords: Animal style, barrow, Baygetobe, dromos, Shilikty.

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7109 The Different Ways to Describe Regular Languages by Using Finite Automata and the Changing Algorithm Implementation

Authors: Abdulmajid Mukhtar Afat

Abstract:

This paper aims at introducing finite automata theory, the different ways to describe regular languages and create a program to implement the subset construction algorithms to convert nondeterministic finite automata (NFA) to deterministic finite automata (DFA). This program is written in c++ programming language. The program reads FA 5tuples from text file and then classifies it into either DFA or NFA. For DFA, the program will read the string w and decide whether it is acceptable or not. If accepted, the program will save the tracking path and point it out. On the other hand, when the automation is NFA, the program will change the Automation to DFA so that it is easy to track and it can decide whether the w exists in the regular language or not.

Keywords: Finite Automata, subset construction DFA, NFA.

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7108 Modelling for Roof Failure Analysis in an Underground Cave

Authors: M. Belén Prendes-Gero, Celestino González-Nicieza, M. Inmaculada Alvarez-Fernández

Abstract:

Roof collapse is one of the problems with a higher frequency in most of the mines of all countries, even now. There are many reasons that may cause the roof to collapse, namely the mine stress activities in the mining process, the lack of vigilance and carelessness or the complexity of the geological structure and irregular operations. This work is the result of the analysis of one accident produced in the “Mary” coal exploitation located in northern Spain. In this accident, the roof of a crossroad of excavated galleries to exploit the “Morena” Layer, 700 m deep, collapsed. In the paper, the work done by the forensic team to determine the causes of the incident, its conclusions and recommendations are collected. Initially, the available documentation (geology, geotechnics, mining, etc.) and accident area were reviewed. After that, laboratory and on-site tests were carried out to characterize the behaviour of the rock materials and the support used (metal frames and shotcrete). With this information, different hypotheses of failure were simulated to find the one that best fits reality. For this work, the software of finite differences in three dimensions, FLAC 3D, was employed. The results of the study confirmed that the detachment was originated as a consequence of one sliding in the layer wall, due to the large roof span present in the place of the accident, and probably triggered as a consequence of the existence of a protection pillar insufficient. The results allowed to establish some corrective measures avoiding future risks. For example, the dimensions of the protection zones that must be remained unexploited and their interaction with the crossing areas between galleries, or the use of more adequate supports for these conditions, in which the significant deformations may discourage the use of rigid supports such as shotcrete. At last, a grid of seismic control was proposed as a predictive system. Its efficiency was tested along the investigation period employing three control equipment that detected new incidents (although smaller) in other similar areas of the mine. These new incidents show that the use of explosives produces vibrations which are a new risk factor to analyse in a next future.

Keywords: Forensic analysis, hypothesis modelling, roof failure, seismic monitoring.

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7107 Speech Data Compression using Vector Quantization

Authors: H. B. Kekre, Tanuja K. Sarode

Abstract:

Mostly transforms are used for speech data compressions which are lossy algorithms. Such algorithms are tolerable for speech data compression since the loss in quality is not perceived by the human ear. However the vector quantization (VQ) has a potential to give more data compression maintaining the same quality. In this paper we propose speech data compression algorithm using vector quantization technique. We have used VQ algorithms LBG, KPE and FCG. The results table shows computational complexity of these three algorithms. Here we have introduced a new performance parameter Average Fractional Change in Speech Sample (AFCSS). Our FCG algorithm gives far better performance considering mean absolute error, AFCSS and complexity as compared to others.

Keywords: Vector Quantization, Data Compression, Encoding, , Speech coding.

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7106 Ontology and CDSS Based Intelligent Health Data Management in Health Care Server

Authors: Eun-Jung Ko, Hyung-Jik Lee, Jeun-Woo Lee

Abstract:

In ubiqutious healthcare environment, user's health data are transfered to the remote healthcare server by the user's wearable system or mobile phone. These collected user's health data should be managed and analyzed in the healthcare server, so that care giver or user can monitor user's physiological state. In this paper, we designed and developed the intelligent Healthcare Server to manage the user's health data using CDSS and ontology. Our system can analyze user's health data semantically using CDSS and ontology, and report the result of user's physiological raw data to the user and care giver.

Keywords: u-healthcare, CDSS, healthcare server, health data, ontology.

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7105 A Holistic Framework for Unifying Data Security and Management in Modern Enterprises

Authors: Ashly Joseph

Abstract:

Modern businesses struggle significantly to secure and manage their data properly as the volume and complexity of their data both expand exponentially. Through the use of a multi-layered defense strategy, a centralized management platform, and cutting-edge technologies like AI, this research paper presents a comprehensive framework to integrate data security and management. The constraints of current data protection and management strategies, technological advancements, and the evolving threat landscape are all examined in this article. It suggests best practices for putting into practice integrated data security and governance models, placing an emphasis on ongoing adaptation. The advantages mentioned include a strengthened security posture, simpler procedures, lower costs, and reduced complexity. Additionally, issues including skill shortages, antiquated systems, and cultural obstacles are examined. Security executives and Chief Information Security Officers are given practical advice on how to evaluate, plan, and put into place strong data-centric security and management capabilities. The goal of the paper is to provide a thorough study of the data security and management landscape and to arm contemporary businesses with the knowledge they need to be proactive in protecting their data assets.

Keywords: Data security, security management, cloud computing, cybersecurity, data governance, security architecture, data management.

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7104 RFID-ready Master Data Management for Reverse Logistics

Authors: Jincheol Han, Hyunsun Ju, Jonghoon Chun

Abstract:

Sharing consistent and correct master data among disparate applications in a reverse-logistics chain has long been recognized as an intricate problem. Although a master data management (MDM) system can surely assume that responsibility, applications that need to co-operate with it must comply with proprietary query interfaces provided by the specific MDM system. In this paper, we present a RFID-ready MDM system which makes master data readily available for any participating applications in a reverse-logistics chain. We propose a RFID-wrapper as a part of our MDM. It acts as a gateway between any data retrieval request and query interfaces that process it. With the RFID-wrapper, any participating applications in a reverse-logistics chain can easily retrieve master data in a way that is analogous to retrieval of any other RFID-based logistics transactional data.

Keywords: Reverse Logistics, Master Data Management, RFID.

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7103 Turbo-Coded Mobile Terrestrial Communication Systems in Urban and Suburban Areas for Wireless Multimedia Applications

Authors: F. Mehran

Abstract:

With the rapid popularization of internet services, it is apparent that the next generation terrestrial communication systems must be capable of supporting various applications like voice, video, and data. This paper presents the performance evaluation of turbo- coded mobile terrestrial communication systems, which are capable of providing high quality services for delay sensitive (voice or video) and delay tolerant (text transmission) multimedia applications in urban and suburban areas. Different types of multimedia information require different service qualities, which are generally expressed in terms of a maximum acceptable bit-error-rate (BER) and maximum tolerable latency. The breakthrough discovery of turbo codes allows us to significantly reduce the probability of bit errors with feasible latency. In a turbo-coded system, a trade-off between latency and BER results from the choice of convolutional component codes, interleaver type and size, decoding algorithm, and the number of decoding iterations. This trade-off can be exploited for multimedia applications by using optimal and suboptimal performance parameter amalgamations to achieve different service qualities. The results are therefore proposing an adaptive framework for turbo-coded wireless multimedia communications which incorporate a set of performance parameters that achieve an appropriate set of service qualities, depending on the application's requirements.

Keywords: Mobile communications, Turbo codes, wireless multimedia communication systems.

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7102 Dynamic Models versus Frailty Models for Recurrent Event Data

Authors: Entisar A. Elgmati

Abstract:

Recurrent event data is a special type of multivariate survival data. Dynamic and frailty models are one of the approaches that dealt with this kind of data. A comparison between these two models is studied using the empirical standard deviation of the standardized martingale residual processes as a way of assessing the fit of the two models based on the Aalen additive regression model. Here we found both approaches took heterogeneity into account and produce residual standard deviations close to each other both in the simulation study and in the real data set.

Keywords: Dynamic, frailty, misspecification, recurrent events.

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7101 Issues and Architecture for Supporting Data Warehouse Queries in Web Portals

Authors: Minsoo Lee, Yoon-kyung Lee, Hyejung Yoon, Soo-kyung Song, Sujeong Cheong

Abstract:

Data Warehousing tools have become very popular and currently many of them have moved to Web-based user interfaces to make it easier to access and use the tools. The next step is to enable these tools to be used within a portal framework. The portal framework consists of pages having several small windows that contain individual data warehouse query results. There are several issues that need to be considered when designing the architecture for a portal enabled data warehouse query tool. Some issues need special techniques that can overcome the limitations that are imposed by the nature of data warehouse queries. Issues such as single sign-on, query result caching and sharing, customization, scheduling and authorization need to be considered. This paper discusses such issues and suggests an architecture to support data warehouse queries within Web portal frameworks.

Keywords: Data Warehousing tools, data warehousing queries, web portal frameworks.

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7100 Recursive Algorithms for Image Segmentation Based on a Discriminant Criterion

Authors: Bing-Fei Wu, Yen-Lin Chen, Chung-Cheng Chiu

Abstract:

In this study, a new criterion for determining the number of classes an image should be segmented is proposed. This criterion is based on discriminant analysis for measuring the separability among the segmented classes of pixels. Based on the new discriminant criterion, two algorithms for recursively segmenting the image into determined number of classes are proposed. The proposed methods can automatically and correctly segment objects with various illuminations into separated images for further processing. Experiments on the extraction of text strings from complex document images demonstrate the effectiveness of the proposed methods.1

Keywords: image segmentation, multilevel thresholding, clustering, discriminant analysis

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