Search results for: Data mining technique

Authors: Kenny Raharjo, Ramon Lawrence

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Game designers have the challenging task of building games that engage players to spend their time and money on the game. There are an infinite number of game variations and design choices, and it is hard to systematically determine game design choices that will have positive experiences for players. In this work, we demonstrate how multi-arm bandits can be used to automatically explore game design variations to achieve improved player metrics. The advantage of multi-arm bandits is that they allow for continuous experimentation and variation, intrinsically converge to the best solution, and require no special infrastructure to use beyond allowing minor game variations to be deployed to users for evaluation. A user study confirms that applying multi-arm bandits was successful in determining the preferred game variation with highest play time metrics and can be a useful technique in a game designer's toolkit.

Keywords: Game design, multi-arm bandit, design exploration and data mining, player metric optimization and analytics.

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Authors: Wen-Jye Shyr, Chia-Ming Lin, Hung-Yun Feng

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The purpose of this study was to develop an energy management system for university campuses based on the Internet of Things (IoT) technique. The proposed IoT technique based on WebAccess is used via network browser Internet Explore and applies TCP/IP protocol. The case study of IoT for lighting energy usage management system was proposed. Structure of proposed IoT technique included perception layer, equipment layer, control layer, application layer and network layer.

Keywords: Energy management, IoT technique, Sensor, WebAccess

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Authors: I. Cano-Aguilera, B. E. Rubio-Campos, G. De la Rosa, A. F. Aguilera-Alvarado

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Mining tailings represent a generating source of rich heavy metal material with a potential danger the public health and the environment, since these metals, under certain conditions, can leach and contaminate aqueous systems that serve like supplying potable water sources. The strategy for this work is based on the observation, experimentation and the simulation that can be obtained by binding real answers of the hydrodynamic behavior of metals leached from mining tailings, and the applied mathematics that provides the logical structure to decipher the individual effects of the general physicochemical phenomenon. The case of study presented herein focuses on mining tailings deposits located in Monte San Nicolas, Guanajuato, Mexico, an abandoned mine. This was considered the contamination source that under certain physicochemical conditions can favor the metal leaching, and its transport towards aqueous systems. In addition, the cartography, meteorology, geology and the hydrodynamics and hydrological characteristics of the place, will be helpful in determining the way and the time in which these systems can interact. Preliminary results demonstrated that arsenic presents a great mobility, since this one was identified in several superficial aqueous systems of the micro watershed, as well as in sediments in concentrations that exceed the established maximum limits in the official norms. Also variations in pH and potential oxide-reduction were registered, conditions that favor the presence of different species from this element its solubility and therefore its mobility.

Keywords: Arsenic, mining tailings, transport.

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Authors: H. T. Barney, G. C. Low

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The design of distributed systems involves dividing the system into partitions (or components) and then allocating these partitions to physical nodes. There have been several techniques proposed for both the partitioning and allocation processes. These existing techniques suffer from a number of limitations including lack of support for replication. Replication is difficult to use effectively but has the potential to greatly improve the performance of a distributed system. This paper presents a new technique technique for allocating objects in order to improve performance in a distributed system that supports replication. The performance of the proposed technique is demonstrated and tested on an example system. The performance of the new technique is compared with the performance of an existing technique in order to demonstrate both the validity and superiority of the new technique when developing a distributed system that can utilise object replication.

Keywords: Allocation, Distributed Systems, Replication.

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Authors: Aneta Oblouková, Eva Vítková

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The article deals with the issue of water and sewerage charge rate prices in the Czech Republic. The research is specifically focused on the analysis of the development of the average prices of water and sewerage charge rate in the Czech Republic in 1994-2021 and on the validation of the chosen methodology relevant for the prediction of the development of the average prices of water and sewerage charge rate in the Czech Republic. The research is based on data collection. The data for this research were obtained from the Czech Statistical Office. The aim of the paper is to validate the relevance of the mathematical linear trend estimate technique for the calculation of the predicted average prices of water and sewerage charge rates. The real values of the average prices of water and sewerage charge rates in the Czech Republic in 1994-2018 were obtained from the Czech Statistical Office and were converted into a mathematical equation. The same type of real data was obtained from the Czech Statistical Office for 2019-2021. Prediction of the average prices of water and sewerage charge rates in the Czech Republic in 2019-2021 was also calculated using a chosen method – a linear trend estimation technique. The values obtained from the Czech Statistical Office and the values calculated using the chosen methodology were subsequently compared. The research result is a validation of the chosen mathematical technique to be a suitable technique for this research.

Keywords: Czech Republic, linear trend estimation, price prediction, water and sewerage charge rate.

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Authors: Ileladewa Adeoye Abiodun, Cheng Wai Khuen

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Multi-Agent Systems (MAS) emerged in the pursuit to improve our standard of living, and hence can manifest complex human behaviors such as communication, decision making, negotiation and self-organization. The Social Network Services (SNSs) have attracted millions of users, many of whom have integrated these sites into their daily practices. The domains of MAS and SNS have lots of similarities such as architecture, features and functions. Exploring social network users- behavior through multiagent model is therefore our research focus, in order to generate more accurate and meaningful information to SNS users. An application of MAS is the e-Auction and e-Rental services of the Universiti Cyber AgenT(UniCAT), a Social Network for students in Universiti Tunku Abdul Rahman (UTAR), Kampar, Malaysia, built around the Belief- Desire-Intention (BDI) model. However, in spite of the various advantages of the BDI model, it has also been discovered to have some shortcomings. This paper therefore proposes a multi-agent framework utilizing a modified BDI model- Belief-Desire-Intention in Dynamic and Uncertain Situations (BDIDUS), using UniCAT system as a case study.

Keywords: Distributed Data Mining, Multi-Agent Systems, Preference-Based, SNS.

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Authors: W. Kultangwattana, K. Somkantha, P. Phuangsuwan

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This paper presents a technique for diagnosis of the abdominal aorta aneurysm in magnetic resonance imaging (MRI) images. First, our technique is designed to segment the aorta image in MRI images. This is a required step to determine the volume of aorta image which is the important step for diagnosis of the abdominal aorta aneurysm. Our proposed technique can detect the volume of aorta in MRI images using a new external energy for snakes model. The new external energy for snakes model is calculated from Law-s texture. The new external energy can increase the capture range of snakes model efficiently more than the old external energy of snakes models. Second, our technique is designed to diagnose the abdominal aorta aneurysm by Bayesian classifier which is classification models based on statistical theory. The feature for data classification of abdominal aorta aneurysm was derived from the contour of aorta images which was a result from segmenting of our snakes model, i.e., area, perimeter and compactness. We also compare the proposed technique with the traditional snakes model. In our experiment results, 30 images are trained, 20 images are tested and compared with expert opinion. The experimental results show that our technique is able to provide more accurate results than 95%.

Keywords: Adbominal Aorta Aneurysm, Bayesian Classifier, Snakes Model, Texture Feature.

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

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Among many factors affecting the stability of mining excavations, rock-bursts and tremors play a special role. These dynamic loads occur practically always and have different sources of generation. The most important of them is the commonly used mining technique, which disintegrates a certain area of the rock mass not only in the area of the planned mining, but also creates waves that significantly exceed this area affecting the structural elements. In this work it is analysed the consequences of dynamic loads over the structural elements in an underground room and pillar mine to avoid roof instabilities. With this end, dynamic loads were evaluated through in situ and laboratory tests and simulated with numerical modelling. Initially, the geotechnical characterization of all materials was carried out by mean of large-scale tests. Then, drill holes were done on the roof of the mine and were monitored to determine possible discontinuities in it. Three seismic stations and a triaxial accelerometer were employed to measure the vibrations from blasting tests, establish the dynamic behaviour of roof and pillars and develop the transmission laws. At last, computer simulations by FLAC3D software were done to check the effect of vibrations on the stability of the roofs. The study shows that in-situ tests have a greater reliability than laboratory samples because of eliminating the effect of heterogeneities, that the pillars work decreasing the amplitude of the vibration around them, and that the tensile strength of a beam and depending on its span is overcome with waves in phase and delayed. The obtained transmission law allows designing a blasting which guarantees safety and prevents the risk of future failures.

Keywords: Dynamic modelling, long term instability risks, room and pillar, seismic collapse.

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Authors: A. Greco, N. Mammone, F.C. Morabito, M.Versaci

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This paper is mainly concerned with the application of a novel technique of data interpretation to the characterization and classification of measurements of plasma columns in Tokamak reactors for nuclear fusion applications. The proposed method exploits several concepts derived from soft computing theory. In particular, Artifical Neural Networks have been exploited to classify magnetic variables useful to determine shape and position of the plasma with a reduced computational complexity. The proposed technique is used to analyze simulated databases of plasma equilibria based on ITER geometry configuration. As well as demonstrating the successful recovery of scalar equilibrium parameters, we show that the technique can yield practical advantages compares with earlier methods.

Keywords: Tokamak, sensors, artificial neural network.

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Authors: Besa Muslimi, Miriam A. M. Capretz, Jagath Samarabandu

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Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.

Keywords: fuzzy rule extraction, fuzzy systems, knowledgeacquisition, pattern recognition, artificial neural networks.

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

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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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Authors: Ali Shatnawi

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Signal processing applications which are iterative in nature are best represented by data flow graphs (DFG). In these applications, the maximum sampling frequency is dependent on the topology of the DFG, the cyclic dependencies in particular. The determination of the iteration bound, which is the reciprocal of the maximum sampling frequency, is critical in the process of hardware implementation of signal processing applications. In this paper, a novel technique to compute the iteration bound is proposed. This technique is different from all previously proposed techniques, in the sense that it is based on the natural flow of tokens into the DFG rather than the topology of the graph. The proposed algorithm has lower run-time complexity than all known algorithms. The performance of the proposed algorithm is illustrated through analytical analysis of the time complexity, as well as through simulation of some benchmark problems.

Keywords: Data flow graph, Iteration period bound, Rateoptimalscheduling, Recursive DSP algorithms.

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Authors: M. Lakshmi, J. Senthil Kumar

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Digital cameras to reduce cost, use an image sensor to capture color images. Color Filter Array (CFA) in digital cameras permits only one of the three primary (red-green-blue) colors to be sensed in a pixel and interpolates the two missing components through a method named demosaicking. Captured data is interpolated into a full color image and compressed in applications. Color interpolation before compression leads to data redundancy. This paper proposes a new Vector Quantization (VQ) technique to construct a VQ codebook with Differential Evolution (DE) Algorithm. The new technique is compared to conventional Linde- Buzo-Gray (LBG) method.

Keywords: Color Filter Array (CFA), Biorthogonal Wavelet, Vector Quantization (VQ), Differential Evolution (DE).

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Authors: Walaa M.Abd-Elhafiez, Wajeb Gharibi

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In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into the edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique that is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio.

Keywords: Image compression, color image, Q-coder, quantization, edge-detection.

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Authors: Ismahafezi Ismail, Mohd Shahrizal Sunar

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The motion of a realistic 3D humanoid character is very important especially for the industries developing computer animations and games. However, this type of motion is seen with a very complex dimensional data as well as body position, orientation, and joint rotation. Integrated Style Motion Editor (ISME), on the other hand, is a method used to alter the 3D humanoid motion capture data utilised in computer animation and games development. Therefore, this study was carried out with the purpose of demonstrating a method that is able to manipulate and deform different motion styles by integrating Key Pose Deformation Technique and Trajectory Control Technique. This motion editing method allows the user to generate new motions from the original motion capture data using a simple interface control. Unlike the previous method, our method produces a realistic humanoid motion style in real time.

Keywords: Computer animation, humanoid motion, motion capture, motion editing.

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Authors: Pavel Turcaj, Yuri I. Abramovich, Gordon J. Frazer

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We introduce an adaptive technique for the joint mitigation of transients and continuous-wave radio-frequency co-channel interference (CW RFI) in high-frequency (HF) over-the-horizon radars (OTHRs). The performance of this technique is illustrated using data from an operational surface-wave radar (SECAR) and from recent experimental trials with sky-wave (SW) and sky-wave–line-of-sight (SKYLOS) HF OTHRs.

Keywords:

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Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: Road accident, machine learning, support vector machines.

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Authors: Matthias Dehmer, Frank Emmert Streib, Alexander Mehler, Jürgen Kilian, Max Mühlhauser

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Due to the tremendous amount of information provided by the World Wide Web (WWW) developing methods for mining the structure of web-based documents is of considerable interest. In this paper we present a similarity measure for graphs representing web-based hypertext structures. Our similarity measure is mainly based on a novel representation of a graph as linear integer strings, whose components represent structural properties of the graph. The similarity of two graphs is then defined as the optimal alignment of the underlying property strings. In this paper we apply the well known technique of sequence alignments for solving a novel and challenging problem: Measuring the structural similarity of generalized trees. In other words: We first transform our graphs considered as high dimensional objects in linear structures. Then we derive similarity values from the alignments of the property strings in order to measure the structural similarity of generalized trees. Hence, we transform a graph similarity problem to a string similarity problem for developing a efficient graph similarity measure. We demonstrate that our similarity measure captures important structural information by applying it to two different test sets consisting of graphs representing web-based document structures.

Keywords: Graph similarity, hierarchical and directed graphs, hypertext, generalized trees, web structure mining.

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Authors: S. Al-Sowayan, K. L. Lear

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A new technique to quantify the differential mode delay (DMD) in multimode fiber (MMF) is been presented. The technique measures DMD based on angular launch and measurements of the difference in modal delay using variable apertures at the fiber face. The result of the angular spatial filtering revealed less excitation of higher order modes when the laser beam is filtered at higher angles. This result would indicate that DMD profiles would experience a data pattern dependency.

Keywords: Fiber measurements, Fiber optic communications

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Authors: M. Salehi, R. Tavakkoli-Moghaddam

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Selection of a project among a set of possible alternatives is a difficult task that the decision maker (DM) has to face. In this paper, by using a fuzzy TOPSIS technique we propose a new method for a project selection problem. After reviewing four common methods of comparing investment alternatives (net present value, rate of return, benefit cost analysis and payback period) we use them as criteria in a TOPSIS technique. First we calculate the weight of each criterion by a pairwise comparison and then we utilize the improved TOPSIS assessment for the project selection.

Keywords: Fuzzy Theory, Pairwise Comparison, ProjectSelection, TOPSIS Technique.

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Authors: Amitava Chakraborty, Sudip Kumar De, Ranjan Dasgupta

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Point quad tree is considered as one of the most common data organizations to deal with spatial data & can be used to increase the efficiency for searching the point features. As the efficiency of the searching technique depends on the height of the tree, arbitrary insertion of the point features may make the tree unbalanced and lead to higher time of searching. This paper attempts to design an algorithm to make a nearly balanced quad tree. Point pattern analysis technique has been applied for this purpose which shows a significant enhancement of the performance and the results are also included in the paper for the sake of completeness.

Keywords: Algorithm, Height balanced tree, Point patternanalysis, Point quad tree.

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Authors: Ahmad. A. Kardan, Amir Narimani, Foozhan Ataiefard

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Recommender Systems have been developed to provide contents and services compatible to users based on their behaviors and interests. Due to information overload in online discussion forums and users diverse interests, recommending relative topics and threads is considered to be helpful for improving the ease of forum usage. In order to lead learners to find relevant information in educational forums, recommendations are even more needed. We present a hybrid thread recommender system for MOOC forums by applying social network analysis and association rule mining techniques. Initial results indicate that the proposed recommender system performs comparatively well with regard to limited available data from users' previous posts in the forum.

Keywords: Association rule mining, hybrid recommender system, massive open online courses, MOOCs, social network analysis.

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Authors: Muhibul Haque Bhuyan, Farseem Mannan Mohammedy, Quazi Deen Mohd Khosru

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This paper presents the doping profile measurement and characterization technique for the pocket implanted nano scale n-MOSFET. Scanning capacitance microscopy and atomic force microscopy have been used to image the extent of lateral dopant diffusion in MOS structures. The data are capacitance vs. voltage measurements made on a nano scale device. The technique is nondestructive when imaging uncleaved samples. Experimental data from the published literature are presented here on actual, cleaved device structures which clearly indicate the two-dimensional dopant profile in terms of a spatially varying modulated capacitance signal. Firstorder deconvolution indicates the technique has much promise for the quantitative characterization of lateral dopant profiles. The pocket profile is modeled assuming the linear pocket profiles at the source and drain edges. From the model, the effective doping concentration is found to use in modeling and simulation results of the various parameters of the pocket implanted nano scale n-MOSFET. The potential of the technique to characterize important device related phenomena on a local scale is also discussed.

Keywords: Linear Pocket Profile, Pocket Implanted n-MOSFET, Scanning Capacitance Microscope, Atomic Force Microscope.

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Authors: Panprapa Yongtrakul, Punyaphat Sirithanabadeekul, Pakjira Siriphan

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Background: The thread lift technique has become popular because it is less invasive, requires a shorter operation, less downtime, and results in fewer postoperative complications. The advantage of the technique is that the thread can be inserted under the skin without the need for long incisions. Currently, there are a lot of thread lift techniques with respect to the specific types of thread used on specific areas, such as the mid-face, lower face, or neck area. Objective: To review the thread lift technique for specific areas according to type of thread, patient selection, and how to match the most appropriate to the patient. Materials and Methods: A literature review technique was conducted by searching PubMed and MEDLINE, then compiled and summarized. Result: We have divided our protocols into two sections: Protocols for short suture, and protocols for long suture techniques. We also created 3D pictures for each technique to enhance understanding and application in a clinical setting. Conclusion: There are advantages and disadvantages to short suture and long suture techniques. The best outcome for each patient depends on appropriate patient selection and determining the most suitable technique for the defect and area of patient concern.

Keywords: Thread lift, thread lift method, thread lift technique, thread lift procedure, threading.

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Authors: S. Prabha, K. Duraiswamy, J. Indhumathi

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Search engine plays an important role in internet, to retrieve the relevant documents among the huge number of web pages. However, it retrieves more number of documents, which are all relevant to your search topics. To retrieve the most meaningful documents related to search topics, ranking algorithm is used in information retrieval technique. One of the issues in data miming is ranking the retrieved document. In information retrieval the ranking is one of the practical problems. This paper includes various Page Ranking algorithms, page segmentation algorithms and compares those algorithms used for Information Retrieval. Diverse Page Rank based algorithms like Page Rank (PR), Weighted Page Rank (WPR), Weight Page Content Rank (WPCR), Hyperlink Induced Topic Selection (HITS), Distance Rank, Eigen Rumor, Distance Rank Time Rank, Tag Rank, Relational Based Page Rank and Query Dependent Ranking algorithms are discussed and compared.

Keywords: Information Retrieval, Web Page Ranking, search engine, web mining, page segmentations.

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Authors: Mountassar Maamoun, Abdelhamid Meraghni, Abdelhalim Benbelkacem, Daoud Berkani

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This paper describes an efficient hardware implementation of a new technique for interfacing the data exchange between the microprocessor-based systems and the external devices. This technique, based on the use of software/hardware system and a reduced physical address, enlarges the interfacing capacity of the microprocessor-based systems, uses the Direct Memory Access (DMA) to increases the frequency of the new bus, and improves the speed of data exchange. While using this architecture in microprocessor-based system or in computer, the input of the hardware part of our system will be connected to the bus system, and the output, which is a new bus, will be connected to an external device. The new bus is composed of a data bus, a control bus and an address bus. A Xilinx Integrated Software Environment (ISE) 7.1i has been used for the programmable logic implementation.

Keywords: Interfacing, Software/hardware System, CPLD, programmable logic, DMA.

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Authors: Maria Paula Santos, Ana Lucas

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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: Critical success factors, data quality, data quality management, Delphi, Q-Sort.

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Authors: I. R. Farah, I. B. Ismail, M. B. Ahmed

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The huge development of new technologies and the apparition of open communication system more and more sophisticated create a new challenge to protect digital content from piracy. Digital watermarking is a recent research axis and a new technique suggested as a solution to these problems. This technique consists in inserting identification information (watermark) into digital data (audio, video, image, databases...) in an invisible and indelible manner and in such a way not to degrade original medium-s quality. Moreover, we must be able to correctly extract the watermark despite the deterioration of the watermarked medium (i.e attacks). In this paper we propose a system for watermarking satellite images. We chose to embed the watermark into frequency domain, precisely the discrete wavelet transform (DWT). We applied our algorithm on satellite images of Tunisian center. The experiments show satisfying results. In addition, our algorithm showed an important resistance facing different attacks, notably the compression (JEPG, JPEG2000), the filtering, the histogram-s manipulation and geometric distortions such as rotation, cropping, scaling.

Keywords: Digital data watermarking, Spatial Database, Satellite images, Discrete Wavelets Transform (DWT).

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: Data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse.

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Authors: P. Valdiviezo, G. Riofrio, R. Reategui

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This article describes the implementation of an intelligent agent that provides recommendations for educational resources in a virtual learning environment (VLE). It aims to support pending (undeveloped) student learning activities. It begins by analyzing the proposed VLE data model entities in the recommender process. The pending student activities are then identified, which constitutes the input information for the agent. By using the attribute-based recommender technique, the information can be processed and resource recommendations can be obtained. These serve as support for pending activity development in the course. To integrate this technique, we used an ontology. This served as support for the semantic annotation of attributes and recommended files recovery.

Keywords: Learning activities, educational resource, recommender agent, recommendation technique, ontology.

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