Search results for: distributed association rule mining

Authors: J. Suneetha, Vijayalaxmi

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Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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Authors: Byung Ho Jung, Ji Eun Shin, Dong Hoon Lim

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Rhipe that integrates R and Hadoop environment made it possible to process and analyze massive amounts of data using a distributed processing environment. In this paper, we implemented multiple regression analysis using Rhipe with various data sizes of actual data. Experimental results for comparing the performance of our Rhipe with stats and biglm packages available on bigmemory, showed that our Rhipe was more fast than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases. We also compared the computing speeds of pseudo-distributed and fully-distributed modes for configuring Hadoop cluster. The results showed that fully-distributed mode was faster than pseudo-distributed mode, and computing speeds of fully-distributed mode were faster as the number of data nodes increases.

Keywords: big data, Hadoop, Parallel regression analysis, R, Rhipe

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Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

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This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

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Authors: Hosein Rahmati

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The Fatimid government was one of the powerful Shiite governments that was formed in 297 AH in the Islamic Maghreb based on Ismaili ideas and played an important role in promoting the culture and civilization of the Islamic world. Ismaili is one of the Shiite sects that has its own beliefs and teachings. This research seeks to find out which of the Ismaili beliefs and teachings were considered by the Fatimid political government and which the Fatimid government paid serious attention to highlighting. The present study, based on library sources and descriptive-analytical method, has concluded that the Ismaili doctrinal foundations, especially the doctrine of Imamate, are essential elements in the formation and continuation of the Fatimid rule. Their goals were approaching.

Keywords: Fatimid rule, The Ismaili, The Islamic Maghreb, Imamate

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Authors: Fahad Hanash Alzahrani

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This paper describes some recent advances in a quickly developing area of data storing and processing based on Data Warehouses and Data Mining techniques, which are associated with software, hardware, data mining algorithms and visualisation techniques having common features for any specific problems and tasks of their implementation.

Keywords: data warehouse, data mining, knowledge discovery in databases, on-line analytical processing

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Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala

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Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.

Keywords: opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet

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Authors: Ishak Suleiman, Ahmad Kamsani Samingan, Yeoh Chun Yeow, Abdul Aziz Bin Abdul Rahman

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In this paper, we evaluate the benefits of distributed 4x4 MIMO LTE downlink systems compared to that of the co-located 4x4 MIMO LTE downlink system. The performance evaluation was carried out experimentally by using Wireless Open-Access Research Platform (WARP), where the comparison between the 4x4 MIMO LTE transmission downlink system in distributed and co-located techniques was examined. The measured Error Vector Magnitude (EVM) results showed that the distributed technique achieved better system performance compared to the co-located arrangement.

Keywords: multiple-input-multiple-output (MIMO), distributed MIMO, co-located MIMO, LTE

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Authors: Lakshya Bhat, Anubhav Shrivastava, Shivarudraswamy

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There has been a formidable interest in the area of Distributed Generation in recent times. A wide number of loads are addressed by Distributed Generators and have better efficiency too. The major disadvantage in Distributed Generation is voltage control- is highlighted in this paper. The paper addresses voltage control at buses in IEEE 14 Bus system by regulating reactive power. An analysis is carried out by selecting the most optimum location in placing the Distributed Generators through load flow analysis and seeing where the voltage profile rises. Matlab programming is used for simulation of voltage profile in the respective buses after introduction of DG’s. A tolerance limit of +/-5% of the base value has to be maintained.To maintain the tolerance limit , 3 methods are used. Sensitivity analysis of 3 methods for voltage control is carried out to determine the priority among the methods.

Keywords: distributed generators, distributed system, reactive power, voltage control, sensitivity analysis

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Authors: Iliya Musa Adamu

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This paper seeks to develop an expert system that would troubleshoot computer network and evaluate the network system performance so as to reduce the workload on technicians and increase the efficiency and effectiveness of solutions proffered to computer network problems. The platform of the system was developed using ASP.NET, whereas the codes are implemented in Visual Basic and integrated with SQL Server 2005. The knowledge base was represented using production rule, whereas the searching method that was used in developing the network troubleshooting expert system is the forward-chaining-rule-based-system. This software tool offers the advantage of providing an immediate solution to most computer network problems encountered by computer users.

Keywords: expert system, forward chaining rule based system, network, troubleshooting

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Authors: Shivarudraswamy, Anubhav Shrivastava, Lakshya Bhat

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Distributed generation has indeed become a major area of interest in recent years. Distributed Generation can address large number of loads in a power line and hence has better efficiency over the conventional methods. However there are certain drawbacks associated with it, increase in voltage being the major one. This paper addresses the voltage control at the buses for an IEEE 30 bus system by regulating reactive power. For carrying out the analysis, the suitable location for placing distributed generators (DG) is identified through load flow analysis and seeing where the voltage profile is dipping. MATLAB programming is used to regulate the voltage at all buses within +/-5% of the base value even after the introduction of DG’s. Three methods for regulation of voltage are discussed. A sensitivity based analysis is later carried out to determine the priority among the various methods listed in the paper.

Keywords: distributed generators, distributed system, reactive power, voltage control

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Rebeca Ramirez Acosta, Sebastian Lenhoff

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Decision makers worldwide need to determine if the implementation of a new market mechanism will contribute to the sustainability and resilience of the power system. Due to smart grid technologies, new products in the distribution and transmission system can be traded; however, the impact of changing a market rule will differ between several regions. To test systematically those impacts, a market categorization has been compiled and organized in a smart grid market testing toolbox. This toolbox maps all actual energy products and sets the basis for running a co-simulation test with the new rule to be implemented. It will help to measure the impact of the new rule, based on the sustainable and resilience indicators.

Keywords: co-simulation, electricity market, smart grid market, market testing

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Authors: Harpreet Singh

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Finding relevant information on the World Wide Web is becoming highly challenging day by day. Web usage mining is used for the extraction of relevant and useful knowledge, such as user behaviour patterns, from web access log records. Web access log records all the requests for individual files that the users have requested from the website. Web usage mining is important for Customer Relationship Management (CRM), as it can ensure customer satisfaction as far as the interaction between the customer and the organization is concerned. Web usage mining is helpful in improving website structure or design as per the user’s requirement by analyzing the access log file of a website through a log analyzer tool. The focus of this paper is to enhance the accessibility and usability of a guitar selling web site by analyzing their access log through Deep Log Analyzer tool. The results show that the maximum number of users is from the United States and that they use Opera 9.8 web browser and the Windows XP operating system.

Keywords: web usage mining, web mining, log file, data mining, deep log analyzer

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Authors: Zhidong Zhang, Zhi-Chao Zhang

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This study investigated the structural validity of externalizing issues of Achenbach System of Empirically Based Assessment (ASEBA) via a Chinese sample. The externalizing problems consist of two sub-problems: rule-breaking behavior and aggressive behavior. The rule-breaking behavior consists of 17 items, and aggressive behavior consists of 18 items. The factor analysis model was used to examine the structure validity. For the rule breaking behavior, at the first step, the most items weighted with component 2. After the rotation, there was a clear weight on both component 1 and 2. For the aggressive behavior, at the first step, there was no clear picture about the components. After the rotation, two clusters of items were closer to component 1 and 2 respectively. It seemed that both rule breaking behavior issue and aggressive behavior issue suggested two components. Further studies should be done to examine both samples and structures of externalizing problems.

Keywords: confirmatory analysis, externalizing issue, structural validity, varimax rotations

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Authors: Saeid Jalilzadeh, Majid Pakdel

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The customer demand for better power quality and higher reliability has forced the power industry to use distributed generations (DGs) such as wind power and photo voltaic arrays. Islanding is a phenomenon occurs when a power grid becomes electrically isolated from the power system and the distribution system is energized by distributed generators. It is necessary to disconnect all distributed generators immediately after islanding occurrence. Therefore a DG system should have the capability to detect islanding phenomena. In this paper, a novel micro controller based relay for anti-islanding protection of a typical DG system is proposed. The simulation results using Proteus software verify the proper operation and effectiveness of the proposed protective relay.

Keywords: islanding, distributed generation (DG), protective relay, micro controller, proteus software

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Authors: Mohamed Haffar, Ramdane Djebarni, Russell Evans

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Despite a growth in literature on distributed leadership, the majority of studies are centred on large public organisations particularly within the health and education sectors. The purpose of this study is to fill the gap in the literature by exploring employee experiences of distributed leadership within two commercial consultancy SME businesses in the UK and USA. The aim of the study informed an exploratory method of research to gather qualitative data drawn from semi-structured interviews involving a sample of employees in each organisation. A series of broad, open questions were used to explore the employees’ experiences; evidence of distributed leadership; and extant barriers and practices in each organisation. Whilst some of our findings aligned with patterns and practices in the existing literature, it importantly discovered some emergent themes that have not previously been recognised in the previous studies. Our investigation identified that whilst distributed leadership was in evidence in both organisations, the interviewees’ experience reported that it was sporadic and inconsistent. Moreover, non-client focused projects were reported to be less important and distributed leadership was found to be inconsistent or non-existent.

Keywords: consultancy, distributed leadership, owner-manager, SME, entrepreneur

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Authors: Tarek Kandil, Ameen Ali

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Distributed generation (DG) has recently gained a lot of momentum in power industry due to market deregulation and environmental concerns. One of the most technical challenges facing DGs is islanding of distributed generators. The current industry practice is to disconnect all distributed generators immediately after the occurrence of islands within 200 to 350 ms after loss of main supply. To achieve such goal, each DG must be equipped with an islanding detection device. Frequency relays are one of the most commonly used loss of mains detection method. However, distribution utilities may be faced with concerns related to false operation of these frequency relays due to improper settings. The commercially available frequency relays are considering standard tight setting. This paper investigates some factors related to relays internal algorithm that contribute to their different operating responses. Further, the relay operation in the presence of multiple distributed at the same network is analyzed. Finally, the relay setting can be accurately determined based on these investigation and analysis.

Keywords: frequency relay, distributed generation, islanding detection, relay setting

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Authors: Ebrahim Taherzadeh, Helmi Z. M. Shafri, Kaveh Shahi

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One of the most important tasks in urban area remote sensing is detection of impervious surface (IS), such as building roof and roads. However, detection of IS in heterogeneous areas still remains as one of the most challenging works. In this study, detection of concrete roof using an object-oriented approach was proposed. A new rule-based classification was developed to detect concrete roof tile. The proposed rule-based classification was applied to WorldView-2 image. Results showed that the proposed rule has good potential to predict concrete roof material from WorldView-2 images with 85% accuracy.

Keywords: object-based, roof material, concrete tile, WorldView-2

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Authors: Peter Mc Coll, Alberto Caro, Chiara Gandolfo, Montserrat Labbe, Francisca Schnaidt, Michela Palazzi

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Self-esteem and emotional intelligence are variables that are related to people's nutritional status. Self-esteem may be at low levels in people living with obesity, while emotional intelligence can play an important role in the way people living with obesity cope. The objective of the study was to measure the association between self-esteem and emotional intelligence to nutritional status in adolescent population. Methodology: A cross-sectional study was carried out with 179 adolescent schoolchildren between 13 and 19 years old from a public school. The objective was to evaluate nutritional status; weight and height were measured by calculating the body mass index and Z score. Self-esteem was evaluated using the Coopersmith Self-esteem Inventory adapted by Brinkmann and Segure. Emotional intelligence was measured using the Emotional Quotient Inventory: short, by Bar On, adapted questionnaire, translated into Spanish by López Zafra. For statistical analysis: Pearson's Chi-square test, Pearson's correlation, and odd ratio calculation were used, with a p value at a significance level < 5%. Results: The study group was composed of 71% female and 29% male. The nutritional status was distributed as eutrophic 41.9%, overweight 20.1%, and obesity 21.1%. In relation to self-esteem, 44.1% presented low and very low levels, without differences by gender. Emotional intelligence was distributed: low 3.4%, medium 81%, and high 13.4% -no differences according to gender. The association between nutritional status (overweight and obesity) with low and very low self-esteem, an odds ratio of 2.5 (95% CI 1.12 – 5.59) was obtained with a p-value = 0.02. The correlation analysis between the intrapersonal sub-dimension emotional intelligence scores and the Z score of nutritional status presented a negative correlation of r = - 0.209 with a p-value < 0.005. The correlation between emotional intelligence subdimension stress management with Z score presented a positive correlation of r = 0.0161 with a p-value < 0.05. In conclusion, the group of adolescents studied had a high prevalence of overweight and obesity, a high prevalence of low self-esteem, and a high prevalence of average emotional intelligence. Overweight and obese adolescents were 2.5 times more likely to have low self-esteem. As overweight and obesity increase, self-esteem decreases, and the ability to manage stress increases.

Keywords: self-esteem, emotional intelligence, obesity, adolescent, nutritional status

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Authors: Tetsuro Saeki, Yuichi Kato, Shoutarou Mizuno

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STRIM (Statistical Test Rule Induction Method) has been proposed as a method to effectively induct if-then rules from the decision table which is considered as a sample set obtained from the population of interest. Its usefulness has been confirmed by simulation experiments specifying rules in advance, and by comparison with conventional methods. However, scope for future development remains before STRIM can be applied to the analysis of real-world data sets. The first requirement is to determine the size of the dataset needed for inducting true rules, since finding statistically significant rules is the core of the method. The second is to examine the capacity of rule induction from datasets with contaminated attribute values created by missing data and noise, since real-world datasets usually contain such contaminated data. This paper examines the first problem theoretically, in connection with the rule length. The second problem is then examined in a simulation experiment, utilizing the critical size of dataset derived from the first step. The experimental results show that STRIM is highly robust in the analysis of datasets with contaminated attribute values, and hence is applicable to realworld data.

Keywords: rule induction, decision table, missing data, noise

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Authors: Taşkın Deniz Yıldız, Mustafa Topaloğlu, Orhan Kural

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The right to operate a fairly long periods of prior periods and after the 3213 Mining Law has been observed to be shortened in Turkey. Permit the realization of business activities (or concession) requested the purchase of the mine operated "found mine" position, as well as the financial and technical capability to have the owner of the right to operate the mines as well as the principle of equality is important in terms of assessing the best way be. In particular, in this context, license fields "negligence" (downsizing) have noted that the current arrangement for all periods. However, in the period after 3213 Mining Act and a permit to operate more effectively within the framework of implementation of negligence is laid down.

Keywords: mining legislation, operation, permit, Turkey

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Authors: Toshiya Kawato, Shin-ichi Motomura, Masayuki Higashino, Takao Kawamura

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Storage for storing data is indispensable. If a storage capacity becomes insufficient, we can increase its capacity by adding new disks. It is, however, difficult to add a new disk when a budget is not enough. On the other hand, there are many unused idle resources such as used personal computers despite those use value. In order to solve those problems, used personal computers can be reused as storage. In this paper, we attempt to reuse used-PCs as a distributed storage. First, we list up the characteristics of used-PCs and design a storage system that utilizes its characteristics. Next, we experimentally implement an auto-construction system that automatically constructs a distributed storage environment in used-PCs.

Keywords: distributed storage, used personal computer, idle resource, auto construction

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Authors: Srushti Patil, Preethi Baligar, Gopalkrishna Joshi, Gururaj N. Bhadri

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In designing learning environments, the instructional strategies can be tailored to suit the learning style of an individual to ensure effective learning. In this study, the information shared on social media like Facebook is being used to predict learning style of a learner. Previous research studies have shown that Facebook data can be used to predict user personality. Users with a particular personality exhibit an inherent pattern in their digital footprint on Facebook. The proposed work aims to correlate the user's’ personality, predicted from Facebook data to the learning styles, predicted through questionnaires. For Millennial learners, Facebook has become a primary means for information sharing and interaction with peers. Thus, it can serve as a rich bed for research and direct the design of learning environments. The authors have conducted this study in an undergraduate freshman engineering course. Data from 320 freshmen Facebook users was collected. The same users also participated in the learning style and personality prediction survey. The Kolb’s Learning style questionnaires and Big 5 personality Inventory were adopted for the survey. The users have agreed to participate in this research and have signed individual consent forms. A specific page was created on Facebook to collect user data like personal details, status updates, comments, demographic characteristics and egocentric network parameters. This data was captured by an application created using Python program. The data captured from Facebook was subjected to text analysis process using the Linguistic Inquiry and Word Count dictionary. An analysis of the data collected from the questionnaires performed reveals individual student personality and learning style. The results obtained from analysis of Facebook, learning style and personality data were then fed into an automatic classifier that was trained by using the data mining techniques like Rule-based classifiers and Decision trees. This helps to predict the user personality and learning styles by analysing the common patterns. Rule-based classifiers applied for text analysis helps to categorize Facebook data into positive, negative and neutral. There were totally two models trained, one to predict the personality from Facebook data; another one to predict the learning styles from the personalities. The results show that the classifier model has high accuracy which makes the proposed method to be a reliable one for predicting the user personality and learning styles.

Keywords: educational data mining, Facebook, learning styles, personality traits

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Authors: Burcu Oralhan, Zeki Oralhan, Nilsun Sariyer, Kumru Uyar

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Data mining has been becoming more and more important and a wide range of applications in recent years. Data mining is the process of find hidden and unknown patterns in big data. One of the applied fields of data mining is Customer Relationship Management. Understanding the relationships between products and customers is crucial for every business. Customer Relationship Management is an approach to focus on customer relationship development, retention and increase on customer satisfaction. In this study, we made an application of a data mining methods in telecommunication customer relationship management side. This study aims to determine the customers profile who likely to leave the system, develop marketing strategies, and customized campaigns for customers. Data are clustered by applying classification techniques for used to determine the churners. As a result of this study, we will obtain knowledge from international telecommunication industry. We will contribute to the understanding and development of this subject in Customer Relationship Management.

Keywords: customer churn analysis, customer relationship management, data mining, telecommunication industry

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Authors: Diriba Dereje

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Background: Cardiac and renal disease are the most prevalent chronic non-communicable diseases (CNCD) affecting the community in a significant manner. The best and recommended method in halting CNCD is by working on prevention as early as possible. This is only possible if early surrogate markers are identified. As part of the stated solution, this study will identify an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Objective: The main aim of this study was to assess an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Methodology: Community based cross sectional study was conducted among 384 adult in Jimma town. A systematic sampling technique was used in selecting participants to the study. In searching for the possible association, binary and multivariate logistic regression and t-test was conducted. Finally, the association between microalbuminuria and lung function test was well stated in the form of figures and written description. Result and Conclusion: A significant association was found between microalbuminuria and different lung function test parameters.

Keywords: microalbuminuria, lung function, association, test

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Authors: Malinwo Estone Ayikpa

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Electric power systems are likely to operate with minimum losses and voltage meeting international standards. This is made possible generally by control actions provide by automatic voltage regulators, capacitors and transformers with on-load tap changer (OLTC). With the development of photovoltaic (PV) systems technology, their integration on distribution networks has increased over the last years to the extent of replacing the above mentioned techniques. The conventional analysis and simulation tools used for electrical networks are no longer able to take into account control actions necessary for studying distributed PV generation impact. This paper presents an unbalanced optimal power flow (OPF) model that minimizes losses with association of active power generation and reactive power control of single-phase and three-phase PV systems. Reactive power can be generated or absorbed using the available capacity and the adjustable power factor of the inverter. The unbalance OPF is formulated by current balance equations and solved by primal-dual interior point method. Several simulation cases have been carried out varying the size and location of PV systems and the results show a detailed view of the impact of PV distributed generation on distribution systems.

Keywords: distribution system, loss, photovoltaic generation, primal-dual interior point method

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Authors: Habila Nuhu

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Natural radionuclides in the environment can significantly contribute to human exposure to ionizing radiation. The knowledge of their levels in an environment can help the radiological protection agencies in policymaking. Measurement of natural radioactivity in major soils in the tin mining state of Perak Malaysia has been conducted using an HPGe detector. Seventy (70) soil samples were collected at widely distributed locations in the state. Six major soil types were sampled, and thirteen districts around the state were covered. The following were the results of the 226Ra (238U), 228Ra (232Th), and 40K activity in the soil samples: 226Ra (238U) has a mean activity concentration of 191.83 Bq kg⁻¹, more than five times the UNSCEAR reference limits of 35 Bq kg⁻¹. The mean activity concentration of 228Ra (232Th) with a value of 232.41 Bq kg⁻¹ is over seven times the UNSCEAR reference values of 30 Bq kg⁻¹. The average concentration of 40K activity was 275.24 Bq kg⁻¹, which was less than the UNSCEAR reference limit of 400 Bq Kg⁻¹. The range of external hazards index (Hₑₓ) values was from 1.03 to 2.05, while the internal hazards index (Hin) was from 1.48 to 3.08. The Hex and Hin should be less than one for minimal external and internal radiation threats as well as secure use of soil material for building construction. The Hₑₓ and Hin results generally indicate that while using the soil types and their derivatives as building materials in the study area, care must be taken.

Keywords: activity concentration, hazard index, soil samples, tin mining

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Authors: Andrew Hall, Paul Clarkson

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Climate change is predicted to increase the number of extreme weather events intensifying the strain on Railway Earthworks. This paper describes the use of Distributed Rayleigh Sensing to monitor low frequency activity on a vulnerable earthworks sectionprone to landslides alongside a railway line in Northern Spain. The vulnerable slope is instrumented with conventional slope stability sensors allowing an assessment to be conducted of the application of Distributed Rayleigh Sensing as an earthwork condition monitoring tool to enhance the resilience of railway networks.

Keywords: condition monitoring, railway earthworks, distributed rayleigh sensing, climate change

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Authors: Benhamouda Sara, Guezouli Larbi

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Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.

Keywords: distributed information retrieval, relevance, server selection, collection selection

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Authors: Rokhmatul Insani, Hira Laksmiwati Soemitro

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Business Intelligence is a methodology that exploits the data to produce information and knowledge systematically, business intelligence can support the decision-making process. Some methods in business intelligence are data warehouse and data mining. A data warehouse can store historical data from transactional data. For data modelling in data warehouse, we apply dimensional modelling by Kimball. While data mining is used to extracting patterns from the data and get insight from the data. Data mining has many techniques, one of which is segmentation. For profiling of telecommunication customer, we use customer segmentation according to customer’s usage of services, customer invoice and customer payment. Customers can be grouped according to their characteristics and can be identified the profitable customers. We apply K-Means Clustering Algorithm for segmentation. The input variable for that algorithm we use RFM (Recency, Frequency and Monetary) model. All process in data mining, we use tools IBM SPSS modeller.

Keywords: business intelligence, customer segmentation, data warehouse, data mining

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