Search results for: government (big) data

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

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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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Authors: Qin Ding, Jim Gasvoda

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Clustering is the process of subdividing an input data set into a desired number of subgroups so that members of the same subgroup are similar and members of different subgroups have diverse properties. Many heuristic algorithms have been applied to the clustering problem, which is known to be NP Hard. Genetic algorithms have been used in a wide variety of fields to perform clustering, however, the technique normally has a long running time in terms of input set size. This paper proposes an efficient genetic algorithm for clustering on very large data sets, especially on image data sets. The genetic algorithm uses the most time efficient techniques along with preprocessing of the input data set. We test our algorithm on both artificial and real image data sets, both of which are of large size. The experimental results show that our algorithm outperforms the k-means algorithm in terms of running time as well as the quality of the clustering.

Keywords: Clustering, data mining, genetic algorithm, image data.

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Authors: Ashly Joseph

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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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Authors: R. Nedunchezhian, K. Anbumani

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A big organization may have multiple branches spread across different locations. Processing of data from these branches becomes a huge task when innumerable transactions take place. Also, branches may be reluctant to forward their data for centralized processing but are ready to pass their association rules. Local mining may also generate a large amount of rules. Further, it is not practically possible for all local data sources to be of the same size. A model is proposed for discovering valid rules from different sized data sources where the valid rules are high weighted rules. These rules can be obtained from the high frequency rules generated from each of the data sources. A data source selection procedure is considered in order to efficiently synthesize rules. Support Equalization is another method proposed which focuses on eliminating low frequency rules at the local sites itself thus reducing the rules by a significant amount.

Keywords: Association rules, multiple data stores, synthesizing, valid rules.

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Authors: Jincheol Han, Hyunsun Ju, Jonghoon Chun

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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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Authors: B. O. Diyaolu, O. O. Oyerinde

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This study examined the effect of sexuality education training programs on the knowledge and practice of sexual risk behavior among secondary school adolescents in Ibadan North Local Government area of Oyo State. A total of 105 students were sampled from two schools in the Local Government area. 70 students constituted the experimental group while 35 constituted the control group. Pretest-Posttest control group quasi-experimental design was adopted. A self-developed questionnaire was used to test participants’ knowledge and practice of sexual risk behavior before and after the training (α = .62, .82 and .74). Analysis indicated a significant effect of sexuality education training on participants’ knowledge and practice of sexual risk behavior, a significant gender difference in knowledge of sexual risk behavior but no significant age and gender difference in the practice of sexual risk behavior. It was thus concluded that sexuality education should be taught in schools and emphasized at homes with no age or gender restrictions.

Keywords: Early adolescent, health risk, sexual risk behavior, sexuality education.

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Authors: Entisar A. Elgmati

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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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Authors: Muñoz-Sanchez, Victor Manuel, Perez-Flores, Antonio Manuel

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The main objective of this paper is to establish the relationship between models of state organization and the various types of collective identity expressed by the Spanish. The question of nationalism and identity ascription in Spain has always been a topic of special importance due to the presence in that country of territories where the population emits very different opinions of nationalist sentiment than the rest of Spain. The current situation of sovereignty challenge of Catalonia to the central government exemplifies the importance of the subject matter. In order to analyze this process of interrelation, we use a secondary data mining by applying the multiple correspondence analysis technique (MCA). As a main result a typology of four types of expression of collective identity based on models of State organization are shown, which are connected with the party position on this issue.

Keywords: Models of organization of the state, nationalism, collective identity, Spain, political parties.

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

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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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Authors: Elin Cahyaningsih, Dana Indra Sensuse, Wahyu Catur Wibowo, Sofiyanti Indriasari

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Bureaucracy reform program drives Indonesian government to change their management to enhance their organizational performance. Information technology became one of strategic plan that organization tried to improve. Knowledge management system is one of information system that supporting knowledge management implementation in government which categorized as people perspective, because this system has high dependency in human interaction and participation. Strategic plan for developing knowledge management system can be determine using some of information system strategic methods. This research conducted to define type of strategic method of information system, stage of activity each method, strength and weakness. Literature review methods used to identify and classify strategic methods of information system, differentiate method type, categorize common activities, strength and weakness. Result of this research are determine and compare six strategic information system methods, Balanced Scorecard and Risk Analysis believe as common strategic method that usually used and have the highest excellence strength.

Keywords: Knowledge management system, balanced scorecard, five force, risk analysis, gap analysis, value chain analysis, SWOT analysis.

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Authors: M. R. Aghaebrahimi, S. H. Zahiri, M. Amiri

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In this paper a data miner based on the learning automata is proposed and is called LA-miner. The LA-miner extracts classification rules from data sets automatically. The proposed algorithm is established based on the function optimization using learning automata. The experimental results on three benchmarks indicate that the performance of the proposed LA-miner is comparable with (sometimes better than) the Ant-miner (a data miner algorithm based on the Ant Colony optimization algorithm) and CNZ (a well-known data mining algorithm for classification).

Keywords: Data mining, Learning automata, Classification rules, Knowledge discovery.

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Authors: A. Krishna Veni, R.Geetha

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Wireless Sensor Networks (WSNs) are suitable for many scenarios in the real world. The retrieval of data is made efficient by the data aggregation techniques. Many techniques for the data aggregation are offered and most of the existing schemes are not energy efficient and secure. However, the existing techniques use the traditional clustering approach where there is a delay during the packet transmission since there is no proper scheduling. The presented system uses the Velocity Energy-efficient and Link-aware Cluster-Tree (VELCT) scheme in which there is a Data Collection Tree (DCT) which improves the lifetime of the network. The VELCT scheme and the construction of DCT reduce the delay and traffic. The network lifetime can be increased by avoiding the frequent change in cluster topology. Secure and Efficient Transmission of Aggregated data (SETA) improves the security of the data transmission via the trust value of the nodes prior the aggregation of data. Since SETA considers the data only from the trustworthy nodes for aggregation, it is more secure in transmitting the data thereby improving the accuracy of aggregated data.

Keywords: Aggregation, lifetime, network security, wireless sensor network.

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Authors: M. Amir Abas, M. Dahlui

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This paper presents the development of analysis tools for Home Agriculture project. The tools are required for monitoring the condition of greenhouse which involves two components: measurement hardware and data analysis engine. Measurement hardware is functioned to measure environment parameters such as temperature, humidity, air quality, dust and etc while analysis tool is used to analyse and interpret the integrated data against the condition of weather, quality of health, irradiance, quality of soil and etc. The current development of the tools is completed for off-line data recorded technique. The data is saved in MMC and transferred via ZigBee to Environment Data Manager (EDM) for data analysis. EDM converts the raw data and plot three combination graphs. It has been applied in monitoring three months data measurement for irradiance, temperature and humidity of the greenhouse..

Keywords: Monitoring, Environment, Greenhouse, Analysis tools

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Authors: Emad T. Khalaf, Norrozila Sulaiman

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Many researchers are working on information hiding techniques using different ideas and areas to hide their secrete data. This paper introduces a robust technique of hiding secret data in image based on LSB insertion and RSA encryption technique. The key of the proposed technique is to encrypt the secret data. Then the encrypted data will be converted into a bit stream and divided it into number of segments. However, the cover image will also be divided into the same number of segments. Each segment of data will be compared with each segment of image to find the best match segment, in order to create a new random sequence of segments to be inserted then in a cover image. Experimental results show that the proposed technique has a high security level and produced better stego-image quality.

Keywords: steganography; LSB Matching; RSA Encryption; data segments

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Authors: S. Sarumathi, N. Shanthi

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Due to the fast and flawless technological innovation there is a tremendous amount of data dumping all over the world in every domain such as Pattern Recognition, Machine Learning, Spatial Data Mining, Image Analysis, Fraudulent Analysis, World Wide Web etc., This issue turns to be more essential for developing several tools for data mining functionalities. The major aim of this paper is to analyze various tools which are used to build a resourceful analytical or descriptive model for handling large amount of information more efficiently and user friendly. In this survey the diverse tools are illustrated with their extensive technical paradigm, outstanding graphical interface and inbuilt multipath algorithms in which it is very useful for handling significant amount of data more indeed.

Keywords: Classification, Clustering, Data Mining, Machine learning, Visualization.

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Authors: Hamed Najafi, Ghasem Nikjou

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Nowadays, there is an increasing attention to the resources scarcity issues. Because of failure in present patterns in the field of the allocation of exhaustible resources between generations and the challenges related to economic justice supply, it is supposed, to present a pattern from the Islamic perspective in this essay. By using content analysis of religious texts, we conclude that governments should remove the gap which is exists between the per capita income of the poor and their minimum consumption (necessary consumption). In order to preserve the exhaustible resources for poor people) not for all), between all generations, government should invest exhaustible resources on endless resources according to Hartwick’s criteria and should spend these benefits for poor people. But, if benefits did not cover the gap between minimum consumption and per capita income of poor levels in one generation, in this case, the government is responsible for covering this gap through the direct consumption of exhaustible resources. For an exact answer to this question, ‘how much of exhaustible resources should expense to maintain justice between generations?’ The theoretical and mathematical modeling has been used and proper function has been provided. The consumption pattern is presented for economic policy makers in Muslim countries, and non-Muslim even, it can be useful.

Keywords: Exhaustible resources, Islamic justice, intergenerational justice, distribution of resources, Hartwick Criteria.

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Authors: Shigeaki Sakurai, Makino Kyoko, Shigeru Matsumoto

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This paper proposes a method that predicts attractive evaluation objects. In the learning phase, the method inductively acquires trend rules from complex sequential data. The data is composed of two types of data. One is numerical sequential data. Each evaluation object has respective numerical sequential data. The other is text sequential data. Each evaluation object is described in texts. The trend rules represent changes of numerical values related to evaluation objects. In the prediction phase, the method applies new text sequential data to the trend rules and evaluates which evaluation objects are attractive. This paper verifies the effect of the proposed method by using stock price sequences and news headline sequences. In these sequences, each stock brand corresponds to an evaluation object. This paper discusses validity of predicted attractive evaluation objects, the process time of each phase, and the possibility of application tasks.

Keywords: Trend rule, frequent pattern, numerical sequential data, text sequential data, evaluation object.

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: Genetic data, Pinzgau cattle, supervised learning.

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Authors: Azhar Rauf, Sareer Badshah, Shah Khusro

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This paper analyzes different techniques of the fine grained security of relational databases for the two variables-data accessibility and inference. Data accessibility measures the amount of data available to the users after applying a security technique on a table. Inference is the proportion of information leakage after suppressing a cell containing secret data. A row containing a secret cell which is suppressed can become a security threat if an intruder generates useful information from the related visible information of the same row. This paper measures data accessibility and inference associated with row, cell, and column level security techniques. Cell level security offers greatest data accessibility as it suppresses secret data only. But on the other hand, there is a high probability of inference in cell level security. Row and column level security techniques have least data accessibility and inference. This paper introduces cell plus innocent security technique that utilizes the cell level security method but suppresses some innocent data to dodge an intruder that a suppressed cell may not necessarily contain secret data. Four variations of the technique namely cell plus innocent 1/4, cell plus innocent 2/4, cell plus innocent 3/4, and cell plus innocent 4/4 respectively have been introduced to suppress innocent data equal to 1/4, 2/4, 3/4, and 4/4 percent of the true secret data inside the database. Results show that the new technique offers better control over data accessibility and inference as compared to the state-of-theart security techniques. This paper further discusses the combination of techniques together to be used. The paper shows that cell plus innocent 1/4, 2/4, and 3/4 techniques can be used as a replacement for the cell level security.

Keywords: Fine Grained Security, Data Accessibility, Inference, Row, Cell, Column Level Security.

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Authors: Sujala.D.Shetty, S.Vadivel, Sakshi Vaghella

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Data mining is the process of sifting through large volumes of data, analyzing data from different perspectives and summarizing it into useful information. One of the widely used desktop applications for data mining is the Weka tool which is nothing but a collection of machine learning algorithms implemented in Java and open sourced under the General Public License (GPL). A web service is a software system designed to support interoperable machine to machine interaction over a network using SOAP messages. Unlike a desktop application, a web service is easy to upgrade, deliver and access and does not occupy any memory on the system. Keeping in mind the advantages of a web service over a desktop application, in this paper we are demonstrating how this Java based desktop data mining application can be implemented as a web service to support data mining across the internet.

Keywords: desktop application, Weka mining, web service

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Authors: Chanisada Choosuk, Napisporn Memongkol Runchana Sinthavalai, Fareeda Lambensah

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The objective of this research is to explore the role of actors at the local level in managing the Pre-hospital Emergency Medical Service (EMS) system in Thailand. The research method was done through documentary research, individual interviews, and one forum conducted in each province. This paper uses the case of three provinces located in three regions in Thailand including; Ubon Ratchathani (North-eastern region), Lampang (Northern Region), and Songkhla (Southern Region). The result shows that, recently, the role of the local government in being the service provider for their local people is increasingly concerned. In identifying the key success factors towards the EMS system, it includes; (i) the local executives- vision and influence that the decisions made by them, for both PAO (Provincial Administration Organisation (PAO) and TAO (Tambon Administration Organisation), is vital to address the overall challenges in EMS development, (ii) the administrative system through reforming their working style create the flexibility in running the EMS task, (iii) the network-based management among different agencies at the local level leads to the better EMS practices, and (iv) the development in human resource is very vital in delivering the effective services.

Keywords: Local governments, Management, Emergency Medical Services (EMS), Thailand

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: Local nonlinear estimation, LWPR algorithm, Online training method.

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Authors: Siyathorn Khunon, Thanawit Buafai

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This paper aims to investigate management of beach safety with a focus on tourist drownings in Samui. The data collected in this investigation will then lead to the proposal of a practical management model suitable for use in Samui. Qualitative research was conducted in the following manner: nine stakeholders from local government organizations and tourism businesses were interviewed in-depth. Additionally, a best practice case study from Phuket was applied to analyze beach safety. Twelve foreign tourists were also interviewed. Then, a focus group comprised of 32 people was used to determine practical solutions for enhancing tourists’ safety on the beach in Samui. A steering committee to coordinate between public and private organizations was proposed to manage and enhance tourists’ safety. A practical model is proposed to increase the safety level of tourists in Samui

Keywords: Beach safety, drowning, tourists, Samui.

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Authors: Aravind Kumar

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The high terrains of Garhwal (Uttarakhand) Himalaya are the niches of a number of rare and endemic plant species of great therapeutic importance. However, the wild flora of the area is still under a constant threat due to rapid upsurge in human interferences, especially through multifarious tourism growth and peri-urban encroachments. After getting the status of a ‘Special State’ of the country since its inception in the year 2000, this newly borne State led to very rapid infrastructural growth and development. Consequently, its townships started expanding in an unmanaged way grabbing nearby agricultural lands and forest areas into peri-urban landscapes. Simultaneously, a boom in tourism and pilgrimage in the state and the infrastructural facilities raised by the government for tourists/pilgrims are destroying its biodiversity. Field survey revealed 242 plant species of therapeutic significance naturally growing in the area and being utilized by local inhabitants as traditional medicines. On conservation scale, 6 species (2.2%) were identified as critically endangered, 19 species (7.1%) as the endangered ones, 8 species (3.0%) under rare category, 17 species (6.4%) as threatened and 14 species (5.2%) as vulnerable. The Government of India has brought mega-biodiversity hot spots of the state under Biosphere Reserve, National Parks, etc. restricting all kinds of human interferences; however, the two most sacred shrines of Hindus and Sikhs viz. Shri Badrinath and Shri Hemkunt Sahib, and two great touristic attractions viz. Valley of Flowers and Auli-Joshimath Skiing Track oblige the government to maintain equilibrium between entries of visitors vis-à-vis biodiversity conservation in high terrains of Uttarakhand Himalaya.

Keywords: Biodiversity conservation, ethno-botany, Garhwal (Uttarakhand) Himalaya, peri-urban encroachment, pilgrimage and tourism.

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Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: Web log data, web user profile, user interest, noise web data learning, machine learning.

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Authors: Walid Cherif

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Data mining has, over recent years, seen big advances because of the spread of internet, which generates everyday a tremendous volume of data, and also the immense advances in technologies which facilitate the analysis of these data. In particular, classification techniques are a subdomain of Data Mining which determines in which group each data instance is related within a given dataset. It is used to classify data into different classes according to desired criteria. Generally, a classification technique is either statistical or machine learning. Each type of these techniques has its own limits. Nowadays, current data are becoming increasingly heterogeneous; consequently, current classification techniques are encountering many difficulties. This paper defines new measure functions to quantify the resemblance between instances and then combines them in a new approach which is different from actual algorithms by its reliability computations. Results of the proposed approach exceeded most common classification techniques with an f-measure exceeding 97% on the IRIS Dataset.

Keywords: Data mining, knowledge discovery, machine learning, similarity measurement, supervised classification.

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Authors: Yasmin Nanabhay

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The paper scrutinizes the literature on accountability and non-accountability, and then presents an analysis of a South African case which demonstrated consequences of a lack of accountability. Ethical conduct displayed by members of the public sector is integral to creating a sustainable democratic government, which upholds the constitutional tenets of accountability, transparency and professional ethicality. Furthermore, a true constitutional democracy emphasises and advocates the notion of service leadership that nurtures public participation and engages with citizens in a positive manner. Ethical conduct and accountability in the public sector earns public trust; hence these are key principles in good governance. Yet, in the years since the advent of democracy in South Africa, the government has been plagued by rampant corruption and mal-administration by public officials and politicians in leadership positions. The control measures passed by government in an attempt to ensure ethicality and accountability within the public sector include codes of ethics, rules of conduct and the enactment of legislation. These are intended to shape the mindset of members of the public sector, with the ultimate aim of an efficient, effective, ethical, responsive and accountable public service. The purpose of the paper is to analyse control systems and accountability within the public sector and to present reasons for non-accountability by means of a selected case study. The selected case study is the corruption trial of Jackie Selebi, who served as National Commissioner of the South African Police Service but was dismissed from the post. The reasons for non-accountability in the public sector as well as recommendations based on the findings to enhance accountability will be undertaken. The case study demonstrates the experience and impact of corruption and/or mal-administration, as a result of a lack of accountability, which has contributed to the increasing loss of confidence in political leadership in the country as elsewhere in the world. The literature is applied to the erstwhile National Commissioner of the South African Police Service and President of Interpol, as a case study of non-accountability.

Keywords: Public sector, public accountability, internal control, oversight mechanisms, non-compliance, corruption, mal-administration.

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Authors: Nittaya Kerdprasop, Kittisak Kerdprasop

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Data mining (DM) is the process of finding and extracting frequent patterns that can describe the data, or predict unknown or future values. These goals are achieved by using various learning algorithms. Each algorithm may produce a mining result completely different from the others. Some algorithms may find millions of patterns. It is thus the difficult job for data analysts to select appropriate models and interpret the discovered knowledge. In this paper, we describe a framework of an intelligent and complete data mining system called SUT-Miner. Our system is comprised of a full complement of major DM algorithms, pre-DM and post-DM functionalities. It is the post-DM packages that ease the DM deployment for business intelligence applications.

Keywords: Business intelligence, data mining, functionalprogramming, intelligent system.

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Authors: S. Sarumathi, N. Shanthi, M. Sharmila

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Clustering in data mining is an unsupervised learning technique of aggregating the data objects into meaningful groups such that the intra cluster similarity of objects are maximized and inter cluster similarity of objects are minimized. Over the past decades several clustering tools were emerged in which clustering algorithms are inbuilt and are easier to use and extract the expected results. Data mining mainly deals with the huge databases that inflicts on cluster analysis and additional rigorous computational constraints. These challenges pave the way for the emergence of powerful expansive data mining clustering softwares. In this survey, a variety of clustering tools used in data mining are elucidated along with the pros and cons of each software.

Keywords: Cluster Analysis, Clustering Algorithms, Clustering Techniques, Association, Visualization.

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Authors: Ahmed S. Khan, Amin Karim

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During the past several decades, the economy of each nation has been significantly affected by globalization and technology. Government regulations and private sector standards affect a majority of world trade. Countries have been working together to establish international standards in almost every field. As a result, workers in all sectors need to have an understanding of standards. Engineering and technology students must not only possess an understanding of engineering standards and applicable government codes, but also learn to apply them in designing, developing, testing and servicing products, processes and systems. Accreditation Board for Engineering & Technology (ABET) criteria for engineering and technology education require students to learn and apply standards in their class projects. This paper is a follow-up of a 2006-2009 NSF initiative awarded to IEEE to help develop tutorials and case study modules for students and encourage standards education at college campuses. It presents the findings of a faculty/institution survey conducted through various U.S.-based listservs representing the major engineering and technology disciplines. The intent of the survey was to the gauge the status of use of standards and regulations in engineering and technology coursework and to identify benchmark practices. In light of survey findings, recommendations are made to standards development organizations, industry, and academia to help enhance the use of standards in engineering and technology curricula.

Keywords: Standards, regulations, ABET, IEEE, engineering and technology curricula.

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