Search results for: linked open data

Authors: Janet B. Badong-Badilla

Abstract:

In Jesuit universities, laypersons, who come from the same or different faith backgrounds or traditions, are considered as collaborators in mission. The Jesuits themselves support the contributions of the lay partners in realizing the mission of the Society of Jesus and recognize the important role that they play in education. This study aims to investigate and generate particular notions and understandings of lived experiences of being a lay partner in Jesuit universities in the Philippines, particularly those involved in higher education. Using the qualitative approach as introduced by grounded theorist Barney Glaser, the lay partners’ concept of being a partner, as lived in higher education, is generated systematically from the data collected in the field primarily through in-depth interviews, field notes and observations. Glaser’s constant comparative method of analysis of data is used going through the phases of open coding, theoretical coding, and selective coding from memoing to theoretical sampling to sorting and then writing. In this study, Glaser’s grounded theory as a methodology will provide a substantial insight into and articulation of the layperson’s actual experience of being a partner of the Jesuits in education. Such articulation provides a phenomenological approach or framework to an understanding of the meaning and core characteristics of Jesuit-Lay partnership in Jesuit educational institution of higher learning in the country. This study is expected to provide a framework or model for lay partnership in academic institutions that have the same practice of having lay partners in mission.

Keywords: Grounded theory, Jesuit mission in higher education, lay partner, lived experience.

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Authors: M. Raciti Castelli, A. Fedrigo, E. Benini

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A multiple-option analytical model for the evaluation of the energy performance and distribution of aerodynamic forces acting on a vertical-axis Darrieus wind turbine depending on both rotor architecture and operating conditions is presented. For this purpose, a numerical algorithm, capable of generating the desired rotor conformation depending on design geometric parameters, is coupled to a Single/Double-Disk Multiple-Streamtube Blade Element – Momentum code. Both single and double-disk configurations are analyzed and model predictions are compared to literature experimental data in order to test the capability of the code for predicting rotor performance. Effective airfoil characteristics based on local blade Reynolds number are obtained through interpolation of literature low-Reynolds airfoil databases. Some corrections are introduced inside the original model with the aim of simulating also the effects of blade dynamic stall, rotor streamtube expansion and blade finite aspect ratio, for which a new empirical relationship to better fit the experimental data is proposed. In order to predict also open field rotor operation, a freestream wind shear profile is implemented, reproducing the effect of atmospheric boundary layer.

Keywords: Wind turbine, BE-M, dynamic stall, streamtube expansion, airfoil finite aspect ratio

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Authors: Stuart Henry, Philip Morrow, John Winder, Bryan Scotney

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The stereophotogrammetry modality is gaining more widespread use in the clinical setting. Registration and visualization of this data, in conjunction with conventional 3D volumetric image modalities, provides virtual human data with textured soft tissue and internal anatomical and structural information. In this investigation computed tomography (CT) and stereophotogrammetry data is acquired from 4 anatomical phantoms and registered using the trimmed iterative closest point (TrICP) algorithm. This paper fully addresses the issue of imaging artifacts around the stereophotogrammetry surface edge using the registered CT data as a reference. Several iterative algorithms are implemented to automatically identify and remove stereophotogrammetry surface edge outliers, improving the overall visualization of the combined stereophotogrammetry and CT data. This paper shows that outliers at the surface edge of stereophotogrammetry data can be successfully removed automatically.

Keywords: Data cleansing, stereophotogrammetry.

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Authors: A. Mohamed Mydeen, Pallapa Venkataram

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The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.

Keywords: Generic knowledge representation, toolkit, toolroom, pervasive computing.

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Authors: Yi Chao Huang, Yu Ling Liao, Chiu Shuang Lin

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A data cutting and sorting method (DCSM) is proposed to optimize the performance of data mining. DCSM reduces the calculation time by getting rid of redundant data during the data mining process. In addition, DCSM minimizes the computational units by splitting the database and by sorting data with support counts. In the process of searching for the relationship between metabolic syndrome and lifestyles with the health examination database of an electronics manufacturing company, DCSM demonstrates higher search efficiency than the traditional Apriori algorithm in tests with different support counts.

Keywords: Data mining, Data cutting and sorting method, Apriori algorithm, Metabolic syndrome

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Authors: Jay Patel

Abstract:

This research is about investigating the ‘image’ of the city, and asks whether this ‘image’ holds any significance that can be changed. Kevin Lynch in the book ‘The Image of the City’ develops a framework that breaks down the city’s image into five physical elements. These elements (Paths, Edge, Nodes, Districts, and Landmarks), according to Lynch assess the legibility of the urbanscapes, that emerged from his perception-based study in three different cities (New Jersey, Los Angeles, and Boston) in the USA. The aim of this research is to investigate whether Lynch’s framework can be applied within an Indian context or not. If so, what are the possibilities and whether the imageability of Indian cities can be depicted through the Lynch’s physical elements or it demands an extension to the framework by either adding or subtracting a physical attribute. For this research project, the walled city of Jaipur was selected, as it is considered one of the futuristic designed cities of all time in India. The other significant reason for choosing Jaipur was that it is a historically planned city with solid historical, touristic and local importance; allowing an opportunity to understand the application of Lynch's elements to the city's image. In other words, it provides an opportunity to examine how the disadvantages of a city's implicit program (its relics of bygone eras) can be converted into assets by improving the imageability of the city. To obtain data, a structured semi-open ended interview method was chosen. The reason for selecting this method explicitly was to gain qualitative data from the users rather than collecting quantitative data from closed-ended questions. This allowed in-depth understanding and applicability of Kevin Lynch’s framework while assessing what needs to be added. The interviews were conducted in Jaipur that yielded varied inferences that were different from the expected learning outcomes, highlighting the need for extension on Lynch’s physical elements to achieve city’s image. Whilst analyzing the data, there were few attributes found that defined the image of Jaipur. These were categorized into two: a Physical aspect (streets and arcade entities, natural features, temples and temporary/informal activities) and Associational aspects (History, culture and tradition, medium of help in wayfinding, and intangible aspects).

Keywords: Imageability, Kevin Lynch, People’s Perception, associational aspects, physical aspects.

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Authors: Md Abdullah Al Faruque

Abstract:

A very large percentage of bridge failures are attributed to scouring around bridge piers and this directly influences public safety. Experiments are carried out in a 12-m long rectangular open channel flume made of transparent tempered glass. A 300 mm thick bed made up of sand particles is leveled horizontally to create the test bed and a 50 mm hollow plastic cylinder is used as a model bridge pier. Tests are carried out with varying flow depths and velocities. Data points of various scour parameters such as scour depth, width, and length are collected based on different flow conditions and visual observations of changes in the stream bed downstream the bridge pier are also made as the scour progresses. Result shows that all three major flow characteristics (flow depth, Froude number and densimetric Froude number) have one way or other affect the scour profile.

Keywords: Bridge pier scour, densimetric Froude number, flow depth, Froude Number, sand.

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: Data mining, hybrid storage system, recurrent neural network, support vector machine.

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Authors: R. Suresh, Pavan Kumar Nimmagadda, Ming Zo Tan, Shane Hart, Sharp Ugwuocha

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Polycrystalline diamond compact (PDC) drill bits are extensively used in the oil and gas industry as well as the mining industry. Industry engineers continually improve upon PDC drill bit designs and hydraulic conditions. Optimized injection nozzles play a key role in improving the drilling performance and efficiency of these ever changing PDC drill bits. In the first part of this study, computational fluid dynamics (CFD) modelling is performed to investigate the hydrodynamic characteristics of drilling fluid flow around the PDC drill bit. An Open-source CFD software – OpenFOAM simulates the flow around the drill bit, based on the field input data. A specifically developed console application integrates the entire CFD process including, domain extraction, meshing, and solving governing equations and post-processing. The results from the OpenFOAM solver are then compared with that of the ANSYS Fluent software. The data from both software programs agree. The second part of the paper describes the parametric study of the PDC drill bit nozzle to determine the effect of parameters such as number of nozzles, nozzle velocity, nozzle radial position and orientations on the flow field characteristics and bit washing patterns. After analyzing a series of nozzle configurations, the best configuration is identified and recommendations are made for modifying the PDC bit design.

Keywords: ANSYS Fluent, computational fluid dynamics, nozzle configuration, OpenFOAM, PDC dill bit.

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Authors: Marco Raciti Castelli, Ernesto Benini

Abstract:

This paper presents a model for the evaluation of energy performance and aerodynamic forces acting on a small straight-bladed Darrieus-type vertical axis wind turbine depending on blade geometrical section. It consists of an analytical code coupled to a solid modeling software, capable of generating the desired blade geometry based on the desired blade design geometric parameters. Such module is then linked to a finite volume commercial CFD code for the calculation of rotor performance by integration of the aerodynamic forces along the perimeter of each blade for a full period of revolution.After describing and validating the computational model with experimental data, the results of numerical simulations are proposed on the bases of two candidate airfoil sections, that is a classical symmetrical NACA 0021 blade profile and the recently developed DU 06-W-200 non-symmetric and laminar blade profile.Through a full CFD campaign of analysis, the effects of blade geometrical section on angle of attack are first investigated and then the overall rotor torque and power are analyzed as a function of blade azimuthal position, achieving a numerical quantification of the influence of airfoil geometry on overall rotor performance.

Keywords: Wind turbine, NACA 0021, DU 06-W-200.

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, data mining, Hadoop, Map Reduce, MongoDB, NoSQL.

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

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Wireless sensor network can be applied to both abominable and military environments. A primary goal in the design of wireless sensor networks is lifetime maximization, constrained by the energy capacity of batteries. One well-known method to reduce energy consumption in such networks is data aggregation. Providing efcient data aggregation while preserving data privacy is a challenging problem in wireless sensor networks research. In this paper, we present privacy-preserving data aggregation scheme for additive aggregation functions. The Cluster-based Private Data Aggregation (CPDA)leverages clustering protocol and algebraic properties of polynomials. It has the advantage of incurring less communication overhead. The goal of our work is to bridge the gap between collaborative data collection by wireless sensor networks and data privacy. We present simulation results of our schemes and compare their performance to a typical data aggregation scheme TAG, where no data privacy protection is provided. Results show the efficacy and efficiency of our schemes.

Keywords: Aggregation, Clustering, Query Processing.

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

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

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

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Authors: Faruq A. Al-Omari, Nabeel I. Al-Fayoumi

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In this paper, we present a new algorithm for clustering data in large datasets using image processing approaches. First the dataset is mapped into a binary image plane. The synthesized image is then processed utilizing efficient image processing techniques to cluster the data in the dataset. Henceforth, the algorithm avoids exhaustive search to identify clusters. The algorithm considers only a small set of the data that contains critical boundary information sufficient to identify contained clusters. Compared to available data clustering techniques, the proposed algorithm produces similar quality results and outperforms them in execution time and storage requirements.

Keywords: Data clustering, Data mining, Image-mapping, Pattern discovery, Predictive analysis.

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Authors: Roselyn A. Maaño

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Eyes are an essential and conspicuous organ of the human body. Human eyes are outward and inward portals of the body that allows to see the outside world and provides glimpses into ones inner thoughts and feelings. Inevitable blindness and visual impairments may results from eye-related disease, trauma, or congenital or degenerative conditions that cannot be corrected by conventional means. The study emphasizes innovative tools that will serve as an aid to the blind and visually impaired (VI) individuals. The researchers fabricated a prototype that utilizes the Microsoft Kinect for Windows and Arduino microcontroller board. The prototype facilitates advanced gesture recognition, voice recognition, obstacle detection and indoor environment navigation. Open Computer Vision (OpenCV) performs image analysis, and gesture tracking to transform Kinect data to the desired output. A computer vision technology device provides greater accessibility for those with vision impairments.

Keywords: Algorithms, Blind, Computer Vision, Embedded Systems, Image Analysis.

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

Abstract:

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

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

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Authors: Sahar Nasrolahi, Mahdi Nikdast, Mehrdad Mahdavi Boroujerdi

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The purpose of semantic web research is to transform the Web from a linked document repository into a distributed knowledge base and application platform, thus allowing the vast range of available information and services to be more efficiently exploited. As a first step in this transformation, languages such as OWL have been developed. Although fully realizing the Semantic Web still seems some way off, OWL has already been very successful and has rapidly become a defacto standard for ontology development in fields as diverse as geography, geology, astronomy, agriculture, defence and the life sciences. The aim of this paper is to classify key concepts of Semantic Web as well as introducing a new practical approach which uses these concepts to outperform Word Wide Web.

Keywords: Semantic Web, Ontology, OWL, Microformat, Word Wide Web.

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Authors: Sadık Kartal

Abstract:

This study was carried out to determine the feedback from the primary school headmasters on in-service training activities. 384 primary school headmasters were asked to give feedback on the in-service training facilities organized by the Ministry of Education through an open –ended question. The study group was formed by 359 primary school headmasters who attended “Management Skills" seminars which were organized in March, April and May in the extent of 2006 In-service Training Facilities Plan by the Ministry of Education and were also volunteers to give feedback on the inservice training activities. The qualitative research method was used in the analysis of the data since the primary school headmasters gave written feedback on the in-service training activities. Having analyzed the feedback, certain categories were formed by coding it. Certain frequencies and percentages were determined according to the codes. It was made obvious that the primary school headmasters benefitted from those facilities by sharing their experiences, problems and their possible solutions mutually

Keywords: In-service training, primary school principles, educates.

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Authors: Tazibt W., Mialhe P.

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This paper presents ageing experiments controlled by the evolution of junction parameters. The deterioration of the device is related to high injection effects which modified the transport mechanisms in the space charge region of the junction. Physical phenomena linked to the degradation of junction parameters that affect the devices reliability are reported and discussed. We have used the method based on numerical analysis of experimental current-voltage characteristic of the junction, in order to extract the electrical parameters. The simultaneous follow-up of the evolutions of the series resistance and of the transition voltage allow us to introduce a new parameter for reliability evaluation.

Keywords: High injection, junction, parameters, reliability

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Authors: Jasmine Adela Mutang, Alfred Chan Huan Zhi, Norzihan Ayub, Chua Bee Seok, Rosnah Ismail, Ooh Siew Ling, Uichol Kim

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This study aims to investigate how much both son and daughter trust their father and what are the underlying reasons they trust their father. The results revealed five main reasons why Malaysian adolescents trust their father. Those reasons are related to the role of father, father-child relationship, father-s characteristics, father-s nurturing nature and father-s attitude and behavior. A total of 1022 students (males = 241, females = 781) from one of public university in Sabah, Malaysia participated in the study. The participants completed open-ended questionnaires developed by Kim (2008), asking how much the adolescents trust their father, and the reasons why they trust their father. The data was analysed by using the indigenous psychology method proposed by [1] Findings of this study revealed the pattern of trust towards father for both Malaysian male and female adolescents. The results contributed new information about Malaysian adolescents- trust towards their father form the indigenous context. The implications of finding will be discussed.

Keywords: Adolescent, Father-child relationship, Indigenous Psychology, Trust.

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

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

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

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Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

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The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool.

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

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

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

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Authors: Jia-Yu Dai, Don-Lin Yang, Jungpin Wu, Ming-Chuan Hung

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In an era of knowledge explosion, the growth of data increases rapidly day by day. Since data storage is a limited resource, how to reduce the data space in the process becomes a challenge issue. Data compression provides a good solution which can lower the required space. Data mining has many useful applications in recent years because it can help users discover interesting knowledge in large databases. However, existing compression algorithms are not appropriate for data mining. In [1, 2], two different approaches were proposed to compress databases and then perform the data mining process. However, they all lack the ability to decompress the data to their original state and improve the data mining performance. In this research a new approach called Mining Merged Transactions with the Quantification Table (M2TQT) was proposed to solve these problems. M2TQT uses the relationship of transactions to merge related transactions and builds a quantification table to prune the candidate itemsets which are impossible to become frequent in order to improve the performance of mining association rules. The experiments show that M2TQT performs better than existing approaches.

Keywords: Association rule, data mining, merged transaction, quantification table.

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Authors: Abubakar Uba Ibrahim, Ibrahim Haruna Shanono

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Smart metering and demand response are gaining ground in industrial and residential applications. Smart Appliances have been given concern towards achieving Smart home. The success of Smart grid development relies on the successful implementation of Information and Communication Technology (ICT) in power sector. Smart Appliances have been the technology under development and many new contributions to its realization have been reported in the last few years. The role of ICT here is to capture data in real time, thereby allowing bi-directional flow of information/data between producing and utilization point; that lead a way for the attainment of Smart appliances where home appliances can communicate between themselves and provide a self-control (switch on and off) using the signal (information) obtained from the grid. This paper depicts the background on ICT for smart appliances paying a particular attention to the current technology and identifying the future ICT trends for load monitoring through which smart appliances can be achieved to facilitate an efficient smart home system which promote demand response program. This paper grouped and reviewed the recent contributions, in order to establish the current state of the art and trends of the technology, so that the reader can be provided with a comprehensive and insightful review of where ICT for smart appliances stands and is heading to. The paper also presents a brief overview of communication types, and then narrowed the discussion to the load monitoring (Non-intrusive Appliances Load Monitoring ‘NALM’). Finally, some future trends and challenges in the further development of the ICT framework are discussed to motivate future contributions that address open problems and explore new possibilities.

Keywords: Communication technology between appliances, demand response, load monitoring, smart appliances and smart grid.

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Authors: I. Abuiziah, A. Oulhaj, K. Sebari, D. Ouazar

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This paper presents the problem of modeling and simulating of transient phenomena in conveying pipeline systems based on the rigid column and full elastic methods. Transient analysis is important and one of the more challenging and complicated flow problem in the design and the operation of water pipeline systems. Transient can produce large pressure forces and rapid fluid acceleration into a water pipeline system, these disturbances may result in device failures, system fatigue or pipe ruptures, and even the dirty water intrusion. Several methods have been introduced and used to analyze transient flow, an accurate analysis and suitable protection devices should be used to protect water pipeline systems. The fourth-order Runge-Kutta method has been used to solve the dynamic and continuity equations in the rigid column method, while the characteristics method used to solve these equations in the full elastic method. The results obtained provide that the model is an efficient tool for flow transient analysis and provide approximately identical results by using these two methods. Moreover; using the simple surge tank ”open surge tank” reduces the unfavorable effects of transients.

Keywords: Elastic method, Flow transient, Open surge tank, Pipeline, Protection devices, Numerical model, Rigid column method.

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Authors: C. A. Barros, Ana P. Barroso

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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.

Keywords: Automotive industry, Industry 4.0, internet of things, IATF 16949:2016, measurement system analysis.

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

Abstract:

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

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

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Authors: Sedigheh Mirzaei S., Debasis Sengupta

Abstract:

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

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

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