Search results for: data management.
8438 DIVAD: A Dynamic and Interactive Visual Analytical Dashboard for Exploring and Analyzing Transport Data
Authors: Tin Seong Kam, Ketan Barshikar, Shaun Tan
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The advances in location-based data collection technologies such as GPS, RFID etc. and the rapid reduction of their costs provide us with a huge and continuously increasing amount of data about movement of vehicles, people and goods in an urban area. This explosive growth of geospatially-referenced data has far outpaced the planner-s ability to utilize and transform the data into insightful information thus creating an adverse impact on the return on the investment made to collect and manage this data. Addressing this pressing need, we designed and developed DIVAD, a dynamic and interactive visual analytics dashboard to allow city planners to explore and analyze city-s transportation data to gain valuable insights about city-s traffic flow and transportation requirements. We demonstrate the potential of DIVAD through the use of interactive choropleth and hexagon binning maps to explore and analyze large taxi-transportation data of Singapore for different geographic and time zones.Keywords: Geographic Information System (GIS), MovementData, GeoVisual Analytics, Urban Planning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23918437 Gene Expression Data Classification Using Discriminatively Regularized Sparse Subspace Learning
Authors: Chunming Xu
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Sparse representation which can represent high dimensional data effectively has been successfully used in computer vision and pattern recognition problems. However, it doesn-t consider the label information of data samples. To overcome this limitation, we develop a novel dimensionality reduction algorithm namely dscriminatively regularized sparse subspace learning(DR-SSL) in this paper. The proposed DR-SSL algorithm can not only make use of the sparse representation to model the data, but also can effective employ the label information to guide the procedure of dimensionality reduction. In addition,the presented algorithm can effectively deal with the out-of-sample problem.The experiments on gene-expression data sets show that the proposed algorithm is an effective tool for dimensionality reduction and gene-expression data classification.Keywords: sparse representation, dimensionality reduction, labelinformation, sparse subspace learning, gene-expression data classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14508436 Framework for Spare Inventory Management
Authors: Eman M. Wahba, Noha M. Galal, Khaled S. El-Kilany
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Spare parts inventory management is one of the major areas of inventory research. Analysis of recent literature showed that an approach integrating spare parts classification, demand forecasting, and stock control policies is essential; however, adapting this integrated approach is limited. This work presents an integrated framework for spare part inventory management and an Excel based application developed for the implementation of the proposed framework. A multi-criteria analysis has been used for spare classification. Forecasting of spare parts- intermittent demand has been incorporated into the application using three different forecasting models; namely, normal distribution, exponential smoothing, and Croston method. The application is also capable of running with different inventory control policies. To illustrate the performance of the proposed framework and the developed application; the framework is applied to different items at a service organization. The results achieved are presented and possible areas for future work are highlighted.Keywords: Demand forecasting, intermittent demand, inventory management, integrated approach, spare parts, spare part classification
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 65768435 Determining Cluster Boundaries Using Particle Swarm Optimization
Authors: Anurag Sharma, Christian W. Omlin
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Self-organizing map (SOM) is a well known data reduction technique used in data mining. Data visualization can reveal structure in data sets that is otherwise hard to detect from raw data alone. However, interpretation through visual inspection is prone to errors and can be very tedious. There are several techniques for the automatic detection of clusters of code vectors found by SOMs, but they generally do not take into account the distribution of code vectors; this may lead to unsatisfactory clustering and poor definition of cluster boundaries, particularly where the density of data points is low. In this paper, we propose the use of a generic particle swarm optimization (PSO) algorithm for finding cluster boundaries directly from the code vectors obtained from SOMs. The application of our method to unlabeled call data for a mobile phone operator demonstrates its feasibility. PSO algorithm utilizes U-matrix of SOMs to determine cluster boundaries; the results of this novel automatic method correspond well to boundary detection through visual inspection of code vectors and k-means algorithm.
Keywords: Particle swarm optimization, self-organizing maps, clustering, data mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17228434 Predictive Analysis for Big Data: Extension of Classification and Regression Trees Algorithm
Authors: Ameur Abdelkader, Abed Bouarfa Hafida
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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.
Keywords: Predictive analysis, big data, predictive analysis algorithms. CART algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10788433 Insight-Based Evaluation of a Map-based Dashboard
Authors: Anna Fredriksson Häägg, Charlotte Weil, Niklas Rönnberg
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Map-based dashboards are used for data exploration every day. The present study used an insight-based methodology for evaluating a map-based dashboard that presents research findings of water management and ecosystem services in the Amazon. In addition to analyzing the insights gained from using the dashboard, the evaluation method was compared to standardized questionnaires and task-based evaluations. The result suggests that the dashboard enabled the participants to gain domain-relevant, complex insights regarding the topic presented. Furthermore, the insight-based analysis highlighted unexpected insights and hypotheses regarding causes and potential adaptation strategies for remediation. Although time- and resource-consuming, the insight-based methodology was shown to have the potential of thoroughly analyzing how end users can utilize map-based dashboards for data exploration and decision making. Finally, the insight-based methodology is argued to evaluate tools in scenarios more similar to real-life usage, compared to task-based evaluation methods.
Keywords: Visual analytics, dashboard, insight-based evaluation, geographic visualization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4198432 Knowledge Management Applied to Forensic Sciences
Authors: Norma Rodrigues Gomes
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This paper presents initiatives of Knowledge Management (KM) applied to Forensic Sciences field, especially developed at the Forensic Science Institute of the Brazilian Federal Police. Successful projects, related to knowledge sharing, drugs analysis and environmental crimes, are reported in the KM perspective. The described results are related to: a) the importance of having an information repository, like a digital library, in such a multidisciplinary organization; b) the fight against drug dealing and environmental crimes, enabling the possibility to map the evolution of crimes, drug trafficking flows, and the advance of deforestation in Amazon rain forest. Perspectives of new KM projects under development and studies are also presented, tracing an evolution line of the KM view at the Forensic Science Institute.Keywords: Business Intelligence, Digital Library, Forensic Science, Knowledge Management
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25008431 A Business-to-Business Collaboration System That Promotes Data Utilization While Encrypting Information on the Blockchain
Authors: Hiroaki Nasu, Ryota Miyamoto, Yuta Kodera, Yasuyuki Nogami
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To promote Industry 4.0 and Society 5.0 and so on, it is important to connect and share data so that every member can trust it. Blockchain (BC) technology is currently attracting attention as the most advanced tool and has been used in the financial field and so on. However, the data collaboration using BC has not progressed sufficiently among companies on the supply chain of the manufacturing industry that handle sensitive data such as product quality, manufacturing conditions, etc. There are two main reasons why data utilization is not sufficiently advanced in the industrial supply chain. The first reason is that manufacturing information is top secret and a source for companies to generate profits. It is difficult to disclose data even between companies with transactions in the supply chain. Blockchain mechanism such as Bitcoin using Public Key Infrastructure (PKI) requires plaintext to be shared between companies in order to verify the identity of the company that sent the data. Another reason is that the merits (scenarios) of collaboration data between companies are not specifically specified in the industrial supply chain. For these problems, this paper proposes a Business to Business (B2B) collaboration system using homomorphic encryption and BC technique. Using the proposed system, each company on the supply chain can exchange confidential information on encrypted data and utilize the data for their own business. In addition, this paper considers a scenario focusing on quality data, which was difficult to collaborate because it is top-secret. In this scenario, we show an implementation scheme and a benefit of concrete data collaboration by proposing a comparison protocol that can grasp the change in quality while hiding the numerical value of quality data.
Keywords: Business to business data collaboration, industrial supply chain, blockchain, homomorphic encryption.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8308430 Complexity Leadership and Knowledge Management in Higher Education
Authors: Prabhakar Venugopal Gantasala
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Complex environments triggered by globalization have necessitated new paradigms of leadership – Complexity Leadership that encompass multiple roles that leaders need to take upon. Success of Higher Education institutions depends on how well leaders can provide adaptive, administrative and enabling leadership. Complexity Leadership seems all the more relevant for institutions that are knowledge-driven and thrive on Knowledge creation, Knowledge storage and retrieval, Knowledge Sharing and Knowledge applications. Discussed in this paper are the elements of Globalization and the opportunities and challenges that are brought forth by globalization. The Complexity leadership paradigm in a knowledge-based economy and the need for such a paradigm shift for higher education institutions is presented. Further, the paper also discusses the support the leader requires in a knowledge-driven economy through knowledge management initiatives.Keywords: Globalization, Complexity Leadership, Knowledge Management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18008429 An Approximation of Daily Rainfall by Using a Pixel Value Data Approach
Authors: Sarisa Pinkham, Kanyarat Bussaban
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The research aims to approximate the amount of daily rainfall by using a pixel value data approach. The daily rainfall maps from the Thailand Meteorological Department in period of time from January to December 2013 were the data used in this study. The results showed that this approach can approximate the amount of daily rainfall with RMSE=3.343.
Keywords: Daily rainfall, Image processing, Approximation, Pixel value data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17598428 Automatic Generation of Ontology from Data Source Directed by Meta Models
Authors: Widad Jakjoud, Mohamed Bahaj, Jamal Bakkas
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Through this paper we present a method for automatic generation of ontological model from any data source using Model Driven Architecture (MDA), this generation is dedicated to the cooperation of the knowledge engineering and software engineering. Indeed, reverse engineering of a data source generates a software model (schema of data) that will undergo transformations to generate the ontological model. This method uses the meta-models to validate software and ontological models.
Keywords: Meta model, model, ontology, data source.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19998427 The Need for the Development of Entrepreneurial Skill in Benue State University Students, Makurdi
Authors: Philomena Ibuh Adzongo, Margaret U. Oluwole, Justina Nguveren Jor.
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This paper investigated the need for the development of entrepreneurial skills for Benue State University students. The population consisted of all 1,500 final year students in Benue State University. A sample of 100 students was selected using simple random sampling. A 12-item self-constructed and content validated questionnaire by research experts titled, the Need for the Development of Entrepreneurial Skills in Benue State University Students (NDECBSUS) was used to collect the data. The questionnaire items were rated using a 4-point modified rating scale of Strongly Agree, Agree, Disagree and Strongly Disagree, assigned the following scores of 4,3,2 and 1, respectively. The questionnaire was administered by the researcher with the help of two research assistants through the primary source. Simple percentages and chi-square were used to answer the research questions and test the hypotheses, respectively. The findings revealed that in business management, business management skills, personal skills, and technical skills need to be developed in students for them to become effective and efficient entrepreneurs and concluded that the acquisition of these skills will reduce the challenge of unemployment. The study recommended that funds should be made available by all education stakeholders for such programmes to remain functional.
Keywords: Entrepreneurial skill, entrepreneurship, need for development, university students.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11138426 Test Data Compression Using a Hybrid of Bitmask Dictionary and 2n Pattern Runlength Coding Methods
Authors: C. Kalamani, K. Paramasivam
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In VLSI, testing plays an important role. Major problem in testing are test data volume and test power. The important solution to reduce test data volume and test time is test data compression. The Proposed technique combines the bit maskdictionary and 2n pattern run length-coding method and provides a substantial improvement in the compression efficiency without introducing any additional decompression penalty. This method has been implemented using Mat lab and HDL Language to reduce test data volume and memory requirements. This method is applied on various benchmark test sets and compared the results with other existing methods. The proposed technique can achieve a compression ratio up to 86%.Keywords: Bit Mask dictionary, 2n pattern run length code, system-on-chip, SOC, test data compression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19258425 Procurement for Management Services in Delivery of Public Construction Projects in Poland
Authors: A. Leśniak, E. Plebankiewicz, K. Zima
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Construction projects can be implemented under various contractual and organizational systems. They can be divided into two groups: systems without the managing company where the Client manages the process, and systems with the managing company, where management is entrusted to an external company. In the public sector of the Polish market there are two ways of delivery of construction projects with the participation of the manager: one is to assign operations to another party, the so called Project Supervisor, whilst the other results from the application of FIDIC conditions of contract, which entail appointment of the Engineer. The decision is to be made by the Client and depends on various factors. On the public procurement market in Poland the selection of construction project manager boils down to awarding the contract for such a service. The selection can be done by one of eight public procurement procedures identified by the procurement law. The paper provides the analysis of 96 contracts for services awarded in 2011, which employed construction management. The study aimed to investigate the methods and criteria for selecting managers, applied in practice by the Polish public Clients.
Keywords: construction management, construction services, methods and criteria of tender selection, public procurement
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17918424 Political Economy of Integrated Soil Fertility Management in the Okavango Delta, Botswana
Authors: Oluwatoyin D. Kolawole, Oarabile Mogobe, Lapologang Magole
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Although many factors play a significant role in agricultural production and productivity, the importance of soil fertility cannot be underestimated. The extent to which small farmers are able to manage the fertility of their farmlands is crucial in agricultural development particularly in sub-Saharan Africa (SSA). This paper assesses the nutrient status of selected farmers’ fields in relation to how government policy addresses the allocation of and access to agricultural inputs (e.g. chemical fertilizers) in a unique social-ecological environment of the Okavango Delta in northern Botswana. It also analyses small farmers and soil scientists’ perceptions about the political economy of integrated soil fertility management (ISFM) in the area. A multi-stage sampling procedure was used to elicit quantitative and qualitative information from 228 farmers and 9 soil researchers through the use of interview schedules and questionnaires, respectively. Knowledge validation workshops and focus group discussions (FGDs) were also used to collect qualitative data from farmers. Thirty-three composite soil samples were collected from 30 farmers’ plots in three farming communities of Makalamabedi, Nokaneng and Mohembo for laboratory analysis. While meeting points exist, farmers and scientists have divergent perspectives on soil fertility management. Laboratory analysis carried out shows that most soils in the wetland and the adjoining dry-land/upland surroundings are low in essential nutrients as well as in cation exchange capacity (CEC). Although results suggest the identification and use of appropriate inorganic fertilizers, the low CEC is an indication that holistic cultural practices, which are beyond mere chemical fertilizations, are critical and more desirable for improved soil health and sustainable livelihoods in the area. Farmers’ age (t= -0.728; p≤0.10); their perceptions about the political economy (t = -0.485; p≤0.01) of ISFM; and their preference for the use of local knowledge in soil fertility management (t = -10.254; p≤0.01) had a significant relationship with how they perceived their involvement in the implementation of ISFM.
Keywords: Access, Botswana, ecology, inputs, Okavango Delta, policy, scientists, small farmers, soil fertility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25708423 Water Crisis Management in a Tourism Dependent Community
Authors: Aishath Shakeela
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At a global level, water stewardship, water stress and water security are crucial factors in tourism planning and development considerations. Challenges associated with water is of particular concern to the Maldives as there is limited availability of freshwater, high dependency on desalinated water, and high unit cost associated with desalinating water. While the Maldives is promoted as an example of sustainable tourism, a key sustainability challenge facing tourism dependent communities is the efficient use and management of available water resources. A water crisis event in the capital island of Maldives highlighted how precarious water related issues are in this tourism dependent destination. Applying netnography, the focus of this working paper is to present community perceptions of how government policies addressed Malé Water and Sewerage Company (MWSC) water crisis event.Keywords: Crisis management, government policies, Maldives, tourism, water.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21228422 Application of Agile Project Methodology in Computational Fluid Dynamics Engineering Project
Authors: Mohammed Bilal, Noor Hyder
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Agile methodology is a popular project management methodology and is widely used in many engineering projects. In the recent years agile methodology is successful in countering the inherent problems seen in traditional methodology. The application of the Agile methodology in the computational fluid dynamic project had improved the project delivery performance. Computational Fluid Dynamics (CFD) is the method to solve and analyze the fluid flow problems by the application of the numerical analysis. In this paper, study is conducted using agile methodology and results are compared with waterfall methodology. The result shows that the agile methodology is improves the final delivery of the project.
Keywords: Agile methodology, traditional methodology, engineering management, engineering technology, Computational Fluid Dynamics, project management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3768421 Energy Management System in HEV Using PI Controller
Authors: S. Saravanan, G. Sugumaran
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Nowadays the use of Hybrid Electric Vehicles (HEV) is increasing dramatically. The HEV is mainly dependent on electricity and there is always a need for storage of charge. Fuel Cell (FC), Batteries and Ultra Capacitor are being used for the proposed HEV as an electric power source or as an energy storage unit. The aim of developing an energy management technique is to utilize the sources according to the requirement of the vehicle with help of controller. This increases the efficiency of hybrid electric vehicle to reduce the fuel consumption and unwanted emission. The Maximum Power Point Tracking (MPPT) in FC is done using (Perturb & Observe) algorithm. In this paper, the control of automobiles at variable speed is achieved effectively.
Keywords: Batteries, Energy Management System (EMS), Fuel Cell (FC), Hybrid Electric Vehicles (HEVs), Maximum Power Point Tracking (MPPT).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33598420 Mathematical Rescheduling Models for Railway Services
Authors: Zuraida Alwadood, Adibah Shuib, Norlida Abd Hamid
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This paper presents the review of past studies concerning mathematical models for rescheduling passenger railway services, as part of delay management in the occurrence of railway disruption. Many past mathematical models highlighted were aimed at minimizing the service delays experienced by passengers during service disruptions. Integer programming (IP) and mixed-integer programming (MIP) models are critically discussed, focusing on the model approach, decision variables, sets and parameters. Some of them have been tested on real-life data of railway companies worldwide, while a few have been validated on fictive data. Based on selected literatures on train rescheduling, this paper is able to assist researchers in the model formulation by providing comprehensive analyses towards the model building. These analyses would be able to help in the development of new approaches in rescheduling strategies or perhaps to enhance the existing rescheduling models and make them more powerful or more applicable with shorter computing time.
Keywords: Mathematical modelling, Mixed-integer programming, Railway rescheduling, Service delays.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32588419 A Hybrid Data Mining Method for the Medical Classification of Chest Pain
Authors: Sung Ho Ha, Seong Hyeon Joo
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Data mining techniques have been used in medical research for many years and have been known to be effective. In order to solve such problems as long-waiting time, congestion, and delayed patient care, faced by emergency departments, this study concentrates on building a hybrid methodology, combining data mining techniques such as association rules and classification trees. The methodology is applied to real-world emergency data collected from a hospital and is evaluated by comparing with other techniques. The methodology is expected to help physicians to make a faster and more accurate classification of chest pain diseases.Keywords: Data mining, medical decisions, medical domainknowledge, chest pain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22278418 Knowledge Discovery and Data Mining Techniques in Textile Industry
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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15418417 Application and Limitation of Parallel Modelingin Multidimensional Sequential Pattern
Authors: Mahdi Esmaeili, Mansour Tarafdar
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The goal of data mining algorithms is to discover useful information embedded in large databases. One of the most important data mining problems is discovery of frequently occurring patterns in sequential data. In a multidimensional sequence each event depends on more than one dimension. The search space is quite large and the serial algorithms are not scalable for very large datasets. To address this, it is necessary to study scalable parallel implementations of sequence mining algorithms. In this paper, we present a model for multidimensional sequence and describe a parallel algorithm based on data parallelism. Simulation experiments show good load balancing and scalable and acceptable speedup over different processors and problem sizes and demonstrate that our approach can works efficiently in a real parallel computing environment.Keywords: Sequential Patterns, Data Mining, ParallelAlgorithm, Multidimensional Sequence Data
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14818416 Differences in IT Effectiveness among Firms: An Empirical Investigation
Authors: Crystal X. Jiang, Tess Han, George J. Titus, Matthew J. Liberatore
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Information is a critical asset and an important source for gaining competitive advantage in firms. The effective maintenance of IT becomes an important task. In order to better understand the determinants of IT effectiveness, this study employs the Industrial Organization (I/O) and Resource Based View (RBV) theories and investigates the industry effect and several major firmspecific factors in relation to their impact on firms- IT effectiveness. The data consist of a panel data of ten-year observations of firms whose IT excellence had been recognized by the CIO Magazine. The non-profit organizations were deliberately excluded, as explained later. The results showed that the effectiveness of IT management varied significantly across industries. Industry also moderated the effects of firm demographic factors such as size and age on IT effectiveness. Surprisingly, R & D investment intensity had negative correlation to IT effectiveness. For managers and practitioners, this study offers some insights for evaluation criteria and expectation for IT project success. Finally, the empirical results indicate that the sustainability of IT effectiveness appears to be short in duration.
Keywords: Firm effect, industry effect, IT effectiveness, sustained IT effectiveness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13218415 Energy Management System in Fuel Cell, Ultracapacitor, Battery Hybrid Energy Storage
Authors: Vinod Tejwani, Bhavik Suthar
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The paper presents and energy management strategy for a Fuel Cell, Ultracapacitor, Battery hybrid energy storage. The fuel cell hybrid power system is devised basically for emergency power requirements and transient load applications. The power density of an Ultracapacitor is extremely high and for a battery, it is subtle. For a fuel cell, the value of power density is medium. The energy density of these three stockpiling gadgets is contrarily about the power density, i.e. for the batteries it is most noteworthy and for the Ultracapacitor, it is least. Again the fuel cell has medium energy density. The proposed Energy Management System (EMS) is trying to rationalize these parameters viz. the energy density and power density. The working of the fuel cell, Ultracapacitor and batteries are controlled in a coordinated environment in a way to optimize the energy usage and at the same time to get benefits of power and energy density from their inherent characteristics. MATLAB/ Simulink® based test bench is created by using different DC-DC converters for all energy storage devices and an inverter is modeled to supply the time varying load. The results provided by the EMS are highly satisfactory that proves its adaptability.
Keywords: Energy Management System (EMS) Fuel Cell, Ultracapacitor, Battery, Hybrid Energy Storage.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17358414 Organizational Involvement and Employees’ Consumption of New Work Practices in State-owned Enterprises: The Ghanaian Case
Authors: M. Aminu Sanda, K. Ewontumah
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This paper explored the challenges faced by the management of a Ghanaian state enterprise in managing conflicts and disturbances associated with its attempt to implement new work practices to enhance its capability to operate as a commercial entity. The purpose was to understand the extent to which organizational involvement, consistency and adaptability influence employees’ consumption of new work practices in transforming the organization’s organizational activity system. Using selfadministered questionnaires, data were collected from one hundred and eighty (180) employees and analyzed using both descriptive and inferential statistics. The results showed that constraints in organizational involvement and adaptability prevented the positive consumption of new work practices by employees in the organization. It is also found that the organization’s employees failed to consume the new practices being implemented, because they perceived the process as non-involving, and as such, did not encourage the development of employee capability, empowerment, and teamwork. The study concluded that the failure of the organization’s management to create opportunities for organizational learning constrained its ability to get employees consume the new work practices, which situation could have facilitated the organization’s capabilities of operating as a commercial entity.Keywords: Organizational transformation, new work practices, work practice consumption, organizational involvement, state-owned enterprise, Ghana.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15788413 Multi-Criteria Decision-Making Selection Model with Application to Chemical Engineering Management Decisions
Authors: Mohsen Pirdashti, Arezou Ghadi, Mehrdad Mohammadi, Gholamreza Shojatalab
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Chemical industry project management involves complex decision making situations that require discerning abilities and methods to make sound decisions. Project managers are faced with decision environments and problems in projects that are complex. In this work, case study is Research and Development (R&D) project selection. R&D is an ongoing process for forward thinking technology-based chemical industries. R&D project selection is an important task for organizations with R&D project management. It is a multi-criteria problem which includes both tangible and intangible factors. The ability to make sound decisions is very important to success of R&D projects. Multiple-criteria decision making (MCDM) approaches are major parts of decision theory and analysis. This paper presents all of MCDM approaches for use in R&D project selection. It is hoped that this work will provide a ready reference on MCDM and this will encourage the application of the MCDM by chemical engineering management.Keywords: Chemical Engineering, R&D Project, MCDM, Selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40938412 Generator of Hypotheses an Approach of Data Mining Based on Monotone Systems Theory
Authors: Rein Kuusik, Grete Lind
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Generator of hypotheses is a new method for data mining. It makes possible to classify the source data automatically and produces a particular enumeration of patterns. Pattern is an expression (in a certain language) describing facts in a subset of facts. The goal is to describe the source data via patterns and/or IF...THEN rules. Used evaluation criteria are deterministic (not probabilistic). The search results are trees - form that is easy to comprehend and interpret. Generator of hypotheses uses very effective algorithm based on the theory of monotone systems (MS) named MONSA (MONotone System Algorithm).Keywords: data mining, monotone systems, pattern, rule.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12608411 Single and Multiple Sourcing in the Auto-Manufacturing Industry
Authors: Sung Ho Ha, Eun Kyoung Kwon, Jong Sik Jin, Hyun Sun Park
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This article outlines a hybrid method, incorporating multiple techniques into an evaluation process, in order to select competitive suppliers in a supply chain. It enables a purchaser to do single sourcing and multiple sourcing by calculating a combined supplier score, which accounts for both qualitative and quantitative factors that have impact on supply chain performance.Keywords: Analytic hierarchy process, Data envelopment analysis, Neural network, Supply chain management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26658410 Categorical Data Modeling: Logistic Regression Software
Authors: Abdellatif Tchantchane
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A Matlab based software for logistic regression is developed to enhance the process of teaching quantitative topics and assist researchers with analyzing wide area of applications where categorical data is involved. The software offers an option of performing stepwise logistic regression to select the most significant predictors. The software includes a feature to detect influential observations in data, and investigates the effect of dropping or misclassifying an observation on a predictor variable. The input data may consist either as a set of individual responses (yes/no) with the predictor variables or as grouped records summarizing various categories for each unique set of predictor variables' values. Graphical displays are used to output various statistical results and to assess the goodness of fit of the logistic regression model. The software recognizes possible convergence constraints when present in data, and the user is notified accordingly.
Keywords: Logistic regression, Matlab, Categorical data, Influential observation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18878409 Study of Hydrocarbons Metering Issues in Algerian Fields under the New Law Context
Authors: A. Hadjadj, S. Maamir
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Since the advent of the law 86/14 concerning theexploitation of the national territory by foreign companies in
partnership with the Algerian oil and gas company, the problem of
hydrocarbons metering in the sharing production come out.
More generally, good management counting hydrocarbons can
provide data on the production wells, the field and the reservoir for
medium and long term planning, particularly in the context of the
management and field development.
In this work, we are interested in the transactional metering which
is a very delicate and crucial period in the current context of the new
hydrocarbon’s law characterized by assets system between the
various activities of Sonatrach and its foreign partners.
After a state of the art on hydrocarbons metering devices in
Algeria and elsewhere, we will decline the advantages and
disadvantages of each system, and then we describe the problem to
try to reach an optimal solution.
Keywords: Flowmeter orifice, heat flow, Sonatrach, Transactional metering.
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