Search results for: environmental data
8205 Future of Electric Power Generation Technologies: Environmental and Economic Comparison
Authors: Abdulrahman A. Bahaddad, Mohammed Beshir
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The objective of this paper is to demonstrate and describe eight different types of power generation technologies and to understand the history and future trends of each technology. In addition, a comparative analysis between these technologies will be presented with respect to their cost analysis and associated performance.
Keywords: Conventional power generation, economic analysis, environmental impact, renewable energy power generation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12298204 Enhanced Data Access Control of Cooperative Environment used for DMU Based Design
Authors: Wei Lifan, Zhang Huaiyu, Yang Yunbin, Li Jia
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Through the analysis of the process digital design based on digital mockup, the fact indicates that a distributed cooperative supporting environment is the foundation conditions to adopt design approach based on DMU. Data access authorization is concerned firstly because the value and sensitivity of the data for the enterprise. The access control for administrators is often rather weak other than business user. So authors established an enhanced system to avoid the administrators accessing the engineering data by potential approach and without authorization. Thus the data security is improved.Keywords: access control, DMU, PLM, virtual prototype.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14588203 Soil Remediation Technologies towards Green Remediation Strategies
Authors: G. Petruzzelli, F. Pedron, M. Grifoni, M. Barbafieri, I. Rosellini, B. Pezzarossa
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As a result of diverse industrial activities, pollution from numerous contaminant affects both groundwater and soils. Many contaminated sites have been discovered in industrialized countries and their remediation is a priority in environmental legislations. The aim of this paper is to provide the evolution of remediation from consolidated invasive technologies to environmental friendly green strategies. Many clean-up technologies have been used. Nowadays the technologies selection is no longer exclusively based on eliminating the source of pollution, but the aim of remediation includes also the recovery of soil quality. “Green remediation”, a strategy based on “soft technologies”, appears the key to tackle the issue of remediation of contaminated sites with the greatest attention to environmental quality, including the preservation of soil functionality.
Keywords: Bioremediation, green remediation, phytoremediation, remediation technologies, soil.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18408202 Pattern Recognition Using Feature Based Die-Map Clusteringin the Semiconductor Manufacturing Process
Authors: Seung Hwan Park, Cheng-Sool Park, Jun Seok Kim, Youngji Yoo, Daewoong An, Jun-Geol Baek
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Depending on the big data analysis becomes important, yield prediction using data from the semiconductor process is essential. In general, yield prediction and analysis of the causes of the failure are closely related. The purpose of this study is to analyze pattern affects the final test results using a die map based clustering. Many researches have been conducted using die data from the semiconductor test process. However, analysis has limitation as the test data is less directly related to the final test results. Therefore, this study proposes a framework for analysis through clustering using more detailed data than existing die data. This study consists of three phases. In the first phase, die map is created through fail bit data in each sub-area of die. In the second phase, clustering using map data is performed. And the third stage is to find patterns that affect final test result. Finally, the proposed three steps are applied to actual industrial data and experimental results showed the potential field application.
Keywords: Die-Map Clustering, Feature Extraction, Pattern Recognition, Semiconductor Manufacturing Process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31368201 Environmental Responsibility and Firm Performance: Evidence from Nigeria
Authors: Collins C. Ngwakwe
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The objective of this paper is to establish a possible relationship between sustainable business practice and firm performance. Using a field survey methodology, a sample of sixty manufacturing companies in Nigeria was studied. The firms were categorised into two groups, environmentally 'responsible' and 'irresponsible' firms. An investigation was undertaken into the possible relationship between firm performance and three selected indicators of sustainable business practice: employee health and safety (EHS), waste management (WM), and community development (CD), common within the 30 'responsible' firms. Findings from empirical results reveal that the sustainable practices of the 'responsible' firms are significantly related with firm performance. In addition, sustainable practices are inversely related with fines and penalties. The paper concludes that, within the Nigerian setting at least, sustainability affects corporate performance and sustainability may be a possible tool for corporate conflict resolution as evidenced in the reduction of fines, penalties and compensations. The paper therefore recommends research into the relationship between sustainability and conflict management.
Keywords: Environmental responsibility, environmental investment, social responsibility, sustainable business, social ethics, environmental ethics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39838200 Speed Characteristics of Mixed Traffic Flow on Urban Arterials
Authors: Ashish Dhamaniya, Satish Chandra
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Speed and traffic volume data are collected on different sections of four lane and six lane roads in three metropolitan cities in India. Speed data are analyzed to fit the statistical distribution to individual vehicle speed data and all vehicles speed data. It is noted that speed data of individual vehicle generally follows a normal distribution but speed data of all vehicle combined at a section of urban road may or may not follow the normal distribution depending upon the composition of traffic stream. A new term Speed Spread Ratio (SSR) is introduced in this paper which is the ratio of difference in 85th and 50th percentile speed to the difference in 50th and 15th percentile speed. If SSR is unity then speed data are truly normally distributed. It is noted that on six lane urban roads, speed data follow a normal distribution only when SSR is in the range of 0.86 – 1.11. The range of SSR is validated on four lane roads also.
Keywords: Normal distribution, percentile speed, speed spread ratio, traffic volume.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42318199 A Comparative Study between Discrete Wavelet Transform and Maximal Overlap Discrete Wavelet Transform for Testing Stationarity
Authors: Amel Abdoullah Ahmed Dghais, Mohd Tahir Ismail
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In this paper the core objective is to apply discrete wavelet transform and maximal overlap discrete wavelet transform functions namely Haar, Daubechies2, Symmlet4, Coiflet2 and discrete approximation of the Meyer wavelets in non stationary financial time series data from Dow Jones index (DJIA30) of US stock market. The data consists of 2048 daily data of closing index from December 17, 2004 to October 23, 2012. Unit root test affirms that the data is non stationary in the level. A comparison between the results to transform non stationary data to stationary data using aforesaid transforms is given which clearly shows that the decomposition stock market index by discrete wavelet transform is better than maximal overlap discrete wavelet transform for original data.
Keywords: Discrete wavelet transform, maximal overlap discrete wavelet transform, stationarity, autocorrelation function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47178198 Comparative Study of Transformed and Concealed Data in Experimental Designs and Analyses
Authors: K. Chinda, P. Luangpaiboon
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This paper presents the comparative study of coded data methods for finding the benefit of concealing the natural data which is the mercantile secret. Influential parameters of the number of replicates (rep), treatment effects (τ) and standard deviation (σ) against the efficiency of each transformation method are investigated. The experimental data are generated via computer simulations under the specified condition of the process with the completely randomized design (CRD). Three ways of data transformation consist of Box-Cox, arcsine and logit methods. The difference values of F statistic between coded data and natural data (Fc-Fn) and hypothesis testing results were determined. The experimental results indicate that the Box-Cox results are significantly different from natural data in cases of smaller levels of replicates and seem to be improper when the parameter of minus lambda has been assigned. On the other hand, arcsine and logit transformations are more robust and obviously, provide more precise numerical results. In addition, the alternate ways to select the lambda in the power transformation are also offered to achieve much more appropriate outcomes.Keywords: Experimental Designs, Box-Cox, Arcsine, Logit Transformations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16088197 Design of a Low Cost Motion Data Acquisition Setup for Mechatronic Systems
Authors: Barış Can Yalçın
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Motion sensors have been commonly used as a valuable component in mechatronic systems, however, many mechatronic designs and applications that need motion sensors cost enormous amount of money, especially high-tech systems. Design of a software for communication protocol between data acquisition card and motion sensor is another issue that has to be solved. This study presents how to design a low cost motion data acquisition setup consisting of MPU 6050 motion sensor (gyro and accelerometer in 3 axes) and Arduino Mega2560 microcontroller. Design parameters are calibration of the sensor, identification and communication between sensor and data acquisition card, interpretation of data collected by the sensor.
Keywords: Calibration of sensors, data acquisition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43248196 Conceptual Multidimensional Model
Authors: Manpreet Singh, Parvinder Singh, Suman
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The data is available in abundance in any business organization. It includes the records for finance, maintenance, inventory, progress reports etc. As the time progresses, the data keep on accumulating and the challenge is to extract the information from this data bank. Knowledge discovery from these large and complex databases is the key problem of this era. Data mining and machine learning techniques are needed which can scale to the size of the problems and can be customized to the application of business. For the development of accurate and required information for particular problem, business analyst needs to develop multidimensional models which give the reliable information so that they can take right decision for particular problem. If the multidimensional model does not possess the advance features, the accuracy cannot be expected. The present work involves the development of a Multidimensional data model incorporating advance features. The criterion of computation is based on the data precision and to include slowly change time dimension. The final results are displayed in graphical form.Keywords: Multidimensional, data precision.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14458195 Real Time Approach for Data Placement in Wireless Sensor Networks
Authors: Sanjeev Gupta, Mayank Dave
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The issue of real-time and reliable report delivery is extremely important for taking effective decision in a real world mission critical Wireless Sensor Network (WSN) based application. The sensor data behaves differently in many ways from the data in traditional databases. WSNs need a mechanism to register, process queries, and disseminate data. In this paper we propose an architectural framework for data placement and management. We propose a reliable and real time approach for data placement and achieving data integrity using self organized sensor clusters. Instead of storing information in individual cluster heads as suggested in some protocols, in our architecture we suggest storing of information of all clusters within a cell in the corresponding base station. For data dissemination and action in the wireless sensor network we propose to use Action and Relay Stations (ARS). To reduce average energy dissipation of sensor nodes, the data is sent to the nearest ARS rather than base station. We have designed our architecture in such a way so as to achieve greater energy savings, enhanced availability and reliability.
Keywords: Cluster head, data reliability, real time communication, wireless sensor networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18068194 Data Mining in Medicine Domain Using Decision Trees and Vector Support Machine
Authors: Djamila Benhaddouche, Abdelkader Benyettou
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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.
Keywords: A classifier, Algorithms decision tree, knowledge extraction, Support Vector Machine.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18628193 A Software Framework for Predicting Oil-Palm Yield from Climate Data
Authors: Mohd. Noor Md. Sap, A. Majid Awan
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Intelligent systems based on machine learning techniques, such as classification, clustering, are gaining wide spread popularity in real world applications. This paper presents work on developing a software system for predicting crop yield, for example oil-palm yield, from climate and plantation data. At the core of our system is a method for unsupervised partitioning of data for finding spatio-temporal patterns in climate data using kernel methods which offer strength to deal with complex data. This work gets inspiration from the notion that a non-linear data transformation into some high dimensional feature space increases the possibility of linear separability of the patterns in the transformed space. Therefore, it simplifies exploration of the associated structure in the data. Kernel methods implicitly perform a non-linear mapping of the input data into a high dimensional feature space by replacing the inner products with an appropriate positive definite function. In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering the data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.Keywords: Pattern analysis, clustering, kernel methods, spatial data, crop yield
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19678192 A Proposal for U-City (Smart City) Service Method Using Real-Time Digital Map
Authors: SangWon Han, MuWook Pyeon, Sujung Moon, DaeKyo Seo
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Recently, technologies based on three-dimensional (3D) space information are being developed and quality of life is improving as a result. Research on real-time digital map (RDM) is being conducted now to provide 3D space information. RDM is a service that creates and supplies 3D space information in real time based on location/shape detection. Research subjects on RDM include the construction of 3D space information with matching image data, complementing the weaknesses of image acquisition using multi-source data, and data collection methods using big data. Using RDM will be effective for space analysis using 3D space information in a U-City and for other space information utilization technologies.
Keywords: RDM, multi-source data, big data, U-City.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7998191 Design and Operation of a Multicarrier Energy System Based On Multi Objective Optimization Approach
Authors: Azadeh Maroufmashat, Sourena Sattari Khavas, Halle Bakhteeyar
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Multi-energy systems will enhance the system reliability and power quality. This paper presents an integrated approach for the design and operation of distributed energy resources (DER) systems, based on energy hub modeling. A multi-objective optimization model is developed by considering an integrated view of electricity and natural gas network to analyze the optimal design and operating condition of DER systems, by considering two conflicting objectives, namely, minimization of total cost and the minimization of environmental impact which is assessed in terms of CO2 emissions. The mathematical model considers energy demands of the site, local climate data, and utility tariff structure, as well as technical and financial characteristics of the candidate DER technologies. To provide energy demands, energy systems including photovoltaic, and co-generation systems, boiler, central power grid are considered. As an illustrative example, a hotel in Iran demonstrates potential applications of the proposed method. The results prove that increasing the satisfaction degree of environmental objective leads to increased total cost.
Keywords: Multi objective optimization, DER systems, Energy hub, Cost, CO2 emission.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24538190 A Decision Support Tool for Evaluating Mobility Projects
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Success is a European project that will implement several clean transport offers in three European cities and evaluate the environmental impacts. The goal of these measures is to improve urban mobility or the displacement of residents inside cities. For e.g. park and ride, electric vehicles, hybrid bus and bike sharing etc. A list of 28 criteria and 60 measures has been established for evaluation of these transport projects. The evaluation criteria can be grouped into: Transport, environment, social, economic and fuel consumption. This article proposes a decision support system based that encapsulates a hybrid approach based on fuzzy logic, multicriteria analysis and belief theory for the evaluation of impacts of urban mobility solutions. A web-based tool called DeSSIA (Decision Support System for Impacts Assessment) has been developed that treats complex data. The tool has several functionalities starting from data integration (import of data), evaluation of projects and finishes by graphical display of results. The tool development is based on the concept of MVC (Model, View, and Controller). The MVC is a conception model adapted to the creation of software's which impose separation between data, their treatment and presentation. Effort is laid on the ergonomic aspects of the application. It has codes compatible with the latest norms (XHTML, CSS) and has been validated by W3C (World Wide Web Consortium). The main ergonomic aspect focuses on the usability of the application, ease of learning and adoption. By the usage of technologies such as AJAX (XML and Java Script asynchrones), the application is more rapid and convivial. The positive points of our approach are that it treats heterogeneous data (qualitative, quantitative) from various information sources (human experts, survey, sensors, model etc.).
Keywords: Decision support tool, hybrid approach, urban mobility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19828189 Agile Methodology for Modeling and Design of Data Warehouses -AM4DW-
Authors: Nieto Bernal Wilson, Carmona Suarez Edgar
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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects. Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.
Keywords: Data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14718188 Distributed Data-Mining by Probability-Based Patterns
Authors: M. Kargar, F. Gharbalchi
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In this paper a new method is suggested for distributed data-mining by the probability patterns. These patterns use decision trees and decision graphs. The patterns are cared to be valid, novel, useful, and understandable. Considering a set of functions, the system reaches to a good pattern or better objectives. By using the suggested method we will be able to extract the useful information from massive and multi-relational data bases.Keywords: Data-mining, Decision tree, Decision graph, Pattern, Relationship.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15488187 K-Means for Spherical Clusters with Large Variance in Sizes
Authors: A. M. Fahim, G. Saake, A. M. Salem, F. A. Torkey, M. A. Ramadan
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Data clustering is an important data exploration technique with many applications in data mining. The k-means algorithm is well known for its efficiency in clustering large data sets. However, this algorithm is suitable for spherical shaped clusters of similar sizes and densities. The quality of the resulting clusters decreases when the data set contains spherical shaped with large variance in sizes. In this paper, we introduce a competent procedure to overcome this problem. The proposed method is based on shifting the center of the large cluster toward the small cluster, and recomputing the membership of small cluster points, the experimental results reveal that the proposed algorithm produces satisfactory results.Keywords: K-Means, Data Clustering, Cluster Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32688186 Representing Data without Lost Compression Properties in Time Series: A Review
Authors: Nabilah Filzah Mohd Radzuan, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan
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Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain data condition by minimizing the loss of compression properties.
Keywords: Compression properties, uncertainty, uncertain time series, mining technique, weather prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16118185 Are XBRL-based Financial Reports Better than Non-XBRL Reports? A Quality Assessment
Authors: Zhenkun Wang, Simon S. Gao
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Using a scoring system, this paper provides a comparative assessment of the quality of data between XBRL formatted financial reports and non-XBRL financial reports. It shows a major improvement in the quality of data of XBRL formatted financial reports. Although XBRL formatted financial reports do not show much advantage in the quality at the beginning, XBRL financial reports lately display a large improvement in the quality of data in almost all aspects. With the improved XBRL web data managing, presentation and analysis applications, XBRL formatted financial reports have a much better accessibility, are more accurate and better in timeliness.Keywords: Data Quality; Financial Report; Information; XBRL
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25488184 Modeling of Random Variable with Digital Probability Hyper Digraph: Data-Oriented Approach
Authors: A. Habibizad Navin, M. Naghian Fesharaki, M. Mirnia, M. Kargar
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In this paper we introduce Digital Probability Hyper Digraph for modeling random variable as the hierarchical data-oriented model.Keywords: Data-Oriented Models, Data Structure, DigitalProbability Hyper Digraph, Random Variable, Statistic andProbability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12588183 Wireless Transmission of Big Data Using Novel Secure Algorithm
Authors: K. Thiagarajan, K. Saranya, A. Veeraiah, B. Sudha
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This paper presents a novel algorithm for secure, reliable and flexible transmission of big data in two hop wireless networks using cooperative jamming scheme. Two hop wireless networks consist of source, relay and destination nodes. Big data has to transmit from source to relay and from relay to destination by deploying security in physical layer. Cooperative jamming scheme determines transmission of big data in more secure manner by protecting it from eavesdroppers and malicious nodes of unknown location. The novel algorithm that ensures secure and energy balance transmission of big data, includes selection of data transmitting region, segmenting the selected region, determining probability ratio for each node (capture node, non-capture and eavesdropper node) in every segment, evaluating the probability using binary based evaluation. If it is secure transmission resume with the two- hop transmission of big data, otherwise prevent the attackers by cooperative jamming scheme and transmit the data in two-hop transmission.Keywords: Big data, cooperative jamming, energy balance, physical layer, two-hop transmission, wireless security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21728182 Study of Efficiency and Capability LZW++ Technique in Data Compression
Authors: Yusof. Mohd Kamir, Mat Deris. Mohd Sufian, Abidin. Ahmad Faisal Amri
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The purpose of this paper is to show efficiency and capability LZWµ in data compression. The LZWµ technique is enhancement from existing LZW technique. The modification the existing LZW is needed to produce LZWµ technique. LZW read one by one character at one time. Differ with LZWµ technique, where the LZWµ read three characters at one time. This paper focuses on data compression and tested efficiency and capability LZWµ by different data format such as doc type, pdf type and text type. Several experiments have been done by different types of data format. The results shows LZWµ technique is better compared to existing LZW technique in term of file size.
Keywords: Data Compression, Huffman Encoding, LZW, LZWµ, RLL, Size.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20798181 Products in Early Development Phases: Ecological Classification and Evaluation Using an Interval Arithmetic Based Calculation Approach
Authors: Helen L. Hein, Joachim Schwarte
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As a pillar of sustainable development, ecology has become an important milestone in research community, especially due to global challenges like climate change. The ecological performance of products can be scientifically conducted with life cycle assessments. In the construction sector, significant amounts of CO2 emissions are assigned to the energy used for building heating purposes. Therefore, sustainable construction materials for insulating purposes are substantial, whereby aerogels have been explored intensively in the last years due to their low thermal conductivity. Therefore, the WALL-ACE project aims to develop an aerogel-based thermal insulating plaster that would achieve minor thermal conductivities. But as in the early stage of development phases, a lot of information is still missing or not yet accessible, the ecological performance of innovative products bases increasingly on uncertain data that can lead to significant deviations in the results. To be able to predict realistically how meaningful the results are and how viable the developed products may be with regard to their corresponding respective market, these deviations however have to be considered. Therefore, a classification method is presented in this study, which may allow comparing the ecological performance of modern products with already established and competitive materials. In order to achieve this, an alternative calculation method was used that allows computing with lower and upper bounds to consider all possible values without precise data. The life cycle analysis of the considered products was conducted with an interval arithmetic based calculation method. The results lead to the conclusion that the interval solutions describing the possible environmental impacts are so wide that the result usability is limited. Nevertheless, a further optimization in reducing environmental impacts of aerogels seems to be needed to become more competitive in the future.
Keywords: Aerogel-based, insulating material, early develop¬ment phase, interval arithmetic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6018180 Impact of Stack Caches: Locality Awareness and Cost Effectiveness
Authors: Abdulrahman K. Alshegaifi, Chun-Hsi Huang
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Treating data based on its location in memory has received much attention in recent years due to its different properties, which offer important aspects for cache utilization. Stack data and non-stack data may interfere with each other’s locality in the data cache. One of the important aspects of stack data is that it has high spatial and temporal locality. In this work, we simulate non-unified cache design that split data cache into stack and non-stack caches in order to maintain stack data and non-stack data separate in different caches. We observe that the overall hit rate of non-unified cache design is sensitive to the size of non-stack cache. Then, we investigate the appropriate size and associativity for stack cache to achieve high hit ratio especially when over 99% of accesses are directed to stack cache. The result shows that on average more than 99% of stack cache accuracy is achieved by using 2KB of capacity and 1-way associativity. Further, we analyze the improvement in hit rate when adding small, fixed, size of stack cache at level1 to unified cache architecture. The result shows that the overall hit rate of unified cache design with adding 1KB of stack cache is improved by approximately, on average, 3.9% for Rijndael benchmark. The stack cache is simulated by using SimpleScalar toolset.
Keywords: Hit rate, Locality of program, Stack cache, and Stack data.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14988179 Cross Project Software Fault Prediction at Design Phase
Authors: Pradeep Singh, Shrish Verma
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Software fault prediction models are created by using the source code, processed metrics from the same or previous version of code and related fault data. Some company do not store and keep track of all artifacts which are required for software fault prediction. To construct fault prediction model for such company, the training data from the other projects can be one potential solution. Earlier we predicted the fault the less cost it requires to correct. The training data consists of metrics data and related fault data at function/module level. This paper investigates fault predictions at early stage using the cross-project data focusing on the design metrics. In this study, empirical analysis is carried out to validate design metrics for cross project fault prediction. The machine learning techniques used for evaluation is Naïve Bayes. The design phase metrics of other projects can be used as initial guideline for the projects where no previous fault data is available. We analyze seven datasets from NASA Metrics Data Program which offer design as well as code metrics. Overall, the results of cross project is comparable to the within company data learning.Keywords: Software Metrics, Fault prediction, Cross project, Within project.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25328178 Implementation of a Low-Cost Instrumentation for an Open Cycle Wind Tunnel to Evaluate Pressure Coefficient
Authors: Cristian P. Topa, Esteban A. Valencia, Victor H. Hidalgo, Marco A. Martinez
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Wind tunnel experiments for aerodynamic profiles display numerous advantages, such as: clean steady laminar flow, controlled environmental conditions, streamlines visualization, and real data acquisition. However, the experiment instrumentation usually is expensive, and hence, each test implies a incremented in design cost. The aim of this work is to select and implement a low-cost static pressure data acquisition system for a NACA 2412 airfoil in an open cycle wind tunnel. This work compares wind tunnel experiment with Computational Fluid Dynamics (CFD) simulation and parametric analysis. The experiment was evaluated at Reynolds of 1.65 e5, with increasing angles from -5° to 15°. The comparison between the approaches show good enough accuracy, between the experiment and CFD, additional parametric analysis results differ widely from the other methods, which complies with the lack of accuracy of the lateral approach due its simplicity.Keywords: Wind tunnel, low cost instrumentation, experimental testing, CFD simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7978177 Performance Assessment of Computational Gridon Weather Indices from HOAPS Data
Authors: Madhuri Bhavsar, Anupam K Singh, Shrikant Pradhan
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Long term rainfall analysis and prediction is a challenging task especially in the modern world where the impact of global warming is creating complications in environmental issues. These factors which are data intensive require high performance computational modeling for accurate prediction. This research paper describes a prototype which is designed and developed on grid environment using a number of coupled software infrastructural building blocks. This grid enabled system provides the demanding computational power, efficiency, resources, user-friendly interface, secured job submission and high throughput. The results obtained using sequential execution and grid enabled execution shows that computational performance has enhanced among 36% to 75%, for decade of climate parameters. Large variation in performance can be attributed to varying degree of computational resources available for job execution. Grid Computing enables the dynamic runtime selection, sharing and aggregation of distributed and autonomous resources which plays an important role not only in business, but also in scientific implications and social surroundings. This research paper attempts to explore the grid enabled computing capabilities on weather indices from HOAPS data for climate impact modeling and change detection.Keywords: Climate model, Computational Grid, GridApplication, Heterogeneous Grid
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14278176 An Ant-based Clustering System for Knowledge Discovery in DNA Chip Analysis Data
Authors: Minsoo Lee, Yun-mi Kim, Yearn Jeong Kim, Yoon-kyung Lee, Hyejung Yoon
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Biological data has several characteristics that strongly differentiate it from typical business data. It is much more complex, usually large in size, and continuously changes. Until recently business data has been the main target for discovering trends, patterns or future expectations. However, with the recent rise in biotechnology, the powerful technology that was used for analyzing business data is now being applied to biological data. With the advanced technology at hand, the main trend in biological research is rapidly changing from structural DNA analysis to understanding cellular functions of the DNA sequences. DNA chips are now being used to perform experiments and DNA analysis processes are being used by researchers. Clustering is one of the important processes used for grouping together similar entities. There are many clustering algorithms such as hierarchical clustering, self-organizing maps, K-means clustering and so on. In this paper, we propose a clustering algorithm that imitates the ecosystem taking into account the features of biological data. We implemented the system using an Ant-Colony clustering algorithm. The system decides the number of clusters automatically. The system processes the input biological data, runs the Ant-Colony algorithm, draws the Topic Map, assigns clusters to the genes and displays the output. We tested the algorithm with a test data of 100 to1000 genes and 24 samples and show promising results for applying this algorithm to clustering DNA chip data.
Keywords: Ant colony system, biological data, clustering, DNA chip.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1962