Search results for: data safety.
6336 2D Human Motion Regeneration with Stick Figure Animation Using Accelerometers
Authors: Alpha Agape Gopalai, S. M. N. Arosha Senanayake
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This paper explores the opportunity of using tri-axial wireless accelerometers for supervised monitoring of sports movements. A motion analysis system for the upper extremities of lawn bowlers in particular is developed. Accelerometers are placed on parts of human body such as the chest to represent the shoulder movements, the back to capture the trunk motion, back of the hand, the wrist and one above the elbow, to capture arm movements. These sensors placement are carefully designed in order to avoid restricting bowler-s movements. Data is acquired from these sensors in soft-real time using virtual instrumentation; the acquired data is then conditioned and converted into required parameters for motion regeneration. A user interface was also created to facilitate in the acquisition of data, and broadcasting of commands to the wireless accelerometers. All motion regeneration in this paper deals with the motion of the human body segment in the X and Y direction, looking into the motion of the anterior/ posterior and lateral directions respectively.Keywords: Motion Regeneration, Virtual Instrumentation, Wireless Accelerometers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18176335 Analysis of Transformer Reactive Power Fluctuations during Adverse Space Weather
Authors: Patience Muchini, Electdom Matandiroya, Emmanuel Mashonjowa
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A ground-end manifestation of space weather phenomena is known as geomagnetically induced currents (GICs). GICs flow along the electric power transmission cables connecting the transformers and between the grounding points of power transformers during significant geomagnetic storms. Zimbabwe has no study that notes if grid failures have been caused by GICs. Research and monitoring are needed to investigate this possible relationship purpose of this paper is to characterize GICs with a power grid network. This paper analyses data collected, which are geomagnetic data, which include the Kp index, Disturbance storm time (DST) index, and the G-Scale from geomagnetic storms and also analyses power grid data, which includes reactive power, relay tripping, and alarms from high voltage substations and then correlates the data. This research analysis was first theoretically analyzed by studying geomagnetic parameters and then experimented upon. To correlate, MATLAB was used as the basic software to analyze the data. Latitudes of the substations were also brought into scrutiny to note if they were an impact due to the location as low latitudes areas like most parts of Zimbabwe, there are less severe geomagnetic variations. Based on theoretical and graphical analysis, it has been proven that there is a slight relationship between power system failures and GICs. Further analyses can be done by implementing measuring instruments to measure any currents in the grounding of high-voltage transformers when geomagnetic storms occur. Mitigation measures can then be developed to minimize the susceptibility of the power network to GICs.
Keywords: Adverse space weather, DST index, geomagnetically induced currents, Kp index, reactive power.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1226334 Spatial Clustering Model of Vessel Trajectory to Extract Sailing Routes Based on AIS Data
Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin
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The automatic extraction of shipping routes is advantageous for intelligent traffic management systems to identify events and support decision-making in maritime surveillance. At present, there is a high demand for the extraction of maritime traffic networks that resemble the real traffic of vessels accurately, which is valuable for further analytical processing tasks for vessels trajectories (e.g., naval routing and voyage planning, anomaly detection, destination prediction, time of arrival estimation). With the help of big data and processing huge amounts of vessels’ trajectory data, it is possible to learn these shipping routes from the navigation history of past behaviour of other, similar ships that were travelling in a given area. In this paper, we propose a spatial clustering model of vessels’ trajectories (SPTCLUST) to extract spatial representations of sailing routes from historical Automatic Identification System (AIS) data. The whole model consists of three main parts: data preprocessing, path finding, and route extraction, which consists of clustering and representative trajectory extraction. The proposed clustering method provides techniques to overcome the problems of: (i) optimal input parameters selection; (ii) the high complexity of processing a huge volume of multidimensional data; (iii) and the spatial representation of complete representative trajectory detection in the context of trajectory clustering algorithms. The experimental evaluation showed the effectiveness of the proposed model by using a real-world AIS dataset from the Port of Halifax. The results contribute to further understanding of shipping route patterns. This could aid surveillance authorities in stable and sustainable vessel traffic management.
Keywords: Vessel trajectory clustering, trajectory mining, Spatial Clustering, marine intelligent navigation, maritime traffic network extraction, sdailing routes extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4196333 Improving University Operations with Data Mining: Predicting Student Performance
Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević
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The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.
Keywords: Data mining, knowledge discovery in databases, prediction models, student success.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25256332 Investigation of Public Perception of Air Pollution and Life Quality in Tehran
Authors: R. Karami, A. Gharaei
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This study was undertaken at four different sites (north polluted, south polluted, south healthy and north healthy) in Tehran, in order to examine whether there was a relationship between publicly available air quality data and the public’s perception of air quality and to suggest some guidelines for reducing air pollution. A total of 200 people were accidentally filled out the research questionnaires at mentioned sites and air quality data were obtained simultaneously from the Air Quality Control Department. Data was analyzed in Excel and SPSS software’s. Clean air and job security were of great importance to people comparing to other pleasant aspect of life. Also air pollution and serious diseases were the most important of people concerns. Street monitors and news paper services on air quality were little used by the public as a means of obtaining information on air pollution. Using public transportation and avoiding inevitable journeys are the most important ways for reducing air pollution. The results reveal that the public’s perception of air quality is not a reliable indicator of the actual levels of air pollution.Keywords: Air pollution, Quality of life, Opinion poll, Public participation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23296331 A Review on the Comparison of EU Countries Based on Research and Development Efficiencies
Authors: Yeliz Ekinci, Raife Merve Ön
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Nowadays, technological progress is one of the most important components of economic growth and the efficiency of R&D activities is particularly essential for countries. This study is an attempt to analyze the R&D efficiencies of EU countries. The indicators related to R&D efficiencies should be determined in advance in order to use DEA. For this reason a list of input and output indicators are derived from the literature review. Considering the data availability, a final list is given for the numerical analysis for future research.Keywords: Data envelopment analysis, economic growth, EU Countries, R&D efficiency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20376330 Real-Time Image Encryption Using a 3D Discrete Dual Chaotic Cipher
Authors: M. F. Haroun, T. A. Gulliver
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In this paper, an encryption algorithm is proposed for real-time image encryption. The scheme employs a dual chaotic generator based on a three dimensional (3D) discrete Lorenz attractor. Encryption is achieved using non-autonomous modulation where the data is injected into the dynamics of the master chaotic generator. The second generator is used to permute the dynamics of the master generator using the same approach. Since the data stream can be regarded as a random source, the resulting permutations of the generator dynamics greatly increase the security of the transmitted signal. In addition, a technique is proposed to mitigate the error propagation due to the finite precision arithmetic of digital hardware. In particular, truncation and rounding errors are eliminated by employing an integer representation of the data which can easily be implemented. The simple hardware architecture of the algorithm makes it suitable for secure real-time applications.Keywords: Chaotic systems, image encryption, 3D Lorenz attractor, non-autonomous modulation, FPGA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12076329 DEA ANN Approach in Supplier Evaluation System
Authors: Dilek Özdemir, Gül Tekin Temur
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In Supply Chain Management (SCM), strengthening partnerships with suppliers is a significant factor for enhancing competitiveness. Hence, firms increasingly emphasize supplier evaluation processes. Supplier evaluation systems are basically developed in terms of criteria such as quality, cost, delivery, and flexibility. Because there are many variables to be analyzed, this process becomes hard to execute and needs expertise. On this account, this study aims to develop an expert system on supplier evaluation process by designing Artificial Neural Network (ANN) that is supported with Data Envelopment Analysis (DEA). The methods are applied on the data of 24 suppliers, which have longterm relationships with a medium sized company from German Iron and Steel Industry. The data of suppliers consists of variables such as material quality (MQ), discount of amount (DOA), discount of cash (DOC), payment term (PT), delivery time (DT) and annual revenue (AR). Meanwhile, the efficiency that is generated by using DEA is added to the supplier evaluation system in order to use them as system outputs.
Keywords: Artificial Neural Network (ANN), DataEnvelopment Analysis (DEA), Supplier Evaluation System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21406328 A Hybrid Approach for Quantification of Novelty in Rule Discovery
Authors: Vasudha Bhatnagar, Ahmed Sultan Al-Hegami, Naveen Kumar
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Rule Discovery is an important technique for mining knowledge from large databases. Use of objective measures for discovering interesting rules lead to another data mining problem, although of reduced complexity. Data mining researchers have studied subjective measures of interestingness to reduce the volume of discovered rules to ultimately improve the overall efficiency of KDD process. In this paper we study novelty of the discovered rules as a subjective measure of interestingness. We propose a hybrid approach that uses objective and subjective measures to quantify novelty of the discovered rules in terms of their deviations from the known rules. We analyze the types of deviation that can arise between two rules and categorize the discovered rules according to the user specified threshold. We implement the proposed framework and experiment with some public datasets. The experimental results are quite promising.
Keywords: Knowledge Discovery in Databases (KDD), Data Mining, Rule Discovery, Interestingness, Subjective Measures, Novelty Measure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13446327 The Use of Lane-Centering to Assure the Visible Light Communication Connectivity for a Platoon of Autonomous Vehicles
Authors: Mohammad Y. Abualhoul, Edgar Talavera Munoz, Fawzi Nashashibi
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The new emerging Visible Light Communication (VLC) technology has been subjected to intensive investigation, evaluation, and lately, deployed in the context of convoy-based applications for Intelligent Transportations Systems (ITS). The technology limitations were defined and supported by different solutions proposals to enhance the crucial alignment and mobility limitations. In this paper, we propose the incorporation of VLC technology and Lane-Centering (LC) technique to assure the VLC-connectivity by keeping the autonomous vehicle aligned to the lane center using vision-based lane detection in a convoy-based formation. Such combination can ensure the optical communication connectivity with a lateral error less than 30 cm. As soon as the road lanes are detectable, the evaluated system showed stable behavior independently from the inter-vehicle distances and without the need for any exchanged information of the remote vehicles. The evaluation of the proposed system is verified using VLC prototype and an empirical result of LC running application over 60 km in Madrid M40 highway.Keywords: VLC, lane-centering, platoon, ITS, road safety applications.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7616326 An Authentication Protocol for Quantum Enabled Mobile Devices
Authors: Natarajan Venkatachalam, Subrahmanya V. R. K. Rao, Vijay Karthikeyan Dhandapani, Swaminathan Saravanavel
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The quantum communication technology is an evolving design which connects multiple quantum enabled devices to internet for secret communication or sensitive information exchange. In future, the number of these compact quantum enabled devices will increase immensely making them an integral part of present communication systems. Therefore, safety and security of such devices is also a major concern for us. To ensure the customer sensitive information will not be eavesdropped or deciphered, we need a strong authentications and encryption mechanism. In this paper, we propose a mutual authentication scheme between these smart quantum devices and server based on the secure exchange of information through quantum channel which gives better solutions for symmetric key exchange issues. An important part of this work is to propose a secure mutual authentication protocol over the quantum channel. We show that our approach offers robust authentication protocol and further our solution is lightweight, scalable, cost-effective with optimized computational processing overheads.Keywords: Quantum cryptography, quantum key distribution, wireless quantum communication, authentication protocol, quantum enabled device, trusted third party.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11946325 Study on Wireless Transmission for Reconnaissance UAV with Wireless Sensor Network and Cylindrical Array of Microstrip Antennas
Authors: Chien-Chun Hung, Chun-Fong Wu
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It is important for a commander to have real-time information to aware situations and to make decision in the battlefield. Results of modern technique developments have brought in this kind of information for military purposes. Unmanned aerial vehicle (UAV) is one of the means to gather intelligence owing to its widespread applications. It is still not clear whether or not the mini UAV with short-range wireless transmission system is used as a reconnaissance system in Taiwanese. In this paper, previous experience on the research of the sort of aerial vehicles has been applied with a data-relay system using the ZigBee modulus. The mini UAV developed is expected to be able to collect certain data in some appropriate theaters. The omni-directional antenna with high gain is also integrated into mini UAV to fit the size-reducing trend of airborne sensors. Two advantages are so far obvious. First, mini UAV can fly higher than usual to avoid being attacked from ground fires. Second, the data will be almost gathered during all maneuvering attitudes.
Keywords: Mini UAV, reconnaissance, wireless transmission, ZigBee modulus.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6806324 Usage of Military Continuity Management System for Supporting of Emergency Management
Authors: R. Hajkova, J. Palecek, H. Malachova, A. Oulehlova
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Ensuring of continuity of business is basic strategy of every company. Continuity of organization activities includes comprehensive procedures that help in solving unexpected situations of natural and anthropogenic character (for example flood, blaze, economic situations). Planning of continuity operations is a process that helps identify critical processes and implement plans for the security and recovery of key processes. The aim of this article is to demonstrate application of system approach to managing business continuity called business continuity management systems in military issues. This article describes the life cycle of business continuity management which is based on the established cycle PDCA (Plan- Do-Check-Act). After this is carried out by activities which are making by University of Defence during activation of forces and means of the integrated rescue system in case of emergencies - accidents at a nuclear power plant in Czech Republic. Activities of various stages of deployment earmarked forces and resources are managed and evaluated by using MCMS application (Military Continuity Management System).Keywords: Business continuity management system, emergency management, military, nuclear safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21196323 Studying on ARINC653 Partition Run-time Scheduling and Simulation
Authors: Dongliang Wang, Jun Han, Dianfu Ma, Xianqi Zhao
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Avionics software is safe-critical embedded software and its architecture is evolving from traditional federated architectures to Integrated Modular Avionics (IMA) to improve resource usability. ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in Safety-critical avionics Real-time operating systems. Arinc653 uses two-level scheduling strategies, but current modeling tools only apply to simple problems of Arinc653 two-level scheduling, which only contain time property. In avionics industry, we are always manually allocating tasks and calculating the timing table of a real-time system to ensure it-s running as we design. In this paper we represent an automatically generating strategy which applies to the two scheduling problems with dependent constraints in Arinc653 partition run-time environment. It provides the functionality of automatic generation from the task and partition models to scheduling policy through allocating the tasks to the partitions while following the constraints, and then we design a simulating mechanism to check whether our policy is schedulable or notKeywords: Arinc653, scheduling, task allocation, simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23266322 Recurrent Radial Basis Function Network for Failure Time Series Prediction
Authors: Ryad Zemouri, Paul Ciprian Patic
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An adaptive software reliability prediction model using evolutionary connectionist approach based on Recurrent Radial Basis Function architecture is proposed. Based on the currently available software failure time data, Fuzzy Min-Max algorithm is used to globally optimize the number of the k Gaussian nodes. The corresponding optimized neural network architecture is iteratively and dynamically reconfigured in real-time as new actual failure time data arrives. The performance of our proposed approach has been tested using sixteen real-time software failure data. Numerical results show that our proposed approach is robust across different software projects, and has a better performance with respect to next-steppredictability compared to existing neural network model for failure time prediction.Keywords: Neural network, Prediction error, Recurrent RadialBasis Function Network, Reliability prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18096321 A Self Adaptive Genetic Based Algorithm for the Identification and Elimination of Bad Data
Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy
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The identification and elimination of bad measurements is one of the basic functions of a robust state estimator as bad data have the effect of corrupting the results of state estimation according to the popular weighted least squares method. However this is a difficult problem to handle especially when dealing with multiple errors from the interactive conforming type. In this paper, a self adaptive genetic based algorithm is proposed. The algorithm utilizes the results of the classical linearized normal residuals approach to tune the genetic operators thus instead of making a randomized search throughout the whole search space it is more likely to be a directed search thus the optimum solution is obtained at very early stages(maximum of 5 generations). The algorithm utilizes the accumulating databases of already computed cases to reduce the computational burden to minimum. Tests are conducted with reference to the standard IEEE test systems. Test results are very promising.Keywords: Bad Data, Genetic Algorithms, Linearized Normal residuals, Observability, Power System State Estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13366320 Information Retrieval in Domain Specific Search Engine with Machine Learning Approaches
Authors: Shilpy Sharma
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As the web continues to grow exponentially, the idea of crawling the entire web on a regular basis becomes less and less feasible, so the need to include information on specific domain, domain-specific search engines was proposed. As more information becomes available on the World Wide Web, it becomes more difficult to provide effective search tools for information access. Today, people access web information through two main kinds of search interfaces: Browsers (clicking and following hyperlinks) and Query Engines (queries in the form of a set of keywords showing the topic of interest) [2]. Better support is needed for expressing one's information need and returning high quality search results by web search tools. There appears to be a need for systems that do reasoning under uncertainty and are flexible enough to recover from the contradictions, inconsistencies, and irregularities that such reasoning involves. In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view algorithms, which reduce the amount of labeled data required for learning, rely on the assumptions that the views are compatible and uncorrelated. This paper describes the use of semi-structured machine learning approach with Active learning for the “Domain Specific Search Engines". A domain-specific search engine is “An information access system that allows access to all the information on the web that is relevant to a particular domain. The proposed work shows that with the help of this approach relevant data can be extracted with the minimum queries fired by the user. It requires small number of labeled data and pool of unlabelled data on which the learning algorithm is applied to extract the required data.Keywords: Search engines; machine learning, Informationretrieval, Active logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20746319 A Detailed Timber Harvest Simulator Coupled with 3-D Visualization
Authors: Jürgen Roßmann, Gerrit Alves
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In today-s world, the efficient utilization of wood resources comes more and more to the mind of forest owners. It is a very complex challenge to ensure an efficient harvest of the wood resources. This is one of the scopes the project “Virtual Forest II" addresses. Its core is a database with data about forests containing approximately 260 million trees located in North Rhine-Westphalia (NRW). Based on this data, tree growth simulations and wood mobilization simulations can be conducted. This paper focuses on the latter. It describes a discrete-event-simulation with an attached 3-D real time visualization which simulates timber harvest using trees from the database with different crop resources. This simulation can be displayed in 3-D to show the progress of the wood crop. All the data gathered during the simulation is presented as a detailed summary afterwards. This summary includes cost-benefit calculations and can be compared to those of previous runs to optimize the financial outcome of the timber harvest by exchanging crop resources or modifying their parameters.Keywords: Timber harvest, simulation, 3-D, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13656318 Belief Theory-Based Classifiers Comparison for Static Human Body Postures Recognition in Video
Authors: V. Girondel, L. Bonnaud, A. Caplier, M. Rombaut
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This paper presents various classifiers results from a system that can automatically recognize four different static human body postures in video sequences. The considered postures are standing, sitting, squatting, and lying. The three classifiers considered are a naïve one and two based on the belief theory. The belief theory-based classifiers use either a classic or restricted plausibility criterion to make a decision after data fusion. The data come from the people 2D segmentation and from their face localization. Measurements consist in distances relative to a reference posture. The efficiency and the limits of the different classifiers on the recognition system are highlighted thanks to the analysis of a great number of results. This system allows real-time processing.
Keywords: Belief theory, classifiers comparison, data fusion, human motion analysis, real-time processing, static posture recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15056317 Using RASCAL and ALOHA Codes to Establish an Analysis Methodology for Hydrogen Fluoride Evaluation
Authors: J. R. Wang, Y. Chiang, W. S. Hsu, H. C. Chen, S. H. Chen, J. H. Yang, S. W. Chen, C. Shih
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In this study, the RASCAL and ALOHA codes are used to establish an analysis methodology for hydrogen fluoride (HF) evaluation. There are three main steps in this study. First, the UF6 data were collected. Second, one postulated case was analyzed by using the RASCAL and UF6 data. This postulated case assumes that fire occurring and UF6 is releasing from a building. Third, the results of RASCAL for HF mass were as the input data of ALOHA. Two postulated cases of HF were analyzed by using ALOHA code and the results of RASCAL. These postulated cases assume fire occurring and HF is releasing with no raining (Case 1) or raining (Case 2) condition. According to the analysis results of ALOHA, the HF concentration of Case 2 is smaller than Case 1. The results can be a reference for the preparing of emergency plans for the release of HF.Keywords: RASCAL, ALOHA, UF6, hydrogen fluoride.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7606316 Model Development for Allocation of Raw Material in Timber Processing Industry in Indonesia
Authors: Muh. Hisjam, Nancy Oktyajati, Wakhid A. Jauhari, Wahyudi Sutopo
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This research is intended to develop a raw material allocation model in timber processing industry in Perum Perhutani Unit I, Central Java, Indonesia. The model can be used to determine the quantity of allocation of timber between chain in the supply chain to select supplier considering factors that are log price and the distance. In determining the quantity of allocation of timber between chains in the supply chain, the model considers the optimal inventory in each chain. Whilst the optimal inventory is determined based on demand forecast, the capacity and safety stock. Problem solving allocation is conducted by developing linear programming model that aims to minimize the total cost of the purchase, transportation cost and storage costs at each chain. The results of numerical examples show that the proposed model can generate savings of the purchase cost of 20.84% and select suppliers with mileage closer.
Keywords: Allocation model, linear programming, purchase costs, storage costs, suppliers, transportation costs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14746315 Genetic Programming Approach for Multi-Category Pattern Classification Appliedto Network Intrusions Detection
Authors: K.M. Faraoun, A. Boukelif
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This paper describes a new approach of classification using genetic programming. The proposed technique consists of genetically coevolving a population of non-linear transformations on the input data to be classified, and map them to a new space with a reduced dimension, in order to get a maximum inter-classes discrimination. The classification of new samples is then performed on the transformed data, and so become much easier. Contrary to the existing GP-classification techniques, the proposed one use a dynamic repartition of the transformed data in separated intervals, the efficacy of a given intervals repartition is handled by the fitness criterion, with a maximum classes discrimination. Experiments were first performed using the Fisher-s Iris dataset, and then, the KDD-99 Cup dataset was used to study the intrusion detection and classification problem. Obtained results demonstrate that the proposed genetic approach outperform the existing GP-classification methods [1],[2] and [3], and give a very accepted results compared to other existing techniques proposed in [4],[5],[6],[7] and [8].Keywords: Genetic programming, patterns classification, intrusion detection
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17016314 Retrofitting of Bridge Piers against the Scour Damages: Case Study of the Marand-Soofian Route Bridge
Authors: Shatirah Akib, Hossein Basser, Hojat Karami, Afshin Jahangirzadeh
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Bridge piers which are constructed in the track of high water rivers cause some variations in the flow patterns. This variation mostly is a result of the changes in river sections. Decreasing the river section, bridge piers significantly impress the flow patterns. Once the flow approaches the piers, the stream lines change their order, causing the appearance of different flow patterns around the bridge piers. New flow patterns are created following the geometry and the other technical characteristics of the piers. One of the most significant consequences of this event is the scour generated around the bridge piers which threatens the safety of the structure. In order to determine the properties of scour holes, to find maximum depth of the scour is an important factor. In this manuscript a numerical simulation of the scour around Marand-Soofian route bridge piers has been carried out via SSIIM 2.0 Software and the amount of maximum scour has been achieved subsequently. Eventually the methods for retrofitting of bridge piers against scours and also the methods for decreasing the amount of scour have been offered.
Keywords: Scour, Bridge pier, numerical simulation, SSIIM 2.0.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27566313 Gel-Based Autologous Chondrocyte Implantation (GACI) in the Knee: Multicentric Short Term Study
Authors: Shaival Dalal, Nilesh Shah, Dinshaw Pardiwala, David Rajan, Satyen Sanghavi, Charul Bhanji
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Autologous Chondrocyte Implantation (ACI) is used worldwide since 1998 to treat cartilage defect. GEL based ACI is a new tissue-engineering technique to treat full thickness cartilage defect with fibrin and thrombin as scaffold for chondrocytes. Purpose of this study is to see safety and efficacy of gel based ACI for knee cartilage defect in multiple centres with different surgeons. Gel-based Autologous Chondrocyte Implantation (GACI) has shown effectiveness in treating isolated cartilage defect of knee joint. Long term results are still needed to be studied. This study was followed-up up to two years and showed benefit to patients. All enrolled patients with a mean age of 28.5 years had an average defect size of3 square centimeters, and were grade IV as per ICRS grading. All patients were followed up several times and at several intervals at 6th week, 8th week, 11th week, 17th week, 29th week, 57th week after surgery. The outcomes were measured based on the IKDC (subjective and objective) and MOCART scores.
Keywords: Knee, chondrocyte, autologous chondrocyte implantation, gel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20066312 Performance Analysis of Routing Protocol for WSN Using Data Centric Approach
Authors: A. H. Azni, Madihah Mohd Saudi, Azreen Azman, Ariff Syah Johari
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Sensor Network are emerging as a new tool for important application in diverse fields like military surveillance, habitat monitoring, weather, home electrical appliances and others. Technically, sensor network nodes are limited in respect to energy supply, computational capacity and communication bandwidth. In order to prolong the lifetime of the sensor nodes, designing efficient routing protocol is very critical. In this paper, we illustrate the existing routing protocol for wireless sensor network using data centric approach and present performance analysis of these protocols. The paper focuses in the performance analysis of specific protocol namely Directed Diffusion and SPIN. This analysis reveals that the energy usage is important features which need to be taken into consideration while designing routing protocol for wireless sensor network.Keywords: Data Centric Approach, Directed Diffusion, SPIN WSN Routing Protocol.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25246311 DD Models for Reports Building
Authors: Ljerka Hrženjak-Šego, Željko Polić, Zdravka Aljinović
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In general, reports are a form of representing data in such way that user gets the information he needs. They can be built in various ways, from the simplest (“select from") to the most complex ones (results derived from different sources/tables with complex formulas applied). Furthermore, rules of calculations could be written as a program hard code or built in the database to be used by dynamic code. This paper will introduce two types of reports, defined in the DB structure. The main goal is to manage calculations in optimal way, keeping maintenance of reports as simple and smooth as possible.Keywords: Data Definition diagram, Server Model Diagram, system modelling, reports.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13336310 The Study of Implications on Modern Businesses Performances by Digital Communities: Case of Data Leak
Authors: Asim Majeed, Anwar Ul Haq, Mike, Lloyd-Williams, Arshad Jamal, Usman Butt
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This study aims to investigate the impact of data leak of M&S customers on digital communities. Modern businesses are using digital communities as an important public relations tool for marketing purposes. This form of communication helps companies to build better relationship with their customers which also act as another source of information. The communication between the customers and the organizations is not regulated so users may post positive and negative comments. There are new platforms being developed on a daily basis and it is very crucial for the businesses to not only get themselves familiar with those but also know how to reach their existing and perspective consumers. The driving force of marketing and communication in modern businesses is the digital communities and these are continuously increasing and developing. This phenomenon is changing the way marketing is conducted. The current research has discussed the implications on M&S business performance since the data was exploited on digital communities; users contacted M&S and raised the security concerns. M&S closed down its website for few hours to try to resolve the issue. The next day M&S made a public apology about this incidence. This information was proliferated on various digital communities and it has impacted negatively on M&S brand name, sales and customers. The content analysis approach is being used to collect qualitative data from 100 digital bloggers including social media communities such as Facebook and Twitter. The results and finding provide useful new insights into the nature and form of security concerns of digital users. Findings have theoretical and practical implications. This research will showcase a large corporation utilizing various digital community platforms and can serve as a model for future organizations.
Keywords: Digital, communities, performance, dissemination, implications, data, exploitation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18056309 MCDM Spectrum Handover Models for Cognitive Wireless Networks
Authors: Cesar Hernández, Diego Giral, Fernando Santa
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Spectrum handover is a significant topic in the cognitive radio networks to assure an efficient data transmission in the cognitive radio user’s communications. This paper proposes a comparison between three spectrum handover models: VIKOR, SAW and MEW. Four evaluation metrics are used. These metrics are, accumulative average of failed handover, accumulative average of handover performed, accumulative average of transmission bandwidth and, accumulative average of the transmission delay. As a difference with related work, the performance of the three spectrum handover models was validated with captured data of spectrum occupancy in experiments performed at the GSM frequency band (824 MHz - 849 MHz). These data represent the actual behavior of the licensed users for this wireless frequency band. The results of the comparison show that VIKOR Algorithm provides a 15.8% performance improvement compared to SAW Algorithm and, it is 12.1% better than the MEW Algorithm.Keywords: Cognitive radio, decision making, MEW, SAW, spectrum handover, VIKOR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21436308 Weak Measurement Theory for Discrete Scales
Authors: Jan Newmarch
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With the increasing spread of computers and the internet among culturally, linguistically and geographically diverse communities, issues of internationalization and localization and becoming increasingly important. For some of the issues such as different scales for length and temperature, there is a well-developed measurement theory. For others such as date formats no such theory will be possible. This paper fills a gap by developing a measurement theory for a class of scales previously overlooked, based on discrete and interval-valued scales such as spanner and shoe sizes. The paper gives a theoretical foundation for a class of data representation problems.
Keywords: Data representation, internationalisation, localisation, measurement theory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14346307 Comparison of Number of Waves Surfed and Duration Using Global Positioning System and Inertial Sensors
Authors: J. Madureira, R. Lagido, I. Sousa
Abstract:
Surf is an increasingly popular sport and its performance evaluation is often qualitative. This work aims at using a smartphone to collect and analyze the GPS and inertial sensors data in order to obtain quantitative metrics of the surfing performance. Two approaches are compared for detection of wave rides, computing the number of waves rode in a surfing session, the starting time of each wave and its duration. The first approach is based on computing the velocity from the Global Positioning System (GPS) signal and finding the velocity thresholds that allow identifying the start and end of each wave ride. The second approach adds information from the Inertial Measurement Unit (IMU) of the smartphone, to the velocity thresholds obtained from the GPS unit, to determine the start and end of each wave ride. The two methods were evaluated using GPS and IMU data from two surfing sessions and validated with similar metrics extracted from video data collected from the beach. The second method, combining GPS and IMU data, was found to be more accurate in determining the number of waves, start time and duration. This paper shows that it is feasible to use smartphones for quantification of performance metrics during surfing. In particular, detection of the waves rode and their duration can be accurately determined using the smartphone GPS and IMU.
Keywords: Inertial Measurement Unit (IMU), Global Positioning System (GPS), smartphone, surfing performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1638