Search results for: maintenance strategy selection multiple criteria decision-making analysis
11043 Application of Computer Aided Engineering Tools in Performance Prediction and Fault Detection of Mechanical Equipment of Mining Process Line
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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.Keywords: Computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 183411042 An Intelligent Combined Method Based on Power Spectral Density, Decision Trees and Fuzzy Logic for Hydraulic Pumps Fault Diagnosis
Authors: Kaveh Mollazade, Hojat Ahmadi, Mahmoud Omid, Reza Alimardani
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Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. The aim of this work is to investigate the effectiveness of a new fault diagnosis method based on power spectral density (PSD) of vibration signals in combination with decision trees and fuzzy inference system (FIS). To this end, a series of studies was conducted on an external gear hydraulic pump. After a test under normal condition, a number of different machine defect conditions were introduced for three working levels of pump speed (1000, 1500, and 2000 rpm), corresponding to (i) Journal-bearing with inner face wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii) Journal-bearing with inner face wear plus Gear with tooth face wear (B&GW). The features of PSD values of vibration signal were extracted using descriptive statistical parameters. J48 algorithm is used as a feature selection procedure to select pertinent features from data set. The output of J48 algorithm was employed to produce the crisp if-then rule and membership function sets. The structure of FIS classifier was then defined based on the crisp sets. In order to evaluate the proposed PSD-J48-FIS model, the data sets obtained from vibration signals of the pump were used. Results showed that the total classification accuracy for 1000, 1500, and 2000 rpm conditions were 96.42%, 100%, and 96.42% respectively. The results indicate that the combined PSD-J48-FIS model has the potential for fault diagnosis of hydraulic pumps.Keywords: Power Spectral Density, Machine ConditionMonitoring, Hydraulic Pump, Fuzzy Logic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 271211041 Evaluation of Classification Algorithms for Road Environment Detection
Authors: T. Anbu, K. Aravind Kumar
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The road environment information is needed accurately for applications such as road maintenance and virtual 3D city modeling. Mobile laser scanning (MLS) produces dense point clouds from huge areas efficiently from which the road and its environment can be modeled in detail. Objects such as buildings, cars and trees are an important part of road environments. Different methods have been developed for detection of above such objects, but still there is a lack of accuracy due to the problems of illumination, environmental changes, and multiple objects with same features. In this work the comparison between different classifiers such as Multiclass SVM, kNN and Multiclass LDA for the road environment detection is analyzed. Finally the classification accuracy for kNN with LBP feature improved the classification accuracy as 93.3% than the other classifiers.Keywords: Classifiers, feature extraction, mobile-based laser scanning, object location estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 77411040 Aspect Oriented Software Architecture
Authors: Pradip Peter Dey, Ronald F. Gonzales, Gordon W. Romney, Mohammad Amin, Bhaskar Raj Sinha
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Natural language processing systems pose a unique challenge for software architectural design as system complexity has increased continually and systems cannot be easily constructed from loosely coupled modules. Lexical, syntactic, semantic, and pragmatic aspects of linguistic information are tightly coupled in a manner that requires separation of concerns in a special way in design, implementation and maintenance. An aspect oriented software architecture is proposed in this paper after critically reviewing relevant architectural issues. For the purpose of this paper, the syntactic aspect is characterized by an augmented context-free grammar. The semantic aspect is composed of multiple perspectives including denotational, operational, axiomatic and case frame approaches. Case frame semantics matured in India from deep thematic analysis. It is argued that lexical, syntactic, semantic and pragmatic aspects work together in a mutually dependent way and their synergy is best represented in the aspect oriented approach. The software architecture is presented with an augmented Unified Modeling Language.Keywords: Language engineering, parsing, software design, user experience.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 174311039 Applying Case-Based Reasoning in Supporting Strategy Decisions
Authors: S. M. Seyedhosseini, A. Makui, M. Ghadami
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Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.
Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 217411038 Oman’s Position in U.S. Tourists’ Mind: The Use of Importance-Performance Analysis on Destination Attributes
Authors: Mohammed Gamil Montasser, Angelo Battaglia
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Tourism is making its presence felt across the Sultanate of Oman. The story is one of the most recognized phenomena as a sustainable solid growth and is considered a remarkable outcome for any destination. The competitive situation and challenges within the tourism industry worldwide entail a better understanding of the destination position and its image to achieve Oman’s aspiration to retain its international reputation as one of the most desirable destinations in the Middle East. To access general perceptions of Oman’s attributes, their importance and their influences among U.S. tourists, an online survey was conducted with 522 American travelers who have traveled internationally, including non-visitors, virtual-visitors and visitors to Oman. This research involved a total of 36 attributes in the survey. Participants were asked to rate their agreement on how each attribute represented Oman and how important each attribute was for selecting destinations on 5- point Likert Scale. They also indicated if each attribute has a positive, neutral or negative influence on their destination selection. Descriptive statistics and importance performance analysis (IPA) were conducted. IPA illustrated U.S. tourists’ perceptions of Oman’s destination attributes and their importance in destination selection on a matrix with four quadrants, divided by actual mean value in each grid for importance (M=3.51) and performance (M=3.57). Oman tourism organizations and destination managers may use these research findings for future marketing and management efforts toward the U.S. travel market.
Keywords: Analysis of importance and performance, destination attributes, Oman’s position, U.S. tourists.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 152311037 Ideological Framing in Television News: The Case of “Settlement Process”
Authors: Mete Kazaz, Birol Gülnar
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Television news has gained a new dimension in terms of ideological approaches as a result of such factors as globalization, cross monopolization, presence of international companies etc. and certain strategies have been developed at the production, presentation and distribution stages of news. In this study, television news about a process called “settlement process” was investigated. In this framework, news about the settlement process on TV channels of TRT 1, ATV, FOX TV, NTV, HABERTÜRK, TRT HABER and STV was investigated using the content analysis method in terms of the strategies the ideology construction, attitude towards the party in power, attitude towards parties in opposition and attitude towards BDP (Peace and Democracy Part) and Imrali (the island where Abdullah Ocalan, head of PKK, is kept). First, the aforementioned TV channels were selected randomly from 3 groups in order to be able to reveal the representational capacity of commercial, news and public channels. The study covers 557 news items broadcast in the main news bulletins between the dates of 15 March 2013 and 15 March 2013. While there was a positive attitude towards the government in a sizable portion of the news about the settlement process (63.6%), the attitude of 25.3% of the news was impartial towards the government and 11.3% had a negative attitude. On the other hand, there was a negative attitude towards the Opposition in a considerable portion of the news about the settlement process (56.1%). The attitude of 35.9% of the news towards the Opposition was impartial whereas 8.0% had a positive attitude. While 34.9% of the news about the settlement process used the legitimization strategy from among the ideology construction strategies, 22.8% used the unification strategy, 15.7% the reification strategy, 15.6% fractional and 11% concealment/mystification strategy.
Keywords: Attitude, Ideological Framing, Television News.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 178211036 Approach Based on Fuzzy C-Means for Band Selection in Hyperspectral Images
Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge
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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.
Keywords: Band selection, fuzzy C-means, K-means, hyperspectral image.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 181511035 On the Fast Convergence of DD-LMS DFE Using a Good Strategy Initialization
Authors: Y.Ben Jemaa, M.Jaidane
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In wireless communication system, a Decision Feedback Equalizer (DFE) to cancel the intersymbol interference (ISI) is required. In this paper, an exact convergence analysis of the (DFE) adapted by the Least Mean Square (LMS) algorithm during the training phase is derived by taking into account the finite alphabet context of data transmission. This allows us to determine the shortest training sequence that allows to reach a given Mean Square Error (MSE). With the intention of avoiding the problem of ill-convergence, the paper proposes an initialization strategy for the blind decision directed (DD) algorithm. This then yields a semi-blind DFE with high speed and good convergence.
Keywords: Adaptive Decision Feedback Equalizer, PerformanceAnalysis, Finite Alphabet Case, Ill-Convergence, Convergence speed.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 207111034 Research on IBR-Driven Distributed Collaborative Visualization System
Authors: Yin Runmin, Song Changfeng
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Image-based Rendering(IBR) techniques recently reached in broad fields which leads to a critical challenge to build up IBR-Driven visualization platform where meets requirement of high performance, large bounds of distributed visualization resource aggregation and concentration, multiple operators deploying and CSCW design employing. This paper presents an unique IBR-based visualization dataflow model refer to specific characters of IBR techniques and then discusses prominent feature of IBR-Driven distributed collaborative visualization (DCV) system before finally proposing an novel prototype. The prototype provides a well-defined three level modules especially work as Central Visualization Server, Local Proxy Server and Visualization Aid Environment, by which data and control for collaboration move through them followed the previous dataflow model. With aid of this triple hierarchy architecture of that, IBR oriented application construction turns to be easy. The employed augmented collaboration strategy not only achieve convenient multiple users synchronous control and stable processing management, but also is extendable and scalable.Keywords: Image-Based Rendering, Distributed CollaborativeVisualization, Computer Supported Cooperative Work, Model andSimulation, Modular Visualization Environment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 148611033 Prediction Heating Values of Lignocellulosics from Biomass Characteristics
Authors: Kaltima Phichai, Pornchanoke Pragrobpondee, Thaweesak Khumpart, Samorn Hirunpraditkoon
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The paper provides biomasses characteristics by proximate analysis (volatile matter, fixed carbon and ash) and ultimate analysis (carbon, hydrogen, nitrogen and oxygen) for the prediction of the heating value equations. The heating value estimation of various biomasses can be used as an energy evaluation. Thirteen types of biomass were studied. Proximate analysis was investigated by mass loss method and infrared moisture analyzer. Ultimate analysis was analyzed by CHNO analyzer. The heating values varied from 15 to 22.4MJ kg-1. Correlations of the calculated heating value with proximate and ultimate analyses were undertaken using multiple regression analysis and summarized into three and two equations, respectively. Correlations based on proximate analysis illustrated that deviation of calculated heating values from experimental heating values was higher than the correlations based on ultimate analysis.
Keywords: Heating value equation, Proximate analysis, Ultimate analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 372411032 A Multiple-Objective Environmental Rationalization and Optimization for Material Substitution in the Production of Stone-Washed Jeans- Garments
Authors: Nabil A. Ibrahim, Nabil M. Abdel Moneim, Mohamed A. Ramadan, Marwa M. Hosni
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As the Textile Industry is the second largest industry in Egypt and as small and medium-sized enterprises (SMEs) make up a great portion of this industry therein it is essential to apply the concept of Cleaner Production for the purpose of reducing pollution. In order to achieve this goal, a case study concerned with ecofriendly stone-washing of jeans-garments was investigated. A raw material-substitution option was adopted whereby the toxic potassium permanganate and sodium sulfide were replaced by the environmentally compatible hydrogen peroxide and glucose respectively where the concentrations of both replaced chemicals together with the operating time were optimized. In addition, a process-rationalization option involving four additional processes was investigated. By means of criteria such as product quality, effluent analysis, mass and heat balance; and cost analysis with the aid of a statistical model, a process optimization treatment revealed that the superior process optima were 50%, 0.15% and 50min for H2O2 concentration, glucose concentration and time, respectively. With these values the superior process ought to reduce the annual cost by about EGP 105 relative to the currently used conventional method.Keywords: Cleaner Production, Eco-friendly of jeans garments, Stone washing, Textile Industry, Textile Wet Processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 207311031 Analytical Mathematical Expression for the Channel Capacity of a Power and Rate Simultaneous Adaptive Cellular DS/FFH-CDMA Systemin a Rayleigh Fading Channel
Authors: P.Varzakas
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In this paper, an accurate theoretical analysis for the achievable average channel capacity (in the Shannon sense) per user of a hybrid cellular direct-sequence/fast frequency hopping code-division multiple-access (DS/FFH-CDMA) system operating in a Rayleigh fading environment is presented. The analysis covers the downlink operation and leads to the derivation of an exact mathematical expression between the normalized average channel capacity available to each system-s user, under simultaneous optimal power and rate adaptation and the system-s parameters, as the number of hops per bit, the processing gain applied, the number of users per cell and the received signal-tonoise power ratio over the signal bandwidth. Finally, numerical results are presented to illustrate the proposed mathematical analysis.
Keywords: Shannon capacity, adaptive systems, code-division multiple access, fading channels.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 152611030 Real-Time Episodic Memory Construction for Optimal Action Selection in Cognitive Robotics
Authors: Deon de Jager, Yahya Zweiri, Dimitrios Makris
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The three most important components in the cognitive architecture for cognitive robotics is memory representation, memory recall, and action-selection performed by the executive. In this paper, action selection, performed by the executive, is defined as a memory quantification and optimization process. The methodology describes the real-time construction of episodic memory through semantic memory optimization. The optimization is performed by set-based particle swarm optimization, using an adaptive entropy memory quantification approach for fitness evaluation. The performance of the approach is experimentally evaluated by simulation, where a UAV is tasked with the collection and delivery of a medical package. The experiments show that the UAV dynamically uses the episodic memory to autonomously control its velocity, while successfully completing its mission.
Keywords: Cognitive robotics, semantic memory, episodic memory, maximum entropy principle, particle swarm optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 163511029 Adhesion Properties of Bifidobacterium Pseudocatenulatum G4 and Bifidobacterium Longum BB536 on HT-29 Human Epithelium Cell Line at Different Times and pH
Authors: Ali Q. S., Farid A. J., Kabeir B. M., Zamberi S., Shuhaimi M., Ghazali H. M., Yazid A. M.
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Adhesion to the human intestinal cell is considered as one of the main selection criteria of lactic acid bacteria for probiotic use. The adhesion ability of two Bifidobacteriums strains Bifidobacterium longum BB536 and Bifidobacterium psudocatenulatum G4 was done using HT-29 human epithelium cell line as in vitro study. Four different level of pH were used 5.6, 5.7, 6.6, and 6.8 with four different times 15, 30, 60, and 120 min. Adhesion was quantified by counting the adhering bacteria after Gram staining. The adhesion of B. longum BB536 was higher than B. psudocatenulatum G4. Both species showed significant different in the adhesion properties at the factors tested. The highest adhesion for both Bifidobacterium was observed at 120 min and the low adhesion was in 15 min. The findings of this study will contribute to the introduction of new effective probiotic strain for future utilization.Keywords: Bifidobacterium, Adhesion, HT-29 human epithelium cells.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 185011028 A Proposed Managerial Framework for International Marketing Operations in the Fast Food Industry
Authors: Emmanuel Selase Asamoah, Miloslava Chovancová
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When choosing marketing strategies for international markets, one of the factors that should be considered is the cultural differences that exist among consumers in different countries. If the branding strategy has to be contextual and in tune with the culture, then the brand positioning variables has to interact, adapt and respond to the cultural variables in which the brand is operating. This study provides an overview of the relevance of culture in the development of an effective branding strategy in the international business environment. Hence, the main objective of this study is to provide a managerial framework for developing strategies for cross cultural brand management. The framework is useful because it incorporates the variables that are important in the competitiveness of fast food enterprises irrespective of their size. It provides practical, proactive and result oriented analysis that will help fast food firms augment their strategies in the international fast food markets. The proposed framework will enable managers understand the intricacies involved in branding in the global fast food industry and decrease the use of 'trial and error' when entering into unfamiliar markets.
Keywords: culture, branding strategy, marketing mix, mass customization, standardization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 264411027 Evaluation of Stiffness and Damping Coefficients of Multiple Axial Groove Water Lubricated Bearing Using Computational Fluid Dynamics
Authors: Neville Fernandes, Satish Shenoy B., Raghuvir Pai B., Rammohan S. Pai B, Shrikanth Rao.D
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This research details a Computational Fluid Dynamics (CFD) approach to model fluid flow in a journal bearing with 8 equispaced semi-circular axial grooves. Water is used as the lubricant and is fed from one end of the bearing to the other, under pressure. The geometry of the bearing is modeled using a commercially available modeling software GAMBIT and the flow analysis is performed using a dedicated CFD analysis software FLUENT. The pressure distribution in the bearing clearance is obtained from FLUENT for various whirl ratios and is used to calculate the hydrodynamic force components in the radial and tangential direction of the bearing. These values along with the various whirl speeds can be used to do a regression analysis to determine the stiffness and damping coefficients. The values obtained are then compared with the stiffness and damping coefficients of a 3 Axial groove water lubricated journal bearing and those obtained from a FORTRAN code for a similar bearing.
Keywords: CFD, multiple axial groove, Water lubricated, Stiffness and Damping Coefficients.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 313411026 Modeling Metrics for Monitoring Software Project Performance Based On the GQM Model
Authors: Mariayee Doraisamy, Suhaimi Bin Ibrahim, Mohd Naz’ri Mahrin
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There are several methods to monitor software projects and the objective for monitoring is to ensure that the software projects are developed and delivered successfully. A performance measurement is a method that is closely associated with monitoring and it can be scrutinized by looking at two important attributes which are efficiency and effectiveness both of which are factors that are important for the success of a software project. Consequently, a successful steering is achieved by monitoring and controlling a software project via the performance measurement criteria and metrics. Hence, this paper is aimed at identifying the performance measurement criteria and the metrics for monitoring the performance of a software project by using the Goal Question Metrics (GQM) approach. The GQM approach is utilized to ensure that the identified metrics are reliable and useful. These identified metrics are useful guidelines for project managers to monitor the performance of their software projects.
Keywords: Software project performance, Goal Question Metrics, Performance Measurement Criteria, Metrics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 252611025 Dynamic Risk Identification Using Fuzzy Failure Mode Effect Analysis in Fabric Process Industries: A Research Article as Management Perspective
Authors: A. Sivakumar, S. S. Darun Prakash, P. Navaneethakrishnan
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In and around Erode District, it is estimated that more than 1250 chemical and allied textile processing fabric industries are affected, partially closed and shut off for various reasons such as poor management, poor supplier performance, lack of planning for productivity, fluctuation of output, poor investment, waste analysis, labor problems, capital/labor ratio, accumulation of stocks, poor maintenance of resources, deficiencies in the quality of fabric, low capacity utilization, age of plant and equipment, high investment and input but low throughput, poor research and development, lack of energy, workers’ fear of loss of jobs, work force mix and work ethic. The main objective of this work is to analyze the existing conditions in textile fabric sector, validate the break even of Total Productivity (TP), analyze, design and implement fuzzy sets and mathematical programming for improvement of productivity and quality dimensions in the fabric processing industry. It needs to be compatible with the reality of textile and fabric processing industries. The highly risk events from productivity and quality dimension were found by fuzzy systems and results are wrapped up among the textile fabric processing industry.
Keywords: Break Even Point, Fuzzy Crisp Data, Fuzzy Sets, Productivity, Productivity Cycle, Total Productive Maintenance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 190311024 Clustering for Detection of Population Groups at Risk from Anticholinergic Medication
Authors: Amirali Shirazibeheshti, Tarik Radwan, Alireza Ettefaghian, Farbod Khanizadeh, George Wilson, Cristina Luca
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Anticholinergic medication has been associated with events such as falls, delirium, and cognitive impairment in older patients. To further assess this, anticholinergic burden scores have been developed to quantify risk. A risk model based on clustering was deployed in a healthcare management system to cluster patients into multiple risk groups according to anticholinergic burden scores of multiple medicines prescribed to patients to facilitate clinical decision-making. To do so, anticholinergic burden scores of drugs were extracted from the literature which categorizes the risk on a scale of 1 to 3. Given the patients’ prescription data on the healthcare database, a weighted anticholinergic risk score was derived per patient based on the prescription of multiple anticholinergic drugs. This study was conducted on 300,000 records of patients currently registered with a major regional UK-based healthcare provider. The weighted risk scores were used as inputs to an unsupervised learning algorithm (mean-shift clustering) that groups patients into clusters that represent different levels of anticholinergic risk. This work evaluates the association between the average risk score and measures of socioeconomic status (index of multiple deprivation) and health (index of health and disability). The clustering identifies a group of 15 patients at the highest risk from multiple anticholinergic medication. Our findings show that this group of patients is located within more deprived areas of London compared to the population of other risk groups. Furthermore, the prescription of anticholinergic medicines is more skewed to female than male patients, suggesting that females are more at risk from this kind of multiple medication. The risk may be monitored and controlled in a healthcare management system that is well-equipped with tools implementing appropriate techniques of artificial intelligence.
Keywords: Anticholinergic medication, socioeconomic status, deprivation, clustering, risk analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 107011023 An Energy Reverse AODV Routing Protocol in Ad Hoc Mobile Networks
Authors: Said Khelifa, Zoulikha Mekkakia Maaza
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In this paper we present a full performance analysis of an energy conserving routing protocol in mobile ad hoc network, named ER-AODV (Energy Reverse Ad-hoc On-demand Distance Vector routing). ER-AODV is a reactive routing protocol based on a policy which combines two mechanisms used in the basic AODV protocol. AODV and most of the on demand ad hoc routing protocols use single route reply along reverse path. Rapid change of topology causes that the route reply could not arrive to the source node, i.e. after a source node sends several route request messages, the node obtains a reply message, and this increases in power consumption. To avoid these problems, we propose a mechanism which tries multiple route replies. The second mechanism proposes a new adaptive approach which seeks to incorporate the metric "residual energy " in the process route selection, Indeed the residual energy of mobile nodes were considered when making routing decisions. The results of simulation show that protocol ER-AODV answers a better energy conservation.
Keywords: Ad hoc mobile networks, Energy AODV, Energy consumption, ER-AODV, Reverse AODV.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 233911022 Explorative Data Mining of Constructivist Learning Experiences and Activities with Multiple Dimensions
Authors: Patrick Wessa, Bart Baesens
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This paper discusses the use of explorative data mining tools that allow the educator to explore new relationships between reported learning experiences and actual activities, even if there are multiple dimensions with a large number of measured items. The underlying technology is based on the so-called Compendium Platform for Reproducible Computing (http://www.freestatistics.org) which was built on top the computational R Framework (http://www.wessa.net).Keywords: Reproducible computing, data mining, explorative data analysis, compendium technology, computer assisted education
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 125311021 Multiple Sensors and JPDA-IMM-UKF Algorithm for Tracking Multiple Maneuvering Targets
Authors: Wissem Saidani, Yacine Morsly, Mohand Saïd Djouadi
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In this paper, we consider the problem of tracking multiple maneuvering targets using switching multiple target motion models. With this paper, we aim to contribute in solving the problem of model-based body motion estimation by using data coming from visual sensors. The Interacting Multiple Model (IMM) algorithm is specially designed to track accurately targets whose state and/or measurement (assumed to be linear) models changes during motion transition. However, when these models are nonlinear, the IMM algorithm must be modified in order to guarantee an accurate track. In this paper we propose to avoid the Extended Kalman filter because of its limitations and substitute it with the Unscented Kalman filter which seems to be more efficient especially according to the simulation results obtained with the nonlinear IMM algorithm (IMMUKF). To resolve the problem of data association, the JPDA approach is combined with the IMM-UKF algorithm, the derived algorithm is noted JPDA-IMM-UKF.Keywords: Estimation, Kalman filtering, Multi-Target Tracking, Visual servoing, data association.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 256411020 A Method for Modeling Multiple Antenna Channels
Authors: S. Rajabi, M. ArdebiliPoor, M. Shahabadi
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In this paper we propose a method for modeling the correlation between the received signals by two or more antennas operating in a multipath environment. Considering the maximum excess delay in the channel being modeled, an elliptical region surrounding both transmitter and receiver antennas is produced. A number of scatterers are randomly distributed in this region and scatter the incoming waves. The amplitude and phase of incoming waves are computed and used to obtain statistical properties of the received signals. This model has the distinguishable advantage of being applicable for any configuration of antennas. Furthermore the common PDF (Probability Distribution Function) of received wave amplitudes for any pair of antennas can be calculated and used to produce statistical parameters of received signals.Keywords: MIMO (Multiple Input Multiple Output), SIMO (Single Input Multiple Output), GBSBEM (Geometrically Based Single Bounce Elliptical Model).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 142211019 Robust Stability Criteria for Uncertain Genetic Regulatory Networks with Time-Varying Delays
Authors: Wenqin Wang, Shouming Zhong
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This paper presents the robust stability criteria for uncertain genetic regulatory networks with time-varying delays. One key point of the criterion is that the decomposition of the matrix ˜D into ˜D = ˜D1 + ˜D2. This decomposition corresponds to a decomposition of the delayed terms into two groups: the stabilizing ones and the destabilizing ones. This technique enables one to take the stabilizing effect of part of the delayed terms into account. Meanwhile, by choosing an appropriate new Lyapunov functional, a new delay-dependent stability criteria is obtained and formulated in terms of linear matrix inequalities (LMIs). Finally, numerical examples are presented to illustrate the effectiveness of the theoretical results.
Keywords: Genetic regulatory network, Time-varying delay, Uncertain system, Lyapunov-Krasovskii functional
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 152311018 A Methodology for Automatic Diversification of Document Categories
Authors: Dasom Kim, Chen Liu, Myungsu Lim, Soo-Hyeon Jeon, Byeoung Kug Jeon, Kee-Young Kwahk, Namgyu Kim
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Recently, numerous documents including large volumes of unstructured data and text have been created because of the rapid increase in the use of social media and the Internet. Usually, these documents are categorized for the convenience of users. Because the accuracy of manual categorization is not guaranteed, and such categorization requires a large amount of time and incurs huge costs. Many studies on automatic categorization have been conducted to help mitigate the limitations of manual categorization. Unfortunately, most of these methods cannot be applied to categorize complex documents with multiple topics because they work on the assumption that individual documents can be categorized into single categories only. Therefore, to overcome this limitation, some studies have attempted to categorize each document into multiple categories. However, the learning process employed in these studies involves training using a multi-categorized document set. These methods therefore cannot be applied to the multi-categorization of most documents unless multi-categorized training sets using traditional multi-categorization algorithms are provided. To overcome this limitation, in this study, we review our novel methodology for extending the category of a single-categorized document to multiple categorizes, and then introduce a survey-based verification scenario for estimating the accuracy of our automatic categorization methodology.Keywords: Big Data Analysis, Document Classification, Text Mining, Topic Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 174611017 Optimization of Air Pollution Control Model for Mining
Authors: Zunaira Asif, Zhi Chen
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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM2.5, PM10, NOx, and SO2. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NOx and SO2 reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.
Keywords: Air pollution, linear programming, mining, optimization, treatment technologies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 160711016 A Study of the Adaptive Reuse for School Land Use Strategy: An Application of the Analytic Network Process and Big Data
Authors: Wann-Ming Wey
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In today's popularity and progress of information technology, the big data set and its analysis are no longer a major conundrum. Now, we could not only use the relevant big data to analysis and emulate the possible status of urban development in the near future, but also provide more comprehensive and reasonable policy implementation basis for government units or decision-makers via the analysis and emulation results as mentioned above. In this research, we set Taipei City as the research scope, and use the relevant big data variables (e.g., population, facility utilization and related social policy ratings) and Analytic Network Process (ANP) approach to implement in-depth research and discussion for the possible reduction of land use in primary and secondary schools of Taipei City. In addition to enhance the prosperous urban activities for the urban public facility utilization, the final results of this research could help improve the efficiency of urban land use in the future. Furthermore, the assessment model and research framework established in this research also provide a good reference for schools or other public facilities land use and adaptive reuse strategies in the future.
Keywords: Adaptive reuse, analytic network process, big data, land use strategy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 92111015 Creeping Control Strategy for Direct Shift Gearbox Based on the Investigation of Temperature Variation of the Wet Clutch
Authors: Biao Ma, Jikai Liu, Man Chen, Jianpeng Wu, Liyong Wang, Changsong Zheng
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Proposing an appropriate control strategy is an effective and practical way to address the overheat problems of the wet multi-plate clutch in Direct Shift Gearbox under the long-time creeping condition. To do so, the temperature variation of the wet multi-plate clutch is investigated firstly by establishing a thermal resistance model for the gearbox cooling system. To calculate the generated heat flux and predict the clutch temperature precisely, the friction torque model is optimized by introducing an improved friction coefficient, which is related to the pressure, the relative speed and the temperature. After that, the heat transfer model and the reasonable friction torque model are employed by the vehicle powertrain model to construct a comprehensive co-simulation model for the Direct Shift Gearbox (DSG) vehicle. A creeping control strategy is then proposed and, to evaluate the vehicle performance, the safety temperature (250 ℃) is particularly adopted as an important metric. During the creeping process, the temperature of two clutches is always under the safety value (250 ℃), which demonstrates the effectiveness of the proposed control strategy in avoiding the thermal failures of clutches.
Keywords: Creeping control strategy, direct shift gearbox, temperature variation, wet clutch.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 72211014 Consistency Model and Synchronization Primitives in SDSMS
Authors: Dalvinder Singh Dhaliwal, Parvinder S. Sandhu, S. N. Panda
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This paper is on the general discussion of memory consistency model like Strict Consistency, Sequential Consistency, Processor Consistency, Weak Consistency etc. Then the techniques for implementing distributed shared memory Systems and Synchronization Primitives in Software Distributed Shared Memory Systems are discussed. The analysis involves the performance measurement of the protocol concerned that is Multiple Writer Protocol. Each protocol has pros and cons. So, the problems that are associated with each protocol is discussed and other related things are explored.
Keywords: Distributed System, Single owner protocol, Multiple owner protocol
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1390