Search results for: Statistical%20size%20effect
1076 Model Discovery and Validation for the Qsar Problem using Association Rule Mining
Authors: Luminita Dumitriu, Cristina Segal, Marian Craciun, Adina Cocu, Lucian P. Georgescu
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There are several approaches in trying to solve the Quantitative 1Structure-Activity Relationship (QSAR) problem. These approaches are based either on statistical methods or on predictive data mining. Among the statistical methods, one should consider regression analysis, pattern recognition (such as cluster analysis, factor analysis and principal components analysis) or partial least squares. Predictive data mining techniques use either neural networks, or genetic programming, or neuro-fuzzy knowledge. These approaches have a low explanatory capability or non at all. This paper attempts to establish a new approach in solving QSAR problems using descriptive data mining. This way, the relationship between the chemical properties and the activity of a substance would be comprehensibly modeled.Keywords: association rules, classification, data mining, Quantitative Structure - Activity Relationship.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17771075 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 14151074 Analytical and Statistical Study of the Parameters of Expansive Soil
Authors: A. Medjnoun, R. Bahar
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The disorders caused by the shrinking-swelling phenomenon are prevalent in arid and semi-arid in the presence of swelling clay. This soil has the characteristic of changing state under the effect of water solicitation (wetting and drying). A set of geotechnical parameters is necessary for the characterization of this soil type, such as state parameters, physical and chemical parameters and mechanical parameters. Some of these tests are very long and some are very expensive, hence the use or methods of predictions. The complexity of this phenomenon and the difficulty of its characterization have prompted researchers to use several identification parameters in the prediction of swelling potential. This document is an analytical and statistical study of geotechnical parameters affecting the potential of swelling clays. This work is performing on a database obtained from investigations swelling Algerian soil. The obtained observations have helped us to understand the soil swelling structure and its behavior.
Keywords: Analysis, estimated model, parameter identification, Swelling of clay.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12771073 Effect of Heat Treatment on the Portevin-Le Chatelier Effect of Al-2.5%Mg Alloy
Authors: A. Chatterjee, A. Sarkar, N. Gayathri, P. Mukherjee, P. Barat
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An experimental study is presented on the effect of microstructural change on the Portevin-Le Chatelier effect behaviour of Al-2.5%Mg alloy. Tensile tests are performed on the as received and heat treated (at 400 ºC for 16 hours) samples for a wide range of strain rates. The serrations observed in the stress-time curve are investigated from statistical analysis point of view. Microstructures of the samples are characterized by optical metallography and X-ray diffraction. It is found that the excess vacancy generated due to heat treatment leads to decrease in the strain rate sensitivity and the increase in the number of stress drop occurrences per unit time during the PLC effect. The microstructural parameters like domain size, dislocation density have no appreciable effect on the PLC effect as far as the statistical behavior of the serrations is considered.Keywords: Dynamic strain ageing, Heat treatment, Portevin-LeChatelier effect
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22231072 A Hybrid GMM/SVM System for Text Independent Speaker Identification
Authors: Rafik Djemili, Mouldi Bedda, Hocine Bourouba
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This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.Keywords: Speaker identification, Gaussian mixture model (GMM), support vector machine (SVM), hybrid GMM/SVM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22251071 Experimental Investigation of On-Body Channel Modelling at 2.45 GHz
Authors: Hasliza A. Rahim, Fareq Malek, Nur A. M. Affendi, Azuwa Ali, Norshafinash Saudin, Latifah Mohamed
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This paper presents the experimental investigation of on-body channel fading at 2.45 GHz considering two effects of the user body movement; stationary and mobile. A pair of body-worn antennas was utilized in this measurement campaign. A statistical analysis was performed by comparing the measured on-body path loss to five well-known distributions; lognormal, normal, Nakagami, Weibull and Rayleigh. The results showed that the average path loss of moving arm varied higher than the path loss in sitting position for upper-arm-to-left-chest link, up to 3.5 dB. The analysis also concluded that the Nakagami distribution provided the best fit for most of on-body static link path loss in standing still and sitting position, while the arm movement can be best described by log-normal distribution.
Keywords: On-Body channel communications, fading characteristics, statistical model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15311070 Comparing Machine Learning Estimation of Fuel Consumption of Heavy-Duty Vehicles
Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi
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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.Keywords: Artificial neural networks, fuel consumption, machine learning, regression, statistical tests.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8081069 What is the Key Element for the Territory's State of Development?
Authors: J. Lonska, V. Boronenko
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The result of process of territory-s development is the territory-s state of development (TSoD), which is pointed towards the provision and improvement of people-s life conditions. The authors offer to measure the TSoD according to their own developed model. Using the available statistical data regarding the values of model-s elements, the authors empirically show which element mainly determines the TSoD. The findings of the research showed that the key elements of the TSoD are the “Material welfare of people" and “People-s health". Performing a deeper statistical analysis of correlation between these elements, it turned out that it is not so necessary for a country to be bent on trying to increase the material growth of a territory, because a relatively high index of life expectancy at birth could be ensured also by much more modest material resources. On the other hand, the economical feedback of longer lifespan within countries with lower material performance is also relatively low.
Keywords: Development indices, health, territory's state of development, wealth.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11801068 An AK-Chart for the Non-Normal Data
Authors: Chia-Hau Liu, Tai-Yue Wang
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Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurement from manufacturing processes are normal distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the propose control charts.
Keywords: Multivariate control chart, statistical process control, one-class classification method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22591067 Predictive Maintenance of Industrial Shredders: Efficient Operation through Real-Time Monitoring Using Statistical Machine Learning
Authors: Federico Pittino, Dominik Holzmann, Krithika Sayar-Chand, Stefan Moser, Sebastian Pliessnig, Thomas Arnold
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The shredding of waste materials is a key step in the recycling process towards circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need of frequent maintenance of critical components. The maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for several months and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring a very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for efficient operation of industrial shredders.
Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6181066 Time-Domain Analysis of Pulse Parameters Effects on Crosstalk (In High Speed Circuits)
Authors: L. Tani, N. El Ouzzani
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Crosstalk among interconnects and printed-circuit board (PCB) traces is a major limiting factor of signal quality in highspeed digital and communication equipments especially when fast data buses are involved. Such a bus is considered as a planar multiconductor transmission line. This paper will demonstrate how the finite difference time domain (FDTD) method provides an exact solution of the transmission-line equations to analyze the near end and the far end crosstalk. In addition, this study makes it possible to analyze the rise time effect on the near and far end voltages of the victim conductor. The paper also discusses a statistical analysis, based upon a set of several simulations. Such analysis leads to a better understanding of the phenomenon and yields useful information.Keywords: Multiconductor transmission line, Crosstalk, Finite difference time domain (FDTD), printed-circuit board (PCB), Rise time, Statistical analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17651065 Words Reordering based on Statistical Language Model
Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou
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There are multiple reasons to expect that detecting the word order errors in a text will be a difficult problem, and detection rates reported in the literature are in fact low. Although grammatical rules constructed by computer linguists improve the performance of grammar checker in word order diagnosis, the repairing task is still very difficult. This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The comparative advantage of this method is that works with a large set of words, and avoids the laborious and costly process of collecting word order errors for creating error patterns.Keywords: Permutations filtering, Statistical languagemodel N-grams, Word order errors
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15751064 Statistical Process Optimization Through Multi-Response Surface Methodology
Authors: S. Raissi, R- Eslami Farsani
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In recent years, response surface methodology (RSM) has brought many attentions of many quality engineers in different industries. Most of the published literature on robust design methodology is basically concerned with optimization of a single response or quality characteristic which is often most critical to consumers. For most products, however, quality is multidimensional, so it is common to observe multiple responses in an experimental situation. Through this paper interested person will be familiarize with this methodology via surveying of the most cited technical papers. It is believed that the proposed procedure in this study can resolve a complex parameter design problem with more than two responses. It can be applied to those areas where there are large data sets and a number of responses are to be optimized simultaneously. In addition, the proposed procedure is relatively simple and can be implemented easily by using ready-made standard statistical packages.Keywords: Multi-Response Surface Methodology (MRSM), Design of Experiments (DOE), Process modeling, Quality improvement; Robust Design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 44451063 Pattern Recognition of Partial Discharge by Using Simplified Fuzzy ARTMAP
Authors: S. Boonpoke, B. Marungsri
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This paper presents the effectiveness of artificial intelligent technique to apply for pattern recognition and classification of Partial Discharge (PD). Characteristics of PD signal for pattern recognition and classification are computed from the relation of the voltage phase angle, the discharge magnitude and the repeated existing of partial discharges by using statistical and fractal methods. The simplified fuzzy ARTMAP (SFAM) is used for pattern recognition and classification as artificial intelligent technique. PDs quantities, 13 parameters from statistical method and fractal method results, are inputted to Simplified Fuzzy ARTMAP to train system for pattern recognition and classification. The results confirm the effectiveness of purpose technique.Keywords: Partial discharges, PD Pattern recognition, PDClassification, Artificial intelligent, Simplified Fuzzy ARTMAP
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30661062 Various Advanced Statistical Analyses of Index Values Extracted from Outdoor Agricultural Workers Motion Data
Authors: Shinji Kawakura, Ryosuke Shibasaki
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We have been grouping and developing various kinds of practical, promising sensing applied systems concerning agricultural advancement and technical tradition (guidance). These include advanced devices to secure real-time data related to worker motion, and we analyze by methods of various advanced statistics and human dynamics (e.g. primary component analysis, Ward system based cluster analysis, and mapping). What is more, we have been considering worker daily health and safety issues. Targeted fields are mainly common farms, meadows, and gardens. After then, we observed and discussed time-line style, changing data. And, we made some suggestions. The entire plan makes it possible to improve both the aforementioned applied systems and farms.
Keywords: Advanced statistical analysis, wearable sensing system, tradition of skill, supporting for workers, detecting crisis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16211061 A Statistical Model for the Dynamics of Single Cathode Spot in Vacuum Cylindrical Cathode
Authors: Po-Wen Chen, Jin-Yu Wu, Md. Manirul Ali, Yang Peng, Chen-Te Chang, Der-Jun Jan
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Dynamics of cathode spot has become a major part of vacuum arc discharge with its high academic interest and wide application potential. In this article, using a three-dimensional statistical model, we simulate the distribution of the ignition probability of a new cathode spot occurring in different magnetic pressure on old cathode spot surface and at different arcing time. This model for the ignition probability of a new cathode spot was proposed in two typical situations, one by the pure isotropic random walk in the absence of an external magnetic field, other by the retrograde motion in external magnetic field, in parallel with the cathode surface. We mainly focus on developed relationship between the ignition probability density distribution of a new cathode spot and the external magnetic field.Keywords: Cathode spot, vacuum arc discharge, transverse magnetic field, random walk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13901060 A Statistical Study on Young UAE Driver’s Behavior towards Road Safety
Authors: Sadia Afroza, Rakiba Rouf
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Road safety and associated behaviors have received significant attention in recent years, reflecting general public concern. This paper portrays a statistical scenario of the young drivers in UAE with emphasis on various concern points of young driver’s behavior and license issuance. Although there are many factors contributing to road accidents, statistically it is evident that age plays a major role in road accidents. Despite ensuring strict road safety laws enforced by the UAE government, there is a staggering correlation among road accidents and young driver’s at UAE. However, private organizations like BMW and RoadSafetyUAE have extended its support on conducting surveys on driver’s behavior with an aim to ensure road safety. Various strategies such as road safety law enforcement, license issuance, adapting new technologies like safety cameras and raising awareness can be implemented to improve the road safety concerns among young drivers.
Keywords: Driving behavior, GLDS, road safety, UAE drivers, young drivers.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13671059 The Effectiveness of Ultrasound Treatment on the Germination Stimulation of Barley Seed and its Alpha-Amylase Activity
Authors: M. Yaldagard, S.A. Mortazavi, F. Tabatabaie
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In the present study, the effects of ultrasound as emerging technology were investigated on germination stimulation, amount of alpha-amylase activity on dry barley seeds before steeping stage of malting process. All experiments were carried out at 20 KHz on the ultrasonic generator in 3 different ultrasonic intensities (20, 60 and 100% setting from total power of device) and time (5, 10 and 15 min) at constant temperature (30C). For determining the effects of these parameters on enzyme the Fuwa method assay based on the decreased staining value of blue starch–iodine complexes employed for measurement an activity. The results of these assays were analyzed by Qualitek4 software using the Taguchi statistical method to evaluate the factor-s effects on enzyme activity. It has been found that when malting barley is irradiated with an ultrasonic power, a stimulating effect occurs as to the enzyme activity.Keywords: ultrasound, alpha-amylase activity, stimulationand Taguchi statistical method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 45921058 Review of Downscaling Methods in Climate Change and Their Role in Hydrological Studies
Authors: Nishi Bhuvandas, P. V. Timbadiya, P. L. Patel, P. D. Porey
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Recent perceived climate variability raises concerns with unprecedented hydrological phenomena and extremes. Distribution and circulation of the waters of the Earth become increasingly difficult to determine because of additional uncertainty related to anthropogenic emissions. The world wide observed changes in the large-scale hydrological cycle have been related to an increase in the observed temperature over several decades. Although the effect of change in climate on hydrology provides a general picture of possible hydrological global change, new tools and frameworks for modelling hydrological series with nonstationary characteristics at finer scales, are required for assessing climate change impacts. Of the downscaling techniques, dynamic downscaling is usually based on the use of Regional Climate Models (RCMs), which generate finer resolution output based on atmospheric physics over a region using General Circulation Model (GCM) fields as boundary conditions. However, RCMs are not expected to capture the observed spatial precipitation extremes at a fine cell scale or at a basin scale. Statistical downscaling derives a statistical or empirical relationship between the variables simulated by the GCMs, called predictors, and station-scale hydrologic variables, called predictands. The main focus of the paper is on the need for using statistical downscaling techniques for projection of local hydrometeorological variables under climate change scenarios. The projections can be then served as a means of input source to various hydrologic models to obtain streamflow, evapotranspiration, soil moisture and other hydrological variables of interest.
Keywords: Climate Change, Downscaling, GCM, RCM.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33611057 The Wijma Delivery Expectancy/Experience Questionnaire (W-DEQ) with Turkish Sample: Confirmatory and Exploratory Factor Analysis
Authors: Oznur Korukcu, Kamile Kukulu, Mehmet Z. Firat
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The propose of this study is to investigate the factor structures of the W-DEQ, originally developed on UK and Swedish women, were confirmed in Turkish samples, and to obtain a new modified factor structure appropriate to Turkish culture. Statistical analyses of the data obtained were performed using SPSS© for Windows version 13.0 and the SAS statistical software Version 9.1. Both confirmatory and exploratory factor analysis of W-DEQ were performed in the study. Factor analysis yielded four factors related to hope, fear, lack of positive anticipation and riskiness. The alpha estimates of the total W-DEQ score were somewhat higher, being 0.92 for the parous and 0.90 for the nulliparous sample. These are well above the accepted limit of 0.70 and indicate excellent levels of internal reliability, thus showing that the questions were appropriate to the Turkish culture and useful scale for the evaluation of fear of childbirth in Turkish pregnants.
Keywords: Confirmatory factor analysis, cross-cultural research, exploratory factor analysis, fear of childbirth.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 51131056 A Hybrid Ontology Based Approach for Ranking Documents
Authors: Sarah Motiee, Azadeh Nematzadeh, Mehrnoush Shamsfard
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Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques to extract phrases from documents and the query and doing stemming on words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done flexible and in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16151055 A New Heuristic Statistical Methodology for Optimizing Queuing Networks Using Discreet Event Simulation
Authors: Mohamad Mahdavi
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Most of the real queuing systems include special properties and constraints, which can not be analyzed directly by using the results of solved classical queuing models. Lack of Markov chains features, unexponential patterns and service constraints, are the mentioned conditions. This paper represents an applied general algorithm for analysis and optimizing the queuing systems. The algorithm stages are described through a real case study. It is consisted of an almost completed non-Markov system with limited number of customers and capacities as well as lots of common exception of real queuing networks. Simulation is used for optimizing this system. So introduced stages over the following article include primary modeling, determining queuing system kinds, index defining, statistical analysis and goodness of fit test, validation of model and optimizing methods of system with simulation.
Keywords: Estimation, queuing system, simulation model, probability distribution, non-Markov chain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16131054 Hardness Variations as Affected by Bar Diameter of AISI 4140 Steel
Authors: Hamad K. Al-Khalid, Ayman M. Alaskari, Samy E. Oraby
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Hardness of the widely used structural steel is of vital importance since it may help in the determination of many mechanical properties of a material under loading situations. In order to obtain reliable information for design, properties homogeneity should be validated. In the current study the hardness variation over the different diameters of the same AISI 4140 bar is investigated. Measurements were taken on the two faces of the stock at equally spaced eight sectors and fifteen layers. Statistical and graphical analysis are performed to asses the distribution of hardness measurements over the specified area. Hardness measurements showed some degree of dispersion with about ± 10% of its nominal value provided by manufacturer. Hardness value is found to have a slight decrease trend as the diameter is reduced. However, an opposite behavior is noticed regarding the sequence of the sector indicating a nonuniform distribution over the same area either on the same face or considering the corresponding sector on the other face (cross section) of the same material bar.Keywords: Hardness; Hardness variation; AISI 4140 steel; Bardiameter; Statistical Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29211053 Observations about the Principal Components Analysis and Data Clustering Techniques in the Study of Medical Data
Authors: Cristina G. Dascâlu, Corina Dima Cozma, Elena Carmen Cotrutz
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The medical data statistical analysis often requires the using of some special techniques, because of the particularities of these data. The principal components analysis and the data clustering are two statistical methods for data mining very useful in the medical field, the first one as a method to decrease the number of studied parameters, and the second one as a method to analyze the connections between diagnosis and the data about the patient-s condition. In this paper we investigate the implications obtained from a specific data analysis technique: the data clustering preceded by a selection of the most relevant parameters, made using the principal components analysis. Our assumption was that, using the principal components analysis before data clustering - in order to select and to classify only the most relevant parameters – the accuracy of clustering is improved, but the practical results showed the opposite fact: the clustering accuracy decreases, with a percentage approximately equal with the percentage of information loss reported by the principal components analysis.Keywords: Data clustering, medical data, principal components analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14901052 Investigating Real Ship Accidents with Descriptive Analysis in Turkey
Authors: İsmail Karaca, Ömer Söner
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The use of advanced methods has been increasing day by day in the maritime sector, which is one of the sectors least affected by the COVID-19 pandemic. It is aimed to minimize accidents, especially by using advanced methods in the investigation of marine accidents. This research aimed to conduct an exploratory statistical analysis of particular ship accidents in the Transport Safety Investigation Center of Turkey database. 46 ship accidents, which occurred between 2010-2018, have been selected from the database. In addition to the availability of a reliable and comprehensive database, taking advantage of the robust statistical models for investigation is critical to improving the safety of ships. Thus, descriptive analysis has been used in the research to identify causes and conditional factors related to different types of ship accidents. The research outcomes underline the fact that environmental factors and day and night ratio have great influence on ship safety.
Keywords: Descriptive analysis, maritime industry, maritime safety, marine accident analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6911051 Optimization of the Nutrient Supplients for Cellulase Production with the Basal Medium Palm Oil Mill Effluent
Authors: Rashid S S, Alam M Z, Karim M I A, Salleh, M H
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A statistical optimization was studied to design a media composition to produce optimum cellulolytic enzyme where palm oil mill effluent (POME) as a basal medium and filamentous fungus, Trichoderma reesei RUT-C30 were used in the liquid state bioconversion(LSB). 2% (w/v) total suspended solid, TSS, of the POME supplemented with 1% (w/v) cellulose, 0.5%(w/v) peptone and 0.02% (v/v) Tween 80 was estimated to produce the optimum CMCase activity of 18.53 U/ml through the statistical analysis followed by the faced centered central composite design(FCCCD). The probability values of cellulose (<0.0011) and peptone (0.0021) indicated the significant effect on the production of cellulase with the determination coefficient (R2) of 0.995.
Keywords: Face centered central composite design (FCCCD), Liquid state bioconversion (LSB), Palm oil mill effluent, Trichoderma reesei RUT C-30.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21311050 ORank: An Ontology Based System for Ranking Documents
Authors: Mehrnoush Shamsfard, Azadeh Nematzadeh, Sarah Motiee
Abstract:
Increasing growth of information volume in the internet causes an increasing need to develop new (semi)automatic methods for retrieval of documents and ranking them according to their relevance to the user query. In this paper, after a brief review on ranking models, a new ontology based approach for ranking HTML documents is proposed and evaluated in various circumstances. Our approach is a combination of conceptual, statistical and linguistic methods. This combination reserves the precision of ranking without loosing the speed. Our approach exploits natural language processing techniques for extracting phrases and stemming words. Then an ontology based conceptual method will be used to annotate documents and expand the query. To expand a query the spread activation algorithm is improved so that the expansion can be done in various aspects. The annotated documents and the expanded query will be processed to compute the relevance degree exploiting statistical methods. The outstanding features of our approach are (1) combining conceptual, statistical and linguistic features of documents, (2) expanding the query with its related concepts before comparing to documents, (3) extracting and using both words and phrases to compute relevance degree, (4) improving the spread activation algorithm to do the expansion based on weighted combination of different conceptual relationships and (5) allowing variable document vector dimensions. A ranking system called ORank is developed to implement and test the proposed model. The test results will be included at the end of the paper.Keywords: Document ranking, Ontology, Spread activation algorithm, Annotation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18791049 The Impact of Environmental Dynamism on Strategic Outsourcing Success
Authors: Mohamad Ghozali Hassan, Abdul Aziz Othman, Mohd Azril Ismail
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Adapting quickly to environmental dynamism is essential for an organization to develop outsourcing strategic and management in order to sustain competitive advantage. This research used the Partial Least Squares Structural Equation Modeling (PLSSEM) tool to investigate the factors of environmental dynamism impact on the strategic outsourcing success among electrical and electronic manufacturing industries in outsourcing management. Statistical results confirm that the inclusion of customer demand, technological change, and competition level as a new combination concept of environmental dynamism, has positive effects on outsourcing success. Additionally, this research demonstrates the acceptability of PLS-SEM as a statistical analysis to furnish a better understanding of environmental dynamism in outsourcing management in Malaysia. A practical finding contributes to academics and practitioners in the field of outsourcing management.
Keywords: Environmental Dynamism, Customer Demand, Technological Change, Competition Level, Outsourcing Success.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21941048 A Relationship Extraction Method from Literary Fiction Considering Korean Linguistic Features
Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim
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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.
Keywords: Data mining, Korean linguistic feature, literary fiction, relationship extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17881047 Estimation of PM2.5 Emissions and Source Apportionment Using Receptor and Dispersion Models
Authors: Swetha Priya Darshini Thammadi, Sateesh Kumar Pisini, Sanjay Kumar Shukla
Abstract:
Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM2.5, while the AERMOD dispersion model has been used to account for missing sources of PM2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.
Keywords: CMB, GIS, AERMOD, PM2.5, fugitive, emission inventory.
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