Search results for: state variables.
1155 Multi-Level Air Quality Classification in China Using Information Gain and Support Vector Machine
Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li
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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.
Keywords: Machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9501154 The Effect of the Hourly Compensation on the Unemployment Rate: Comparative Analysis of United States, Canada and the United Kingdom Using Panel Data Regression Analysis
Authors: Ashiquer Rahman, Hares Mohammad, Ummey Salma
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A country’s hourly compensation and unemployment rates are two of its most crucial components. They are not merely statistics but they have profound effects on individual, families, country, and the economy. They are inversely related to one another. The increased hourly compensation in the manufacturing sector can have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, in order to determine the effect of hourly compensation on unemployment rate, we use the panel data regression models and evaluate the expected link between hourly compensation and unemployment rate. We estimate the fixed effects model (FEM), evaluate the error components model (ECM), and determine which model (the FEM or ECM) is better through pooling all 60 observations. We then analyze and review the data by comparing countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of this extensive research on how the hourly compensation affects unemployment rate. Additionally, this paper offers relevant and useful guideline for the government and academic community to use an econometrics and social approach for the hourly compensation on unemployment rate to eliminate the problem.
Keywords: Hourly compensation, unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 781153 Communication Styles of Business Students: A Comparison of Four National Cultures
Authors: Tiina Brandt, Isaac Wanasika
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Culturally diverse global companies need to understand cultural differences between leaders and employees from different backgrounds. Communication is culturally contingent and has a significant impact on effective execution of leadership goals. The awareness of cultural variations related to communication and interactions will help leaders modify their own behavior, and consequently improve the execution of goals and avoid unnecessary faux pas. Our focus is on young adults that have experienced cultural integration, culturally diverse surroundings in schools and universities, and cultural travels. Our central research problem is to understand the impact of different national cultures on communication. We focus on four countries with distinct national cultures and spatial distribution. The countries are Finland, Indonesia, Russia and USA. Our sample is based on business students (n = 225) from various backgrounds in the four countries. Their responses of communication and leadership styles were analyzed using ANOVA and post-hoc test. Results indicate that culture impacts on communication behavior. Even young culturally-exposed adults with cultural awareness and experience demonstrate cultural differences in their behavior. Apparently, culture is a deeply seated trait that cannot be completely neutralized by environmental variables. Our study offers valuable input for leadership training programs and for expatriates when recognizing specific differences on leaders’ behavior due to culture.
Keywords: Culture, communication, Finland, Indonesia, Russia, USA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6781152 Graphical Programming of Programmable Logic Controllers -Case Study for a Punching Machine-
Authors: Vasile Marinescu, Ionut Clementin Constantin, Alexandru Epureanu, Virgil Teodor
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The Programmable Logic Controller (PLC) plays a vital role in automation and process control. Grafcet is used for representing the control logic, and traditional programming languages are used for describing the pure algorithms. Grafcet is used for dividing the process to be automated in elementary sequences that can be easily implemented. Each sequence represent a step that has associated actions programmed using textual or graphical languages after case. The programming task is simplified by using a set of subroutines that are used in several steps. The paper presents an example of implementation for a punching machine for sheets and plates. The use the graphical languages the programming of a complex sequential process is a necessary solution. The state of Grafcet can be used for debugging and malfunction determination. The use of the method combined with a set of knowledge acquisition for process application reduces the downtime of the machine and improve the productivity.Keywords: Grafcet, Petrinet, PLC, punching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21211151 Quantitative Precipitation Forecast using MM5 and WRF models for Kelantan River Basin
Authors: Wardah, T., Kamil, A.A., Sahol Hamid, A.B., Maisarah, W.W.I
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Quantitative precipitation forecast (QPF) from atmospheric model as input to hydrological model in an integrated hydro-meteorological flood forecasting system has been operational in many countries worldwide. High-resolution numerical weather prediction (NWP) models with grid cell sizes between 2 and 14 km have great potential in contributing towards reasonably accurate QPF. In this study the potential of two NWP models to forecast precipitation for a flood-prone area in a tropical region is examined. The precipitation forecasts produced from the Fifth Generation Penn State/NCAR Mesoscale (MM5) and Weather Research and Forecasting (WRF) models are statistically verified with the observed rain in Kelantan River Basin, Malaysia. The statistical verification indicates that the models have performed quite satisfactorily for low and moderate rainfall but not very satisfactory for heavy rainfall.Keywords: MM5, Numerical weather prediction (NWP), quantitative precipitation forecast (QPF), WRF
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29341150 Active Control Improvement of Smart Cantilever Beam by Piezoelectric Materials and On-Line Differential Artificial Neural Networks
Authors: P. Karimi, A. H. Khedmati Bazkiaei
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The main goal of this study is to test differential neural network as a controller of smart structure and is to enumerate its advantages and disadvantages in comparison with other controllers. In this study, the smart structure has been considered as a Euler Bernoulli cantilever beam and it has been tried that it be under control with the use of vibration neural network resulting from movement. Also, a linear observer has been considered as a reference controller and has been compared its results. The considered vibration charts and the controlled state have been recounted in the final part of this text. The obtained result show that neural observer has better performance in comparison to the implemented linear observer.Keywords: Smart material, on-line differential artificial neural network, active control, finite element method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8171149 Design Optimization of Doubly Fed Induction Generator Performance by Differential Evolution
Authors: Mamidi Ramakrishna Rao
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Doubly-fed induction generators (DFIG) due to their advantages like speed variation and four-quadrant operation, find its application in wind turbines. DFIG besides supplying power to the grid has to support reactive power (kvar) under grid voltage variations, should contribute minimum fault current during faults, have high efficiency, minimum weight, adequate rotor protection during crow-bar-operation from +20% to -20% of rated speed. To achieve the optimum performance, a good electromagnetic design of DFIG is required. In this paper, a simple and heuristic global optimization – Differential Evolution has been used. Variables considered are lamination details such as slot dimensions, stack diameters, air gap length, and generator stator and rotor stack length. Two operating conditions have been considered - voltage and speed variations. Constraints included were reactive power supplied to the grid and limiting fault current and torque. The optimization has been executed separately for three objective functions - maximum efficiency, weight reduction, and grid fault stator currents. Subsequent calculations led to the conclusion that designs determined through differential evolution help in determining an optimum electrical design for each objective function.
Keywords: Design optimization, performance, doubly fed induction generators, DFIG, differential evolution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9801148 Performance Evaluation of Cooperative Diversity in Flat Fading Channel with Error Control Coding
Authors: Oluseye Adeniyi Adeleke, Mohd Fadzli Salleh
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Cooperative communication provides transmit diversity, even when, due to size constraints, mobile units cannot accommodate multiple antennas. A versatile cooperation method called coded cooperation has been developed, in which cooperation is implemented through channel coding with a view to controlling the errors inherent in wireless communication. In this work we evaluate the performance of coded cooperation in flat Rayleigh fading environment using a concept known as the pair wise error probability (PEP). We derive the PEP for a flat fading scenario in coded cooperation and then compare with the signal-to-noise ratio of the users in the network. Results show that an increase in the SNR leads to a decrease in the PEP. We also carried out simulations to validate the result.
Keywords: Channel state information, coded cooperation, cooperative systems, pairwise-error-probability, Reed-Solomon codes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17731147 Effects of Arcing in Air on the Microstructure, Morphology and Photoelectric Work Function of Ag- Ni (60/40) Contact Materials
Authors: Mohamed Akbi
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The present work aims to throw light on the effects of arcing in air on the surface state of contact pastilles made of silvernickel Ag-Ni (60/40). Also, the photoelectric emission from these electrical contacts has been investigated in the spectral range of 196- 256 nm. In order to study the effects of arcing on the EWF, the metallic samples were subjected to electrical arcs in air, at atmospheric pressure and room temperature, after that, they have been introduced into the vacuum chamber of an experimental UHV set-up for EWF measurements. Both Fowler method of isothermal curves and linearized Fowler plots were used for the measurement of the EWF by the photoelectric effect. It has been found that the EWF varies with the number of applied arcs. Thus, after 500 arcs in air, the observed EWF increasing is probably due to progressive inclusion of oxide on alloy surface. Microscopic examination is necessary to get better understandings on EWF of silver alloys, for both virgin and arced electrical contacts.
Keywords: Ag-Ni contact materials, arcing effects, electron work function, Fowler methods, photoemission.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23781146 Uneven Development: Structural Changes and Income Outcomes across States in Malaysia
Authors: Siti Aiysyah Tumin
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This paper looks at the nature of structural changes—the transition of employment from agriculture, to manufacturing, then to different types of services—in different states in Malaysia and links it to income outcomes for households and workers. Specifically, this paper investigates the conditional association between the concentration of different economic activities and income outcomes (household incomes and employee wages) in almost four decades. Using publicly available state-level employment and income data, we found that significant wage premium was associated with “modern” services (finance, real estate, professional, information and communication), which are urban-based services sectors that employ a larger proportion of skilled and educated workers. However, employment in manufacturing and other services subsectors was significantly associated with a lower income dispersion and inequality, alluding to their importance in welfare improvements.Keywords: Employment, labour market, structural change, wages.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5401145 Traffic Flow Prediction using Adaboost Algorithm with Random Forests as a Weak Learner
Authors: Guy Leshem, Ya'acov Ritov
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Traffic Management and Information Systems, which rely on a system of sensors, aim to describe in real-time traffic in urban areas using a set of parameters and estimating them. Though the state of the art focuses on data analysis, little is done in the sense of prediction. In this paper, we describe a machine learning system for traffic flow management and control for a prediction of traffic flow problem. This new algorithm is obtained by combining Random Forests algorithm into Adaboost algorithm as a weak learner. We show that our algorithm performs relatively well on real data, and enables, according to the Traffic Flow Evaluation model, to estimate and predict whether there is congestion or not at a given time on road intersections.Keywords: Machine Learning, Boosting, Classification, TrafficCongestion, Data Collecting, Magnetic Loop Detectors, SignalizedIntersections, Traffic Signal Timing Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39151144 Digital Transformation as the Subject of the Knowledge Model of the Discursive Space
Authors: Rafal Maciag
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Due to the development of the current civilization, one must create suitable models of its pervasive massive phenomena. Such a phenomenon is the digital transformation, which has a substantial number of disciplined, methodical interpretations forming the diversified reflection. This reflection could be understood pragmatically as the current temporal, a local differential state of knowledge. The model of the discursive space is proposed as a model for the analysis and description of this knowledge. Discursive space is understood as an autonomous multidimensional space where separate discourses traverse specific trajectories of what can be presented in multidimensional parallel coordinate system. Discursive space built on the world of facts preserves the complex character of that world. Digital transformation as a discursive space has a relativistic character that means that at the same time, it is created by the dynamic discourses and these discourses are molded by the shape of this space.
Keywords: Knowledge, digital transformation, discourse, discursive space, complexity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6611143 Operations Research Applications in Audit Planning and Scheduling
Authors: Abdel-Aziz M. Mohamed
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This paper presents a state-of-the-art survey of the operations research models developed for internal audit planning. Two alternative approaches have been followed in the literature for audit planning: (1) identifying the optimal audit frequency; and (2) determining the optimal audit resource allocation. The first approach identifies the elapsed time between two successive audits, which can be presented as the optimal number of audits in a given planning horizon, or the optimal number of transactions after which an audit should be performed. It also includes the optimal audit schedule. The second approach determines the optimal allocation of audit frequency among all auditable units in the firm. In our review, we discuss both the deterministic and probabilistic models developed for audit planning. In addition, game theory models are reviewed to find the optimal auditing strategy based on the interactions between the auditors and the clients.Keywords: Operations research applications, audit frequency, audit planning, audit-staff scheduling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29371142 Influence Maximization in Dynamic Social Networks and Graphs
Authors: Gkolfo I. Smani, Vasileios Megalooikonomou
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Influence and influence diffusion have been studied extensively in social networks. However, most existing literature on this task are limited on static networks, ignoring the fact that the interactions between users change over time. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time is studied. The DM algorithm is an extension of Matrix Influence (MATI) algorithm and solves the Influence Maximization (IM) problem in dynamic networks and is proposed under the Linear Threshold (LT) and Independent Cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.
Keywords: Influence maximization, dynamic social networks, diffusion, social influence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4231141 A Comparison of YOLO Family for Apple Detection and Counting in Orchards
Authors: Yuanqing Li, Changyi Lei, Zhaopeng Xue, Zhuo Zheng, Yanbo Long
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In agricultural production and breeding, implementing automatic picking robot in orchard farming to reduce human labour and error is challenging. The core function of it is automatic identification based on machine vision. This paper focuses on apple detection and counting in orchards and implements several deep learning methods. Extensive datasets are used and a semi-automatic annotation method is proposed. The proposed deep learning models are in state-of-the-art YOLO family. In view of the essence of the models with various backbones, a multi-dimensional comparison in details is made in terms of counting accuracy, mAP and model memory, laying the foundation for realising automatic precision agriculture.
Keywords: Agricultural object detection, Deep learning, machine vision, YOLO family.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11101140 Microencapsulation of Ascorbic Acid by Spray Drying: Influence of Process Conditions
Authors: Addion Nizori, Lan T.T. Bui, Darryl M. Small
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Ascorbic acid (AA), commonly known as vitamin C, is essential for normal functioning of the body and maintenance of metabolic integrity. Among its various roles are as an antioxidant, a cofactor in collagen formation and other reactions, as well as reducing physical stress and maintenance of the immune system. Recent collaborative research between the Australian Defence Science and Technology Organisation (DSTO) in Scottsdale, Tasmania and RMIT University has sought to overcome the problems arising from the inherent instability of ascorbic acid during processing and storage of foods. The recent work has demonstrated the potential of microencapsulation by spray drying as a means to enhance retention. The purpose of this current study has been focused upon the influence of spray drying conditions on the properties of encapsulated ascorbic acid. The process was carried out according to a central composite design. Independent variables were: inlet temperature (80-120° C) and feed flow rate (7-14 mL/minute). Process yield, ascorbic acid loss, moisture content, water activity and particle size distribution were analysed as responses. The results have demonstrated the potential of microencapsulation by spray drying as a means to enhance retention. Vitamin retention, moisture content, water activity and process yield were influenced positively by inlet air temperature and negatively by feed flow rate.
Keywords: Microencapsulation, spray drying, ascorbic acid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 44621139 Examining Occupational Health and Safety Inspection and Supervision in Turkey by Comparison to EU Countries
Authors: Nuray Gökçek Karaca
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This study aims to examine the application of occupational health and safety supervision in Turkey and EU countries in terms of legal regulations. The results of research reveal that occupational health and safety supervision in EU countries, whatever the understanding of welfare state, is effectively carried out and almost all legal regulations on this subject are consistent with the EU directives. On the other hand, there are serious problems in applications, not legal regulations, of occupational health and safety supervision in Turkey by the side of EU countries. Indeed, Turkey has modern regulations on occupational health and safety supervision whereas there are several problems such as ignoring prevention policy on occupational health and safety supervision, understanding of monotype inspector, problems resulting from this understanding and dispersed structure of occupational health and safety organizations in workplaces. As a result, Turkey needs to carry out effective supervision mechanisms.
Keywords: Legal Rules, Occupational Health and Safety, Inspection, Supervision, Legislation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23891138 Multi Task Scheme to Monitor Multivariate Environments Using Artificial Neural Network
Authors: K. Atashgar
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When an assignable cause(s) manifests itself to a multivariate process and the process shifts to an out-of-control condition, a root-cause analysis should be initiated by quality engineers to identify and eliminate the assignable cause(s) affected the process. A root-cause analysis in a multivariate process is more complex compared to a univariate process. In the case of a process involved several correlated variables an effective root-cause analysis can be only experienced when it is possible to identify the required knowledge including the out-of-control condition, the change point, and the variable(s) responsible to the out-of-control condition, all simultaneously. Although literature addresses different schemes to monitor multivariate processes, one can find few scientific reports focused on all the required knowledge. To the best of the author’s knowledge this is the first time that a multi task model based on artificial neural network (ANN) is reported to monitor all the required knowledge at the same time for a multivariate process with more than two correlated quality characteristics. The performance of the proposed scheme is evaluated numerically when different step shifts affect the mean vector. Average run length is used to investigate the performance of the proposed multi task model. The simulated results indicate the multi task scheme performs all the required knowledge effectively.
Keywords: Artificial neural network, Multivariate process, Statistical process control, Change point.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16861137 Impact of Fixation Time on Subjective Video Quality Metric: a New Proposal for Lossy Compression Impairment Assessment
Authors: M. G. Albanesi, R. Amadeo
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In this paper, a new approach for quality assessment tasks in lossy compressed digital video is proposed. The research activity is based on the visual fixation data recorded by an eye tracker. The method involved both a new paradigm for subjective quality evaluation and the subsequent statistical analysis to match subjective scores provided by the observer to the data obtained from the eye tracker experiments. The study brings improvements to the state of the art, as it solves some problems highlighted in literature. The experiments prove that data obtained from an eye tracker can be used to classify videos according to the level of impairment due to compression. The paper presents the methodology, the experimental results and their interpretation. Conclusions suggest that the eye tracker can be useful in quality assessment, if data are collected and analyzed in a proper way.Keywords: eye tracker, video compression, video qualityassessment, visual attention
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16091136 French Managers and Their Subordinates’ Well-Being
Authors: B. Gangloff, N. Malleh
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Well-being at work has many positive aspects. Our general hypothesis is that employees who feel well-being at work will be positively valued by their superiors, and that this positive value, which evokes the concept of social norms, allows us to assign to well-being at work a normative status. Three populations (line managers, students destined to become human resource managers, and employees) responded to a well-being questionnaire. Managers had to indicate, for each item, if they appreciated (or not) an employee feeling the well-being presented in the item; students had to indicate which items an employee should check if s/he wants to be positively (versus negatively) appreciated by his/her superior; and employees had to indicate to what degree each item corresponded to the well-being they used to feel. Three hypotheses are developed and confirmed: Managers positively value employees feeling some sense of well-being; students are aware of this positivity; spontaneously employees show a state of well-being, which means, knowing that spontaneous self-presentation is often produced by social desirability, that employees are aware of the well-being positivity. These data are discussed under a conceptual and applied angle.
Keywords: Normativity, well-being at work, organization, evaluation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11291135 Fuzzy Logic Approach to Robust Regression Models of Uncertain Medical Categories
Authors: Arkady Bolotin
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Dichotomization of the outcome by a single cut-off point is an important part of various medical studies. Usually the relationship between the resulted dichotomized dependent variable and explanatory variables is analyzed with linear regression, probit regression or logistic regression. However, in many real-life situations, a certain cut-off point dividing the outcome into two groups is unknown and can be specified only approximately, i.e. surrounded by some (small) uncertainty. It means that in order to have any practical meaning the regression model must be robust to this uncertainty. In this paper, we show that neither the beta in the linear regression model, nor its significance level is robust to the small variations in the dichotomization cut-off point. As an alternative robust approach to the problem of uncertain medical categories, we propose to use the linear regression model with the fuzzy membership function as a dependent variable. This fuzzy membership function denotes to what degree the value of the underlying (continuous) outcome falls below or above the dichotomization cut-off point. In the paper, we demonstrate that the linear regression model of the fuzzy dependent variable can be insensitive against the uncertainty in the cut-off point location. In the paper we present the modeling results from the real study of low hemoglobin levels in infants. We systematically test the robustness of the binomial regression model and the linear regression model with the fuzzy dependent variable by changing the boundary for the category Anemia and show that the behavior of the latter model persists over a quite wide interval.
Keywords: Categorization, Uncertain medical categories, Binomial regression model, Fuzzy dependent variable, Robustness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15631134 Effect of Indole-3-Acetic Acid on Arsenic Translocation in Agricultural Crops
Authors: Ye. V. Lyubun
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The problem of agricultural-soil pollution is closely linked to the production of ecologically pure foodstuffs and to human health. An important task, therefore, is to rehabilitate agricultural soils with the help of state-of-the-art biotechnologies, based on the use of metal-accumulating plants. In this work, on the basis of literature data and the results of prior research from this laboratory, plants were selected for which the growing technology is well developed and which are widespread locally: sugar sorghum (Sorghum saccharatum), sudangrass (Sorghum sudanense (Piper.) Stapf.), and sunflower (Helianthus annuus L.). I report on laboratory experiments designed to study the influence of synthetic indole-3- acetic acid and the extracellular indole-3-acetic acid released by the plant-growth-promoting rhizobacterium Azospirillum brasilense Sp245 on growth of and arsenic accumulation by these plants.Keywords: Arsenic, bioaccumulation, plant-growth-promoting rhizobacteria, phytohormones.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17151133 The Virtual Container Yard: Identifying the Persuasive Factors in Container Interchange
Authors: L. Edirisinghe, Zhihong Jin, A. W. Wijeratne, R. Mudunkotuwa
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The virtual container yard is an effective solution to the container inventory imbalance problem which is a global issue. It causes substantial cost to carriers, which inadvertently adds to the prices of consumer goods. The virtual container yard is rooted in the fundamentals of container interchange between carriers. If carriers opt to interchange their excess containers with those who are deficit, a substantial part of the empty reposition cost could be eliminated. Unlike in other types of ships, cargo cannot be directly loaded to a container ship. Slots and containers are supplementary components; thus, without containers, a carrier cannot ship cargo if the containers are not available and vice versa. Few decades ago, carriers recognized slot (the unit of space in a container ship) interchange as a viable solution for the imbalance of shipping space. Carriers interchange slots among them and it also increases the advantage of scale of economies in container shipping. Some of these service agreements between mega carriers have provisions to interchange containers too. However, the interchange mechanism is still not popular among carriers for containers. This is the paradox that prevails in the liner shipping industry. At present, carriers reposition their excess empty containers to areas where they are in demand. This research applied factor analysis statistical method. The paper reveals that five major components may influence the virtual container yard namely organisation, practice and culture, legal and environment, international nature, and marketing. There are 12 variables that may impact the virtual container yard, and these are explained in the paper.
Keywords: Virtual container yard, imbalance, management, inventory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8441132 Lightweight High-Pressure Ratio Centrifugal Compressor for Vehicles-Investigation of Pipe Diffuser Designs by Means of CFD
Authors: Eleni Ioannou, Pascal Nucara, Keith Pullen
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The subject of this paper is the investigation of the best efficiency design of a compressor diffuser applied in new lightweight, ultra efficient micro-gas turbine engines for vehicles. The Computational Fluid Dynamics (CFD) results are obtained utilizing steady state simulations for a wedge and an ”oval” type pipe diffuser in an effort to identify the beneficial effects of the pipe diffuser design. The basic flow features are presented with particular focus on the optimization of the pipe diffuser leading to higher efficiencies for the compressor stage. The optimised pipe diffuser is designed to exploit the 3D freedom enabled by Selective Laser Melting, hence purposely involves an investigation of geometric characteristics that do not follow the traditional diffuser concept.Keywords: CFD, centrifugal compressor, micro-gas turbine, pipe diffuser, SLM, wedge diffuser.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19291131 Iron Doped Biomaterial Calcium Borate: Synthesis and Characterization
Authors: G. Çelik Gül, F. Kurtuluş
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Colemanite is the most common borate mineral, and the main source of the boron required by plants, human, and earth. Transition metals exhibit optical and physical properties such as; non-linear optical character, structural diversity, thermal stability, long cycle life and luminescent radiation. The doping of colemanite with a transition metal, bring it very interesting and attractive properties which make them applicable in industry. Iron doped calcium borate was synthesized by conventional solid state method at 1200 °C for 12 h with a systematic pathway. X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy/energy dispersive analyze (SEM/EDS) were used to characterize structural and morphological properties. Also, thermal properties were recorded by thermogravimetric-differential thermal analysis (TG/DTA).
Keywords: Colemanite, conventional synthesis, powder x-ray diffraction, borates.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10101130 Comparative Safety Performance Evaluation of Profiled Deck Composite Slab from the Use of Slope-Intercept and Partial Shear Methods
Authors: Izian Abd. Karim, Kachalla Mohammed, Nora Farah A. A. Aziz, Law Teik Hua
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The economic use and ease of construction of profiled deck composite slab is marred with the complex and un-economic strength verification required for the serviceability and general safety considerations. Beside these, albeit factors such as shear span length, deck geometries and mechanical frictions greatly influence the longitudinal shear strength, that determines the ultimate strength of profiled deck composite slab, and number of methods available for its determination; partial shear and slope-intercept are the two methods according to Euro-code 4 provision. However, the complexity associated with shear behavior of profiled deck composite slab, the use of these methods in determining the load carrying capacities of such slab yields different and conflicting values. This couple with the time and cost constraint associated with the strength verification is a source of concern that draws more attentions nowadays, the issue is critical. Treating some of these known shear strength influencing factors as random variables, the load carrying capacity violation of profiled deck composite slab from the use of the two-methods defined according to Euro-code 4 are determined using reliability approach, and comparatively studied. The study reveals safety values from the use of m-k method shows good standing compared with that from the partial shear method.Keywords: Composite slab, first order reliability method, longitudinal shear, partial shear connection, slope-intercept.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19121129 Sustainability of Healthcare Insurance in India: A Review of Health Insurance Scheme Launched by States in India
Authors: Mohd Zuhair, Ram Babu Roy
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This paper presents an overview of the accessibility, design, and functioning of health insurance plans launched by state governments in India. In recent years, the governments of several states in India have come forward to provide health insurance coverage for the low-income group and rural population to reduce the out of pocket expenditure (OPE) on healthcare. Different health insurance schemes have different structures and offerings which differ in the different demographic factors. This study will portray a comparative analysis of the various health insurance schemes by analyzing different offerings and finance generation of the schemes. The comparative analysis will explain the lesson to be learned from these schemes and extend the existing knowledge of the health insurance in India. This would help in recognizing tension between various drivers and identifying issues pertaining to the sustainability of health insurance schemes in India.
Keywords: Health insurance, out of pocket expenditure, universal healthcare, sustainability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11641128 On the Interactive Search with Web Documents
Authors: Mario Kubek, Herwig Unger
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Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-ofthe- art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents.
Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16511127 Design of Bayesian MDS Sampling Plan Based on the Process Capability Index
Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi
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In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.
Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index, average sample number, Bayesian approach.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10131126 Deep-Learning Based Approach to Facial Emotion Recognition Through Convolutional Neural Network
Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah
Abstract:
Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. However, accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER benefiting from deep learning, especially CNN and VGG16. First, the data are pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.
Keywords: CNN, deep-learning, facial emotion recognition, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 719