Search results for: web-based group decision support system.
8937 Calibration Method for an Augmented Reality System
Authors: S. Malek, N. Zenati-Henda, M. Belhocine, S. Benbelkacem
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In geometrical camera calibration, the objective is to determine a set of camera parameters that describe the mapping between 3D references coordinates and 2D image coordinates. In this paper, a technique of calibration and tracking based on both a least squares method is presented and a correlation technique developed as part of an augmented reality system. This approach is fast and it can be used for a real time systemKeywords: Camera calibration, pinhole model, least squares method, augmented reality, strong calibration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20018936 Hybrid Power – Application for Tourism in Isolated Areas
Authors: Aurelian Octavian Ciucâ, Ioan Bitir-Istrate, Mircea Scripcariu
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The rapidly increasing costs of power line extensions and fossil fuel, combined with the desire to reduce carbon dioxide emissions pushed the development of hybrid power system suited for remote locations, the purpose in mind being that of autonomous local power systems. The paper presents the suggested solution for a “high penetration" hybrid power system, it being determined by the location of the settlement and its “zero policy" on carbon dioxide emissions. The paper focuses on the technical solution and the power flow management algorithm of the system, taking into consideration local conditions of development.Keywords: Renewable energy, hybrid power system, wind turbine, photovoltaic panels, bio-diesel cogeneration, bio-fuel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16208935 Modeling of Reinforcement in Concrete Beams Using Machine Learning Tools
Authors: Yogesh Aggarwal
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The paper discusses the results obtained to predict reinforcement in singly reinforced beam using Neural Net (NN), Support Vector Machines (SVM-s) and Tree Based Models. Major advantage of SVM-s over NN is of minimizing a bound on the generalization error of model rather than minimizing a bound on mean square error over the data set as done in NN. Tree Based approach divides the problem into a small number of sub problems to reach at a conclusion. Number of data was created for different parameters of beam to calculate the reinforcement using limit state method for creation of models and validation. The results from this study suggest a remarkably good performance of tree based and SVM-s models. Further, this study found that these two techniques work well and even better than Neural Network methods. A comparison of predicted values with actual values suggests a very good correlation coefficient with all four techniques.Keywords: Linear Regression, M5 Model Tree, Neural Network, Support Vector Machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20358934 Impact of Some Experimental Procedures on Behavioral Patterns and Physiological Traits of Rats
Authors: Amira, A. Goma, U. E. Mahrous
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Welfare may be considered to be a subjective experience; it has a biological function that is related to the fitness and survival of the animal accordingly, researches have suggested that welfare is compromised when the animal's evolutionary fitness is reduced. This study was carried out to explain the effect of some managerial stressors as handling and restraint on behavioral patterns and biochemical parameters of rats. A total of 24 (12 males & 12 females) Sprague-Dawley rats (12 months & 150-180g) were allotted into 3 groups, handled group (4 male & 4 female), restrained group (4 male & 4 female) and control group (4 males & 4 females). The obtained results revealed that time spent feeding, drinking, movement and cage exploration frequencies increased significantly in handled rats than other groups, while lying time and licking increased significantly in restrained rats than handled and controls. Moreover, social behavior decreased in both stressed groups than control. Triglycerides were significantly increased in handled rats than other groups, while total lipid, total protein and globulin significantly increased in both treated groups than control. Corticosterone increased in restrained and handled rats than control ones. Moreover, there was an increment in packed cell volume significantly in restrained rats than others. These deducted that if we want to study the effect of stress on animal welfare it is necessary to study the effect of such stressors on animal’s behavior and physiological responses.
Keywords: Behavior, handling, restraint, rat, welfare.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22618933 Assessment of Irrigation Practices at Main Irrigation Network in the Nile Delta
Authors: Ahmed Mohsen, Yoshinobu Kitamura, Katsuyuki Shimizu
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The improvement of irrigation systems in the Nile Delta is one of the most important attempts in Egypt to implement more effective irrigation technology by improving the existing irrigation networks. Demand delivery system in the existing irrigation network is using of mechanical gates structures to automatically divert water from one portion of an agricultural field to another in the desired amount and sequence. This paper discusses evaluating main irrigation networks system under the government managed before and after improvement systems in the Nile Delta. The overall results indicate that policy of using the demand delivery concept through irrigation networks is successful by improving water delivery performance among them than the rotation delivery concept that used before. It is provided fair share of water delivery among irrigation districts and available water in the end of irrigation network, although this system located in an end of irrigation networks in the Nile Delta.Keywords: Automation system, Irrigation district, Rotation system, Water delivery performance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24048932 Hybrid Approach for Software Defect Prediction Using Machine Learning with Optimization Technique
Authors: C. Manjula, Lilly Florence
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Software technology is developing rapidly which leads to the growth of various industries. Now-a-days, software-based applications have been adopted widely for business purposes. For any software industry, development of reliable software is becoming a challenging task because a faulty software module may be harmful for the growth of industry and business. Hence there is a need to develop techniques which can be used for early prediction of software defects. Due to complexities in manual prediction, automated software defect prediction techniques have been introduced. These techniques are based on the pattern learning from the previous software versions and finding the defects in the current version. These techniques have attracted researchers due to their significant impact on industrial growth by identifying the bugs in software. Based on this, several researches have been carried out but achieving desirable defect prediction performance is still a challenging task. To address this issue, here we present a machine learning based hybrid technique for software defect prediction. First of all, Genetic Algorithm (GA) is presented where an improved fitness function is used for better optimization of features in data sets. Later, these features are processed through Decision Tree (DT) classification model. Finally, an experimental study is presented where results from the proposed GA-DT based hybrid approach is compared with those from the DT classification technique. The results show that the proposed hybrid approach achieves better classification accuracy.
Keywords: Decision tree, genetic algorithm, machine learning, software defect prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14658931 Cascaded Neural Network for Internal Temperature Forecasting in Induction Motor
Authors: Hidir S. Nogay
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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.Keywords: Cascaded neural network, internal temperature, three-phase induction motor, inverter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8738930 Improving Production Capacity through Efficient PPC System: Lesson from Leather Manufacturing
Authors: Mengist Hailemariam, Silma Yoseph
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A well designed and executed Production Planning and Control (PPC) system is one of the key levers for superior performance in the current manufacturing set-up. Hence, measuring the PPC system performance has become a necessity for long term success. The present study examined PPC related issues which impact the production capacity and productivity of leather companies with special focus on Kombolcha Tannery Share Company (KTSC), Ethiopia. Physical observation, interview, and questionnaire were used to generate necessary information from the respondents and reach valid conclusions. Company annual reports were referred and analyzed to triangulate primary data. Consequently, the study revealed that KTSC runs below its capacity due to its inefficient PPC system being in use for which the root causes were identified. The study thereby conceptualizes a PPC system improvement framework comprising three pillars viz., management culture, internal capability and performance measurement together with key considerations in each case. The study findings enable the company to recognize the importance of efficient PPC system as a source of competitive advantage. It also aid managers in evaluating various PPC execution schemes to enhance productivity.
Keywords: Ethiopia, Leather manufacturing, Production planning and control, PPC improvement framework.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37348929 Using Thinking Blocks to Encourage the Use of Higher Order Thinking Skills among Students When Solving Problems on Fractions
Authors: Abdul Halim Abdullah, Nur Liyana Zainal Abidin, Mahani Mokhtar
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Problem-solving is an activity which can encourage students to use Higher Order Thinking Skills (HOTS). Learning fractions can be challenging for students since empirical evidence shows that students experience difficulties in solving the fraction problems. However, visual methods can help students to overcome the difficulties since the methods help students to make meaningful visual representations and link abstract concepts in Mathematics. Therefore, the purpose of this study was to investigate whether there were any changes in students’ HOTS at the four highest levels when learning the fractions by using Thinking Blocks. 54 students participated in a quasi-experiment using pre-tests and post-tests. Students were divided into two groups. The experimental group (n=32) received a treatment to improve the students’ HOTS and the other group acted as the control group (n=22) which used a traditional method. Data were analysed by using Mann-Whitney test. The results indicated that during post-test, students who used Thinking Blocks showed significant improvement in their HOTS level (p=0.000). In addition, the results of post-test also showed that the students’ performance improved significantly at the four highest levels of HOTS; namely, application (p=0.001), analyse (p=0.000), evaluate (p=0.000), and create (p=0.000). Therefore, it can be concluded that Thinking Blocks can effectively encourage students to use the four highest levels of HOTS which consequently enable them to solve fractions problems successfully.Keywords: Thinking blocks, higher order thinking skills, fractions, problem solving.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13578928 Formation and Development of a New System of Government of the Republic of Kazakhstan in the Globalization
Authors: Kadyrzhan Smagulov, Beken Makhmutov, Abai Kurmankulov
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The concept of the new government should focus on forming a new relationship between public servants and citizens of the state, formed on the principles of transparency, accountability, protection of citizens' rights. These principles are laid down in the problem of administrative reform in the Republic of Kazakhstan. Also, this wish arises, contributing to the improvement of the system of political management in our country. For the full realization of the goals is necessary to develop a special state program designed to improve the regulatory framework for public service, improving training, retraining and advanced training of civil servants, forming a system of incentives in public service and other activities aimed at achieving the efficiency of the entire system government.Keywords: Kazakhstan, political management, independence
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14618927 Computing Entropy for Ortholog Detection
Authors: Hsing-Kuo Pao, John Case
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Biological sequences from different species are called or-thologs if they evolved from a sequence of a common ancestor species and they have the same biological function. Approximations of Kolmogorov complexity or entropy of biological sequences are already well known to be useful in extracting similarity information between such sequences -in the interest, for example, of ortholog detection. As is well known, the exact Kolmogorov complexity is not algorithmically computable. In prac-tice one can approximate it by computable compression methods. How-ever, such compression methods do not provide a good approximation to Kolmogorov complexity for short sequences. Herein is suggested a new ap-proach to overcome the problem that compression approximations may notwork well on short sequences. This approach is inspired by new, conditional computations of Kolmogorov entropy. A main contribution of the empir-ical work described shows the new set of entropy-based machine learning attributes provides good separation between positive (ortholog) and nega-tive (non-ortholog) data - better than with good, previously known alter-natives (which do not employ some means to handle short sequences well).Also empirically compared are the new entropy based attribute set and a number of other, more standard similarity attributes sets commonly used in genomic analysis. The various similarity attributes are evaluated by cross validation, through boosted decision tree induction C5.0, and by Receiver Operating Characteristic (ROC) analysis. The results point to the conclu-sion: the new, entropy based attribute set by itself is not the one giving the best prediction; however, it is the best attribute set for use in improving the other, standard attribute sets when conjoined with them.
Keywords: compression, decision tree, entropy, ortholog, ROC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18278926 Fuzzy Control of the Air Conditioning System at Different Operating Pressures
Authors: Mohanad Alata , Moh'd Al-Nimr, Rami Al-Jarrah
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The present work demonstrates the design and simulation of a fuzzy control of an air conditioning system at different pressures. The first order Sugeno fuzzy inference system is utilized to model the system and create the controller. In addition, an estimation of the heat transfer rate and water mass flow rate injection into or withdraw from the air conditioning system is determined by the fuzzy IF-THEN rules. The approach starts by generating the input/output data. Then, the subtractive clustering algorithm along with least square estimation (LSE) generates the fuzzy rules that describe the relationship between input/output data. The fuzzy rules are tuned by Adaptive Neuro-Fuzzy Inference System (ANFIS). The results show that when the pressure increases the amount of water flow rate and heat transfer rate decrease within the lower ranges of inlet dry bulb temperatures. On the other hand, and as pressure increases the amount of water flow rate and heat transfer rate increases within the higher ranges of inlet dry bulb temperatures. The inflection in the pressure effect trend occurs at lower temperatures as the inlet air humidity increases.
Keywords: Air Conditioning, ANFIS, Fuzzy Control, Sugeno System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33678925 Feasibility Study of a Solar Farm Project with an Executive Approach
Authors: Amir Reza Talaghat
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Since 2015, a new approach and policy regarding energy resources protection and using renewable energies has been started in Iran which was developing new projects. Investigating about the feasibility study of these new projects helped to figure out five steps to prepare an executive feasibility study of the concerned projects, which are proper site selections, authorizations, design and simulation, economic study and programming, respectively. The results were interesting and essential for decision makers and investors to start implementing of these projects in reliable condition. The research is obtained through collection and study of the project's documents as well as recalculation to review conformity of the results with GIS data and the technical information of the bidders. In this paper, it is attempted to describe the result of the performed research by describing the five steps as an executive methodology, for preparing a feasible study of installing a 10 MW – solar farm project. The corresponding results of the research also help decision makers to start similar projects is explained in this paper as follows: selecting the best location for the concerned PV plant, reliable and safe conditions for investment and the required authorizations to start implementing the solar farm project in the concerned region, selecting suitable component to achieve the best possible performance for the plant, economic profit of the investment, proper programming to implement the project on time.
Keywords: Solar farm, solar energy, execution of PV power plant, PV power plant, feasibility study.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17428924 Studies on the Applicability of Artificial Neural Network (ANN) in Prediction of Thermodynamic Behavior of Sodium Chloride Aqueous System Containing a Non-Electrolytes
Authors: Dariush Jafari, S. Mostafa Nowee
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In this study a ternary system containing sodium chloride as solute, water as primary solvent and ethanol as the antisolvent was considered to investigate the application of artificial neural network (ANN) in prediction of sodium solubility in the mixture of water as the solvent and ethanol as the antisolvent. The system was previously studied using by Extended UNIQUAC model by the authors of this study. The comparison between the results of the two models shows an excellent agreement between them (R2=0.99), and also approves the capability of ANN to predict the thermodynamic behavior of ternary electrolyte systems which are difficult to model.
Keywords: Thermodynamic modeling, ANN, solubility, ternary electrolyte system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21548923 Technical and Economic Analysis of Smart Micro-Grid Renewable Energy Systems: An Applicable Case Study
Authors: M. A. Fouad, M. A. Badr, Z. S. Abd El-Rehim, Taher Halawa, Mahmoud Bayoumi, M. M. Ibrahim
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Renewable energy-based micro-grids are presently attracting significant consideration. The smart grid system is presently considered a reliable solution for the expected deficiency in the power required from future power systems. The purpose of this study is to determine the optimal components sizes of a micro-grid, investigating technical and economic performance with the environmental impacts. The micro grid load is divided into two small factories with electricity, both on-grid and off-grid modes are considered. The micro-grid includes photovoltaic cells, back-up diesel generator wind turbines, and battery bank. The estimated load pattern is 76 kW peak. The system is modeled and simulated by MATLAB/Simulink tool to identify the technical issues based on renewable power generation units. To evaluate system economy, two criteria are used: the net present cost and the cost of generated electricity. The most feasible system components for the selected application are obtained, based on required parameters, using HOMER simulation package. The results showed that a Wind/Photovoltaic (W/PV) on-grid system is more economical than a Wind/Photovoltaic/Diesel/Battery (W/PV/D/B) off-grid system as the cost of generated electricity (COE) is 0.266 $/kWh and 0.316 $/kWh, respectively. Considering the cost of carbon dioxide emissions, the off-grid will be competitive to the on-grid system as COE is found to be (0.256 $/kWh, 0.266 $/kWh), for on and off grid systems.
Keywords: Optimum energy systems, renewable energy sources, smart grid, micro-grid system, on- grid system, off-grid system, modeling and simulation, economical evaluation, net present value, cost of energy, environmental impacts.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24258922 Identification of Nonlinear Systems Structured by Hammerstein-Wiener Model
Authors: A. Brouri, F. Giri, A. Mkhida, F. Z. Chaoui, A. Elkarkri, M. L. Chhibat
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Standard Hammerstein-Wiener models consist of a linear subsystem sandwiched by two memoryless nonlinearities. The problem of identifying Hammerstein-Wiener systems is addressed in the presence of linear subsystem of structure totally unknown and polynomial input and output nonlinearities. Presently, the system nonlinearities are allowed to be noninvertible. The system identification problem is dealt by developing a two-stage frequency identification method. First, the parameters of system nonlinearities are identified. In the second stage, a frequency approach is designed to estimate the linear subsystem frequency gain. All involved estimators are proved to be consistent.
Keywords: Nonlinear system identification, Hammerstein systems, Wiener systems, frequency identification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24008921 Using Focus Group Method to Identify Citizen Requirements to Saudi Mobile Government Services
Authors: S. Alotaibi, D. Roussinov
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Mobile government services implementation faces several challenges in developing countries. This paper studies some of those challenges in the context of Saudi Arabia. The study aims to investigate factors affecting m-government acceptance in Saudi Arabia, including ease of use, usefulness, service quality, trust, intention to use and users’ satisfaction. Our investigation will help in integrating the m-government services in citizens’ everyday life. We collected and analyzed our data from focus groups. These focus groups are from King Saud University and Imam Muhammed Bin Saud University, so the samples size are five and seven participants, respectively. We found that there are some factors to identifying citizen requirements to Saudi mobile government services. These services should be easy to use and not require too much effort. Also, these services must be fully trusted.Keywords: E-government, M-government, focus group, Saudi mobile government services.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9858920 A Web and Cloud-Based Measurement System Analysis Tool for the Automotive Industry
Authors: C. A. Barros, Ana P. Barroso
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Any industrial company needs to determine the amount of variation that exists within its measurement process and guarantee the reliability of their data, studying the performance of their measurement system, in terms of linearity, bias, repeatability and reproducibility and stability. This issue is critical for automotive industry suppliers, who are required to be certified by the 16949:2016 standard (replaces the ISO/TS 16949) of International Automotive Task Force, defining the requirements of a quality management system for companies in the automotive industry. Measurement System Analysis (MSA) is one of the mandatory tools. Frequently, the measurement system in companies is not connected to the equipment and do not incorporate the methods proposed by the Automotive Industry Action Group (AIAG). To address these constraints, an R&D project is in progress, whose objective is to develop a web and cloud-based MSA tool. This MSA tool incorporates Industry 4.0 concepts, such as, Internet of Things (IoT) protocols to assure the connection with the measuring equipment, cloud computing, artificial intelligence, statistical tools, and advanced mathematical algorithms. This paper presents the preliminary findings of the project. The web and cloud-based MSA tool is innovative because it implements all statistical tests proposed in the MSA-4 reference manual from AIAG as well as other emerging methods and techniques. As it is integrated with the measuring devices, it reduces the manual input of data and therefore the errors. The tool ensures traceability of all performed tests and can be used in quality laboratories and in the production lines. Besides, it monitors MSAs over time, allowing both the analysis of deviations from the variation of the measurements performed and the management of measurement equipment and calibrations. To develop the MSA tool a ten-step approach was implemented. Firstly, it was performed a benchmarking analysis of the current competitors and commercial solutions linked to MSA, concerning Industry 4.0 paradigm. Next, an analysis of the size of the target market for the MSA tool was done. Afterwards, data flow and traceability requirements were analysed in order to implement an IoT data network that interconnects with the equipment, preferably via wireless. The MSA web solution was designed under UI/UX principles and an API in python language was developed to perform the algorithms and the statistical analysis. Continuous validation of the tool by companies is being performed to assure real time management of the ‘big data’. The main results of this R&D project are: MSA Tool, web and cloud-based; Python API; New Algorithms to the market; and Style Guide of UI/UX of the tool. The MSA tool proposed adds value to the state of the art as it ensures an effective response to the new challenges of measurement systems, which are increasingly critical in production processes. Although the automotive industry has triggered the development of this innovative MSA tool, other industries would also benefit from it. Currently, companies from molds and plastics, chemical and food industry are already validating it.
Keywords: Automotive industry, Industry 4.0, internet of things, IATF 16949:2016, measurement system analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9958919 Wood Species Recognition System
Authors: Bremananth R, Nithya B, Saipriya R
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The proposed system identifies the species of the wood using the textural features present in its barks. Each species of a wood has its own unique patterns in its bark, which enabled the proposed system to identify it accurately. Automatic wood recognition system has not yet been well established mainly due to lack of research in this area and the difficulty in obtaining the wood database. In our work, a wood recognition system has been designed based on pre-processing techniques, feature extraction and by correlating the features of those wood species for their classification. Texture classification is a problem that has been studied and tested using different methods due to its valuable usage in various pattern recognition problems, such as wood recognition, rock classification. The most popular technique used for the textural classification is Gray-level Co-occurrence Matrices (GLCM). The features from the enhanced images are thus extracted using the GLCM is correlated, which determines the classification between the various wood species. The result thus obtained shows a high rate of recognition accuracy proving that the techniques used in suitable to be implemented for commercial purposes.Keywords: Correlation, Grey Level Co-Occurrence Matrix, ProbabilityDensity Function, Wood Recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24628918 A PI Controller for Enhancing the Transient Stability of Multi Pulse Inverter Based Static Synchronous Series Compensator (SSSC) With Superconducting Magnetic Energy Storage(SMES)
Authors: S. Padma, Dr. R. Lakshmipathi, K. Ramash Kumar, P. Nandagopal
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The power system network is becoming more complex nowadays and it is very difficult to maintain the stability of the system. Today-s enhancement of technology makes it possible to include new energy storage devices in the electric power system. In addition, with the aid of power electronic devices, it is possible to independently exchange active and reactive power flow with the utility grid. The main purpose of this paper proposes a Proportional – Integral (PI) control based 48 – pulse Inverter based Static Synchronous Series Compensator (SSSC) with and without Superconducting Magnetic Energy Storage (SMES) used for enhancing the transient stability and regulating power flow in automatic mode. Using a test power system through the dynamic simulation in Matlab/Simulink platform validates the performance of the proposed SSSC with and without SMES system.Keywords: Flexible AC transmission system (FACTS), PIControl, Superconducting Magnetic Energy Storage (SMES), Static Synchronous Series Compensator (SSSC).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23548917 An Experimental Multi-Agent Robot System for Operating in Hazardous Environments
Authors: Y. J. Huang, J. D. Yu, B. W. Hong, C. H. Tai, T. C. Kuo
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In this paper, a multi-agent robot system is presented. The system consists of four robots. The developed robots are able to automatically enter and patrol a harmful environment, such as the building infected with virus or the factory with leaking hazardous gas. Further, every robot is able to perform obstacle avoidance and search for the victims. Several operation modes are designed: remote control, obstacle avoidance, automatic searching, and so on.
Keywords: autonomous robot, field programmable gate array, obstacle avoidance, ultrasonic sensor, wireless communication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17788916 Optimizing the Components of Grid-Independent Microgrids for Rural Electrification Utilizing Solar Panel and Supercapacitor
Authors: Astiaj Khoramshahi, Hossein Ahmadi Danesh Ashtiani, Ahmad Khoshgard, Hamidreza Damghani, Leila Damghani
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Rural electrification rates are generally low in Iran and many parts of the world that lack sustainable renewable energy resources. Many homes are based on polluting solutions such as crude oil and diesel generators for lighting, heating, and charging electrical gadgets. Small-scale portable solar battery packs are accessible to the public; however, they have low capacity and are challenging to be distributed in developing countries. To design a battery-based microgrid power systems, the load profile is one of the key parameters. Additionally, the reliability of the system should be taken into account. A conventional microgrid system can be either AC or coupling DC. Both AC and DC microgrids have advantages and disadvantages depending on their application and can be either connected to the main grid or perform independently. This article proposes a tool for optimal sizing of microgrid-independent systems via respective analysis. To show such an analysis, the type of power generation, number of panels, battery capacity, microgrid size, and group of available consumers should be considered. Therefore, the optimization of different design scenarios is based on number of solar panels and super saving sources, ranges of the depth of discharges, to calculate size and estimate the overall cost. Generally, it is observed that there is an inverse relationship between the depth spectrum of discharge and the solar microgrid costs.
Keywords: Storage, super-storage, grid-independent, economic factors, microgrid.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3178915 Improvement of Ride Comfort of Turning Electric Vehicle Using Optimal Speed Control
Authors: Yingyi Zhou, Tohru Kawabe
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With the spread of EVs (electric Vehicles), the ride comfort has been gaining a lot of attention. The influence of the lateral acceleration is important for the improvement of ride comfort of EVs as well as the longitudinal acceleration, especially upon turning of the vehicle. Therefore, this paper proposes a practical optimal speed control method to greatly improve the ride comfort in the vehicle turning situation. For consturcting this method, effective criteria that can appropriately evaluate deterioration of ride comfort is derived. The method can reduce the influence of both the longitudinal and the lateral speed changes for providing a confortable ride. From several simulation results, we can see the fact that the method can prevent aggravation of the ride comfort by suppressing the influence of longitudinal speed change in the turning situation. Hence, the effectiveness of the method is recognized.Keywords: Electric vehicle, speed control, ride comfort, optimal control theory, driving support system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9168914 The Role of Human Resource System on Crisis Resolve
Authors: Abbas Haddadzadeh, Marzieh Sharif Paghaleh
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Within the new world order, the term “crisis" is nowadays familiar to companies. Organizations are experiencing conditions which are surprising, uncertain, often adverse and usually unstable. The companies, who grasp the importance of transformation within the information age, have felt the need to develop modern methods to achieve the ability to thrive despite severe shocks. Through strategically managing human resource and developing appropriate elements of human resource system, companies can be assured for resolving the crisis. In this paper the role of HR system on resolving crisis has been evaluated. To help accomplish this, an insight on previous strategic HRM literature and an introduction to the elements and relationship within HR systems has been presented. It also reviews different attitude around resilience in literature. It continues by reviewing three elements central to developing an organization-s capacity for crisis resolving and it will demonstrate how designing proper elements of HR system can lead the organizations to possess the ability for passing through crisis. Finally it will evaluate an Iranian Insurance organization in case of one of the three central elements (specific cognitive ability) and observe how successful they were on developing an effective HR system to be ready for facing crisis.
Keywords: Crisis, HR System, Resilience, Strategic Human Resource Management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18608913 Persistence of Termination for Non-Overlapping Term Rewriting Systems
Authors: Munehiro Iwami
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A property is called persistent if for any many-sorted term rewriting system , has the property if and only if term rewriting system , which results from by omitting its sort information, has the property. In this paper,we show that termination is persistent for non-overlapping term rewriting systems and we give the example as application of this result. Furthermore we obtain that completeness is persistent for non-overlapping term rewriting systems.Keywords: Theory of computing, Model-based reasoning, termrewriting system, termination
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13918912 The Efficacy of Andrographis paniculata and Chromolaena odorata Plant Extract against Malaria Parasite
Authors: Funmilola O. Omoya, Abdul O. Momoh
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Malaria constitutes one of the major health problems in Nigeria. One of the reasons attributed for the upsurge was the development of resistance of Plasmodium falciparum and the emergence of multi-resistant strains of the parasite to anti-malaria drugs. A continued search for other effective, safe and cheap plantbased anti-malaria agents thus becomes imperative in the face of these difficulties. The objective of this study is therefore to evaluate the in vivo anti-malarial efficacy of ethanolic extracts of Chromolaena odorata and Androgaphis paniculata leaves. The two plants were evaluated for their anti-malaria efficacy in vivo in a 4-day curative test assay against Plasmodium berghei strain in mice. The group treated with 500mg/ml dose of ethanolic extract of A. paniculata plant showed parasite suppression with increase in Packed Cell Volume (PCV) value except day 3 which showed a slight decrease in PCV value. During the 4-day curative test, an increase in the PCV values, weight measurement and zero count of Plasmodium berghei parasite values was recorded after day 3 of drug administration. These results obtained in group treated with A. paniculata extract showed anti-malarial efficacy with higher mortality rate in parasitaemia count when compared with Chromolaena odorata group. These results justify the use of ethanolic extracts of A. paniculata plant as medicinal herb used in folklore medicine in the treatment of malaria.
Keywords: Anti-malaria, Curative, Plant-based anti-malaria agents.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20698911 The Effect of Pilates Method in Scholar’s Trunk Strength and Hamstring Flexibility: Gender Differences
Authors: Noelia González-Gálvez, María Carrasco Poyatos, Pablo Jorge Marcos Pardo, Yuri Feito
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Musculoskeletal injuries in school children could be reduced improving trunk strength and hamstring flexibility. Low levels of trunk muscle strength and hamstring flexibility may result in acute and musculoskeletal chronic diseases. The Pilates Method can be appropriate to improve these physical condition attributes and has been rarely employed by this social group. On the other hand, it has been shown that trunk strength and flexibility are different between genders, but there is no evidence about the effect of exercise programs designed to improve both items in school children. Therefore the objective of this study was to measure the effect of a six-week Pilates-based exercise program in 14 year old school children trunk strength and hamstring flexibility, establishing differences in gender. The sample was composed of 57 students divided into experimental group (EG; n=30) and control group (CG; n=27). Bench Trunk Curl test (BTC), Sörensen test and Toe-touch test (TT) were used to measure dynamic muscular resistance in trunk flexion, isometric strength in trunk extension and hamstring flexibility, respectively. EG utilized the Pilates exercise program during six-weeks (2 days/week, 55minutes/session). After this period of training, EG improved trunk strength and hamstring flexibility significantly but there were no significant differences within CG. Although boys were better in BTC test and girls were better in TT test, there were no significant differences between them.
Keywords: Teens, school, trunk muscular resistance, intervention, physical performance, abdominal, back.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25258910 Creative Technology as Open Ended Learning Tool: A Case Study of Design School in Malaysia
Authors: Sri Kusumawati Md Daud, Fauzan Mustaffa, Hanafizan Hussain, Md Najib Osman
Abstract:
Does open ended creative technology give positive impact in learning design? Although there are many researchers had examined on the impact of technology on design education but there are very few conclusive researches done on the impact of open ended used of software to learning design. This paper sought to investigate a group of student-s experience on relatively wider range of software application within the context of design project. A typography design project was used to create a learning environment with the aim of inculcate design skills into the learners and increase their creative problem-solving and critical thinking skills. The methods used in this study were questionnaire survey and personal observation which will be focus on the individual and group response during the completion of the task.
Keywords: Learning Tool, Creative Technology, Software, Software Skills, Typography Design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16148909 A New Approach to Polynomial Neural Networks based on Genetic Algorithm
Authors: S. Farzi
Abstract:
Recently, a lot of attention has been devoted to advanced techniques of system modeling. PNN(polynomial neural network) is a GMDH-type algorithm (Group Method of Data Handling) which is one of the useful method for modeling nonlinear systems but PNN performance depends strongly on the number of input variables and the order of polynomial which are determined by trial and error. In this paper, we introduce GPNN (genetic polynomial neural network) to improve the performance of PNN. GPNN determines the number of input variables and the order of all neurons with GA (genetic algorithm). We use GA to search between all possible values for the number of input variables and the order of polynomial. GPNN performance is obtained by two nonlinear systems. the quadratic equation and the time series Dow Jones stock index are two case studies for obtaining the GPNN performance.Keywords: GMDH, GPNN, GA, PNN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20958908 Analysis of Sequence Moves in Successful Chess Openings Using Data Mining with Association Rules
Authors: R.M.Rani
Abstract:
Chess is one of the indoor games, which improves the level of human confidence, concentration, planning skills and knowledge. The main objective of this paper is to help the chess players to improve their chess openings using data mining techniques. Budding Chess Players usually do practices by analyzing various existing openings. When they analyze and correlate thousands of openings it becomes tedious and complex for them. The work done in this paper is to analyze the best lines of Blackmar- Diemer Gambit(BDG) which opens with White D4... using data mining analysis. It is carried out on the collection of winning games by applying association rules. The first step of this analysis is assigning variables to each different sequence moves. In the second step, the sequence association rules were generated to calculate support and confidence factor which help us to find the best subsequence chess moves that may lead to winning position.Keywords: Blackmar-Diemer Gambit(BDG), Confidence, sequence Association Rules, Support.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3093