Search results for: directional overcurrent relay coordination problem
1009 Fuzzy Logic Controller Based Shunt Active Filter with Different MFs for Current Harmonics Elimination
Authors: Shreyash Sinai Kunde, Siddhang Tendulkar, Shiv Prakash Gupta, Gaurav Kumar, Suresh Mikkili
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One of the major power quality concerns in modern times is the problem of current harmonics. The current harmonics is caused due to the increase in non-linear loads which is largely dominated by power electronics devices. The Shunt active filtering is one of the best solutions for mitigating current harmonics. This paper describes a fuzzy logic controller based (FLC) based three Phase Shunt active Filter to achieve low current harmonic distortion (THD) and Reactive power compensation. The performance of fuzzy logic controller is analysed under both balanced sinusoidal and unbalanced sinusoidal source condition. The above controller serves the purpose of maintaining DC Capacitor Voltage constant. The proposed shunt active filter uses hysteresis current controller for current control of IGBT based PWM inverter. The simulation results of model in Simulink MATLAB reveals satisfying results.
Keywords: Shunt active filter, Current harmonics, Fuzzy logic controller, Hysteresis current controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27111008 Visual Analytics in K 12 Education - Emerging Dimensions of Complexity
Authors: Linnea Stenliden
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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors within Actor-network theory (ANT). The learning conditions are found to be distinguished by broad complexity, characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.
Keywords: Analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16861007 Impacts of Rail Transportation Projects on Urban Areas in Izmir-Turkey
Authors: Y. Egercioglu, S. Yalciner
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With the development of technology, the growing trend of fast and safe passenger transport, air pollution, traffic congestion, increase in problems such as the increasing population and the high cost of private vehicle usage made many cities around the world with a population of more or less, start to build rail systems as a means of urban transport in order to ensure the economic and environmental sustainability and more efficient use of land in the city. The implementation phase of rail systems costs much more than other public transport systems. However, social and economic returns in the long term made these systems the most popular investment tool for planned and developing cities. In our country, the purpose, goals and policies of transportation plans are away from integrity, and the problems are not clearly detected. Also, not defined and incomplete assessment of transportation systems and insufficient financial analysis are the most important cause of failure. Rail systems and other transportation systems to be addressed as a whole is seen as the main factor in increasing efficiency in applications that are not integrated yet in our country to come to this point has led to the problem.Keywords: Urban Transportation Projects, Urban Light Rail Systems, Urbanization, Izmir.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26721006 Methodology of Islamic Economics: Scope and Prospects
Authors: Ahmad Abdulkadir Ibrahim
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Observation of the methodology of Islamic economics laid down for the methods and instruments of analysis and even some of its basic assumptions in the modern world; is a matter that is of paramount importance. There is a need to examine the implications of different suggested definitions of Islamic economics, exploring its scope and attempting to outline its methodology. This paper attempts to deal with the definition of Islamic economics, its methodology, and its scope. It will outline the main methodological problem by addressing the question of whether Islamic economics calls for a methodology of its own or as an expanded economics. It also aims at drawing the attention of economists in the modern world to the obligation and consideration of the methodology of Islamic economics. The methodology adopted in this research is library research through the consultation of relevant literature, which focuses on the thematic study of the subject matter. This is followed by an analysis and discussion of the contents of the materials used. It is concluded that there is a certain degree of inconsistency in the way assumptions are incorporated that perhaps are alien to Islamic economics. The paper also observed that there is a difference between Islamic economists and other (conventional) economists in the profession. An important conclusion is that Islamic economists need to rethink what economics is all about and whether we really have to create an alternative to economics in the form of Islamic economics or simply have an Islamic perspective of the same discipline.
Keywords: Islamic economics, conventional economics, Muslim economists, modern economy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3531005 Control Improvement of a C Sugar Cane Crystallization Using an Auto-Tuning PID Controller Based on Linearization of a Neural Network
Authors: S. Beyou, B. Grondin-Perez, M. Benne, C. Damour, J.-P. Chabriat
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The industrial process of the sugar cane crystallization produces a residual that still contains a lot of soluble sucrose and the objective of the factory is to improve its extraction. Therefore, there are substantial losses justifying the search for the optimization of the process. Crystallization process studied on the industrial site is based on the “three massecuites process". The third step of this process constitutes the final stage of exhaustion of the sucrose dissolved in the mother liquor. During the process of the third step of crystallization (Ccrystallization), the phase that is studied and whose control is to be improved, is the growing phase (crystal growth phase). The study of this process on the industrial site is a problem in its own. A control scheme is proposed to improve the standard PID control law used in the factory. An auto-tuning PID controller based on instantaneous linearization of a neural network is then proposed.
Keywords: Auto-tuning, PID, Instantaneous linearization, Neural network, Non linear process, C-crystallisation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14561004 A New Graphical Password: Combination of Recall & Recognition Based Approach
Authors: Md. Asraful Haque, Babbar Imam
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Information Security is the most describing problem in present times. To cop up with the security of the information, the passwords were introduced. The alphanumeric passwords are the most popular authentication method and still used up to now. However, text based passwords suffer from various drawbacks such as they are easy to crack through dictionary attacks, brute force attacks, keylogger, social engineering etc. Graphical Password is a good replacement for text password. Psychological studies say that human can remember pictures better than text. So this is the fact that graphical passwords are easy to remember. But at the same time due to this reason most of the graphical passwords are prone to shoulder surfing. In this paper, we have suggested a shoulder-surfing resistant graphical password authentication method. The system is a combination of recognition and pure recall based techniques. Proposed scheme can be useful for smart hand held devices (like smart phones i.e. PDAs, iPod, iPhone, etc) which are more handy and convenient to use than traditional desktop computer systems.
Keywords: Authentication, Graphical Password, Text Password, Information Security, Shoulder-surfing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 41331003 Modified Naïve Bayes Based Prediction Modeling for Crop Yield Prediction
Authors: Kefaya Qaddoum
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Most of greenhouse growers desire a determined amount of yields in order to accurately meet market requirements. The purpose of this paper is to model a simple but often satisfactory supervised classification method. The original naive Bayes have a serious weakness, which is producing redundant predictors. In this paper, utilized regularization technique was used to obtain a computationally efficient classifier based on naive Bayes. The suggested construction, utilized L1-penalty, is capable of clearing redundant predictors, where a modification of the LARS algorithm is devised to solve this problem, making this method applicable to a wide range of data. In the experimental section, a study conducted to examine the effect of redundant and irrelevant predictors, and test the method on WSG data set for tomato yields, where there are many more predictors than data, and the urge need to predict weekly yield is the goal of this approach. Finally, the modified approach is compared with several naive Bayes variants and other classification algorithms (SVM and kNN), and is shown to be fairly good.
Keywords: Tomato yields prediction, naive Bayes, redundancy
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 50981002 Analysis of Web User Identification Methods
Authors: Renáta Iváncsy, Sándor Juhász
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Web usage mining has become a popular research area, as a huge amount of data is available online. These data can be used for several purposes, such as web personalization, web structure enhancement, web navigation prediction etc. However, the raw log files are not directly usable; they have to be preprocessed in order to transform them into a suitable format for different data mining tasks. One of the key issues in the preprocessing phase is to identify web users. Identifying users based on web log files is not a straightforward problem, thus various methods have been developed. There are several difficulties that have to be overcome, such as client side caching, changing and shared IP addresses and so on. This paper presents three different methods for identifying web users. Two of them are the most commonly used methods in web log mining systems, whereas the third on is our novel approach that uses a complex cookie-based method to identify web users. Furthermore we also take steps towards identifying the individuals behind the impersonal web users. To demonstrate the efficiency of the new method we developed an implementation called Web Activity Tracking (WAT) system that aims at a more precise distinction of web users based on log data. We present some statistical analysis created by the WAT on real data about the behavior of the Hungarian web users and a comprehensive analysis and comparison of the three methodsKeywords: Data preparation, Tracking individuals, Web useridentification, Web usage mining
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 43851001 A New Hybrid K-Mean-Quick Reduct Algorithm for Gene Selection
Authors: E. N. Sathishkumar, K. Thangavel, T. Chandrasekhar
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Feature selection is a process to select features which are more informative. It is one of the important steps in knowledge discovery. The problem is that all genes are not important in gene expression data. Some of the genes may be redundant, and others may be irrelevant and noisy. Here a novel approach is proposed Hybrid K-Mean-Quick Reduct (KMQR) algorithm for gene selection from gene expression data. In this study, the entire dataset is divided into clusters by applying K-Means algorithm. Each cluster contains similar genes. The high class discriminated genes has been selected based on their degree of dependence by applying Quick Reduct algorithm to all the clusters. Average Correlation Value (ACV) is calculated for the high class discriminated genes. The clusters which have the ACV value as 1 is determined as significant clusters, whose classification accuracy will be equal or high when comparing to the accuracy of the entire dataset. The proposed algorithm is evaluated using WEKA classifiers and compared. The proposed work shows that the high classification accuracy.
Keywords: Clustering, Gene Selection, K-Mean-Quick Reduct, Rough Sets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22901000 An Efficient 3D Animation Data Reduction Using Frame Removal
Authors: Jinsuk Yang, Choongjae Joo, Kyoungsu Oh
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Existing methods in which the animation data of all frames are stored and reproduced as with vertex animation cannot be used in mobile device environments because these methods use large amounts of the memory. So 3D animation data reduction methods aimed at solving this problem have been extensively studied thus far and we propose a new method as follows. First, we find and remove frames in which motion changes are small out of all animation frames and store only the animation data of remaining frames (involving large motion changes). When playing the animation, the removed frame areas are reconstructed using the interpolation of the remaining frames. Our key contribution is to calculate the accelerations of the joints of individual frames and the standard deviations of the accelerations using the information of joint locations in the relevant 3D model in order to find and delete frames in which motion changes are small. Our methods can reduce data sizes by approximately 50% or more while providing quality which is not much lower compared to original animations. Therefore, our method is expected to be usefully used in mobile device environments or other environments in which memory sizes are limited.
Keywords: Data Reduction, Interpolation, Vertex Animation, 3D Animation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1650999 Single Image Defogging Method Using Variational Approach for Edge-Preserving Regularization
Authors: Wan-Hyun Cho, In-Seop Na, Seong-ChaeSeo, Sang-Kyoon Kim, Soon-Young Park
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In this paper, we propose the variational approach to solve single image defogging problem. In the inference process of the atmospheric veil, we defined new functional for atmospheric veil that satisfy edge-preserving regularization property. By using the fundamental lemma of calculus of variations, we derive the Euler-Lagrange equation foratmospheric veil that can find the maxima of a given functional. This equation can be solved by using a gradient decent method and time parameter. Then, we can have obtained the estimated atmospheric veil, and then have conducted the image restoration by using inferred atmospheric veil. Finally we have improved the contrast of restoration image by various histogram equalization methods. The experimental results show that the proposed method achieves rather good defogging results.
Keywords: Image defogging, Image restoration, Atmospheric veil, Transmission, Variational approach, Euler-Lagrange equation, Image enhancement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2933998 3D Network-on-Chip with on-Chip DRAM: An Empirical Analysis for Future Chip Multiprocessor
Authors: Thomas Canhao Xu, Bo Yang, Alexander Wei Yin, Pasi Liljeberg, Hannu Tenhunen
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With the increasing number of on-chip components and the critical requirement for processing power, Chip Multiprocessor (CMP) has gained wide acceptance in both academia and industry during the last decade. However, the conventional bus-based onchip communication schemes suffer from very high communication delay and low scalability in large scale systems. Network-on-Chip (NoC) has been proposed to solve the bottleneck of parallel onchip communications by applying different network topologies which separate the communication phase from the computation phase. Observing that the memory bandwidth of the communication between on-chip components and off-chip memory has become a critical problem even in NoC based systems, in this paper, we propose a novel 3D NoC with on-chip Dynamic Random Access Memory (DRAM) in which different layers are dedicated to different functionalities such as processors, cache or memory. Results show that, by using our proposed architecture, average link utilization has reduced by 10.25% for SPLASH-2 workloads. Our proposed design costs 1.12% less execution cycles than the traditional design on average.
Keywords: 3D integration, network-on-chip, memory-on-chip, DRAM, chip multiprocessor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2435997 Prediction of Rubberised Concrete Strength by Using Artificial Neural Networks
Authors: A. M. N. El-Khoja, A. F. Ashour, J. Abdalhmid, X. Dai, A. Khan
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In recent years, waste tyre problem is considered as one of the most crucial environmental pollution problems facing the world. Thus, reusing waste rubber crumb from recycled tyres to develop highly damping concrete is technically feasible and a viable alternative to landfill or incineration. The utilization of waste rubber in concrete generally enhances the ductility, toughness, thermal insulation, and impact resistance. However, the mechanical properties decrease with the amount of rubber used in concrete. The aim of this paper is to develop artificial neural network (ANN) models to predict the compressive strength of rubberised concrete (RuC). A trained and tested ANN was developed using a comprehensive database collected from different sources in the literature. The ANN model developed used 5 input parameters that include: coarse aggregate (CA), fine aggregate (FA), w/c ratio, fine rubber (Fr), and coarse rubber (Cr), whereas the ANN outputs were the corresponding compressive strengths. A parametric study was also conducted to study the trend of various RuC constituents on the compressive strength of RuC.Keywords: Rubberized concrete, compressive strength, artificial neural network, prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 898996 OCR for Script Identification of Hindi (Devnagari) Numerals using Feature Sub Selection by Means of End-Point with Neuro-Memetic Model
Authors: Banashree N. P., R. Vasanta
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Recognition of Indian languages scripts is challenging problems. In Optical Character Recognition [OCR], a character or symbol to be recognized can be machine printed or handwritten characters/numerals. There are several approaches that deal with problem of recognition of numerals/character depending on the type of feature extracted and different way of extracting them. This paper proposes a recognition scheme for handwritten Hindi (devnagiri) numerals; most admired one in Indian subcontinent. Our work focused on a technique in feature extraction i.e. global based approach using end-points information, which is extracted from images of isolated numerals. These feature vectors are fed to neuro-memetic model [18] that has been trained to recognize a Hindi numeral. The archetype of system has been tested on varieties of image of numerals. . In proposed scheme data sets are fed to neuro-memetic algorithm, which identifies the rule with highest fitness value of nearly 100 % & template associates with this rule is nothing but identified numerals. Experimentation result shows that recognition rate is 92-97 % compared to other models.Keywords: OCR, Global Feature, End-Points, Neuro-Memetic model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1753995 Method of Parameter Calibration for Error Term in Stochastic User Equilibrium Traffic Assignment Model
Authors: Xiang Zhang, David Rey, S. Travis Waller
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Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model.
Keywords: Parameter calibration, sequential quadratic programming, Stochastic User Equilibrium, traffic assignment, transportation planning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2115994 Evaluation of Model Evaluation Criterion for Software Development Effort Estimation
Authors: S. K. Pillai, M. K. Jeyakumar
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Estimation of model parameters is necessary to predict the behavior of a system. Model parameters are estimated using optimization criteria. Most algorithms use historical data to estimate model parameters. The known target values (actual) and the output produced by the model are compared. The differences between the two form the basis to estimate the parameters. In order to compare different models developed using the same data different criteria are used. The data obtained for short scale projects are used here. We consider software effort estimation problem using radial basis function network. The accuracy comparison is made using various existing criteria for one and two predictors. Then, we propose a new criterion based on linear least squares for evaluation and compared the results of one and two predictors. We have considered another data set and evaluated prediction accuracy using the new criterion. The new criterion is easy to comprehend compared to single statistic. Although software effort estimation is considered, this method is applicable for any modeling and prediction.
Keywords: Software effort estimation, accuracy, Radial Basis Function, linear least squares.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2027993 Thailand and Procession of Trafficking Human Beings (Women and Children)
Authors: Kawinphat Lertpongmanee
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The problems of trafficking human beings were continuously violent in Thailand. The problems occurred from a variety of factors such as unemployment, agricultural workers’ urban immigration, sex tour, attitude of materialism society, divorced family, unsavourily effected law, and officers’ ignorance. The purposes of this study were to study the structure, connection, a number of trafficking human beings in Thailand. Qualitative and quantitative and results of previous research were used in this research. The previous procurers, interested persons, experienced people, human beings-aiding organization, and women-children rights organization were interviewed in depth. The field was used in a variety of regions. The findings showed that the structure and connection of trafficking human beings and their values are $8,750 million. There are 240,000 people in trafficked human beings. The trend of trafficking human beings grows continuously. It is changed according to economic circumstance, society and culture, and law. The state must be aware of its problem. The law is enacted by adding high penalty for serious fear.
Keywords: Human Trade, Prostitution trafficking, trafficking in women and children.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1611992 A Black-box Approach for Response Quality Evaluation of Conversational Agent Systems
Authors: Ong Sing Goh, C. Ardil, Wilson Wong, Chun Che Fung
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The evaluation of conversational agents or chatterbots question answering systems is a major research area that needs much attention. Before the rise of domain-oriented conversational agents based on natural language understanding and reasoning, evaluation is never a problem as information retrieval-based metrics are readily available for use. However, when chatterbots began to become more domain specific, evaluation becomes a real issue. This is especially true when understanding and reasoning is required to cater for a wider variety of questions and at the same time to achieve high quality responses. This paper discusses the inappropriateness of the existing measures for response quality evaluation and the call for new standard measures and related considerations are brought forward. As a short-term solution for evaluating response quality of conversational agents, and to demonstrate the challenges in evaluating systems of different nature, this research proposes a blackbox approach using observation, classification scheme and a scoring mechanism to assess and rank three example systems, AnswerBus, START and AINI.
Keywords: Evaluation, conversational agents, Response Quality, chatterbots
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1915991 Optimal Design of Multimachine Power System Stabilizers Using Improved Multi-Objective Particle Swarm Optimization Algorithm
Authors: Badr M. Alshammari, T. Guesmi
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In this paper, the concept of a non-dominated sorting multi-objective particle swarm optimization with local search (NSPSO-LS) is presented for the optimal design of multimachine power system stabilizers (PSSs). The controller design is formulated as an optimization problem in order to shift the system electromechanical modes in a pre-specified region in the s-plan. A composite set of objective functions comprising the damping factor and the damping ratio of the undamped and lightly damped electromechanical modes is considered. The performance of the proposed optimization algorithm is verified for the 3-machine 9-bus system. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and superiority of the NSPSO-LS algorithm in tuning PSSs over a wide range of loading conditions and large disturbance compared to the classic PSO technique and genetic algorithms.
Keywords: Multi-objective optimization, particle swarm optimization, power system stabilizer, low frequency oscillations.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1219990 N-Grams: A Tool for Repairing Word Order Errors in Ill-formed Texts
Authors: Theologos Athanaselis, Stelios Bakamidis, Ioannis Dologlou, Konstantinos Mamouras
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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. A possible way for reordering the words is to use all the permutations. The problem is that for a sentence with length N words the number of all permutations is N!. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The confusion matrix technique has been designed in order to reduce the search space among permuted sentences. The limitation of search space is succeeded using the statistical inference of N-grams. The results of this technique are very interesting and prove that the number of permuted sentences can be reduced by 98,16%. For experimental purposes a test set of TOEFL sentences was used and the results show that more than 95% can be repaired using the proposed method.
Keywords: Permutations filtering, Statistical language model N-grams, Word order errors, TOEFL
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1659989 Structural Modelling of the LiCl Aqueous Solution: Using the Hybrid Reverse Monte Carlo (HRMC) Simulation
Authors: M. Habchi, S.M. Mesli, M. Kotbi
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The Reverse Monte Carlo (RMC) simulation is applied in the study of an aqueous electrolyte LiCl6H2O. On the basis of the available experimental neutron scattering data, RMC computes pair radial distribution functions in order to explore the structural features of the system. The obtained results include some unrealistic features. To overcome this problem, we use the Hybrid Reverse Monte Carlo (HRMC), incorporating an energy constraint in addition to the commonly used constraints derived from experimental data. Our results show a good agreement between experimental and computed partial distribution functions (PDFs) as well as a significant improvement in pair partial distribution curves. This kind of study can be considered as a useful test for a defined interaction model for conventional simulation techniques.
Keywords: RMC simulation, HRMC simulation, energy constraint, screened potential, glassy state, liquid state, partial distribution function, pair partial distribution function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1456988 Effect of Different Treatments on Heavy Metal Concentration in Sugar Cane Molasses
Authors: Gomaa N. Abdel-Rahman, Nadia R. A. Nassar, Yehia A. Heikal, Mahmoud A. M. Abou-Donia, Mohamed M. Naguib, Mohamed Fadel
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Cane molasses is used as a raw material for the production of baker’s yeast (Saccharomyces cerevisiae) in Egypt. The high levels of heavy metals in molasses cause a critical problem during fermentation and cause various kinds of technological difficulties (yield and quality of yeast become lower). The aim of the present study was to determine heavy metal concentrations (cadmium, nickel, lead, and copper) in crude and treated molasses obtained from the storage tanks of the baker’s yeast factory through four seasons. Also, the effect of crude molasses treatment by different methods (at laboratory scale) on heavy metals reduction and its comparison with factory treated molasses were conducted. The molasses samples obtained at autumn season had the highest values of all the studied heavy metals. The molasses treated by cation exchange resin then sulfuric acid had the lowest concentrations of heavy metals compared with other treatments.
Keywords: Molasses, baker’s yeast, heavy metals, treatment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2475987 Aircraft Selection Problem Using Decision Uncertainty Distance in Fuzzy Multiple Criteria Decision Making Analysis
Authors: C. Ardil
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Aircraft have different capabilities and specifications according to the required strategic goals and objectives in operations. With various types on the market with different aircraft characteristics, it becomes difficult to select a suitable aircraft for certain operations and requirements. The entropy weighting method (EWM) is a useful, highly consistent, and reliable method for obtaining the weights of the criteria and is worth integrating with the decision uncertainty distance (DUD) method, which is more applicable and requires less computation than other methods. An illustrative example is presented to demonstrate the validity and usability of the proposed methodology. Comparing the ranking results matches the distance-based approach, which is the technique for order preference by similarity to ideal solution (TOPSIS) method, which shows the robustness of the entropy DUD hybrid method. Validity analysis shows that the proposed hybrid multiple criteria decision-making analysis (MCDMA) methodology is quantitatively stable and reliable.
Keywords: aircraft selection, decision uncertainty distance (DUD), multiple criteria decision making analysis, MCDMA, TOPSIS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 517986 An Algorithm for Secure Visible Logo Embedding and Removing in Compression Domain
Authors: Hongyuan Li, Guang Liu, Yuewei Dai, Zhiquan Wang
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Digital watermarking is the process of embedding information into a digital signal which can be used in DRM (digital rights managements) system. The visible watermark (often called logo) can indicate the owner of the copyright which can often be seen in the TV program and protects the copyright in an active way. However, most of the schemes do not consider the visible watermark removing process. To solve this problem, a visible watermarking scheme with embedding and removing process is proposed under the control of a secure template. The template generates different version of watermarks which can be seen visually the same for different users. Users with the right key can completely remove the watermark and recover the original image while the unauthorized user is prevented to remove the watermark. Experiment results show that our watermarking algorithm obtains a good visual quality and is hard to be removed by the illegally users. Additionally, the authorized users can completely remove the visible watermark and recover the original image with a good quality.Keywords: digital watermarking, visible and removablewatermark, secure template, JPEG compression
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1527985 Enhancing Rural Agricultural Value Chains through Electric Mobility Services in Ethiopia
Authors: Clemens Pizzinini, Philipp Rosner, David Ziegler, Markus Lienkamp
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Transportation is a constitutional part of most supply and value chains in modern economies. Smallholder farmers in rural Ethiopia face severe challenges along their supply and value chains. In particular, suitable, affordable, and available transport services are in high demand. To develop context-specific technical solutions, a problem-to-solution methodology based on the interaction with technology is developed. With this approach, we fill the gap between proven transportation assessment frameworks and general user-centered techniques. Central to our approach is an electric test vehicle that is implemented in rural supply and value chains for research, development, and testing. Based on our objective and the derived methodological requirements, a set of existing methods is selected. Local partners are integrated in an organizational framework that executes major parts of this research endeavour in Arsi Zone, Oromia Region, Ethiopia.
Keywords: Agricultural value chain, participatory methods, agile methods, sub-Saharan Africa, Ethiopia, electric vehicle, transport service.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 140984 Learning Algorithms for Fuzzy Inference Systems Composed of Double- and Single-Input Rule Modules
Authors: Hirofumi Miyajima, Kazuya Kishida, Noritaka Shigei, Hiromi Miyajima
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Most of self-tuning fuzzy systems, which are automatically constructed from learning data, are based on the steepest descent method (SDM). However, this approach often requires a large convergence time and gets stuck into a shallow local minimum. One of its solutions is to use fuzzy rule modules with a small number of inputs such as DIRMs (Double-Input Rule Modules) and SIRMs (Single-Input Rule Modules). In this paper, we consider a (generalized) DIRMs model composed of double and single-input rule modules. Further, in order to reduce the redundant modules for the (generalized) DIRMs model, pruning and generative learning algorithms for the model are suggested. In order to show the effectiveness of them, numerical simulations for function approximation, Box-Jenkins and obstacle avoidance problems are performed.Keywords: Box-Jenkins’s problem, Double-input rule module, Fuzzy inference model, Obstacle avoidance, Single-input rule module.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1948983 Elman Neural Network for Diagnosis of Unbalance in a Rotor-Bearing System
Authors: S. Sendhilkumar, N. Mohanasundaram, M. Senthilkumar, S. N. Sivanandam
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The operational life of rotating machines has to be extended using a predictive condition maintenance tool. Among various condition monitoring techniques, vibration analysis is most widely used technique in industry. Signals are extracted for evaluating the condition of machine; further diagnostics is carried out with detected signals to extend the life of machine. With help of detected signals, further interpretations are done to predict the occurrence of defects. To study the problem of defects, a test rig with various possibilities of defects is constructed and experiments are performed considering the unbalanced condition. Further, this paper presents an approach for fault diagnosis of unbalance condition using Elman neural network and frequency-domain vibration analysis. Amplitudes with variation in acceleration are fed to Elman neural network to classify fault or no-fault condition. The Elman network is trained, validated and tested with experimental readings. Results illustrate the effectiveness of Elman network in rotor-bearing system.Keywords: Elman neural network, fault detection, rotating machines, unbalance, vibration analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1456982 Towards a Load Balancing Framework for an SMS–Based Service Invocation Environment
Authors: Mandla T. Nene, Edgar.Jembere, Matthew O. Adigun, Themba Shezi, Siyabonga S. Cebekhulu
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The drastic increase in the usage of SMS technology has led service providers to seek for a solution that enable users of mobile devices to access services through SMSs. This has resulted in the proposal of solutions towards SMS-based service invocation in service oriented environments. However, the dynamic nature of service-oriented environments coupled with sudden load peaks generated by service request, poses performance challenges to infrastructures for supporting SMS-based service invocation. To address this problem we adopt load balancing techniques. A load balancing model with adaptive load balancing and load monitoring mechanisms as its key constructs is proposed. The load balancing model then led to realization of Least Loaded Load Balancing Framework (LLLBF). Evaluation of LLLBF benchmarked with round robin (RR) scheme on the queuing approach showed LLLBF outperformed RR in terms of response time and throughput. However, LLLBF achieved better result in the cost of high processing power.Keywords: SMS (Short Message Service), LLLBF (Least Loaded Load Balancing Framework), Service Oriented Computing (SOC).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1634981 Unlocking Tourism Value through a Tourist Experience Management Paradigm
Authors: Siphiwe P. Mandina, Tinashe Shamuyashe
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Tourism has become a topical issue amongst academics and practitioners due to its potential to contribute significantly towards an economy’s GDP. The problem underpinning this research is the fact that the major attraction, Victoria Falls, is being marketed in neighboring countries like South Africa, Botswana and Zambia with tour operators providing just day trips to the Victoria Falls. This has deprived Zimbabwe of income from tourism with tourists making day trips and actually not spending nights in Zimbabwe. This therefore calls for cutting edge marketing strategies that are superior to or inimitable by competing nations such as South Africa and Zambia. This study proposes a shift towards an experience management paradigm in the tourism sector. A qualitative research was adopted for this study, and findings of this study were generalized across different tourism contexts, therefore making the survey based research design more appropriate. The target population for this study is tourists visiting Zimbabwe over the period 2016 and ZTA visitor database acquired from the Department of Immigration will form the sampling frame for the purposes of this study.
Keywords: Competitiveness, tourist arrivals, tourist experience, Zimbabwe.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1090980 Robust Design of Power System Stabilizers Using Adaptive Genetic Algorithms
Authors: H. Alkhatib, J. Duveau
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Genetic algorithms (GAs) have been widely used for global optimization problems. The GA performance depends highly on the choice of the search space for each parameter to be optimized. Often, this choice is a problem-based experience. The search space being a set of potential solutions may contain the global optimum and/or other local optimums. A bad choice of this search space results in poor solutions. In this paper, our approach consists in extending the search space boundaries during the GA optimization, only when it is required. This leads to more diversification of GA population by new solutions that were not available with fixed search space boundaries. So, these dynamic search spaces can improve the GA optimization performances. The proposed approach is applied to power system stabilizer optimization for multimachine power system (16-generator and 68-bus). The obtained results are evaluated and compared with those obtained by ordinary GAs. Eigenvalue analysis and nonlinear system simulation results show the effectiveness of the proposed approach to damp out the electromechanical oscillation and enhance the global system stability.Keywords: Genetic Algorithms, Multiobjective Optimization, Power System Stabilizer, Small Signal Stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1717