Search results for: Learning algorithm
1908 PI Control for Second Order Delay System with Tuning Parameter Optimization
Authors: R. Farkh, K. Laabidi, M. Ksouri
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In this paper, we consider the control of time delay system by Proportional-Integral (PI) controller. By Using the Hermite- Biehler theorem, which is applicable to quasi-polynomials, we seek a stability region of the controller for first order delay systems. The essence of this work resides in the extension of this approach to second order delay system, in the determination of its stability region and the computation of the PI optimum parameters. We have used the genetic algorithms to lead the complexity of the optimization problem.Keywords: Genetic algorithm, Hermit-Biehler theorem, optimization, PI controller, second order delay system, stability region.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17751907 The Multi-Layered Perceptrons Neural Networks for the Prediction of Daily Solar Radiation
Authors: Radouane Iqdour, Abdelouhab Zeroual
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The Multi-Layered Perceptron (MLP) Neural networks have been very successful in a number of signal processing applications. In this work we have studied the possibilities and the met difficulties in the application of the MLP neural networks for the prediction of daily solar radiation data. We have used the Polack-Ribière algorithm for training the neural networks. A comparison, in term of the statistical indicators, with a linear model most used in literature, is also performed, and the obtained results show that the neural networks are more efficient and gave the best results.Keywords: Daily solar radiation, Prediction, MLP neural networks, linear model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13291906 A 2D-3D Hybrid Vision System for Robotic Manipulation of Randomly Oriented Objects
Authors: Moulay A. Akhloufi
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This paper presents an new vision technique for robotic manipulation of randomly oriented objects in industrial applications. The proposed approach uses 2D and 3D vision for efficiently extracting the 3D pose of an object in the presence of multiple randomly positioned objects. 2D vision permits to quickly select the objects of interest for 3D processing with a new modified ICP algorithm (FaR-ICP), thus reducing significantly the processing time. The extracted 3D pose is then sent to the robot manipulator for picking. The tests show that the proposed system achieves high performancesKeywords: 3D vision, Hand-Eye calibration, robot visual servoing, random bin picking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18141905 Transformation of Course Timetablinng Problem to RCPSP
Authors: M. Ahmad, M. Gourgand, C. Caux
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The Resource-Constrained Project Scheduling Problem (RCPSP) is concerned with single-item or small batch production where limited resources have to be allocated to dependent activities over time. Over the past few decades, a lot of work has been made with the use of optimal solution procedures for this basic problem type and its extensions. Brucker and Knust[1] discuss, how timetabling problems can be modeled as a RCPSP. Authors discuss high school timetabling and university course timetabling problem as an example. We have formulated two mathematical formulations of course timetabling problem in a new way which are the prototype of single-mode RCPSP. Our focus is to show, how course timetabling problem can be transformed into RCPSP. We solve this transformation model with genetic algorithm.Keywords: Course Timetabling, Integer programming, Combinatorial optimizations
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20161904 Face Recognition using Radial Basis Function Network based on LDA
Authors: Byung-Joo Oh
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This paper describes a method to improve the robustness of a face recognition system based on the combination of two compensating classifiers. The face images are preprocessed by the appearance-based statistical approaches such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). LDA features of the face image are taken as the input of the Radial Basis Function Network (RBFN). The proposed approach has been tested on the ORL database. The experimental results show that the LDA+RBFN algorithm has achieved a recognition rate of 93.5%
Keywords: Face recognition, linear discriminant analysis, radial basis function network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21221903 Accuracy of Divergence Measures for Detection of Abrupt Changes
Authors: P. Bergl
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Numerous divergence measures (spectral distance, cepstral distance, difference of the cepstral coefficients, Kullback-Leibler divergence, distance given by the General Likelihood Ratio, distance defined by the Recursive Bayesian Changepoint Detector and the Mahalanobis measure) are compared in this study. The measures are used for detection of abrupt spectral changes in synthetic AR signals via the sliding window algorithm. Two experiments are performed; the first is focused on detection of single boundary while the second concentrates on detection of a couple of boundaries. Accuracy of detection is judged for each method; the measures are compared according to results of both experiments.Keywords: Abrupt changes detection, autoregressive model, divergence measure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14491902 Enhanced Bidirectional Selection Sort
Authors: Jyoti Dua
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An algorithm is a well-defined procedure that takes some input in the form of some values, processes them and gives the desired output. It forms the basis of many other algorithms such as searching, pattern matching, digital filters etc., and other applications have been found in database systems, data statistics and processing, data communications and pattern matching. This paper introduces algorithmic “Enhanced Bidirectional Selection” sort which is bidirectional, stable. It is said to be bidirectional as it selects two values smallest from the front and largest from the rear and assigns them to their appropriate locations thus reducing the number of passes by half the total number of elements as compared to selection sort.
Keywords: Bubble sort, cocktail sort, selection sort, heap sort.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23731901 Design of an Artificial Intelligence Based Automatic Task Planner or a Robotic System
Authors: T. C. Manjunath, C. Ardil
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This paper deals with the design and the implementation of an automatic task planner for a robot, irrespective of whether it is a stationary robot or a mobile robot. The aim of the task planner nothing but, they are planning systems which are used to plan a particular task and do the robotic manipulation. This planning system is embedded into the system software in the computer, which is interfaced to the computer. When the instructions are given using the computer, this is transformed into real time application using the robot. All the AI based algorithms are written and saved in the control software, which acts as the intelligent task planning system.Keywords: AI, Robot, Task Planner, RT, Algorithm, Specs, Controller.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6201900 Machine Learning Framework: Competitive Intelligence and Key Drivers Identification of Market Share Trends among Healthcare Facilities
Authors: A. Appe, B. Poluparthi, L. Kasivajjula, U. Mv, S. Bagadi, P. Modi, A. Singh, H. Gunupudi, S. Troiano, J. Paul, J. Stovall, J. Yamamoto
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The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data are considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP (SHapley Additive exPlanations), to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since it is data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for e.g., quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP, a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.
Keywords: Competition, DAGs, hospital, healthcare, machine learning, market share, random forest, SHAP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2861899 Evaluation of Ultrasonic C-Scan Images by Fractal Dimension
Authors: S. Samanta, D. Datta, S. S. Gautam
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In this paper, quantitative evaluation of ultrasonic Cscan images through estimation of their Fractal Dimension (FD) is discussed. Necessary algorithm for evaluation of FD of any 2-D digitized image is implemented by developing a computer code. For the evaluation purpose several C-scan images of the Kevlar composite impacted by high speed bullet and glass fibre composite having flaw in the form of inclusion is used. This analysis automatically differentiates a C-scan image showing distinct damage zone, from an image that contains no such damage.Keywords: C-scan, Impact, Fractal Dimension, Kevlar composite and Inclusion Flaw
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17441898 Hybrid Model Based on Artificial Immune System and Cellular Automata
Authors: Ramin Javadzadeh, Zahra Afsahi, MohammadReza Meybodi
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The hybridization of artificial immune system with cellular automata (CA-AIS) is a novel method. In this hybrid model, the cellular automaton within each cell deploys the artificial immune system algorithm under optimization context in order to increase its fitness by using its neighbor-s efforts. The hybrid model CA-AIS is introduced to fix the standard artificial immune system-s weaknesses. The credibility of the proposed approach is evaluated by simulations and it shows that the proposed approach achieves better results compared to standard artificial immune system.Keywords: Artificial Immune System, Cellular Automat, neighborhood
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16031897 Motion Protection System Design for a Parallel Motion Platform
Authors: Dongsu Wu, Hongbin Gu
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A motion protection system is designed for a parallel motion platform with subsided cabin. Due to its complex structure, parallel mechanism is easy to encounter interference problems including link length limits, joints limits and self-collision. Thus a virtual spring algorithm in operational space is developed for the motion protection system to avoid potential damages caused by interference. Simulation results show that the proposed motion protection system can effectively eliminate interference problems and ensure safety of the whole motion platform.Keywords: Motion protection, motion platform, parallelmechanism, Stewart platform, collision avoidance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15711896 Dynamic Attribute Dependencies in Relational Attribute Grammars
Authors: K. Barbar, M. Dehayni, A. Awada, M. Smaili
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Considering the theory of attribute grammars, we use logical formulas instead of traditional functional semantic rules. Following the decoration of a derivation tree, a suitable algorithm should maintain the consistency of the formulas together with the evaluation of the attributes. This may be a Prolog-like resolution, but this paper examines a somewhat different strategy, based on production specialization, local consistency and propagation: given a derivation tree, it is interactively decorated, i.e. incrementally checked and evaluated. The non-directed dependencies are dynamically directed during attribute evaluation.Keywords: Input/Output attribute grammars, local consistency, logical programming, propagation, relational attribute grammars.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14611895 An Efficient Iterative Updating Method for Damped Structural Systems
Authors: Jiashang Jiang
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Model updating is an inverse eigenvalue problem which concerns the modification of an existing but inaccurate model with measured modal data. In this paper, an efficient gradient based iterative method for updating the mass, damping and stiffness matrices simultaneously using a few of complex measured modal data is developed. Convergence analysis indicates that the iterative solutions always converge to the unique minimum Frobenius norm symmetric solution of the model updating problem by choosing a special kind of initial matrices.
Keywords: Model updating, iterative algorithm, damped structural system, optimal approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20841894 Optimum Cascaded Design for Speech Enhancement Using Kalman Filter
Authors: T. Kishore Kumar
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Speech enhancement is the process of eliminating noise and increasing the quality of a speech signal, which is contaminated with other kinds of distortions. This paper is on developing an optimum cascaded system for speech enhancement. This aim is attained without diminishing any relevant speech information and without much computational and time complexity. LMS algorithm, Spectral Subtraction and Kalman filter have been deployed as the main de-noising algorithms in this work. Since these algorithms suffer from respective shortcomings, this work has been undertaken to design cascaded systems in different combinations and the evaluation of such cascades by qualitative (listening) and quantitative (SNR) tests.Keywords: LMS, Kalman filter, Speech Enhancement and Spectral Subtraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17331893 Three-Level Converters Back-to-Back DC Bus Control for Torque Ripple Reduction of Induction Motor
Authors: T. Abdelkrim, K. Benamrane, B. Bezza, Aeh Benkhelifa, A. Borni
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This paper proposes a regulation method of back-to-back connected three-level converters in order to reduce the torque ripple in induction motor. First part is dedicated to the presentation of the feedback control of three-level PWM rectifier. In the second part, three-level NPC voltage source inverter balancing DC bus algorithm is presented. A theoretical analysis with a complete simulation of the system is presented to prove the excellent performance of the proposed technique.
Keywords: Back-to-back connection, Feedback control, Neutral-point balance, Three-level converter, Torque ripple.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25041892 Extended Minimal Controller Synthesis for Voltage-Fed Induction Motor Based on the Hyperstability Theory
Authors: A. Ramdane, F.Naceri, S. Ramdane
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in this work, we present a new strategy of direct adaptive control denoted: Extended minimal controller synthesis (EMCS). This algorithm is designed for an induction motor, which includes both electrical and mechanical dynamics under the assumptions of linear magnetic circuits. The main motivation of the EMCS control is to enhance the robustness of the MRAC algorithms, i.e. the rejection of bounded effects of rapidly varying external disturbances.
Keywords: Adaptive Control, Simple model reference adaptive control (SMRAC), Extended Minimal Controller synthesis (EMCS), Induction Motor (IM)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16401891 Comparison of Different Types of Sources of Traffic Using SFQ Scheduling Discipline
Authors: Alejandro Gomez Suarez, H. Srikanth Kamath
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In this paper, SFQ (Start Time Fair Queuing) algorithm is analyzed when this is applied in computer networks to know what kind of behavior the traffic in the net has when different data sources are managed by the scheduler. Using the NS2 software the computer networks were simulated to be able to get the graphs showing the performance of the scheduler. Different traffic sources were introduced in the scripts, trying to establish the real scenario. Finally the results were that depending on the data source, the traffic can be affected in different levels, when Constant Bite Rate is applied, the scheduler ensures a constant level of data sent and received, but the truth is that in the real life it is impossible to ensure a level that resists the changes in work load. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21381890 Co-Creational Model for Blended Learning in a Flipped Classroom Environment Focusing on the Combination of Coding and Drone-Building
Authors: A. Schuchter, M. Promegger
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The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.Keywords: Flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5041889 Comparison of Frequency Estimation Methods for Reflected Signals in Mobile Platforms
Authors: Kathrin Reinhold
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Precise frequency estimation methods for pulseshaped echoes are a prerequisite to determine the relative velocity between sensor and reflector. Signal frequencies are analysed using three different methods: Fourier Transform, Chirp ZTransform and the MUSIC algorithm. Simulations of echoes are performed varying both the noise level and the number of reflecting points. The superposition of echoes with a random initial phase is found to influence the precision of frequency estimation severely for FFT and MUSIC. The standard deviation of the frequency using FFT is larger than for MUSIC. However, MUSIC is more noise-sensitive. The distorting effect of superpositions is less pronounced in experimental data.
Keywords: Frequency estimation, pulse-echo-method, superposition, echoes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11681888 Islamic Education System: Implementation of Curriculum Kuttab Al-Fatih Semarang
Authors: Basyir Yaman, Fades Br. Gultom
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The picture and pattern of Islamic education in the Prophet's period in Mecca and Medina is the history of the past that we need to bring back. The Basic Education Institute called Kuttab. Kuttab or Maktab comes from the word kataba which means to write. The popular Kuttab in the Prophet’s period aims to resolve the illiteracy in the Arab community. In Indonesia, this Institution has 25 branches; one of them is located in Semarang (i.e. Kuttab Al-Fatih). Kuttab Al-Fatih as a non-formal institution of Islamic education is reserved for children aged 5-12 years. The independently designed curriculum is a distinctive feature that distinguishes between Kuttab Al-Fatih curriculum and the formal institutional curriculum in Indonesia. The curriculum includes the faith and the Qur’an. Kuttab Al-Fatih has been licensed as a Community Activity Learning Center under the direct supervision and guidance of the National Education Department. Here, we focus to describe the implementation of curriculum Kuttab Al-Fatih Semarang (i.e. faith and al-Qur’an). After that, we determine the relevance between the implementation of the Kuttab Al-Fatih education system with the formal education system in Indonesia. This research uses literature review and field research qualitative methods. We obtained the data from the head of Kuttab Al-Fatih Semarang, vice curriculum, faith coordinator, al-Qur’an coordinator, as well as the guardians of learners and the learners. The result of this research is the relevance of education system in Kuttab Al-Fatih Semarang about education system in Indonesia. Kuttab Al-Fatih Semarang emphasizes character building through a curriculum designed in such a way and combines thematic learning models in modules.
Keywords: Islamic education system, implementation of curriculum, Kuttab Al-Fatih semarang, formal education system in Indonesia.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13021887 Enhancing Security in Resource Sharing Using Key Holding Mechanism
Authors: M. Victor Jose, V. Seenivasagam
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This paper describes a logical method to enhance security on the grid computing to restrict the misuse of the grid resources. This method is an economic and efficient one to avoid the usage of the special devices. The security issues, techniques and solutions needed to provide a secure grid computing environment are described. A well defined process for security management among the resource accesses and key holding algorithm is also proposed. In this method, the identity management, access control and authorization and authentication are effectively handled.
Keywords: Grid security, Irregular binary series, Key holding mechanism, Resource identity, Secure resource access.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17251886 Fuzzy Multi-Criteria Framework for Supporting Biofuels Policy Making
Authors: Jadwiga R. Ziolkowska
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In this paper, a fuzzy algorithm and a fuzzy multicriteria decision framework are developed and used for a practical question of optimizing biofuels policy making. The methodological framework shows how to incorporate fuzzy set theory in a decision process of finding a sustainable biofuels policy among several policy options. Fuzzy set theory is used here as a tool to deal with uncertainties of decision environment, vagueness and ambiguities of policy objectives, subjectivities of human assessments and imprecise and incomplete information about the evaluated policy instruments.Keywords: Fuzzy set theory, multi-criteria decision-makingsupport, uncertainties, policy making, biofuels
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20301885 BIBD-s for (13, 5, 5), (16, 6, 5) and (21, 6, 4) Possessing Possibly an Automorphism of Order 3
Authors: Ivica Martinjak, Mario-Osvin Pavcevic
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When trying to enumerate all BIBD-s for given parameters, their natural solution space appears to be huge and grows extremely with the number of points of the design. Therefore, constructive enumerations are often carried out by assuming additional constraints on design-s structure, automorphisms being mostly used ones. It remains a hard task to construct designs with trivial automorphism group – those with no additional symmetry – although it is believed that most of the BIBD-s belong to that case. In this paper, very many new designs with parameters 2-(13, 5, 5), 2-(16, 6, 5) and 2-(21, 6, 4) are constructed, assuming an action of an automorphism of order 3. Even more, it was possible to construct millions of such designs with no non-trivial automorphisms.Keywords: BIBD, incidence matrix, automorphism group, tactical decomposition, deterministic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13191884 Comparative Study of Universities’ Web Structure Mining
Authors: Z. Abdullah, A. R. Hamdan
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This paper is meant to analyze the ranking of University of Malaysia Terengganu, UMT’s website in the World Wide Web. There are only few researches have been done on comparing the ranking of universities’ websites so this research will be able to determine whether the existing UMT’s website is serving its purpose which is to introduce UMT to the world. The ranking is based on hub and authority values which are accordance to the structure of the website. These values are computed using two websearching algorithms, HITS and SALSA. Three other universities’ websites are used as the benchmarks which are UM, Harvard and Stanford. The result is clearly showing that more work has to be done on the existing UMT’s website where important pages according to the benchmarks, do not exist in UMT’s pages. The ranking of UMT’s website will act as a guideline for the web-developer to develop a more efficient website.Keywords: Algorithm, ranking, website, web structure mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16671883 Edge Detection in Low Contrast Images
Authors: Koushlendra Kumar Singh, Manish Kumar Bajpai, Rajesh K. Pandey
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The edges of low contrast images are not clearly distinguishable to human eye. It is difficult to find the edges and boundaries in it. The present work encompasses a new approach for low contrast images. The Chebyshev polynomial based fractional order filter has been used for filtering operation on an image. The preprocessing has been performed by this filter on the input image. Laplacian of Gaussian method has been applied on preprocessed image for edge detection. The algorithm has been tested on two test images.
Keywords: Chebyshev polynomials, Fractional order differentiator, Laplacian of Gaussian (LoG) method, Low contrast image.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32761882 Modeling and Optimization of Aggregate Production Planning - A Genetic Algorithm Approach
Authors: B. Fahimnia, L.H.S. Luong, R. M. Marian
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The Aggregate Production Plan (APP) is a schedule of the organization-s overall operations over a planning horizon to satisfy demand while minimizing costs. It is the baseline for any further planning and formulating the master production scheduling, resources, capacity and raw material planning. This paper presents a methodology to model the Aggregate Production Planning problem, which is combinatorial in nature, when optimized with Genetic Algorithms. This is done considering a multitude of constraints of contradictory nature and the optimization criterion – overall cost, made up of costs with production, work force, inventory, and subcontracting. A case study of substantial size, used to develop the model, is presented, along with the genetic operators.Keywords: Aggregate Production Planning, Costs, and Optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25861881 Efficient Mean Shift Clustering Using Exponential Integral Kernels
Authors: S. Sutor, R. Röhr, G. Pujolle, R. Reda
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This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.
Keywords: Clustering, Integral Images, Kernels, Person Detection, Person Tracking, Intelligent Video Surveillance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15291880 Feature Subset Selection Using Ant Colony Optimization
Authors: Ahmed Al-Ani
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Feature selection is an important step in many pattern classification problems. It is applied to select a subset of features, from a much larger set, such that the selected subset is sufficient to perform the classification task. Due to its importance, the problem of feature selection has been investigated by many researchers. In this paper, a novel feature subset search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.Keywords: Ant Colony Optimization, ant systems, feature selection, pattern recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16021879 A Mean–Variance–Skewness Portfolio Optimization Model
Authors: Kostas Metaxiotis
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Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.
Keywords: Evolutionary algorithms, portfolio optimization, skewness, stock selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1417