Search results for: Expanded Invasive Weed Optimization algorithm (exIWO)
916 An Earth Mover’s Distance Algorithm Based DDoS Detection Mechanism in SDN
Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu
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Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.Keywords: DDoS detection, EMD, relative entropy, SDN.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 766915 Image Retrieval Using Fused Features
Authors: K. Sakthivel, R. Nallusamy, C. Kavitha
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The system is designed to show images which are related to the query image. Extracting color, texture, and shape features from an image plays a vital role in content-based image retrieval (CBIR). Initially RGB image is converted into HSV color space due to its perceptual uniformity. From the HSV image, Color features are extracted using block color histogram, texture features using Haar transform and shape feature using Fuzzy C-means Algorithm. Then, the characteristics of the global and local color histogram, texture features through co-occurrence matrix and Haar wavelet transform and shape are compared and analyzed for CBIR. Finally, the best method of each feature is fused during similarity measure to improve image retrieval effectiveness and accuracy.
Keywords: Color Histogram, Haar Wavelet Transform, Fuzzy C-means, Co-occurrence matrix; Similarity measure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2127914 Optimal Placement of DG in Distribution System to Mitigate Power Quality Disturbances
Authors: G.V.K Murthy, S. Sivanagaraju, S. Satyanarayana, B. Hanumantha Rao
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Distributed Generation (DG) systems are considered an integral part in future distribution system planning. Appropriate size and location of distributed generation plays a significant role in minimizing power losses in distribution systems. Among the benefits of distributed generation is the reduction in active power losses, which can improve the system performance, reliability and power quality. In this paper, Artificial Bee Colony (ABC) algorithm is proposed to determine the optimal DG-unit size and location by loss sensitivity index in order to minimize the real power loss, total harmonic distortion (THD) and voltage sag index improvement. Simulation study is conducted on 69-bus radial test system to verify the efficacy of the proposed method.
Keywords: Distributed generation, artificial bee colony method, loss reduction, radial distribution network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2859913 Sorption of Nickel by Hypnea Valentiae: Application of Response Surface Methodology
Authors: M. Rajasimman, K. Murugaiyan
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In this work, sorption of nickel from aqueous solution on hypnea valentiae, red macro algae, was investigated. Batch experiments have been carried out to find the effect of various parameters such as pH, temperature, sorbent dosage, metal concentration and contact time on the sorption of nickel using hypnea valentiae. Response surface methodology (RSM) is employed to optimize the process parameters. Based on the central composite design, quadratic model was developed to correlate the process variables to the response. The most influential factor on each experimental design response was identified from the analysis of variance (ANOVA). The optimum conditions for the sorption of nickel were found to be: pH – 5.1, temperature – 36.8oC, sorbent dosage – 5.1 g/L, metal concentration – 100 mg/L and contact time – 30 min. At these optimized conditions the maximum removal of nickel was found to be 91.97%. A coefficient of determination R2 value 0.9548 shows the fitness of response surface methodology in this work.
Keywords: Optimization, metal, Hypnea valentia, response surface methodology, red algae.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1662912 Optimization of Surface Finish in Milling Operation Using Live Tooling via Taguchi Method
Authors: Harish Kumar Ponnappan, Joseph C. Chen
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The main objective of this research is to optimize the surface roughness of a milling operation on AISI 1018 steel using live tooling on a HAAS ST-20 lathe. In this study, Taguchi analysis is used to optimize the milling process by investigating the effect of different machining parameters on surface roughness. The L9 orthogonal array is designed with four controllable factors with three different levels each and an uncontrollable factor, resulting in 18 experimental runs. The optimal parameters determined from Taguchi analysis were feed rate – 76.2 mm/min, spindle speed 1150 rpm, depth of cut – 0.762 mm and 2-flute TiN coated high-speed steel as tool material. The process capability Cp and process capability index Cpk values were improved from 0.62 and -0.44 to 1.39 and 1.24 respectively. The average surface roughness values from the confirmation runs were 1.30 µ, decreasing the defect rate from 87.72% to 0.01%. The purpose of this study is to efficiently utilize the Taguchi design to optimize the surface roughness in a milling operation using live tooling.
Keywords: Live tooling, surface roughness, Taguchi analysis, Computer Numerical Control (CNC) milling operation, CNC turning operation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 771911 Development of Intelligent Time/Frequency Based Signal Detection Algorithm for Intrusion Detection System
Authors: Waqas Ahmed, S Sajjad Haider Zaidi
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For the past couple of decades Weak signal detection is of crucial importance in various engineering and scientific applications. It finds its application in areas like Wireless communication, Radars, Aerospace engineering, Control systems and many of those. Usually weak signal detection requires phase sensitive detector and demodulation module to detect and analyze the signal. This article gives you a preamble to intrusion detection system which can effectively detect a weak signal from a multiplexed signal. By carefully inspecting and analyzing the respective signal, this system can successfully indicate any peripheral intrusion. Intrusion detection system (IDS) is a comprehensive and easy approach towards detecting and analyzing any signal that is weakened and garbled due to low signal to noise ratio (SNR). This approach finds significant importance in applications like peripheral security systems.Keywords: Data Acquisition, fast frequency transforms, Lab VIEW software, weak signal detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2510910 Location Detection of Vehicular Accident Using Global Navigation Satellite Systems/Inertial Measurement Units Navigator
Authors: Neda Navidi, Rene Jr. Landry
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Vehicle tracking and accident recognizing are considered by many industries like insurance and vehicle rental companies. The main goal of this paper is to detect the location of a car accident by combining different methods. The methods, which are considered in this paper, are Global Navigation Satellite Systems/Inertial Measurement Units (GNSS/IMU)-based navigation and vehicle accident detection algorithms. They are expressed by a set of raw measurements, which are obtained from a designed integrator black box using GNSS and inertial sensors. Another concern of this paper is the definition of accident detection algorithm based on its jerk to identify the position of that accident. In fact, the results convinced us that, even in GNSS blockage areas, the position of the accident could be detected by GNSS/INS integration with 50% improvement compared to GNSS stand alone.
Keywords: Driving behavior, integration, IMU, GNSS, monitoring, tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1230909 Mobile Robot Navigation Using Local Model Networks
Authors: Hamdi. A. Awad, Mohamed A. Al-Zorkany
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Developing techniques for mobile robot navigation constitutes one of the major trends in the current research on mobile robotics. This paper develops a local model network (LMN) for mobile robot navigation. The LMN represents the mobile robot by a set of locally valid submodels that are Multi-Layer Perceptrons (MLPs). Training these submodels employs Back Propagation (BP) algorithm. The paper proposes the fuzzy C-means (FCM) in this scheme to divide the input space to sub regions, and then a submodel (MLP) is identified to represent a particular region. The submodels then are combined in a unified structure. In run time phase, Radial Basis Functions (RBFs) are employed as windows for the activated submodels. This proposed structure overcomes the problem of changing operating regions of mobile robots. Read data are used in all experiments. Results for mobile robot navigation using the proposed LMN reflect the soundness of the proposed scheme.Keywords: Mobile Robot Navigation, Neural Networks, Local Model Networks
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2021908 Modeling, Analysis and Control of a Smart Composite Structure
Authors: Nader H. Ghareeb, Mohamed S. Gaith, Sayed M. Soleimani
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In modern engineering, weight optimization has a priority during the design of structures. However, optimizing the weight can result in lower stiffness and less internal damping, causing the structure to become excessively prone to vibration. To overcome this problem, active or smart materials are implemented. The coupled electromechanical properties of smart materials, used in the form of piezoelectric ceramics in this work, make these materials well-suited for being implemented as distributed sensors and actuators to control the structural response. The smart structure proposed in this paper is composed of a cantilevered steel beam, an adhesive or bonding layer, and a piezoelectric actuator. The static deflection of the structure is derived as function of the piezoelectric voltage, and the outcome is compared to theoretical and experimental results from literature. The relation between the voltage and the piezoelectric moment at both ends of the actuator is also investigated and a reduced finite element model of the smart structure is created and verified. Finally, a linear controller is implemented and its ability to attenuate the vibration due to the first natural frequency is demonstrated.
Keywords: Active linear control, Lyapunov stability theorem, piezoelectricity, smart structure, static deflection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1497907 Heat Transfer Modeling in Multi-Layer Cookware using Finite Element Method
Authors: Mohammad Reza Sedighi, Behnam Nilforooshan Dardashti
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The high temperature degree and uniform Temperature Distribution (TD) on surface of cookware which contact with food are effective factors for improving cookware application. Additionally, the ability of pan material in retaining the heat and nonreactivity with foods are other significant properties. It is difficult for single material to meet a wide variety of demands such as superior thermal and chemical properties. Multi-Layer Plate (MLP) makes more regular TD. In this study the main objectives are to find the best structure (single or multi-layer) and materials to provide maximum temperature degree and uniform TD up side surface of pan. And also heat retaining of used metals with goal of improving the thermal quality of pan to economize the energy. To achieve this aim were employed Finite Element Method (FEM) for analyzing transient thermal behavior of applied materials. The analysis has been extended for different metals, we achieved the best temperature profile and heat retaining in Copper/ Stainless Steel MLP.Keywords: Cookware, Energy optimization, Heat retaining, Laminated plate, Temperature distribution
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2383906 Advanced Neural Network Learning Applied to Pulping Modeling
Authors: Z. Zainuddin, W. D. Wan Rosli, R. Lanouette, S. Sathasivam
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This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Keywords: Convergence, pulping modeling, neural networks, preconditioned conjugate gradient.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1408905 Kalman Filter Gain Elimination in Linear Estimation
Authors: Nicholas D. Assimakis
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In linear estimation, the traditional Kalman filter uses the Kalman filter gain in order to produce estimation and prediction of the n-dimensional state vector using the m-dimensional measurement vector. The computation of the Kalman filter gain requires the inversion of an m x m matrix in every iteration. In this paper, a variation of the Kalman filter eliminating the Kalman filter gain is proposed. In the time varying case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix and the inversion of an m x m matrix in every iteration. In the time invariant case, the elimination of the Kalman filter gain requires the inversion of an n x n matrix in every iteration. The proposed Kalman filter gain elimination algorithm may be faster than the conventional Kalman filter, depending on the model dimensions.
Keywords: Discrete time, linear estimation, Kalman filter, Kalman filter gain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 638904 Exploring the Ambiguity Resolution in Spacecraft Attitude Determination Using GNSS Phase Measurement
Authors: Lv Meibo, Naqvi Najam Abbas, Li YanJun
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Attitude Determination (AD) of a spacecraft using the phase measurements of the Global Navigation Satellite System (GNSS) is an active area of research. Various attitude determination algorithms have been developed in yester years for spacecrafts using different sensors but the last two decades have witnessed a phenomenal increase in research related with GPS receivers as a stand-alone sensor for determining the attitude of satellite using the phase measurements of the signals from GNSS. The GNSS-based Attitude determination algorithms have been experimented in many real missions. The problem of AD algorithms using GNSS phase measurements has two important parts; the ambiguity resolution and the determining of attitude. Ambiguity resolution is the widely addressed topic in literature for implementing the AD algorithm using GNSS phase measurements for achieving the accuracy of millimeter level. This paper broadly overviews the different techniques for resolving the integer ambiguities encountered in AD using GNSS phase measurements.
Keywords: Attitude Determination, Ambiguity Resolution, GNSS, LAMBDA Method, Satellite.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2744903 Walking Hexapod Robot in Disaster Recovery: Developing Algorithm for Terrain Negotiation and Navigation
Authors: Md. Masum Billah, Mohiuddin Ahmed, Soheli Farhana
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In modern day disaster recovery mission has become one of the top priorities in any natural disaster management regime. Smart autonomous robots may play a significant role in such missions, including search for life under earth quake hit rubbles, Tsunami hit islands, de-mining in war affected areas and many other such situations. In this paper current state of many walking robots are compared and advantages of hexapod systems against wheeled robots are described. In our research we have selected a hexapod spider robot; we are developing focusing mainly on efficient navigation method in different terrain using apposite gait of locomotion, which will make it faster and at the same time energy efficient to navigate and negotiate difficult terrain. This paper describes the method of terrain negotiation navigation in a hazardous field.Keywords: Walking robots, locomotion, hexapod robot, gait, hazardous field.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4433902 Online Brands: A Comparative Study of World Top Ranked Universities with Science and Technology Programs
Authors: Zullina H. Shaari, Amzairi Amar, Abdul Mutalib Embong, Hezlina Hashim
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University websites are considered as one of the brand primary touch points for multiple stakeholders, but most of them did not have great designs to create favorable impressions. Some of the elements that web designers should carefully consider are the appearance, the content, the functionality, usability and search engine optimization. However, priority should be placed on website simplicity and negative space. In terms of content, previous research suggests that universities should include reputation, learning environment, graduate career prospects, image destination, cultural integration, and virtual tour on their websites. The study examines how top 200 world ranking science and technology-based universities present their brands online and whether the websites capture the content dimensions. Content analysis of the websites revealed that the top ranking universities captured these dimensions at varying degree. Besides, the UK-based university had better priority on website simplicity and negative space compared to the Malaysian-based university.
Keywords: Science and technology programs, top-ranked universities, online brands, university websites.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2292901 Analysis of Diverse Cluster Ensemble Techniques
Authors: S. Sarumathi, N. Shanthi, P. Ranjetha
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Data mining is the procedure of determining interesting patterns from the huge amount of data. With the intention of accessing the data faster the most supporting processes needed is clustering. Clustering is the process of identifying similarity between data according to the individuality present in the data and grouping associated data objects into clusters. Cluster ensemble is the technique to combine various runs of different clustering algorithms to obtain a general partition of the original dataset, aiming for consolidation of outcomes from a collection of individual clustering outcomes. The performances of clustering ensembles are mainly affecting by two principal factors such as diversity and quality. This paper presents the overview about the different cluster ensemble algorithm along with their methods used in cluster ensemble to improve the diversity and quality in the several cluster ensemble related papers and shows the comparative analysis of different cluster ensemble also summarize various cluster ensemble methods. Henceforth this clear analysis will be very useful for the world of clustering experts and also helps in deciding the most appropriate one to determine the problem in hand.Keywords: Cluster Ensemble, Consensus Function, CSPA, Diversity, HGPA, MCLA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1841900 Stability Analysis and Controller Design of Further Development of MIMOS II for Space Applications with Focus on the Extended Lyapunov Method: Part I
Authors: Mohammad Beyki, Justus Pawlak, Robert Patzke, Franz Renz
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In the context of planetary exploration, the MIMOS II (miniaturized M¨ossbauer spectrometer) serves as a proven and reliable measuring instrument. The transmission behaviour of the electronics in the M¨ossbauer spectroscopy is further developed and optimized. For this purpose, the overall electronics is split into three parts. This elaboration deals exclusively with the first part of the signal chain for the evaluation of photons in experiments with gamma radiation. Parallel to the analysis of the electronics, an additional method for analysing the stability of linear and non-linear systems is presented: The extended method of Lyapunov’s stability criteria. The design helps to weigh advantages and disadvantages against other simulated circuits in order to optimize the MIMOS II for the terestric and extraterestric measurment. Finally, after stability analysis, the controller design according to Ackermann is performed, achieving the best possible optimization of the output variable through a skillful pole assignment.
Keywords: Controller design for MIMOS II, stability analysis, M¨ossbauer spectroscopy, electronic signal amplifier, light processing technology, photocurrent, transimpedance amplifier, extended Lyapunov method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 49899 A Survey: Clustering Ensembles Techniques
Authors: Reza Ghaemi , Md. Nasir Sulaiman , Hamidah Ibrahim , Norwati Mustapha
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The clustering ensembles combine multiple partitions generated by different clustering algorithms into a single clustering solution. Clustering ensembles have emerged as a prominent method for improving robustness, stability and accuracy of unsupervised classification solutions. So far, many contributions have been done to find consensus clustering. One of the major problems in clustering ensembles is the consensus function. In this paper, firstly, we introduce clustering ensembles, representation of multiple partitions, its challenges and present taxonomy of combination algorithms. Secondly, we describe consensus functions in clustering ensembles including Hypergraph partitioning, Voting approach, Mutual information, Co-association based functions and Finite mixture model, and next explain their advantages, disadvantages and computational complexity. Finally, we compare the characteristics of clustering ensembles algorithms such as computational complexity, robustness, simplicity and accuracy on different datasets in previous techniques.Keywords: Clustering Ensembles, Combinational Algorithm, Consensus Function, Unsupervised Classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3449898 A Generic Approach to Achieve Optimal Server Consolidation by Using Existing Servers in Virtualized Data Center
Authors: Siyuan Jing, Kun She
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Virtualization-based server consolidation has been proven to be an ideal technique to solve the server sprawl problem by consolidating multiple virtualized servers onto a few physical servers leading to improved resource utilization and return on investment. In this paper, we solve this problem by using existing servers, which are heterogeneous and diversely preferred by IT managers. Five practical consolidation rules are introduced, and a decision model is proposed to optimally allocate source services to physical target servers while maximizing the average resource utilization and preference value. Our model can be regarded as a multi-objective multi-dimension bin-packing (MOMDBP) problem with constraints, which is strongly NP-hard. An improved grouping generic algorithm (GGA) is introduced for the problem. Extensive simulations were performed and the results are given.Keywords: GGA-based Heuristics, Preference, Real-worldConstraints, Resource Utilization, Server Consolidation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1647897 Novel Direct Flux and Torque Control of Optimally Designed 6 Phase Reluctance Machine with Special Current Waveform
Authors: E T. Rakgati, E. Matlotse
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In this paper the principle, basic torque theory and design optimisation of a six-phase reluctance dc machine are considered. A trapezoidal phase current waveform for the machine drive is proposed and evaluated to minimise ripple torque. Low cost normal laminated salient-pole rotors with and without slits and chamfered poles are investigated. The six-phase machine is optimised in multi-dimensions by linking the finite-element analysis method directly with an optimisation algorithm; the objective function is to maximise the torque per copper losses of the machine. The armature reaction effect is investigated in detail and found to be severe. The measured and calculated torque performances of a 35 kW optimum designed six-phase reluctance dc machine drive are presented.
Keywords: Reluctance dc machine, current waveform, design optimisation, finite element analysis, armature reaction effect.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1728896 A Distributed Approach to Extract High Utility Itemsets from XML Data
Authors: S. Kannimuthu, K. Premalatha
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This paper investigates a new data mining capability that entails mining of High Utility Itemsets (HUI) in a distributed environment. Existing research in data mining deals with only presence or absence of an items and do not consider the semantic measures like weight or cost of the items. Thus, HUI mining algorithm has evolved. HUI mining is the one kind of utility mining concept, aims to identify itemsets whose utility satisfies a given threshold. Although, the approach of mining HUIs in a distributed environment and mining of the same from XML data have not explored yet. In this work, a novel approach is proposed to mine HUIs from the XML based data in a distributed environment. This work utilizes Service Oriented Computing (SOC) paradigm which provides Knowledge as a Service (KaaS). The interesting patterns are provided via the web services with the help of knowledge server to answer the queries of the consumers. The performance of the approach is evaluated on various databases using execution time and memory consumption.
Keywords: Data mining, Knowledge as a Service, service oriented computing, utility mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2454895 A Combination of Similarity Ranking and Time for Social Research Paper Searching
Authors: P. Jomsri
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Nowadays social media are important tools for web resource discovery. The performance and capabilities of web searches are vital, especially search results from social research paper bookmarking. This paper proposes a new algorithm for ranking method that is a combination of similarity ranking with paper posted time or CSTRank. The paper posted time is static ranking for improving search results. For this particular study, the paper posted time is combined with similarity ranking to produce a better ranking than other methods such as similarity ranking or SimRank. The retrieval performance of combination rankings is evaluated using mean values of NDCG. The evaluation in the experiments implies that the chosen CSTRank ranking by using weight score at ratio 90:10 can improve the efficiency of research paper searching on social bookmarking websites.Keywords: combination ranking, information retrieval, time, similarity ranking, static ranking, weight score
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1666894 A Feasibility and Implementation Model of Small-Scale Hydropower Development for Rural Electrification in South Africa: Design Chart Development
Authors: Gideon J. Bonthuys, Marco van Dijk, Jay N. Bhagwan
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Small scale hydropower used to play a very important role in the provision of energy to urban and rural areas of South Africa. The national electricity grid, however, expanded and offered cheap, coal generated electricity and a large number of hydropower systems were decommissioned. Unfortunately, large numbers of households and communities will not be connected to the national electricity grid for the foreseeable future due to high cost of transmission and distribution systems to remote communities due to the relatively low electricity demand within rural communities and the allocation of current expenditure on upgrading and constructing of new coal fired power stations. This necessitates the development of feasible alternative power generation technologies. A feasibility and implementation model was developed to assist in designing and financially evaluating small-scale hydropower (SSHP) plants. Several sites were identified using the model. The SSHP plants were designed for the selected sites and the designs for the different selected sites were priced using pricing models (civil, mechanical and electrical aspects). Following feasibility studies done on the designed and priced SSHP plants, a feasibility analysis was done and a design chart developed for future similar potential SSHP plant projects. The methodology followed in conducting the feasibility analysis for other potential sites consisted of developing cost and income/saving formulae, developing net present value (NPV) formulae, Capital Cost Comparison Ratio (CCCR) and levelised cost formulae for SSHP projects for the different types of plant installations. It included setting up a model for the development of a design chart for a SSHP, calculating the NPV, CCCR and levelised cost for the different scenarios within the model by varying different parameters within the developed formulae, setting up the design chart for the different scenarios within the model and analyzing and interpreting results. From the interpretation of the develop design charts for feasible SSHP in can be seen that turbine and distribution line cost are the major influences on the cost and feasibility of SSHP. High head, short transmission line and islanded mini-grid SSHP installations are the most feasible and that the levelised cost of SSHP is high for low power generation sites. The main conclusion from the study is that the levelised cost of SSHP projects indicate that the cost of SSHP for low energy generation is high compared to the levelised cost of grid connected electricity supply; however, the remoteness of SSHP for rural electrification and the cost of infrastructure to connect remote rural communities to the local or national electricity grid provides a low CCCR and renders SSHP for rural electrification feasible on this basis.Keywords: Feasibility, cost, rural electrification, small-scale hydropower.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1084893 Power Generation Scheduling of Thermal Units Considering Gas Pipelines Constraints
Authors: Sara Mohtashami, Habib Rajabi Mashhadi
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With the growth of electricity generation from gas energy gas pipeline reliability can substantially impact the electric generation. A physical disruption to pipeline or to a compressor station can interrupt the flow of gas or reduce the pressure and lead to loss of multiple gas-fired electric generators, which could dramatically reduce the supplied power and threaten the power system security. Gas pressure drops during peak loading time on pipeline system, is a common problem in network with no enough transportation capacity which limits gas transportation and causes many problem for thermal domain power systems in supplying their demand. For a feasible generation scheduling planning in networks with no sufficient gas transportation capacity, it is required to consider gas pipeline constraints in solving the optimization problem and evaluate the impacts of gas consumption in power plants on gas pipelines operating condition. This paper studies about operating of gas fired power plants in critical conditions when the demand of gas and electricity peak together. An integrated model of gas and electric model is used to consider the gas pipeline constraints in the economic dispatch problem of gas-fueled thermal generator units. Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2142892 Market Segmentation and Conjoint Analysis for Apple Family Design
Authors: Abbas Al-Refaie, Nour Bata
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A distributor of Apple products' experiences numerous difficulties in developing marketing strategies for new and existing mobile product entries that maximize customer satisfaction and the firm's profitability. This research, therefore, integrates market segmentation in platform-based product family design and conjoint analysis to identify iSystem combinations that increase customer satisfaction and business profits. First, the enhanced market segmentation grid is created. Then, the estimated demand model is formulated. Finally, the profit models are constructed then used to determine the ideal product family design that maximizes profit. Conjoint analysis is used to explore customer preferences with their satisfaction levels. A total of 200 surveys are collected about customer preferences. Then, simulation is used to determine the importance values for each attribute. Finally, sensitivity analysis is conducted to determine the product family design that maximizes both objectives. In conclusion, the results of this research shall provide great support to Apple distributors in determining the best marketing strategies that enhance their market share.
Keywords: Market segmentation, conjoint analysis, market strategies, optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2518891 A New Technique for Solar Activity Forecasting Using Recurrent Elman Networks
Authors: Salvatore Marra, Francesco C. Morabito
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In this paper we present an efficient approach for the prediction of two sunspot-related time series, namely the Yearly Sunspot Number and the IR5 Index, that are commonly used for monitoring solar activity. The method is based on exploiting partially recurrent Elman networks and it can be divided into three main steps: the first one consists in a “de-rectification" of the time series under study in order to obtain a new time series whose appearance, similar to a sum of sinusoids, can be modelled by our neural networks much better than the original dataset. After that, we normalize the derectified data so that they have zero mean and unity standard deviation and, finally, train an Elman network with only one input, a recurrent hidden layer and one output using a back-propagation algorithm with variable learning rate and momentum. The achieved results have shown the efficiency of this approach that, although very simple, can perform better than most of the existing solar activity forecasting methods.
Keywords: Elman neural networks, sunspot, solar activity, time series prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1854890 MIMO Broadcast Scheduling for Weighted Sum-rate Maximization
Authors: Swadhin Kumar Mishra, Sidhartha Panda, C. Ardil
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Multiple-Input-Multiple-Output (MIMO) is one of the most important communication techniques that allow wireless systems to achieve higher data rate. To overcome the practical difficulties in implementing Dirty Paper Coding (DPC), various suboptimal MIMO Broadcast (MIMO-BC) scheduling algorithms are employed which choose the best set of users among all the users. In this paper we discuss such a sub-optimal MIMO-BC scheduling algorithm which employs antenna selection at the receiver side. The channels for the users considered here are not Identical and Independent Distributed (IID) so that users at the receiver side do not get equal opportunity for communication. So we introduce a method of applying weights to channels of the users which are not IID in such a way that each of the users gets equal opportunity for communication. The effect of weights on overall sum-rate achieved by the system has been investigated and presented.
Keywords: Antenna selection, Identical and Independent Distributed (IID), Sum-rate capacity, Weighted sum rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1590889 Portfolio Management: A Fuzzy Set Based Approach to Monitoring Size to Maximize Return and Minimize Risk
Authors: Margaret F. Shipley
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Fuzzy logic can be used when knowledge is incomplete or when ambiguity of data exists. The purpose of this paper is to propose a proactive fuzzy set- based model for reacting to the risk inherent in investment activities relative to a complete view of portfolio management. Fuzzy rules are given where, depending on the antecedents, the portfolio size may be slightly or significantly decreased or increased. The decision maker considers acceptable bounds on the proportion of acceptable risk and return. The Fuzzy Controller model allows learning to be achieved as 1) the firing strength of each rule is measured, 2) fuzzy output allows rules to be updated, and 3) new actions are recommended as the system continues to loop. An extension is given to the fuzzy controller that evaluates potential financial loss before adjusting the portfolio. An application is presented that illustrates the algorithm and extension developed in the paper.Keywords: Portfolio Management, Financial Market Monitoring, Fuzzy Controller, Fuzzy Logic,
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1853888 Avoiding Catastrophic Forgetting by a Dual-Network Memory Model Using a Chaotic Neural Network
Authors: Motonobu Hattori
Abstract:
In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.
Keywords: catastrophic forgetting, chaotic neural network, complementary learning systems, dual-network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2102887 Using a Semantic Self-Organising Web Page-Ranking Mechanism for Public Administration and Education
Authors: Marios Poulos, Sozon Papavlasopoulos, V. S. Belesiotis
Abstract:
In the proposed method for Web page-ranking, a novel theoretic model is introduced and tested by examples of order relationships among IP addresses. Ranking is induced using a convexity feature, which is learned according to these examples using a self-organizing procedure. We consider the problem of selforganizing learning from IP data to be represented by a semi-random convex polygon procedure, in which the vertices correspond to IP addresses. Based on recent developments in our regularization theory for convex polygons and corresponding Euclidean distance based methods for classification, we develop an algorithmic framework for learning ranking functions based on a Computational Geometric Theory. We show that our algorithm is generic, and present experimental results explaining the potential of our approach. In addition, we explain the generality of our approach by showing its possible use as a visualization tool for data obtained from diverse domains, such as Public Administration and Education.Keywords: Computational Geometry, Education, e-Governance, Semantic Web.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1756