Search results for: Task Scenarios
794 Dynamics Simulation Approach in Analyzing Pension Expenditure
Authors: Hasimah Sapiri, Anton Abdulbasah Kamil, Razman Mat Tahar, Hanafi Tumin
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Salary risk and demographic risk have been identified as main risks in analyzing pension expenditure particularly in Defined Benefit pension plan. Therefore, public pension plan in Malaysia is studied to analyze pension expenditure due to salary and demographic risk. Through the literature review and interview session with several officers in public sector, factors affecting pension expenditure are determined. Then, the inter-relationships between these factors are analyzed through causal loop diagram. The System Dynamics model is later developed using iThink software to show how demographic and salary changes affect the pension expenditure. Then, by using actual data, the impact of different policy scenarios on pension expenditure is analyzed. It is shown that dynamics simulation model of pension expenditure is useful to evaluate the impact of changes and policy decisions on risk particularly involving demographic and salary risk.Keywords: Demographic and Salary risk, Pension Expenditure, Public Policy, System Dynamics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2693793 Proposition of a Knowledge Management Approach Based on the Cloud Computing
Authors: Imane Chikhi, Hafida Abed
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The significant growth in the use of technologies in all life domains created numerous hurdles that derailed many knowledge management projects. Cloud computing choices are commencement to untangle these obstacles. Linking Cloud computing with knowledge management (KM) is a challenging task. Small amount of researches have been done regarding cloud computing and KM. In this paper, we consider Cloud-based KM as a new KM approach, and study the contribution of Cloud Computing to organizational KM. In fact, KM and cloud computing have many things in common, this similarity allows deriving very interesting features. Our approach is based on these features and focuses on the advantages of Cloud computing in the context of organizational KM. Finally, we highlight some challenges that have to be addressed when adopting a Cloud Computing approach to KM.
Keywords: Knowledge management, cloud computing, knowledge management approaches, cloud-based knowledge management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1403792 Simulation Study for Performance Comparison of Routing Protocols in Mobile Adhoc Network
Authors: Ahmad Anzaar, Husain Shahnawaz, Chand Mukesh, S. C. Gupta, R. Gowri, H. L. Mandoria
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Due to insufficient frequency band and tremendous growth of the mobile users, complex computation is needed for the use of resources. Long distance communication began with the introduction of telegraphs and simple coded pulses, which were used to transmit short messages. Since then numerous advances have rendered reliable transfer of information both easier and quicker. Wireless network refers to any type of computer network that is wireless, and is commonly associated with a telecommunications network whose interconnections between nodes is implemented without the use of wires. Wireless network can be broadly categorized in infrastructure network and infrastructure less network. Infrastructure network is one in which we have a base station to serve the mobile users and in the infrastructure less network is one in which no infrastructure is available to serve the mobile users this kind of networks are also known as mobile Adhoc networks. In this paper we have simulated the result for different scenarios with protocols like AODV and DSR; we simulated the result for throughput, delay and receiving traffic in the given scenario.
Keywords: Adhoc network, AODV, DSR. mobility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2092791 Control-flow Complexity Measurement of Processes and Weyuker's Properties
Authors: Jorge Cardoso
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Process measurement is the task of empirically and objectively assigning numbers to the properties of business processes in such a way as to describe them. Desirable attributes to study and measure include complexity, cost, maintainability, and reliability. In our work we will focus on investigating process complexity. We define process complexity as the degree to which a business process is difficult to analyze, understand or explain. One way to analyze a process- complexity is to use a process control-flow complexity measure. In this paper, an attempt has been made to evaluate the control-flow complexity measure in terms of Weyuker-s properties. Weyuker-s properties must be satisfied by any complexity measure to qualify as a good and comprehensive one.
Keywords: Business process measurement, workflow, complexity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2673790 Crude Oil Price Prediction Using LSTM Networks
Authors: Varun Gupta, Ankit Pandey
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Crude oil market is an immensely complex and dynamic environment and thus the task of predicting changes in such an environment becomes challenging with regards to its accuracy. A number of approaches have been adopted to take on that challenge and machine learning has been at the core in many of them. There are plenty of examples of algorithms based on machine learning yielding satisfactory results for such type of prediction. In this paper, we have tried to predict crude oil prices using Long Short-Term Memory (LSTM) based recurrent neural networks. We have tried to experiment with different types of models using different epochs, lookbacks and other tuning methods. The results obtained are promising and presented a reasonably accurate prediction for the price of crude oil in near future.
Keywords: Crude oil price prediction, deep learning, LSTM, recurrent neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3684789 Present and Future Climate Extreme Indices over Sinai Peninsula, Egypt
Authors: Mahmoud Roushdi, Hany Mostafa, Khaled Kheireldin
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Sinai Peninsula and Suez Canal Corridor are promising and important economic regions in Egypt due to the unique location and development opportunities. Thus, the climate change impacts should be assessed over the mentioned area. Accordingly, this paper aims to assess the climate extreme indices in through the last 35 year over Sinai Peninsula and Suez Canal Corridor in addition to predict the climate extreme indices up to 2100. Present and future climate indices were analyzed with using different RCP scenarios 4.5 and 8.5 from 2010 until 2100 for Sinai Peninsula and Suez Canal Corridor. Furthermore, both CanESM and HadGEM2 global circulation models were used. The results indicate that the number of summer days is predicted to increase, on the other hand the frost days is predicted to decrease. Moreover, it is noted a slight positive trend for the percentile of wet and extremely days R95p and R99p for RCP4.5 and negative trend for RCP8.5.
Keywords: Climate change, extreme indices, RCP, Sinai Peninsula.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1552788 Breast Cancer Prediction Using Score-Level Fusion of Machine Learning and Deep Learning Models
Authors: [email protected]
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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data need a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM), ensemble learning with hyper parameters optimization, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.
Keywords: Machine learning, Deep learning, cancer prediction, breast cancer, LSTM, Score-Level Fusion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 367787 Efficiency of Different GLR Test-statistics for Spatial Signal Detection
Authors: Olesya Bolkhovskaya, Alexander Maltsev
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In this work the characteristics of spatial signal detec¬tion from an antenna array in various sample cases are investigated. Cases for a various number of available prior information about the received signal and the background noise are considered. The spatial difference between a signal and noise is only used. The performance characteristics and detecting curves are presented. All test-statistics are obtained on the basis of the generalized likelihood ratio (GLR). The received results are correct for a short and long sample.
Keywords: GLR test-statistic, detection task, generalized likelihood ratio, antenna array, detection curves, performance characteristics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1509786 Digital Individual Benefit Statement: The Use of a Triangulation Methodology to Design a Digital Platform for Switzerland
Authors: Catherine Equey Balzli
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Old age retirement pensions are an important concern among the Swiss but estimating one’s income after retirement is difficult due to the Swiss insurance system’s complexity. This project’s aim is to prepare for developing a digital platform that will allow individuals to plan for retirement in a simplified manner. The main objective of the platform will be to give individuals the tools to check that their savings and retirement benefits will allow them to continue the lifestyle to which they are accustomed once they are retired. The research results from qualitative (focus group) and quantitative (survey) methodologies, recommend the scope and functionalities for a digital platform to be developed. A main outcome is the need to limit the platform’s scope to old-age pension only (excluding survivors’ or disability pensions, for instance). Furthermore, an outcome regarding the functionalities is the proposition of scenarios such as early retirement, changes to income, or modifications to personal status. The development of the digital platform will be a subsequent project.
Keywords: Benefit statement, digital platform, retirement financial planning, social insurances.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 566785 Double Clustering as an Unsupervised Approach for Order Picking of Distributed Warehouses
Authors: Hsin-Yi Huang, Ming-Sheng Liu, Jiun-Yan Shiau
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Planning the order picking lists for warehouses to achieve some operational performances is a significant challenge when the costs associated with logistics are relatively high, and it is especially important in e-commerce era. Nowadays, many order planning techniques employ supervised machine learning algorithms. However, to define features for supervised machine learning algorithms is not a simple task. Against this background, we consider whether unsupervised algorithms can enhance the planning of order-picking lists. A double zone picking approach, which is based on using clustering algorithms twice, is developed. A simplified example is given to demonstrate the merit of our approach.
Keywords: order picking, warehouse, clustering, unsupervised learning
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 490784 Vr-GIS and Ar-GIS In Education: A Case Study
Authors: Ilario Gabriele Gerloni, Vincenza Carchiolo, Alessandro Longheu, Ugo Becciani, Eva Sciacca, Fabio Vitello
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ICT tools and platforms endorse more and more educational process. Many models and techniques for people to be educated and trained about specific topics and skills do exist, as classroom lectures with textbooks, computers, handheld devices and others. The choice to what extent ICT is applied within learning contexts is related to personal access to technologies as well as to the infrastructure surrounding environment. Among recent techniques, the adoption of Virtual Reality (VR) and Augmented Reality (AR) provides significant impulse in fully engaging users senses. In this paper, an application of AR/VR within Geographic Information Systems (GIS) context is presented. It aims to provide immersive environment experiences for educational and training purposes (e.g. for civil protection personnel), useful especially for situations where real scenarios are not easily accessible by humans. First acknowledgments are promising for building an effective tool that helps civil protection personnel training with risk reduction.Keywords: Education, virtual reality, augmented reality, civil protection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 900783 A Self Configuring System for Object Recognition in Color Images
Authors: Michela Lecca
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System MEMORI automatically detects and recognizes rotated and/or rescaled versions of the objects of a database within digital color images with cluttered background. This task is accomplished by means of a region grouping algorithm guided by heuristic rules, whose parameters concern some geometrical properties and the recognition score of the database objects. This paper focuses on the strategies implemented in MEMORI for the estimation of the heuristic rule parameters. This estimation, being automatic, makes the system a highly user-friendly tool.
Keywords: Automatic object recognition, clustering, content based image retrieval system, image segmentation, region adjacency graph, region grouping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1392782 Improving the Quality of Transport Management Services with Fuzzy Signatures
Authors: Csaba I. Hencz, István Á. Harmati
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Nowadays the significance of road transport is gradually increasing. All transport companies are working in the same external environment where the speed of transport is defined by traffic rules. The main objective is to accelerate the speed of service and it is only dependent on the individual abilities of the managing members. These operational control units make decisions quickly (in a typically experiential and/or intuitive way). For this reason, support for these decisions is an important task. Our goal is to create a decision support model based on fuzzy signatures that can assist the work of operational management automatically. If the model sets parameters properly, the management of transport could be more economical and efficient.
Keywords: Freight transport, decision support, information handling, fuzzy methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 804781 Performance Evaluation of XMAC and BMAC Routing Protocol under Static and Mobility Scenarios in Wireless Sensor Network
Authors: M. V. Ramana Rao, T. Adilakshmi
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Based on application requirements, nodes are static or mobile in Wireless Sensor Networks (WSNs). Mobility poses challenges in protocol design, especially at the link layer requiring mobility adaptation algorithms to localize mobile nodes and predict link quality to be established with them. This study implements XMAC and Berkeley Media Access Control (BMAC) routing protocols to evaluate performance under WSN’s static and mobility conditions. This paper gives a comparative study of mobility-aware MAC protocols. Routing protocol performance, based on Average End to End Delay, Average Packet Delivery Ratio, Average Number of hops, and Jitter is evaluated.Keywords: Wireless Sensor Network (WSN), Medium Access Control (MAC), Berkeley Media Access Control (BMAC), mobility.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2371780 Investments Attractiveness via Combinatorial Optimization Ranking
Authors: Ivan C. Mustakerov, Daniela I. Borissova
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The paper proposes an approach to ranking a set of potential countries to invest taking into account the investor point of view about importance of different economic indicators. For the goal, a ranking algorithm that contributes to rational decision making is proposed. The described algorithm is based on combinatorial optimization modeling and repeated multi-criteria tasks solution. The final result is list of countries ranked in respect of investor preferences about importance of economic indicators for investment attractiveness. Different scenarios are simulated conforming to different investors preferences. A numerical example with real dataset of indicators is solved. The numerical testing shows the applicability of the described algorithm. The proposed approach can be used with any sets of indicators as ranking criteria reflecting different points of view of investors.
Keywords: Combinatorial optimization modeling, economics investment attractiveness, economics ranking algorithm, multi-criteria problems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2092779 The Fiscal and Macroeconomic Impacts of Reforming Energy Subsidy Policy in Malaysia
Authors: Nora Yusma Bte Mohamed Yusoff, Hussain Ali Bekhet
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The rationalization of a gradual subsidies reforms plan has been set out by the Malaysian government to achieve the high-income nation target. This paper attempts to analyze the impacts of energy subsidy reform policy on fiscal deficit and macroeconomics variables in Malaysia. The Computable General Equilibrium (CGE) Model is employed. Three simulations based on different groups of scenarios have been developed. Importantly, the overall results indicate that removal of fuel subsidy has significantly improved the real GDP and reduced the government fiscal deficit. On the other hand, the removal of the fuel subsidy has increased most of the local commodity prices, especially energy commodities. The findings of the study could provide some imperative inputs for policy makers, especially to identify the right policy mechanism. This is especially ensures the subsidy savings from subsidy removal could be transferred back into the domestic economy in the form of infrastructure development, compensation and increases in others sector output contributions towards a sustainable economic growth.Keywords: CGE, deficit, energy, reform, subsidy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1043778 Acquiring Contour Following Behaviour in Robotics through Q-Learning and Image-based States
Authors: Carlos V. Regueiro, Jose E. Domenech, Roberto Iglesias, Jose L. Correa
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In this work a visual and reactive contour following behaviour is learned by reinforcement. With artificial vision the environment is perceived in 3D, and it is possible to avoid obstacles that are invisible to other sensors that are more common in mobile robotics. Reinforcement learning reduces the need for intervention in behaviour design, and simplifies its adjustment to the environment, the robot and the task. In order to facilitate its generalisation to other behaviours and to reduce the role of the designer, we propose a regular image-based codification of states. Even though this is much more difficult, our implementation converges and is robust. Results are presented with a Pioneer 2 AT on a Gazebo 3D simulator.Keywords: Image-based State Codification, Mobile Robotics, ReinforcementLearning, Visual Behaviour.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1591777 Automatic Recognition of an Unknown and Time-Varying Number of Simultaneous Environmental Sound Sources
Authors: S. Ntalampiras, I. Potamitis, N. Fakotakis, S. Kouzoupis
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The present work faces the problem of automatic enumeration and recognition of an unknown and time-varying number of environmental sound sources while using a single microphone. The assumption that is made is that the sound recorded is a realization of sound sources belonging to a group of audio classes which is known a-priori. We describe two variations of the same principle which is to calculate the distance between the current unknown audio frame and all possible combinations of the classes that are assumed to span the soundscene. We concentrate on categorizing environmental sound sources, such as birds, insects etc. in the task of monitoring the biodiversity of a specific habitat.
Keywords: automatic recognition of multiple sound sources, enumeration of sound sources, computational ecology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1544776 Uncertainty of the Brazilian Earth System Model for Solar Radiation
Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Deivid Pires, Rafael Haag, Elton Gimenez Rossini
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This study evaluated the uncertainties involved in the solar radiation projections generated by the Brazilian Earth System Model (BESM) of the Weather and Climate Prediction Center (CPTEC) belonging to Coupled Model Intercomparison Phase 5 (CMIP5), with the aim of identifying efficiency in the projections for solar radiation of said model and in this way establish the viability of its use. Two different scenarios elaborated by Intergovernmental Panel on Climate Change (IPCC) were evaluated: RCP 4.5 (with more optimistic contour conditions) and 8.5 (with more pessimistic initial conditions). The method used to verify the accuracy of the present model was the Nash coefficient and the Statistical bias, as it better represents these atmospheric patterns. The BESM showed a tendency to overestimate the data of solar radiation projections in most regions of the state of Rio Grande do Sul and through the validation methods adopted by this study, BESM did not present a satisfactory accuracy.
Keywords: Climate changes, projections, solar radiation, uncertainty.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 978775 MNECLIB2 – A Classical Music Digital Library
Authors: Zoran Constantinescu, Monica Vlâdoiu
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Lately there has been a significant boost of interest in music digital libraries, which constitute an attractive area of research and development due to their inherent interesting issues and challenging technical problems, solutions to which will be highly appreciated by enthusiastic end-users. We present here a DL that we have developed to support users in their quest for classical music pieces within a particular collection of 18,000+ audio recordings. To cope with the early DL model limitations, we have used a refined socio-semantic and contextual model that allows rich bibliographic content description, along with semantic annotations, reviewing, rating, knowledge sharing etc. The multi-layered service model allows incorporation of local and distributed information, construction of rich hypermedia documents, expressing the complex relationships between various objects and multi-dimensional spaces, agents, actors, services, communities, scenarios etc., and facilitates collaborative activities to offer to individual users the needed collections and services.Keywords: audio recordings, music metadata, music digitallibrary, socio-semantic model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1641774 On Decomposition of Maximal Prefix Codes
Authors: Nikolai Krainiukov, Boris Melnikov
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We study the properties of maximal prefix codes. The codes have many applications in computer science, theory of formal languages, data processing and data classification. Our approaches to study use finite state automata (so-called flower automata) for the representation of prefix codes. An important task is the decomposition of prefix codes into prime prefix codes (factors). We discuss properties of such prefix code decompositions. A linear time algorithm is designed to find the prime decomposition. We used the GAP computer algebra system, which allows us to perform algebraic operations for free semigroups, monoids and automata.
Keywords: Maximal prefix code, regular languages, flower automata, prefix code decomposing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13773 A Weighted Approach to Unconstrained Iris Recognition
Authors: Yao-Hong Tsai
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This paper presents a weighted approach to unconstrained iris recognition. In nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.
Keywords: Authentication, iris recognition, Adaboost, local binary pattern.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1926772 Efficient Feature Fusion for Noise Iris in Unconstrained Environment
Authors: Yao-Hong Tsai
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This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.
Keywords: Image fusion, iris recognition, local binary pattern, wavelet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2203771 An Efficient and Secure Solution for the Problems of ARP Cache Poisoning Attacks
Authors: Md. Ataullah, Naveen Chauhan
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The Address Resolution Protocol (ARP) is used by computers to map logical addresses (IP) to physical addresses (MAC). However ARP is an all trusting protocol and is stateless which makes it vulnerable to many ARP cache poisoning attacks such as Man-in-the-Middle (MITM) and Denial of service (DoS) attacks. These flaws result in security breaches thus weakening the appeal of the computer for exchange of sensitive data. In this paper we describe ARP, outline several possible ARP cache poisoning attacks and give the detailed of some attack scenarios in network having both wired and wireless hosts. We have analyzed each of proposed solutions, identify their strengths and limitations. Finally get that no solution offers a feasible solution. Hence, this paper presents an efficient and secure version of ARP that is able to cope up with all these types of attacks and is also a feasible solution. It is a stateful protocol, by storing the information of the Request frame in the ARP cache, to reduce the chances of various types of attacks in ARP. It is more efficient and secure by broadcasting ARP Reply frame in the network and storing related entries in the ARP cache each time when communication take place.Keywords: ARP cache poisoning, MITM, DoS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2910770 Best Option for Countercyclical Capital Buffer Implementation - Scenarios for Baltic States
Authors: Ģirts Brasliņš, Ilja Arefjevs, Nadežda Tarakanova
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The objective of countercyclical capital buffer is to encourage banks to build up buffers in good times that can be drawn down in bad times. The aim of the report is to assess such decisions by banks derived from three approaches. The approaches are the aggregate credit-to-GDP ratio, credit growth as well as banking sector profits. The approaches are implemented for Estonia, Latvia and Lithuania for the time period 2000-2012. The report compares three approaches and analyses their relevance to the Baltic States by testing the correlation between a growth in studied variables and a growth of corresponding gaps. Methods used in the empirical part of the report are econometric analysis as well as economic analysis, development indicators, relative and absolute indicators and other methods. The research outcome is a cross-Baltic comparison of two alternative approaches to establish or release a countercyclical capital buffer by banks and their implications for each Baltic country.
Keywords: Basel III, countercyclical capital buffer, banks, credit growth, Baltic States.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1863769 ECG Analysis using Nature Inspired Algorithm
Authors: A.Sankara Subramanian, G.Gurusamy, G.Selvakumar, P.Gnanasekar, A.Nagappan
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This paper presents an algorithm based on the wavelet decomposition, for feature extraction from the ECG signal and recognition of three types of Ventricular Arrhythmias using neural networks. A set of Discrete Wavelet Transform (DWT) coefficients, which contain the maximum information about the arrhythmias, is selected from the wavelet decomposition. After that a novel clustering algorithm based on nature inspired algorithm (Ant Colony Optimization) is developed for classifying arrhythmia types. The algorithm is applied on the ECG registrations from the MIT-BIH arrhythmia and malignant ventricular arrhythmia databases. We applied Daubechies 4 wavelet in our algorithm. The wavelet decomposition enabled us to perform the task efficiently and produced reliable results.Keywords: Daubechies 4 Wavelet, ECG, Nature inspired algorithm, Ventricular Arrhythmias, Wavelet Decomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2293768 Genetic-Fuzzy Inverse Controller for a Robot Arm Suitable for On Line Applications
Authors: Abduladheem A. Ali, Easa A. Abd
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The robot is a repeated task plant. The control of such a plant under parameter variations and load disturbances is one of the important problems. The aim of this work is to design Geno-Fuzzy controller suitable for online applications to control single link rigid robot arm plant. The genetic-fuzzy online controller (indirect controller) has two genetic-fuzzy blocks, the first as controller, the second as identifier. The identification method is based on inverse identification technique. The proposed controller it tested in normal and load disturbance conditions.Keywords: Fuzzy network, genetic algorithm, robot control, online genetic control, parameter identification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1447767 Performance Evaluation of Content Based Image Retrieval Using Indexed Views
Authors: Tahir Iqbal, Mumtaz Ali, Syed Wajahat Kareem, Muhammad Harris
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Digital information is expanding in exponential order in our life. Information that is residing online and offline are stored in huge repositories relating to every aspect of our lives. Getting the required information is a task of retrieval systems. Content based image retrieval (CBIR) is a retrieval system that retrieves the required information from repositories on the basis of the contents of the image. Time is a critical factor in retrieval system and using indexed views with CBIR system improves the time efficiency of retrieved results.
Keywords: Content based image retrieval (CBIR), Indexed view, Color, Image retrieval, Cross correlation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1843766 Low-Cost and Highly Accurate Motion Models for Three-Dimensional Local Landmark-based Autonomous Navigation
Authors: Gheorghe Galben, Daniel N. Aloi
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Recently, the Spherical Motion Models (SMM-s) have been introduced [1]. These new models have been developed for 3D local landmark-base Autonomous Navigation (AN). This paper is revealing new arguments and experimental results to support the SMM-s characteristics. The accuracy and the robustness in performing a specific task are the main concerns of the new investigations. To analyze their performances of the SMM-s, the most powerful tools of estimation theory, the extended Kalman filter (EKF) and unscented Kalman filter (UKF), which give the best estimations in noisy environments, have been employed. The Monte Carlo validation implementations used to test the stability and robustness of the models have been employed as well.
Keywords: Autonomous navigation, extended kalman filter, unscented kalman filter, localization algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1303765 Process Modeling of Electric Discharge Machining of Inconel 825 Using Artificial Neural Network
Authors: Himanshu Payal, Sachin Maheshwari, Pushpendra S. Bharti
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Electrical discharge machining (EDM), a non-conventional machining process, finds wide applications for shaping difficult-to-cut alloys. Process modeling of EDM is required to exploit the process to the fullest. Process modeling of EDM is a challenging task owing to involvement of so many electrical and non-electrical parameters. This work is an attempt to model the EDM process using artificial neural network (ANN). Experiments were carried out on die-sinking EDM taking Inconel 825 as work material. ANN modeling has been performed using experimental data. The prediction ability of trained network has been verified experimentally. Results indicate that ANN can predict the values of performance measures of EDM satisfactorily.Keywords: Artificial neural network, EDM, metal removal rate, modeling, surface roughness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1149