Search results for: Unmanned Intervention Algorithm.
576 Ensuring Data Security and Consistency in FTIMA - A Fault Tolerant Infrastructure for Mobile Agents
Authors: Umar Manzoor, Kiran Ijaz, Wajiha Shamim, Arshad Ali Shahid
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Transaction management is one of the most crucial requirements for enterprise application development which often require concurrent access to distributed data shared amongst multiple application / nodes. Transactions guarantee the consistency of data records when multiple users or processes perform concurrent operations. Existing Fault Tolerance Infrastructure for Mobile Agents (FTIMA) provides a fault tolerant behavior in distributed transactions and uses multi-agent system for distributed transaction and processing. In the existing FTIMA architecture, data flows through the network and contains personal, private or confidential information. In banking transactions a minor change in the transaction can cause a great loss to the user. In this paper we have modified FTIMA architecture to ensure that the user request reaches the destination server securely and without any change. We have used triple DES for encryption/ decryption and MD5 algorithm for validity of message.Keywords: Distributed Transaction, Security, Mobile Agents, FTIMA Architecture.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1525575 Information Gain Ratio Based Clustering for Investigation of Environmental Parameters Effects on Human Mental Performance
Authors: H. Mehdi, Kh. S. Karimov, A. A. Kavokin
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Methods of clustering which were developed in the data mining theory can be successfully applied to the investigation of different kinds of dependencies between the conditions of environment and human activities. It is known, that environmental parameters such as temperature, relative humidity, atmospheric pressure and illumination have significant effects on the human mental performance. To investigate these parameters effect, data mining technique of clustering using entropy and Information Gain Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of clusters. It is shown that the information gain ratio (IGR) grows monotonically and simultaneously with degree of connectivity between two variables. This approach has some preferences if compared, for example, with correlation analysis due to relatively smaller sensitivity to shape of functional dependencies. Variant of an algorithm to implement the proposed method with some analysis of above problem of environmental effects is also presented. It was shown that proposed method converges with finite number of steps.Keywords: Clustering, Correlation analysis, EnvironmentalParameters, Information Gain Ratio, Mental Performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1824574 Experimental Results about the Dynamics of the Generalized Belief Propagation Used on LDPC Codes
Authors: Jean-Christophe Sibel, Sylvain Reynal, David Declercq
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In the context of channel coding, the Generalized Belief Propagation (GBP) is an iterative algorithm used to recover the transmission bits sent through a noisy channel. To ensure a reliable transmission, we apply a map on the bits, that is called a code. This code induces artificial correlations between the bits to send, and it can be modeled by a graph whose nodes are the bits and the edges are the correlations. This graph, called Tanner graph, is used for most of the decoding algorithms like Belief Propagation or Gallager-B. The GBP is based on a non unic transformation of the Tanner graph into a so called region-graph. A clear advantage of the GBP over the other algorithms is the freedom in the construction of this graph. In this article, we explain a particular construction for specific graph topologies that involves relevant performance of the GBP. Moreover, we investigate the behavior of the GBP considered as a dynamic system in order to understand the way it evolves in terms of the time and in terms of the noise power of the channel. To this end we make use of classical measures and we introduce a new measure called the hyperspheres method that enables to know the size of the attractors.
Keywords: iterative decoder, LDPC, region-graph, chaos.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1648573 BasWilCalc – Basket Willow (Salix viminalis) Biomass Yield Calculator
Authors: Wiesław Szulczewski, Wojciech Jakubowski, Andrzej Żyromski, Małgorzata Biniak-Pieróg
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The aim of the paper was to elaborate a novel calculator BasWilCalc, that allows to estimate the actual amount of biomass on the basket willow plantations. The proposed method is based on the results of field experiment conducted during years 2011-2013 on basket willow plantation in the south-western part of Poland. As input data the results of destructive measurements of the diameter, length and weight of willow stems and non-destructive biometric measurements of diameter in the middle of stems and their length during the growing season performed at weekly intervals were used. Performed analysis enabled to develop the algorithm which, due to the fact that energy plantations are of known and constant planting structure, allows to estimate the actual amount of willow basket biomass on the plantation with a given probability and accuracy specified by the model, based on the number of stems measured and the age of the plantation.
Keywords: Basket willow (Salix viminalis) biomass, biometric measurements, yield, biomass calculator.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1667572 Adaptive Network Intrusion Detection Learning: Attribute Selection and Classification
Authors: Dewan Md. Farid, Jerome Darmont, Nouria Harbi, Nguyen Huu Hoa, Mohammad Zahidur Rahman
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In this paper, a new learning approach for network intrusion detection using naïve Bayesian classifier and ID3 algorithm is presented, which identifies effective attributes from the training dataset, calculates the conditional probabilities for the best attribute values, and then correctly classifies all the examples of training and testing dataset. Most of the current intrusion detection datasets are dynamic, complex and contain large number of attributes. Some of the attributes may be redundant or contribute little for detection making. It has been successfully tested that significant attribute selection is important to design a real world intrusion detection systems (IDS). The purpose of this study is to identify effective attributes from the training dataset to build a classifier for network intrusion detection using data mining algorithms. The experimental results on KDD99 benchmark intrusion detection dataset demonstrate that this new approach achieves high classification rates and reduce false positives using limited computational resources.Keywords: Attributes selection, Conditional probabilities, information gain, network intrusion detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2699571 Renovation Planning Model for a Shopping Mall
Authors: Hsin-Yun Lee
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In this study, the pedestrian simulation VISWALK integration and application platform ant algorithms written program made to construct a renovation engineering schedule planning mode. The use of simulation analysis platform construction site when the user running the simulation, after calculating the user walks in the case of construction delays, the ant algorithm to find out the minimum delay time schedule plan, and add volume and unit area deactivated loss of business computing, and finally to the owners and users of two different positions cut considerations pick out the best schedule planning. To assess and validate its effectiveness, this study constructed the model imported floor of a shopping mall floor renovation engineering cases. Verify that the case can be found from the mode of the proposed project schedule planning program can effectively reduce the delay time and the user's walking mall loss of business, the impact of the operation on the renovation engineering facilities in the building to a minimum.Keywords: Pedestrian, renovation, schedule, simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2331570 Spatial-Temporal Awareness Approach for Extensive Re-Identification
Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush
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Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.
Keywords: Long-short-term memory, re-identification, security critical application, spatial-temporal awareness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 533569 Security Architecture for At-Home Medical Care Using Sensor Network
Authors: S.S.Mohanavalli, Sheila Anand
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This paper proposes a novel architecture for At- Home medical care which enables senior citizens, patients with chronic ailments and patients requiring post- operative care to be remotely monitored in the comfort of their homes. This architecture is implemented using sensors and wireless networking for transmitting patient data to the hospitals, health- care centers for monitoring by medical professionals. Patients are equipped with sensors to measure their physiological parameters, like blood pressure, pulse rate etc. and a Wearable Data Acquisition Unit is used to transmit the patient sensor data. Medical professionals can be alerted to any abnormal variations in these values for diagnosis and suitable treatment. Security threats and challenges inherent to wireless communication and sensor network have been discussed and a security mechanism to ensure data confidentiality and source authentication has been proposed. Symmetric key algorithm AES has been used for encrypting the data and a patent-free, two-pass block cipher mode CCFB has been used for implementing semantic security.Keywords: data confidentiality, integrity, remotemonitoring, source authentication
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1742568 Low-Latency and Low-Overhead Path Planning for In-band Network-Wide Telemetry
Authors: Penghui Zhang, Hua Zhang, Jun-Bo Wang, Cheng Zeng, Zijian Cao
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With the development of software-defined networks and programmable data planes, in-band network telemetry (INT) has become an emerging technology in communications because it can get accurate and real-time network information. However, due to the expansion of the network scale, existing telemetry systems, to the best of the authors’ knowledge, have difficulty in meeting the common requirements of low overhead, low latency and full coverage for traffic measurement. This paper proposes a network-wide telemetry system with a low-latency low-overhead path planning (INT-LLPP). This paper builds a mathematical model to analyze the telemetry overhead and latency of INT systems. Then, we adopt a greedy-based path planning algorithm to reduce the overhead and latency of the network telemetry with the full network coverage. The simulation results show that network-wide telemetry is achieved and the telemetry overhead can be reduced significantly compared with existing INT systems. INT-LLPP can control the system latency to get real-time network information.
Keywords: Network telemetry, network monitoring, path planning, low latency.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 256567 Genetic Folding: Analyzing the Mercer-s Kernels Effect in Support Vector Machine using Genetic Folding
Authors: Mohd A. Mezher, Maysam F. Abbod
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Genetic Folding (GF) a new class of EA named as is introduced for the first time. It is based on chromosomes composed of floating genes structurally organized in a parent form and separated by dots. Although, the genotype/phenotype system of GF generates a kernel expression, which is the objective function of superior classifier. In this work the question of the satisfying mapping-s rules in evolving populations is addressed by analyzing populations undergoing either Mercer-s or none Mercer-s rule. The results presented here show that populations undergoing Mercer-s rules improve practically models selection of Support Vector Machine (SVM). The experiment is trained multi-classification problem and tested on nonlinear Ionosphere dataset. The target of this paper is to answer the question of evolving Mercer-s rule in SVM addressed using either genetic folding satisfied kernel-s rules or not applied to complicated domains and problems.Keywords: Genetic Folding, GF, Evolutionary Algorithms, Support Vector Machine, Genetic Algorithm, Genetic Programming, Multi-Classification, Mercer's Rules
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1627566 The Effectiveness of Teaching Games for the Improvement of the Hockey Tactical Skills and the State of Self-Confidence among 16 Years Old Students
Authors: Wee A. S. S. Lee, S. Rengasamy, Lim Boon Hooi, C. Varatharajoo, M. Ibrahim K. Azeez
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This study was conducted to examine the effectiveness of Teaching Games For Understanding (TGFU) in improving the hockey tactical skills and state self-confidence among 16-year-old students. Two hundred fifty-nine (259) school students were selected for the study based on the intact sampling method. One class was used as the control group (Boys=60, Girls=70), while another as the treatment group (Boys=60, Girls=69) underwent intervention with TGFU in physical education class conducted twice a week for four weeks. The Games Performance Assessment Instrument was used to observe the hockey tactical skills and The State Self-Confidence Inventory was used to determine the state of self-confidence among the students. After four weeks, ANCOVA analysis indicated the treatment groups had significant improvement in hockey tactical skills with F (1, 118) =313.37, p<.05 for school boys, and F (1, 136) =92.62, p<.05 for school girls. The MannWhitney U test also showed the treatment groups had significant improvement in state self-confidence with U=428.50, z= -7.22, p < .05, r=.06 for school boys. ANCOVA analysis also showed the treatment group had significant improvement in state self-confidence with F (1, 136) =74.40, p<.05 for school girls. This indicates that TGFU in a 40-minute physical education class conducted twice a week for four weeks can significantly improve the hockey tactical skills and state self-confidence among 16-year-old students. The findings give new knowledge to PE teachers to implement the TGFU method as it enhances the hockey tactical skills and state selfconfidence among 16-year-old students. Some recommendation was suggested for future research.
Keywords: Hockey tactical skills, state self-confidence, teaching games for understanding, traditional teaching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2426565 Accuracy of Displacement Estimation and Selection of Capacitors for a Four Degrees of Freedom Capacitive Force Sensor
Authors: Chisato Murakami, Makoto Takahashi
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Force sensor has been used as requisite for knowing information on the amount and the directions of forces on the skin surface. We have developed a four-degrees-of-freedom capacitive force sensor (approximately 20×20×5 mm3) that has a flexible structure and sixteen parallel plate capacitors. An iterative algorithm was developed for estimating four displacements from the sixteen capacitances using fourth-order polynomial approximation of characteristics between capacitance and displacement. The estimation results from measured capacitances had large error caused by deterioration of the characteristics. In this study, effective capacitors had major information were selected on the basis of the capacitance change range and the characteristic shape. Maximum errors in calibration and non-calibration points were 25%and 6.8%.However the maximum error was larger than desired value, the smallness of averaged value indicated the occurrence of a few large error points. On the other hand, error in non-calibration point was within desired value.
Keywords: Force sensors, capacitive sensors, estimation, iterative algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1616564 High Secure Data Hiding Using Cropping Image and Least Significant Bit Steganography
Authors: Khalid A. Al-Afandy, El-Sayyed El-Rabaie, Osama Salah, Ahmed El-Mhalaway
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This paper presents a high secure data hiding technique using image cropping and Least Significant Bit (LSB) steganography. The predefined certain secret coordinate crops will be extracted from the cover image. The secret text message will be divided into sections. These sections quantity is equal the image crops quantity. Each section from the secret text message will embed into an image crop with a secret sequence using LSB technique. The embedding is done using the cover image color channels. Stego image is given by reassembling the image and the stego crops. The results of the technique will be compared to the other state of art techniques. Evaluation is based on visualization to detect any degradation of stego image, the difficulty of extracting the embedded data by any unauthorized viewer, Peak Signal-to-Noise Ratio of stego image (PSNR), and the embedding algorithm CPU time. Experimental results ensure that the proposed technique is more secure compared with the other traditional techniques.
Keywords: Steganography, stego, LSB, crop.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1553563 A Bi-Objective Model for Location-Allocation Problem within Queuing Framework
Authors: Amirhossein Chambari, Seyed Habib Rahmaty, Vahid Hajipour, Aida Karimi
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This paper proposes a bi-objective model for the facility location problem under a congestion system. The idea of the model is motivated by applications of locating servers in bank automated teller machines (ATMS), communication networks, and so on. This model can be specifically considered for situations in which fixed service facilities are congested by stochastic demand within queueing framework. We formulate this model with two perspectives simultaneously: (i) customers and (ii) service provider. The objectives of the model are to minimize (i) the total expected travelling and waiting time and (ii) the average facility idle-time. This model represents a mixed-integer nonlinear programming problem which belongs to the class of NP-hard problems. In addition, to solve the model, two metaheuristic algorithms including nondominated sorting genetic algorithms (NSGA-II) and non-dominated ranking genetic algorithms (NRGA) are proposed. Besides, to evaluate the performance of the two algorithms some numerical examples are produced and analyzed with some metrics to determine which algorithm works better.Keywords: Queuing, Location, Bi-objective, NSGA-II, NRGA
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2277562 Journey on Image Clustering Based on Color Composition
Authors: Achmad Nizar Hidayanto, Elisabeth Martha Koeanan
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Image clustering is a process of grouping images based on their similarity. The image clustering usually uses the color component, texture, edge, shape, or mixture of two components, etc. This research aims to explore image clustering using color composition. In order to complete this image clustering, three main components should be considered, which are color space, image representation (feature extraction), and clustering method itself. We aim to explore which composition of these factors will produce the best clustering results by combining various techniques from the three components. The color spaces use RGB, HSV, and L*a*b* method. The image representations use Histogram and Gaussian Mixture Model (GMM), whereas the clustering methods use KMeans and Agglomerative Hierarchical Clustering algorithm. The results of the experiment show that GMM representation is better combined with RGB and L*a*b* color space, whereas Histogram is better combined with HSV. The experiments also show that K-Means is better than Agglomerative Hierarchical for images clustering.Keywords: Image clustering, feature extraction, RGB, HSV, L*a*b*, Gaussian Mixture Model (GMM), histogram, Agglomerative Hierarchical Clustering (AHC), K-Means, Expectation-Maximization (EM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2206561 Model of Transhipment and Routing Applied to the Cargo Sector in Small and Medium Enterprises of Bogotá, Colombia
Authors: Oscar Javier Herrera Ochoa, Ivan Dario Romero Fonseca
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This paper presents a design of a model for planning the distribution logistics operation. The significance of this work relies on the applicability of this fact to the analysis of small and medium enterprises (SMEs) of dry freight in Bogotá. Two stages constitute this implementation: the first one is the place where optimal planning is achieved through a hybrid model developed with mixed integer programming, which considers the transhipment operation based on a combined load allocation model as a classic transshipment model; the second one is the specific routing of that operation through the heuristics of Clark and Wright. As a result, an integral model is obtained to carry out the step by step planning of the distribution of dry freight for SMEs in Bogotá. In this manner, optimum assignments are established by utilizing transshipment centers with that purpose of determining the specific routing based on the shortest distance traveled.Keywords: Transshipment model, mixed integer programming, saving algorithm, dry freight transportation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 914560 An Educational Application of Online Games for Learning Difficulties
Authors: M. Margoudi, Z. Smyrnaiou
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The current paper presents the results of a conducted case study. During the past few years the number of children diagnosed with Learning Difficulties has drastically augmented and especially the cases of ADHD (Attention Deficit Hyperactivity Disorder). One of the core characteristics of ADHD is a deficit in working memory functions. The review of the literature indicates a plethora of educational software that aim at training and enhancing the working memory. Nevertheless, in the current paper, the possibility of using for the same purpose free, online games will be explored. Another issue of interest is the potential effect of the working memory training to the core symptoms of ADHD. In order to explore the abovementioned research questions, three digital tests are employed, all of which are developed on the E-slate platform by the author, in order to check the levels of ADHD’s symptoms and to be used as diagnostic tools, both in the beginning and in the end of the case study. The tools used during the main intervention of the research are free online games for the training of working memory. The research and the data analysis focus on the following axes: a) the presence and the possible change in two of the core symptoms of ADHD, attention and impulsivity and b) a possible change in the general cognitive abilities of the individual. The case study was conducted with the participation of a thirteen year-old, female student, diagnosed with ADHD, during after-school hours. The results of the study indicate positive changes both in the levels of attention and impulsivity. Therefore, we conclude that the training of working memory through the use of free, online games has a positive impact on the characteristics of ADHD. Finally, concerning the second research question, the change in general cognitive abilities, no significant changes were noted.Keywords: ADHD, attention, impulsivity, online games.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1866559 Contention Window Adjustment in IEEE 802.11-Based Industrial Wireless Networks
Authors: Mohsen Maadani, Seyed Ahmad Motamedi
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The use of wireless technology in industrial networks has gained vast attraction in recent years. In this paper, we have thoroughly analyzed the effect of contention window (CW) size on the performance of IEEE 802.11-based industrial wireless networks (IWN), from delay and reliability perspective. Results show that the default values of CWmin, CWmax, and retry limit (RL) are far from the optimum performance due to the industrial application characteristics, including short packet and noisy environment. In this paper, an adaptive CW algorithm (payload-dependent) has been proposed to minimize the average delay. Finally a simple, but effective CW and RL setting has been proposed for industrial applications which outperforms the minimum-average-delay solution from maximum delay and jitter perspective, at the cost of a little higher average delay. Simulation results show an improvement of up to 20%, 25%, and 30% in average delay, maximum delay and jitter respectively.Keywords: Average Delay, Contention Window, Distributed Coordination Function (DCF), Jitter, Industrial Wireless Network (IWN), Maximum Delay, Reliability, Retry Limit.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2035558 Underrepresentation of Women in Management Information Systems: Gender Differences in Key Environmental Barriers
Authors: Asli Yagmur Akbulut
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Despite a robust and growing job market and lucrative salaries, there is a global shortage of Information Technology (IT) professionals. To make matters worse, women continue to be underrepresented in the IT workforce and among IT degree holders. In today’s knowledge based economy and society, it is extremely important to increase the presence of women in the IT field. In order to do so, it is necessary to reduce entry barriers and attract more women to pursue degrees in various IT fields including the field of Management Information Systems (MIS). Even though MIS is considered to have a more feminine nature, women still tend to avoid majoring in this field. Unfortunately, there is a lack of research that investigates the specific factors that may deter women from pursuing a degree in MIS. To address this research gap, this study examined a set of key environmental barriers that might prevent women from pursuing an MIS degree and explored whether there were any gender differences between female and male students in terms of these key barriers. Based on a survey of 280 students enrolled in an introductory level MIS course, the study empirically confirmed that there were significant differences between male and female students in terms of the key contextual barriers perceived. Female students demonstrated major concerns about gender discrimination related barriers, whereas male students were more concerned about negative social influences. Both male and female students were equally concerned about not being able to fit in well with other MIS majors. The findings have important implications for MIS programs, as the information gained can be used to design and implement specific intervention strategies to overcome the barriers and attract larger pools of women to the MIS discipline. The paper concludes with a discussion of the findings, implications, and future research directions.
Keywords: Gender differences, MIS major, underrepresentation, women in IT.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1571557 Simplified Space Vector Based Decoupled Switching Strategy for Indirect Vector Controlled Open-End Winding Induction Motor Drive
Authors: Syed Munvar Ali, V. Vijaya Kumar Reddy, M. Surya Kalavathi
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In this paper, a dual inverter configuration has been implemented for induction motor drive. This isolated dual inverter is capable to produce high quality of output voltage and minimize common mode voltage (CMV). To this isolated dual inverter a decoupled space vector based pulse width modulation (PWM) technique is proposed. Conventional space vector based PWM (SVPWM) techniques require reference voltage vector calculation and sector identification. The proposed decoupled SVPWM technique generates gating pulses from instantaneous phase voltages and gives a CMV of ±vdc/6. To evaluate proposed algorithm MATLAB based simulation studies are carried on indirect vector controlled open end winding induction motor drive.Keywords: Inverter configuration, decoupled SVPWM, common mode voltage, vector control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 734556 SC-LSH: An Efficient Indexing Method for Approximate Similarity Search in High Dimensional Space
Authors: Sanaa Chafik, ImaneDaoudi, Mounim A. El Yacoubi, Hamid El Ouardi
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Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbour search problem in high dimensional space. Euclidean LSH is the most popular variation of LSH that has been successfully applied in many multimedia applications. However, the Euclidean LSH presents limitations that affect structure and query performances. The main limitation of the Euclidean LSH is the large memory consumption. In order to achieve a good accuracy, a large number of hash tables is required. In this paper, we propose a new hashing algorithm to overcome the storage space problem and improve query time, while keeping a good accuracy as similar to that achieved by the original Euclidean LSH. The Experimental results on a real large-scale dataset show that the proposed approach achieves good performances and consumes less memory than the Euclidean LSH.
Keywords: Approximate Nearest Neighbor Search, Content based image retrieval (CBIR), Curse of dimensionality, Locality sensitive hashing, Multidimensional indexing, Scalability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2577555 Effects of Introducing Similarity Measures into Artificial Bee Colony Approach for Optimization of Vehicle Routing Problem
Authors: P. Shunmugapriya, S. Kanmani, P. Jude Fredieric, U. Vignesh, J. Reman Justin, K. Vivek
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Vehicle Routing Problem (VRP) is a complex combinatorial optimization problem and it is quite difficult to find an optimal solution consisting of a set of routes for vehicles whose total cost is minimum. Evolutionary and swarm intelligent (SI) algorithms play a vital role in solving optimization problems. While the SI algorithms perform search, the diversity between the solutions they exploit is very important. This is because of the need to avoid early convergence and to get an appropriate balance between the exploration and exploitation. Therefore, it is important to check how far the solutions are diverse. In this paper, we measure the similarity between solutions, which ABC exploits while optimizing VRP. The similar solutions found are discarded at the end of the iteration and only unique solutions are passed on to the next iteration. The bees of discarded solutions become scouts and they start searching for new solutions. This process is continued and results show that the solution is optimized at lesser number of iterations but with the overhead of computing similarity in all the iterations. The problem instance from Solomon benchmarked dataset has been used for evaluating the presented methodology.
Keywords: ABC algorithm, vehicle routing problem, optimization, Jaccard’s similarity measure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 846554 Adaptive Filtering of Heart Rate Signals for an Improved Measure of Cardiac Autonomic Control
Authors: Desmond B. Keenan, Paul Grossman
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In order to provide accurate heart rate variability indices of sympathetic and parasympathetic activity, the low frequency and high frequency components of an RR heart rate signal must be adequately separated. This is not always possible by just applying spectral analysis, as power from the high and low frequency components often leak into their adjacent bands. Furthermore, without the respiratory spectra it is not obvious that the low frequency component is not another respiratory component, which can appear in the lower band. This paper describes an adaptive filter, which aids the separation of the low frequency sympathetic and high frequency parasympathetic components from an ECG R-R interval signal, enabling the attainment of more accurate heart rate variability measures. The algorithm is applied to simulated signals and heart rate and respiratory signals acquired from an ambulatory monitor incorporating single lead ECG and inductive plethysmography sensors embedded in a garment. The results show an improvement over standard heart rate variability spectral measurements.Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, spectral analysis, adaptive filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1755553 Despiking of Turbulent Flow Data in Gravel Bed Stream
Authors: Ratul Das
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The present experimental study insights the decontamination of instantaneous velocity fluctuations captured by Acoustic Doppler Velocimeter (ADV) in gravel-bed streams to ascertain near-bed turbulence for low Reynolds number. The interference between incidental and reflected pulses produce spikes in the ADV data especially in the near-bed flow zone and therefore filtering the data are very essential. Nortek’s Vectrino four-receiver ADV probe was used to capture the instantaneous three-dimensional velocity fluctuations over a non-cohesive bed. A spike removal algorithm based on the acceleration threshold method was applied to note the bed roughness and its influence on velocity fluctuations and velocity power spectra in the carrier fluid. The velocity power spectra of despiked signals with a best combination of velocity threshold (VT) and acceleration threshold (AT) are proposed which ascertained velocity power spectra a satisfactory fit with the Kolmogorov “–5/3 scaling-law” in the inertial sub-range. Also, velocity distributions below the roughness crest level fairly follows a third-degree polynomial series.
Keywords: Acoustic Doppler Velocimeter, gravel-bed, spike removal, Reynolds shear stress, near-bed turbulence, velocity power spectra.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1180552 Using Case-Based Reasoning to New Service Development from User Innovation Community in Mobile Application Services
Authors: Jieun Kim, Yongtae Park, Hakyeon Lee
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The emergence of mobile application services and App Store has led to the explosive growth of user innovation, which users voluntarily contribute to. User innovation communities where end users freely reveal innovative ideas and needs with other community members are becoming increasingly influential in this area. However, user-s ideas in user innovation community are not enough to be new service opportunity, because some of them can already developed as existing services in App Store. Moreover, the existing services similar to new service opportunity can be significant references to apply analogy to develop service concept. In response, this research proposes Case-Based Reasoning approach to matching the user needs and existing services, identifying unmet opportunistic user needs, and retrieving similar services with opportunity. Due to its intuitive and transparent algorithm, users related to App Store innovation communities can easily employ Case-Based Reasoning based approach to their innovation.Keywords: App Store, Case-Based Reasoning, Mobile Application Service, User innovation community.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1903551 Socio-Demographic Characteristics and Psychosocial Consequences of Sickle Cell Disease: The Case of Patients in a Public Hospital in Ghana
Authors: Vincent A. Adzika, Franklin N. Glozah, Collins S. K. Ahorlu
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Background: Sickle Cell Disease (SCD) is of major public-health concern globally, with majority of patients living in Africa. Despite its relevance, there is a dearth of research to determine the socio-demographic distribution and psychosocial impact of SCD in Africa. The objective of this study therefore was to examine the socio-demographic distribution and psychosocial consequences of SCD among patients in Ghana and to assess their quality of life and coping mechanisms. Methods: A cross-sectional research design was used, involving the completion of questionnaires on socio-demographic characteristics, quality of life of individuals, anxiety and depression. Participants were 387 male and female patients attending a sickle cell clinic in a public hospital. Results: Results showed no gender and marital status differences in anxiety and depression. However, there were age and level of education variances in depression but not in anxiety. In terms of quality of life, patients were more satisfied by the presence of love, friends, relatives as well as home, community and neighbourhood environment. While pains of varied nature and severity were the major reasons for attending hospital in SCD condition, going to the hospital as well as having Faith in God was the frequently reported mechanisms for coping with an unbearable SCD attacks. Multiple regression analysis showed that some socio-demographic and quality of life indicators had strong associations with anxiety and/or depression. Conclusion: It is recommended that a multi-dimensional intervention strategy incorporating psychosocial dimensions should be considered in the treatment and management of SCD.
Keywords: Sickle cell disease, quality of life, anxiety, depression, socio-demographic characteristics, Ghana.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1826550 Quadratic Pulse Inversion Ultrasonic Imaging(QPI): A Two-Step Procedure for Optimization of Contrast Sensitivity and Specificity
Authors: Mamoun F. Al-Mistarihi
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We have previously introduced an ultrasonic imaging approach that combines harmonic-sensitive pulse sequences with a post-beamforming quadratic kernel derived from a second-order Volterra filter (SOVF). This approach is designed to produce images with high sensitivity to nonlinear oscillations from microbubble ultrasound contrast agents (UCA) while maintaining high levels of noise rejection. In this paper, a two-step algorithm for computing the coefficients of the quadratic kernel leading to reduction of tissue component introduced by motion, maximizing the noise rejection and increases the specificity while optimizing the sensitivity to the UCA is presented. In the first step, quadratic kernels from individual singular modes of the PI data matrix are compared in terms of their ability of maximize the contrast to tissue ratio (CTR). In the second step, quadratic kernels resulting in the highest CTR values are convolved. The imaging results indicate that a signal processing approach to this clinical challenge is feasible.Keywords: Volterra Filter, Pulse Inversion, Ultrasonic Imaging, Contrast Agent.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1590549 Fuzzy Optimization in Metabolic Systems
Authors: Feng-Sheng Wang, Wu-Hsiung Wu, Kai-Cheng Hsu
Abstract:
The optimization of biological systems, which is a branch of metabolic engineering, has generated a lot of industrial and academic interest for a long time. In the last decade, metabolic engineering approaches based on mathematical optimizations have been used extensively for the analysis and manipulation of metabolic networks. In practical optimization of metabolic reaction networks, designers have to manage the nature of uncertainty resulting from qualitative characters of metabolic reactions, e.g., the possibility of enzyme effects. A deterministic approach does not give an adequate representation for metabolic reaction networks with uncertain characters. Fuzzy optimization formulations can be applied to cope with this problem. A fuzzy multi-objective optimization problem can be introduced for finding the optimal engineering interventions on metabolic network systems considering the resilience phenomenon and cell viability constraints. The accuracy of optimization results depends heavily on the development of essential kinetic models of metabolic networks. Kinetic models can quantitatively capture the experimentally observed regulation data of metabolic systems and are often used to find the optimal manipulation of external inputs. To address the issues of optimizing the regulatory structure of metabolic networks, it is necessary to consider qualitative effects, e.g., the resilience phenomena and cell viability constraints. Combining the qualitative and quantitative descriptions for metabolic networks makes it possible to design a viable strain and accurately predict the maximum possible flux rates of desired products. Considering the resilience phenomena in metabolic networks can improve the predictions of gene intervention and maximum synthesis rates in metabolic engineering. Two case studies will present in the conference to illustrate the phenomena.
Keywords: Fuzzy multi-objective optimization problem, kinetic model, metabolic engineering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2020548 Skew Detection Technique for Binary Document Images based on Hough Transform
Authors: Manjunath Aradhya V N, Hemantha Kumar G, Shivakumara P
Abstract:
Document image processing has become an increasingly important technology in the automation of office documentation tasks. During document scanning, skew is inevitably introduced into the incoming document image. Since the algorithm for layout analysis and character recognition are generally very sensitive to the page skew. Hence, skew detection and correction in document images are the critical steps before layout analysis. In this paper, a novel skew detection method is presented for binary document images. The method considered the some selected characters of the text which may be subjected to thinning and Hough transform to estimate skew angle accurately. Several experiments have been conducted on various types of documents such as documents containing English Documents, Journals, Text-Book, Different Languages and Document with different fonts, Documents with different resolutions, to reveal the robustness of the proposed method. The experimental results revealed that the proposed method is accurate compared to the results of well-known existing methods.Keywords: Optical Character Recognition, Skew angle, Thinning, Hough transform, Document processing
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2095547 Multiclass Support Vector Machines with Simultaneous Multi-Factors Optimization for Corporate Credit Ratings
Authors: Hyunchul Ahn, William X. S. Wong
Abstract:
Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.
Keywords: Corporate credit rating prediction, feature selection, genetic algorithms, instance selection, multiclass support vector machines.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1411