World Academy of Science, Engineering and Technology
[Computer and Information Engineering]
Online ISSN : 1307-6892
3122 Maximum Entropy Based Image Segmentation of Human Skin Lesion
Authors: Sheema Shuja Khattak, Gule Saman, Imran Khan, Abdus Salam
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Image segmentation plays an important role in medical imaging applications. Therefore, accurate methods are needed for the successful segmentation of medical images for diagnosis and detection of various diseases. In this paper, we have used maximum entropy to achieve image segmentation. Maximum entropy has been calculated using Shannon, Renyi and Tsallis entropies. This work has novelty based on the detection of skin lesion caused by the bite of a parasite called Sand Fly causing the disease is called Cutaneous Leishmaniasis.
Keywords: Shannon, Maximum entropy, Renyi, Tsallis entropy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23773121 Synthesis of Filtering in Stochastic Systems on Continuous-Time Memory Observations in the Presence of Anomalous Noises
Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov
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We have conducted the optimal synthesis of rootmean- squared objective filter to estimate the state vector in the case if within the observation channel with memory the anomalous noises with unknown mathematical expectation are complement in the function of the regular noises. The synthesis has been carried out for linear stochastic systems of continuous - time.
Keywords: Mathematical expectation, filtration, anomalous noise, memory.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19403120 Knowledge Representation Based On Interval Type-2 CFCM Clustering
Authors: Myung-Won Lee, Keun-Chang Kwak
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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.
Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25993119 Improved FP-growth Algorithm with Multiple Minimum Supports Using Maximum Constraints
Authors: Elsayeda M. Elgaml, Dina M. Ibrahim, Elsayed A. Sallam
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Association rule mining is one of the most important fields of data mining and knowledge discovery. In this paper, we propose an efficient multiple support frequent pattern growth algorithm which we called “MSFP-growth” that enhancing the FPgrowth algorithm by making infrequent child node pruning step with multiple minimum support using maximum constrains. The algorithm is implemented, and it is compared with other common algorithms: Apriori-multiple minimum supports using maximum constraints and FP-growth. The experimental results show that the rule mining from the proposed algorithm are interesting and our algorithm achieved better performance than other algorithms without scarifying the accuracy.
Keywords: Association Rules, FP-growth, Multiple minimum supports, Weka Tool
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32933118 An Efficient Gaussian Noise Removal Image Enhancement Technique for Gray Scale Images
Authors: V. Murugan, R. Balasubramanian
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Image enhancement is a challenging issue in many applications. In the last two decades, there are various filters developed. This paper proposes a novel method which removes Gaussian noise from the gray scale images. The proposed technique is compared with Enhanced Fuzzy Peer Group Filter (EFPGF) for various noise levels. Experimental results proved that the proposed filter achieves better Peak-Signal-to-Noise-Ratio PSNR than the existing techniques. The proposed technique achieves 1.736dB gain in PSNR than the EFPGF technique.
Keywords: Gaussian noise, adaptive bilateral filter, fuzzy peer group filter, switching bilateral filter, PSNR
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24633117 Efficient Utilization of Commodity Computers in Academic Institutes: A Cloud Computing Approach
Authors: Jasraj Meena, Malay Kumar, Manu Vardhan
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Cloud computing is a new technology in industry and academia. The technology has grown and matured in last half decade and proven their significant role in changing environment of IT infrastructure where cloud services and resources are offered over the network. Cloud technology enables users to use services and resources without being concerned about the technical implications of technology. There are substantial research work has been performed for the usage of cloud computing in educational institutes and majority of them provides cloud services over high-end blade servers or other high-end CPUs. However, this paper proposes a new stack called “CiCKAStack” which provide cloud services over unutilized computing resources, named as commodity computers. “CiCKAStack” provides IaaS and PaaS using underlying commodity computers. This will not only increasing the utilization of existing computing resources but also provide organize file system, on demand computing resource and design and development environment.
Keywords: Commodity Computers, Cloud Computing, KVM, Cloudstack, Appscale.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19943116 Fault Tolerance in Wireless Sensor Networks – A Survey
Authors: B. R. Tapas Bapu, K. Thanigaivelu, A. Rajkumar
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Wireless Sensor Networks (WSNs) have wide variety of applications and provide limitless future potentials. Nodes in WSNs are prone to failure due to energy depletion, hardware failure, communication link errors, malicious attacks, and so on. Therefore, fault tolerance is one of the critical issues in WSNs. We study how fault tolerance is addressed in different applications of WSNs. Fault tolerant routing is a critical task for sensor networks operating in dynamic environments. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. The focus, however, has been given to the routing protocols which might differ depending on the application and network architecture.
Keywords: Resiliency, Self-diagnosis, Smart Grid, TinyOS, WSANs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27113115 Improved of Elliptic Curves Cryptography over a Ring
Authors: A. Chillali, A. Tadmori, M. Ziane
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In this article we will study the elliptic curve defined over the ring An and we define the mathematical operations of ECC, which provides a high security and advantage for wireless applications compared to other asymmetric key cryptosystem.
Keywords: Elliptic Curves, Finite Ring, Cryptography.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20833114 A Combined Neural Network Approach to Soccer Player Prediction
Authors: Wenbin Zhang, Hantian Wu, Jian Tang
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An artificial neural network is a mathematical model inspired by biological neural networks. There are several kinds of neural networks and they are widely used in many areas, such as: prediction, detection, and classification. Meanwhile, in day to day life, people always have to make many difficult decisions. For example, the coach of a soccer club has to decide which offensive player to be selected to play in a certain game. This work describes a novel Neural Network using a combination of the General Regression Neural Network and the Probabilistic Neural Networks to help a soccer coach make an informed decision.
Keywords: General Regression Neural Network, Probabilistic Neural Networks, Neural function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37353113 Designing a Tool for Software Maintenance
Authors: Amir Ngah, Masita Abdul Jalil, Zailani Abdullah
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The aim of software maintenance is to maintain the software system in accordance with advancement in software and hardware technology. One of the early works on software maintenance is to extract information at higher level of abstraction. In this paper, we present the process of how to design an information extraction tool for software maintenance. The tool can extract the basic information from old programs such as about variables, based classes, derived classes, objects of classes, and functions. The tool have two main parts; the lexical analyzer module that can read the input file character by character, and the searching module which users can get the basic information from the existing programs. We implemented this tool for a patterned sub-C++ language as an input file.
Keywords: Extraction tool, software maintenance, reverse engineering, C++.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23743112 Seismic Evaluation with Shear Walls and Braces for Buildings
Authors: S. K. Madan, R. S. Malik, V. K. Sehgal
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R.C.C. buildings with dual structural system consisting of shear walls (or braces) and moment resisting frames have been widely used to resist lateral forces during earthquakes. The dual systems are designed to resist the total design lateral force in proportion to their lateral stiffness. The response of combination of braces and shear walls has not yet been studied. The combination may prove to be more effective to resist lateral forces during earthquakes. This concept has been applied to regular R.C.C. buildings provided with shear walls, braces and their combinations.
Keywords: Dynamic analysis, Displacement, Dual structural system, Storey drift.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40973111 A Medical Resource Forecasting Model for Emergency Room Patients with Acute Hepatitis
Authors: R. J. Kuo, W. C. Cheng, W. C. Lien, T. J. Yang
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Taiwan is a hyper endemic area for the Hepatitis B virus (HBV). The estimated total number of HBsAg carriers in the general population who are more than 20 years old is more than 3 million. Therefore, a case record review is conducted from January 2003 to June 2007 for all patients with a diagnosis of acute hepatitis who were admitted to the Emergency Department (ED) of a well-known teaching hospital. The cost for the use of medical resources is defined as the total medical fee. In this study, principal component analysis (PCA) is firstly employed to reduce the number of dimensions. Support vector regression (SVR) and artificial neural network (ANN) are then used to develop the forecasting model. A total of 117 patients meet the inclusion criteria. 61% patients involved in this study are hepatitis B related. The computational result shows that the proposed PCA-SVR model has superior performance than other compared algorithms. In conclusion, the Child-Pugh score and echogram can both be used to predict the cost of medical resources for patients with acute hepatitis in the ED.
Keywords: Acute hepatitis, Medical resource cost, Artificial neural network, Support vector regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18993110 A High Level Implementation of a High Performance Data Transfer Interface for NoC
Authors: Mansi Jhamb, R. K. Sharma, A. K. Gupta
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The distribution of a single global clock across a chip has become the major design bottleneck for high performance VLSI systems owing to the power dissipation, process variability and multicycle cross-chip signaling. A Network-on-Chip (NoC) architecture partitioned into several synchronous blocks has become a promising approach for attaining fine-grain power management at the system level. In a NoC architecture the communication between the blocks is handled asynchronously. To interface these blocks on a chip operating at different frequencies, an asynchronous FIFO interface is inevitable. However, these asynchronous FIFOs are not required if adjacent blocks belong to the same clock domain. In this paper, we have designed and analyzed a 16-bit asynchronous micropipelined FIFO of depth four, with the awareness of place and route on an FPGA device. We have used a commercially available Spartan 3 device and designed a high speed implementation of the asynchronous 4-phase micropipeline. The asynchronous FIFO implemented on the FPGA device shows 76 Mb/s throughput and a handshake cycle of 109 ns for write and 101.3 ns for read at the simulation under the worst case operating conditions (voltage = 0.95V) on a working chip at the room temperature.Keywords: Asynchronous, FIFO, FPGA, GALS, Network-on- Chip (NoC), VHDL.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20193109 Tool for Analysing the Sensitivity and Tolerance of Mechatronic Systems in Matlab GUI
Authors: Bohuslava Juhasova, Martin Juhas, Renata Masarova, Zuzana Sutova
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The article deals with the tool in Matlab GUI form that is designed to analyse a mechatronic system sensitivity and tolerance. In the analysed mechatronic system, a torque is transferred from the drive to the load through a coupling containing flexible elements. Different methods of control system design are used. The classic form of the feedback control is proposed using Naslin method, modulus optimum criterion and inverse dynamics method. The cascade form of the control is proposed based on combination of modulus optimum criterion and symmetric optimum criterion. The sensitivity is analysed on the basis of absolute and relative sensitivity of system function to the change of chosen parameter value of the mechatronic system, as well as the control subsystem. The tolerance is analysed in the form of determining the range of allowed relative changes of selected system parameters in the field of system stability. The tool allows to analyse an influence of torsion stiffness, torsion damping, inertia moments of the motor and the load and controller(s) parameters. The sensitivity and tolerance are monitored in terms of the impact of parameter change on the response in the form of system step response and system frequency-response logarithmic characteristics. The Symbolic Math Toolbox for expression of the final shape of analysed system functions was used. The sensitivity and tolerance are graphically represented as 2D graph of sensitivity or tolerance of the system function and 3D/2D static/interactive graph of step/frequency response.Keywords: Mechatronic systems, Matlab GUI, sensitivity, tolerance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20323108 Survey on Strategic Games and Decision Making
Authors: S. Madhavi, K. Baala Srinivas, G. Bharath, R. K. Indhuja, M. Kowser Chandini
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Game theory is the study of how people interact and make decisions to handle competitive situations. It has mainly been developed to study decision making in complex situations. Humans routinely alter their behaviour in response to changes in their social and physical environment. As a consequence, the outcomes of decisions that depend on the behaviour of multiple decision makers are difficult to predict and require highly adaptive decision-making strategies. In addition to the decision makers may have preferences regarding consequences to other individuals and choose their actions to improve or reduce the well-being of others. Nash equilibrium is a fundamental concept in the theory of games and the most widely used method of predicting the outcome of a strategic interaction in the social sciences. A Nash Equilibrium exists when there is no unilateral profitable deviation from any of the players involved. On the other hand, no player in the game would take a different action as long as every other player remains the same.
Keywords: Game Theory, Nash Equilibrium, Rules of Dominance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23503107 The Solution of the Direct Problem of Electrical Prospecting with Direct Current under Conditions of Ground Surface Relief
Authors: Balgaisha Mukanova, Tolkyn Mirgalikyzy
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Theory of interpretation of electromagnetic fields studied in the electrical prospecting with direct current is mainly developed for the case of a horizontal surface observation. However in practice we often have to work in difficult terrain surface. Conducting interpretation without the influence of topography can cause non-existent anomalies on sections. This raises the problem of studying the impact of different shapes of ground surface relief on the results of electrical prospecting's research. This research examines the numerical solutions of the direct problem of electrical prospecting for two-dimensional and three-dimensional media, taking into account the terrain. The problem is solved using the method of integral equations. The density of secondary currents on the relief surface is obtained.
Keywords: Ground surface relief, method of integral equations, numerical method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20973106 IT/IS Organisation Design in the Digital Age – A Literature Review
Authors: Dominik Krimpmann
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Information technology and information systems are currently at a tipping point. The digital age fundamentally transforms a large number of industries in the ways they work. Lines between business and technology blur. Researchers have acknowledged that this is the time in which the IT/IS organisation needs to re-strategize itself. In this paper, the author provides a structured review of the IS and organisation design literature addressing the question of how the digital age changes the design categories of an IT/IS organisation design. The findings show that most papers just analyse single aspects of either IT/IS relevant information or generic organisation design elements but miss a holistic ‘big-picture’ onto an IT/IS organisation design. This paper creates a holistic IT/IS organisation design framework bringing together the IS research strand, the digital strand and the generic organisation design strand. The research identified four IT/IS organisation design categories (strategy, structure, processes and people) and discusses the importance of two additional categories (sourcing and governance). The authors findings point to a first anchor point from which further research needs to be conducted to develop a holistic IT/IS organisation design framework.
Keywords: IT/IS strategy, IT/IS organisation design, digital age, organisational effectiveness, literature review.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36963105 Automatic LV Segmentation with K-means Clustering and Graph Searching on Cardiac MRI
Authors: Hae-Yeoun Lee
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Quantification of cardiac function is performed by calculating blood volume and ejection fraction in routine clinical practice. However, these works have been performed by manual contouring, which requires computational costs and varies on the observer. In this paper, an automatic left ventricle segmentation algorithm on cardiac magnetic resonance images (MRI) is presented. Using knowledge on cardiac MRI, a K-mean clustering technique is applied to segment blood region on a coil-sensitivity corrected image. Then, a graph searching technique is used to correct segmentation errors from coil distortion and noises. Finally, blood volume and ejection fraction are calculated. Using cardiac MRI from 15 subjects, the presented algorithm is tested and compared with manual contouring by experts to show outstanding performance.
Keywords: Cardiac MRI, Graph searching, Left ventricle segmentation, K-means clustering.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20743104 Feature-Based Summarizing and Ranking from Customer Reviews
Authors: Dim En Nyaung, Thin Lai Lai Thein
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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.
Keywords: Opinion Mining, Opinion Summarization, Sentiment Analysis, Text Mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29123103 Customer Churn Prediction: A Cognitive Approach
Authors: Damith Senanayake, Lakmal Muthugama, Laksheen Mendis, Tiroshan Madushanka
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Customer churn prediction is one of the most useful areas of study in customer analytics. Due to the enormous amount of data available for such predictions, machine learning and data mining have been heavily used in this domain. There exist many machine learning algorithms directly applicable for the problem of customer churn prediction, and here, we attempt to experiment on a novel approach by using a cognitive learning based technique in an attempt to improve the results obtained by using a combination of supervised learning methods, with cognitive unsupervised learning methods.
Keywords: Growing Self Organizing Maps, Kernel Methods, Churn Prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25353102 An ANN-Based Predictive Model for Diagnosis and Forecasting of Hypertension
Authors: O. O. Obe, V. Balanica, E. Neagoe
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The effects of hypertension are often lethal thus its early detection and prevention is very important for everybody. In this paper, a neural network (NN) model was developed and trained based on a dataset of hypertension causative parameters in order to forecast the likelihood of occurrence of hypertension in patients. Our research goal was to analyze the potential of the presented NN to predict, for a period of time, the risk of hypertension or the risk of developing this disease for patients that are or not currently hypertensive. The results of the analysis for a given patient can support doctors in taking pro-active measures for averting the occurrence of hypertension such as recommendations regarding the patient behavior in order to lower his hypertension risk. Moreover, the paper envisages a set of three example scenarios in order to determine the age when the patient becomes hypertensive, i.e. determine the threshold for hypertensive age, to analyze what happens if the threshold hypertensive age is set to a certain age and the weight of the patient if being varied, and, to set the ideal weight for the patient and analyze what happens with the threshold of hypertensive age.
Keywords: Neural Network, hypertension, data set, training set, supervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16463101 A Robust Implementation of a Building Resources Access Rights Management System
Authors: E. Neagoe, V. Balanica
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A Smart Building Controller (SBC) is a server software that offers secured access to a pool of building specific resources, executes monitoring tasks and performs automatic administration of a building, thus optimizing the exploitation cost and maximizing comfort. This paper brings to discussion the issues that arise with the secure exploitation of the SBC administered resources and proposes a technical solution to implement a robust secure access system based on roles, individual rights and privileges (special rights).
Keywords: Access authorization, smart building controller, software security, access rights.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18853100 STATISTICA Software: A State of the Art Review
Authors: S. Sarumathi, N. Shanthi, S. Vidhya, P. Ranjetha
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Data mining idea is mounting rapidly in admiration and also in their popularity. The foremost aspire of data mining method is to extract data from a huge data set into several forms that could be comprehended for additional use. The data mining is a technology that contains with rich potential resources which could be supportive for industries and businesses that pay attention to collect the necessary information of the data to discover their customer’s performances. For extracting data there are several methods are available such as Classification, Clustering, Association, Discovering, and Visualization… etc., which has its individual and diverse algorithms towards the effort to fit an appropriate model to the data. STATISTICA mostly deals with excessive groups of data that imposes vast rigorous computational constraints. These results trials challenge cause the emergence of powerful STATISTICA Data Mining technologies. In this survey an overview of the STATISTICA software is illustrated along with their significant features.
Keywords: Data Mining, STATISTICA Data Miner, Text Miner, Enterprise Server, Classification, Association, Clustering, Regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25873099 Visual Analytics in K 12 Education - Emerging Dimensions of Complexity
Authors: Linnea Stenliden
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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors within Actor-network theory (ANT). The learning conditions are found to be distinguished by broad complexity, characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.
Keywords: Analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16763098 Big Data Analytics and Data Security in the Cloud via Fully Homomorphic Encryption
Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Moses Noel Dogonyaro
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This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.
Keywords: Data Analytics, Security, Privacy, Bootstrapping, and Fully Homomorphic Encryption Scheme.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34303097 Video Summarization: Techniques and Applications
Authors: Zaynab Elkhattabi, Youness Tabii, Abdelhamid Benkaddour
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Nowadays, huge amount of multimedia repositories make the browsing, retrieval and delivery of video contents very slow and even difficult tasks. Video summarization has been proposed to improve faster browsing of large video collections and more efficient content indexing and access. In this paper, we focus on approaches to video summarization. The video summaries can be generated in many different forms. However, two fundamentals ways to generate summaries are static and dynamic. We present different techniques for each mode in the literature and describe some features used for generating video summaries. We conclude with perspective for further research.
Keywords: Semantic features, static summarization, video skimming, Video summarization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 70363096 Empirical Exploration for the Correlation between Class Object-Oriented Connectivity-Based Cohesion and Coupling
Authors: Jehad Al Dallal
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Attributes and methods are the basic contents of an object-oriented class. The connectivity among these class members and the relationship between the class and other classes play an important role in determining the quality of an object-oriented system. Class cohesion evaluates the degree of relatedness of class attributes and methods, whereas class coupling refers to the degree to which a class is related to other classes. Researchers have proposed several class cohesion and class coupling measures. However, the correlation between class coupling and class cohesion measures has not been thoroughly studied. In this paper, using classes of three open-source Java systems, we empirically investigate the correlation between several measures of connectivity-based class cohesion and coupling. Four connectivity-based cohesion measures and eight coupling measures are considered in the empirical study. The empirical study results show that class connectivity-based cohesion and coupling internal quality attributes are inversely correlated. The strength of the correlation depends highly on the cohesion and coupling measurement approaches.
Keywords: Object-oriented class, software quality, class cohesion measure, class coupling measure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23703095 Investigation on Novel Based Naturally-Inspired Swarm Intelligence Algorithms for Optimization Problems in Mobile Ad Hoc Networks
Authors: C. Rajan, K. Geetha, C. Rasi Priya, S. Geetha
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Nature is the immense gifted source for solving complex problems. It always helps to find the optimal solution to solve the problem. Mobile Ad Hoc NETwork (MANET) is a wide research area of networks which has set of independent nodes. The characteristics involved in MANET’s are Dynamic, does not depend on any fixed infrastructure or centralized networks, High mobility. The Bio-Inspired algorithms are mimics the nature for solving optimization problems opening a new era in MANET. The typical Swarm Intelligence (SI) algorithms are Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Modified Termite Algorithm, Bat Algorithm (BA), Wolf Search Algorithm (WSA) and so on. This work mainly concentrated on nature of MANET and behavior of nodes. Also it analyses various performance metrics such as throughput, QoS and End-to-End delay etc.
Keywords: Ant Colony Algorithm, Artificial Bee Colony algorithm, Bio-Inspired algorithm, Modified Termite Algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24473094 Similarity Based Retrieval in Case Based Reasoning for Analysis of Medical Images
Authors: M. Das Gupta, S. Banerjee
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Content Based Image Retrieval (CBIR) coupled with Case Based Reasoning (CBR) is a paradigm that is becoming increasingly popular in the diagnosis and therapy planning of medical ailments utilizing the digital content of medical images. This paper presents a survey of some of the promising approaches used in the detection of abnormalities in retina images as well in mammographic screening and detection of regions of interest in MRI scans of the brain. We also describe our proposed algorithm to detect hard exudates in fundus images of the retina of Diabetic Retinopathy patients.
Keywords: Case based reasoning, Exudates, Retina image, Similarity based retrieval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20993093 Stealth Laser Dicing Process Improvement via Shuffled Frog Leaping Algorithm
Authors: Pongchanun Luangpaiboon, Wanwisa Sarasang
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In this paper, performances of shuffled frog leaping algorithm was investigated on the stealth laser dicing process. Effect of problem on the performance of the algorithm was based on the tolerance of meandering data. From the customer specification it could be less than five microns with the target of zero microns. Currently, the meandering levels are unsatisfactory when compared to the customer specification. Firstly, the two-level factorial design was applied to preliminarily study the statistically significant effects of five process variables. In this study one influential process variable is integer. From the experimental results, the new operating condition from the algorithm was superior when compared to the current manufacturing condition.
Keywords: Stealth Laser Dicing Process, Meandering, Metaheuristics, Shuffled Frog Leaping Algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2604