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Keyword: AlgorithmsEAES: Extended Advanced Encryption Standard with Extended Security
Though AES is the highest secure symmetric cipher at present, many attacks are now effective against AES too which is seen from the review of recent attacks of AES. This paper describes an extended AES algorithm with key sizes of 256, 384 and 512 bits with round numbers of 10, 12 and 14 respectively. Data…
Read MoreEfficient Alignment of Very Long Sequences
We consider the problem of aligning two very long biological sequences. The score for the best alignment may be found using the Smith-Waterman scoring algorithm while the best alignment itself may be determined using Myers and Miller’s alignment algorithm. Neither of these algorithms takes advantage of computer caches to obtain high efficiency. We propose cache-efficient…
Read MoreFrameworks for Performing on Cloud Automated Software Testing Using Swarm Intelligence Algorithm: Brief Survey
This paper surveys on Cloud Based Automated Testing Software that is able to perform Black-box testing, White-box testing, as well as Unit and Integration Testing as a whole. In this paper, we discuss few of the available automated software testing frameworks on the cloud. These frameworks are found to be more efficient and cost effective…
Read MoreSystematic Tool Support of Engineering Education Performance Management
Engineering schools must adopt or develop their own systems and processes for graduate attribute assessment. In this paper, we take a systems engineering approach to graduate attribute assessment and propose a system architecture and tool-supported continuous improvement process with key algorithms and mathematical analysis to process the data and provide performance management reporting. Over several…
Read MoreVelocity obstacles for car-like mobile robots: Determination of colliding velocity and curvature pairs
This paper addresses the motion planning problem of Reeds-Shepp-type car-like mobile robots moving among static and dynamic obstacles. If the positions and the velocity vectors of the obstacles are known or well estimated, the Velocity Obstacles (VO) method and its non-linear version (NLVO) can be used to plan a collision-free trajectory for a robot in…
Read MoreDevelopment of Indicators for Technical Condition Indexing of Power Transformers
Reliable operation of a power transformer with a certain load depends on the technical condition of individual construction parts and the ability to prevent defects that can cause a failure. During the lifecycle of a transformer, valuable data is constantly accumulated, which forms the basis for technical or risk assessment of the equipment. Therefore it…
Read MoreVirtual Memory Introspection Framework for Cyber Threat Detection in Virtual Environment
In today’s information based world, it is increasingly important to safeguard the data owned by any organization, be it intellectual property or personal information. With ever increasing sophistication of malware, it is imperative to come up with an automated and advanced methods of attack vector recognition and isolation. Existing methods are not dynamic enough to…
Read MoreMachine Learning framework for image classification
Hereby in this paper, we are going to refer image classification. The main issue in image classification is features extraction and image vector representation. We expose the Bag of Features method used to find image representation. Class prediction accuracy of varying classifiers algorithms is measured on Caltech 101 images. For feature extraction functions we evaluate…
Read MoreApplying Machine Learning and High Performance Computing to Water Quality Assessment and Prediction
Water quality assessment and prediction is a more and more important issue. Traditional ways either take lots of time or they can only do assessments. In this research, by applying machine learning algorithm to a long period time of water attributes’ data; we can generate a decision tree so that it can predict the future…
Read MoreA Relational Database Model and Tools for Environmental Sound Recognition
Environmental sound recognition (ESR) has become a hot topic in recent years. ESR is mainly based on machine learning (ML) and ML algorithms require first a training database. This database must comprise the sounds to be recognized and other related sounds. An ESR system needs the database during training, testing and in the production stage.…
Read MoreDistributing the computation in combinatorial optimization experiments over the cloud
Combinatorial optimization is an area of great importance since many of the real-world problems have discrete parameters which are part of the objective function to be optimized. Development of combinatorial optimization algorithms is guided by the empirical study of the candidate ideas and their performance over a wide range of settings or scenarios to infer…
Read MoreA novel beamforming based model of coverage and transmission costing in IEEE 802.11 WLAN networks
IEEE 802.11 WLAN indoor networks face major inherent and environmental issues such as interference, noise, and obstacles. At the same time, they must provide a maximal service performance in highly changing radio environments and conformance to various applications’ requirements. For this purpose, they require a solid design approach that considers both inputs from the radio…
Read MoreSoft Handoff Evaluation and Efficient Access Network Selection in Next Generation Cellular Systems
The increased motivation (by service providers) to offer user-centric and seamless communication services – that satisfies users’ quality of experience (QoE), has manifested a myriad of challenges in the field of wireless communication; and given the increased traffic capacity and sudden explosion of cellular devices, communication systems are constantly threatened by performance related issues –…
Read MoreOn the Performance of a Clustering-based Task Scheduling in a Heterogeneous System
Recent task scheduling algorithms for a generalized workflow job in heterogeneous system adopt list-based scheduling. In those algorithms, the response time cannot be effectively reduced if the given workflow job is data-intensive. If the workflow job is computationally intensive, an attempt is made to assign tasks to many processors, which can lead to resource starvation.…
Read MoreEstimation of Power System Stabilizer Parameters Using Swarm Intelligence Techniques to Improve Small Signal Stability of Power System
Interconnection of the power system utilities and grids offers a formidable dispute in front of design engineers. With the interconnections, power system has emerged as a more intricate and nonlinear system. Recent years small signal stability problems have achieved much significance along with the conventional transient constancy problems. Transient stability of the power system can…
Read MorePixel-Based Unsupervised Classification Approach for Information Detection on Optical Markup Recognition Sheet
This paper proposed an Optical Markup Recognition (OMR) system to be used to detect shaded options of students after MCQ-type examinations. The designed system employed the pixel-based unsupervised classification approach with image pre-processing strategies and compared its efficiencies, in terms of speed and accuracy, with object-based supervised or unsupervised classification OMR systems. Speed and accuracy…
Read MoreA Machine Learning based Framework for Parameter based Multi-Objective Optimisation of Video CODECs
All multimedia devices now incorporate video CODECs that comply with international video coding standards such as H.264 / MPEG4-AVC and the new High Efficiency Video Coding Standard (HEVC), otherwise known as H.265. Although the standard CODECs have been designed to include algorithms with optimal efficiency, a large number of coding parameters can be used to…
Read MoreUse of machine learning techniques in the prediction of credit recovery
This paper is an extended version of the paper originally presented at the International Conference on Machine Learning and Applications (ICMLA 2016), which proposes the construction of classifiers, based on the application of machine learning techniques, to identify defaulting clients with credit recovery potential. The study was carried out in 3 segments of a Bank’s…
Read MoreContent Reordering Based on Mouse-tracking for Web Applications
Rising usage of web applications in every aspect of life has created intense need of enhancement of user experience and formation of intelligent web applications. This research work was conducted with a view to do so. This paper focuses on the reorganization of web application content based on user’s specific interests while browsing any web…
Read MorePublic transportation network design: a geospatial data-driven method
The paper explores an issue of efficient public transportation network design as a part of the urban developing process. Having data about everyday residents travelling inside of an urban area, we can consider this data as people’s requirements for the public transport system. We propose a novel method for initial public transportation network design based…
Read MoreTowards Deployment Strategies for Deception Systems
Network security is often built on perimeter defense. Sophisticated attacks are able to penetrate the perimeter and access valuable resources in the network. A more complete defense strategy also contains mechanisms to detect and mitigate perimeter breaches. Deceptive systems are a promising technology to detect, deceive and counter infiltration. In this work we provide an…
Read MoreSelective Detrending using Baseline Drift Detection Index for Task-dependant fNIRS Signal
A functional near-infrared spectroscopy (fNIRS) can be employed to investigate brain activation by measuring the absorption of near-infrared light through the intact skull. The general linear model (GLM) as a standard model for fMRI analysis has been applied to functional near-infrared spectroscopic (fNIRS) imaging analysis as well. The GLM has drawback of failure in fNIRS…
Read MoreEnsemble of Neural Network Conditional Random Fields for Self-Paced Brain Computer Interfaces
Classification of EEG signals in self-paced Brain Computer Interfaces (BCI) is an extremely challenging task. The main difficulty stems from the fact that start time of a control task is not defined. Therefore it is imperative to exploit the characteristics of the EEG data to the extent possible. In sensory motor self-paced BCIs, while performing…
Read MoreA novel model for Time-Series Data Clustering Based on piecewise SVD and BIRCH for Stock Data Analysis on Hadoop Platform
With the rapid growth of financial markets, analyzers are paying more attention on predictions. Stock data are time series data, with huge amounts. Feasible solution for handling the increasing amount of data is to use a cluster for parallel processing, and Hadoop parallel computing platform is a typical representative. There are various statistical models for…
Read MoreAn efficient model to improve the performance of platelet inventory of the blood banks
Platelet transfusions are vital for the prevention of fatal hemorrhage. Therefore, a stable inventory of platelets is required for an efficient and effective delivery of services in all the hospitals and medical centers. However, over the past decades, the requirement for platelets seems to be continuously increasing, while the number of potential donors is decreasing.…
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