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Keyword: clusterMulti Biometric Thermal Face Recognition Using FWT and LDA Feature Extraction Methods with RBM DBN and FFNN Classifier Algorithms
Person recognition using thermal imaging, multi-biometric traits, with groups of feature filters and classifiers, is the subject of this paper. These were used to tackle the problems of biometric systems, such as a change in illumination and spoof attacks. Using a combination of, hard and soft-biometric, attributes in thermal facial images. The hard-biometric trait, of…
Read MoreImproving the Performance of Hadoop Framework Using Optimization Process in the Information Management
Hadoop has certain issues that could be taken care to execute the job efficiently. These limitations are due to the locality of the data in the cluster, allocation of the jobs, scheduling of the tasks and resource allocations in Hadoop. Execution in the mapreduce remains a challenge in terms of efficiency. So, an improved Hadoop…
Read MoreA Novel Strategy For Prompt Small Cell Deployment In Heterogeneous Networks
Popularity and a_ordability of smart phones and other data hungry devices add exponentially to the tra_c demand of existing cellular networks. Cell densification and small cell deployment over existing macrocell has been identified as an e_ective solution to high tra_c demand predicted for future wireless networks like 5G. Small cells are deployed over existing macrocells…
Read MoreA Proposed Architecture for Parallel HPC-based Resource Management System for Big Data Applications
Big data can be considered to be at the forefront of the present and future research activities. The volume of data needing to be processed is growing dramatically in both velocity and variety. In response, many big data technologies have emerged to tackle the challenges of collecting, processing and storing such large-scale datasets. High-performance computing…
Read MoreMRI images Enhancement and Brain Tumor Segmentation
Brain tumor is the abnormal growth of cancerous cells in Brain. The development of automated methods for segmenting brain tumors remains one of the most difficult tasks in medical data processing. Accurate segmentation can improve diagnosis, such as evaluating tumor volume. However, manual segmentation in magnetic resonance data is a laborious task. The main problem…
Read MoreThe Visualization of Cattle Movement Data in The State of Pará in 2016 Through Networks of Animal Transit Graphs and Guides
Animal movement is inherent in the marketing between the rural productive units, establishing space-time connections between them. The relational nature of such information is kept in the Animal Transit Guides (GTA), a mandatory issuance in Brazil. When evaluating such set of information, this work aimed at characterizing the bovine movement network in the state of…
Read MoreTextural Analysis of Pap Smears Images for k-NN and SVM Based Cervical Cancer Classification System
Early detection and treatment of cervical cancer is crucial to patients’ recovery with a reported success rate of nearly 100%. Presently, Pap smear test which is a visual inspection of cells collected from the ectocervix is the screening tool mainly used in cancer prevention programs. The Pap smear is relatively easy to handle however, it…
Read MoreAn Aggregation Model for Energy Resources Management and Market Negotiations
Currently the use of distributed energy resources, especially renewable generation, and demand response programs are widely discussed in scientific contexts, since they are a reality in nowadays electricity markets and distribution networks. In order to benefit from these concepts, an efficient energy management system is needed to prevent energy wasting and increase profits. In this…
Read MoreInterference Avoidance using Spatial Modulation based Location Aware Beamforming in Cognitive Radio IOT Systems
The Internet of Things (IOT) is a revolutionary communication technology which enables numerous heterogeneous objects to be inter-connected. In such a wireless system, interference management between the operating devices is an important challenge. Cognitive Radio (CR) seems to be a promising enabler transmission technology for the 5G-IOT system. The “sense-and-adapt” smart transmission strategy in CR…
Read MoreAn Advanced Algorithm Combining SVM and ANN Classifiers to Categorize Tumor with Position from Brain MRI Images
Brain tumor is such an abnormality of brain tissue that causes brain hemorrhage. Therefore, apposite detections of brain tumor, its size, and position are the foremost condition for the remedy. To obtain better performance in brain tumor and its stages detection as well as its position in MRI images, this research work proposes an advanced…
Read MoreTwo-Stage Performance Engineering of Container-based Virtualization
Cloud computing has become a compelling paradigm built on compute and storage virtualization technologies. The current virtualization solution in the Cloud widely relies on hypervisor-based technologies. Given the recent booming of the container ecosystem, the container-based virtualization starts receiving more attention for being a promising alternative. Although the container technologies are generally considered to be…
Read MoreBuilding an Efficient Alert Management Model for Intrusion Detection Systems
This paper is an extension of work originally presented in WITS-2017 CONF. We extend our previous works by improving the Risk calculation formula, and risk assessment of an alert cluster instead of every single alert. Also, we presented the initial results of the implementation of our model based on risk assessment and alerts prioritization. The…
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 MoreComparison of K-Means and Fuzzy C-Means Algorithms on Simplification of 3D Point Cloud Based on Entropy Estimation
In this article we will present a method simplifying 3D point clouds. This method is based on the Shannon entropy. This technique of simplification is a hybrid technique where we use the notion of clustering and iterative computation. In this paper, our main objective is to apply our method on different clouds of 3D points.…
Read MoreDiscovering Interesting Biological Patterns in the Context of Human Protein-Protein Interaction Network and Gene Disease Profile Data
The current advances in proteomic and transcriptomic technologies produced huge amounts of high-throughput data that spans multiple biological processes and characteristics in different organisms. One of the important directions in today’s bioinformatics research is to discover patterns of genes that have interesting properties. These groups of genes can be referred to as functional modules. Detecting…
Read MoreCall Arrival Rate Prediction and Blocking Probability Estimation for Infrastructure based Mobile Cognitive Radio Personal Area Network
The Cognitive Radio usage has been estimated as non-emergency service with low volume traffic. Present work proposes an infrastructure based Cognitive Radio network and probability of success of CR traffic in licensed band. The Cognitive Radio nodes will form cluster. The cluster nodes will communicate on Industrial, Scientific and Medical band using IPv6 over Low-Power…
Read MoreClean Energy Use for Cloud Computing Federation Workloads
Cloud providers seek to maximize their market share. Traditionally, they deploy datacenters with sufficient capacity to accommodate their entire computing demand while maintaining geographical affinity to its customers. Achieving these goals by a single cloud provider is increasingly unrealistic from a cost of ownership perspective. Moreover, the carbon emissions from underutilized datacenters place an increasing…
Read MoreRadiation Hybrid Mapping: A Resampling-based Method for Building High-Resolution Maps
Abstract— The process of mapping large numbers of markers is computationally complex, as the increase of numbers of markers results in an exponential increase in the mapping runtime. Also, having unreliable markers in the dataset adds more complexity to the mapping process. In this research, we have addressed these two issues and proposed our solution.…
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 MoreImproving the Performance of Fair Scheduler in Hadoop
Cloud computing is a power platform to deal with big data. Among several software frameworks used for the construction of cloud computing systems, Apache Hadoop, which is an open-source software, becomes a popular one. Hadoop supports for distributed data storage and the process of large data sets on computer clusters based on a MapReduce parallel…
Read MorePerformance Evaluation of Associative Classifiers in Perspective of Discretization Methods
Discretization is the process of converting numerical values into categorical values. Contemporary literature study reveals that there are many techniques available for numerical data discretization. The performance of classification method is dependent on the exploitation of the data discretizing method. In this article, we investigate the effect of discretization methods on the performance of associative…
Read MoreSchizophrenia Prediction Using Integrated Imaging Genomic Networks
In order to increase the diagnosis accuracy of schizophrenia (SCZ) disease, it is essential to comprehensively employ complementary information from multiple types of data. It is well known that a network is a general method for analyzing relationships between patients, with its nodes representing patients and its edges showing relationships between them. In this study,…
Read MoreComputational Intelligence Methods for Identifying Voltage Sag in Smart Grid
In recent years pattern recognition of power quality (PQ) disturbances in smart grids has developed into crucial topic for system equipments and end-users. Undoubtedly analyzing the PQ disturbances develop and maintain smart grids effectiveness. Voltage sags are the most common events that affect power quality. These faults are also the most costly. This paper represents…
Read MoreInternet of Things: An Evolution of Development and Research area topics
Internet of Things (IoT) is a hot topic in the Europe Union (EU). In the year of 2015 the EU established an Alliance of Internet of Things Innovation (AIOTI) and this alliance included the IoT European Research Cluster (IERC) on the Internet of Things in the work group 01. IERC was established in 2007 and…
Read MoreMobi-Sim: An Emulation and Prototyping Platform for Protocols Validation of Mobile Wireless Sensors Networks
The objective of this paper is to provide a new simulator framework for mobile WSN that emulate a sensor node at a laptop i.e. the laptop will model and replace a sensor node within a network. This platform can implement di?erent WSN routing protocols to simulate and validate new developed protocols in terms of energy…
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