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Keyword: ClusteringStudents’ Preparedness to Learn in e-Learning Environment and their Perception on The MPKT Lecturers’ Readiness to Manage Online Class
This study has two objectives: to determine the level of readiness of first-year undergraduate students at the Universitas Indonesia (UI) and to investigate student’s perception of MPKT (Integrated Character Development course) lecturers’ readiness to manage online learning class. Proportional cluster sampling was applied, and 1466 freshmen from thirteen faculties participated. Data clustering and imputation of…
Read MoreEvent Modeller Data Analytic for Harmonic Failures
The optimum performance of power plants has major technical and economic benefits. A case study in one of the Malaysian power plants reveals an escalating harmonic failure trend in their Continuous Ship Unloader (CSU) machines. This has led to a harmonic filter failure causing performance loss leading to costly interventions and safety concerns. Analysis of…
Read MoreWireless Sensor Networks Simulation Model to Compute Verification Time in Terms of Groups for Massive Crowd
Everyone needs fast response or output against its request or need. Therefore, technologies are used to make the processing fast and accurate according to our needs. But in some situations, still we need to do more. Especially, when we need to process a massive or huge crowd of people in limited time frame such as…
Read MoreElasticity Based Med-Cloud Recommendation System for Diabetic Prediction in Cloud Computing Environment
Day to day huge medical data have been accumulating for diabetic diseases. The complexity of storing, processing ,analyzing and predicting the data related to diabetics is not so easy for healthcare professionals .The prediction of accurate results also has the limitation due to scale of data increasing worldwide for patients, symptoms and test results .In…
Read MoreHigh-Performance Computing: A Cost Effective and Energy Efficient Approach
The world is witnessing unprecedented advancements in ICT (Information & Communication Technology) related fields. These advancements are further boosted with the emergence of big data. It goes without saying that big data requires two major operations: storage and processing. The latter is usually provided through High-Performance Computing (HPC) which is delivered through two main venues:…
Read MoreLEACH Based Protocols: A Survey
Advances in the world of communications and information technology, as well as the urgent necessity to monitor particular areas and regions, have led to a considerable and influential development in the world of wireless sensor nodes. As they are small, low-cost multi-purpose nodes with limited energy and capabilities. The most important points that deserve research…
Read MoreA Novel Approach of Smart Logistics for the Health-Care Sector Using Genetic Algorithm
The heath-care sector has confronted significant difficulties in the past few years due to several issues such as insufficient human resources, budget cuts, and shortage of equipment and drugs. The logistics in the health-care sector take an extensive part of the budget, especially since it is the main axis to provide the hospital’s pharmacies with…
Read MoreProjection of Wireless Multipath Clusters Using Multi-Dimensional Visualization Techniques
Advances in channel modeling allow wireless communication designers to accurately model and understand the channel’s phenomena within different propagation scenarios. A precise channel model results in the wireless system’s optimized performance while considering trade-offs due to the effects of the channel. The geometric-based stochastic channel model considers different interacting objects affecting the parameters using the…
Read MoreStudent’s Belief Detection and Segmentation for Real-Time: A Case Study of Indian University
This paper has explored the technology beliefs of university students considering four parameters. We have proposed an automatic belief identification system for academic institutions. For this, we used two different clustering algorithms to segment the student group with different beliefs about the technology. In the Hierarchical Clustering (HC), the Agglomerative approach was followed. The beliefs…
Read MoreA Typological Study of Portuguese Mortality from Non-communicable Diseases
The most common non-communicable diseases, such as cardiovascular diseases and cancer, are a problem in global and national growth. The World Health Organization considers it a priority to study the specific causes of these diseases for trend monitoring. The aim of this paper is to identify a hierarchy of clusters of Portuguese mortality by non-communicable…
Read MoreKnowledge Mapping of Virtual Academic Communities: A Bibliometric Study Using Visual Analysis
This study aims to provide a systematic and complete knowledge map for researchers in the field of virtual academic communities (VACs) and to help them quickly understand the key knowledge, evolution trends and research frontiers. This paper adopts the bibliometric method, with the help of bibliometric analysis software Citespace and VOSviewer quantitative analyze the retrieved…
Read MoreMentoring Model in an Active Learning Culture for Undergraduate Projects
Senior projects allow students to move the learning process from basic knowledge to an interdisciplinary approach. The purpose of this research is (1) to analysis attitude and perception, which is a collaboration between teachers and students to develop a model for clustering of appropriate advisors and advisee who cooperate in senior project, and (2) to…
Read MoreCluster Centroid-Based Energy Efficient Routing Protocol for WSN-Assisted IoT
Wireless sensor network is highly resource constrained, where energy efficiency and network lifetime plays a major role for its sustenance. As the sensor nodes are battery operated and deployed in hostile environments, either recharging or replacement of batteries in sensor nodes is not possible after its deployment in inaccessible areas. In such condition, energy is…
Read MoreA Novel Hybrid Method for Segmentation and Analysis of Brain MRI for Tumor Diagnosis
It is difficult to accurately segment brain MRI in the complex structures of brain tumors, blurred borders, and external variables such as noise. Much research in developing as well as developed countries show that the number of individuals suffering tumor of the brain has died as a result of the inaccurate diagnosis. The proposed article,…
Read MoreStatistical Aspects of the Environment of Albanian Students Who Were Admitted to Higher Public Education Institutions in the Year 2014
The research presents a statistical analysis that characterize the environment of the admitted students to Higher Public Education Institutions, by providing an overview of student’s distribution to the courses of studies offered by universities in Albania, such as, economy, medicine, technical etc., and grouping them according to the relative density of 38 (thirty eight) administrative…
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 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 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 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 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 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 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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