bluuebunny/crossref_metadata_2025_split huggingface dataset:
Management Information System for Monitoring and Inspection of the Implementation of Universities
Authors: Gerit John Rupilele Frits , Soulis Irwan , Palilu Aram , Hasibuan Abdurrozzaq , Fransisca Winesty Tutupary Ontje , Alfret Goraph Frets , Sidete Herman , Mouw Erland , Laritmas Selfianus , Tondo Simson , Jamil Mohamad , Dara Utama Mutiara , Tahitu Amelia , Freedom Nanuru Ricardo 
Published: April 2019

Inspection of Universities infringement (PT) is one of Controlling, Supervising and Guidance (dalwasbin) activities aimed at developing problematic universities in order to be back on track and able to run Tri Dharma of Higher Education in accordance with National Standard of Higher Education. Based on the results of evaluation and inspection of Higher Education in 2017 at Coordination of Private Higher Education Region XIV there found 29 Universities out of 61 Universities that committed violations. Management of infringement inspection of Higher Education requires the role of information technology due to the geographic area of the Higher Education and management of Higher Education inspection that is still manual causing management to be ineffective and inefficient. Coordination of Private Higher Education Region XIV requires an information system that can support and assist data of infringement in universities and management of universities inspection. The design of information system in this research used waterfall method. The design of system models used unified modeling language diagrams (UML) including use case diagrams and activity diagrams. The design of this information system generated a system that can support the management of integrated and centralized infringement inspection to facilitate the inspection, monitoring and reporting of inputs and information for Coordination of Private Higher Education and the ministry in mapping the institutional quality Higher Education.
Emprical Study of Iot Solution for The Security Threats In Real Life Scenario: State of The Art
Authors: Bala Murugan C , Koteeswaran S 
Published: April 2019

IoT technology and applications represents security as a significant issue for facilitating the tremendous implementation. Devoid of IoTs technology ensures the device level confidentiality, privacy and authenticity. The applicable users are not going to undertake answers for security in IoT in huge scale. The earlier stage deployments of IoT devices are primarily based on RFIDs technology which results in simplest, security solutions inside the principal been devised in an advert hoc manner [8]. This brings the fact that such deployments were typically vertically incorporated, with all additives beneath the manage of a single administrative entity. In the angle of an IoT eco-system, in which unique person may be worried in a given software state of affairs. One person owing the physical operations of sensors, one stakeholder deals with the statistics and processing them and other numerous stakeholders supplies different services based totally on such statistics to the customers. This leads to numerous variety of safety demanding situations and security for the IoT. In this paper, we address the revisited security issues and discuss the critical safety protection conditions of Internet of Things era into a mainstream. To support this, the three key problems requiring cutting-edge techniques includes are data confidentiality, privacy and trust.In this review, we presented net factors with architectural design goals of IoT. We surveyed security and privacy issues in IoTs. Also the discussion on several open issues based on the privacy and security is addressed. Many real time applications of IoTs in real life treats the security issues of IoT as a main factor. Thus the IoT of complicated security issues have been anticipated the researchers to address.
A Study on Machine Learning: Elements, Characteristics and Algorithms
Authors: Chokkanathan K , Koteeswaran S 
Published: April 2019

Machine learning algorithms are used immensely for performing most important computational tasks with the help of sample data sets. Most of the cases Machine learning algorithms will provide best solution where the programming languages failed to produce viable and economically cost-effective results. Huge volume of deterministic problems are addressed and tackled by using the available sample data sets. Because of this now a days machine learning concepts are extensively used in computer science and many other fields. But still we need to explore more to implement machine learning in a specific field such as network analysis, stock trading, spam filters, traffic analysis, real-time and non-real time traffic etc., which may not be available in text books. Here I would like to discourse some of the key points that the machine learning researchers and practitioners can make use of them. These include shortcomings and concerns also.
Analysis of modern construction projects using montecarlo simulation technique
Authors: Arunmohan A. M. , Lakshmi M. 
Published: April 2019

Today, Construction based Industry is the prospering industry which has a high economical influence on any nation. Delay in the huge construction project increases the total project cost. Henceforth, uncertainties as well as risks must be significantly regarded during the project. For organizing and completing the projects in a financially, timely and qualitatively accountable manner, careful scheduling of projects is compulsory. Effectual scheduling of project assures project success. This study concentrates on qualitative analysis, risk identification, together with quantitative analysis. The targets are i) to ascertain the key risk aspects that disturb the project schedule, and ii) to find the probability of finishing the project within specified time. Questionnaires are distributed amongst 20 industry practitioners with disparate experience from [1] to [25] years. Quantitative analysis is made by the methods like Monte Carlo simulation (MCS) and PERT. @RISK by Palisade corp. is utilized for MCS.
A Hybrid AFSS-SHC Optimization Methodology for Balancing the Load Efficiently in Cloud Environment
Authors: J Aswini , Malarvizhi N , K Anitha. , . . 
Published: April 2019

Cloud computing helps to share data and provide many resources to users. Users pay only for those resources as much they used. Rapid increase in load to these cloud framework cannot be predicted. Load balancing is one of the issues in cloud computing that distributes the workload to the nodes in such a way no node is overloaded or under - loaded. Load balancing is a main challenge in cloud environment. In this work, scheduling algorithm is applied for load balancing by considering the cost of task execution and make span. This scheduling algorithm efficiently maps task to available nodes in cloud and it is beneficial to user and service provider. Load balancing segregates assignments of tasks among all available virtual machines from datacenters. Assignment of tasks to virtual machines can be done with minimum delay. To enhance the make span, resource utilization, our proposed framework utilizes AFSS-SHC load balancing strategy. A metaheuristics swarm intelligence algorithm which is NP-hard have been suggested to balance load across devices. The algorithms taken into account are-HEFT,PSO and PSO-HC. The proposed methodology AFSS-SHC optimized the task scheduling. Random tasks have been taken for this purpose and simulated to show that the proposed methodology works efficiently to reduce the make span of tasks to reduce the cost.
A Survey on Image Fusion Requirements, Techniques, Evaluation Metrics, and Its Applications
Authors: N. Narsaiah M , Vathsal S , Venkat Reddy D 
Published: April 2019

Fusion refers to combining two or more distinct things, the main objective of employing fusion is to generate results that provides the most detailed, reliable and accurate information possible. The image fusion is one of the main branchof data fusion. In image fusion the images are fused at different levels of images like pixel, feature and decision level. The necessity of image fusion for high resolution on multispectral and panchromatic images or realtime images for better vision. This paper reviews the general requirements of image fusion, widely used image fusion techniques such as PCA,IHS,DWT,NSCT etc.,summarizes the Quality Assessment Metrics in terms of metric, description and its principle, finally image fusion applications in various fields such as object detection, object identification, optimization and pattern reorganization, medical imaging, etc.,
Multinode Cluster Analysis for Prediction of Heart Disease Using Biglm Algorithm
Authors: Leelavathy J , S.Selva brundha Dr 
Published: April 2019

The manuscript proposes a novel approach to uncover pattern from a huge chunk of data with minimal time consumption. The goal of the manuscript is to build a robust predictive model to handle big data in patient data. The manuscript follows a master-slave approach. The training data is divided into n number of chunks and processed. The data involves 32,96,168 row vectors and each row vector holds 14 attributes. The model is given a row vector with 14 attributes whether the system could predict the target class by linear modeling. From the experimentation done in single master and four slave setup, we infer that the system could fit a linear model in 1800 seconds. A comparative study has been made on training the huge chunk of data in a standalone device and in master-slave devices. From the experimental analysis, we infer that the training time of the proposed approach has been reduced by more than half since the proposed approach divides the huge chunk of data into independent chunks and computation is done at multiple nodes.
Space Vector Pulse Width Modulation Method to Reducing a Switching Loss in Inverter
Authors: M.Revathi S. , R.Balamurugan C. , Shanmugasundaram N. 
Published: April 2019

In This paper proposedÂ an area space Â vector PWMÂ technique Â thatÂ reducesÂ switchÂ victims ofÂ anÂ electrical converter Â mainly efficiently by two-phase modulationÂ technique. This technique chooses the most favorable one Â that Â minimizes Â a replacement Â switchÂ (SW) defeat judgment Â supportedÂ lessening belongings in switch period allowing forÂ sectionÂ currents in numerous lessening patterns. This paper proposes Â anÂ basic Â curved Â PWM Â techniqueÂ . The Â planned Â techniqueÂ created Â itÂ attainable Â toÂ scaleÂ back Â range Â of Â switch Â of Â theÂ biggest Â or Â secondÂ major presentÂ sectionÂ .Â And itÂ willÂ mechanicallyÂ acclimatizeÂ toÂ weightÂ circumstancesÂ with Â variedÂ power factors. Calculated switch woundedÂ area unit condensed toÂ regardingÂ 50% Â by theÂ planned technique.Â Â
Smart Technological Learning Conceptual model
Authors: Sarma Cakula 
Published: April 2019

Lifelong learning in one of most important aspects of nowdays educational system, which is understood as continuation of the previously acquired education and the enrichment of the professional skills according to the demands of the vocation in question. It is very important to figure out the most effective technological solutions and principal directions for implementing work-based learning strategies in the learning process. New smart learning individually oriented methodology has been developed based on human individual perception for fast growing information and big data society.
An Encrypted Log File Keylogger System for Parental Control
Authors: S. Li L , M. Fauzee Z , Zamin N , Kamarudin N , A.Sabri N , S.Nik Ab Aziz N 
Published: April 2019

Keystroke logging, often referred to as keylogger, keylogging or keyboard capturing, is the process of recording all the pressed keys on a keyboard autonomously so that the person who is using the keyboard is unaware that their actions on the computer are being monitored. In the world of cyber-crime, keylogger tool has been used mostly for malicious purposes such as stealing personal information and credit card details. However, for ethical purposes, keylogger can be useful in terms of monitoring user’s activities without being noticed. For instance, parents can use keylogger to monitor their child’s activity on the web. The log file is used to store the recorded keystrokes. However, current log files in keylogger are not encrypted, which can be easily hacked for malicious purposes. This paper proposes a new software based keylogger with log file encryption to increase the keylogging security towards Industrial Revolution 4.0.
Emotional Classification of Acoustic Information With Optimal Feature Subset Selection Methods
Authors: Swarna Kuchibhotla Dr , Niranjan M.S.R Mr 
Published: April 2019

This paper mainly focuses on classification of various Acoustic emotional corpora with frequency domain features using feature subset selection methods. The emotional speech samples are classified into neutral, happy, fear , anger, disgust and sad states by using properties of statistics of spectral features estimated from Berlin and Spanish emotional utterances. The Sequential Forward Selection(SFS) and Sequential Floating Forward Selection(SFFS)feature subset selection algorithms are for extracting more informative features. The number of speech emotional samples available for training is smaller than that of the number of features extracted from the speech sample in both Berlin and Spanish corpora which is called curse of dimensionality. Because of this feature vector of high dimensionality the efficiency of the classifier decreases and at the same time the computational time also increases. For additional improvement in the efficiency of the classifier a subset of features which are optimal is needed and is obtained by using feature subset selection methods. This will enhances the performance of the system with high efficiency and lower computation time. The classifier used in this work is the standard K Nearest Neighbour (KNN) Classifier. Experimental evaluation proved that the performance of the classifier is enhanced with SFFS because it vanishes the nesting effect suffered by SFS. The results also showed that an optimal feature subset is a better choice for classification rather than full feature set.
A Study on Wavelet Transform Using Image Analysis
Authors: Zeelan Basha CMAK. , M. Sricharan K , Krishna Dheeraj Ch , Ramya Sri R 
Published: April 2019

The wavelet transforms have been in use for variety of applications. It is widely being used in signal analysis and image analysis. There have been lot of wavelet transforms for compression, decomposition and reconstruction of images. Out of many transforms Haar wavelet transform is the most computationally feasible wavelet transform to implement. The wave analysis technique has an understandable impact on the removal of noise within the signal. The paper outlines the principles and performance of wavelets in image analysis. Compression performance and decomposition of images into different layers have been discussed in this paper. We used Haar distinct wavelet remodel (HDWT) to compress the image. Simulation of wavelet transform was done in MATLAB. Simulation results are conferred for the compression with Haar rippling with totally different level of decomposition. Energy retention and PSNR values are calculated for the wavelets. Result conjointly reveals that the extent of decomposition will increase beholding of the photographs goes on decreasing however the extent of compression is incredibly high. Experimental results demonstrate the effectiveness of the Haar wavelet transform in energy retention in comparison to other wavelet transforms.
A brief review on Word Sense Disambiguation Approaches
Authors: Kale Swati , Gawande Ujjwala 
Published: April 2019

To deal with the problem of text retrieval, machine translation, query processing, speech processing, the word sense disambiguation (WSD) performs very important role. WSD is an AI complete problem. This paper presents the significance, approaches along with work done in the field of WSD. Apple amount of work has been done in WSD for foreign languages but for Indian languages this issue is still about to concern. This paper tries to find out different limitations and challenges in WSD, based on which better approach will be decided by the researchers to solve the problem of WSD.
TSD Algorithm to Design CA Based Expert System for Pipelining to Stop Urban Flood
Authors: Kumar Neeraj , Arora Geeta , Agrawal Alka , Ahmad Khan Raees 
Published: April 2019

Flood is a frequent disaster disturbing the daily life and sometimes found deadly. Out of all kind of floods, urban flood is avoidable through quick exit of drainage. Urban flood starts water logging that can be eliminated by efficient pipeline structure. A dedicated drainage pipeline structure may facilitate better during urban flood. A Cellular Automata is a theoretical computer science tool used to solve complex problems as well as to design structures. In these days, applications of CA continuously increasing, out of which an application of designing a flood avoidance drainage mechanism using CA based structure presented in this paper. To generate knowledge for an expert system to design a flood free city in initial stage of development of a city this paper presents a structure for maximum way of exit. This structure including tanks connected at every corner to minimize the dependency on ground water and reuse the rainwater. In order to avoid flood, minimum size of tanks has been calculated by proposed Tank Size Descriptor (TSD) algorithm with the help of actual rainfall data. With the help of TSD algorithm any expert system of civil engineering will be able to suggest a design of a flood free city using hexagonal shapes within the cellular automata.
An Efficient Improved Weighted Round Robin Load Balancing Algorithm in Cloud Computing
Authors: N Manikandan , A Pravin 
Published: April 2019

Cloud Computing is an era when various trends showed up. It is the type of development, based solely on the Internet. The computer technology has brought in several changes along the years. SaaS is an architecture that comes under computing technology, involving the use of powerful processors, that helps in transforming data centers, scaling services involving computing technology across all fields. Various trends are opening in the field of Cloud Computing, developed mainly on Internet basis and use of computing technology. The computing architecture of SaaS along with powerful processors, are transforming data centers into a huge scale of pools of computing services. Balancing load efficiently is one of the key areas involved in cloud computing. Services that are of very high quality can be subscribed for lower cost, along with completely reliable network connections with their bandwidth being increased , providing a flexible service residing in remote data centers. Load Balancing is the concept involved in the storage of computing resources. It is the partition of work which requires processing between two or more number of computers and/or CPUs, storage devices which ultimately leads to providing higher efficiency with much faster service. The improved WRR algorithm which is improved has been proposed in order to distribute the workload efficiently, thereby enhancing various other features that are associated with it.
An Experimental Study on Structural Behavior of Lathe Waste in Conventional and Self-Compacting Concrete
Authors: Bhavana Aluri , L. Sai Rangarao M 
Published: April 2019

To diminish the effect on condition and impact of soil disintegration the lathe waste or steel scrap i.e. machine squander, which is acquired from mechanical machines, can be utilized as reusing material in the concrete blend. This project emphasizes the study on self-compacting concrete (SCC) and conventional concrete (CC) with the addition of machine squander. The investigation is done with and without the addition of steel scrap in conventional and self-compacting concrete. The optimal content of steel scrap is utilized out of 1%, 2%, and 3%. Multiple trail mixes were carried out to find out the optimal content of steel scrap. The fresh and hardened properties of concrete are resolved. The test completed determining flow properties of SCC are Slump, L-box, V-funnel tests. The flexural, compressive and split tensile strengths of concrete were resolved. A total 8 beam specimens were cast and tested under simply supported condition. Deformational behavior was compared between conventional concrete, beam specimens to SCC concrete beam specimens.
An efficient scheme to support direct revocation in cloud computing using CPABE: The approach with less time constraints
Authors: G. Dande Rupali , Amol D. Potgantwar Dr , Amol D. Potgantwar Dr 
Published: April 2019

Secure Data sharing is a major issue of concern in cloud computing. CPABE is well known encryption technique for dealing with the problem of data security over network. Most of the files have multilevel access hierarchy especially in health care and military domain. The hierarchy structure and revocation of shared files is not scrutinized in CP-ABE. In this paper, experts proposed the enhanced method of encryption to support the direct revocation, in which sender specifies the revocation list during encryption of cipher text so that the problem of releasing periodic key update information in indirect revocation is vanished. Here the direct revocation mechanism and file access based hierarchy are merged to get enhanced CPABE. The multilevel access structure is integrated and merged with encrypted files with current access structure. Along with revocation, aim is also to improve the overall system performance with respect to encryption time and decryption time. Experimental result shows the enhanced performance of the proposed system as compared to existing system with respect to time and security constraints. Moreover the scheme is secure under the standard security assumption. Finally, based on the research, it gives forthcoming research direction to expand and implement the scheme in any practical application where security is main concern by proper coalition of the proposed technologies.
The Significance of Delta Wave Among Athletes
Authors: Fauzan Norsiah , Mazlina Ghazali Nor 
Published: April 2019

This article reports on the differences between the physiological response of the brain between athletes and non-athletes by using Quantitative Electroencephalography (QEEG). EEG waves were observed using qEEG and analysis were compared between the two groups. This research involved 41 undergraduates of Universiti Malaysia Sarawak (UNIMAS). The qEEG recordings were made during the Eyes opened, Eyes Closed, and Stroop task conditions to find out the dominant wave during each of the conditions in different region of the brain. The results revealed higher EEG Delta and Beta1 at frontal region (Fp1, Fp2), somatosensory, (C3, P4) and visual spatial area (P3, P4). Delta, Beta and Gamma wave were dominant while the participants were performing the Stroop Task. Coupling of delta and beta oscillations might be due to the athletes’ anxiety during the Stroop task. In Eyes Closed state, delta and alpha wave were dominant at the fronto-parietal attention network area. This study contributes to the development of training protocol for neurofeedback training for athletes in preparation for training of peak performance in any sports activity. It is recommended that extensive analysis should be done on the interaction of delta-gamma oscillations in different parts of the brain to find out its implication on attention and emotion during the cognitive process.