Reviewerly/exHarmony huggingface dataset:
Advanced Principal Component Analysis for Analysis of Optimized Credit Card Fraud Detection

The information has turned out to be increasingly more imperative to people, associations, and organizations, and thusly, shielding this delicate information in social databases has turned into a basic issue. In any case, in spite of customary security systems, assaults coordinated to databases still happen. In this way, an intrusion detection system (IDS) explicitly for the database that can give security from all conceivable malignant clients is important. In this paper, we present the Principal Component Analysis (PCA) technique with weighted voting in favor of the assignment of inconsistency location. PCA is a diagram based procedure reasonable for demonstrating bunching questions, and weighted casting a ballot improves its capacities by adjusting the casting a ballot effect of each tree. Trials demonstrate that RF with weighted casting a ballot shows a progressively predominant presentation consistency, just as better blunder rates with an expanding number of trees, contrasted with traditional grouping approaches. Besides, it outflanks all other best in class information mining calculations as far as false positive rate and false negative rate.
Image Retrieval with Fusion of T hepade’s Sorted B lock Truncation C oding n ary based Colo r and Local Binary Pattern based Texture F eature s with D ifferent C olor Plac es

In these years, there has been a gigantic growth in the generation of data. Innovations such as the Internet, social media and smart phones are the facilitators of this information boom. Since ancient times images were treated as an effective mode of communication. Even today most of the data generated is image data. The technology for capturing, storing and transferring images is well developed but efficient image retrieval is still a primitive area of research. Content Based Image Retrieval (CBIR) is one such area where lot of research is still going on. CBIR systems rely on three aspects of the image content namely texture, shape and color. Application specific CBIR systems are effective whereas Generic CBIR systems are being explored. Previously, descriptors are used to extract shape, color or texture content features, but the effect of using more than one descriptor is under research and may yield better results. The paper presents the fusion of TSBTC n-ary (Thepade's Sorted n-ary Block Truncation Coding) Global Color Features and Local Binary Pattern (LBP) Local Texture Features in Content Based Image with Different Color Places TSBTC n-ary devises global color features from an image. It is a faster and better technique compared to Block Truncation Coding. It is also rotation and scale invariant. When applied on an image TSBTC n-ary gives a feature vector based on the color space, if TSBTC n-ary is applied on the obtained LBP (Local Binary Patterns) of the image color planes, the feature vector obtained is be based on local texture content. Along with RGB, the Luminance chromaticity color space like YCbCr and Kekre’s LUV are also used in experimentation of proposed CBIR techniques. Wang dataset has been used for exploration of proposed method. It consists of 1000 images (10 categories having 100 images each). Obtained results have shown performance improvement using fusion of BTC extracted global color features and local texture features extracted with TSBTC n-ary applied on Local Binary Patterns (LBP).
Non-English Major Students Perception Toward the Teaching of English as a Compulsory Subject

English as a compulsory subject in university means that students from various majors are mandated to take English as one of their subjects in university. This research aims to investigate students perceptions toward the teaching of English as a compulsory subject at University. Despite many research have been conducted related to the subject, it seems salient to shed some light on this area especially due to the importance of mastery of the English language these days. The result of the research showed that students have a positive attitude toward the teaching of the English language as a compulsory subject. One of the most important discoveries lies in the students being motivated when the English being taught is closely related to their major. Last but not the least, due to some limitation of the studies suggestion for further research is expected.Keywords: perception, teaching, Compulsory subject
A Fear State Judgement System for Alleviating Fear of Heights Gradually in VR

VR has been expanding into various fields in recent years.The medical field is no exception to this trend.For example, VR technology is expected to be used to treat acrophobia, the most common phobia.There are many patients with acrophobia, and many of them have difficulties in their daily lives.One way to solve this problem is to treat acrophobia with VR.However, VR treatment is a big problem in the treatment of phobia because there are many individual differences.In this study, we propose a system that can acquire the fear state of an individual in real-time by vital sensing and can treat phobia of altitude gradually adjusted to the individual using a placebo effect.
Online Crime File Station

The task titled as "online crime file station" is web-based application.This application gives facility for reporting online crimes, complaints, missing person, show most-wanted person details, mailing as well as visiting.Any number of customers can associate with the server.Every client first makes their login to server to demonstrate their appearance.The server can be any web server.
PENERAPAN FEATURE WEIGHTING OPTIMIZED PADA NAÏVE BAYES UNTUK PREDIKSI PROSES PERSALINAN

Birth of a baby is something that is very desirable for every married couple. All parties expect safety for mothers and babies who have just been born. Medical personnel make various efforts to help the delivery process run smoothly and the mother and baby survive. But in the labor process not all the baby's birth process runs smoothly. Problems often occur during labor. There are several obstacles so that there is a risk of labor, namely maternal and infant mortality. Every mother wants to be able to give birth to a baby normally, but due to medical reasons the delivery process is done by cesarean. The act of choosing a type of delivery faster can affect the safety of the mother and baby. The selection of the cesarean method is carried out late so it will increase the risk of maternal and infant mortality. For this reason, it is necessary to conduct research by using labor delivery data so that they can choose the right type of labor. In this study the classification of maternity labor will be carried out with data mining methods, namely Naive Bayes, which are improved by using the Optimize Weight (PSO) method. Naive Bayes was able to produce a high accuracy value for processing labor data for mothers, namely 94%. The final results of this study obtained the value of naïve bayes performance that can be improved by the Optimize Weights (PSO) method to be better at 98%
Dehydroxylation of Minerals of Gadisunkapur Area with Special Reference to FTIR and Thermal Study

This paper attempts to explain the presence of OH group for micas along with some sulfate, chlorite, quartz and feldspar minerals. These minerals are found to be associated with barite vein, metasediments (quartz-chlorite schist), metarhyolite and varieties of granitic rocks of Gadisunkapur area of Hungund-Kushtagi Schist belt. The samples were collected in and around Gadisunkapur village of Bagalkote district, Karnataka and further processed to determine OH group anion in different minerals present based on FTIR and Thermal studies such as Thermogravimetric analysis (TGA) and Differential Thermal analysis (DTA). The high temperature dehydroxylation is investigated using this analysis. Furthermore, present study indicates the presence of different extra species (CO2, CO32- and OH-). The results show the incorporation of CO2 into the structures due to heating or enhanced by the dehydroxylation process.
A Comparative Analysis of Evidence-based Selection, Professional Selection, and Selection by Approval Plan

This study compares three different models for selecting e-books for a research library’s collection. From 2013 to 2018, the University of Oklahoma Libraries contracted with Elsevier for an evidence-based selection (EBS) agreement. The titles in that EBS package were compared to the approval plan parameters to determine which books would have been purchased on approval during those years if Elsevier had been included among the publishers profiled. Subject librarians also made hypothetical selections as though they were placing firm orders from this collection. The approval plan selections and librarians’ selections were compared to usage data to determine how closely each selection model matched patrons’ choices.
THE ROLE OF PERCEIVED UTILITARIAN VALUE AND STUDENT SATISFACTION IN MEDIATING THE EFFECT OF SERVICE QUALITY AND IMAGE TOWARDS LOYALTY AT UNIVERSITIESIN BANDA ACEH

This study intends to examine the Role of Perceived Utilitarian Value and Student Satisfaction in Mediating the Influence of Service Quality (Servqual) and University Image on Loyalty at Universities in Banda Aceh city, Indonesia.This research was conducted on students of the Muhammadiyah University, SerambiMekkah University, and the Getsempena National Education and Teaching College, with a population of 1916 people.The sampling technique used is the Probability Sampling Technique.While the sampling method used was stratified random sampling to obtain a sample of 170 students.Data were analyzed using Structural Equation Modeling (SEM) with the help of Amos software.The results of the research found that all hypotheses proven in this research were accepted.This means that student loyalty in private university institutions in Aceh does have a determinant variable Servqual, University Image, Perceived Utilitarian Value, Customer Satisfaction, both of which affect loyalty directly or indirectly.The novelty of the research lies in the research model that results from the integration of previous causality theories and on new objects.Further researchers are expected to contribute by adding other variables such as student competence and religiosity.
A Robust Watermarking Method for an Authentication of Video Surveillance Applications

The problem of authenticating the video content is the major role of any automated video surveillance systems (AVS). This research work delivers an approach to authenticate the surveillance video which can be used by attorneys to prove their clients using Digital Watermarking. The digital watermark gives an assurance that the provided video surveillance frame is not tampered. In this paper, we proposed a robust video watermarking approach for an authentication of video surveillance applications. The digital watermark is embedded into the Discrete Wavelet domain of the identified key frames using holoentropy. Here, the pixel map will be optimallygenerated for the watermarking and the image embedding using the proposed classifier using Moth – flame - Rider optimization based Neural Network (MF-ROA-based NN) will generate the optimal map prediction based on the fitness measure, such as wavelet coefficient, energy, entropy, loop coefficient, and standard deviation, respectively. This optimal map is used for both embedding and extraction. The experimental results proves that the proposed systems can authenticate the surveillance video frames against various attacks when compared to the existing systems.
Quality assessment of the cloud-oriented environment for flipped learning of the future IT specialists

The article discusses the essence of the qualimetry approach and defines its role in the procedures for assessing the quality of the cloud-oriented environment for flipped learning in the process of training future IT specialists in higher education institutions. It offers a basic factor-qualimetry model for assessing the quality of such an environment, which can serve as a tool for its current monitoring and periodic review in the implementation of the internal quality assurance system of the educational process. The proposed basic factor-qualimetry model is based on the relevant criteria and indicators that have a specific weight. When building a factor-qualimetry model to assess the quality of the cloud-oriented environment for flipped learning of future IT professionals, 3 criteria and 26 evaluation indicators were identified, which were analyzed using the method of expert assessment. An example of calculating the quality of the environment is given. The obtained results allow to form individual approaches to the assessment of the quality of cloud-oriented environments, which are designed and applied in higher education institutions.
Comparative Analysis of the Impact of Server Operating Systems on Web Site Performance

This work analyses the impact of the server operating system on the overall performance of hosted web sites.In the paper, we are presenting the results of comparing the influence of the two most common server operating system families, Windows and the GNU/Linux distributions.Through experiments, we have collected data based on which we have concluded the impact of these operating systems on the performance of a web site developed using the most commonly used web platform -WordPress.The experiment was set up in such a way as to eliminate the impact of hardware on our measurements, which is done by using the same hardware, network and matching conditions.The experiment was conducted with a large number of repetitions to reduce relative errors in measurements.The performance analysis covers files of different sizes and types, including text and multimedia content typical for modern web sites.
Upcoding Fraud Discovery in the Economical Fields Using Block Chain Technology

Discovering the fraud is the most important now a days as it is observed in every sector starting from Banks to schools. Therefore it is significant discover this fraud so that the loss could be zero. Upcoding fraudulence is one kind of fraud observed now days in which the provider gains extra monetary by coding a solution in spite it is taken by the claimer the fraud will claim the insurance one more time without allusion of certified person. Owed to this claimer could misplace assurance still he is endorsed person to increase due to fraud has already claimed the monetary. With the help of expert system and data withdrawal it’s easier to recognize scam. With superior technologies like block chaining it’s easier to detect fraud in the addition of fraud it is also known the history of the fraud. This paper concentrates on up coding Fraudulence discovery using block chain technology.
Retraction: Cloud Computing in Libraries and Higher Education: An Innovative User-Centric Quality of Service Model

This article refers to:RETRACTED ARTICLE: Cloud Computing in Libraries and Higher Education: An Innovative User-Centric Quality of Service Model
One-Stop Course Readings: a Breakthrough in Campus Collaboration

&lt;p&gt;What is meant by “one-stop course readings”?&lt;/p&gt; &lt;ul&gt; &lt;li&gt;Course readings of all formats delivered through Blackboard, the course management system&lt;/li&gt; &lt;li&gt;The Library does the copyright pre-checking for printed course packs processed by the Bookstore &lt;/li&gt; &lt;li&gt;Ares becomes [sic] the centralized copyright permissions database for: &lt;/li&gt; &lt;li&gt;the Library’s E-Reserve &amp; Audio Visual services, &lt;/li&gt; &lt;li&gt;the Bookstore &lt;/li&gt; &lt;li&gt;Distance Education (part of Chang School Continuing Ed.)&lt;/li&gt; &lt;/ul&gt;
considerations about training samples and classifiers

we appreciate your comments.10 iterations were performed in relation to the training samples, but we did not report it in the manuscript.Now we will repeat the sampling process but we will evaluate the effects of the training sample size on the results of the classification algorithms.10 subsets of training data will be created by increasing the number of pixels per class in each subset.New pixel-wise classifiers algorithms will also be implemented (DT,KNN, ANN, DNN).
Implementation of Template based Datacenter Broker Policy for Cloud to Improve the QoS

Cloud computing is abstraction of web based services for businesses having dynamic requirements of resources. The cloud offers noteworthy benefits to business world by providing hardware set up, software and management of the system software. It puts in together elastic resources including hardware, software in virtual platform dynamically to meet computing need. The Quality of service parameters (QoS) comprises different parameters like, performance, availability and reliability, response time, throughput and bandwidth etc. There is need for proper monitoring, management of these parameters for effective cloud services and to maintain customer base. An efficient DCB policy reduce the overall execution time of the requested Cloudlets (Jobs/Tasks). An important policy of the Datacenter Broker (DCB) is binding of Cloudlets with an available VMs. For efficient load balancing there is need of proper allocation of cloudlets to the appropriate available VMs as per application requirement. In present study, we proposed a Template Based Resource Provisioning algorithm for effective resource utilization and allocation of Cloudlets to the available VMs in a Datacenter. The proposed method takes into consideration application requirement with its size (Cloudlet length) along with power and capacity of VMs. Experimental are performed using CloudSim under different workload scenario and results are obtained for comparison. The proposed algorithm creates performance supremacy over existing DCB algorithm for high workload.
Applying Agile Methodology in Mobile Software Engineering: Android Application Development and its Challenges

&lt;p&gt; &lt;/p&gt; &lt;p&gt;Highly volatile requirements of mobile applications require adaptive software development methods. Several attempts to address challenges in mobile software engineering have found agile methodology to be appropriate for mobile application development. This project report provides a detailed analysis on various challenges involved in mobile software development which are addressed using Agile-SCRUM methodologies. An efficient mobile software development concept derived from Agile-Scrum methodology is designed in this project. A light-weight Android application for secure and incremental backup has been developed using the proposed methodology. An in-depth illustration of the practical experience in developing the application has been discussed. Unlike other prominent languages like Java, the use of Python for Android platform has emerged recently. Hence developing the secure-backup application in Python was a challenge, which has been dealt in this report. We believe our proposed methodology has a potential to help developers deliver improved quality of mobile applications in short time. Keywords: agile, scrum, mobile software engineering, mobile application, android, python, sl4a&lt;/p&gt;
Deterministic planning in incompletely known domains with local effects

Conformant planning has been traditionally studied in the form of classical planning extended with a mechanism for expressing unknown facts and/or disjunctive knowledge. Despite a sizable body of research, most approaches do not attempt to move beyond essentially propositional planning. We address this shortcoming by defining conformant planning in terms of the situation calculus semantics and use recent advances in the fields of first-order knowledge base progression and query answering to develop a sound and complete conformant planning algorithm capable of handling knowledge defined in an expressive fragment of first-order logic. We implement a prototype planner and evaluate its performance on several existing domains.
Scalable Pattern Recognition and Real Time Tracking of Moving Objects

This paper proposed a new approach for object tracking and pattern recognition of moving objects during real time video streaming. This approach uses motion based multi-object movement techniques for tracking the objects. Moreover, Spectral clustering with Dynamic Time Warping (DTW) and Naïve Bayes method are used for pattern recognition of tracked objects. This system tracks the moving objects collected as a batch of videos then the pattern recognition technique uses for analyzing vehicles movement to determine normal or abnormal behavior. This paper proposes the tracking algorithm for all moving objects and pattern recognition for only moving vehicles. The performance of tracking trajectories is calculated by finding recall and precision values, which are greater than 95%. The experimental result shows that Naïve Bayes is better than spectral clustering for the classification of vehicle trajectories that conforms Naïve Bayes is an effective tool to scale the pattern recognition of moving vehicles.
The economic context of counterfeiting and piracy

Sweden is an advanced, knowledge-based economy that produces highly valued products and services that benefit significantly from intellectual property.Sweden has an open economy, actively participating in global value chains.While these are features of a modern, dynamic economy, they also make Sweden vulnerable to the global risks of counterfeiting and piracy.Illicit trade in counterfeit goods is a vital threat to Swedish industry, government and society.To provide policy makers with solid empirical evidence for taking action against this risk, this OECD report measures the direct economic effects of counterfeiting on consumers, retail and manufacturing industries, and government.It assesses both the impact of imports of fake products to Sweden and the impact of the global trade in fake products on Swedish intellectual property rights holders.The results are alarming.In 2016, world trade in counterfeit and pirated goods that infringe on Swedish brands reduced sales of legitimate Swedish right owners by at least USD 2 billion, or 2% of their annual sales, and lowered the tax revenue of Swedish government by about USD 900 million, or 0.2% of Swedish GDP.A vast majority of lossesincluding more than two-thirds of lost jobs, and three-quarters of foregone tax revenueis due to trade in fake goods outside of Sweden that infringe on Swedish intellectual property (IP) rights.These results underscore the need for co-ordinated international action against IP crime in general and trade in counterfeits in particular.This report is designed to deepen our understanding of the vital risk that counterfeiting poses for global economy, and should help support policy makers as they shape effective solutions to counter this threat.