Reviewerly/exHarmony huggingface dataset:
Improving Speed and Accuracy of Image Retrieval using Elastic Search and Features Nearest Neighbor Search

A developing interest had shown as late in structure closest neighbor search arrangements inside Elastic search–one of the most well-known full-content web indexes. In this paper, we focus explicitly around Elastic search and Features Nearest Neighbor search (ESFNNS), which accomplishes sensitive speed-ups over the current term coordinate gauge. Features Nearest Neighbor search performs the image retrieval, which integrates the features of color, shape, and texture. This will engage an Elastic search with the capacity of quick data retrieval and accuracy when compared to the FENSHSES method.
Cloud Forensics

One of the fast-growing trends in the IT industry today is the widespread use of cloud computing. Developers are using cloud computing platform to develop tools, services, and products for a variety of fields.
Pengaruh Metode Pembelajaran Student Teams Achivement Divisions (STAD) terhadap Hasil Belajar Matematika Siswa Madrasah Ibtidaiyah

This study aims to examine the effect of the Student Teams Achievement Division (STAD) method on the mathematics learning outcomes of grade V students at MIS Yapis Al Falah, Bojonggede District. This study used a pre-experimental method with a pre-post test design, while the sample of this study consisted of 15 grade V students. The results showed that there was an effect of the Student Teams Achievement Division (STAD) method on the Mathematics learning outcomes of class V students as seen from the results of the grades. sig 0.000 &lt;0.05 so also obtained tcount = 7.897 while t table = 2.14. Then t count&gt; ttable (-7,897&gt; 2.14) and it can be concluded that there is an influence between the STAD method on the Mathematics learning outcomes of class V students at MIS Yapis Al Falah. &#x0D;
Conditional Process Model of the Learning Organization in the Dubai Healthcare Sector

UAE healthcare sector has been discussed by many researchers and organizations in the past, but very limited literature is available explaining the factors which can provide control in the hands of healthcare sector leadership to achieve sustainable competitive advantage. The unique cultural environment in UAE healthcare sector requires the control structure based on certain indigenous conditions prevailing in local environment. Three key cultural factors are borrowed from the past literature and model was built to examine the mediating role of the culture of creativity and innovation between the culture of collective leadership and the culture of learning organization. In addition to this, how the leadership commitment moderates the relationship between the culture of collective leadership and the culture of creativity and innovation. The conditional process model, explaining the moderated mediation among these cultural variables, provides knowledge about key relationships among these cultural factors and give better control in the hands of the leadership of the healthcare organizations to achieve sustainable growth and quality of services in the highly competitive environment. The key cultural variables and their interrelationship were borrowed from the author’s previous researches and remodeled them to examine the hypothesized framework on the data collected from the sample of 320 employees working in the five healthcare organizations in Dubai. The “Healthcare Sector Learning Organization Scale” was developed and analyzed by the explorative factor analysis to factor out four variables. The output of the conditional process modeling proposed by Andrew F. Hayes has verified the presence of the culture of creativity and innovation as the mediator in the relationship between the culture of collective leadership and the culture of learning organization. Moreover, the moderating role of the leadership commitment on the relationship between the culture of collective leadership and the culture of creativity and innovation was also significantly verified. Research findings show that organizations in the healthcare sector need regular emphasis on research and development practices to help employees in building and managing new knowledge in order to achieve competitive advantage. In this case, the leadership has a key role to play enabling the organization to transform into the culture of learning organizations by implementing knowledge management processes and support for the experimentation in the day-to-day operations of the organization.
Don't Wanna Cry: A Cyber Crisis Table Top Exercise for Assessing the Preparedness against Eminent Threats

Cyber Security Exercises are emerged as useful tool for assessing and improving preparedness of the organizations and nations against cyber threats. Cyber security exercises of different types &amp; duration with various objectives are conducted across the globe. These exercises vary from quiz type exercises to full simulated attack based exercises. One such type of exercise is Table Top Exercise (TTX). TTX are discussion based exercises involving decision makers of the participating entities to meet and discuss the response during the hypothetical emergency situations. These exercises primarily focused on to clarify roles and responsibilities, assessment of effectiveness of plans and further improvements in cyber security. In this paper we presented Objective, Design and Execution of Cyber Crisis Table Top eXercise (CCTTx) named "Don't WannaCry" conducted for Indian entities. 5 CCTTx involving decision makers from 65 organizations with the objective to encourage self-realization of true cyber security posture of their own entity were conducted in 2017.Exercises were divided into three segments starting with (i) Self-assessment in which participating organization self-assess their cyber security posture in pre-defined 6 domains, followed by (ii) Exercise Play in which participating entity act as a hypothetical entity and respond to the presented cyber crisis situation and finally (iii) Hotwash session was executed with purpose of inducing self-realization of their true cyber security posture. Exercise take away for participants was self-realization and identification of improvement plan to enhance cyber security posture of their entities against the cyber attacks. These exercises are unique in design, execution and their objective of self-realization by the participating entities. Success of these exercises is evident from the feedback and adoption of exercises for domestic purpose by participating organizations.
CODM: an outlier detection method for medical insurance claims fraud

Data is the high dimensional in medical insurance claims management, and there are both dense and sparse regions in these datasets, so traditional outlier detection methods are not suitable for these data. In this paper, we propose a novel method to detect the outliers for abnormal medical insurance claims. Our method consists of three core steps - feature bagging to reduce the dimensions of data, calculating the core of the object's k-nearest neighbours, and computing the outlier score for each object by measuring the amount of movement of core by sequentially increasing k. Experimental results demonstrate our method is promising to tackle this problem.
STRATEGI SKIMMING DALAM MENINGKATKAN EFEKTIVITAS BACA SISWA PADA KELAS XI SMK NURUL JADID PAITON PROBOLINGGO

The objective of this research is to find out the effectiveness of Skimming-Scanning Strategy in improving students reading comprehension. It covered students’ literal, inferential, critical comprehension in three types of text. They were narrative, descriptive, and news item texts. The research applied quasi experimental design. The subject of the research was the second grade students of SMK Nurul Jadid Paiton Probolinggo. The data collected were the students’ reading achievement through test (pretest and posttest). This research was divided into two groups, experimental and control group, the groups consisted of 28 and 27 students, respectively. The result of the data analysis showed that t-test was higher than t-table (6.373&gt;2.000) or Pvalue (Sig.) was smaller than alpha (0.000 &lt; 0.05). It meant that mean score of the experimental group was higher than the control group.
Statistical Methods in the Usage of Correlation and Regression of the Machine Learning Models

The predictive analytics is the most commonly used methodology in the usage of Machine Learning class of algorithms. Based on the values generated at the time of running the algorithm the significance of the model can be estimated. The current work gives a complete focus on P value and the significance levels of the P value in the correlation analysis of the algorithms. Based on the P value the impact of the model can be notified and the interpretation of the results can be done in the efficient way. The other dimension of the work is the usage of statistical functionalities in the regression analysis, most of the researchers are focusing on the shallow usage of regression analysis in the classification of the tasks. The current work explains the complete internals of the regression models available and the usage of the statistical functionalities utilized in the implementation of the corresponding variants of the algorithms. We believe that the current work exclusively helps the upcoming researcher in the areas of regression in the context of the statistical functionalities which are vital in the implementation of the tasks. The outcome of the work is to exploit the correlation analysis with various significance levels and the issues in the processing of the analysis. The another point here is the regression internals with the focus of statistical methods available in the processing of regression variants. The regression analysis involves various types like linear regression, multiple regressions and logistic regression. The current work gives an overview of all these three types of regressions and also the significance of P value in the prediction of outcome. In the examples such as house rate prediction based on the given area, salary of an employee based on the experience level, profit of the start-up companies based on the spending on research, admin marketing and state of the country are best suitable in the explanation of regression.
Design and Development of a Modular K-12 Cybersecurity Curriculum

Prior to joining academia as a faculty, she
Evaluating and Forecasting rate of Counterfeit Banknote Detection

Detection of counterfeit banknotes becoming a major issue in today’s scenario, as it is seems to be weighty aspect in terms of socio-economy of every living being. This paper highlights various distinguishing features of currencies of different countries, having an objective to secure their currency less susceptible from forgery. Afterwards, the paper focuses on analysing and comparing the rate of counterfeit detection with the forecasted rate of counterfeit currency detection. The analysis has been performed using, paired sample t-test and elementary time series forecasting in IBM SPSS 21 and RStudio respectively. Data points from 1999-00 to 2017-18 have been collected from Reserve Bank of India Annual reports under currency management section.
Analisis Tingkat Kepuasan Pengguna Sistem Informasi Kerja Praktek dan Skripsi (SKKP) Menggunakan Metode End User Computing Satisfaction (EUCS)

The advantages of information technology in the education has developed a lot, especially in universities. An example of the application of tertiary level information technology is the delivery of information presented through the university's official website. One of the web-based systems owned by the STTI Tanjungpinang is the Sistem Informasi Kerja Praktek dan Skripsi (SKKP). With this technology, the process of submitting titles to the registration of practical work trials and student theses has been switched online. Analysis of the level of satisfaction is important to know the extent of expectations and perceptions of system users in an effort to achieve the perfection of an information system and can meet user expectations. One method in analyzing user satisfaction levels is end user computing satisfaction (EUCS). Dimensions in EUCS consist of content, accuracy, format, ease of use and timeliness. This type of research is descriptive research that is intended to describe the phenomena that exist, which took place at this time or in the past. Data collection methods included observation, interviews and distribution of questionnaires with a sample of 35 respondents who were active SKKP users. The results of the analysis of user satisfaction level SKKP STTI Tanjungpinang using the EUCS method of 78.69% with a gap of 21.31% means users are in the range of satisfied categories. From the five dimensions, the variable content has the smallest gap of 8.69% while the largest gap is in the accuracy variable, which is 32.02%.
Fraudsters rob banks of millions via emulated mobile devices

Millions have been stolen from a number of US and EU banks using sophisticated fraud techniques carried out with mobile phone emulators. In each incident, the attacks took just a few days to commit, with the thieves being careful to clean up and cover their tracks afterwards.
Good and bad modeling practices

Enterprises have made amazing advances by taking advantage of data about their business to provide predictions and understanding of their customers, markets, and products. But as the world of business becomes more interconnected and global, enterprise data is no long a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today.
International Conference on Science and Innovated Engineering (I-COSINE)

International Conference on Science and Innovated Engineering (i-COSINE) is an inaugural conference organized by the Lhokseumawe State Polytechnique. It was held on 21 and 22 October 2018 at Mata Ie Resort, Sabang, Aceh, Indonesia. The main goal of i-COSINE is to bring together researchers, scientists and experts in universities, companies, institutions, communities, agencies, associations and societies to provide them a unique platform for sharing worldwide ideas as well as the recent developments on science, innovation and engineering technology. This conference has received nearly 200 participants from various field of technology, engineering, and sciences. It attracts researcher and academician from ASEAN region to gather in Sabang for this conference. A compilation of articles that represent the significant results of the conference has been selected to publish in this volume.
Optimisation of Optical Network for Continuous-Variable Quantum Key Distribution by Means of Simulation

The unprecedented breakthrough in the field of quantum computing in the last several years is threatening with the exploitation of our current communication systems.To address this issue, researchers are getting more involved in finding methods to protect these systems.Amongst other tools, quantum key distribution could be a potentially applicable way to achieve the desired level of protection.In this paper we are evaluating the physical layer of an optical system realising continuous variable quantum key distribution (CVQKD) with simulations to determine its weak points and suggest methods to improve them.We found that polarisation dependent devices are crucial for proper operation, therefore we determined their most defining parameters from the point of operation and suggested extra optical devices to largely improve transmission quality.We also paid attention to polarisation controlling in these sort of systems.Our findings could be valuable as practical considerations to construct reliable CVQKD optical transmission links.
Face Mask Detection

Businessesare constantly overhauling their existing infrastructure and processes to be more efficient, safe, and usable for employees, customers, and the community. With the ongoing pandemic, it's even more important to have advanced applications and services in place to mitigate risk. For public safety and health, authorities are recommending the use of face masks and coverings to control the spread of Coronovirus. The COVID-19 pandemic is devastation to themankind irrespective of caste, creed, gender, and religion. Using a face mask can undoubtedly help in managing the spread of the virus. COVID-19 face mask detector uses deep learning techniques to successfully test whether a person is wearing a face mask or not. Using a deep learning method called Convolutional Neural Network, got an accuracy of 98.6 %. It can work with still images and also works with a live video stream. Cases in which the mask is improperly worn are when the nose and mouth are partially covered is considered as the mask is not worn. Our face mask identifier is the least complex in structure and gives quick results and hence can be used in CCTV footage to detect whether a person is wearing a mask perfectly so that he does not pose any danger to others. Mass screening is possible and hence can be used in crowded places like railway stations, bus stops, markets, streets, mall entrances, schools, colleges, etc. By monitoring the placement of the face mask on the face, we can make sure that an individual wears it the right way and helps to curb the scope of the virus
Semantic Web application architecture

Enterprises have made amazing advances by taking advantage of data about their business to provide predictions and understanding of their customers, markets, and products. But as the world of business becomes more interconnected and global, enterprise data is no long a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today.
Testing Pyramid

Now that we know how to use XCTest and XCUITest to write tests in iOS, we need to know the types of tests we should be writing, as well as the quantity of each type of testing. And this is where the “Testing Pyramid" comes in. It is a concept that helps in answering both of these questions. Mike Cohn came up with this concept in his book Succeeding with Agile. It's a great visual metaphor telling you to think about different layers of testing. It also tells you how much testing to do on each layer.
Exemplars of Integration in Engineering Education’s Use of Mixed Methods Research

Her research and scholarship are focused on exploring the implementation of mixed methods, qualitative, and artsinformed research designs in studies examining issues of education research.Her work in these areas includes but is not limited to her dissertation study examining youth acculturation patterns through an arts-informed approach to mixed methods, exploring professional identity
Analysis on Detecting a Bug in a Software using Machine Learning

In today’s scenario, it is very essential in the development phase of a software, predicting a bug and to obtain a successful software. This can be achieved only through predicting some of the faults in the earlier phase itself such that, it can lead to have a reliable, efficient and a quality software. The challenging task here is to have a well sophisticated model that can predict the bug leading to a cost-effective software. In order to achieve this, few machine learning algorithms are used that produce accuracy with trained and test datasets. A variety of machine learning methodologies have been developed to learn and detect a bug in a software. In this paper, we perform the analysis on detecting a bug in a software using machine learning methods which is very much useful for Software Industries. It summarizes the existing work on detecting a bug in a software by providing the information about various methods involved in bug prediction and points out at the accuracy obtained by the existing methods, advantages, and the drawbacks while working with bug prediction.
Ray Tracing

Ray tracing originated in optics to determine the path of light. However, ray tracing is used in modern technology by many fields, such as acoustics and computer graphics. Ray tracing is at the heart of optical design. Most optical calculations are done by tracing rays of light and, therefore, for competent lens design, it is important to have an understanding about how ray tracing is performed. This chapter provides an introduction to ray tracing, to ray tracing pitfalls, and to some useful ray tracing techniques.
The Role of Forgiveness in the Effect of Leader-Member Exchange Relationship and Organizational Justice on Job Satisfaction and Subjective Well Being: Mediation of Relational Efforts Complemented by Forgiveness Climate.

Relationship conflict, although commonplace in organizational life, has serious implications for individual, interpersonal, and organizational outcomes such as performance, engagement, and retention, as it is characterized by high levels of interdependence and thus is more vulnerable to the damaging effects of transgression incidents. These relationship conflicts can be minimized through forgiveness and organizational justice. Hence, this study aims to explore how organizational justice along with leader-member exchange (LMX) leads towards employees satisfaction and wellbeing. For this, we proposed a theoretical framework, modifying the Radulovic et. al. (2019) model to incorporate organizational justice, We contend that organizational justice including, distributive, procedural, and interactional justice, along with LMX, increase forgiveness, this would, in turn, raise the relational efforts (RE) leading towards subjective wellbeing, and job satisfaction. We also imply that forgiveness climate moderates the effect of justice and LMX on forgiveness in a way that a forgiveness conducive climate would strengthen the effect of justice and LMX on forgiveness. Empirical validity was established by conducting a survey using a close-ended questionnaire. Data was collected from 341 respondents and analyzed using confirmatory factor analysis and structured equation modeling. The results show that distributive procedural, and interactional justice as well as LMX seems to have a direct and positive effect on job satisfaction (JS) and wellbeing (SWB). Forgiveness seems to positively mediate LMX, distributive, and interactional justice on JS directly, as well as through RE. forgiveness also mediates the effect of distributive justice on SWB directly, and through RE. Moderation analysis showed that forgiveness climate (FC) negative moderates the effect of LMX, and distributive justice on forgiveness. Meaning higher FC would decrease the impact of LMX, and distributive justice on forgiveness. results form the base for further surveys. We can examine the variables of procedural justice in terms of how they can help improve job satisfaction and the subjective well-being of workers. We can see the components like trust, sovereignty, appreciation to improve the relationship between pioneers and individuals. We can also use the components that can prevent the agents from scraping substantial cheapness that degrades the moa; different employees, lead to job satisfaction.
Proposed A New Multidimensional Face Recognition For Surgically Altered Faces In Security Surveillance

From previously carried out review results, authors have proposed a new multidimensional face recognition approach and applied on the sample database of sensitive medical images. The basic idea is to differentiate an individual’s identity with its own core features extracted from local or global plastic surgery. Features are being highlighted to match pre-to-post or post-to-pre surgery face images. The procedure may affect different face recognition algorithms working on linear or non-liner variations approach and that’s what multidimensional approach is meant. Hence it proves that the performance of verified rank accuracy ratio has increased in face recognition for security surveillance.