Reviewerly/exHarmony huggingface dataset:
SECURITY ISSUES COMPANY FACE WHEN TRANSITIONING TO THE CLOUD

Cloud Computing is now a worldwide concept which is being utilized by majority of internet users. Technological advancement has reinforced organizations to adopt cloud systems to deploy software products, data and provide ease of maintenance as well as cost of implementation. Hence, the skyrocketing demand for cloud computing tools among business organizations. However, there are several security challenges related to Cloud computing such as data leakage, intrusion of hackers and others. In this paper, thorough study and analysis has been done on the security challenges faced by organizations in adoption of cloud computing techniques, effects and possible solutions companies can adopt to prevent such security breach.
SECURITY ISSUES COMPNY FACE WHEN TRANSITIONING TO THE CLOUD

Cloud Computing is now a worldwide concept which is being utilized by majority of internet users. Technological advancement has reinforced organizations to adopt cloud systems to deploy software products, data and provide ease of maintenance as well as cost of implementation. Hence, the skyrocketing demand for cloud computing tools among business organizations. However, there are several security challenges related to Cloud computing such as data leakage, intrusion of hackers and others. In this paper, thorough study and analysis has been done on the security challenges faced by organizations in adoption of cloud computing techniques, effects and possible solutions companies can adopt to prevent such security breach.
Interrogating the Quality of Junior High School Final Exam Made by EFL Teacher Using ITEMAN 4.3 Program

The ministry of Education Department, since the removal of USBN, mandates every school to conduct a school final exam that should made by the teachers. In this study, the writer focuses on the English Junior High School Final Exam made by EFL teacher distributed in Mojokerto academic year 2021/2022. In order to know the quality of the item test, the analysis can be done by investigating the validity, reliability, item difficulty, item discrimination, and item distractors. This study used descriptive quantitative. The respondents of this study were taken from English school final exam of 9th-grade students in MTS Bahrul Ulum which consists of 50 multiple choice items from 31 students. The instrument are the test question, the students’ answer sheet, and the answer key. It will be analyzed by using ITEMAN 4.3 program as an effective solution for item test analysis. The result indicates that the content validity still do not cover the whole material in the syllabus. The reliability of the test is 0.91 which is categorized as reliable. The difficulty level of the item test is 0.60 or 60% which is considered good. The item discrimination is 0.38 considered as satisfactory. The effective item distractors is 48%, smaller than the percentage of ineffective items. In conclusion, the quality of English Junior High School Final Exam made by EFL teacher distributed in Mojokerto academic year 2021/2022 in terms of validity, reliability, item difficulty, item discrimination, and item distractors absolutely needs improving.&#x0D; Keywords: item analysis, validity, reliability, item distractor, item discrimination, item difficulty, descriptive quantitative
Analisis Sentimen Aplikasi WETV di Google Play Store Menggunakan Algoritma Support Vector Machine

WeTV is an online streaming application widely used by Indonesia’s people as an entertainment medium while at home. This application has been downloaded more than 50 million times on the official Google Play Store website. The number of users who use it makes the reviews of this application abundant as well. Large numbers of reviews are very difficult to read manually, sentiment analysis is needed to classify reviews into positive and negative classes. This study uses a support vector machine algorithm with a linear kernel to classify review data from the WeTV application. KDD was used as a method to complete this research. In the analysis process to obtain information, 4 scenarios were carried out, with the division in the first scenario consisting of 60% training data and 40% test data, the second scenario consisting of 70% training data and 30% test data, the third scenario 80% training data and 20% test data, and the last scenario 90% training data and 10% test data. The highest test results of 85% were obtained from the second scenario with the distribution of training data of 70% and 30% of test data, the third with the distribution of training data of 80% and 20% of test data, and the fourth with the distribution of training data of 90% and test 10% data. The confusion matrix is used as an evaluation of the model that has been made, the results show an accuracy in the first scenario of 83%, with a precision value of 83%, recall 89%, and an f1-score of 86%. The accuracy in the second scenario is 85%, precision is 86%, recall is 89%, f1-score is 87%, accuracy in the third scenario is 85%, precision is 85%, recall is 90%, and f1-score is 88%. And the fourth scenario gets an accuracy of 85%, precision 86%, recall 90%, and f1-score 90%.
Opening Research Data: What Does It Mean for Social Sciences?

Recent international trends demonstrate multilevel efforts to ‘open’ science across its whole ecosystem and lifecycle – from capturing research data through to publishing results. In social sciences, the publication process is already largely ‘open access’ or transitioning toward it. However, opening research data raises specific issues and concerns for the field. Here, we set out to understand what open research data mean for social sciences, and if, why, and how data should be made open. We argue that while the ecosystem of actors, infrastructures, standards, and principles is starting to take structure in France and abroad, there are several barriers to the process of opening data in social sciences: (1) a misperception of the motivations for opening data (i.e., focusing on risks of exercising control over researchers and their academic freedom and overlooking motivations like data patrimonialization, pooling and potential synergies, trust-building, and broader engagement), (2) a system based on competition and the dominant process of ‘starification’ in research, (3) a lack of resources and capabilities that might further exacerbate inequalities among genders, communities, institutions, and countries, and (4) the potential risks inherent to opening data and the specific constraints posed by social science data. Against this backdrop, we investigate several ways forward to operationalize not only FAIR (Findable, Accessible, Interoperable and Reusable) but also CARE (Collective benefit, Authority to control, Responsibility, Ethics) principles for open data in social sciences, before going on to present M@n@gement’s new open data policy.
Implementation of Beeman's algorithm to calculate execution time on GPU using CUDA

&#x0D; Graphics processing units (GPUs) are microprocessors designed to the operation of display and manipulation of graphics data. . Currently, these graphics processor are found on all graphics hardware and have become very important instruments for parallel computing. GPUs are practical tools for the development of several fields like decoding and encoding, solving differential equations. Their advantages are increase in performance, faster data processing and reduced power consumption. It is simple to program a GPU with CUDA C to run parallel calculations. But it is necessary to have an understanding of the architectural aspects of the GPU and CUDA C. This paper, we will describe and implement Beeman's algorithm on GPU and CPU using CUDA C to solve the differential equation of charged particles in an electromagnetic field. Our goal is to evaluate the performances of the implementation on GPU and CPU processors and to deduce the efficiency of the use of GPUs.&#x0D;
GBL UNTUK MENINGKATKAN AKTIVITAS DAN PRESTASI BELAJAR MATERI MENGENAL AKUN BELAJAR.ID DALAM BIMBINGAN TIK

This research is aimed to improve students learning activity and achievement through introducing belajar.id account at the eight grade students of SMP N 19 Purworejo by using Game Based Learning. This research show 85% of students gained the average score of 75, the percentage of students activity reach 80% . This student’s activity categorized good. This research is conducted on March to May of 2021, on the second semester at the eight grade students of SMP N 19 Purworejo in the academic year of 2021/2022. This research is conducted on VIII C students of SMP N 19 Purworejo which consist of 32 students (male and female). The techniques of collecting data used in this research are observation and test. The collected data is analyzed descriptively by using percentage analysis. The steps used in this research are as follow: 1) planning, (2) acting, (3) observing and evaluating, and 4) reflecting and follow –up. This class action research activity is carried out in 2 cycles, namely cycle I and cycle II. The result of the research shows that there is a enhancement in stuedents learning activity. It can be seen from data observation/monitoring of student learning activities. On cycle I, the average students activity obtained 80,21%. On cycle II , It is increased to 83,51 %. This research shows that there is a enhancement in students learning achievement in knowing belajar id. account. Before this reasearch is conducted, the students only obtained the average score 66,25 , with a classical learning mastery of 40.63%. However, students can obtain the average score 76,49 in cycle I, with a classical learning mastery 66,50 %. Then students can obtain the average score 87,11 in cycle II, with a classical learning mastery 96.88 %. The result of this reaserach show that there is a increasing positive students behaviour in learning belajar id account . In the first cycle, the change of student behavior towards postitive is 81.43% and in the second cycle, it is increased to 82.99%. The result of this research shows that there is an increase in students activity and students learning achievement as well as changes of student behavior towards positive in learning belajar.id accounts at eight grade (VIII C) students of SMP Negeri 19 Purworejo through Game Based Learning learning.
Data prediction system in malaria control based on physio-chemical parameters of anopheles breeding sites

&#x0D; Malaria is a public health problem in Senegal. As a result, a real program focused on prevention and treatment has been put in place to fight it. Despite the efforts made, the prevalence rate of malaria is still worrying. To have a prediction system that, once certain physicochemical information, will inform if we can or not attend to the development of anopheles larvae. Our work consisted of collecting data on mosquito breeding sites, processing, and analyzing them in order to predict the physicochemical conditions for the development of Anopheles larvae. Larval control is an alternative to reduce the prevalence rate of malaria. We retain logistic regression as an algorithm and water electrical conductivity, water turbidity, temperature, and dissolved oxygen as determinant parameters. The learning and prediction system set up on the basis of the determining parameters and logistic regression worked. The predictions will be improved by further training our system with field data.&#x0D;
Pembagian Task Karyawan Berdasarkan Riwayat Kerja dengan Metode Naive Bayes

Accuracy and suitability in the division of employee tasks have an important role in the division of employee tasks, in order to obtain a list of criteria that are in accordance with the abilities of employees in one division. PT. Assist Software Indonesia Pratama is currently still in manual division of tasks, namely by sorting out tasks based on features, applications, divisions, and employees who usually do the work. So that it takes a long time in the process of dividing employee tasks, one of the factors is HRD must sort out tasks based on features, applications in order to determine the division and employees who work on the task. The purpose of the research is to facilitate the division of tasks to employees in order to get a list of criteria that are in accordance with the abilities of employees in one division using the Naive Bayes method. So we need a system that can help HRD in distributing employee tasks in accordance with the division and employee capabilities. In this task distribution system using the Multinomial Naïve Bayes Classifier method as a determinant of employee task distribution. The division of employee tasks is based on the tasks that have been done by the previous employee, so that the system can perform the appropriate task division. The system can see the similarities between tasks using the Multinomial Naïve Bayes method as a consideration for determining the divisions and employees who work with the percentage accuracy of 92.5% and 82.5%.
Adversarial Multi - View Domain Adaptation for Regression

In this paper, we address the problem of domain adaptation in a regression setting, where only a few labeled samples are available in the source domain, and no labeled samples in the target domain. In addition, we consider that source data have different representations (multiple views). In this work, we investigate an original method to take advantage of different representations using a weighted combination of views. Besides, we use a co-training approach to include information from unlabeled instances by ensuring that models trained on different views make similar predictions. For this purpose, we introduce a novel formulation of the optimization objective for domain adaptation that relies on a discrepancy distance. Then, we develop an adversarial network domain adaptation algorithm adjusting weights given to each view, ensuring that those related to the target receive higher weights. Finally, we evaluate our method on different public datasets and compare it to other domain adaptation baselines to demonstrate the improvement for regression tasks.
Tree trace reconstruction using subtraces

Tree trace reconstruction aims to learn the binary node labels of a tree, given independent samples of the tree passed through an appropriately defined deletion channel. In recent work, Davies, R\'acz, and Rashtchian used combinatorial methods to show that $\exp(\mathcal{O}(k \log_{k} n))$ samples suffice to reconstruct a complete $k$-ary tree with $n$ nodes with high probability. We provide an alternative proof of this result, which allows us to generalize it to a broader class of tree topologies and deletion models. In our proofs, we introduce the notion of a subtrace, which enables us to connect with and generalize recent mean-based complex analytic algorithms for string trace reconstruction.
Topic Modeling Using Latent Dirichlet Allocation &amp; Multinomial Logistic Regression

Unsupervised categorization for datasets has benefits, but not without a few difficulties. Unsupervised algorithms cluster groups of documents in an unsupervised fashion, and often output findings as vectors containing distributions of words clustered according to their probability of occurring together. Additionally, this technique requires human or domain expert interpretation in order to correctly identify clusters of words as belonging to a certain topic. We propose combining Latent Dirichlet Allocation (LDA) with multi-class Logistic Regression for topic modelling as a multi-step classification process in order to extract and classify topics from unseen texts without relying on human labelling or domain expert interpretation in order to correctly identify clusters of words as belonging to a certain topic. The findings suggest that the two procedures were complementary in terms of identifying textual subjects and overcoming the difficulty of comprehending the array of topics from the output of LDA. Keywords: Natural Language Processing; Topic Modeling; Latent Dirichlet Allocation; Logistic Regression
Buttons and Sliders

In this chapter, we will discuss how to create different types of buttons. These buttons are a medium for interaction between the user and the application. Let’s start by creating these buttons one by one.
CMSec: A Vulnerability Prevention Tool for Supporting Migrations in Cloud Composite Services

The growing maturity of orchestration languages, such as the Topology and Orchestration Specification for Cloud Applications (TOSCA) language, and the continuous improvement of virtualization techniques contribute to the large-scale deployment of cloud composite services based on multiple resources that may be hosted over different cloud service providers. The resources composing these services may be subject to migrations, either live or offline, in order to cope with performance objectives, such as load balancing, latency minimization, and energy savings. However, these migrations may induce changes affecting the configurations of migrated resources. In particular, these changes may lead to vulnerabilities, that may compromise the security of resources, or even the security of the whole cloud service. This demonstration showcases a vulnerability prevention tool, called CMSec, for supporting the resource migrations of TOSCA-based cloud composite services by considering OVAL vulnerability descriptions together with verification techniques. Based on two main scenarios, we will expose how the CMSec tool is able to detect vulnerable configurations prior to resource migrations, and to suggest corrective operations for remediating them.
Retracted: A Cluster Analysis Model for PhD Dissertation Quality Based on the Depth Algorithm

2], signifcant concerns were identifed with the peer reviewers assigned to this article; the investigation has concluded that the peer review process was compromised.We therefore can no longer trust the peer review process, and the article is being retracted with the agreement of the Chief Editor.
Presentation Slide Control Based on Hand Gestures

In today's digital world, presentation using a slideshow is an effective and attractive way that helps speakers to convey information and convince the audience. There are ways to control slides with devices like a mouse, keyboard, or laser pointer. The drawback is that one should have previous knowledge about the devices to manage them. Gesture recognition acquired importance a couple of years prior and is utilized to control applications like media players, robot control, and gaming. The hand gesture recognition system is built with gloves and markers. However, using such gloves or tags expands the expense of the system. An Artificial intelligence-based hand gesture detection methodology is proposed in this proposed system. By hand gestures, users can change the presentation slides in forward and backward directions. The use of hand gestures causes the connection simple and helpful and does not need any additional gadgets. The suggested method is to help speakers with a product presentation with naturally improved communication with the computer. Specifically, the proposed system is more viable than a laser pointer since the hand is more apparent and thus can better grab the audience's attention.
Learning Vision and Language Relations from Pre-trained Unimodal Encoders with Cross Attention

&lt;p&gt;Pre-trained vision language models (VL) have seen a rise in recent years, achieving state-of-the-art performance on tasks such as visual question answering, image captioning, zero-shot tasks, text-to-image synthesis, and many more. However, these models are large, also requiring large amounts of data, which can hinder application on resource-limited settings. This paper proposes CAPIT (&lt;strong&gt;C&lt;/strong&gt;ross &lt;strong&gt;A&lt;/strong&gt;ttention on &lt;strong&gt;P&lt;/strong&gt;re-trained &lt;strong&gt;I&lt;/strong&gt;mage and &lt;strong&gt;T&lt;/strong&gt;ext models), a novel architecture built on top of frozen pre-trained unimodal encoders, utilizing transferable knowledge from pre-trainined models through cross-attentional transformers. CAPIT is trained with a simple supervised task that learns to predict the correspondence between image-text pairs. It is then tested on zero-shot image classification. The proposed model contains less parameters and uses less data compared to other methods, while performing fairly well with trade-offs between compute requirements performance, showing promise for future work in resource-limited settings.&lt;/p&gt;
Item Selection Algorithm Based on Collaborative Filtering for Item Exposure Control

In computerized adaptive testing, overexposure of items in the bank is a serious problem and might result in item compromise (e.g., Veldkamp et al., 2010). We develop an item selection algorithm that utilizes the entire bank well and reduces overexposure of items. The algorithm is based on collaborative filtering (Su &amp;amp; Khoshgoftaar, 2009) and selects an item in two stages. In the first stage, a set of candidate items whose expected performance well matches the examinee’s current performance is selected. In the second stage, an item that is the approximately matched to the most recently administered item is selected from the candidate set. The expected performance of an examinee on an item is predicted by autoencoders (Goodfellow et al., 2016). Simulation results show that the proposed algorithm outperforms existing item selection algorithms in terms of item exposure while incurring only a small loss in measurement precision.
Visual tools for teaching mathematics in conditions of computerization of education

The article describes the changes that have taken place in connection with the process of creating and using visual aids for teaching mathematics in the era of computerization of education. The main new formation is the transformation of static visibility into dynamic. The computer literacy of schoolchildren, which has grown over the years of computerization of education, makes it possible for not only teachers, but also the students themselves to participate in the creation of visual aids. The article focuses on the advantages and disadvantages of visual aids that appeared in the computer age. The possibilities of computer visualization make it possible to visualize educational material not only offline, but also in online learning mode. Platforms for creating virtual visualization for mathematics lessons are briefly described. While expensive, but popular and of interest to schoolchildren, augmented reality technology can claim to be one of the main means of creating visual aids in the future.