Reviewerly/exHarmony huggingface dataset:
Analisis Sitasi Koleksi Perpustakaan dalam Menyusun Karya Akhir Mahasiswa Departemen Matematika Fakultas MIPA UGM

The Faculty of Mathematics and Natural Sciences library provides various collections of library materials as learning resources in supporting the implementation of the Tri Darma of Higher Education. The background of this research is that the library does not yet know the citation of collections by students of the Department of Mathematics in compiling the final work. The purpose of this research is to analyze the citation of library collections which include type, language, year of publication, and availability of literature. The research method used is descriptive research with a quantitative approach. The research subject is a collection of thesis, theses, and dissertations for 2019 Mathematics Department students, while the object of research is a bibliography of the collection. Methods of data collection using the method of documentation. Analysis of the data used is descriptive quantitative analysis. The results of this analysis show the average citation of all samples of 21 citations; in the collection of literary thesis the most cited are books 50.2%, theses, books are most cited 47%, dissertations are most cited journals 61%; most of the cited literature is in English 84%; the year of publication cited is mostly the younger year, and the overall availability of literature in the sufficient category is 53%. The conclusion of this study, the most widely cited books by students of the Department of Mathematics at the S1 and S2 levels, while S3 students cite journals the most.
Evolution of community radio in India and its application with respect to information &amp; communication technology in education

The COVID-19 pandemic has revolutionized the way we work, communicate, and impart knowledge. Due to the need to maintain physical distancing, education in India has been greatly hindered in the last two years. The education of around 250 million children in India was gravely impacted due to school closures which were caused by strict lockdown. To counter this crisis, governments all over the world collaborated with industry stakeholders and managed to create an education ecosystem which relied on Information &amp; Communication Technology. But due to uneven broadband connectivity in rural areas and prohibitive costs associated with high-speed internet, most students are not able to fully exploit this new online education ecosystem. This research paper seeks to outline an alternative method of remote learning which employs community radio as the medium. Community Radio is one of the most cost-efficient modes of communication and has a distinctive edge when it comes to accessibility in villages and other far-flung regions of the country. Hence the integration of community radio in the overall Information &amp; Communication Technology ecosystem will go a long way in solving the present education crisis.
Design of Face Recognition Security System on Public Spaces

&lt;p class="Abstract"&gt;Implementation of physical security such as recruitment of security officers, installation of CCTV, and restrictions on public access have become commonplace nowadays. Computer systems equipped with archival storage media must be properly maintained, including computer systems containing sensitive information that must be stored in a locked and secure place. This study applies a security system using facial recognition to determine who is authorized over the data in the computer system—using Haar Cascade as a face detector and LBPH as a match between faces that can access and those that are not on the list. On the other hand, if the person is unidentified, preventive measures will be performed. Based on the result, the proposed system using Raspberry Pi 4 is able to identify a face using Haar Cascade algorithm with an accuracy of 68% and average duration process of 0.392s, and able to recognize face using LBPH algorithm with accuracy between 50.74% to 100% and average duration process of 0.548s.&lt;em&gt;&lt;/em&gt;&lt;/p&gt;
Project-Based Blended Learning to Improve Reading Interest and Writing Skills Research Proposal

The purpose of this research was to increase reading interest and research proposal writing skills. The type of research used is classroom action with two cycles. The participants in this study were all seventh-semester physical education students who attended the proposal seminar lecture, totaling 80 students. Data collection techniques used observation guides, questionnaires, and product assessments in the form of research proposals. Data analysis techniques using categories and percentages. Based on the results of data analysis, it was known that in cycle 1 students' interest in reading was in the medium category, and cycle 2 is in the high category. Meanwhile, students' research proposal writing skills in cycle 1 was in the medium category, and in cycle 2 was in the high category. Classical completeness in cycle 1 was 18.75% for reading interest, and 17.5% for research proposal writing skills. Meanwhile, classical completeness in cycle 2 in this study was 81.25% for reading interest, and 82.5% for research proposal writing skills. So it can be concluded that the application of project-based blended learning increased reading interest and research proposal writing skills.
Mutual- and Self- Prototype Alignment for Semi-supervised Medical Image Segmentation

Semi-supervised learning methods have been explored in medical image segmentation tasks due to the scarcity of pixel-level annotation in the real scenario. Proto-type alignment based consistency constraint is an intuitional and plausible solu-tion to explore the useful information in the unlabeled data. In this paper, we propose a mutual- and self- prototype alignment (MSPA) framework to better utilize the unlabeled data. In specific, mutual-prototype alignment enhances the information interaction between labeled and unlabeled data. The mutual-prototype alignment imposes two consistency constraints in reverse directions between the unlabeled and labeled data, which enables the consistent embedding and model discriminability on unlabeled data. The proposed self-prototype alignment learns more stable region-wise features within unlabeled images, which optimizes the classification margin in semi-supervised segmentation by boosting the intra-class compactness and inter-class separation on the feature space. Extensive experimental results on three medical datasets demonstrate that with a small amount of labeled data, MSPA achieves large improvements by leveraging the unlabeled data. Our method also outperforms seven state-of-the-art semi-supervised segmentation methods on all three datasets.
Causal Explanations for Sequential Decision Making Under Uncertainty

We introduce a novel framework for causal explanations of stochastic, sequential decision-making systems built on the well-studied structural causal model paradigm for causal reasoning. This single framework can identify multiple, semantically distinct explanations for agent actions -- something not previously possible. In this paper, we establish exact methods and several approximation techniques for causal inference on Markov decision processes using this framework, followed by results on the applicability of the exact methods and some run time bounds. We discuss several scenarios that illustrate the framework's flexibility and the results of experiments with human subjects that confirm the benefits of this approach.
Nitriding: A tool kit for building scalable, networked, secure enclaves

Enclave deployments often fail to simultaneously be secure (e.g., resistant to side channel attacks), powerful (i.e., as fast as an off-the-shelf server), and flexible (i.e., unconstrained by development hurdles). In this paper, we present nitriding, an open tool kit that enables the development of enclave applications that satisfy all three properties. We build nitriding on top of the recently-proposed AWS Nitro Enclaves whose architecture prevents side channel attacks by design, making nitriding more secure than comparable frameworks. We abstract away the constrained development model of Nitro Enclaves, making it possible to run unmodified applications inside an enclave that have seamless and secure Internet connectivity, all while making our code user-verifiable. To demonstrate nitriding's flexibility, we design three enclave applications, each a research contribution in its own right: (i) we run a Tor bridge inside an enclave, making it resistant to protocol-level deanonymization attacks; (ii) we built a service for securely revealing infrastructure configuration, empowering users to verify privacy promises like the discarding of IP addresses at the edge; (iii) and we move a Chromium browser into an enclave, thereby isolating its attack surface from the user's system. We find that nitriding enables rapid prototyping and alleviates the deployment of production-quality systems, paving the way toward usable and secure enclaves.
Factors Contributing to Students’ Speaking Anxiety: A Case Study at Students’ Junior High School

This article aimed of investigating the causes of students’ speaking anxiety at a Private Junior High School at Salatiga, Central Java. The method used case study. This study used a set of questionnaires distributed to sixty-six participants from grade 7 to grade 9. The participants were asked to choose the causes of their speaking anxiety offered in the questionnaire items according to their personal opinions. The questionnaire items were developed based on the literature used in this study. After that, the quantitative data were presented and then the data were described and interpreted. The results of this study revealed that the major factor contributing to the participants’ speaking anxiety was the concern about accuracy and grammar. Interestingly, the quantitative data of this study showed that a significant number of participants were less anxious especially when dealing with classroom settings and activities, and teachers. The result of the study was expected to contribute to student teachers and language teachers in general. This study helped them to be aware that speaking anxiety may exist among EFL students, hence they could develop their teaching methods and approaches in teaching speaking to minimize their students’ anxiety and to give more exposure to English for their students.&#x0D; Keywords: Speaking Anxiety, Factor Contributing Speaking, English Language Learning
IMPLEMENTASI SCRUM PADA FRAMEWORK SISTEM INFORMASI PENJUALAN DAN PEMBELIAN CAT PADA TOKO CAD

ABSTRACT&#x0D; &#x0D; In the business world in the company's time that applies information technology because technology is needed in the world of work to facilitate in completing a job so that it is more effective and efficient. One example of the development of information technology in the world of work or the business world is data processing systems. In case studies in cad business units still use manual recording, the management and input process is still manual so it is less effective, efficient, and there are errors in recording inaccurately. Peneliti designed a web-based paint sales and purchase application where this application can facilitate the sale and purchase of paint without location limitations. This method in design uses the Agile method with its continuous development in a process called Scrum that overcomes complexity in the work by making it easier to understand and transparent, allowing teams to examine and adapt depending on current conditions, not the predicted scenario. The implementation of the scrum method is built with framework and MySQL databases. Hasil from research system sales and purchase of web-based paints facilitates purchases, so that customers can make purchases through the website indefinitely, where customers can buy and transact and make it easier for admins to make sales, with this paint sales and purchase system to support a wider market reach without location limitations.&#x0D; &#x0D; Keywords: Implementation, Scrum method, Framework, Design, Sales System
APPLICATION STRATEGY OF SMART FARMING TECHNOLOGY 4.0 IN UTILIZING RITX SOIL AND WEATHER SENSOR

Research design is predictive and descriptive involving several concepts. Partial least squares , research and development tests are used in developing the application of smart farming technology. The results analysis prove the direct influence of variables X_1 (genetic factors) to Y_1 (farmer behavior in the application smart farming) of -0.269 . It show does not have a positive impact on the contrary reducing the behavior of farmers in implementing smart farming. The relationship between X_2 (individual external factors) to Y_1 is 0.392 show that individual external factors give positive impact on increasing farmer behavior in the application of smart farming by 39.2%.
Penerapan Metode System Usability Scale dalam Pengujian Rancangan Mobile Apps Gamification Tari Rakyat di Indonesia

Indonesia has many dances in each region. Traditional dance and folk dance are dances that existed in Indonesia before the development of contemporary dance. As one of the local cultures in each area, dance art is included in local content at the elementary to high school level. The changing curriculum has disrupted local cultural education in the world of education some time ago. In addition to these factors, the lack of interactive learning media at least affects. The purpose of this study is to develop a learning pattern for folk dance as a local culture in Indonesia through an interactive mobile application. In addition, this research is used to help preserve and introduce the folk dance arts of each region to students in Indonesia. Gamification can be an alternative for developing folk dance learning. What usually happens is the lack of innovation in conventional learning media to attract students' interest in studying local culture, especially folk dance as a local content subject. This activity is a folk dance education about history, regional origins and dance movements. The result of this application is a folk dance game in Indonesia. There are several levels that must be passed to be able to complete this game. Each season will be taken 3 people who get the reward. The rewards that we design are based on the prizes preferred by elementary, junior high and high school students. Based on the results of the System Usability Scale evaluation, the prototype designed got a score of 86.25% and was considered to have met the usability element.
RPG and Story-based Game in Game Development

Abstract: In these days video games are most popular and today most of the people spend their time playing video games. A Game can have multiple Genre like Adventure, action, Puzzle or RPG games where they can become the main protagonist. Do computer games tell stories or not and how to make a game more use a storytelling adventure having limitless possible creativity and art. Any one can share their story with game development. Keywords: Game Development, RPG games, Story Based Games, Video Games
The Correlation Between Health Care Access and Pregnancy Checkup with Choice of Birth Attendants

An ideal place for childbirth is a health facility with adequate equipment and personnel ready to help at any time of labor complications. This study aimed to analyze the correlation between health care access and pregnancy check-up with a selection of birth attendants.
Preface

Abstract We are glad to introduce you that the 2022 International Conference on Intelligent Dynamics and Control Technology (IDC 2022) was successfully held on April 22-24, 2022. In light of worldwide travel restriction and the impact of COVID-19, IDC 2022 was carried out in the form of virtual conference to avoid personnel gatherings. Because most participants were still highly enthusiastic about participating in this conference, we chose to carry out IDC 2022 via online platform according to the original schedule instead of postponing it. The 2022 International Conference on Intelligent Dynamics and Control Technology (IDC 2022) invited scholars, researchers and students to publish unpublished original research papers and important ongoing papers and research results in the field of intelligent dynamics control actively. The objective of the conference, which aimed to address key issues related to intelligent dynamics control, witness a number of countries, international representatives and researchers sharing their perspectives and new ideas in the areas of intelligent computing, dynamic control and communication, and providing an opportunity for researchers to discuss the latest solutions, scientific results and methods in addressing issues in the field of intelligent dynamics control. We are greatly honored to have invited Prof. Wanmi Chen, from Shanghai University, China to serve as our Conference Chair. This scientific event brings together more than 50 national and international researchers in intelligent dynamics and control technology area. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&amp;A discussion. In the first part, some scholars, whose submissions were selected as the excellent papers, were given about 5-10 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches. List of Committee member is available in this pdf.
WAYS OF FORMING VALUES AND BEHAVIOR IN THE SOCIETY IN THE PROCESS OF SOCIALIZATION OF PUPILS IN PRESCHOOL EDUCATIONAL INSTITUTIONS

In the process of socialization, the formation of spiritual and cultural heritage of the younger generation, ways to inculcate traditions in the minds, to give students an understanding of the values and moral norms of society on the basis of systematic approaches.
case study on cloud security controls

Cloud computing is a highly discussed topic in today’s technical and economic world. Many big players of the software industry are concentrating more on cloud services. Companies are racing to incorporate cloud infrastructures into their businesses or provide their own. While speaking of development, we cannot let down an important aspect called security. A misconfiguration or a minor vulnerability in a way the services are handled may result in a huge loss of data, which in turn would result in great loss of revenue. Money can be generated in one way or the other, but reputation once lost cannot be brought back again. In this paper, we discuss about the security controls and misconfigurations that frequently happen in AWS environments and discuss ways to avoid it using Capital One Data Breach as an example.
Improving VAE-based Representation Learning

Latent variable models like the Variational Auto-Encoder (VAE) are commonly used to learn representations of images. However, for downstream tasks like semantic classification, the representations learned by VAE are less competitive than other non-latent variable models. This has led to some speculations that latent variable models may be fundamentally unsuitable for representation learning. In this work, we study what properties are required for good representations and how different VAE structure choices could affect the learned properties. We show that by using a decoder that prefers to learn local features, the remaining global features can be well captured by the latent, which significantly improves performance of a downstream classification task. We further apply the proposed model to semi-supervised learning tasks and demonstrate improvements in data efficiency.
Big Data using Cloud Computing: Security Issues and Approaches

Big Data is a data analysis methodology made possible by current technological and architectural advancements. However, big data requires a significant investment in hardware and processing power, making it prohibitively expensive for small and medium-sized firms to implement. Small and medium-sized enterprises can benefit from cloud computing promise of big data implementation. The MapReduce programming paradigm is used to process large amounts of data. The MapReduce paradigm typically necessitates networked connected storage and parallel computation. The computing requirements of MapReduce programming are frequently beyond the capabilities of small and medium-sized businesses. Cloud computing is network access to computing resources on demand, given by a third party Hardware cost reduction, processing cost reduction, and the flexibility to verify the value of big data are three significant reasons for small and medium-sized organizations to embrace cloud computing for big data technology implementation. Security and loss of control are two main concerns with cloud computing. Key Words: Big data, MapReduce, cloud computing, private cloud, public cloud, and hybrid cloud.
Wasserstein Distributionally Robust Gaussian Process Regression and  Linear Inverse Problems

We study a distributionally robust optimization formulation (i.e., a min-max game) for problems of nonparametric estimation: Gaussian process regression and, more generally, linear inverse problems. We choose the best mean-squared error predictor on an infinite-dimensional space against an adversary who chooses the worst-case model in a Wasserstein ball around an infinite-dimensional Gaussian model. The Wasserstein cost function is chosen to control features such as the degree of roughness of the sample paths that the adversary is allowed to inject. We show that the game has a well-defined value (i.e., strong duality holds in the sense that max-min equals min-max) and show existence of a unique Nash equilibrium that can be computed by a sequence of finite-dimensional approximations. Crucially, the worst-case distribution is itself Gaussian. We explore properties of the Nash equilibrium and the effects of hyperparameters through a set of numerical experiments, demonstrating the versatility of our modeling framework.
DARK TIMES IN EKA KURNIAWAN’S NOVEL BEAUTY IS A WOUND

The purpose of this research is to find out the dark times experiences that the protagonist undergoes in the novel Beauty is A Wound written by Eka Kurniawan in i 2002. This novel tells the story of Dewi Ayu who is willing to be trampled by the power of the Japanese army, because Dewi Ayu wants to save her best friend’s mother. Dark times is a natural feeling which, if unfelt, will stay in one’s array of unresolved trauma knots. This research uses qualitative method in which the data are taken by quoting the relevant proofs from the novel then analyzing them and making the conclusion in the description forms. The findings show that the dark times undergone by the protagonist’s gives negative impact to her life. The dark times period experienced by the protagonist covers violence, slavery, social status discrimination, and being a single parent. The dark period experienced by the protagonist makes her feel sad, but i, precisely, makes her much stronger to live. It is reflected here how she negotiates with the colonizers in defending his life, although, it does not stop until the end of the colonial period and she lives as a prostitute until the end of her life.
Confounder Analysis in Measuring Representation in Product Funnels

This paper discusses an application of Shapley values in the causal inference field, specifically on how to select the top confounder variables for coarsened exact matching method in a scalable way. We use a dataset from an observational experiment involving LinkedIn members as a use case to test its applicability, and show that Shapley values are highly informational and can be leveraged for its robust importance-ranking capability.