Reviewerly/exHarmony huggingface dataset:
The Impact of Positional Encodings on Multilingual Compression

In order to preserve word-order information in a non-autoregressive setting, transformer architectures tend to include positional knowledge, by (for instance) adding positional encodings to token embeddings.Several modifications have been proposed over the sinusoidal positional encodings used in the original transformer architecture; these include, for instance, separating position encodings and token embeddings, or directly modifying attention weights based on the distance between word pairs.We first show that surprisingly, while these modifications tend to improve monolingual language models, none of them result in better multilingual language models.We then answer why that is: Sinusoidal encodings were explicitly designed to facilitate compositionality by allowing linear projections over arbitrary time steps.Higher variances in multilingual training distributions requires higher compression, in which case, compositionality becomes indispensable.Learned absolute positional encodings (e.g., in mBERT) tend to approximate sinusoidal embeddings in multilingual settings, but more complex positional encoding architectures lack the inductive bias to effectively learn compositionality and cross-lingual alignment.In other words, while sinusoidal positional encodings were originally designed for monolingual applications, they are particularly useful in multilingual language models.
Risk and abuse: Everyday copyright enforcement on YouTube

We analyzed 144 YouTube videos to get an understanding of how YouTubers experience copyright law on the platform. The results were fascinating.
BiRdQA: A Bilingual Dataset for Question Answering on Tricky Riddles

A riddle is a question or statement with double or veiled meanings, followed by an unexpected answer. Solving riddle is a challenging task for both machine and human, testing the capability of understanding figurative, creative natural language and reasoning with commonsense knowledge. We introduce BiRdQA, a bilingual multiple-choice question answering dataset with 6614 English riddles and 8751 Chinese riddles. For each riddle-answer pair, we provide four distractors with additional information from Wikipedia. The distractors are automatically generated at scale with minimal bias. Existing monolingual and multilingual QA models fail to perform well on our dataset, indicating that there is a long way to go before machine can beat human on solving tricky riddles. The dataset is publicly available at https://forms.gle/NvT7DfWhAPhvoFvH7.
Hubungan Kemampuan Literasi Numerasi dengan Hasil Belajar Matematika Siswa Kelas V SD Gugus II

The purpose of this study was to determine whether or not there was a significant positive relationship between numeracy literacy skills and mathematics learning outcomes for fifth grade elementary school students. The method used is quantitative research with a correlational model. The research data were obtained by distributing numeracy literacy test questions to students. Based on the t-test, the results of tcount = 12, 36448 are greater than ttable = 1.66462 with a significance level of 5%. The conclusion of this study is that there is a significant positive relationship between numeracy literacy skills and mathematics learning outcomes for fifth grade elementary school students in cluster II. Based on these conclusions, the impact obtained in this study is to determine the level of a significant relationship between literacy ability and mathematics learning outcomes for fifth grade students so that this will have an impact that at the school the teacher knows that it turns out that good numeracy literacy skills will produce good learning outcomes. also for students.
PERSONALITIES AND PSYCHOLOGICAL FEATURES OF PERPETRATORS OF COMPUTER CRIMES AGAINST CHILDREN

With increasing technology and moving people to interpersonal relationships with each other, online communication begins to shift the real world and increasingly to virtual communication. Much of the crimes and incitement to child-directed crime begin to turn into online crime. It hides even greater dangers, greater psychological pressure, victimization and harassment on victims than in real contact with them. The attempt to create a psychological profile to identify the personal and behavioral characteristics of cybercriminals against the personality is a central focus of this article. In general, malware distributors have an increased need for recognition, expression and self-assertion. They demonstrate narcissistic attitudes, egocentrism and passive-aggressive self-assertion. Most often, perpetrators show different kinds of obsessions. Malware distributors among children usually reduce their own anxiety, depression and frustration. A distinctive feature is the dehumanization of the victim and the realization of fantastic behavior. Sexual crimes in the Internet on children are sexual sadism and violence against children. Depending on the type of event, they are: "confident in their strength"; "Strong and assertive"; "Angry revenge" and "angry excitement." The perpetrators of this type of crimes are largely self-controlled, impulsive and lacking in social contacts. They lack respect for moral and legal norms.
Stereo Correspondence Estimation by Two Dimensional Real Time Spiral Search Algorithm

This paper presents a new searching algorithm titled “Two Dimensional Real Time Spiral Search Algorithm (2DRTSSA)” to compute the stereo correspondence or dense disparity map of two rectified images. The proposed algorithm can estimate the minimum stereo correspondence or disparity among all the window costs of a fixed axis from minimum to maximum range of that axis. It can also simultaneously calculate the dense disparity of another axis with the same range of axis. So the proposed method calculates stereo correspondence two dimensionally at a time and thus it increases the speed and accuracy over the existing state-of-the-arts methods of one dimensional and left-right searching strategy. The 2DRTSSA method calculates firstly the two window costs; one is along with the +x direction and another is along with –y direction .The minimum disparity of estimated two window costs and their distance parameters are remaining contribute in final selection. The rest of two window costs of –x direction and +y direction are also calculated using the same procedure. The minimum disparity of newly estimated two window costs and their distance are remaining contribute in final selection. The process is then repeated for the successive pixels of reference image along with the 2D scan lines from left to right of the whole image. The 2DRTSSA method is able to optimize the speed and accuracy of estimated dense disparity. Experimental results are compared in Section-IV (A), Section-IV (B) and Section-IV(C) with the current state-of-the-arts methods those are tested on Middlebury Standard stereo data set. The proposed 2DRTSSA method establishes the highest speed and accuracy with properly reconstructed 3D of dense disparity image.
Developing a Pop-Up Book for Written Descriptive Text for Senior High school Students

Most students get bored and unenthusiastic in mastering English descriptive text using media textbook and worksheet because they consist of one dimension and the paper on every page was not colorful and interesting.Moreover, media and material in learning English descriptive text the teachers used were limited.This research used research and development method from Sugiyono [1] adopted from Borg & Gall.The instruments of this research were the assessment rubrics of learning media from the experts, a questionnaire about students' responses toward Pop-Up Book for Descriptive Text, and test to find out the effectiveness of Pop-Up Book analysis.The experts' assessment results showed that Pop-Up Book scored 4.6 in terms of media and 4.5 in terms of the subject matter.The score showed that both media and material from the Pop-Up Book for Descriptive Text were categorized as very good criteria.The results of the questionnaire about students' response to the Pop-Up Book for Descriptive Text was 4.24 on small-scale product trial and 4.5 on a large-scale product trial with very good criteria.Both results on students' response questionnaires showed that the Pop-Up Book for Descriptive Text gained positive responses from the students.Meanwhile, the data about Pop-Up Book for Descriptive Text effectiveness was analyzed using the T-test.The result of the T-test obtained from SPSS indicated that there was a significant influence of Pop-Up Book for Descriptive text on the average score of students' descriptive text performance.Overall, it can be concluded that the Pop-Up Book for Descriptive Text is feasible and effective to be utilized as a learning media for Senior High School students.
Learning the Indonesian Language through Fictional Text Based on Ecological Literacy (Malay-Langkat) as an Effort to Realize Literate Generation

Education is a place where humans are formed to find and collect various information that will certainly be useful for shaping and developing human cognitive intelligence about many things, one of which is about ecology (environment / nature). In studying Indonesian, ecological discourse material (text) is one strategy to integrate environmental education and social interaction, as well as cultural customs of the community, especially Malay-Langkat which aims to form and develop mindsets and patterns of action, as well as healthy behavior both physically and mentally in everyday life. Through literary learning, educators are required to be more creative and sensitive in choosing interesting and suitable materials to be delivered instead of just fixating on the targets to be delivered and existing lesson plans, without thinking further about other things that can be used as a source of learning. But the availability of local ecology-based texts is still very little. This research aims to produce a Malay- Langkat literacy-based fiction text material that is feasible and effectively used at the high school level. So this research will focus more on developing a literacy culture to produce a literate generation, a generation that understands what is read and does something based on its understanding of the content of the reading. The literate generation is a generation that is intelligent, capable, characterful, and competitive. This research is a development research that adapts the 4-D Development model. Research and development steps are carried out using modifications and the Thiagarajan development model that is 4-D. This development model uses 4 stages consisting of define, design, development and dissemination.
Bi-encoder Network with Structure-texture Consistency for Image Inpainting

Existing image inpainting methods have shown their potential in filling corrupted regions with plausible contents. However, these methods tend to produce results with distorted structures or unnatural textures since they neglect the difference between structures and textures in images and jointly process these two different types of information. To solve this problem, we propose a bi-encoder network (BE-Net) that seeks to handle structure and texture information separately, and fuse them to reconstruct completed images. Specifically, BE-Net first uses two parallel encoders to infer structure and texture features of the input images respectively. Then a structure-texture consistency module (STCM) is designed to weaken artifacts and enhance visual coherency of the output images by keeping the texture features consistent with the structure features. Finally, the structure features and the texture features are fused at each level of the decoder to recover images with reasonable structures and realistic textures. Extensive experiments on Paris StreetView and CelebA datasets show the proposed approach is effective in generating realistic and visually plausible results and outperforms several state-of-the-art methods.
GENERATING APPLICATION TO HANDLE SNAPSHOTS IN GOOGLE CLOUD PLATFORM

- In this paper, we present the system for managing the snapshots on the Google Cloud Platform (GCP) environment using a scheduling mechanism to assist the people to recover their data during data failure or disaster. The usage of cloud services has been increasing and along with that there is a need to protect data in the cloud. The approach of our system adopts usage of the snapshot to manage and protect the data present in disks of the virtual machines in google cloud using scheduling and tag- based scheduling mechanism for snapshots. This will help users during disaster situation to protect and restore their data present in the Google cloud.
USING REMOTE SENSING IN STUDY OF EL NIÑO EXTREME DIFFERENCES BETWEEN 1997/1998 AND 2015/2016

The years 1997/1998 and 2015/2016 saw the occurrence of El Niño occur among the worst in human history. Until now there is still a lack of research in studying the degree of El Niño's strength impact on climate and weather, especially in the tropic region. The objective of this study is to study the effectiveness of remote sensing technology in identifying the differences between the 1997/1998 and 2015/2016 El Niño events. This study uses six satellite data and temperature data from the Malaysia Meteorology Department (MMD). The first step of remote sensing data will be through pre-processing, converting digital Numbers (DN) to Land Surface Temperature (LST). The results of the study found that there was a change in the pattern of LST columns during the 1997/1998 and 2015/2016 El Niño events. Spatial patterns change based on Oceanic Niño Index (ONI) values. The results of this study are important because of the importance of spatial information to those responsible for preparing measures to overcome and reduce the impact of El Niño on the population. at the developing country level, including Malaysia, there is still a lack of information technology infrastructure in channeling useful information to the community. Through the information, this spatial information provides critical hot spot information that needs more attention.
DEVELOPMENT OF THE EDUCATION PROCESS AND NOWADAYS SCIENTIFIC KNOWLEDGE AGAINST THE GLOBALIZATION PROCESS

This paper aims at reviewing the current situation of two fundamental issues directly related to education. First, it focuses on the process of globalization and, secondly, on the problems of the global science-driven knowledge that are needed to education and society as a whole. The term globalization is neither new nor casual in the last two decades. The development of human society has brought a lot of changes in the sphere of education. Increasingly, education systems are being transformed from their past role and content. Starting from the developments, recently, they are beginning to take new roles and functions as a function of the need to be confident in a global society and economy. Starting from the developments, recently, they are beginning to take new definitions and roles in the function of need to be more competitive in a global society and economy. The process of education itself cannot be seen or imagined disconnected from the social development. They have already become determinative of each other's development and performance, at a time when the impact of globalization directly affects the quality of education. Many researchers have tried to explain the way of changing the education process is going through, by examining the key factors associated with globalization. Likewise, the problems and challenges faced by education and research as part of it, around the world, are many. This, according to researchers, is explained by the complex nature of globalization itself.
DETECTION OF DYNAMIC HAND GESTURE USING SUPPORT VECTOR MACHINE

During past few years, human hand gesture for interaction with computing devices has continues to be thriving area of research. Hand gesture Recognition system received great attention in recent years because it provides human computer interaction and sign language. Hand gesture recognition is contain three stages: Pre-Processing, Features Extraction, classification. Most current approaches is based on the static hand gesture recognition Hand gesture recognition is often too sensitive to poor resolution ,environment of background, occultation among other prevalent problems and recognition dynamic hand gesture. So, proposed work investigates dynamic hand gesture recognition using Conditional Random Field. Result shows dynamic hand gesture recognition under complex background and achieve better recognition rate.
Generation and Visualization of Static Function Call Graph for Large C Codebases

As software systems evolve, there is a growing concern on how to manage and maintain a large codebase and fully understand all the modules present in it. Developers spend a significant amount of time analyzing dependencies before making any changes into codebases. Therefore, there is a growing need for applications which can easily make developers comprehend dependencies in large codebases. These applications must be able to analyze large codebases and must have the ability to identify all the dependencies, so that new developers can easily analyze the codebase and start making changes in short periods of time. Static analysis provides a means of analyzing dependencies in large codebases and is an important part of software development lifecycle. Static analysis has been proven to be extremely useful over the years in their ability to comprehend large codebases. Out of the many static analysis methods, this paper focuses on static function call graph (SFCG) which represents dependencies between functions in the form of a graph. This paper illustrates the feasibility of many tools which generate SFCG and locks in on Doxygen which is extremely reliant for large codebases. The paper also discusses the optimizations, issues and its corresponding solutions for Doxygen. Finally, this paper presents a way of representing SFCG which is easier to comprehend for developers.
A systematic review of CryptDB: Implementation, challenges, and future opportunities

In the case of compromised databases or interested database managers, CryptDB has been built for validated and realistic protection. CryptDB operates through encrypted data while executing SQL queries. The key concept of the SQL-aware encryption technique is to map SQL operations to encryption methods, adjustable query-driven encryption which facilitates CryptDB to modify the encryption level of data depending on user queries and to alter the data through layered encryption levels in an efficient manner. The systematic literature review in this paper shows that there is ongoing research regarding the implementation of CryptDB in new applications such as cloud computing and management information systems. Experiments are being conducted to improve the encryption schemes and layers to avoid data leakage when CryptDB is applied in dynamic applications. Further, there are studies on alternative query-processing systems to improve the performance and throughput. However, CryptDB is found to be the only practical approach to process the queries for encrypted data.
ANALISIS KEMAS ULANG INFORMASI FORMAT TEKS KE AUDIOVISUAL (STUDI KASUS VIDEO RESENSI DI KANAL YOUTUBE PERPUSTAKAAN UNIVERSITAS SANATA DHARMA YOGYAKARTA)

The purpose of this study was to know the process of producing book reviews in audiovisual format at the Sanata Dharma University Library in Yogyakarta. This type of research is classified as qualitative descriptive. Collecting data using observation, interview, and documentation techniques. The data analysis technique used in this study was the data analysis model of Miles and Huberman, namely data reduction, data presentation, and conclusion drawing. Test the credibility of the research data using triangulation and member checks. The results of this study indicate that, in general, it can be concluded that first, in the process of production of visual audio reviews some of the planning strategies done, the development of the library movie maker team, the individual movie maker, was prepared through several written and spoken tests, and good budgeting of the meeting records as referencing the production process, he set of books to be reviewed, the concept stage, the concept and the location for the shoot. The production of the stage (1) preproduction; a) preparation, b) counter-culture concept, a location, c) budgeting, and d) planning the feedback. (2) production process; and post-production.
Deploying a Kubernetes Cluster with Kubernetes Operation kops on AWS Cloud Experiments and Lessons Learned

In today's world, new virtualization technologies have become popular like container-based virtualization technologies due to its nature like lightweight, scalability, and flexibility. Kubernetes is the most popular open-source platform for container-based cluster management systems that provide mechanisms for deploying, maintaining, and scaling containerized applications across a cluster of hosts. KOPS is a Kubernetes Operations for attempting at simplifying complex installation and maintenance processes of the Kubernetes cluster. Kops helps in deploying highly available Kubernetes cluster, make installation secure, easy, and automatable applications on the AWS cloud. The rapid increase of cloud-native applications has taken cloud computing to the next level, but there are several issues in the deployment of automatable applications, and also complexity increases due to this. Nevertheless, there are still issues to be solved, such as cluster monitoring and cluster deployment automation. The goal of this paper is to deploy a containerized application onto a Kubernetes cluster using KOPS on cloud providers like AWS. This paper discusses how the Kubernetes cluster is deployed on the cloud service provider like AWS cloud using Kops which is the best tool for deploying Kubernetes cluster on AWS and also the Kubernetes services available today on cloud providers like AWS cloud and examines what they offer in comparison with other cloud providers like Google(GKE), Azure(AKE), and also the security issues in AWS cloud provider.
Sentiment Analysis on Social Media during COVID-19

Sentiment analysis is the technology under Natural Language Processing and text analysis techniques to identify and extract subjective information from text.Sentiment analysis is used in many applications for recommendation and feedback analysis.Sentiment analysis over Social Media offers organizations and individuals a fast and effective way to monitor the publics' feelings towards them and their competitors.There are several challenges facing the sentiment analysis and evaluation process.These challenges become obstacles in analyzing the accurate meaning of sentiments and detecting the suitable orientation of the expressed sentiment.Sentiment analysis is process of extracting information from the user's opinions.Every person shares his or her information on social network sites, blogs, product review websites.This paper focuses on evaluating the predictions of sentiment classifiers, additional feature extractions with practical results on defining the sentiment analysis of COVID-19 using twitter data.The analyses are based on the machine learning algorithms.This article provides an analysis on how people react to a pandemic outbreak, how much they are aware of the disease and its symptoms, what precautionary measures they are taking.Algorithms for sentiment analysis and the steps involved in it.A brief description of complex sequence-based Neural Network sentiment classifiers.