Reviewerly/exHarmony huggingface dataset:
Smart Hand Glove for Hearing and Speech Impaired

Abstract: With the advancement of technology, we can implement a variety of ideas to serve mankind in numerous ways. Inspired by this, we have developed a smart hand glove system which will be able to help the people having hearing and speech disabilities. In the world of sound, for those without it, sign language is a powerful tool to make their voices heard. The American Sign Language (ASL) is the most frequently used sign language in the world, with some differences depending on the nation. We created a wearable wireless gesture decoder module in this project that can transform the basic set of ASL motions into alphabets and sentences. Our project utilizes a glove that houses a series of flex sensors on the metacarpal and interphalange joints of the fingers to detect the bending of fingers, through piezoresistive (change in electrical resistance when the semiconductor or metal is subjected to mechanical strain) effect. The glove is attached with an accelerometer as well, that helps to detect the hand movements. Simple classification algorithms from machine learning are then applied to translate the gestures into alphabets or words. Keywords: Arduino; MPU6050; Flex sensor; Machine learning; SVM classifier
Progger: Programming by Errors (Work In Progress)

This paper describes a work in progress implementation of a programming tool that puts errors and their provenance at the forefront of the interaction between a developer and a compiler. We discuss the motivation for such a tool, it’s design and implementation, and reflect upon avenues for further research which it can facilitate.
SISTEM NOTIFIKASI MASA TENGGANG PEMINJAMAN ALAT BERAT BERBASIS GSM SERVICE PADA CV.CIPTA KARYA GROUP

Heavy equipment lending services at CV.Karya Cipta Group in their daily management still use the concept of simple recording using a loan master book which is managed by the company's administrative officer. Currently, it often happens that the consumer of the loan company is late in returning the loan of heavy equipment, thus increasing the cost of borrowing that is not known by the consumer. This is certainly detrimental to the borrower because they do not know or forget the date of return. While the CV.Karya Cipta Group as a provider of heavy equipment lending services is often forgotten to remind. Based on the borrowing process and the problem of returning heavy equipment borrowing, a reminder system is needed which is intended for heavy equipment borrowers consumers who are recorded in the information system. The reminder system can be in the form of a GSM service system such as an SMS gateway that can be forwarded in the form of notification of information on the grace period for returning the heavy equipment vehicle, so that it can be returned on time. CV.Cipta Karya Group. This final project research uses the SDLC (Software Development Life Cycle) method using PHP, MySQL and Gammu programming. This final project produces a notification system for a GSM service-based heavy equipment loan grace period based on PHP programming and a MySQL database, and information on the loan grace period will be sent via SMS Gateway to the heavy equipment consumer company.
The Development of Chinese Language and Literature Major Under the Background of Big Data

At this stage, under the background of the rapid development of network technology, the ways and means of information transmission have become more abundant.Our society should conform to the development trend of the times and enter the era of big data.In the era of big data, all people's social activities can not leave the network, and information dissemination and convergence are becoming more and more rapid.In this context, the professional development of Chinese language and literature has encountered more opportunities and challenges.This paper aims at how to avoid the impact of the new environment, conform to the trend of network development, optimize and expand the prospects of Chinese language and literature, and launch a series of reasonable analysis, as a reference
THE CORRELATION BETWEEN GRAMMAR MASTERY AND WRITING ABILITY ON MIDWIFERY STUDENTS OF STIKES PEMBINA PALEMBANG IN 2019

The purpose of this study was to determine the relationship between grammar mastery and writing ability on midwifery students at STIKES Pembina Palembang. The population in this study was 22 of fourth semester students of the midwifery study program, STIKES Pembina and study sample were all the population that using total sampling. The data were obtained by using 2 tests, namely the TOEFL (structure and written expression) test and the English writing test. To verify the hypothesis, the data were analyzed by using correlation analysis and using the Statistical Product and Service Solution (SPSS) software version 21.00. Based on data analysis the correlation coefficient on grammar mastery and writing ability was 0.790, this showed that the relationship had a very high relationship and the value of r- is higher than the critical value of r null hypothesis table (Ho) was rejected and consequently, the research hypothesis (H1) received. Keywords : Grammar Mastery, and Writing Ability
BCS Partner: Outsource.Dev - How to Optimise Teams When Outsourcing

Abstract Ideas for team building and organisational structures for software development projects involving internal staff and outsourced developers, from Greg Billington MBCS, CEO and Founder of outsource.dev.
ASSESSING READABILITY OF READING TEXT 'BRIGHT', AN ENGLISH COURSE FOR JUNIOR HIGH SCHOOL STUDENTS

Textbook is one of media instruction that used in almost every grade level student at the school. Textbook is crucial teaching learning material composed of text or images that is used in many schools and facilitating sequences of learning activities. This title of this study “Assessing Readability of Reading Texts in ‘Bright’, an English Course for Junior High School Students” is taken because predicting readability level of reading texts can help the teachers to match the texts with students in comprehending the material. The causes of this observe is to recognize the clarity degree of studying texts in English language textbooks utilized by trainer. These studies make use of quantitative technique to investigate the information. Twelve studying texts are decided on as studies population. All of decided on texts are analyzed using Flesch Reading Ease method. In this studies, the researchers locate clarity of studying texts with inside the ‘’Bright’’ aren’t appropriate for 9th grade students. Based at the end result of Flesch reading ease method, from 12 reading texts, 9 (75%) studying texts are too Easy for 9th grade students, 3 (25%) studying texts are Standard for 9th grade students. They are three studying texts (25%) appropriate for 9th grade students.
Securing Web Services with Keycloak

We have been talking about web services, how the approaches evolved, and how to write web services, but there is a very important topic when we are talking about exposing services on the Internet that I didn’t mention: security.
The impact of access to finance and institutional barriers on SMEs' performance: difference between the formal and informal sector

This paper explores the impact of access to finance and institutional barriers on small and medium-sized enterprises' (SMEs) sales. For the purpose of this empirical study, two samples were used for both formal and informal SMEs in Kosovo. The sample of formal SMEs consists of 1,000 businesses, while the sample of informal SMEs consists of 250 businesses. The logit models were employed to find out the impact of access to finance and institutional barriers on SMEs performance in both sectors. Findings indicate that access to finance and institutions affect the performance of SMEs in the formal and informal sector. Furthermore, findings show that access to finance and institutional barriers affect the performance of formal SMEs more than informal ones. The evidences show that formal SMEs outperform informal ones in terms of sales.
Privacy and Security: Ethical Impact Assessment on Deploying Automated Facial Recognition Technology (AFRT) in Government Sectors

This research report details the findings from an analysis, evaluation, deployment of an Automated Facial Recognition Technology (AFRT) government utilize this system to magnify user authentication, authorization, and exclusive identification for access to various state-level services for instance to enhance an application for, and renewal of, state vehicle, boat, and firearms licences. The government put AFRA as a trial model to conduct an assessment to understand the preliminary’s factors of project deployment, CAPEX/ OPEX cost, performance, and benefits to the state departments. During the project trial, the State Police department have manifested their interest in AFRA and that they would like to see a roll-out of AFRA into the streets of all major cities in the state to enhance their monitoring, security capability, and quickly identify criminals and other “persons of interest”. The role of AFRT will be part of the state police organizational routine operational activities. The national and economic day-to-day operations of countries across the globe now rely entirely on cyberspace as virtually all business processes, state government projects are vastly utilizing cloud resources for storage, access, and management operations. Because of any potential identity theft either any organization facing a major security breach of their data which emanate the disclosure of sensitive assets could have profound consequences which affect the organization’s core values and causing financial impoverishment, disruption of services, legal and regulatory compliance issues, affects public reputation and workforce reduction. In this report, we consider the project potentials, all the possible risks, benefits, and ethical implications of the proposed deployment of the AFRA system in the state government services and vastly covered attack formulation phases, biometric use cases on the public and private sector, privacy policy, frameworks, data protection laws, and violations, and privacy impact assessment
PENINGKATAN HASIL BELAJAR SISWA MELALUI PENERAPAN METODE DISKUSI PARTISIPATIF PADA SISWAKELAS IV SD NEGERI BUNG KECAMATAN TAMALANREA KOTA MAKASSAR

ABSTRACT: Improving Student Learning Outcomes through the Method of Participatory Discussion On the Students Class IV of SD Negeri Bung District Tamalanrea Makassar City. Day is aim at the goal to determine the effectiveness of the use of Methods of Participatory Discussion in improving student learning outcomes. The type of this research is using classroom action research. The subject of this study as many as 35 students of class IV SD Negeri Dude Makassar, this Study is divided into 2 cycles. This study lasted for one month which consists of 4 meetings, data Collection was done qualitatively that obtained from the observation during the teaching and learning process during the study and the quantitative are obtained from the test results of the learning of subjects in each cycle. Furthermore, the data were analyzed qualitatively, which describes the results of actions during the learning process, and quantitatively by using descriptive statistics, namely the average score, frequency table, minimum value, maximum value and distribution tables and percentages. The results of this study showed that the activeness of students in the learning process and learning outcomes of students has increased through the application of the Method Participatory Discussion. It is based on the data obtained from the studies conducted in Cycle I with the learning outcomes of students 63,42% and sikulus cycle II with the results of the student learning 76%. Keywords : Hasill learning, Participatory Discussion.
Best Razer Mechanical Keyboard

I had always wondered about what was so special about a Razer mechanical keyboard that made my brother make the brand his first and only choice for a ...
Comparison of the School Systems in Japan and Korea: From the Perspective of IB

The world''s demand for quality of life is changing. This means that the world is changing from a competitive society to a cooperative society. In order to realize this, it is important to make the individual "self" the basis of the International Baccalaureate Program. The introduction of the International Baccalaureate Program makes it necessary to reexamine conventional schooling. Comparing the state of educational policy in Korea and Japan, the most important difference is that in Korea decentralization of education has begun, but in Japan centralization of education has remained. In terms of culture, the two countries share common roots in Confucianism. However, there are significant differences between the two governments in the way their cultures have developed. These differences in structural changes are affecting various aspects of life. The purpose of this paper is to use the above as a basis for identifying a curriculum in which the two countries can work together to raise children who can appreciate the differences between the people of Korea and Japan, as described in the I.B. philosophy.
Knowledge-Enhanced Graph Attention Network for Fact Verification

Fact verification aims to evaluate the authenticity of a given claim based on the evidence sentences retrieved from Wikipedia articles. Existing works mainly leverage the natural language inference methods to model the semantic interaction of claim and evidence, or further employ the graph structure to capture the relation features between multiple evidences. However, previous methods have limited representation ability in encoding complicated units of claim and evidences, and thus cannot support sophisticated reasoning. In addition, a limited amount of supervisory signals lead to the graph encoder could not distinguish the distinctions of different graph structures and weaken the encoding ability. To address the above issues, we propose a Knowledge-Enhanced Graph Attention network (KEGA) for fact verification, which introduces a knowledge integration module to enhance the representation of claims and evidences by incorporating external knowledge. Moreover, KEGA leverages an auxiliary loss based on contrastive learning to fine-tune the graph attention encoder and learn the discriminative features for the evidence graph. Comprehensive experiments conducted on FEVER, a large-scale benchmark dataset for fact verification, demonstrate the superiority of our proposal in both the multi-evidences and single-evidence scenarios. In addition, our findings show that the background knowledge for words can effectively improve the model performance.
Why the New Administration Should Bury the New Madison Approach

The “New Madison” approach sounds so promising. Old but new. Updating the classics for the modern era. What could be bad? In a word: everything. The intersection of patent and antitrust law has a long pedigree. For decades, antitrust’s role in patent-based activity has been acknowledged. Patent licenses are subject to antitrust scrutiny. “Pay for delay” settlements are not entitled to antitrust immunity. And activity in the context of standard setting organizations could conceivably violate antitrust law. That history has recently come under attack. Between 2017 and 2020, the head of the Department of Justice’s Antitrust Division, Makan Delrahim, introduced a radical framework — the “New Madison” approach — that extricated patent-based conduct from antitrust scrutiny. Such a gambit diverged from the longstanding bipartisan approach that had recognized antitrust’s role in policing standards-based conduct. This essay introduces standards and then addresses five tenets of Delrahim’s approach. For each, it presents the argument and then discusses its flaws.
PEMEROLEHAN BAHASA ANAK USIA 3-4 TAHUN DI DESA TEGALREJO BANYUWANGI DALAM KAJIAN PSIKOLINGUISTIK

This research will discuss the form of language acquisition for children aged 3-4 years and what factors influence language acquisition in children aged 3-4 years. In this case the researcher studies in the realm of psycholinguistics, because the language process in children is inseparable from psychology in humans. This research uses descriptive qualitative type. Retrieval of data using observation, interviews, and documentation techniques. The object of this study was children aged 3-4 years. Data Analisys from this reseach is The use of data analisys model interaktif according from Milles and Huberman is data collectif, data reducsi, data presentation, adn conclusion. The results and conclusions of this study are that 3-year-old children are able to communicate with their interlocutors using simple sentences. Consonantal pronunciation /r/ and consonant groups are not yet mastered. Children who are 3.5 years old can say declarative, introgative sentences. Mastery of several objects around him can he express through storytelling. Consonantal pronunciation /r/ and consonant groups are not yet mastered. Children aged 4 years have increased language production. Language acquisition factors for children aged 3-4 years are biological, environmental, cognitive, and electronic media that are often accessed such as devices and television.
Frameworkfor Pervasive Context Aware Pandemic Diseases Infected Person Identificationand Information Deliverywith Special Referenceto COVID-19 (The Caseof ETHIOPIA)

Human history is observing an awfully strange time fighting an invisible enemy; the novelpandemic COVID-19 coronavirus. Initially observed within the Wuhan province of China,now fastly spreading around the world. An emerging area of great impact and significance isthe application of pervasive computing technologies in healthcare; that specialize in enablingpervasive computing environment using mobile devices. Currently there are issues in home tohome testing/investigation for corona virus infected peoples while they are migrating fromplace to place for testing, timeliness, opportunity missing due to anxiety, anywhere, anytimeinaccessibility, dynamic and static reporting over small hand held devices like mobiles. Thisresearch aims to develop a framework for pervasive context aware pandemic diseasesinfected person identification and information delivery with special reference to COVID-19.The researcher followed an applied research design with empirical analysis. This is the mixof two main approaches (quantitative and qualitative). For primary data collection Survey,Interview and Practical observation of the researcher are used for collecting the relevant factson researchability attributes, issues and challenges. Edraw-Max is used for designing thesystem framework and Google Form for Survey. The system framework consists of clientserver architecture in which citizens’ and health care workers are the two sorts of clients anda server serves to both of them. The information’s of infected people are delivered to theserver either in PULL/PUSH mode then the server implicitly PUSH’s the information tohealth care worker. In PULL mode, the system provides a listing of possible signs andsymptoms for the user to explicitly pass his/her signs and symptoms to the server and theserver analysing the user signs/symptoms and performs reasoning and decisions supportedcontext data store in the context repository backend databases.Then, it delivers the relevantinformation to the health care workers. On the opposite hand, in PUSH mode, the serveranalysing the user’s signs and symptoms based on the information from the user mobiledevice while they are using or opening by automatically measuring their temperature, thesystem pushes notification message to the health care workers.
Tjøme Investigation Progress

A distinction is made in the Norwegian criminal justice system between suspected, charged, indicted, convicted, and lawfully convicted person. Many individuals were in the spring 2018 suspected based on rumors, allegations, and accusations. To charge someone, the police needs a solid basis for suspicion. When they have charged someone, the police have powers available to them, such as search warrants, seizure of documents, and wiretapping. The next step of indictment after a charge means that the suspect becomes a defendant during court hearings. A conviction can be appealed, while a lawfully convicted person has received the final verdict. When Okokrim later changed the position of architect Breili from suspected to charged individual, they searched his home and his office.
실시간 화상 한국어 수업에서의 상호작용 활성화를 위한 온라인 도구 활용 방안

This study aims to examine the diverse types of available online tools in synchronous Korean language classes and propose practical application methods. Research on synchronous Korean classes in Korean language education began at the start of the COVID-19 pandemic, and studies have demonstrated that active interactions are necessary for successful online classes. Applications such as Zoom, Google Meet, and Webex are used by default in online classes, but Google Docs, Google Forms, Padlet and Mentimeter can also be used to promote interaction. In this paper, these tools were utilized for small group conversations, simple response displays, data retrieval and sharing, memo boards, questionnaires/ statistics, mind maps, and quizzes. To demonstrate each tool’s application in the Korean classes, a section of “Sejong Korean Conversation” was used as an example. Before the class, Zoom’s annotation function or Padlet’s memo function was used to enhance familiarity and bring attention to the teacher’s presence. During the introduction phase, Mentimeter’s survey, wordcloud, and mind-mapping function were used to generate interest in the topic and activate background knowledge. At the activity/task level, Google Docs was used for engaged discussion. In the final phase, Padlet and Google Survey were used to receive feedback about the lesson or perform a self-assessment.
Detection of Hate Speech and Offensive Language in Twitter Using Sentiment Analysis

Abstract: The dramatic development of online media, for example, Twitter and local area gatherings has upset correspondence and content distributing, but at the same time is progressively misused for the spread of disdain discourse and the association of disdain based exercises. The secrecy and portability managed by such media has made the rearing and spread of disdain discourse – in the long run prompting disdain wrongdoing – easy in a virtual land scape past the domains of conventional law requirement. Existing techniques in the identification of disdain discourse principally cast the issue as a regulated report grouping task [33]. These can be partitioned into two classifications: one depends on manual element designing that are then devoured by calculations, for example, SVM, Naive Bayes, and Logistic Regression [3, 9, 11, 15, 19, 23, 35–39] (exemplary techniques); the other addresses the later profound learning worldview that utilizes neural organizations to consequently learn multi-facets of dynamic highlights from crude information [13, 26, 30, 34] (profound learning strategies). In this technique We show that it is a significantly more testing task, as our examination of the language in the commonplace datasets shows that disdain discourse needs interesting, discriminative highlights and hence is found in the 'long tail' in a dataset that is hard to find. We then, at that point propose Deep Neural Network structures filling in as highlight extractors that are especially powerful for catching the semantics of disdain discourse. Our techniques are assessed on the biggest assortment of disdain discourse datasets dependent on Twitter, and are demonstrated to have the option to beat best in class by up to 6 rate focuses in large scale normal F1, or 9 rate focuses in the seriously difficult instance of recognizing derisive substance. As an intermediary to evaluate and think about the semantic attributes of disdain and non-disdain Tweets, we additionally propose to contemplate the 'uniqueness' of the jargon for each class. Keywords: Classic Methods; DNN; Detection of hate speech and offensive language in Twitter; Sentimental Analysis