Reviewerly/exHarmony huggingface dataset:
PENGGUNAAN MEDIA ANIMASI TULISAN TANGAN UNTUK MENINGKATKAN KETERAMPILAN MENULIS KARANGAN DESKRIPSI PADA MAHASISWA

USE OF HAND WRITING ANIMATION MEDIA TO IMPROVE WRITING SKILLS DESCRIPTION OF DESCRIPTION IN STUDENTSOne of the functions of the Indonesian Language and Literature Learning course in general is as a means of increasing knowledge and skills in Indonesian language to gain and develop science, technology, and art. This research was conducted on November 20, 2019 in Class 5D PGSD FKIP UNPAK with a total of 26 people consisting of 3 men and 23 women, Odd Academic Year 2019-2020. The results of research that researchers do are processed using descriptive statistics. Based on research conducted on the assessment of descriptive essays using Handwriting Animation media, the recapitulation results are obtained as follows: For the content or ideas expressed, obtained a score of 77 with very good criteria. Content organizations score 78 with Very Good criteria. Grammar scores 78 with Very Good criteria. Style: choice of structure and vocabulary scored 76 with Very Good criteria. Results of recapitulation Assessment of the use of animated media Handwriting on the making of descriptive essays for indicators of the suitability of the material 100% of students are in conformity so that the criteria are Very Good ,. The duration of making animation 100% in accordance with the time that has been set is a maximum of 30 minutes so the criteria are Very Good. The beauty of the appearance in Handwritten animation that has been made is only 75% with the criteria Very Good. Posts that are made get 100% accordingly so that the criteria are very good..
International Law and Interdisciplinarity

The article presents three main arguments in favour of an interdisciplinary opening of international law. The first emerges from the transition from traditional international law to transnational law, as a result of which specialized legal subsystems increasingly overcome the boundaries of nation states and, by making themselves independent of the pyramidal structure of the constitutional order, tend to overlap one another. Consequently, the transnational sphere is characterized by a significant intersection of competences, so that contemporary international law cannot be understood properly without a substantial expertise in fields that transcend its usual understanding. The second argument in favour of interdisciplinarity is related to the content of law in general and of international law in particular. Because a set of norms fulfils the task of stabilizing the normative expectations that are generated within a specific social subsystem, it inevitably incorporates the kind of rationality that characterizes the functioning of that same social subsystem. Thus, to understand how a legal subsystem works, it is necessary to take into account the fundamental constituents of that kind of rationality which makes up the rules of interaction within the social subsystem related to that particular set of norms. The third argument for interdisciplinarity derives, finally, from the overall rationale of law. In fact, beyond the functional rationality that the legal norms acquire insofar as they fulfil the task of stabilizing the normative expectations generated within specialized social subsystems, the law also enshrines a more inclusive understanding of a metasystemic rationality, namely a comprehensive idea of social order. Therefore, law is to be interpreted as the system of formal propositions that lay down the rules and principles that govern human interaction according to a specific view of how the “well-ordered society” should be defined. While law’s relation to the specialized subsystems is the expression of its functional rationale, its link to the idea of how the “well-ordered society” is understood manifests its more encompassing social rationality and, by reflecting what we can define as the paradigms of order, incorporates the knowledge developed within extra-legal discourses.
Mediating Intimacy through Phatic Tokens in Social Media Communication: A Pragmatic Inquiry

People nowadays have most of their conversations on social media apps.They use many phatic tokens while having online conversations.The present study aims to analyze the types of phatic tokens youngsters use in their conversations on social networking sites.Laver's theory of phatic tokens and Scheff 's Bond Theory have been used as theoretical framework for better understanding of this discursive mechanism of phatic communication.Following mixed method approach, a small scale corpus of watsapp real interactions have been collected from 10 participants and analyzed using mixed method approach.Data reveal that phatic tokens perform the function of conflict avoidance hence very helpful in keeping harmony and balance in the community or a society.It is suggested that knowledge and awareness about the phatic communication should be made compulsory at all levels in different social institutions to create social bonds and minimizes the damages caused by conflicts and tensions, through applications of phatic communications
Detecting nondeterministic payment bugs in Ethereum smart contracts

The term “smart contracts” has become ubiquitous to describe an enormous number of programs uploaded to the popular Ethereum blockchain system. Despite rapid growth of the smart contract ecosystem, errors and exploitations have been constantly reported from online contract systems, which has put financial stability at risk with losses totaling millions of US dollars. Most existing research focuses on pinpointing specific types of vulnerabilities using known patterns. However, due to the lack of awareness of the inherent nondeterminism in the Ethereum blockchain system and how it affects the funds transfer of smart contracts, there can be unknown vulnerabilities that may be exploited by attackers to access numerous online smart contracts. In this paper, we introduce a methodical approach to understanding the inherent nondeterminism in the Ethereum blockchain system and its (unwanted) influence on contract payments. We show that our new focus on nondeterminism-related smart contract payment bugs captures the root causes of many common vulnerabilities without relying on any known patterns and also encompasses recently disclosed issues that are not handled by existing research. To do so, we introduce techniques to systematically model components in the contract execution context and to expose various nondeterministic factors that are not yet fully understood. We further study how these nondeterministic factors impact contract funds transfer using information flow tracking. The technical challenge of detecting nondeterministic payments lies in discovering the contract global variables subtly affected by read-write hazards because of unpredictable transaction scheduling and external callee behavior. We show how to augment and instrument a contract program into a representation that simulates the execution of a large subset of the contract behavior. The instrumented code is then analyzed to flag nondeterministic global variables using off-the-shelf model checkers. We implement the proposed techniques as a practical tool named NPChecker (Nondeterministic Payment Checker) and evaluate it on 30K online contracts (3,075 distinct) collected from the Ethereum mainnet. NPChecker has successfully detected nondeterministic payments in 1,111 online contracts with reasonable cost. Further investigation reports high precision of NPChecker (only four false positives in a manual study of 50 contracts). We also show that NPChecker unveils contracts vulnerable to recently-disclosed attack vectors. NPChecker can identify all six new vulnerabilities or variants of common smart contract vulnerabilities that are missed by existing research relying on a “contract vulnerability checklist.”
Research on the Majorization of the Internal Factor of the Incentive Mechanism of the Scientific Research and Training for Undergraduates

In view of the current situation and existing problems of the incentive mechanism of the scientific research and training for undergraduates, through a questionnaire survey of 800 students in RA college, and taking this as a sample for empirical analysis, this paper systematically studies the internal factors of the incentive mechanism, including the subject of incentive mechanism, the object of incentive mechanism, the process of incentive mechanism, external environment and guarantee conditions of incentive mechanism, the measures of Incentive, evaluation and feedback of incentive mechanism.
DRIVER ASSISTANCE SYSTEM FOR DISORDERED PEOPLE

Autonomous driving is currently a very active research area with virtually all automotive manufacturers competing to bring the first autonomous car to the market.This race leads to billions of dollars being invested in the development of novel sensors, processing platforms, and algorithms.In this paper, we explore the synergies between the challenges in self-driving technology and development of navigation aids for blind people and hearing loss people.The study of leverage the recently emerged methods for self-driving cars, and use it to develop assistive technology for the visually impaired, hearing impaired and mentally retarded.the task of perceiving the environment in real time from cameras.First, we review current developments in embedded platforms for real-time computation as well as current algorithms for image processing, obstacle segmentation and classification, machine learning, deep learning, iot.Our study shows that what are the problem facing visually impaired, hearing impaired and mental retarded people while driving.
Effect of Public Elementary School Financial Challenges on Student Achievement

The quality of education is often seen from the achievements of students. Meanwhile, student achievement in school is influenced by many factors. The financing factor is one factor that cannot be separated from the teaching and learning process. The relationship between educational funding and student achievement is still being debated. This study aims to reveal the relationship between the number of funding resources in schools and student achievement. This research used qualitative methods. Data collection was carried out using interviews, observation, and documentation techniques. The collected data were analyzed using interactive model analysis and purposive sampling techniques. The results of this study indicate that public elementary schools have limited sources of funding. The amount of money managed by one school differs depending on the number of students and the ability of parents. This study finds that education funding has no direct effect on student achievement. Schools that have significant financial resources do not necessarily have high achievements. The effectiveness of schools in managing their finances also becomes essential. Besides, the role of policymakers, the ability of teachers, and the participation of parents are crucial to increase the education quality.
SISTEM INFORMASI ABSENSI SISWA BERBASIS SMS GATEWAY DENGAN MENGGUNAKAN PHP PADA PROGRAM MONITORING ABSENSI PESERTA DIDIK

Discipline of students and students in the school environment is very important in the process of teaching and learning activities in the school environment, where the discipline can be seen from the results of the attendance attendance of students and students every day. Monitoring student attendance is carried out by each subject teacher who teaches in each class, and then gives it to the student administration staff. The method used in this research is the waterfall method (Waterfall Model) which begins with an analysis of the applications that are running, design, coding, and maintenance of information systems. The author conducts research and looks at student attendance information systems that still have problems that occur. Problems that often occur are the slow process of delivering student absenteeism information to the homeroom teacher, the absence of applications for delivering student absentee information that is fast, accurate and relevant to administrative staff, homeroom teachers, and student guardians, and the absence of student attendance monitoring applications as information media realtime student attendance. Based on the analysis that has been done, it is obtained that, to overcome the problems that occur in the existing student attendance Information System, it is necessary to design and implement a structured system in order to run as expected&#x0D;
MASTER STUDENTS` WORK WITH AUTHENTIC SCIENTIFIC MATERIALS AS A KEY FACTOR OF ADVANCEMENT OF SCIENTIFIC DISCOURSE

mAstEr stuDEnts` worK with AuthEntic sciEntific mAtEriAlsAs A KEY fActor of ADvAncEmEnt of sciEntific DiscoursE summary.Today, the world`s countries are experiencing a new stage of economic development and changes in social and political life.These changes form new, more sophisticated requirements for the professional training of young specialists.Every university graduate should possess a high level of professional competencies as well as communication skills necessary for effective communication and interconnection when solving professional tasks.Speaking about young scientists, one can mention that they are to be armed not only with practical and theoretical knowledge but with foundations of a methodology of scientific work, with the skills to collect and process information, develop programs of scientific research, analyze the results and formulate them in the form of scientific reports, abstracts of scientific conferences, other academic papers.For this purpose, Masters of Science are taught the discipline "English for Scientists", the main task of which is to prepare them for independent and effective research activities.The article emphasizes that mastering the peculiarities of the scientific style suggests mastering the rules of written and oral foreign language communication between scholars.Recent research in the field of scientific translation was analyzed.Some aspects of organizing students' work on authentic texts in foreign language classes were highlighted.It was found that the essential practical skills that a student has to master are abstracting a scientific text, writing an annotation to a scientific article in English, which, in its turn, indicates the formation of functional and linguistic competences.For this reason, the structural elements of the scientific article are highlighted and the basic requirements for writing the abstract are named.The authors of the article conducted a survey of Master students, which revealed the need for systematic work with the authentic scientific texts in foreign language classes, which could provide a thorough knowledge of lexical and grammatical features of the scientific style of speech.A high level of proficiency in academic communication in English is an important prerequisite for self-realization in the scientific field of the international arena.
Detection of Militia Object in Libya by Using YOLO Transfer Learning

Humans can recognize and classify shapes, names, and provide responses to object that are received by visually quickly and accurately. More importantly, it is expected that the system created is able to help provide response in all tasks and time, for example when driving, walking in the crowd even when patrolling as a member of the military on dangerous terrain.This has become a problem in the system used on the battlefield. In the proposed system, the object detection model must be able to sort out the objects of armed humans (militia) with unarmed human objects. To overcome the problem the author uses the YOLO transfer learning algorithm which currently has the third version. It is stated that YOLOv3 has very extreme speed and accuracy. In mean Average Precision (mAP) obtained by 0.5 IOU, YOLOv3 is equivalent to 4x faster than Focal Loss. Moreover, YOLOv3 also offers optimal speed and accuracy simply by changing the size of the model, without the need for retraining. DOI: https://doi.org/10.26905/jtmi.v6i1.4025
Implementation of Autoencoder based Neural Network for Realtime Ray Tracing

This paper proposes a denoising neural network for real-time ray tracing.The ray-tracing method is applied in graphics to increase the reality and in particular, Monte Carlo Rendering is most effective.However, ray tracing that applies Monte Carlo Rendering has a steep rise in the number of calculations with the increase of the number of rays.Therefore, to solve this problem, various methods are being proposed to reduce the number of rays and to decrease the occurring noise.In this paper, an autoencoder-based neural network that can effectively remove noise while using a small number of rays was implemented.An autoencoder that uses a 1×1 convolution in creating the last feature map was proposed to significantly lower the amount of calculation.The proposed structure can handle an 8196 spp ray-tracing image in 20 seconds at 64 spp.
PEMBANGUNAN SISTEM INFORMASI POSYANDU DI KECAMATAN SINDANG KABUPATEN INDRAMAYU (Studi Kasus : Posyandu Mawar Desa Panyindangan Wetan)

Posyandu Mawar is a health service unit that is tasked with carrying out maternal and child health services (KIA) in the RW 02 Panyindangan Wetan Village, Sindang District, Indramayu Regency. At present, the data management process in Mawar Posyandu is still done manually by recording data into seven (7) register formats. This method is considered inefficient because it causes difficulties in the Posyandu Mawar data management process. To overcome these problems, the authors intend to develop a web-based posyandu information system using PHP as a programming language and MySQL as a database management system. Data collection is done by observation and interview. The system development method used is a structured method. The tools used in system analysis and design are Flow Of Diagrams (FOD), Data Flow Diagrams, Data Dictionaries, Entity Relationship Diagrams (ERD) so as to produce an integrated application. The results of this study are posyandu data processing applications that can help Posyandu Mawar in reporting service activities to infants and pregnant women. In subsequent developments, it is expected that the posyandu information system is equipped with KMS ribbon chart features to monitor the child's weight development.
Crime Investigation using Data Mining

The Crime rate around the world is very large in number and increasing dramatically. In the present investigation techniques and approaches, police officers have to put their time and manpower to solve these cases by analysing collected information, figuring suspects & finding criminal(s). As information collected throughout crime investigation is enormous, data processing is the technique that can prove very helpful. Data Mining is a technique that will be used to extract useful information from a large amount of crime information so that possible suspects of the crime will be known with efficiency. The best playacting algorithmic program is used against sample crime and criminal information to spot the possible suspects of the crime.
Study Of Understanding Types Of Occupational Students End Of Semester Of Indonesian Language And Literature Education Study Programs In Banda Aceh

This research was conducted with the aim of describing the politeness of the speech acts of students in the final semester of Indonesian Language and Literature Education in Banda Aceh. The focus of this research is what kind of politeness is used by students in the last semester of Indonesian Langu
Efficient Online Multi-Task Learning via Adaptive Kernel Selection

Conventional multi-task model restricts the task structure to be linearly related, which may not be suitable when data is linearly nonseparable. To remedy this issue, we propose a kernel algorithm for online multi-task classification, as the large approximation space provided by reproducing kernel Hilbert spaces often contains an accurate function. Specifically, it maintains a local-global Gaussian distribution over each task model that guides the direction and scale of parameter updates. Nonetheless, optimizing over this space is computationally expensive. Moreover, most multi-task learning methods require accessing to the entire training instances, which is luxury unavailable in the large-scale streaming learning scenario. To overcome this issue, we propose a randomized kernel sampling technique across multiple tasks. Instead of requiring all inputs’ labels, the proposed algorithm determines whether to query a label or not via considering the confidence from the related tasks over label prediction. Theoretically, the algorithm trained on actively sampled labels can achieve a comparable result with one learned on all labels. Empirically, the proposed algorithm is able to achieve promising learning efficacy, while reducing the computational complexity and labeling cost simultaneously.
MEASURING THE EFFECT OF SOCIAL NETWORKING, ORGANIZATIONAL CULTURE TOWARD EMPLOYEE ENGAGEMENT IN SOES ORGANIZATION: CASE STUDY OF SOES IN INDONESI

SOEs in Indonesia has been expanded their project with tight time and more challenged business climate. In fact, similar to private organization, SOEs also faced with employee performance in their projects. The employee performance has many aspects of social networking, organizational culture and employee engagement. This study tested the influence of social networking, organizational culture and employee engagement on in several projects which ventured by State Owned Enterprises in Indonesia. The variables are analyzed by using SEM AMOS. It is explained that social networking, organizational culture and employee engagement affect employee engagement in SOEs-based projects in Indonesia. This study suggested an approach to improve social networking, organizational culture and employee engagement as new strategies for SOEs in Indonesia. This study result can be a recommendation to the SOEs managers to maintain social networking, organizational culture and employee engagement in order their project to be manageable.
Few-shot learning via model composition

国家重点研发计划 "大数据分析的基础理论和技术方法" (批准号: 2018YFB1004300)、国家自然科学基金 (批准号: 61773198, 61632004) 和计算机软件新技术协同创新中心, 南京大学优秀博士研究生创新能力提升计划项目资助 摘要 机器学习依赖大量样本的统计信息进行模型的训练, 从而能对未知样本进行精准的预测.搜集 样本及标记需要耗费大量的资源, 因而如何基于少量样本 (few-shot learning) 进行模型的训练至关重 要. 有效的模型先验