Reviewerly/exHarmony huggingface dataset:
대학생의 글쓰기 능력 변화과정 추적을 위한 단기 종단 연구

The purpose of this study is to suggest a systematic and effective writing education method through tracking the changing process of writing ability of university students. For this purpose, this study examined how university students'' writing ability developed according to the writing process. According to the analysis of writing ability evaluation results, the better the writer was, the more negative the subject evaluation was. On the other hand, the response of the inexperienced writer was negative in the composition evaluation, and the same result was obtained in the actual teacher evaluation. In expression evaluation, a good writer wrote fewer inscriptions considering the response of subject and predicate. In addition, the supporting sentences for the soju statement were properly prepared to complete the article. In the evaluation of creativity, the better the writer, the more negative the reaction was. By tracking these changes in writing skills, we can suggest that the teaching methods in the writing process can utilize the following writing strategies. First, in the pre-writing stage, the learner should organize the composition of the writing, ask questions by himself, and specify the outline of the writing. Second, draft writing should organize and elaborate writing activities, evaluate learners themselves, and embody what they write through questions, checks, and reading. Third, the revision requires a writing strategy to re-edify and reorganize draft articles, and to review, restructure, and revise the entire article through advisors, reevaluation, and material statements.
Classification of Emojis using Artificial Neural Network and Natural Language Processing

This paper presents a generalized system which can be integrated with any machine learning or deep learning classification algorithm to find the intended interpretation of an emoji in a sentence. The primary purpose of this system is to detect and translate the offensive or the sexual meanings represented by the emojis into English words so that it can be classified by any classifier. The system is designed to store and retrieve the emojis and their meanings into a hierarchical lookup data structure. This data structure uses natural language processing to translate an emoji or a string of emojis into the meaning that best fits the sentence in which they were in. As a result, this system was able to determine the possible meaning from all the plausible meaning of an emoji or a string of emojis with respect to the statement. These results were further supported and validated by the high accuracy of the deep learning classifier used to classify the translated sentences.
Estimation of the probability of correct determination of the coordinates of an object in computer modeling of methods for selecting their images

Abstract The article discusses the issues of computer modeling of methods for selecting images of objects. It considers a test video sequence with given background and object parameters. The issues of computer simulation of the formation of such a video sequence, as well as the process of selecting an image of an object and measuring its coordinates are discussed. Examples of test images and graphs of the obtained dependencies of the probability of the correct determination of coordinates depending on the specified parameters of the object and background are given.
PROSEDUR PEMBAYARAN UTANG PENGISI ACARAPADA PT. NET MEDIATAMA TELEVISI

This final assignment Report aims to learn more about the debt payment procedures of performer in the world of work and has a specific purpose for writing this final assignment, namely the Diploma Three (DIII) graduation program for the Veteran National Development University accounting department Jakarta. In carrying out the Field Work Practice, there are many benefits, one of is to improve and sharpen the skills possessed in the real world of work. The author chooses the place of Field Work Practices at PT. Net Mediatama Televisi is located at The East Building 30th floor, Jl. DR. Ide Anak Agung Gde Agung Kav. E3.2, East Kuningan, South Jakarta, DKI Jakarta, Indonesia. PT. Net Mediatama Televisi is a service company engaged in the field of Entertainment Media and Information Technology services. During carrying out Field Work Activities, the author is placed in the Budget Management Accounting department. Procedure is a step that must be obeyed by each work unit in the framework of cooperation to launch information flow. Debt payment procedures are needed to complete a Debt activity that arises due to the purchase of goods or services on credit and must be paid to the vendor or supplier carried out by staff payments so that effective cooperation is established, namely as applied at PT. Net Mediatama Televisi in carrying out debt activities in carrying out the debt process uses Gamba System Applications and manually. After carrying out the Field Work Practices conclusions can be drawn that can make students improve to be more confident in the world of work and gain experience in the world of work. So that it can be used as a provision for writers to enter the world of work to come.
Generalized Doubly Reparameterized Gradient Estimators

Efficient low-variance gradient estimation enabled by the reparameterization trick (RT) has been essential to the success of variational autoencoders. Doubly-reparameterized gradients (DReGs) improve on the RT for multi-sample variational bounds by applying reparameterization a second time for an additional reduction in variance. Here, we develop two generalizations of the DReGs estimator and show that they can be used to train conditional and hierarchical VAEs on image modelling tasks more effectively. First, we extend the estimator to hierarchical models with several stochastic layers by showing how to treat additional score function terms due to the hierarchical variational posterior. We then generalize DReGs to score functions of arbitrary distributions instead of just those of the sampling distribution, which makes the estimator applicable to the parameters of the prior in addition to those of the posterior.
Recurrent Waves of Jailbreak in Nigeria: The Imperatives of Prison Intelligence and Dynamic Security Strategies in Managing the Nigerian Correctional Facilities

This paper painstakingly addresses the phenomenon of rising waves of prison or jailbreak in Nigeria. And as generally observed according to the dictates of Nigerian law, jail or prison break remains an illegal or unlawful act under which a prisoner forces his or her way out of the prison in a state. This phenomenon of jailbreaks has in one way or the other impacted negatively on the society and posed dangerous threats to national peace and security. The paper in its objectives endeavours to: highlight the series of jailbreaks that have taken place in Nigeria and the various techniques employed by the escapees; interrogate the causal factors of jailbreaks in the country; and also examine the roles of prison intelligence and dynamic security in curtailing the menace. The study makes use of the regulatory capture theory to explain the bane of the phenomena while descriptive and content-analysis techniques are adopted. With the aid of primary and secondary data, the paper is able to reveal that; corruption, ineffective Correctional Service Arms Squad and Intelligence Unit, lack of prison intelligence and dynamic security, among others have weakened the Nigerian Correctional facilities’ security and led to incessant jailbreaks in Nigeria. The paper, however, recommended; putting in place a very sensitive nature of prison information and intelligence; establishing a prison intelligence management board; adopting a multi-agency approach security strategy; and training of prison-based intelligence officers for intelligence gathering and information sharing as strategies of curtailing the rising spate of jailbreaks in Nigeria.
An On-Road Study in Mitigating Motion Sickness When Reading in Automated Driving

This on-road study explores the effect of a visual (VPIS) and haptic peripheral information system (HPIS) on a user’s level of motion sickness when engaging in reading activity while being driven in a fully automated vehicle (AV). Both systems notify the user regarding the upcoming navigational information in the lateral direction, and HPIS also supports the user from being involuntarily moved by the lateral acceleration when cornering. It was hypothesized that both systems would reduce the experienced motion sickness compared to those without any intervention. Eighteen participants with severe motion sickness susceptibility were exposed to low-frequency lateral acceleration that induces a moderate-to-severe dose of motion sickness. The automated driving was simulated by an automated-like instrumented vehicle and performed with the Wizard-of-Oz approach. The participants were asked to perform reading while being exposed to three different conditions (control-, VPIS-, and HPIS-condition), each for about 15-minutes. Results from a self-rating questionnaire indicated statistically significant decreases in motion sickness found with the presence of HPIS but not with VPIS. Results showed HPIS produced the least experienced motion sickness while VPIS exacerbated the symptoms of motion sickness. Adaptation effects were also found due to the repetitive exposure to the same route of automated driving. Keywords: automated driving, peripheral information system, motion sickness.
THE CORRELATION BETWEEN ENGLISH CLASS PERFORMANCE AND SPEAKING SKILL

Speaking skill is one of important skill that should be mastered by English Education Department students. To improve speaking skill, English Students Association in STKIP PGRI Tulungagung make a program which is called as ECP (English Class Performance). In this program, all students from second to sixth semester shoul present a speech in front of all students from second to sixth semester. The objective of this study is to know whether ECP correlated to studentsâ?? speaking skill. Based on the result of this study, it is known that there is correlation (positive correlation) between ECP and speaking skill of English Education Department students at STKIP PGRI Tulungagung
KETRAMPILAN KEWIRAUSAHAAN SEBAGAI PEMBERDAYAAN POTENSI ANAK ASUH YAYASAN PANTI ASUHAN KRISTEN JAWA TIMUR DI MALANG

The purpose of this PkM activity is to empower the potential of foster children (girl) of the East Java Christian Orphanage Foundation as the target audiences to spark motivation and creativity so that they become independent individuals. Empowerment is carried out by providing entrepreneurship skills training. The material studied is Basic Knitting using the Single Crochet Stitch, Half Double Crochet Stitch and Double Crochet Stitch technique to create a Semi Solid Granny Square pattern which will produce a product in the form of a Tote Bag. PkM activities are divided into 3 modules, the first is theoretical briefing about the objectives, benefits and tips, as well as the importance of having an entrepreneurial spirit and high motivation to learn various kinds of skills, the second is a theoretical explanation of basic knitting techniques / Crocheting and the Semi Solid Granny Square pattern for making Tote Bags, and the third practice and practice to produce a product that is worth selling so that it can be marketed so that it can help with economic problems and welfare in their families.  From the training that was held for 2 days, and assistance for independent learning online through Whatsapp media to 10 foster children (girl), 4 gilrs were successful with their commitment to produce the final product in the form of a Tote Bag, even 1 of them managed to enrich and sharpen her own skills by combining the thread color in the final product. Based on the results of the evaluation, it can be concluded that the training ran smoothly and effectively and brought benefits, because the target audiences could absorb the knowledge conveyed and was able to produce the finished product as targeted from the start
Mobile Apps Pendidikan Islam SPM Sirah dan Tamadun (Khulafa’ Ar-Rasyidin)

Pendidikan Islam is one of the subjects which become compulsory for Muslim students taking Sijil Pelajaran Malaysia (SPM) examination. Pendidikan Islam is divided into sections including al-Quran, Hadith, Akidah, Fiqh, Akhlak and Sirrah. Khulafa 'Ar-Rasyidin is one of the topics in Sirrah that describes the history and events in the Islamic era after the demise of prophet Muhammad (pbuh). Technological advancement and various applications, such as entertainment, will now contribute to a lack of interest in education for students. As an alternative, the research practically developed a 2D animation as an edutainment to improve the quality of learning for students, especially SPM students, as well as to promote a mobile application for education. Islamic history is very important to students in connecting the past with the present era. The design and prototypes development employed in this study are based on waterfall model. This application was evaluated by 30 respondents, consisting of teachers and students, using a pilot test to find out its acceptance as an edutainment material. The overall evaluation of this apps had a positive impact on teachers and students as they enjoyed learning Pendidikan Islam through Mobile Application.
Histogram based QR Code Authentication using Medical Images

Medical images require proper attention during the information embedding since the information which is to be embedded should not disturb the image quality. The remedy for the distortion caused by embedding data into medical images can be overcome by using lossless data hiding techniques. QR Code are consisting of relevant medical information that can be retrieved easily. In the present, information security become vital asset at the communication services, thereby concealing of information become a dilemma. For this issue, we employ a method known as Steganography in which the data is concealed in a medium like text, image etc., and appears to be normal, without affecting the quality of the hidden medium. Watermarking enables the protection of data format which is embedded with other data format and provides ownership access to the end user in unrecognizable format. Both steganography and watermarking techniques employ greater security to the information which can be embedded within a data format of any type.
Explainable Reinforcement Learning for Risk Mitigation in a human-robot collaboration scenario

Reinforcement Learning (RL) algorithms are highly popular in the robotics field because the can solve complex control problems, learn from dynamic environments and generate the optimal outcome. Explainability for all Machine Learning (ML)-based algorithms including RL is gaining importance because of the increasing complexity of the models, which makes them more accurate but at the same time less transparent. The need for explainability increases even more in Human-Robot Collaboration (HRC) scenarios where safety is an important aspect to be guaranteed. This work focuses on the application of two explainability techniques, “Reward Decomposition” and “Autonomous Policy Explanation”, on a RL algorithm which is the core of a risk mitigation module for robots’ operation in an automated warehouse scenario, a HRC environment where human and robots work together without harming one another. The first technique used is “Reward decomposition” which gives an insight on the factors that impacted the robot’s choice by decomposing the reward function into sub-functions, each considering a specific aspect of the robot’s state, and using a graphical type of explanation. It also allows to create Minimal Sufficient Explanation (MSX), sets of relevant reasons for each decision taken during the robot’s operation. On the other hand, the second applied technique, “Autonomous Policy Explanation”, provides a global overview of the robot’s behaviour, letting it answer either targeted or general queries asked by human users, but also providing insight on the decision guidelines embedded in the policy learnt by the robot. Since the synthesis of the policy descriptions and the queries’ answers are in natural language, this tool facilitates algorithm diagnosis even by non-expert users. The work provides an analysis of the results of the application of both techniques which both led to increased transparency of the robot’s decision process, building trust in its choices which proved to be among the optimal ones in most of the cases, but also made possible to find weaknesses in the robot’s policy helpful for debugging purposes.
Ownership and Bank Efficiency in Africa: True Fixed Effects Stochastic Frontier Analysis

This paper investigates the effects of ownership patterns on bank cost and profit efficiencies taking a sample of 607 commercial banks operating in 53 African countries during the period 2005-2015. Using pooled and modified true fixed effects (TFE) stochastic frontier panel approaches, we obtain two principal results. First, foreign-owned banks are more profit and cost efficient than their domestic peers. Second, privately owned banks outperform state-owned banks. These findings result not only from bank-level inefficiency but also from differences related to other bank- and country-specific factors. Specifically, larger, older, and listed banks with many years of operations in host countries are associated with higher cost and profit efficiency. This study also reveals that ownership concentration (blockholding) has adverse effects for the profit and cost efficiency of banks.
Sosialisasi Pembelajaran E- Learning Menggunakan Aplikasi Edmodo Pada Siswa-Siswi Kelas XI SMA Adiguna Bandar Lampung

The use of technology in the learning process changes our understanding that IT-based learning is being intensified. Learning using technology, one of which is internet-based learning or so-called e-learning. In e-learning, many learning media are used to help implement the learning process, one of which is Edmodo. Edmodo is a digital learning platform for teachers / lecturers and students / students that provides several features to support e-learning such as assignments, quizzes, assessments, and so on. Through edmodo teachers and students can share notes and documents and can have online discussions. The target of the implementation of this service activity is the XI grade students of SMA Adiguna Bandar Lampung. This service activity was held on Saturday, March 21, 2020 and took place at the Adiguna SMA Bandar Lampung Hall with 50 participants. The results of the evaluation, the results and benefits of this service activity were obtained, including the increase in student knowledge about e-learning using the Edmodo application.
FILTRA: Rethinking Steerable CNN by Filter Transform

Steerable CNN imposes the prior knowledge of transformation invariance or equivariance in the network architecture to enhance the the network robustness on geometry transformation of data and reduce overfitting. It has been an intuitive and widely used technique to construct a steerable filter by augmenting a filter with its transformed copies in the past decades, which is named as filter transform in this paper. Recently, the problem of steerable CNN has been studied from aspect of group representation theory, which reveals the function space structure of a steerable kernel function. However, it is not yet clear on how this theory is related to the filter transform technique. In this paper, we show that kernel constructed by filter transform can also be interpreted in the group representation theory. This interpretation help complete the puzzle of steerable CNN theory and provides a novel and simple approach to implement steerable convolution operators. Experiments are executed on multiple datasets to verify the feasibility of the proposed approach.
Weathering and Mineral Formation in Soils

The term weathering comprises all changes that rocks and minerals undergo in contact with the atmosphere or hydrosphere, referred to as subaeric weathering or subaquatic weathering, respectively.
저널리즘 생산자로서 '문제적 기자'에 관한 연구 - 민속지학적 방법을 중심으로 -

The study began with a focus on social phenomena in which producers, journalists, are in the spotlight rather than articles, which are the result of journalism. After an era of exclamations, exclusive or in-depth articles, recent audience of journalism have begun to attack journalists. The behavior, which began from a critical perspective on the results of journalism produced by a particular journalist, came at last to attach the scornful term ‘Kireki(journalist+trash)’ to journalists. Many people are concerned about this social phenomenon as a ‘crisis of journalism’. Therefore, the crisis phenomenon of journalism was approached through in-depth interview with journalists who are considered to be representative 'problematic journalist' among journalists and news consumers. The ‘problem journalists’ had something in common that the way they entered the world of journalists was not orthodox and did not have a proper journalism education. They pretended to be a fanatic even before entering the world of journalist in the field they were covering, and after becoming a journalist, they were either overly friendly to what they liked or obsessed with comments advocating their own articles. However, the fact that they have become 'problematic journalists' could not simply turn it into an individual problem. The reality that the control of the newsroom has become meaningless due to changes in the media environment, and the excessive authority given to journalists' individuals have also made them problematic journalists.
Deep Learning to Improve Breast Cancer Detection on Screening Mammography

The speedy development of deep learning, a family of machine learning techniques, has spurred abundant interest in its application to medical imaging issues. Here, we have a tendency to develop a deep learning algorithmic program which will accurately sight carcinoma on screening mammograms victimization AN “end-to-end” coaching approach that with efficiency leverages coaching datasets with either complete clinical annotation or solely the cancer standing (label) of the complete image. during this approach, lesion annotations square measure needed solely within the initial coaching stage, and future stages need solely image-level labels, eliminating the reliance on seldom offered lesion annotations. our all-convolutional network technique for classifying screening mammograms earned glorious performance compared with previous strategies. On AN freelance take a look at set of digitized film mammograms from the Digital info for Screening diagnostic technique (CBIS-DDSM), the most effective single model achieved a per-image United Self-Defense Force of Colombia of zero.88, and four-model averaging improved the United Self-Defense Force of Colombia to zero.91 (sensitivity: eighty-six.1%, specificity: eighty.1%). On AN freelance take a look at set of full-field digital diagnostic technique (FFDM) pictures from the IN-breast info, the most effective single model achieved a per-image United Self-Defense Force of Colombia of zero.95, and four-model averaging improved the United Self-Defense Force of Colombia to zero.98 (sensitivity: eighty-six.7%, specificity: ninety-six.1%). we have a tendency to additionally demonstrate that a full image classifier trained victimization our end to-end approach on the CBIS-DDSM digitized film mammograms may be transferred to IN breast FFDM pictures victimization solely a set of the IN-breast information for fine-tuning and while not any reliance on the supply of lesion annotations. These findings show that automatic deep learning strategies may be without delay trained to realize high accuracy on heterogeneous diagnostic technique platforms, and hold tremendous promise for up clinical tools to scale back false positive and false negative screening diagnostic technique results.