Reviewerly/exHarmony huggingface dataset:
Attendance System Implementation Existing Android Platform Using React Native Framework

In a school that has hundreds of students, the attendance system or attendance recording is a problem in terms of practicality and data capture. Especially during a pandemic like this, learning is carried out online or in a network, commonly called distance learning (PJJ). Currently, various applications of technological advances have been created and begun to replace conventional systems. One of them is an Android-based attendance application system. The purpose of this study is to analyze and design an application that can help manage attendance data more easily and accurately. System modeling uses Unified Modelling Language (UML) to describe visually, then implemented with PHP and JavaScript programming languages, React Native Framework, and MySQL database as a database. With the mobile-based attendance system, it can make it easier for teachers to conduct attendance effectively and efficiently.
Classification of Health and Nutritional Status of Toddlers Using the Naïve Bayes Classification

Life is characterized by the presence of symptoms of growth and development. The growth and development of the degree of health of each individual are different. In this case, one of the efforts to improve health status is to improve nutritional status. Nutritional status is the state of the body related to food consumption patterns and the use of nutrients that are tailored to the body's needs. Improving nutritional status is useful for increasing body resistance and promoting normal growth. In the daily actualization of the nutritional status of toddlers at the posyandu, it is usually obtained through anthropometric measurements, namely by using the weight/age index or weight-for-age to determine nutritional status. However, in measuring with anthropometry, there was confusion in determining nutritional quality, so to get accurate results, a data mining method is needed, namely the Naive Bayes Classification (NBC) Algorithm, which will be implemented in research. With this research, it is hoped that it can help posyandu cadres in the Baros sub-district, Cimahi sub-district, and Cimahi city determine the level of health and nutritional status of toddlers better and more accurately.
Inception Models for Fashion Image Captioning: An Extensive Study on Multiple Datasets

Fashion e-commerce platforms are becoming increasingly popular. However, scanning, rendering, and captioning fashion items are still done mostly manually. In this work, we address the task of generating a textual description of a fashion item from an image portraying it. We carry out an extensive study with several neural architectures based on InceptionV3. We consider two existing fashion image captioning datasets, FACAD and InFashAI. We also curate a novel dataset, Fashion-Cap, that contains more than 290,000 images and 40,000 corresponding captions. In our analysis, we observe significant differences between the three datasets' captions, with Fashion-Cap having higher quality captions. To the best of our knowledge, this is the most extensive experimental study in fashion image captioning to date. Our experimental results show that our dataset is less challenging than FACAD but more than InFashAI, which confirms our insights, suggesting that it could be a valuable benchmark for this domain.
A Retrospective Study on English Teachers’ Strategies to Increase Students’ Vocabulary Mastery

Various teaching methods and techniques have been the focus of numerous studies on teaching strategies used to increase students' vocabulary understanding. Few studies, however, have looked at the methods teachers employ to increase their students' vocabulary mastery through retrospective study. This retrospective review of the study collected various types of teaching strategies that benefit teachers. Researchers combined a descriptive method with a qualitative research approach with a questionnaire design for this study. Instruments in this research is a survey in the form of google form. The types of questions in previous research surveys used many types of closed-ended questions in the form of statements. In contrast, the types of questions in this study used many open-ended questions that produced answers consisting of many ideas. Fifteen English teachers who teach English in Medan are the subjects of this study. The result of this research is the strategies used by teachers in teaching student vocabulary mastery are very diverse depending on students' and teachers' abilities. The more diverse the teacher's teaching strategies, the more successfully students will learn new words. The teaching strategy is then divided into three, namely preparation, practice, and evaluation strategies. In the end, it is anticipated that the findings of this study will help teachers succeed in developing their students’ vocabulary mastery.Various teaching methods and techniques have been the focus of numerous studies on teaching strategies used to increase students' vocabulary understanding. Few studies, however, have looked at the methods teachers employ to increase their students' vocabulary mastery through retrospective study. This retrospective review of the study collected various types of teaching strategies that benefit teachers. Researchers combined a descriptive method with a qualitative research approach with a questionnaire design for this study. Instruments in this research is a survey in the form of google form. The types of questions in previous research surveys used many types of closed-ended questions in the form of statements. In contrast, the types of questions in this study used many open-ended questions that produced answers consisting of many ideas. Fifteen English teachers who teach English in Medan are the subjects of this study. The result of this research is the strategies used by teachers in teaching student vocabulary mastery are very diverse depending on students' and teachers' abilities. The more diverse the teacher's teaching strategies, the more successfully students will learn new words. The teaching strategy is then divided into three, namely preparation, practice, and evaluation strategies. In the end, it is anticipated that the findings of this study will help teachers succeed in developing their students’ vocabulary mastery.
Assessing the Use of Cohesive Devices in Reading Texts of English Textbook

The present study began with wide use of a textbook entitled "Bahasa Inggris" in Sorong. The book is written by Utami Widiati, Zuliati Rohmah, and Furaidah. It focuses on analyzing all the reading passages in the chosen chapters. Qualitative descriptive implemented in assessing the use of cohesive devices proposed by Halliday and Hasan’s (1976) theory. The findings reveal 895 grammatical and 222 lexical cohesions in the reading passages. The grammatical consisted of 622 references, 15 substitutions, 22 ellipses, and 236 conjunctions and the lexical cohesion consisted of 186 reiterations and 36 collocations. Furthermore, as support in providing the text's coherence, the researchers asked the students as ttextbook users to read the passages. It was proven that the texts were readable and understood by the readers. However, they took time to understand the passages with more ellipsis and collocation. Hopefully, this study will give the readers and authors insight of the reading texts by using appropriate cohesive devices in creating coherent reading texts as instruments for teaching and learning.
Realization of Thematic Progression to Achieve Grammatical Cohesion in Students' Final Project Backgrounds

This research aimed to find out how the thematic progression structure is applied in the background of students’ research project proposal and how the thematic progression functions to achieve cohesion in the background of the research project proposal. The objectives of this research were to explain the structure of thematic progression and to explain the function of thematic progression to achieve cohesion in the background of the studies section of students’ final project proposal. This research used a descriptive qualitative approach. Fifteen research project proposals were used as the source of the data. The research findings reveal that a constant theme was the primarily used pattern of thematization to organize the research project proposal background in students’ writings. It concluded that the realization of the constant theme was the most straightforward pattern of thematization applied by the students to organize the final projects. That was not hard because the form of the constant theme was just repeated, replaced, substituted, or changed some non-numeral description into a similar way to a clause. Besides, it was found that the amount of reference, substitution, and conjunction occurs in the text, and Ellipsis did not apply to 15 texts. So both grammatical references and substitutions were achieved in this area through thematic progression. The thematization used by the students was able to achieve grammatical cohesion in their writings
Pedagogical, Interpersonal and Instructional Functions of Code-switching to Support Online Classroom Learning

This study was conducted during the COVID-19 pandemic when a shift from traditional classrooms to online classroom learning happened. Faced with online learning challenges, teachers practiced various strategies to support their classes. In EFL contexts, the way teachers manage these challenges can be investigated through online code-switching. The present qualitative study investigates an Indonesian EFL teacher’s perception and use of classroom code-switching in promoting pedagogical, interpersonal, and instructional functions to support teaching and learning in online classroom settings. The study gained data through a semi-structured interview to gauge the EFL teacher’s perception and by observing several online English classroom recordings. The findings were analyzed using Ferguson’s (2003) and Gumperz’s (1982) theories, supported by stimulated recall interviews. The study found that the EFL teacher has a positive and supportive perception of classroom code-switching for online classroom teaching and learning. In realization, analysis results showed that the EFL teacher practiced classroom code-switching in her online classrooms and promoted functions including pedagogical (e.g., reiteration, message qualification, etc.), interpersonal (e.g., establish rapport, negotiate identities), and instructional functions (e.g., negotiate task instruction, disciplining, etc.). The study provided insights on classroom code-switching practice in online settings to encourage teachers to efficiently use code-switching to support their online classroom teaching and learning.
Survey of Undergraduate Students' Perceptions through the Online Learning

The purpose of this study was to determine how students’ perception of online learning during the Pandemic of COVID-19. Quantitative descriptive analysis was used to analyze the data. The researchers used a Google Form questionnaire as the instrument to obtain the data. The researchers used a Likert scale to examine the questionnaire and analyze the results. To find out how students’ perception of online learning during the Pandemic of Covid -19, ten questions of questionnaires were evaluated. The result of study indicated various students’ perspective to the online learning implementation. The various perceptions came from different situation such as environment, family, finance, and others.The highest percentage of positive perceptions regarding to online learning was from the students at University of Tridinanti Palembang and continued from the students at University of Muhammadiyah Palembang, then the students at Collage of Agriculture and Science Palembang, and the last was from students of Islamic University of Raden Fatah Palembang. Furthermore, some students also showed low percentage of neutral and negative perception. Therefore, universities and lecturers must work together to minimize the negative sides of online learning, as well as optimize the advantages of the internet and technology.
The Effect of College Students' Ego Resilience on Career Preparation Behavior -The Recognition of strengths-

본 연구의 목적은 대학생의 자아탄력성이 진로준비행동에 어떠한 영향을 미치는 지를 알아 보고 대학생의 자아탄력성이 진로준비행동에서 강점인식의 매개효과를 검증하는 것이다. 연구대상은 4년제 대학생 300명이며, 연구방법은 대학생의 강점인식, 자아탄력성, 진로준비행동을 측정한 자료로 각 변인 간의 상관관계를 확인하기 위하여 Pearson의 상관분석을 실시하였다. 대학생의 자아탄력성이 진로준비행동의 관계에서 강점인식의 매개효과를 검증하기 위하여 회귀분석을 실시하였다. 연구결과 대학생의 자아탄력성이 진로준비행동에 미치는 영향 연구에서 강점인식의 매개효과 검증을 종합해보면 다음과 같다. 첫째, 자아탄력성과 강점인식, 진로준비행동과의 관계를 살펴본 결과 세 변인 간의 정상적인 범위로 경향성을 충족시켰다. 둘째, 진로준비행동, 자아탄력성, 강점인식 주요변인 간에 모두 유의미한 정적상관관계를 보였다. 셋째, 자아탄력성과 진로준비행동의 관계에서 감정인식이 부분 매개 효과를 보였다. 이러한 연구결과는 대학생의 자아탄력성이 진로준비행동을 하는데 강점을 인식하는 것은 대학생들의 진로와 취업에 대한 확신을 주는 변인으로 대학생들에게 기여할 것이다.The purpose of this study is to find out how college students ego resilience affects their career preparation behavior and to verify the mediating effect of college students self-resilience in their career preparation behaviors. The subjects of the study were 300 four-year university college students, and the research method was data that measured college students strength perception, self-resilience, and career preparation behavior. Regression analysis was performed to verify the mediating effect of strength recognition in the relationship between career preparation behaviors. The results of the study are as follows. First, as a result of examining the relationship between ego resilience, strength perception, and career preparation behavior, the tendency was satisfied within the norma l range among the three variables. Second, there was a significant positive correlation among the major variables of career preparation behavior, self-resilience, and strength perception. Third, emotional recognition showed a partial mediating effect in the relationship between self-resilience and career preparation behavior. The results of this study show that recognizing the strength of college students self-resilience in their career preparation behavior will contribute to college students as a variable that gives them confidence in their career path and employment.
The Realization of the Derivational and the Inflectional Processes in the Students’ Writing

In learning a language, students are supposed to study linguistics in order to be able to recognize the root of words, how they are formed, and the context of language. This study aimed to explain the realization of the derivational process, the inflectional process, and the causes of the error in the students’ writing. This study used a descriptive qualitative design. The researchers analyzed the students’ writing essays written by the XII-graders of the Vocational High School Al-Musyaffa Kendal in the academic year 2021/2022. The instruments are document analysis theory and interview. It used the theory of Dulay et.al. (1982). The findings demonstrate that the students made errors that belong to both the derivational and the inflectional processes. Most of the students made errors in the omission of derivation, yet they made fewer errors in the addition and malformation of derivation. Besides, there were many problems in dealing with the inflection. Most of the students were confused about how to deal with the omission of noun inflection and the omission of verb inflection. Nevertheless, they made fewer errors in the misordering of verb inflection. In addition, the cause of the error that the students did was mostly carelessness as it occurs due to students’ lack of motivation and less enthusiasm in engaging in the teaching and learning process. Expectantly, this research will provide an essential contribution as a reference in comprehending word formation and contribute to teaching and learning of forming English words.
Data Privacy for Digital Asset Systems

Data privacy in digital asset systems is of sustained importance to end users. However, there can be disconnect between an end user’s expectations of privacy while using a digital asset payment system and the system’s actual treatment of collected, stored, and used data. This paper provides foundational primer on data privacy alongside qualitative and technical assessments of various approaches to data privacy frameworks and strategies relevant to the early stages of a digital asset system’s design. Analysis relies initially on an outlay of foundational data privacy concepts, including anonymity, confidentiality, and full disclosure, alongside three differing approaches to data privacy frameworks. Analysis finds that some concepts, such as a desire for “cash-like anonymity,” are based on false underlying assumptions. The paper moves away from a likely unattainable standard of anonymity and instead focuses on a hybrid approach to data privacy, inclusive of Cavoukian’s privacy-by-design and popular applications of privacy-by-policy. This hybrid approach is visualized with a technical comparison of privacy-enhancing technologies (PET) across architectural layers, detailing both popular and emerging PETs relevant to digital asset systems which prioritize a hybrid approach to confidentiality. The paper further finds that a particular combination of popular and emerging technologies may provide as-yet untested but novel benefits to maintaining strong confidentiality – and possibly end users’ expectations of privacy – while data is under audit. A nuanced approach, rather than a reliance on a singular novel PET or dubious assurances of anonymity, may best facilitate strong confidentiality with sustainable end-user privacy protections for digital asset system users.
Comparing the Pretrained Models of Source Code by Re-pretraining Under a Unified Setup

Recent years have seen the successful application of large pretrained models of source code (CodePTMs) to code representation learning, which have taken the field of software engineering (SE) from task-specific solutions to task-agnostic generic models. By the remarkable results, CodePTMs are seen as a promising direction in both academia and industry. While a number of CodePTMs have been proposed, they are often not directly comparable because they differ in experimental setups such as pretraining dataset, model size, evaluation tasks, and datasets. In this article, we first review the experimental setup used in previous work and propose a standardized setup to facilitate fair comparisons among CodePTMs to explore the impacts of their pretraining tasks. Then, under the standardized setup, we re-pretrain CodePTMs using the same model architecture, input modalities, and pretraining tasks, as they declared and fine-tune each model on each evaluation SE task for evaluating. Finally, we present the experimental results and make a comprehensive discussion on the relative strength and weakness of different pretraining tasks with respect to each SE task. We hope our view can inspire and advance the future study of more powerful CodePTMs.
LITERATUR REVIEW AUGMENTED REALITY SEBAGAI MEDIA PROMOSI DENGAN METODE MARKER BASED TRACKING

Augmented Reality (AR) is a technology that combines real-world objects with virtual or digital objects in a real-world setting. Real and virtual objects are merged using appropriate technologies, and interactions occur through specific tools and devices. The use of AR in solving everyday life problems has expanded across various fields, including advertising. Brochures are one of the print media that can be used for advertising and integrated with augmented reality technology. The use of augmented reality technology in brochures can provide a new solution in brochure creation, making them more creative, engaging, and accessible to a wider audience. It offers complete, clear, and easily accessible information compared to traditional brochures
Joint Probability Distribution Regression for Image Cropping

Image cropping aims at locating a candidate (rectangle region) with the highest aesthetic quality in professional photography. One solution of the previous methods is to generate a large number of candidates and then filter them, which leads to low efficiency. Another idea directly regresses the candidate coordinates to speed up but ignores the aesthetic subjectivity of the candidate’s evaluation, limiting the model’s performance. In this paper, we present an Aesthetic and Composition joint Probability Distribution regression Network (ACPD-Net) to explicitly investigate the process of generating the candidate with a joint probability distribution paradigm to improve the performance of cropping results in an efficient way. The joint probability distribution paradigm between location and size branch can identify the subjective aesthetic region and satisfy the objective composition rules in an end-to-end manner. Our method has been tested on the FCDB and FLMS datasets, which shows the superiority of ACPD-Net. The code is available at https://github.com/flyingbird93/ACPD-Net.
ULcompress: A Unified low bit-rate image Compression Framework via Invertible Image Representation

In this paper, we propose a unified low bit-rate image compression framework, namely ULCompress, via invertible image representation. The proposed framework is composed of two important modules, including an invertible image rescaling (IIR) module and a compressed quality enhancement (CQE) module. The role of IIR module is to learn a compression-friendly low-resolution (LR) image from the high-resolution (HR) image. Instead of the HR image, we compress the LR image to save the bit-rates. The compression codecs can be any existing codecs. After compression, we propose a CQE module to enhance the quality of the compressed LR image, which is then sent back to the IIR module to restore the original HR image. The network architecture of IIR module is specially designed to ensure the invertibility of LR and HR images, i.e., the downsampling and upsampling processes are invertible. The CQE module works as a buffer between IIR module and the codec, which plays an important role in improving the compatibility of our framework. Experimental results show that our ULCompress is compatible with both standard and learning-based codecs, and is able to significantly improve their performance at low bit-rates.
NSGA-II optimal Evolutionary echo state network for performance degradation prediction of PEMFC

Proton exchange membrane fuel cell (PEMFC) is regarded as the future energy capable of replacing existing fossil fuels. Performance degradation prediction is an effective method to improve the durability of PEMFC. However, traditional performance degradation prediction focuses solely on the accuracy of estimation results without focusing on how to achieve better estimation results with fewer resources. In this paper, we proposed an echo state network (ESN) to estimate the performance degradation. To improve the prediction accuracy and decrease the computing complexity, NSGA-II is used to optimize the hyperparameters of ESN. The simulation results show the RMSE is less than 0.0035. The NSGA-II-ESN can obtain Pareto solutions between accuracy and computing complexity, then provide corresponding optimal ESN models for devices with different performances.
Tell Your Story: Text-Driven Face Video Synthesis with High Diversity via Adversarial Learning

Face synthesis is a rapidly growing area of research in computer vision. Text-driven face synthesis is particularly flexible, but challenges still exist in fusing the semantics of text and images, as well as generating diverse faces. To address these challenges, we propose a cross-modality adversarial learning framework to generate highly diverse face videos that correspond to given text descriptions. We encode text and images into a common latent space and align text and image features to control the synthesis of face attributes. We have designed a novel auto-encoder with a face identity discriminator that enlarges the margin between different individuals, increasing the variety of created faces while maintaining the semantic coherence of text and images. Our proposed method has been successfully tested on the recently released Multimodal VoxCeleb dataset. Our code is public available at https://github.com/sunmeng7/TYS.git.