Reviewerly/exHarmony huggingface dataset:
Probabilistic matching of real and generated data statistics in generative adversarial networks

Generative adversarial networks constitute a powerful approach to generative modeling. While generated samples often are indistinguishable from real data, mode-collapse may occur and there is no guarantee that they will follow the true data distribution. For scientific applications in particular, it is essential that the true distribution is well captured by the generated distribution. In this work, we propose a method to ensure that the distributions of certain generated data statistics coincide with the respective distributions of the real data. In order to achieve this, we add a new loss term to the generator loss function, which quantifies the difference between these distributions via suitable f-divergences. Kernel density estimation is employed to obtain representations of the true distributions, and to estimate the corresponding generated distributions from minibatch values at each iteration. When compared to other methods, our approach has the advantage that the complete shapes of the distributions are taken into account. We evaluate the method on a synthetic dataset and a real-world dataset and demonstrate improved performance of our approach.
PENGEMBANGAN BAHAN PEMBELAJARAN DENGAN MENGGUNAKAN BUKU BERGAMBAR SEBAGAI MEDIA PEMEROLEHAN BAHASA INDONESIA

The objectives of this study are 1) to describe the acquisition of Indonesian language by means of picture books for elementary school children; 2) describe the development of picture books in accordance with the cognitive development of elementary school students.This research belongs to the type of development research or what is called research and development (R&amp;D). Sources of research data are teachers, parents and first grade students of SD Negeri 068074 Medan. Data collection techniques using observation, questionnaires and interviews. The data analysis techniques used are qualitative and quantitative techniques&#x0D; The results of the acquisition of Indonesian for elementary school children consist of several stages, namely the pre-linguistic stage, the one-word stage, the two-word stage, and the many-word stage. The development of picture books in the study went through the stages of gathering information and it was known that there were problems in developing children's language acquisition due to the limitations of books and also the competence of teachers in teaching. The next stage is the preparation of the instrument and continued with the validation of the instrument that has been compiled, the results are that the instrument is suitable for use. The next stage is the development of book designs, namely teacher guidebooks and student books. The results of expert validation on the product showed that the average score for the assessment of the teacher's manual and student's book products was 3.98, so the book developed was suitable for use without revision. The next stage is product testing. The results of the teacher's guide book assessment get a score of 3.93 in the "very good" category and the student book gets a score of 3.96 in the "very good" category. This research resulted in the final product in the form of a picture book equipped with a teacher's manual for one year, student books for semester one and two.
(ψ, ϕ)-Wardowski contraction for three maps in Gb-metric spaces

Introducing (ψ, ϕ) − Gb-Wardowski contraction for three maps, a common fixed point result is obtained for complete Gb-metric spaces. An application related to discontinuous activation function in neural network is also established.
mRNA Approach Image Encryption Using LUC Algorithm

Bioinformatics is one of the computer science and biology sub-subjects concerned with the processes applied to biological data, such as gathering, processing, storing, and analyzing it. Biological data (ribonucleic acid (RNA), deoxyribonucleic acid (DNA), and protein sequences) has many applications and uses in many fields (data security, data segmentation, feature extraction, etc.). DNA sequences are used in the cryptography field, using the properties of biomolecules as the carriers of the data. Messenger RNA (mRNA) is a single strand used to make proteins containing genetic information. The information recorded from DNA also carries messages from DNA to ribosomes in the cytosol. In this paper, a new encryption technique based on (mRNA) amino acids to increase the diffusion of the algorithm was proposed, also using the LUC algorithm with finite field arithmetic to increase the complexity of the algorithm. The results show high resistance against well-known attacks on the proposed method. For Entropy, the achieved value for the encrypted images was above 7.998. The range of peak signal to noise ratio (PSNR) between plain and encrypted images was below 8.7. Finally, the unified average change intensity (UACI) was close to 0.335. The number of changing pixel rates (NPCR) was close to 0.996, which is considered a good result.
Blockchain Technology Aimed at Solving Internet of Things Challenges: A Systematic Literature Review

The main objective of this work is to conduct a systematic review of the literature on IoT technology (internet of things) and the application of blockchain technology. For this, an exhaustive research was carried out and when analyzing the documentation of aspects such as: area of study on the integration of technologies, most used consensus techniques and the benefits of technology were considered. The results of the study indicated blockchain technology with IoT being implemented in companies and industries; with the most consensus techniques being POW and POS, while the benefits are manifested in terms of improved scalability and security of companies.
Controlling Type Confounding in Ad Hoc Teamwork with Instance-wise Teammate Feedback Rectification

Ad hoc teamwork requires an agent to cooperate with unknown teammates without prior coordination. Many works propose to abstract teammate instances into high-level representation of types and then pre-train the best response for each type. However, most of them do not consider the distribution of teammate instances within a type. This could expose the agent to the hidden risk of \emph{type confounding}. In the worst case, the best response for an abstract teammate type could be the worst response for all specific instances of that type. This work addresses the issue from the lens of causal inference. We first theoretically demonstrate that this phenomenon is due to the spurious correlation brought by uncontrolled teammate distribution. Then, we propose our solution, CTCAT, which disentangles such correlation through an instance-wise teammate feedback rectification. This operation reweights the interaction of teammate instances within a shared type to reduce the influence of type confounding. The effect of CTCAT is evaluated in multiple domains, including classic ad hoc teamwork tasks and real-world scenarios. Results show that CTCAT is robust to the influence of type confounding, a practical issue that directly hazards the robustness of our trained agents but was unnoticed in previous works.
The Speaking Skill by Using Slang Words in a Movie through Mind-Mapping Strategy

The main objective of this study is to apply the teaching of speaking English through mind mapping strategy for the students at the English Department of Bina Sarana Informatika University. The participants included 20 students in the third semester. Speaking is an important skill in English language learning which is used by the students to communicate in their class and daily activities as a way of learning practice. By this mind mapping strategy, this paper aims at showing that this strategy can be implemented to get active speaking skills. This research uses a qualitative method to describe the practice application of classroom observations and the emerging themes of the original slang words gained through watching a movie. The data were carried out by observing, documenting, and interviewing students about the speaking teaching-learning process in the classroom using the English slang words in a movie with a mind-mapping strategy. The data was analyzed and focused on classroom practice directly related to the use of slang words in a movie and the mind-mapping strategy. The results showed that implementing a mind-mapping strategy through slang words in a movie can be conducted by knowing the meaning of the slang word in the movie, mapping the slang word into the sentence, and practicing the slang word in the student’s conversation. This mind-mapping strategy is effective in helping the EFL students to enrich their vocabularies, enhance their memory in making conversation, and remember the material easier and more creatively.
Expression Techniques for Human Body Motion Using a Game Engine

In this paper, we acquired Taekwondo motion data using motion capture technology and conducted realistic and abstract visualization studies of the motion data. The motion expression techniques was composed of four stages of character, mesh, skeleton and joint visualization according to the degree of realism to abstraction. The Unity game engine was used to create interactive content that can visualize Taekwondo movements in real time with various expression methods. According to the expression method, the audience's opinions on the four perspectives of understanding, creativity, aesthetics, and interaction were surveyed and analyzed.
Financing Management in Islam-Based Schools in the City of Tasikmalaya

The purpose of this study was to analyze budget planning to improve education in Islamic-based schools, organize and implement financial management in improving the quality of education, as well as the monitoring and accountability system for financing education in Islamic-based schools in Tasikmalaya City. The research design is qualitative combined with percentage descriptive. Data collection uses observation and interview methods, as well as documentation. The data analysis technique uses the Miles and Hubermann interactive analysis model which includes four stages, namely data collection, data reduction, data presentation according to the classification of themes, and drawing conclusions. The results of the study found that 1) education budget planning was prepared and stated in the form of a school income and expenditure budget plan which was prepared at the end of each year by establishing all program plans and the budget for each program, involving internal school stakeholders through meetings, 2) organizing funding Education starts from the source of the funds themselves, 3) budget execution is used according to plan with slight modifications in real implementation, 4) the supervision of education financing is carried out by foundations, and 5) the responsibility for school financing is left to school committees, foundations, and education offices.
Fast 128-bit Multi-Pass Stream Ciphering Method

Information is an essential and valuable object in all systems. The more information you have about your issue, the better you can conform to the world around you. Moreover, information recognizes companies and provides influence that helps one company be more effective than another. So, protecting this information using better security controls and providing a high level of access to authorized parties becomes an urgent need. As a result, many algorithms and encryption techniques have been developed to provide a high level of protection for system information. Therefore, this paper presents an enhancement to the Blowfish algorithm as one of the cryptography techniques. Then it proposes an enhancement for increasing efficiency and secrecy for this algorithm, which are the main criteria for these modifications. In this paper, the main modification made for the Blowfish algorithm is altering the S-box according to the principles of the block cipher (OFB). The results were approved using hamming distance and avalanche effect. The proposed algorithm presents advantages on several points, including reducing the required time for the encryption and decryption processes and preventing transmission errors from perpetuating all data. Also, we can conclude that the modified Blowfish algorithm can be used for all text encryption systems because of its flexibility (unlimited input text size and expanding key size).
Virtual Reality Technology in Teaching Computer Hardware: A Prototype and Assessment from User Perspectives

Computer courses in public schools are typically taught by traditional methods, that involve images and written text explanations. This makes the content of learning materials unclear and hard to understand. Moreover, it is not easy for public schools to equip computer labs with the required devices, as schools have limited budgets. In this paper a protype using VR technology was introduced and assessed in terms of usability, and acceptance. The aim was to provide an interactive virtual learning environment for teaching/learning computer hardware with the most effective method that allow keeping pace with the rapid evolution in this field. The prototype was based on the use of a VR headset to allow the user to explore the internal components of a computer. A test in terms of functionalities and usability was conducted. Results confirmed that the prototype functions were successfully implemented. Subsequent tests on usability proved satisfactory. It is expected that the proposed prototype and study will enrich the teaching methods of public schools with limited budgets - especially for practical and applied courses.
Sign Language Detection Using Deep Learning

Abstract: People with hearing impairments are found worldwide; therefore, the development of effective local level sign language recognition (SLR) tools is essential. We conducted a comprehensive review of automated sign language recognition based on machine/deep learning methods and techniques published between 2014 and 2021 and concluded that the current methods require conceptual classification to interpret all available data correctly. Thus, we turned our attention to elements that are common to almost all sign language recognition methodologies. This paper discusses their relative strengths and weaknesses, and we propose a general framework for researchers. This study also indicates that input modalities bear great significance in this field; it appears that recognition based on a combination of data sources, including vision-based and sensorbased channels, is superior to a unimodal analysis. In addition, recent advances have allowed researchers to move from simple recognition of sign language characters and words towards the capacity to translate continuous sign language communication with minimal delay. Many of the presented models are relatively effective for a range of tasks, but none currently possess the necessary generalization potential for commercial deployment. However, the pace of research is encouraging, and further progress is expected if specific difficulties are resolved.
Phonetic Study: The Use of Diction in Short Story Essays of Class XI Students of SMA Negeri 10 Depok

The aim of the research was to find out the diction used by students in composing short stories. The research method used is descriptive qualitative method. The data source for this research was short stories written by students of class XI at SMA Negeri 10 Depok in the 2021/2022 academic year. The results of the study obtained 10 requirements for the accuracy of the use of diction using the percentage technique. Based on the research conducted by the researcher, 81 data were obtained from 42 students' short story essays. Of the 10 types of diction accuracy requirements analyzed, the results of inaccurate use of diction were as follows: use of general and special words 11.11%, use of connotative and denotative words 27.16%, use of almost synonymous words 35.81%, use of idioms 4.93%, continuity of word choice 11.11 %, and the use of the word senses 9.87%. From the results obtained, it can be concluded that class XI students used a lot of synonymous diction in the short story essays they made and only a few found inaccuracies, most of them were correct and appropriate for their use in short story essays.
Combined CNN with STARGAN for Wheat Yellow Rust Disease Classification

Experienced evaluators takes a lot of time for the correct prediction of wheat yellow rust.For better prediction of wheat yellow rust disease in wheat plant, computer assisted techniques such as machine learning (ML), deep learning (DL), image processing and computer vision techniques are employed.While considering these aspects, an automatic classification system for wheat yellow rust using a hybrid approach of a generative adversarial network (GAN) and convolutional neural network (CNN) is proposed.Also, the proposed model helps to identify wheat yellow rust disease at different severity levels (very low, low, medium, high, and very high).For achieving objectives about proposed model, State of Art GAN (STARGAN) helps in data augmentation of wheat plant disease images.Finally, a wheat rust model based on convolutional networks was trained on generated data.A case study has also been accomplished on the generated data by deploying a CNN model for classification.Then a comparative analysis of the proposed methodology has been consummated by differentiating the performance metric with the fully convolutional network, deep CNN (DCNN) and random forest models.A Deep CNN is a CNN model with a huge number of hidden layers.Comparing the proposed approach with other models, the proposed approach achieves a greater classification accuracy of 95.6% at a medium severity level.
Presentation Design System to Promote the Lecturer-Audience Interaction in Lessons

Slides are material that supports the information expressed by a speaker. Slides have increased their importance in education due to the multimedia information that we can represent in them and their easy access. Most conference or class presentations do not engage participants in an adequate way. Therefore, this research aims to develop a presentation and survey system in a real-time web application that allows interaction between the teacher-lecturer and the audience in an active way during the session. This research evaluated the system from three approaches: usability, acquired knowledge and user experience. The results suggested that SlideCheck could be an excellent option to encourage students to participate during classes, improve knowledge acquisition and improve interaction with the teacher during the session, making the lesson more dynamic.
The Use of Animated Videos In Teaching Vocabulary For Young Learners

- English has an important role in correspondence around the world so that it becomes a global language that is understood by all nations in the world. Therefore, it is important to teach English from an early age. One of the things that teachers need to pay attention to in teaching early childhood is learning media. Animated video itself is one of the learning media that can be applied as a learning medium for young learners. In this study, the researcher wanted to analyze the effect of learning media using animated videos in teaching English to young students, especially vocabulary mastery. From the calculation using SPSS 16.0, data were obtained based on descriptive statistics, namely, the average pretest was 53.750 and the posttest average was 73.375. This indicates an increase in the average value from pretest to posttest. In addition, the pretest score shows a minimum score of 45 students and a maximum score of 72.5 students. and experienced an increase in the posttest score, namely the student's minimum score of 65.0 and the maximum student's score of 87.5. The hypothesis testing using paired sample test showed that the significance value is lower than the level of significance (0.000 &lt; 0.05). Thus, it can be concluded that there is a significant difference in students' vocabulary mastery before and after being taught using animated videos
Study on Organisational ethos on leader’s behaviour, managerial effectiveness and work motivation

The business paradigms of today are undergoing shifts like never before. Businesses are going global and technology is improving at a very rapid pace. Innovation along with the development of Artificial Intelligence is growing in such leaps and bounds that even the experts can&#39;t keep pace with it and the core values of organisations are going down day by day. In this present study, an effort is made to investigate organisational culture in relation to leadership behaviour, managerial effectiveness and work motivation among the middle and lower managerial cadre of ECHS (Ex – Servicemen Contributory Health Scheme).
SOCIAL MEDIA AS A FLATFORM IN PUBLIC SPEAKING COURSES

Social media is one of the platforms for the public speaking lecture process for students during the pandemic. Various platforms are used to support lecture activities. The purpose of this study is to find out which social media is often used in the public speaking lecture process during the pandemic. The method used is a qualitative method which is intended to explain or describe the phenomenon of which platforms are widely used during the pandemic. Analyzing several journals related to social media which are more effectively used as a platform for the public speaking lecture process. So that, according to several sources, Instagram is a platform that is widely used in lectures in public speaking courses as a platform that supports public speaking activities.
Deep Learning based Text Abstraction

Abstract: Text abstraction plays a vital role in extracting crucial information from large textual datasets. With the advancements in deep learning, the application of transformer models has shown great potential in the field of text abstraction. This technical paper presents a comprehensive study on "Deep Learning-Based Text Abstraction" with a specific focus on utilizing transformer models for effective abstraction. The paper begins by providing an overview of text abstraction and its significance in handling extensive amounts of textual data while preserving essential information. It then delves into the fundamentals of transformer models, explaining their architecture and mechanisms, particularly attention mechanisms that enable capturing contextual relationships within text. The main contribution of this paper lies in the implementation of text abstraction using transformer models. It discusses the utilization of pre-trained transformer models and their adaptation for text abstraction tasks. The paper elaborates on techniques like fine-tuning and transfer learning to optimize the transformer models for text abstraction. Furthermore, the paper presents a detailed experimental setup, including the selection of datasets, evaluation metrics, and training procedures. It discusses the performance evaluation of the implemented transformer-based text abstraction system, comparing it against existing techniques and benchmark datasets. The results and analysis section showcases the effectiveness and efficiency of the proposed approach, highlighting improvements achieved in terms of extraction accuracy, summarization quality, and computational efficiency. Finally, the paper concludes by outlining potential areas for future research and development in deep learning-based text abstraction using transformer models. Overall, this technical paper provides a comprehensive study on deep learning-based text abstraction, with a focus on transformer models. It serves as a valuable resource for researchers and practitioners interested in leveraging transformers for efficient and accurate text abstraction, opening avenues for advancements in natural language processing and information extraction.