Reviewerly/exHarmony huggingface dataset:
DiDA: Iterative Boosting of Disentangled Synthesis and Domain Adaptation

Unsupervised domain adaptation aims at learning a shared model for two related domains by leveraging supervision from a source domain to an unsupervised target domain. A number of effective domain adaptation approaches rely on the ability to extract domain-invariant latent factors which are common to both domains. Extracting latent commonality is also useful for disentanglement analysis. It enables separation between the common and the domain-specific features of both domains, which can be recombined for synthesis. In this paper, we propose a strategy to boost the performance of domain adaptation and disentangled synthesis iteratively. The key idea is that by learning to separately extract both the common and the domain-specific features, one can synthesize more target domain data with supervision, thereby boosting the domain adaptation performance. Better common feature extraction, in turn, helps further improve the feature disentanglement and the following disentangled synthesis. We show that iterating between domain adaptation and disentangled synthesis can consistently improve each other on several unsupervised domain adaptation benchmark datasets and tasks, under various domain adaptation backbone models.
Research Progress of Monitoring System Based on Wearable Fall Detection Equipment for The Elderly

Falling will cause significant health risks to the elderly. Wearable fall detection system will effectively reduce the risk of fall-related complications, and improve the quality of life and well-being of the elderly. The behavior analysis of falls and the research progress of fall detection through the architecture of wearable fall detection equipment for the elderly are introduced. Furthermore, the procedures of the fall detection system for the elderly such as sensor data acquisition and preprocess, feature extraction and analysis, classification algorithm, performance evaluation and the classification technology are also introduced. In addition, the current research work from several aspects, such as classification technology, comparison and statistical analyzation, and summary and prospect are introduced for some meaningful references.
A Fall Detection using Sound Technology Based on TinyML

With the increasing ageing of our society, the need of fall detection for the elderly is becoming more and more important. In this paper, a convolutional neural network model is established and trained to study the fall detection using sound technology, so that the model can realize the autonomous recognition ability of the elderly fall sound from the other noises. This network model will be finally deployed and realized on a small wearable device using TinyML technology. A certain amount of falling sound data and noise data is collected by ourselves, and used as a training data set for neural network. The audio data is converted into a Mel spectrogram firstly, and data features are extracted, and then inputted into the convolutional neural network. This network is trained with TensorFlow offline before deployment. Finally, under an experiment environment, the accuracy of the model's recognition of falling sounds reached more than 95%. Combining the sound technology with acceleration and gyroscope sensors will be a good way to detect the fall of elderly.
Pengembangan Media Pembelajaran Matematika menggunakan Google Site dengan Pendekatan Metakognisi untuk Kelas XI

Online learning now days, learners experience a decrease in the understanding of learning materials. This happens, because the learning media used by teachers still uses conventional learning media such as Ms.word / PDF. Moreover, learners are required to learn independently. Therefore, a learning media is needed to help students overcome the problem. This research is a website-based learning media development research that aims to help students in the online learning process, as well as knowing the feasibility of learning media using google with a metacognition approach to problem solving. The data collection instruments used are observations and questionnaires. The development of this learning media, is done by the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) method. Technical data analysis is carried out qualitatively to measure data descriptively and quantitatively to calculate the score of the feasibility trial results of learning media that researchers have developed. The results of this learning media development research based on the feasibility of learning media earned a percentage on an 83% basis with excellent categories. For trials the metacognition capability of problem solving obtained a percentage of 76% with good categories. Thus, the learning media of mathematical learning media using google that researchers developed is very feasible to use.
Design Of Wedding Jewelry Stacking Mechanism With Vina Musical Instrument Theme On Kendalisodo Temple Relief

Kendalisada temple dates from the middle of the 15th century which is the last stage of the Majapahit period. The author would like to re-introduce the existence of Kendalisada Temple to modern society today by designing a wedding jewelry set product inspired by the reliefs of Kendalisada Temple which tells the story of Prince Panji and Dewi Sekartaji who are sitting intimately, then the prince plays the Vina musical instrument to entertain his lover, where for the surroundings there are natural landscapes such as mountains and water. In the design process, the author used a qualitative method in the form of a literature study which includes searching for data through books, electronic sources, and related journals about Kendalisada Temple, Kendalisada Temple reliefs, Vina musical instruments, types of jewelry, jewelry materials, wedding jewelry, jewelry making techniques, markets. research, and trend forecasting. The author also used the cultural design method to transfer the culture in the relief into a product. The design process used 4 stages, namely investigation, interaction, script development, and product design. After that, the author made some ornaments and then developed more. The author uses the stacking method in jewelry making where the use of jewelry in the form of sets is stacked with a total of 2-3 pcs for each type of jewelry.
STRATEGIES IN OVERCOMING SPEAKING ANXIETY IN A VIRTUAL CLASSROOM PRESENTATION: A DESCRIPTIVE QUALITATIVE STUDY AT ONE VOCATIONAL SCHOOL

&#x0D; &#x0D; &#x0D; The purpose of this research is to investigate the factors that caused speaking anxiety in a virtual classroom presentation and the strategies to overcome it. The research setting is in one vocational high school in Cimahi, West Java, Indonesia in which ten second grade students majoring in fashion design class (Tata Busana) were selected to be participants of the study. The study employed descriptive qualitative design where the data obtained in a mixed way through observation, modified FLCAS questionnaire and interview. Due to the pandemic situation, classroom observations were carried out in the virtual classroom. Then the data were analyzed in accordance with the theme called coding and categorizing. The findings showed that the factors caused students’ speaking anxiety in delivering virtual classroom presentation are: personal and interpersonal anxiety, learner beliefs about language learning, lack of preparation and fear of making mistakes. The researchers also found some students’ strategies to overcome their speaking anxiety which are greatly helped them lessen their speaking anxiety. Those are: relaxation and resignation, preparation, peer seeking, and positive thinking. The findings of this research provide suggestions for teachers to improve their creativity in teaching process to create a friendly classroom environment to overcome students’ anxiety in classroom presentation.&#x0D; &#x0D; &#x0D;
Model ARIMA Terbaik Prediksi Latitude dan Longitude Kegiatan Kapal Imigran Ilegal

The migration of a person to another country without following the law is illegal immigration. Many problems are caused by this activity, ranging from population problems to increased crime. Predicting the emergence of ships carrying illegal immigrants can assist border patrols in planning patrols to planning defense equipment. Time series forecasting to predict the latitude and longitude of boats carrying illegal immigrants is the Autoregressive Integrated Moving Average (ARIMA) model. The case studies for this research are the Straits of Malacca and the Riau Islands. The prediction range is from one to four weeks to find the model with the smallest error. The ARIMA model for one-week prediction distance succeeded in obtaining the smallest RMSE. However, the smallest RMSE result (0.28730) was obtained for a four-week prediction distance with ARIMA model parameters (4,0,2) for longitude prediction. Meanwhile, the prediction of latitude. The best model is ARIMA (4,0,1), with an RMSE of 0.11457. For latitude and longitude predictions in the Riau Islands, the best models are ARIMA (3,0,0) with RMSE of 0.009074 and ARIMA (2,0,0) with RMSE 0.045815. Based on this study, the ARIMA model is suitable for predicting latitude and longitude data with a short prediction distance (one week)
Relatório de Pesquisa NESCoM 2021

The NESCoM is a multidisciplinary research centre formed by musicians, engineers and computer scientists. This paper reports the ongoing projects and developments over the last two years, thus it is an update over the research report published in 2019. As a Brazilian research group, with solid international collaboration, we have opted to intercalate the language used to write the report, therefore the 2021 version is written in Portuguese. The main projects developed in these two years timeframe are related to interaction design based on (bio)musicality, robotic music performance, and ubiquitous music. In addition, a strong artistic production is also described. If you are interested to get to know more about the projects, do not hesitate to contact us.
Playing Time-Variant Audio Feedback Networks

This article presents practical and artistic contributions to the field of computational musical systems based on audio feedback networks which have been used as instruments for music creation in the author's artistic practice. The article begins with an introduction to the research field of feedback and selforganized music systems. Later on two systems are presented: the first is a network of cross-modulated sinusoidal oscillators (by frequency modulation), and the second is a network of transforming processes of pre-recorded sound samples.
Construction of Fuzzy Comprehensive Evaluation Model of Students' General Education Ability by Fuzzy Comprehensive Evaluation Analysis Method

With the development of the times, society has put forward more requirements for nursing talents, not only to possess professional knowledge and skills, but also to be able to integrate different knowledge and use them to solve practical problems. Therefore, it is necessary for colleges and universities to strengthen general education in nursing, combine advanced technology to improve the quality of general education, and accelerate the realization of general education goals. Based on the fuzzy comprehensive evaluation and analysis, this paper constructs a fuzzy comprehensive evaluation model of general education ability of nursing students, and on this basis, discusses the implementation strategies of general nursing education, aiming to provide some useful references and speed up nursing general education Educational development will cultivate more professional nursing talents.
AN AUTOMATED PARALLEL COMPATIBILITY TESTING FRAMEWORK FOR WEB-BASED SYSTEMS

With the growth and wide use of web-based applications in many domains, it is crucial to check their conformance with regards to their requirements.Among the important set of testing types, compatibility testing is of high importance.Indeed, ubiquity is required and the way of interacting with these applications can be performed in many manners.Compatibility testing aims at determining if the web application is proficient enough to run in different browsers, database, hardware, operating system, mobile devices, networks, etc.In this context, one challenge for compatibility testing is how to execute multiple tests cases, in a correct and efficient way, that may cover several environments and functionalities of the tested applications, while reducing the consumed resources and time.In our work, we propose a methodology to efficiently perform compatibility tests through several environments with different versions of operating systems (OS) and browsers.We emphasize on resource consumption improvement by using parallel testing and containerization.
Combining semantic and linguistic representations for media recommendation

Content-based recommendation systems offer the possibility of promoting media (e.g., posts, videos, podcasts) to users based solely on a representation of the content (i.e., without using any user-related data such as views or interactions between users and items). In this work, we study the potential of using different textual representations (based on the content of the media) and semantic representations (created from a knowledge graph of media metadata). We also show that using off-the-shelf automatic annotation tools from the Information Extraction literature, we can improve recommendation performance, without any extra cost of training, data collection or annotation. We first evaluate multiple textual content representations on two tasks of recommendation: user-specific, which is performed by suggesting new items to the user given a history of interactions, and item-based, which is based solely on content relatedness, and is rarely investigated in the literature of recommender systems. We compare how using automatically extracted content (via ASR) compares to using human-written summaries. We then derive a semantic content representation by combining manually created metadata and automatically extracted annotations and we show that Knowledge Graphs, through their embeddings, constitute a great modality to seamlessly integrate extracted knowledge to legacy metadata and can be used to provide good content recommendations. We finally study how combining both semantic and textual representations can lead to superior performance on both recommendation tasks. Our code is available at https://github.com/D2KLab/ka-recsys to support experiment reproducibility.
Linguistics Landscapes: New Normal Life Representation in Kuta, Bali

The covid-19 pandemic has influenced all human life worldwide. This pandemic affects all life in the world, including in Indonesia. Covid-19 had destroyed all aspects of life in Indonesia. One of the most devastating sectors affected is the tourism industry. In order to boost economic sustainability, the Indonesian government, through the Health Ministry, had issued a circular letter no. HK.02.01/MENKES/335/2020 about Protokol Pencegahan Penularan Corona Virus Disease (Covid-19) di Tempat Kerja Sektor Jasa dan Perdagangan (Area Publik) dalam Mendukung Keberlangsungan Usaha [Protocol for Prevention of Corona Virus Disease (Covid-19) Transmission in the Workplace of the Service and Trade Sector (Public Area) in Supporting Business Continuity]. This study is aimed to investigate the implementation of the Covid-19 protocol as an adaptation of New Normal life in Kuta village, Bali, Indonesia. It is chosen as the research area since Kuta is one of the international tourist destinations in Bali that mostly rely on the tourism industry. The data of this study is taken from any outdoor sign representing New Normal protocol in the area. The documentation method and note-taking technique were applied in collecting the data. The analysis is based on linguistics landscapes theory. The result showed that there are 199 outdoors signs found in 10 groups of most tourism facilities. The language of the sign is dominated by the Indonesian language with 84 signs, followed by the combination of English and Indonesian language with 55 signs.
Pedagogical content knowledge of English teacher on reading comprehension during pandemic covid-19 with online classes in senior high school

The research of Pedagogical Content Knowledge (PCK) uses a qualitative approach. The purpose of this research is to obtain the Pedagogical Content Knowledge (PCK) of prospective teachers of English Courses in terms of academic ability during the Covid-19 pandemic, as it is known that the pandemic has changed the structure of life that has been neatly arranged in this world. Data were analysed in the form of documents, observed, and interviewed with prospective English teachers on SMAN 15 SURABAYA. The technique of taking the data in this study was purposive sampling. The subjects in this study are teachers with more learning hours because in general they are categorized as professional teachers, then teachers with many teaching hours will be examined how the PCK is. The instruments in this study used CoRe and Vignette. The data analysis technique uses the Miles and Huberman model, namely data reduction, data presentation, and conclusions. Based on the results of the study, it shows that the pedagogical content knowledge of English teachers on reading comprehension during the pandemic still needs more creative and innovative adjustments, this is indicated by the number of teachers who are still hampered during learning hours.
Chinese Writing System

With an aim to assist the Chinese learners to have comprehensive understanding and overall knowledge about Chinese character and writing, this paper mainly discusses the origin and development of Chinese character and writing, analyzes the structure of Chinese character, the phonology of Chinese (Pronunciation) and the reform of Chinese.
Analysis of Online News Popularity Data in Machine Learning Repository using R Studio

Media are tools to get information across the globe. And online news is described as an article that is made for spreading awareness on all kinds of topics or issues published on the internet. In this research, the researcher wanted to analyze the online news popularity data in a machine learning repository using the R Studio in terms of the relationship of variables to identify the popularity of online news articles. Specifically, the researcher desired to identify the results in Principal Component Analysis using the Online News Popularity data in Machine Learning Repository; show the results in the Path Analysis using the online news popularity mined data; reveal the relationship of the variables (publication article, words, and links) towards the popularity of online news; display the structural equation model derived from the mined data; and determine the relationship between confirmatory factor analysis and the structural equation model. The data consisted of a heterogeneous set of features which was extracted into 61 characteristics (58 predictive features, two non-predictive, and one goal field) and from the overall of 39,644 respondents. The mined data set came from UCI Machine Learning Repository in the CSV file. This study employed a quantitative method. RStudio is software used which was a computational research tool for creating dynamic and reproducible research. R software is installed in the computer and used to treat and analyze the data in all statistical requirements of the study.
4G L.I.V.E. Learning through Instructional Videos and E-Learning Resources: An Intervention on the Grammatical Competence of Grade 4 ESL Learners

The study determined the effects of Learning through Instructional Videos and E-learning resources (4G L.I.V.E) as an intervention in developing grammatical competence of Grade 4 ESL Learners in MDL classes for S.Y. 2020-2021. This was initiated as a response to the occurrence of challenges in implementing MDL as mandated in BE-LCP. The material is a child-centered, self-paced, MELC-based learning package which includes, instructional video presentations, and other e-materials covering English 4 grammar lessons. This study used purposive sampling with quasi-experimental design and involved 55 Grade 4 learners. Findings revealed that the grammatical competence of the learners increases on average level by the mean percentage score (MPS). The differences observed in the MPS were further subjected to T-test. The paired t-test revealed that there is significant difference between the pre-test and posttest in terms of the grammatical competence of the respondents. This means that they have improved after the intervention program. The results of this study serve as a basis for the English teachers to craft appropriate instructional materials to be given to the learners, as well as a guide for planning of trainings for the development of instructional materials.
PEMBUATAN GAME AUGMENTED REALITY FIRST PERSON SHOOTER "APOCALYPTIC REALITY" DENGAN VUFORIA

"Apocalyptic Reality" is a first-person shooter game that can be played on Android device. Augmented reality features make a three-dimensional display. This game is made using the Unity3D game engine and the Vuforia software development kit to detect the position and rotation of the device in the real world. There are nine stages available in this game. player must collect money to buy items in the Shop and fight zombies that arrives. The game was tested using black box testing, alpha testing, and beta testing with questionnaire to 30 respondents. The test results show that this game has provide a unique way to play First Person Shooter and this game can be played using minimal Android Version 5 or above.
Study on obesity and overweight among children in the primary cycle at national plan

Prevention of childhood obesity is a public health issue and requires close monitoring of those with a tendency to gain weight.Most researchers believe that obesity that has appeared since childhood and is maintained until adolescence is much more difficult to treat.Obesity among children inevitably decreases life expectancy.The problem of overweight and excessive growth of obesity since childhood it can be prevented or slowed down by implementing diversified programs if society focuses more on the causes.There are many causes, some more crucial than others, but through a balanced diet, combined with systematic physical activity, it can prevent obesity and overweight in all children around the world.[7] Next, I will present the studies done at the national level regarding the presence of obesity and overweight in children aged 6-19 years.