Reviewerly/exHarmony huggingface dataset:
THE INFLUENCE OF CLUSTERING TECHNIQUE ON STUDENTS’ DESCRIPTIVE TEXT WRITING ABILITY AT SEVENTH GRADE OF MTS MUHAMMADIYAH PADANGPANJANG

The purpose of this research is to investigate whether any significant influence of using clustering technique on students’ descriptive text writing ability at seventh grade of MTs Muhammadiyah Padangpanjang. The population of this research at the seventh grade of MTs Muhammadiyah Padangpanjang. The sample of this research was class seven which consisted of 34 students. The design of this research was pre-experimental research in one group design which divided into two stages consisting of pre-test and post-test in the learning process. Then, the instrument of this research was a writing test, to score the students’ descriptive text writing ability on pre-test and post-test the researcher used rubric assessment from Brown (2003). Furthermore, the success criteria were determined on the five indicators of writing namely content, organization, vocabulary, language use/grammar, and mechanics. The researcher analyzed the data by using statistical formulation and Microsoft Excel 2010 with 0,05 significance level. After analyzed the data, the result of the average post-test score is 80, increased from pre-test score is 60. Next, the value of tcount was higher than ttable. It can be seen from tcount is 12,98 &gt; ttable is 2,035 at the significance level 0,05 and degree of freedom (df) = 33. It means that, the alternative hypothesis (Ha) is accepted and the null hypothesis (H0) is rejected. It can be concluded that, the use of clustering technique is giving significant influence to students’ descriptive text writing ability at seventh grade of MTs Muhammadiyah Padangpanjang.&#x0D; Key Words: Clustering Technique, Writing, and Descriptive Text.
UPAYA MENINGKATKAN PENGEMBANGAN BAHASA ANAK MELALUI LAYAR PROYEKTOR

This study aims to improve language development through the media of group B projector screens at Kusuma Mekar I Kindergarten. Language development in this study is the child's ability to understand language, express language, and literacy. This research is a class action research (classroom action research). The subjects of this study were 19 students in group B, consisting of 8 boys and 11 girls. Data collection techniques are carried out by means of observation and documentation. The research instrument is an observation guide. The data analysis used in this study is descriptive qualitative and quantitative descriptive with percentages. The results showed that language development in group B children at Kusuma Mekar I Kindergarten could be improved through the media of a projector screen. This is evidenced by the results achieved in cycle 1, language skills with an average BB reaching 2 children (10%), MB reaching an average of 11 children (58%), BSH reaching an average of 3 children (17%) ), and language skills with average BSB achievements reached 3 children (17%). In cycle 2, language skills with BB achieved an average of 0 children (0%), MB averaged 0 children (0%), BSH averaged 3 children (16%), and language skills with achievements BSB averaged 16 children (84%). Effective steps in this study in an effort to improve language development through a projector screen for group B children of Kusuma Mekar I Kindergarten, namely 1) The teacher changes the implementation technique classically divided into three playing groups, 2) To spur enthusiasm and self-confidence of children in express opinions, the researchers provide rewards in the form of gifts for children who are able to play educational games well, 3) educational game games are made with variations, so it is hoped that children will be more interested.
Media Pembelajaran Berbasis Augmented Reality pada Mata Kuliah Mesin – Mesin Listrik

This study aims to produce effective Augmented Reality-based learning media in the electrical machinery course in the Department of Electrical Engineering, Padang State University. The research method used is the method of research using the pre-Experimental research method with a One-Shot Case Study design. This type of One-Shot Case Study aims to see the power of measurement and the scientific value of a research design. In this method the application is made using supporting software, namely the Unity 2018 software, Android studio and Vuforia. Furthermore, the authors see whether the application that the author makes is feasible and effective to use as a learning medium through a questionnaire that will be provided and tested for validity. In its application, this learning media is applied to twenty-two students who are taking the Electrical Machines course at the Department of Electrical Engineering, Padang State University in 2022. Testing the feasibility of research materials obtained a figure of ninety-five percent for the feasibility test of the content of the material and ninety-five percent three percent for the media feasibility test where the figure shows that the learning media made are said to be very feasible to be used as research material. The implementation of the research shows that the use of Augmented Reality-based learning media in the Electrical Machines course can improve the quality of the learning process and student learning motivation. Based on data analysis, the average value of the effectiveness of learning media is seventy-point fifty six percent where this value can be categorized as effective as an alternative interactive learning media.
Implementasi Green Economy pada Sistem Instalasi Pengolahan Air Limbah Tahu dan Sensor Terintegrasi di Kediri

Every industry has special attention to environmental preservation; however, it has become an unresolved problem in the industrial center of tofu village. Based on the analysis, there were problems related to liquid waste produced by tofu craftsmen that doesn’t meet the Quality Standards for liquid waste of the Food Products Industry, limited costs, land, and space thus that it didn’t meet the adequacy of space for Wastewater Treatment Plants (WWTP). The PKM (Community Service Program) activity aimed to implement Green Economy Concept on Integrated WWTP Systems and Sensors for the Kediri Tofu Industry as an effort to solve the waste problem in the tofu industry. This activity began with field observations, compatibility and requirements analysis, construction design and designing WWTP systems and sensors, small-scale trials, analysis, and evaluation. The WWTP system used involves components of pre-treatment, neutralization, coagulation and flotation, sedimentation, and filtration. The designed sensors included Arduino Nano-based pH meter and TDS meter sensors that were connected to computers and smartphones by Arduino IDE and Blynk software. It was hoped that this activity might spur business actors to actively participate in solving waste problems and reducing environmental impact pollution with all the space and cost limitations.
Eye-BEHAVIOR: An Eye-Tracking Dataset for Everyday Household Activities in Virtual, Interactive, and Ecological Environments

We present a large-scale dataset of human body and eye movements in 3D, interactive, and ecological household VR environments. Our simulation platform BEHAVIOR includes 100 essential daily activities according to the American Time Use Survey, such as cleaning and cooking. The simulator (iGibson 2.0) provides photo-realistic, fully interactive 3D scenes reconstructed from real homes, and supports physically realistic articulated objects. The dataset contains 500 trials (5 trials per activity), collected from 8 subjects, in 15 virtual scenes with 244 different types of objects. The total length is 18 hours, with each trial ranging from 6 seconds to 11 minutes. We provide rich annotations for visual stimuli, including depth, surface normal, optical flow, object segmentation, and object poses. Additionally, we extract abstract state information, such as object relations, represented in a symbolic logic language (e.g., sliced(objectA), onTop(objectB, objectC)). The goal of each activity is encoded in this logic representation, which facilitates understanding the low-level behaviors as evidence of high-level reasoning towards the completion of a task. Our initial results show that this dataset introduces several challenges to modeling attentional control: 1) Distribution of gaze indicates strong top-down task modulation of attention, as 34% of gaze are on goal objects. 2) 3D scenes with diverse and visually rich objects challenge the most advanced saliency models. 3) The long-horizon activities involve navigation and object manipulation, capturing diverse cognitive abilities such as physical scene understanding, visual search, and eye-hand coordination. We propose to tackle these challenges by reconciling bottom-up sensory inputs and top-down task signals, and leveraging state-of-the-art machine learning models. Together with the dataset, we open-source our simulation environment and tools. Researchers can modify or create their own activities by adding new objects and designing new household environments. We hope this will make BEHAVIOR an appealing VR experimental platform.
Analysis Students Addition Error in Writing Thesis Abstract Of English Education Department STKIP AL Maksum Langkat

The focus of this research was to describe the addition errors detected in the writing of the thesis abstract, to figure out why they happened, and to figure out how they happened at the Department of English Education for Students at STKIP Al Maksum Langkat. This research revolves around the abstract of an undergraduate thesis from the English department. In this study, the descriptive qualitative method was applied. This study's data comes from ten abstract manuscripts of undergraduate thesis dissertations published in 2022. The steps in error analysis are collection, identification, description, explanation, and error evaluation. As illustrated by these statistics, the errors made by undergraduate students are additional words that can occur as a result of interlanguage interference, intralingual interference, insufficient command of English syntax and vocabulary.
TREINAMENTO COGNITIVO CONTINUADO EM PACIENTES COM ESCLEROSE MÚLTIPLA ANALISADO POR RESSONÂNCIA MAGNÉTICA: UMA REVISÃO DE LITERATURA

The current Covid-19 pandemic was characterized by a massive global outbreak in the first three months of 2020.The countries' lack of preparation for this type of virus and the characteristic exponential spread of daily Covid-19 cases 19, generated an unprecedented health crisis in the last century, a crisis that is still present.Goal.Make a chronological analysis of the different waves of COVID -19, to continue in search of complete knowledge of SARS-CoV-2 and its variants, lineages and sublineages, to obtain a comprehensive treatment.Methodology: This research is analytical, descriptive, cross-sectional, it is carried out under the review of scientific articles from different journals.The main sources of information used in the study are: the Johns Hopkins University website and the official page of the WHO, PAHO, GISAID and Bibliography of indexed medical journals Results: The teaching of the evolutionary knowledge of this pandemic has shown us that governmental and medical prevention measures have been insufficient to eradicate this pandemic, however we have learned the physiological, genetic and genomic bases of the components of the virus and its variants, which have made it possible to reduce its incidence and mortality, but there is still much to study and discover for its comprehensive treatment.Conclusions: We have learned to survive and live with this virus that until now seems to be here to stay if it does not work collectively, harmoniously among world organizations (WHO, PAHO, GISAID, OECD, ECLAC), Secretaries of Health, among others, governments and citizens of each country with a single purpose and without vested ideological interests, otherwise we are exposed to a global recession of social, economic and educational health that conditions a global setback.
An analysis on the structural relationships among young children’s social competence, self-regulation and play immersion in using artificial intelligence

Objectives The purpose of this study is to explore the relationship among young children’s social competence, self-regulation and play immersion in using artificial intelligence(AI). Methods The research subjects are 238 young children who are 3, 4, and 5 years olds and attending preschools located in G city. Data about the characteristics of young children were collected through related questionnaires by their preschool teachers. The data were analyzed through descriptive analysis, correlation analysis, regression analysis, factor analysis, and structural equation model analysis. Results The research results were as follows; first, there were significant correlations among young children’s social competence, self-regulation, and play immersion in using AI. Second, young children’s social competence directly affected on play immersion in using AI and indirectly gave an influence on play immersion in using AI by a mediation of self-regulation. In accordance, there was a significant partial mediating effects of young children’s self-regulation on the relationship between their social competence and play immersion in using AI. Conclusions In conclusion, these findings suggest that, for supporting child-centered and play-directed AI education with young children, teachers and parents should acknowledge the importance of educational supports to promote young children’s meaningful play immersion in using AI.
PENERAPAN PRINSIP ERGONOMIS DALAM PROSES MENYIAPKAN TEMPAT TIDUR TAMU OLEH PARAMUGRAHA DI HOTEL CATUR ADI PUTRA DENPASAR BAL

This study aims to understand the importance of applying ergonomics principles when carrying out an activity or work in the Housekeeping Department, especially when preparing guest beds by the Room boys/Room attendants. It uses a qualitative method, in which primary data will be collected through observation, documentation, and face-to-face interviews with the four informants present. Selected using purposive sampling so that they are able to understand and be aware of the case being studied and secondary data collected through documents related to the operations of the Housekeeping Department at Hotel Catur Adi Putra Denpasar. This research was initiated by identifying the problem at the object of the research, where it was seen that the Room boys/Room attendants were still bent over while making the guest bed preparation process, whether it was lifting the mattress, tidying the mattress and its mobility. Next is the making of research methods that will be used by researchers. The data sources used are primary and secondary data, while the type of data to be used is qualitative. After this research is completed, the final stage is to make a presentation of the results of the analysis, then the results will be presented in formal and informal forms.
Aplikasi Komunikasi Data Menggunakan Instant Messengger Dan SMS Gateway di PT. Sarandi Karya Nugraha Sukabumi

Existence of information which quickly and accurate is true very expected by each and everyone which is communicating, not the problem of if us each other dealing with what becoming the source of information. Other but again its problem if the communications blocked with difference of distance or place which not enable us to be able to give or accept information directly and will be more be complicated if beside difference of place, also that information should be able to be kept as reference or requirement of this othera. The trouble happened PT. Sarandi Karya Nugraha where each every division or department even with departmental office of branch in this case department Marketing departement need the existence of communications to confirm or advise about existing problems each every its department or ask departmental information of other.Then is intention of this writing is to give application and knowledge about a communications system, conducive of inter department relation or division can intertwin better.&#x0D; As for this writing method for example using field study, where information and also data obtained from result of interview with side of menejer departmental head and or existing division and also passstudy of kepustakaan. Trouble this require to get attention, in order not to happened wrong effect misunderstanding or is late of accepted information him.&#x0D; Thereby pursuant to analysis which have been done in PT. Sarandi Karya Nugraha this, its&#x0D; its is existence of internal issue of communication and with existence of network facility which have been woke up will be more add its benefit made of communications system as communications medium.&#x0D; Information quickly will add work productivity and also minimized the happening of misunderstanding, that thing can reach with existence of communications system. This system can be done by exploiting network system, developing application software for the communications of, saving order into database and also evaluate data order if needed.&#x0D; &#x0D; Keywords : Information, knowledge, application, communication, networking
The Using of Media Games to Improve SMCP (Standard Marine Communication Phrases) Vocabulary in Maritime English

Purpose: Shipping is the world's largest trade and also one of the most dangerous. Safety of life at sea, the environment at sea, and 80% of world trade depend on professional and competent seafarers. Ziarati (2006) identified that poor communication as one of the most significant factors in accidents at sea and ports. SMCP is a collection of words or phrases in English which is supported by the international community means of communication at sea then developed and adapted to IMO (International Maritime Organization) standards. SMCP aims to explain external communication phrases such as communication between ships, between ships and land parties such as ports. The main goal is to reduce language problems in communicating at sea and also to avoid misunderstandings that can lead to accidents. So, it is possible to learn vocabulary in SMCP to achieve maximum results if it is done in a pleasant atmosphere.&#x0D; Design/methodology/approach: This study uses a quantitative approach using a quasi-experimental method.&#x0D; Findings: In this study, the result in question was the use of games to support the learning of maritime English SMCP vocabulary.&#x0D; Research limitations/implications: The population in this study was the cadets of the diploma program majoring in Nautica in the second semester of The Surabaya Shipping Polytechnic (2015-2016) academic year, amounting to 110 people. The sample of this study was 20 cadets in class C.&#x0D; Paper type: A case study
A model of the stable functioning of the data collection, processing and protection system

Abstract The system of data collection, processing and protection is considered. In such system data is transmitted via data channels from the data collection and processing blocks to the data protection block. The received data arrays are stored in the data protection block. The functioning termination one of the data collection blocks may lead to the loss of the received data. The problem of ensuring the stable functioning of the system for collecting, processing and protecting data is formalized and studied in this paper. It is also considered the case when the system has a data backup block. An illustrative numerical example is solved.
Pairwise learning for personalized ranking with noisy comparisons

Learning-to-rank from pairwise comparisons has a wide spectrum of applications in diverse domains. For personalized recommendation applications, the widely used implicit feedback is kind of incomplete data where only the interaction can be observed while the preference intensity for the interaction cannot be observed. Existing solutions degrade pairwise learning from implicit feedback by setting the preference intensity of each interaction as 1 to learn representations as model parameters. Noisy comparisons consisting of untrustful interactions (e.g. mistaken clicks) may lead to inaccurate optimization of a pairwise learning model. In this paper, we propose a new pairwise learning algorithm to learn personalized ranking from incomplete data where noisy comparisons are widely existed, called BPRAC. As prior knowledge about trustful interactions are not available, we introduce new indicators for measuring interaction trustfulness, which are to be learned together with users’ and items’ representations as model parameters in our BPRAC algorithm. We first derive the distribution of estimated item scores for trustful interactions from pairwise comparisons. The proposed BPRAC algorithm adopts the expectation-and-maximization framework: We estimate indicators using Bayesian inference in the expectation step; while learning representations for personalized ranking in the maximization step. We also analyze the convergence of our learning algorithm. Experiments on real-world datasets validate the effectiveness of our estimation of trustful interactions and the superiority of our personalized ranking over peer algorithms.
Applying neural networks-based modelling to the prediction of mineralization: A case-study using the Western Australian Geochemistry (WACHEM) database

Geochemical data collected and stored by government and private sectors are becoming increasingly complex and too large for manual interpretation. The use of automatic methods for identification of potentially spurious data and estimation of missing values in very sparse geochemical datasets can significantly improve our understanding of geological systems. Deep neural networks have recently achieved remarkable success in a wide range of applied problems. These methods do not require manual feature engineering and significantly outperform traditional machine learning algorithms when applied to large datasets. We present a deep learning based method for estimation of unknown sample analytes in geochemical data. This approach is entirely data-driven and, once the network is trained, delivers the results in real time by predicting the distribution of an unknown analyte in a single step. A case study on the Western Australian Geochemistry (WACHEM) database demonstrates the efficiency of the method. Base metals as well as many other metals show good predictive capability (average symmetric mean absolute percentage errors range from 20% to 26.1%). Silver, platinum and especially gold are found to be more difficult to predict. The estimation of rock types from geochemical data allows for validation of existing datasets and prediction of rock types directly from geochemical data when there is no other existing information. The results of this study can benefit mineral explorers by indicating exploration targets and highlighting gaps in existing data.
Boosting Self-supervised Video-based Human Action Recognition Through Knowledge Distillation

Deep learning architectures lead the state-of-the-art in several computer vision, natural language processing, and reinforcement learning tasks due to their ability to extract multi-level representations without human engineering. The model’s performance is affected by the amount of labeled data used in training. Hence, novel approaches like self-supervised learning (SSL) extract the supervisory signal using unlabeled data. Although SSL reduces the dependency on human annotations, there are still two main drawbacks. First, high-computational resources are required to train a large-scale model from scratch. Second, knowledge from an SSL model is commonly finetuning to a target model, which forces them to share the same parameters and architecture and make it task-dependent. This paper explores how SSL benefits from knowledge distillation in constructing an efficient and non-task-dependent training framework. The experimental design compared the training process of an SSL algorithm trained from scratch and boosted by knowledge distillation in a teacher-student paradigm using the video-based human action recognition dataset UCF101. Results show that knowledge distillation accelerates the convergence of a network and removes the reliance on model architectures.