Reviewerly/exHarmony huggingface dataset:
Medical Information Retrieval with Weighting Critical Score for Acute Respiratory Infection (ARI) Desease Detection

Medical Information Retrieval (Med-IR )is part of computer science that discusses the search for a medical document. Medical Information Retrieval is needed by patients to know the initial prediction of the symptoms they are experiencing. ARI (Acute Respiratory Infection) is a disease that almost everyone has experienced which can cause death. This study uses a dataset of ARI sufferers and user queries that contain symptoms in text form. Furthermore, the query data is processed with the Med-IR application using Bi-Gram, TF-IDF as the feature extraction and Cosine Similarity as the similarity method, so that a return document is produced which is expected to be used as an early prediction of ARI in patients. The research also uses a critical disease wighting process, so that the results of the Med-IR are complemented by predictions of the severity level of the disease. From the results of research conducted at the Assyafi'u Sentosa Lengkong Clinic, Nganjuk, the best results were obtained for precision values ​​of 85.5% and 52.9% for recall values ​. The evaluation of disease severity with Mean Absolute Percentage Error (MAPE) getting a low score of 2,529%. Keyword : Medical Information Retrieval, ARI, Weighting critical disease, Bi-Gram, TF-IDF, Cosine Similarity.
The effectiveness of the scientist: How to turn science into a report and a competition for resources

The article shows various aspects of the application in the practice of labor relations of a teacher (scientist) and an educational (scientific) institution of such a tool for regulating activities as an effective contract. It is shown that an effective contract is a way to reduce the income of a teacher (scientist) by increasing the amount of time needed to fulfill all the conditions of the contract. It is also shown that an effective contract is a way to reduce the quality of the educational and research process, which ceases to be evaluated by the quality of its results and in the course of the work of the expert community, and acquires the character of a pursuit of achieving quantitative indicators recorded by formal information systems, such as various databases indexing publishing activity.
Perancangan Game Kasual Pongo Tap Pixel Art 2D

Interactive multimedia applications play a very important role as a medium for information, socialization and education. Video games as part of interactive digital applications have the opportunity to be an effective entertainment and learning medium, if designed appropriately. The casual game PongoTap can be used as a socialization medium to increase public awareness of the importance of preserving orangutan habitat. Information about orangutans in 2017, orangutans are included in the Red List of critically endangered (CR) animals whose population is estimated to continue to decline. Based on these reasons, the game concept tells the story of a young orangutan who has lost his habitat, and must go on an adventure to try to survive by finding a comfortable place for him. Pongo is the main character in this casual game. The methodology in game design uses research and development (Research &amp; &amp; Development). Data collection was carried out by searching for library data (supporting theories) and factual data (creation sources) and then data processing was used as a reference in preparing the game design concept. The visual appearance of Pongo Tap 2D is in pixel art style. The game is designed in 4 stages, each stage is identical with a different level regarding; gameplay, characters, and environment. The final result of the creation stage is an interactive application in the form of a video game for Android-based smartphone devices. Conclusion of design analysis; side scrolling platformer gameplay, orangutan characters, and endemic animal habitat environments.
School biology education in the context of Orthodox creed.

The article is devoted to the teaching of biology in high school under conditions of confrontation between materialism and creationism on the problem of life origin on Earth. Possibilities for solving this problem are considered that do not contradict either the Orthodox doctrine or the established standards of normative and variable content of biological education. The difficulties that an Orthodox teacher will encounter in the process of teaching the basics of creationism in a general education institution are analyzed. Original data on the design of alternative approaches to introducing students to the basics of creationism are provided.
A Combination of Light Pre-trained Convolutional Neural Networks and Long Short-Term Memory for Real-Time Violence Detection in Videos

Machine learning techniques have been used widely to analyze videos that have scenes of violence for censorship or surveillance purposes. Violence detection plays a crucial role in preventing underage and teenage exposure to violent acts and ensuring a safer viewing environment. The automatic identification of violent scenes is significant to classify videos into two classes, including violence and non-violence. The existing violence detection models suffer from several problems, including memory inefficiency and low-speed inference, and thus make them unsuitable to be implemented on embedding systems with limited resources. This article aims to propose a novel combination of light Convolutional Neural Networks (CNN), namely EfficientNet-B0 and Long Short-Term Memory (LSTM). The public dataset which consists of two different datasets, was utilized to train, evaluate, and compare the deep learning models used in this study. The experimental results show the superiority of EfficientNet B0-LSTM, which outperform other models in terms of accuracy (86.38%), F1 score (86.39%), and False Positive Rate (13.53%). Additionally, the proposed model has been deployed to a low-cost embedding device such as Raspberry Pi for real-time violence detection.
Managing Cybersecurity Risks in Emerging Technologies

Nowadays, it has become increasingly important for companies to effectively manage cybersecurity risks in emerging technologies. This article presents an overview of cybersecurity in these technologies. It sheds light on the obstacles that businesses encounter when dealing with these risks. The field of cybersecurity poses challenges that need to be overcome. Technical challenges include securing communication networks and protecting data and systems from threats. Moreover, it is crucial to ensure the dependability and trustworthiness of emerging technologies. Organisational challenges involve preparing and training employees and devising effective strategies to address the unique cybersecurity issues associated with new technologies. Regulatory challenges arise due to changing compliance requirements in a global context where different countries have diverse cybersecurity laws. To effectively manage cybersecurity risks, it is essential to follow established risk management practices, such as identifying and assessing risks systematically. However, there are gaps in research and practices that should be addressed. These gaps include the lack of frameworks for conducting cost-benefit analyses, a limited understanding of the role played by error in cybersecurity incidents, and the necessity for comprehensive strategies to deal with the constantly evolving landscape of cybersecurity threats. Bridging these gaps requires investigation along with developing effective strategies for improving cybersecurity in emerging technologies.
Pengaruh Brand ambassador dan Keuntungan Reksa Dana Pada Minat Mahasiswa Dalam Berinvestasi Reksa Dana Pada Aplikasi Bibit (Studi Pada STIE Satya Dharma angkatan 2019).

The purpose of this study was to determine the effect o f brand ambassadors and mutual fund benefits on students' interest in investing in mutual funds in Bibit applications (studies at STIE Satya Dharma class of 2019). The analysis technique used in this research is validity and reliability test, classical assumption test, multiple linear regression analysis, and model feasibility test. The results of the study show that Brand ambassadors have an effect on student interest in investing in mutual funds in the Bibit application (Study at STIE Satya Dharma class of 2019) from the results of hypothesis testing with the T test showing that Brand ambassadors have a positive and significant effect on student interest in investing in mutual funds. Profits affect student interest in investing in mutual funds in the Bibit application (Study at STIE Satya Dharma class of 2019) from the results of hypothesis testing with the T test showing that profits have a positive and significant effect on student interest in investing in mutual funds.&#x0D;
Using Latent Diffusion Models for Generating Conditional Facies Realizations: a Study Against Truncated Gaussian Random Fields

Summary Diffusion models have recently gained significant attention, especially the text-to-image models that produce realistic artworks. The challenge of conditional sampling is somewhat similar to our current focus: analyzing facies well logs and aiming to reconstruct complete 2 or 3-dimensional subsurface facies models based on well observations. We introduce a diffusion model that uses latent Gaussian variables and is paired with an encoder-decoder for the discrete representation of facies. Trained on a comprehensive collection of simulated samples, our model can generate samples. We have analyzed the statistical characteristics of the generated samples in comparison to others and believe that our method offers a promising approach for conditional sampling of subsurface geological models.
A Sparse Matrix Formulation of Model-Based Ensemble Kalman Filter

Summary The ensemble Kalman filter (EnKF) introduced in Evensen (1994) has been used successfully in many applications to do data assimilation in state-space models. EnKF represents the knowledge about the latent process in the state-space model through a set of realizations. The filter alternates between a prediction step and an update step. The prediction step can be performed analytically, while the update step must be approximated. In Loe and Tjelmeland (2021) a Bayesian model is used to perform the update step. Specifically, the model parameters are assigned priors and simulated. Moreover, a set of valid update procedures are derived, and the ensemble is updated according to an update procedure that satisfies a specified criterion. However, the procedure introduced in Loe and Tjelmeland (2021) is computationally demanding. In our work we introduce a computationally efficient alternative to the approach in Loe and Tjelmeland (2021) . We formulate a prior for the model parameters which enables efficient sampling, and we partition the update of each ensemble realization into smaller blocks. Simulation studies suggest that the reduction in computational demands is considerable and that the results provided by our approach are essentially similar to the results obtained with the approach from Loe and Tjelmeland (2021) .
ANALISIS PEMBELAJARAN PROBLEM BASED LEARNING (PBL) DENGAN PEMECAHAN MASALAH BERBANTUAN KOMIK LITERASI NUMERASI DAN ETNOMATEMATIKA

The purpose of this research is to find out the application of learning problems (PBL) with the help of comic based literacy numeration and ethnomathematics in the Integrated High School of Madinatul Ulum class VIIIB cangkrung jenggawa based on the theorem pythagoras. This research used qualitative descriptive approaches. The collection of data were observations, interviews, documentation, and tests. Based on a comic-aided problem-solving learning analysis that focuses on the material of the pythagorean theorem and numeration and ethnomathematics literacy, it was found that 80% of students showed improvement. Based on data analysis, it can be concluded that the PBL model improves the learning outcomes of integrated high school students Madinatul Hikmah. The results show that 1. The PBL Model is more attractive to use as a learning model. 2. The students are more involved in working on the pythagoras theorem. 3. The PBL model can improve the critical thinking ability of the pupils and encourage them to do something.
Dual Education Models in Modern Educational Institutions

The aimof the research is to verify the effectiveness of the dual education in modern educational institutions. The research involved the following methods: testing method (Self-Attitude Test) and methods of studying self-assessment through the ranking procedure; the peer-review method; Human Volitional Qualities Questionnaire; Student’s t-test and the Kolmogorov-Smirnov test; Spearman's Rank correlation coefficient; Survey Response Rate calculation. Students expressed the greatest satisfaction with such aspects as the relationship with the tutor (0.84), tutor’s objectivity in work evaluation (0.91), safe working environment (0.92), individual workplace (0.89). There were 58% of respondents who favoured dual education compared to traditional education. A group of experts who studied academic performance noted the advantage of the flipped classroom-based model. The level of special competencies in the control group was 4.5 units, while it was 4.9 units in the experimental group. The results of the study showed the high efficiency of dual education based on the flipped classroom model. The research identified a more effective implementation model. This model shows significant positive results, both in the context of higher education and vocational education. Future research should be aimed at finding an effective model for implementing the dual system in vocational education. Also, it is necessary to study the effectiveness of such innovations in modern realities.
MetaPortal: Business Intelligence and Machine Learning Approach for VR Data

Virtual reality (VR) is a technology that offers near real-world experiences in various fields. With the widespread use of virtual environments designed to provide VR experiences, the amount of data collected from these environments has increased rapidly. However, as the volume of data grows, there is a need to develop analysis processes and advance the data-driven development model. In this study, an application called MetaPortal was developed, utilizing personal characteristics, activity, location, and interaction data of users in the immersive learning environment of Manisa Celal Bayar University (MetaCBU). By employing business intelligence techniques and machine learning algorithms, the application can analyze the vast amount of VR data and classify users in MetaCBU based on their characteristics, activities, and interactions. This paper proposes a combination of business intelligence and machine learning approaches for VR data analysis and provides detailed information about the MetaPortal application developed in this context.
Comparison of Deep Learning and MOORA Performance Methods in Multi Criteria Decision Making with Case Studies Best public health center

This research paper compares the performance of the deep learning and MOORA methods in making multi-criteria decisions to choose the best puskesmas. This paper discusses the methodologies used in both approaches, the architectures and equations used in deep learning, and the advantages and limitations of each method. The results show that the deep learning approach achieves 100% accuracy and the MOORA approach dss model obtains an accuracy of 95.75%.
The Effects of University Students' Career Self-doubt and Emotional Intelligence on Life Satisfaction and Career Satisfaction: Focusing on the Career Construction Model of Adaptation

Objectives To comprehend the career adaptation process among university students, this study chose career self-doubt, emotional intelligence, career adaptability, SCCI, life satisfaction, and career satisfaction as variables that can be incorporated into the career construction model of adaptation. It then analyzed the structural relation-ships among these variables.&#x0D; Methods For this purpose, a survey was conducted among four-year university students, and the data of 231 stu-dents were used for analysis, and the structural equation model was verified using Mplus 8.10.&#x0D; Results First, The model fit of the Career Construction Theory Model of Adaptation established in this study was found to be adequate. Second, Emotional Intelligence had a positive effect on Life Satisfaction and Career Satisfaction through Career Adaptability and SCCI. Third, Career Self-doubt has a negative effect on Career Satisfaction through Career Adaptability and SCCI. Fourth, Emotional Intelligence has a positive effect on Life Satisfaction, and Career Self-doubt has a negative effect on SCCI and Career Satisfaction.&#x0D; Conclusions Through the validation of the suitability of the variables used in this study within the context of the Career Construction Model of Adaptation, we have presented valuable empirical findings that contribute to the comprehension and intervention in the career adaptation process of university students. Additionally, we have discussed the diversification of pathways in the Career Construction Model of Adaptation by establishing relation-ships that consider the unique characteristics of the variables.
Analysis of Applications Principles of Barcode Technology in Product Cost Estimation and Identification

Bar codes are a technology for automatic identification which has found application in many business sectors. As we know that, bar codes have many applications; they have been mostly used in segments of the retail grocery as well as consumer goods industries. They use computers for barcode detection. A bar code has a self-contained message whose information is encoded in the geometry of its printed bars and spaces. When a bar code is read, the patterns of light and dark contained in the bars and spaces are translated into patterns of ones and zeros, which the reading computer interprets as numeric or alphanumeric data. In a simple barcode system, bar codes are read by passing a wand containing a light source and a photo-diode across the code to be read.
Pemberdayaan Masyarakat Pemula (PMP) Peningkatan Kompetensi Pendidik Dalam Pengembangan Perangkat Assessment of Learning Berbasis Digital (ASLIBIDAL) di Sekolah Menengah Atas Kota Surakarta

Learning as a process of organizing the environment around students might meet the National Education Standards. Most educators in Surakarta City had minimal understanding of the assessment of learning outcomes. How was the technique of preparing the right assessment tool in measuring student learning achievement? Based on the situation analysis, the partner's problems were found, including the lack of understanding of educators in the form and technique of preparing appropriate assessment tools, as well as the limited ability of educators to translate assessment techniques into digital form. The proposer's solution was through training, namely first training, designing the preparation of good item items, and providing strategies for composing good item items by paying attention to validity, level of difficulty, discriminating power, and reliability. The second training is monitoring the preparation of item items as well as strengthening the concepts and skills of item analysis techniques as well as assessment tool techniques with the assistance of digital media. The result of the implementation was that the activities run in an orderly manner according to the plan and according to the targets set. From this activity, it could be concluded that there was an increase in the competence of educators in developing digital-based assessments of learning tools after being given training.
An Innovative Exploration of the Integration of Information Technology and Education Teaching Content

The digital era has profoundly changed the way people live and work, and the field of education is no exception. The integration of information technology and educational teaching content aims to give full play to the advantages of information technology, improve the traditional teaching mode, enrich the teaching content, and improve the teaching effect and learning quality. This paper centers on the innovative exploration of the integration of information technology and educational teaching content and proposes effective strategies such as advocating the change of school teaching philosophy and culture, professional training and development of teachers, construction, and sharing of educational resources, establishment of technological infrastructure to support the integration of teaching and learning, as well as the use of data analysis and evaluation, and discusses in depth the possibility of realizing the integration of teaching and learning and its prospects.
STRATEGIES USED BY STUDENTS TO REDUCE ANXIETY IN SPEAKING ENGLISH

Speaking English as a foreign language is a complex process that involves not only speaking skills but also various psychological aspects. Students’ anxiety in speaking English as a foreign language has been a prominent area of concern since many English as a foreign language student have been suffering from this feeling and dealing with various strategies to cope with it. This study aimed to investigate the strategies students used to deal with speaking anxiety. The research was conducted in a junior high school in East Jakarta. A total of 100 respondents were selected based on the criteria, which were students who felt anxious about speaking English. The method used in this study is descriptive qualitative. The instruments applied in this study were interviews and Likert scale questionnaires. The data obtained were then accumulated and narrated. The findings indicate that students do not only use one strategy. The highest strategy used by students was Preparation Strategy (69%). Meanwhile, the least strategy (30%), is the Positive Thinking strategy.
Towards Developing Parallel Corpora for Portuguese and Portuguese Sign Languages

Low-resource languages, including sign languages, are a challenge for machine translation research. Given the lack of large-scale parallel corpora, researchers must use small parallel corpora for training an automatic translation system. This article aims to address this problem by building artificial parallel corpora for Portuguese sign language in automatic translation systems. In this work, we obtained small parallel corpora of Portuguese text and Portuguese Sign Language gloss from the Metro of Porto. We used these corpora to learn grammar rules in translation between Portuguese text and Portuguese Sign language gloss. Ap- plying obtained rules to our data, we generated artificial parallel corpora for Portuguese and Portuguese sign language gloss.
TRACER STUDY: AN IN-DEPTH SEARCH OF THE ENGLISH EDUCATION PROGRAM GRADUATES

Universities have an important role in generating amazing alums who can compete with others. This role makes universities try to find a way to increase the alums' quality. One of them is the tracer study. Tracer study is a technique to track the alums' quality. Therefore, the research objective was to investigate the status, quality, and accomplishment of the graduates/alums of the English Education Program of FKIP UHAMKA. This research employed a mixed-method sequential explanatory research design which combined quantitative and qualitative research design. As many as 98 graduates from the English Education Program participated in the study. A questionnaire that was validated using a validity test before it was distributed through several social media was used as the instrument of this study. Findings have discovered that most of the graduates of the English Education Program who graduated in 2021 can implement their knowledge and abilities per the field of education they had on campus. Unfortunately, graduates whose jobs were in line with their field of study still got low payment. Further research is needed to evaluate the competencies and training that need to be accommodated by the campus to prepare upcoming alums before entering the workspace.