Reviewerly/exHarmony huggingface dataset:
THE ROLE OF PROFESSIONAL COMPETENCE OF A TEACHER IN THE CONDITIONS OF EDUCATIONAL DIGITALIZATION

This article emphasizes the role of improving the professional competence of teachers in the modernization of modern education in the conditions of digitalization, determining and evaluating the level of competence, personal qualities of teachers, as well as the depth of their professional knowledge is the most valuable wealth of society. The teacher is not only the main figure of society in the legal and regulatory activities, but also an active employee, re-implementing their methods in everyday life for the benefit of society. Professional formation and development of teachers plays an important role in the development of society as a whole. One of the requirements of the quality of professorial competence of a modern teacher is the knowledge of the technology of content design, its methods, methods and the ability to use digital tools, choosing them correctly according to the requirements, goals and advantages of the state.
A Mobile Application for Calculating Nutrition of Cervical Cancer Patien

Nutritional balance is one of the complex problems that can occur in cervical cancer patients. This problem can lead to a decrease in the quality of life of patients during treatment, so the nutritional needs of cervical cancer patients must be controlled and maintained in order to improve the quality of life of patients. It takes a nutrient that cervical cancer patients can use to help them calculate and balance these nutritional needs. This study aimed to create an application to help cervical cancer patients manage their nutritional needs. Research and development research was carried out using the ADDIE method. A limited test of this application was carried out by involving 30 cervical cancer patients who meet the inclusion criteria, namely, cervical cancer patients who had received curative treatment in the form of chemotherapy or radiotherapy in the Cancer Information and Support Center (CISC). The average score of the System Usability Scale used in this limited test was obtained with a value of 79.90 which was in the good and acceptable category. This application can certainly be one way to help cervical cancer patients in managing nutrition and improving their quality of life.
The Effect of Puzzle as Health Education Media on Knowledge and Attitude of DHF Prevention Among Trash Warrior Community

Dengue Haemorrhagic Fever (DHF) is a significant public health threat that can be controlled by engaging all community groups in preventive measures. Interventions targeting early age are pivotal in improving knowledge and attitudes toward DHF prevention. This study proposes a health promotion strategy using a Puzzle as an educational media targeting the Trash Warrior Community members aged 9-12 years to enhance knowledge and attitudes towards DHF prevention. This was a pre-experimental study with a one-group pretest-posttest conducted from February to March 2023. All Trash Warrior Community members aged 9 – 12 (n=20) were included as respondents. They were given a questionnaire consisting of 13 questions of knowledge and ten statements of attitudes towards DHF prevention before and after the health education. The intervention in this study was health education using puzzles in 5 small groups, each consisting of 4 children. Each group was given 30 minutes to arrange the puzzle. This study shows an improvement of mean value on knowledge for 2.1 points and attitude for 0,75 points. Based on the result of bivariate analysis using the Wilcoxon test, it was found that there was a significant effect of education using puzzle media on knowledge (p=0.000, p&lt;0.05) and attitudes (p=0.045, p&lt;0.05) in preventing DHF among Trash Warrior Community members aged 9-12 years. Health education using puzzles effectively increases children’s knowledge and attitude toward DHF prevention.
Implementasi Algoritma Random Forest dengan Forward Selection untuk Klasifikasi Indeks Pembangunan Manusia

Development is essentially a process of continuous change carried out to achieve better living condition. So that the benchmark for the success of a development is seen in its human development. 3 The basic dimensions that form human development are long and healthy life, knowledge, and a decent life. The indicators that represent the three dimensions are summarized in a single value, namely the Human Development Index (IPM). In 2021 the HDI figure in Indonesia is 72.29, which means it is high. However, due to the diverse geographical location of regions in Indonesia, this also influences the HDI rate in each region in Indonesia, so this study uses the Random Forest Algorithm to obtain accurate results from the HDI classification and uses Forward Selection to determine features that influence the classification. The results of the study show that the features that influence the classification are per capita spending, expected length of schooling, life expectancy, and average length of schooling, and get a final accuracy of 80%.
Implementasi Deep Learning dalam Pengklasifikasian Wajah Menggunakan Library Tensorflow pada Algoritma Convolutional Neural Network (CNN)

The convolutional neural network is a deep learning method that functions to recognize and classify objects in an image. An example of its application is a facial recognition system which consists of a detection and classification process. Facial recognition by computers can be influenced by many things such as lighting, expressions, and the amount of dataset provided. This study aims to find out how to implement CNN to identify faces using Tensorflow with the Python programming language. The number of datasets used is 120 data and 10 respondents in total with different lighting conditions and shooting angles. Apart from the dataset, this study also uses several different scenarios in the training process, namely the difference in the number of epochs and the difference in the number of learning rates. Based on the results of the discussion, two models were obtained. In the first model, the results obtained an accuracy of 100% in the training process and 65% in the testing process. In the second model, the results obtained are 100% accuracy in the training process and 75% in the testing process. performance of the model made in this study can be said to be optimal in recognizing objects in several lighting conditions and image angles.
Pemodelan Kadar Hemoglobin pada Pasien Demam Berdarah di Kota Samarinda Menggunakan Regresi Semiparametrik Spline Truncated

This article discusses the innovation of statistical modeling in regression analysis with a semiparametric approach applied to health data. Regression analysis is a method in statistics that takes a lot of roles in statistical modeling. Regression analysis is used to model the relationship between the independent variable (x) and the dependent variable (y). There are three approaches to regression analysis, namely parametric, nonparametric, and a combination of the two, namely semiparametric. Semiparametric regression is used when the dependent variable has a known relationship with some of the independent variables and has an unknown pattern of a relationship with some of the other independent variables. The purpose of this study was to model hemoglobin levels in dengue fever patients, with the independent variables used being the number of hematocrits (x1) and the number of leukocytes (x2). The method used is spline truncated semiparametric regression. The truncated spline estimator was chosen for the nonparametric component because it has many advantages in modeling, one of which is being able to model patterns where the form of the relationship is unknown. The parameter estimation used is the maximum estimation. Selection of the optimal knot point using Generalized Cross-Validation (GCV). Based on the results of the analysis, the truncated spline semiparametric regression model was obtained which was applied to the hemoglobin level data in a model with three knots which have a coefficient of determination of 89.074%. Based on the results of testing the hypothesis simultaneously, it can be concluded that simultaneously the independent variable has a significant effect on the dependent variable. In the partial test, it is concluded that the variables x1 and x2 have a significant influence on the dependent variable y .
Why should Firms Especially smaller Firms Focus on IAM (Identity &amp; Access Management), Zero Trust Instead of Investing in Wide Array of Complex Tools and Security Solutions

Every firm big or small, regardless of the industry, operating capital, size, geographical coverage, aims at improving its cybersecurity and risk posture. These firms build on that strategy by investing in cybersecurity defense tools and processes. The cybersecurity defense industry is filled with various companies providing security tools that span across the information security domains like access management, physical controls, encryption etc.
Decentralized Consensus Mechanisms in Blockchain: A Comparative Analysis

Blockchain technology relies on decentralized consensus mechanisms that allow distributed networks of nodes to agree on the state of a ledger without central coordination. This paper provides a comparative analysis of major consensus protocols utilized in blockchain systems, including proof-of-work (PoW), proof-of-stake (PoS), delegated proof-of-stake (DPoS), practical Byzantine fault tolerance (PBFT), and federated consensus. We analyze the core principles behind each mechanism, strengths and weaknesses in terms of security, scalability, energy efficiency, and decentralization. We also provide examples of major blockchain platforms utilizing these protocols. Our analysis finds that no consensus mechanism optimizes across all attributes, with inherent tradeoffs between decentralization, transaction throughput, energy use, and finality. Hybrid models are emerging which aim to balance these tradeoffs.
A Dense Network Model for Outlier Prediction Using Learning Approaches

There are various sub-categories in outlier prediction and the investigators show less attention to related domains like outliers in audio recognition, video recognition, music recognition, etc. However, this research is specific to medical data analysis. It specifically concentrates on predicting the outliers from the medical database. Here, feature mapping and representation are achieved by adopting stacked LSTM-based CNN. The extracted features are fed as an input to the Linear Support Vector Machine () is used for classification purposes. Based on the analysis, it is known that there is a strong correlation between the features related to an individual's emotions. It can be analyzed in both a static and dynamic manner. Adopting both learning approaches is done to boost the drawbacks of one another. The statistical analysis is done with MATLAB 2016a environment where metrics like ROC, MCC, AUC, correlation co-efficiency, and prediction accuracy are evaluated and compared to existing approaches like standard CNN, standard SVM, logistic regression, multi-layer perceptrons, and so on. The anticipated learning model shows superior outcomes, and more concentration is provided to select an emotion recognition dataset connected with all the sub-domains.
Navigating the Landscape of Robust and Secure Artificial Intelligence: A Comprehensive Literature Review

Addressing the multidimensional nature of Artificial Intelligence assurance, this thorough survey is dedicated to elaborating on various aspects of ensuring the reliability and safety of computerized systems. It steers through the turbulent seas of model enervates, unmodelled phenomena, and security menaces to give an elaborate lit review. The review touches upon the boisterous ways of addressing these intricate mitigation strategies for model errors used in the past, the challenges of under-specification with modern ML models, and how understanding uncertainty is crucial. In addition, it evaluates the AI system’s security basis, the emerging Adversary Machine Learning field, and its processes necessary for testing and evaluation of weaker adversarial case studies. The review of literature also looks upon the situation of DoD context, how the terrain surrounding developmental and operational testing is altering with all these shifts in culture that must be implemented if not to implement robust but secure AI implementation.
SSO Based Fingerprint Authentication of Cloud Services for Organizations

Access to a pool of programmable resources, such as storage space, applications, services, and on-demand networks, is made possible by cloud computing technology. Involving the cloud with the organization reduces its efforts to meet the needs of its customers. The Single Sign-On (SSO) method, which enables users to access various application services using a single user credential, is one of the key benefits of cloud computing. There are numerous problems and difficulties with cloud computing that need to be highlighted. However, protecting user agent privacy against security assaults is far more challenging. To combat security and privacy assaults, this study suggests SSO-based biometric authentication architecture for cloud computing services. Since end devices are computationally inefficient for processing user information during authentication, biometric authentication is effective for resources controlled by end devices at the time of accessing cloud services. As a result, the proposed design minimizes security attacks in cloud computing. An innovative strategy that establishes a one-to-one interaction between the user agent and the service provider is also included in the suggested design. In this case, user agents can use their fingerprint to access various cloud application services and seek registration. The highlights of the suggested architecture have been offered based on comparison analysis with a number of existing architectures.
Handwritten Vedic Sanskrit Text Recognition Using Deep Learning and Convolutional Neural Networks

Recognizing Vedic Sanskrit text is essential for accessing classical Indo-Aryan language, predominantly utilized in the Vedas. Currently, there is limited awareness about the Vedas, making this field a highly demanding and challenging area in pattern recognition. To accelerate progress in optical character recognition (OCR), deep learning methods are indispensable. This article presents a novel approach to Vedic Sanskrit text recognition, incorporating deep convolutional architectures with their respective interpretations. We introduce three modified 4-fold CNN architectures and the AlexNet model. Our system comprises a handwritten dataset containing 140 distinct Vedic Sanskrit words, with approximately 500 images per word, totaling around 70,000 images. The dataset is partitioned for training and testing in an 80:20 ratio. Training is conducted using 20% of the samples, and the resulting model is applied to the deep convolutional network with varied sets of neurons in their hidden layers. Our proposed method demonstrates robust support for accurate Vedic Sanskrit word classification. The recognition rate achieved in our research is 97.42%, with an average recognition time of 0.3640 milliseconds, surpassing existing CNN-based approaches.
Morphological Analysis of Compound Form (Fukugoudoushi) Verb+Ageru in Japanese

This study aims to investigate the formation and meaning of fukugoudoushi or compound verb formed from the Verb+ageru. This study is a qualitative descriptive research. The total of 35 data is in the form of sentences in data sources taken from the 2021 edition of the NHK Japan articles. The data collection method is the note-taking method. Data analysis uses the distributional method with advanced techniques for direct elements, namely by dividing the fukugoudoushi forming elements into front and back elements. Furthermore, it explains the characteristics of the front elements based on the theory of Kindaichi (1989) which divides doushi into 4 groups, namely joutaidoushi, keizokudoushi, shunkandoushi, and daiyonshu-doushi. The results showed that out of 35 data analyzed there were front elements of fukugoudoushi ~ageru in the form of tadoushi-keizokudoushi (20 data), tadoushi-shunkandoushi (9 data), jidoushi-keizokudoushi (1 datum), jidoushi-shunkandoushi (3 data), and futsuumeishi (2 data). The meanings resulting from the formation of fukugoudoushi ~ageru include showing direction, showing improvement, showing high value, expressing self-demeaning, and ending an activity.
Peran Teknologi dalam Mengurangi Konflik Bahasa: Tinjauan Solusi Digital

Purpose- This research aims to explore the impact of highly advanced technology in reducing cross-cultural language conflicts, especially in Indonesia, which boasts rich linguistic and cultural diversity. Information technology has significant potential to serve as a catalyst in mitigating language conflicts amid the cultural and linguistic diversity in Indonesia. Design/Methodology/Approach- The research employs a descriptive-analytical literature review method, which highlights various relevant theories supporting an understanding of how technology can play a crucial role in dampening language conflicts. Data collection from literature reviewed by several researchers is conducted to gain a profound understanding of the impact of information technology in mitigating language conflicts among different language and cultural groups. Findings- The findings indicate that information technology serves not only as a tool to reduce conflicts among groups with different linguistic and cultural backgrounds but also as a facilitator in building intercultural and interreligious communication. By exploring digital solutions, it is evident that technology plays a significant role in deepening cross-cultural understanding and strengthening inter-country relationships. With technological advancements, it is expected that these solutions will continue to innovate and contribute to creating a more inclusive and mutually understanding society amidst the linguistic and cultural diversity in Indonesia. Research Limitation/Implications- This research is still in the theoretical realm and does not involve field testing as a comparative method. Nevertheless, this study can be considered as a preliminary step in exploring the role of rapidly developing technology in addressing language conflict issues.
استخدام أسلوب اختبار الكلمات في انستجرام لمادة التركيب لترقية تحصيل الطلاب الدراسي / Penggunaan Teknik Kuis Intagram pada Materi Tarkib Untuk Meningkatkan Hasil Belajar Mahasiswa

Purpose - The purpose of this research is to determine the learning outcomes of students at Ma'had al-Jami'ah of the Persis Islamic Institute Bandung in the subject of 'tarkib' before and after the implementation of quiz techniques using Instagram as a medium. Design/Methodology/Approach- The method employed in this research is a Quasi Experiment with a pre-test and post-test design model. The data collected for this study is both qualitative, examining the conditions of the location, and quantitative, focusing on calculations. Data collection techniques involve a combination of observation, interviews, testing, research, and literature review. Findings - Referring to the research findings obtained in this study, it is evident that the learning outcomes of students at Ma'had al-Jami'ah of the Persis Islamic Institute Bandung in the subject of 'tarkib' before using the Instagram quiz technique yielded a score of 65 within the interpretation range of 60-65, indicating a good level. Following the implementation of the Instagram quiz method in the 'tarkib' subject, the post-test results yielded a score of 82 within the interpretation range of 80-89, denoting an excellent level. Furthermore, the N-Gen testing resulted in a score of 4.2%, implying that the use of the Instagram quiz technique in the subject matter has a significant impact on student scores at a moderate level. Research Limitation/Implications- The issue in this research is confined by directing the study's focus on the influence of using the Instagram quiz method within the subject of 'tarkib' among the students of Ma'had al-Jami'ah at STAI Persis Bandung.
ARTISTIC AND EPISTEMOLOGICAL POSSIBILITIES OF THE NOVEL

The development of the novel took place in the form of adaptation of the genre to the needs of cognition. The decisive characteristic of the novel genre was not the volume, the type of hero or the way of presenting the material, but the cultural functions of the novel, understood as a type of information management. The novel reflected the "information movement" from a person to a person. These functions should be called personocentric. The author identifies four stages of the novel's development (respectively, four types of novel). 1. The novel of events. 2. A novel of characters. 3. Novel situations. 4. The novel of knowledge (epistemological novel).
FEATURES OF RETROUTOPIA IN THE DRAMATURGY OF BULAT GAVRILOV

The play of the Russian-speaking Buryat playwright B. Gavrilov “Genghis Khan” (2001) is considered from the point of view of its re-interpretation with an idealizing message of the personality and activities of the founder of the Mongol Empire. The ruler is shown as a sage, comprehending and realizing his mystical purpose. In this coordinate system, the capital of Khara-Khorin acquires the features of an ideal city, symbolizing the idea of the unity of peoples and cultures, and play genre is complicated by elements of retro-utopia.
“THE WORDS ARE YOURS, BUT THE ORDER OF THE WORDS IS MINE” (ON THE CREATIVE METHOD OF L.A. ANNINSKY)

The article analyzes the genre and stylistic features of Lev Anninsky’s critical articles, the image of the author and his interpretative strategy, the problems of his key articles and books.
SYNTHETIC TEXT: TO THE PROBLEM OF DIFFERENTIATION OF THE PHENOMENON OF SONG POETRY

The article treats the song text as a kind of synthetic text. The intermediate nature of the object of study gives rise to difficulties associated with the need for an interdisciplinary approach to its study. Author's and bard's song, rock poetry and rap poetry - these and adjacent types of combining music and text cannot be described and classified using the available tools. The interaction of music and text, the peculiarities of performance, the variability of song texts - all these complicates the research task. An attempt to resolve the terminological confusion that aroses almost simultaneously with the phenomenon of literary chant and accompanying the entire history of research, is being made. The option of differentiating song texts depending on the category of authorship is proposed. It also seems to be important to determine the degree of influence of third-party subtexts on meaning.
Development of the Country’s Economy Through the Development of the Stock Market in Developing Countries

This article explores the pivotal role of stock market development in driving economic growth and stability indeveloping countries, with a focus on Uzbekistan. It identifies key challenges faced by developing nations and offersstrategic recommendations to unlock the transformative potential of a thriving stock market. Recommendations encompassregulatory enhancements, investor education, infrastructure development, investor protection, foreign investmentpromotion, market information accessibility, diversification of listing requirements, and collaboration for capacity building.