Reviewerly/exHarmony huggingface dataset:
HC-MAE: Hierarchical Cross-attention Masked Autoencoder Integrating Histopathological Images and Multi-omics for Cancer Survival Prediction

Accurate cancer survival prediction enables clinicians to tailor treatment regimens based on individual patient prognoses, effectively mitigating over-treatment and inefficient medical resource allocation. Recently, the integration of histopathological images and multi-omics data, together with deep learning, has become increasingly applied to predict cancer survival. However, current deep learning-based integration methods ignore the spatial relationships across various fields of view within gigapixel histopathological images, since they mainly focus on a specific field of view. Inspired by the hierarchical image pyramid transformer (HIPT), we propose a hierarchical cross-attention masked autoencoder (HC-MAE) to integrate histopathological images and multi-omics data for cancer survival prediction. Specifically, HC-MAE aggregates the representations learned from different fields of view, effectively capturing the fine-grained details and the spatial relationships within histopathological images. We conduct experiments to compare the HC-MAE method with current state-of-the-art methods on six cancer datasets sourced from The Cancer Genome Atlas (TCGA). The experimental results demonstrate that HC-MAE achieves superior performance on five out of six cancer datasets, significantly outperforming the compared methods. The code is available at https://github.com/SuixueWang/HC-MAE.
Crow Search Algorithm Based on Information Interaction for Epistasis Detection

In the genome-wide association study, the interactions of single nucleotide polymorphisms (SNPs) play an important role in revealing the genetic mechanism of complex diseases, and such interaction is called epistasis or epistatic interactions. In recent years, swarm intelligence methods have been widely used to detect epistatic interactions because they can effectively deal with global optimization problems. In this study, we propose a crow search algorithm based on information interaction (FICSA) to detect epistatic interactions. FICSA combines particle swarm optimization (PSO) and crow search algorithm (CSA) to balance the exploration and exploitation in the search process, which can effectively improve the ability of the algorithm to detect epistatic interactions. In addition, opposition-based learning strategy and adaptive parameters are used to further improve the performance of the algorithm. We compare FICSA with seven other epistasis detection algorithms using both simulated datasets and a real-life age-related macular degeneration (AMD) dataset. The results on simulated datasets show that FICSA has better detection power, while the results on the real dataset demonstrate the effectiveness of the proposed algorithm.
Comparing the Prediction of Numeric Patterns on Form C1 Using the K-Nearest Neighbors (K-NN) Method and a Combination of K-Nearest Neighbors (K-NN) with Connected Component Labeling (CCL)

Indonesia's elections serve as a cornerstone of its democratic system, with the active participation of its citizens being of paramount importance. To bolster transparency and civic engagement during these elections, the SITUNG system (Election Result Information System) is employed for the tabulation of election results. However, the current tabulation process remains manual, potentially leading to data entry errors and a reduced accuracy of election outcomes. This research endeavor seeks to enhance the efficiency and accuracy of election result tabulation by employing the K-Nearest Neighbors (K-NN) method for recognizing numeric patterns on Form C1, both independently and in combination with Connected Component Labeling (CCL). The K-NN method demonstrates a commendable 60.0% accuracy in recognizing numeric patterns from the original Form C1 data. However, when combined with CCL, the accuracy drops to 51.2%. This research makes a significant contribution by simplifying the tabulation process and improving the accuracy of election results in Indonesia through the application of the K-NN method. The technology is anticipated to fortify democracy by promoting a more transparent and participatory electoral process for the citizens.
Detection of Hate Speech Code Mix Involving English and Other Nigerian Languages

Hate speech is a recurrent event and has become a cause for global concern. The proliferation of hate speech has recently become prevalent, breeding room for violence and discrimination against specific individuals or groups. In Nigeria, message masking (use of language-mix) has become the new normal, especially in disseminating hateful and inciting comments. Hence, there is a need to curb the spread over social media. Therefore, this research focuses on detecting hate speech on social media with a code-mix of English, Pidgin and any of the three major Nigerian languages (Hausa, Igbo and Yoruba). The research used two machine learning algorithms: Support Vector Machine (SVM) and Random Forest (RF). Data were collected from tweets on the EndSARS protest and the 2023 Nigerian elections. The major features were extracted, and the text was converted into vectors using TF-IDF and Bag-of-words (BoW), which were used to train and test the model. The result showed that SVM performed better in classifying hate speech than RF on both TF-IDF and BoW features, averaging 93.43% for accuracy, 93.70% for precision, 93.43% for recall, and 93.57% for F1-score.
The Assessing Cimenyan Village's IT Readiness for Digital Transformation in West Java

Digital Village Development has become an important agenda in efforts to modernize and improve the quality of life in rural areas. This transformation relies on the use of information and communication technology (ICT) to increase convenience and efficiency in various fields.&#x0D; The success of developing a Digital Village depends on the readiness of ICT infrastructure. The village office, which is the center for administration and services to the community, must have adequate ICT infrastructure as the main requirement for activating various digital initiatives.&#x0D; The research was conducted to determine the current state of readiness of Cimenyan village, Bandung Regency in implementing ICT in village government offices. The readiness level analysis is prepared based on the COBIT framework in 3 domains, namely: IT process domain PO1 (defining IT strategic plans), PO2 (determining information architecture), and PO4 (defining IT processes, IT organization, and their relationships)&#x0D; The results of the analysis will be mapped based on the maturity level of each domain in COBIT. The level of maturity obtained will help the Cimenyan Village government to make appropriate preparations for implementing ICT so that the goal of Cimenyan Village becoming a digital village in West Java can be achieved.
Development of Web-based Application for Private School Tuition Fee Management with Prototyping Model

Private schools need help in handling school fees and financial processes. Traditional manual payment systems result in data processing issues, delayed financial reporting, and complications from misplaced records. Late fee payments threaten school income, which is crucial for staff salaries. Modern solutions are imperative. Desktop applications have limitations, requiring installation on specific devices, leading to compatibility concerns. This research opts for a web-based application. It employs prototyping models and predictive abilities using the Naïve Bayes algorithm. The web-based application aims to streamline fee management and predict payment delays, enhancing financial transaction management while prioritizing data security through database encryption. This web-based solution aligns with private schools' operational needs, simplifying payments and increasing late payment prediction accuracy. Extensive black-box testing validated its suitability, satisfying administrative staff needs. Four test cases gained administrative team approval. This innovation empowers private schools to optimize operations and financial management. In summary, the research tackles critical financial challenges private schools face by introducing a web-based application that simplifies payment processes, enhances accuracy in predicting late payments, and aligns seamlessly with administrative needs.
An Indonesian student's perspective on the use of English by teachers as a monolingual language

This study intends to determine how college students understand an instructor who instructs in a monolingual form of English in an English as a Foreign Language study room. This study involved 20 interviewees and 32 questionnaire respondents in an English as a Foreign Language, classroom. Interviews and questionnaires are the strategies used to collect data, hence, ensuring triangulation of data. Based on the evaluation and interpretation of the records obtained from the questionnaire and interview, the results of this look display that scholars have positive perceptions of teachers who train English as a monolingual language in their English classrooms. This is verified by the imperative tendency of ten questionnaire statements, and declaration. Nevertheless, the most persuasive remark succeeds in moving the main tendency to the "impartial" stage, allowing us to classify it as supporting evidence that students have favorable opinions of English-speaking teachers. Keywords: EFL; English as a foreign language; monolingual; students’ perception; teacher.
Evaluation the Information Security Management System: A Path Towards ISO 27001 Certification

This study addresses the urgent need for robust data security by evaluating the Information Security Management System (ISMS) of a private contractor poised for ISO 27001 certification. It introduces the context of pervasive data breaches that necessitate stringent security measures. Employing a mixed-methods approach, the research method combines the KAMI index for quantitative maturity assessment with qualitative insights from staff interviews and literature reviews. The results reveal the contractor's ISMS maturity at levels I+ to II, indicating a shortfall in meeting the ISO 27001 benchmark. The discussion highlights the efficacy of the PDCA cycle in ISMS implementation, but also underscores the imperative for enhancements to fulfill certification requirements.
Empowering Pregnancy Risk Assessment: A Web-Based Classification Framework with K-Means Clustering Enhanced Models

This study aims to determine whether there is an increase in accuracy results for predicting pregnancy risk with a classification algorithm that goes through and without going through the clustering stage. After that, compare which classification algorithm gets the best improvement. This study uses the K-Means clustering approach, as well as the SVM, Naive Bayes, and K-Nearest Neighbor (KNN) classification algorithms. The pregnancy risk dataset used comes from the UCI Machine Learning Repository. Evaluation metrics used include accuracy, precision, recall, and F1-score. The results of the study revealed that the K-Means model with KNN provided the highest performance compared to the other two, with an accuracy of 79.53% and an average F1-score of 0.8. The implementation of K-Means resulted in an increase in accuracy of 0.4%, 1.57%, and 2.76% on KNN, SVM, and Naive Bayes respectively, which confirms the impact of clustering in improving classification performance. The resulting model can be used in real-time via a website built using the Flask API, and offers tools that can help health practitioners to plan treatments effectively and minimize the risk of pregnancy.
Analysis of ESG Management Issues in Small and Medium-sized Enterprises (SMEs) and Small Businesses Using Big Data: Focusing on Seasonal and Size-based Comparisons

In the context of experiencing unexpected external factors like COVID-19, businesses are facing a significant demand for change. The management focus on ESG has emerged as a practical issue concerning the survival and sustainability of companies.&#x0D; Existing research has primarily concentrated on empirical analysis based on ESG evaluation systems, with relatively little attention given to analyzing key ESG-related keywords. This study aims to fill the gap in such research.&#x0D; To achieve this, the study utilized big data from news channels operating on major portal sites such as Naver, Daum, and Google. Through the application of big data analysis tools, the study performed the extraction and analysis of ESG-related keywords targeting small and medium-sized enterprises (SMEs) and small businesses.&#x0D; The ESG keywords extracted through the use of big data analysis tools contribute to the ongoing discussions about integrated approaches to ESG evaluation criteria. Additionally, they provide foundational data necessary for developing differentiated ESG strategies based on the size of the companies. As a result, this study holds significance in deriving both academic and practical insights.
Pelatihan Penulisan Artikel Ilmiah bagi Guru-guru di Sekolah Dasar Negeri 01 Sukamulia

Writing is not only an essential skill for students but also a crucial aspect in the development of teaching and learning skills for teachers. This abstract discusses the key role of writing in strengthening the abilities of teachers. Based on the analysis of the situation and challenges faced by partners, faculty members as implementers of the Community Service Program (PKM) and professionals from the university will provide a solution to address the difficulties experienced by teachers in writing scientific articles. The solution comes in the form of training in writing scientific papers for elementary school teachers at SDN 01 Sukamulia, Sukamulia District, East Lombok Regency. This training can be described as running with enthusiasm and smoothness due to the significant support in this activity. This activity is also beneficial for teachers to practice writing scientific articles, thereby enhancing the abilities of each teacher at SDN 01 Sukamulia. The results of this activity indicate that elementary school teachers at SDN 01 Sukamulia have gained understanding in writing scientific articles and the methods of publication in accredited or non-accredited national journals.
Penghematan Energi Pada Sistim Pendingin Bangunan Hotel “The Dharmawangsa

Abstract :&#x0D; Conservation of natural resources, one of which is electrical energy, is mostly generated from limited natural resources such as coal, petroleum, and natural gas. Electrical energy is crucial in the natural hospitality/ tourism industry, where air conditioning (AC) equipment consumes a significant amount of electrical energy, typically accounting for around 60% of the electricity usage. The purpose of this research is to analyze the consumption of electrical energy related to the operational efficiency of a hotel building. Energy auditing is the technique used to calculate the energy consumption and determine methods to control it in order to achieve energy savings. The activity involves determining the “Energy Efficiency Ratio” based on standards applied in Indonesia. By implementing electrical energy conservation measures, there can be economic benefits as well. The more efficient the energy usage, the lower the costs incurred to meet electricity needs.&#x0D; Keywords : Conservation Energy, Cold Storage
“The Future of Education, Mindset and Skillset” at the VIII BRICS Young Scientists Forum: philosophical and anthropological understanding

The article presents an analytical review of the section “The Future of Education, Mindset and Skillset” of the VIII BRICS Young Scientists Forum (31 July — 2 August 2023, Gkeberha, South Africa). The programme of this Forum section includes such sub-themes as application of new and convergent technologies in education, new educational tools for overcoming local socio-economic barriers, as well as leadership and entrepreneurial thinking for navigating the ever-changing future. The Forum in general and this section in particular brought together young scientists from five countries (Brazil, Russia, India, China, South Africa) representing both technical and humanitarian scientific fields. The author identifies three key markers in the reports on the education made by young scientists from the BRICS countries and provides their philosophical and anthropological understanding.
Training of Future Specialists in Preschool Education for the Formation of the Activity of Preschool Children

In the article, the problem of training future educators for the development of research activity of older preschoolers is revealed, research analysis is carried out, features of the development of research activity of preschoolers are identified, theoretical approaches to understanding the concept of “research activity” are revealed. To solve the above-mentioned problem, theoretical methods of analysis and synthesis of theoretical and scientific-methodological sources from psychology, pedagogy were used to develop the main concepts of the research on the training of future specialists in the preschool field for the formation of the activity of preschool children.We consider the concept of “research activity” as a persistent desire of the personality of a child of older preschool age to realize, with the help of search activity, the need to learn about the objects of the surrounding world and to discover new knowledge for him.The attention of future educators is drawn to the structure (acceptance of a cognitive task; putting forward hypotheses for obtaining results; selecting methods and planning to achieve results; checking the chosen method of putting forward assumptions) and characteristic features of the development of research activities in preschool childhood (at 5–6 years of age, a child begins to develop selectivity of research activity that ensures the child’s constant openness to new things, which is expressed in the search for inconsistencies and contradictions).We see the competence of a teacher in successfully solving interrelated tasks: seeing a child in the educational process, creating conditions for the successful development of research activity, achieving educational goals, effectively interacting with children and other subjects of education, organizing and using a developmental educational environment. The training of future educators involves the development of the necessary skills and abilities needed to organize the process of developing the research activity of preschoolers.In the process of implementing the theoretical principles of training future educators for the development of preschoolers’ research activity, a business game “The role of the subject-developmental environment in the development of research activity of older preschoolers” was held in a preschool education institution. Ensuring the quality of the educational process for the development of research activity of older preschoolers requires the need to increase the theoretical, practical, organizational and methodological training of future teachers in a higher education institution.
Traditional and interactive technologies for business foreign language teaching in a technical university

Teaching a foreign language at a non-linguistic university should be a purposeful, intensive, exciting and effective process, capable of ensuring both the development of foreign language skills and abilities and high motivation of technical students to learn a foreign language. The author of the article determines that the combination of traditional and interactive teaching technologies at the practical lessons of business foreign language increases the efficiency of the process. The author's textbook "Business English" for the bachelors of technical specialties on business foreign language in the informational-didactic base of Samara Technical University is presented in the article. The aim of this textbook is to develop foreign language communicative success of students of technical specialties through the skillful use of traditional and interactive educational technologies for business foreign language teaching in a technical university
КЛАССИФИКАТОР NAIVE BAYES ДЛЯ НОРМАЛИЗАЦИИ ТЕКСТА: ПРИМЕР ДЛЯ КАЗАХСКОГО ЯЗЫКА

The amount of complicated documents and texts has increased exponentially in recent years, necessitating a deeper understanding of machine learning technologies in order to effectively identify texts in numerous applications. Text normalization is one of the best decisions. It is the reduction of all words of the text to the original form. This paper investigates a layered strategy for fixing mistakes in Kazakh language literature downloaded from the Internet. Because of the widespread use of social media as a source for linguistic study, error correction is a critical issue. The goal of this research was to look at the current Naive Bayes algorithm in English, as well as the normalization of words and sentences in natural languages, in order to create a similar algorithm for the Kazakh language. The method of morphology of Kazakh words and their difference from English was considered suitable for processing words in a dictionary. As a result of the normalization system, the efficiency of this method for the Kazakh language was proved. Keywords: text normalization, Naïve Bayes algorithm, natural language, processing of text, classifier
The Infusion of Moral Values in A Commercial Publisher English Textbook

This research aims to examine the infusion of moral value in English textbooks for middle school in Indonesia. The data were collected through transferring and normalizing the written data from a commercial English textbook entitled: English on Sky 2 forÂ SMP/MTs kelas VII to the Antconc software. The data were analyzed by using corpus based analysis. In order to employ this type of analysis, we used the AntConc corpus analysis software and using vocabularies adopted by previous researchers. The findings of this research showed that the moral values that are represented in this textbook there are two moral values, which are values toward others and values toward self. For values toward others, there are sub values such as conveying kindness, as example is being helpful, and keeping promise; showing respect, such as asking permission and apologizing; showing affection, such as giving compliments, showing close relation with God. Moreover, for moral values towards self such as conveying how to appreciate, accept, yourself.Â
Handwritten Steno Character Recognition in Gujarati

Abstract: Steno is symbol of shorthand character which is used to record spoken word. court reporters use the steno language for quick recording of each moment in court room. Some stenographer can write 300 word per minute. many implementations has been done in recognition of different steno symbol into particular language. In this paper we recognize steno symbol (small script) into Indian language which is gujarati. HSCRG stands for Handwritten Steno Character Recognition In Gujarati. HSCRG Algorithm is a process of recognition steno symbol and extract it into equivalent gujarati character based on PCA and Logistic Regression. HSCRG is based on PCA and Logistic Regression accordingly unsupervised and supervised learning. These system mainly has five stages Preprocessing, Feature Selection, classification, Logistic Regression, Extract into gujarati character.