Reviewerly/exHarmony huggingface dataset:
The Role of the Discipline of Information Technology: A Systematic Literature Review

Aim/Purpose. The goal of this publication is to explore methods for advancing student success in technology related disciplines via improved program classification and selection within higher education. Background. Increased demand for information technology (IT) professionals has been cited as a challenge in many fields including cybersecurity and software development. Many highlight the challenge as not just a numbers gap but a skills gap when comparing industry needs to the curricula in traditional disciplines within higher education. Closing the gap by increasing the number of skilled graduates remains a critical challenge we must address. Methodology. This publication leverages a systematic literature review to identify factors that classify existing higher education programs within the discipline of information technology. Contribution. Research in this area can act as a catalyst to increase relevance of IT related programs as well as graduation rates in technology and engineering. Findings. Authors analyzed forty-four primary studies and found that 56.8% of the publications referenced programs that meet the IT framework definition although they were not classified as IT programs. The findings and further analysis highlight direct challenges between program classification and the potential impact on student success. Recommendations for Practitioners. Research in this area is relevant for academic administrators, private sector executives and others working to increase the technology pipeline. Recommendations for Researchers. Researchers may benefit by exploring thematic analysis as a means of generating relevant classifications and taxonomies that highlight opportunities for improvement in a broad set of subject areas. Impact on Society. Research in this area can serve as a catalyst to increase graduation rates in programs related to technology and engineering. Future Research. This area would benefit from further research by comparing program success rates within varied disciplines. Future research may also produce a classification process.
Enhanced Text Emotion Prediction Algorithm: A Comparative Study with Support Vector Machines for Emotion Prediction in Text

Text emotion prediction is a critical task in various applications, including sentiment analysis, customer feedback analysis, and social media monitoring.This paper presents a comparative study between the Enhanced Text Emotion Prediction (ETEP) algorithm and the Support Vector Machines (SVM) algorithm for text emotion prediction.The ETEP algorithm incorporates data preprocessing, feature extraction, and machine learning techniques to predict emotions from textual data.SVM, a widely used machine learning method, is employed as a benchmark for comparison.A comprehensive evaluation is conducted using a suitable dataset, and performance metrics such as accuracy, precision, recall, and F1-score are utilized to compare the two algorithms.Experimental results demonstrate that the ETEP algorithm achieves competitive performance compared to SVM, highlighting its effectiveness in text emotion prediction.The proposed algorithm successfully captures emotional cues by leveraging appropriate preprocessing techniques, feature extraction methods, and machine learning models.The findings of this study provide valuable insights into the development of accurate and efficient algorithms for text emotion prediction, contributing to advancements in natural language processing and sentiment analysis.The ETEP algorithm's ability to accurately predict emotions from textual data has significant implications for improving user experience, sentiment analysis applications, and decisionmaking processes based on emotional responses.Further research can explore the algorithm's scalability and adaptability to larger and more diverse datasets to enhance its practical applicability in real-world scenarios.
Online Sequential Sparse Robust Neural Networks With Random Weights for Imperfect Industrial Streaming Data Modeling

Industrial streaming data exhibits the concept drift characteristic due to the time-variant operating conditions, which degrades the performance of models established by traditional offline batch learning. Moreover, the widespread outliers and the correlations between data variables in industrial data streams can have a devastating impact on modeling. Therefore, this paper presents a novel online sequential sparse robust neural networks with random weights (OSSR-NNRW) for imperfect industrial streaming data to achieve highly reliable online modeling of time-variant dynamic systems. First, sparse partial least squares regression is used to replace least squares estimation for network output weights calculation, which not only can effectively solve the multicollinearity problem caused by correlations, but also enable variable selection to improve the performance and interpretability. Second, we introduce the online sequential learning strategy with forgetting factor to realize adaptive updating of model parameters, thus enhancing the online learning ability and overcoming the time-variant dynamics of industrial systems. More importantly, in order to strengthen the robustness of the model, Schweppe generalized M-estimation is adopted to determine the modeling weights by the model residual size and the distance information of input vectors in the high-dimensional space to resolve the prevalent existence of outliers in the input and output samples. Finally, data experiments on two industrial systems have validated the effectiveness, advancement, and practicality of the proposed method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In the process industry, the product quality relies on the timely and accurate measurement of key production indicators. However, owing to the time-varying characteristics of industrial processes and the limitations of measurement devices, conventional batch learning-based data-driven models are difficult to apply to imperfect industrial data stream scenarios. To this end, the OSSR-NNRW is proposed for online robust modeling of complex time-variant dynamic systems by combining sparse robust modeling and online learning strategy in a unified framework of neural networks with random weights. The OSSR-NNRW enables online learning based on industrial data streams while resolving correlations between data variables and mitigating the negative effects of outliers from both input and output samples on the modeling process. Experimental results using two typical process industry datasets show that the proposed OSSR-NNRW has high estimation accuracy and can be easy to implement in industrial processes.
Visualisation of Some Poems of Yahya Kemal with Artificial Intelligence Technology

We think that addressing the view of artificial intelligence, which is used in almost every field today, from literary genres to poetry will fill a gap in the literature. In this context, in this study, we examined how to visualise poems from literary products with artificial intelligence and whether the visuals created will be related to poetry. For this purpose, we selected Yahya Kemal's poems titled Gurbet, Bir Yıldız Aktı, Uçuş, Ziyaret, Siliz Gemi, Maltepe, Akşam Musikisi, Gece, Mevsimler, which have an important place in Turkish literature. We obtained visuals for the poems using Dall. E and Artbreeder applications. In the study, we examined how compatible the visuals were with the poems by using the content analysis method. As a result; artificial intelligence produced visuals suitable for the words, themes and emotions in the poems. We determined that the visuals produced by artificial intelligence were reminiscent of poems in terms of colour and shape.
Investigating the Relationship between the Influencing Fire Factors and Forest Fire Occurrence in the Districts of Rompin, Pekan, and Kuantan in the State of Pahang, Malaysia, Using Google Earth Engine

Forest fires pose a significant threat to ecosystems and human livelihoods. Understanding the role of climatic factors in fire occurrence is crucial for effective fire management and prevention. This study analyses the influences of temperature, precipitation, and wind speed on fire incidents in the districts of Rompin, Pekan, and Kuantan in Pahang, Malaysia. The investigation is motivated by newspaper articles dated early March 2021, which report that the fires in these districts were triggered by an extended period of hot and dry conditions, as highlighted by the Director of the Fire and Rescue Department of Pahang, Malaysia. However, no further investigation or detailed discussion has been deliberated. By examining the historical climatic data and fire incidents, this study aims to investigate the relationships between these climatic variables and fire occurrences. The results reveal that higher temperatures and lower precipitation are associated with increased fire susceptibility due to reduced soil moisture. In contrast, wind speed does not appear to impact fire spread significantly. These findings will undoubtedly provide valuable insights into the complex interactions between climatic variables and regional fire incidents, enabling policymakers and fire management authorities to develop targeted fire prevention and mitigation strategies.
PEMBINAAN PEMBELAJARAN BAHASA INGGRIS DALAM MENINGKATKAN KOSAKATA MELALUI FUN ENGLISH LEARNING

This community service program aims to introduce English vocabulary learning among early childhood or children in the Kindergarten/TPA of Balle Village. The teaching method used in this activity is through the Fun English Learning method, which means teaching English to children who have a fun English learning concept. It includes learning activities using songs and games. The results of this program show that the participants have started to have fun learning English and that students' vocabulary and understanding of English vocabulary have increased compared to the beginning of the meeting. Even though there are still mistakes, they have started to be confident and don't feel ashamed.
Reality and Beyond: Proxemics as a Lens for Designing Handheld Collaborative Augmented Reality

Augmented Reality (AR) has shown great potential for supporting co-located collaboration. Yet, it is rarely articulated in the design rationales of AR systems that they promote a certain socio-spatial configuration of the users. Learning from proxemics, we argue that such configurations enable and constrain different co-located spatial behaviors with consequences for collaborative activities. We focus specifically on enabling different collaboration styles via the design of Handheld Collaborative Augmented Reality (HCAR) systems. Drawing upon notions of proxemics, we show how different HCAR designs enable different socio-spatial configurations. Through a design exploration, we demonstrate interaction techniques to expand on the notion of collaborative coupling styles by either deliberately designing for aligning with physical reality or going beyond. The main contributions are a proxemics-based conceptual lens and vocabulary for supporting interaction designers in being mindful of the proxemic consequences when developing handheld multi-user AR systems.
Perancangan Keamanan Jaringan Komputer Pada Router Dengan Metode ACL Pada PT. Aruna Sinar Jaya Jakarta

At PT. Aruna Sinar Jaya, the Internet network plays an important role in running the company's wheel. The problem is that some client computers that do not require an internet connection in their work still have access to the Internet, sometimes the Internet is overused that is not related to work. To solve the above problems, network security methods such as Access Control List (ACL) are needed to make Internet use in Aruna Sinar Jaya more controlled and efficient. In this case, the author recommends implementing ACL on Mikrotik routers using Winbox to restrict internet connections.&#x0D; Keywords: Access Control List, Microtic Router, Winbox.
Perancangan Sistem Informasi Pos Pelayanan Terpadu Apel Merah Kelurahan Jati Padang Berbasis Website

Integrated Health Post (Posyandu) is one form of Community-Based Health Effort (CBHE) managed by, for, and together with the community, aimed at empowering and providing facilities to the community in obtaining healthcare services for mothers, infants, and toddlers. The challenges faced by Posyandu Apel Merah include the manual recording of data, which is done by hand using shortcut books to document the activities of the Posyandu. The purpose of this research is not only to fulfill the requirements for our literature degree but also to assist Posyandu cadres in simplifying the recording of Posyandu activities using the system we are developing, called "Sahabat Posyandu." The research method we employed involved interviews and data collection conducted with the chairwoman of Posyandu Apel Merah, Mrs. Saimah herself. The results of our research will be implemented into the system we are building to aid Posyandu cadres in recording data related to weight measurements and pregnant women. The system we are developing is titled "Sahabat Posyandu: Integrated Post Service Information System for Apel Merah Subdistrict, Jati Padang, Based on a Website.&#x0D; &#x0D; Keywords: Information System, Integrated Service Center, Website
Implementation of a Marker Type Augmented Reality-based Free Music Trial Listening Application at Physical Music Stores

The way we listen to music has undergone major changes—from cassette tapes and records to com- pact disks (CDs) and digital music that includes subscription-based online streaming and download- able sound sources. However, despite the popularity of digital music, CDs continue to be used as a means of listening to music due to the following reasons: the sense of safety felt upon holding the actual product and the collection factor for people interested in building personal collections. However, since the COVID-19 pandemic occurred in 2019, amid growing anxiety and turmoil about contact with “people” and “things,” users have become sensitive to the use of auditioning machines at CD shops. Therefore, we have developed a music trial listening application that uses augmented reality (AR) technology to enable people who visit CD shops to listen to the music of artists they are interested in without any physical contact with the auditioning machines. Users can feel the com- mitment of the artist by actually holding the CD jacket in their hands via AR; they can also view various types of information about the artist by recognizing the image on the CD jacket by using our AR technology-based developed application. Our proposed application consists of the “Listening Mode,” which provides the music trial listening function, and “AR Mode,” which provides the artist information presentation function. Further, we conducted an evaluation experiment with 30 sub- jects to evaluate the operability, readability, functionality, relevance, effectiveness, applicability, and safety of our developed application compared to the CD auditioning machine. The experiment results showed highly positive user evaluations regarding most of the abovementioned tested attributes. The user evaluations also showed that there is room for improvement regarding the operability of the AR objects generated via the application. In future studies, we aim to focus on the improvement of the application’s operability and enrichment of its contents, for example, we plan to add the “background playback function” and “administrator content registration function” to the existing functions of the applications.
Role of Enterprise Applications for Pharmaceutical Drug Traceability

The role of enterprise applications in pharmaceutical industries is driving the digital transformation of various critical processes, and one process benefiting from this innovation is pharmaceutical drug traceability. This industry grapples with challenges like a lack of transparency, difficulties in tracking products, a deficit of trust, and issues related to shipping expired products. To address these concerns, blockchain technology as an enterprise application has been harnessed as a solution. Notably, counterfeit drug prevention emerged as the most prevalent category, aligning with the pharmaceutical industry's primary objective. Blockchain technology is an emerging innovation that is finding enterprise applications in various industries, including healthcare. In the healthcare sector, Blockchain networks are being utilized to securely store and exchange patient data across hospitals, diagnostic laboratories, pharmacies, and medical practitioners. These enterprise applications can effectively identify and mitigate critical errors, including potentially hazardous ones within the realm of healthcare. Consequently, this enterprise technology holds the promise of enhancing the efficiency, security, and transparency of medical data sharing within the healthcare system. Moreover, it offers valuable tools for medical institutions to gain insights and improve the analysis of medical records. It visually represents the diverse capabilities, enablers, and the unified workflow process of Blockchain technology in supporting healthcare on a global scale. Additionally, the paper presents a thorough discussion of fourteen significant applications of Blockchain in healthcare, underscoring its pivotal role in addressing issues like deception in clinical trials.
The Implementing of Using Wordwall as a Media to Improve The Students’ Vocabulary Achievement in New Normal Era

The objectives of this research were to improve vocabulary achievement by using Wordwall web-based application at the eleventh grade students of SMAN 1 KRIAN. Classroom action research was used as the research approach. This study's sample consisted of one class of 28 eleventh grade students. The data were gathered by using observation, tests and questionnaire and were analysed by descriptive statistic for vocabulary test scores and descriptive qualitative for the observation results and questionnaire. In accordance with the findings, only 21% of students passed the KKM during pre-cycle. Students' results improved in post-test I, with 71% passed the KKM. Students' scores improved in the post-test II, with 86% of students who completed the KKM. As many as 93% students gave positive opinion that said was fun and easier did exercieses in Wordwall. In conclusion, used Wordwall in learning can improve student’s vocabulary achievment.&#x0D;
Semiotics and Brand Perception: How Symbols and Signs Influence Consumer Behavior

In the world of branding, using symbols and signs effectively is essential to developing a powerful and recognisable identity. Semiotics, the study of signs, symbols, and how they are interpreted, is important in forming brand perception and affecting consumer behaviour. Being able to convey a company's message and values through visual signals is crucial to building a strong and successful brand. In order to better understand how signs and symbols are used to influence customer behaviour, this article will investigate the connection between semiotics and brand perception. We will examine the fundamentals of semiotics, how it affects consumer behaviour and brand perception, the value of brand identity, and the best methods for integrating semiotics into branding. We will also look at recent developments in semiotic branding and how technology is influencing this important aspect of effective branding in the future. With this investigation, we hope to offer tips and advice to help businesses develop a distinctive brand identity that appeals to their target market and encourages customer loyalty.
BEST PRACTICE PENERAPAN MODEL PEMBELAJARAN PROBLEM BASED LEARNING (PBL) DENGAN MENGGUNAKAN MEDIA GAMBAR BERSERI UNTUK MENINGKATKAN KEMAMPUAN MENULIS TEKS CERPEN

This best practice activity was carried out at SMP Negeri 1 Pelalawan, which is located at Jalan Tugu Kemerdekaan 05 Pelalawan, Pelalawan Village, Pelalawan Regency, Riau Province. The problem encountered was the low ability of class IX students of SMP Negeri 1 Pelalawan, Pelalawan District, in writing short stories. The purpose of this best practice activity is to improve students’ ability to write short stories. The model used is Problem Based Learning (PBL) using serial image media. The results of the best practice activities showed an increase in the ability of class IX students of SMP Negeri 1 Pelalawan, Pelalawan District, in writing short stories.
PENINGKATAN KEMAMPUAN SISWA DALAM MENULIS TEKS BERITA DENGAN MODEL PROBLEM BASED LEARNING (PBL) DENGAN MEDIA TEKS BERITA

The Problem Based Learning using ficture can be used to improve the ability to write short stories because these models, strategies, and media provide students whith idiom to find and start short story writing activities. The activity of writing short stories in the process of good practice by author has shown an increase in the ability to write short stories. The improvement in the ability to write short stories made by student can be seen from the increase in the enthusias tic learning process and the work in the form of write short stories
Project: A Simple Guessing Game

JavaScript can be used to write some pretty sophisticated games, but that’s not going to happen here. Instead, we’ll write a very simple guessing game. This will help us to develop skills in some of the important concepts in the JavaScript language.
VIDEO MODELING TECHNOLOGY IN EVALUATING EDUCATIONAL RESULTS OF PRESCHOOL CHILDREN IN THE INTERACTION BETWEEN PRESCHOOL INSTITUTIONS AND PARENTS

The relevance of using video modeling technology is due to the nature of changes in everyday information space, availability of technical means for video, high diagnostic and educational potential provided by the integrative nature of the product in relation to the user (uniqueness and complex nature of the impact). Video-modeling technology in preschool education institution is a wide range of video materials for educational purposes. The use of the technology is determined by the nature of interaction between the main subjects of the educational process of preschool education. Purpose of the study: substantiation of using video modeling to demonstrate and evaluate the educational results of senior preschool children. A questionnaire survey of parents (n=) showed that virtually all parents use everyday video in their interaction with children. Parents are interested in the innovative technologies being implemented in the educational process. They are also interested in assessing the educational results of their children in all areas of development. In order to apply a video-modeling technology to assess the educational results of preschool children in different areas of development, the following materials were developed: a system of standardized story assignments to be performed at home together with parents, a bank of video materials in developmental areas, a block of assessment scales in developmental areas of preschool children. Eighty-six educators and parents of preschool age children participated in the evaluation of the prepared informational and methodical materials. The testing of video modeling technology revealed the high potential of the elaborated information and methodological materials for use in the educational process of preschool institutions and family education to assess the educational results of preschool children.