Reviewerly/exHarmony huggingface dataset:
Embracing Mobile Learning: Exploring the Acceptance Among Undergraduates in Sri Lankan Universities

This research explores the emerging trend of mobile learning in the higher education sector, with a focus on identifying key factors influencing its adoption in Sri Lanka. In this study, a quantitative approach was employed, encompassing a participant pool of 323 undergraduates drawn from Sri Lankan national universities. The study scrutinizes the factors that influence the acceptance of mobile learning by investigating performance expectancy, effort expectancy, social influence, facilitating conditions, perceived playfulness, and self-management of learning employing mainly correlation and multiple regression data analysis techniques. A notable revelation emerges as the research highlights "self-management of learning" as the most influential factor, surpassing the conventional assumption regarding the significance of "performance expectancy," which surprisingly exhibits no direct impact on mobile learning acceptance. The model effectively explains an impressive almost sixty-eight percent of the variance in undergraduates' acceptance of mobile learning. Beyond the academic context, the insights that emerged from this study hold the potential to revolutionize educational practices in Sri Lanka, offering valuable guidance to educators, policymakers, and educational technology developers striving to seamlessly integrate mobile learning into the higher education landscape while contributing to the broader discourse on innovative pedagogical strategies.
syntax and collocations of Akan ideophonic words

This paper examines the syntactic behavior of Akan ideophonic words. Scholars such as Dolphyne (1987) and Saah (1995) have dilated on the morphological behaviors of the variant in Akan negation morphemes thus generating the syntactic behaviors underpinning the operation of Akan negation inflections. Though Giannakidou (2008) asserts that negative polarity items can be found in all natural languages, it is an aspect of negation in syntax having little studies. Following Ampofo (2015) enlistment of negative polarity items in Akan, we limit the discussion to ideophones and argue that negative polarity in Akan is a syntactic feature of ideophonic nominal and modifiers having both recessive and dominant sensitivity with respect to negated constructions. Therefore, this study discusses the syntactic behavior of ideophonic polarity to affirmative and negated constructions. Their syntactic sensitivity categorizes the ideophones into affirmative polarity items (API) with a dominance for positive verbals as a typology only collocating with affirmative verbals and the category of negative polarity items (NPI) having a dominance sensitivity for negative verbals as a typology collocating negated verbals. It considers the permissibility of ideophonic modifiers in tense aspects and its corresponding collocants. The syntax- semantics of downward entailment theory and binding theory of Ladusaw (1980) and Progovac (1988) are employed to account for the syntactic behavior of ideophonic modifiers and their resulting collocants.
Automated Abstractive Text Summarization Using Multidimensional Long Short-Term Memory

Text summarization is a technique for condensing and presenting the most crucial information from a larger text in a succinct manner. It is a challenging task for human beings to manually summarize extensive documents due to the time required and cognitive effort involved. The increasing amount of textual data generated in recent years has led to a greater demand for efficient and automated text summarization methods. This study explores the utilization of deep learning and neural network concepts to create an automatic abstractive text summarization system for product reviews using multi-dimensional long short-term memory. Since, reading product reviews can be a time-consuming task, especially given the abundance and diversity of reviews written by numerous individuals. The proposed model was evaluated by comparing the generated summaries to reference summaries using metrics such as Rouge. Further, the performance of the model is compared with the prevalent state-of-the-art techniques. The proposed Multi-Dimensional LSTM model was evaluated using the Amazon food review dataset and compared with four other text summarization methods. The proposed model outperformed the prevalent models in terms of ROUGE-1 and ROUGE-L scores but was slightly outperformed in terms of the ROUGE-2 score.
Rancang Bangun E-Learning Pelajaran Pilihan Pada SMAN 3 Palangkaraya Berbasis Web (Studi Kasus Pelajaran Bahasa Jerman)

The current development of Information Technology makes it easier for people to access information anytime and anywhere, making distance not an obstacle to getting information from various corners of the world. Therefore, mastery of a foreign language other than English is important. One of the foreign languages ​​that has an important role is German, so German language subjects are currently one of the foreign language subjects besides English taught in both SMA, MA and SMK. Using e-Learning makes it possible for the educational process to take place without face-to-face contact and the development of knowledge for students can be done easily. The problem of this research is how to build a Web-Based German e-Learning Application at SMA Negeri 3 Palangkaraya. This application aims to make it easy for students to be able to access German language learning materials wherever they want to access them when connected to the internet network, so that it can encourage students' interest in learning German. The application that will be created is web-based using the PHP programming language with a MySQL database and utilizing tools in web programming, namely bootstrap, which is used to create a website page that supports all kinds of devices. The software development method used is the waterfall model which includes the stages of system/information engineering, analysis, design, implementation (coding), testing and maintenance.
Permodelan Air Terjun Pada Rancang Bangun Panduan Lalu Lintas Berbasis Android

This Android Mobile Based Traffic Guide Application is an application that can help make it easier for the public to get information about knowledge and understanding of traffic signs and criminal provisions in traffic, which can be used anywhere, anytime, and is more practical. Apart from providing the public with an understanding of traffic signs and related criminal provisions, the public can also reduce the rate of accidents that cause fatalities. This application runs on the Android platform using SQLite as a database. Users only need to see how to use the application to run it. In this application system process, the Unified Modeling Language (UML) diagram is used which refers to the waterfall model SDLC (System Development Life Cycle) system development life cycle. The results of everything that has been carried out will form an Android mobile application that will be used by all people who need it
ANALYSIS AND DESIGN OF THE BPK RI LIBRARY INFORMATION SYSTEM REPRESENTATIVE OF CENTRAL KALIMANTAN PROVINCE ANDROID BASED

Library staff record books and it takes a relatively long time and is less accurate. In addition, visitors have not been able to get the information provided by the library directly, be it announcement information, news about the library, agenda of events carried out in the library. Library's web can only be accessed by library employees. Using the PIECES analysis method, and tools using UML (Unified Modeling Language), as well as interface design using Figma and draw,io are used to describe data flow diagrams. Android which can be used by the office as a reference if you want to develop or implement it into a program. The results of this research has been presented to the office, where they have also provided feedback through filling out questionnaires. Overall, based on the results of the questionnaire analysis, it can be concluded that the design of an Android-based library obtains an interpretation value of 96% so that it can be concluded that the design has followed the needs of the user's system.
Penggunaan Mendeley Untuk Peningkatan Literasi Digital Mahasiswa Program Studi Pendidikan Bahasa Arab Uin Fatmawati Sukarno Bengkulu

Digital literacy is something that cannot be avoided in writing an article or scientific work. Digital literacy has begun to replace manual literacy which has been used by academics in writing scientific papers. Migration of manual literacy to digital literacy from year to year is absolutely necessary. One of the reference manager applications that can be used is Mendeley. The Mendeley application makes it easy for users to include digital references, but the Mendeley application tends to only support Latin writing, while for Arabic writing there are still some obstacles. Mendeley has an important role in writing the thesis because reference management can facilitate the academic community to quote citations and good reference management and can minimize the occurrence of plagiarism.
Database Development in Using and Maintaining Machine and its accessories at SMK Muhammadiyah Kartasura and Jatinom Klaten in Community service

The aim of the program was community service types of application of scienceand technology by Database Creation and Usage Machine Maintenance and itsEquipment at Muhammadiyah Kartasura and Jatinom Klaten as VocationalSchool to support the practicum process in the Muhammadiyah VocationalSchool laboratory. The implementation method was by synchronize basicinventory, then made a data base application by means of machine toolssticking with barcodes on a laboratory scale. With this activity, its willfacilitating the implementation of routines and practicum readiness from timeto time. Thus at the same time this will add value to the teaching and learningprocess at SMK which includes 40% theory and 60% practice manufacture.Through this activity it will also add value to their vocation which will bringthe world of education and industry much closer, especially in the field ofgoods assembling and manufacturing. From observations while working withpartners, namely SMK Muhammadiyah Kartasura and SMK MuhammadiyahJatinom Klaten, the obstacle faced is in coaching on the creation of a data basefor the use and maintenance or readiness of tools for practice. The process ofcreating a database of equipment, usage and conditions, this will support thecontinuity of the practicum process smoothly. The making of this database willbe transmitted and will become provision for students primarily forcompetence in the area of manufacturing work or for future entrepreneurship.So it is expected from this process, students and teachers get a new way oflearning, useful for students and the existence of the SMK in the future,particularly in learning assembly making and thinking steps to control theunderlying equipment. Thus the students have enough competence andadaptive when entering the world of work related to the process design basedon data collection and monitoring using technology growing of smartphones.
GIS Solutions for Monitoring Disasters and Their Impact on the Assessment of Land Resources

Summary GIS hardware and software can assist in assessing the condition and value of land based on various factors such as accessibility to infrastructure, soil fertility, etc. Currently, it is man-made and environmental disasters that have the greatest impact on the condition of the soil and the availability of infrastructure. In the paper, the authors investigate the methods of recording disasters using GIS technologies and the impact of disasters on the land resources evaluation. A sequence of steps has been developed, with the help of which various GIS programs (QGIS, ArcGIS Pro - Esri, Digitals, online GIS services) can be used to establish the impact of disasters on the condition of land resources. GIS functions (Databases, Data analysis, Machine learning, Modelling) allow to study how disasters affect investments and development. Demand and supply on the land market and its valuation depend on them. The possibility of using and integrating different types of input data was investigated, a combination of channels of multispectral satellite images and radiological data on the topography of the area. It is indicated which characteristics of the resources condition are more affected, for example fixation of the dam destruction, shallowing of the reservoir and fires. Man-made and environmental disasters, as well as the distance to the combat zone, are currently one of the main factors that affect the ecological condition and economic evaluation of land resources. GIS functions allow to record changes caused by disasters, to study trends, recovery options, use of objects and territories that have been affected. Indicators obtained with the help of GIS technologies are further used for ecological and economic assessment of land resources.
Data Analysis Using Generative AI: Opportunities and Challenges

The article examines topical issues of using generative artificial intelligence, in particular large language models ChatGPT and Claude, for data analysis. The essence of the term «artificial intelligence» changes over time. And if earlier, when using this term, was talked about expert systems, machine learning, etc., now this term means primarily large language models, among which the most famous are ChatGPT, Claude, Bing, Bard. These models allow you to generate texts, images, audio, and video based on user requests. The purpose of the article is to explore the opportunities and challenges of using ChatGPT and Claude in data analysis based on existing publications and our own experience. After all, the ability of large language models to communicate in natural language makes them a powerful analytics tool. The paper considers aspects of the main stages of data analysis in the context of the use of large language models: obtaining, collecting and loading input data, their pre-processing, application of mathematical models, visualization and interpretation of results. Practical recommendations for formulating requests to ChatGPT and Claude at each stage of data analysis are provided. It is noted that ChatGPT, thanks to the built-in Advanced Data Analysis service, allows an effectively analysis of data, powered by Python language. This provides higher accuracy of results compared to other large language models. Using a conditional example, a comparison of the capabilities of ChatGPT and Claude in data analysis is carried out. It is shown that ChatGPT allows you to build dependency models, generate graphs and give meaningful explanations of the results obtained. At the same time, Claude’s capabilities in data analysis are quite limited. It is concluded that ChatGPT has significantly greater potential for data analysis compared to Claude and other chatbots. However, so far, large language models cannot completely replace data analysts and powerful decision support systems. In further research, it is proposed to focus on the study of the practical application of the capabilities of ChatGPT and, in particular, its Advanced Data Analysis service to solve various data analysis problems.
DETEKSI DINI PENYAKIT JANTUNG KORONER DENGAN PEMERIKSAAN REKAM EKG (ELEKTROKARDIOGRAM) DI RT 04 RW 01 LORONG SIANJUR, KELURAHAN 5 ILIR, KECAMATAN ILIR TIMUR II KOTA PALEMBANG

Coronary Heart Disease (CHD) or cardiovascular disease is currently one of the main and first causes of death in developed and developing countries, including Indonesia. By 2010, globally this disease will be the leading cause of death in developing countries, replacing deaths from infection. It is estimated that worldwide, CHD in 2020 will be the most common first killer, accounting for 36% of all deaths, this figure is twice as high as the death rate from cancer. In Indonesia, it is reported that CHD (which is grouped into diseases of the circulatory system) is the main and first cause of all deaths, which is 26.4%, this figure is four times higher than the death rate caused by cancer (6%). In other words, approximately one in four people who die in Indonesia is due to CHD. Various risk factors have an important role in the emergence of CHD, ranging from aspects of metabolism, hemostasis, immunology, infection, and many other interrelated factors. Coronary heart disease is a condition due to narrowing, blockage or abnormalities of the coronary arteries. Coronary heart disease is caused by narrowing or blockage of coronary arteries. This narrowing or blockage can stop blood flow to the heart muscle which is often characterized by pain (Yenrina, Krisnatuti, 1999). Coronary heart disease is heart disease due to abnormalities in the coronary vessels, namely the arteries that deliver blood to the aorta to the tissue that protects the heart cavities (Kartohoesodo, 1982). Coronary heart disease (CHD) is currently one of the main causes of death in developed and developing countries (Ministry of Health, 2006). Combined data from Clientman et al and GUSTO-I showed that the mortality rate in the first 30 days of hospitalization for patients with AMI was 52% before admission, 19% within 24 hours of hospitalization, 8% during 48 hours of hospitalization, and 21% after 30 days. . Globally, of the 55 million deaths in a year, 30% are caused by cardiovascular disease, of which almost 50% are due to AMI attacks (Yusuf, S et al 2001). (USU.ac.id)
IbM PADA ANAK SEKOLAH DASAR DENGAN STATUS GIZI KURANG

Breakfast or breakfast provides an important meaning for everyone to start the activity throughout the day. This activity is carried out until nine in the morning. Breakfast should be able to meet 15% to 30% of the total daily nutritional needs. Breakfast is expected to be able to realize a healthy, active and intelligent life (Hardinsyah, 2013). School-age children require good and sufficient intake of nutrients for activities, especially during breakfast (Susyani et al., 2014). In addition to adequate and balanced nutritional content, menu choices must be practical and varied from various types of food ingredients (Ministry of Health, 2013). Breakfast is beneficial for good school attendance, nutrient intake, academic achievement, fitness and a healthy weight (Hardinsyah; Perdana, 2013). Meanwhile, the impact of not eating breakfast on children has been shown to have an effect on academic achievement at school (Muchtar et al., 2011). There are various reasons why children skip breakfast, namely, long distance to school, late getting up in the morning, not in taste, not used to or afraid of being late for school (Mardiana, et al, 2013; Irianto in Ristiana, 2009). The habit of not eating breakfast results in a decrease in blood sugar levels (hypoglycemia) so that the energy supply decreases, if this happens continuously it causes the body to tremble, get tired quickly and decrease motivation to learn (Wardoyo; Mahmudiono, 2013). According to Hardinsyah (2012) in Briawan, et al (2013), it is recorded that 20%-40% of Indonesian children do not eat breakfast every day. Hardinsyah and Aries (2012), stated that 44.6% of school-age children consume low-quality breakfast, which is below 15% of the daily nutritional adequacy. Lack of knowledge about the importance of eating breakfast in children is one of the factors that cause children to ignore breakfast (Notoatmodjo, 2012). Nutrition education needs to be given in order to achieve health behavior (Healthy Behavior). Based on the above background, it is necessary to provide counseling and examples of providing breakfast for school children.
ICAR-IIOR sunflower: an android mobile app for knowledge dissemination

India has become the fastest growing mobile market in recent years. In India, there are enormous opportunities for utilizing the smart phones as a part of agribusiness improvement. Usage of smart phones is exponentially increasing in rural areas hence, providing information to large number of farmers. In this context ICAR-IIOR-SUNFLOWER, mobile app was developed by ICAR-IIOR to provide entire package of practices required for sunflower cultivation. The App supports English language and available on Google play store. Features include offline and online mode and offer valuable information to the extension workers, farmers, sunflower researchers and other stakeholders.
SQL Optimization in Oracle using Hybrid Genetic and Ant Colony Algorithm

In this paper, the input user Structured Query Language (SQL) query is converted into an optimized SQL query using a hybrid algorithm. The main aim is to reduce query execution time using PHP language and oracle database. These performance has been evaluated using different performance metrics: Cost of individuals, Query execution time. The hybrid algorithm method combines the evolutionary effect of the Genetic Algorithm (GA) and the cooperative effect of Ant Colony Optimization (ACO). A GA with a great global converging rate aims to produce an initial optimum for allocating initial pheromones of ACO. An ACO with great parallelism and effective feedback is then served to obtain the optimal solution. A fused algorithm of a GA and ACO to solve SQL optimization problems is an innovative solution that presents a clear methodological contribution to the optimization algorithm. In the simulation result, we found the algorithm of a GA and ACO to solve SQL optimization problems in Oracle. It is an innovative solution that presents a clear methodological contribution to the optimization algorithm.
Offensive Text Classification based on Ernie??s Dual Channel Composite Model

With the widespread popularity of the Internet, offensive text information in cyberspace has attracted widespread attention from society. Currently, offensive text recognition mainly relies on pre constructed sensitive words for recognition, which cannot effectively intercept text without obvious offensive words. This article proposes a dual channel composite model based on the Ernie pre training model. First, the Ernie pre training model is used to construct a dynamic word vector, and more efficient text semantic information is obtained through its internal multi-layer and bidirectional Transformer structure. Then, a dual channel model is added to further refine text information. Bi-GRU is used to extract global semantics and TextCNN is used to extract local information, extracting semantic information features at different abstract levels. The experimental results show that when tested on the Chinese offensive language dataset COLDataset, the accuracy and F1 value of the model are significantly better than the baseline model COLDetector, reaching 83.81% and 82.90%, respectively. This verifies that adding a dual channel fusion network to the Ernie pre trained model can more effectively extract text features and improve the classification performance of the model.