Reviewerly/exHarmony huggingface dataset:
The Role of Cloud Computing in Transforming ICT Infrastructure in Educational Institutions

The integration of cloud computing into the Information and Communication Technology (ICT) infrastructure of educational institutions is a transformative paradigm that holds significant implications for the efficiency and efficacy of academic processes. This paper explores the role of cloud computing in reshaping ICT infrastructure within educational settings. A comprehensive literature review establishes the current landscape of ICT in education, identifying challenges and limitations. The study delves into the theoretical foundations of cloud computing and investigates its potential benefits, including improved accessibility, scalability, and cost-effectiveness. Empirical evidence and case studies are presented to illustrate the transformative impact of cloud computing on educational ICT infrastructure. The discussion encompasses challenges and considerations, including data security and privacy concerns, and offers insights into the future directions of cloud computing in education. This research contributes to the ongoing dialogue surrounding technology in education and provides practical recommendations for harnessing the full potential of cloud computing.
Evaluation of Passive Fire Protection Systems for Library and Service Buildings Archives of Indragiri Hulu Regency

The purpose of this research is to determine the evaluation of the protection system passive in fire prevention efforts in official buildings Library and Archives of Indragiri Hulu Regency, Riau Province. Data collection was carried out by observation, document review and interviews regarding passive fire protection systems in Service Buildings Library and Archives of Indragiri Hulu Regency, Riau Province. The results of this research are to show that the building has a passive fire protection system with assessment standards and the results of the conformity assessment against applicable standards, namely the Service Building Libraries and Archives have a score of 67.39%.
Development of Google Sites Web-Based Multimedia Learning in the Arts and Culture Subject for Class X TKJ 2 UPT SMK Negeri 2 Sidenreng Rappang

This advancement investigate points to create a item within the shape of Google Destinations Web Learning Mixed media for the Expressions and Culture subject lesson X TKJ 2 UPT SMK Negeri 2 Sidenreng Rappang. The investigate strategy utilized is the Investigate and Advancement (R&amp;D) improvement show with the 4D advancement demonstrate which has been created by Thiagarajan, Semmel and Semmel (1974) which incorporates four stages, to be specific: Characterize which incorporates the beginning last investigation steps, understudy Investigation , concept investigation, and detailing of learning targets; Plan or arranging which incorporates the steps of planning tests, selecting media, selecting instructing fabric groups, and making starting plans; Create or improvement which incorporates item improvement steps, master evaluation, improvement trials, and item modifications. Information collection strategies utilize perception, interviews, surveys and tests which are at that point analyzed quantitatively distinctly; Spread or spread which incorporates the steps of disseminating media. The appraisal comes about appear that the advancement of Google Destinations Web Learning mixed media is evaluated as exceptionally substantial and exceptionally viable. These comes about were gotten from media and fabric master approval, instructor reactions, and reactions from course X TKJ 2 UPT SMK Negeri 2 Sidrap students.
In Pursuit for Legitimacy: An Overview of Contemporary Policing In Indonesia

The Indonesian National Police (Polri) is currently placing a fair amount of concern on the state of its police legitimacy. However, numerous evidence of public response to date indicated some problems that threaten the legitimacy of Polri and might affect their performance. Following the public response, Polri launched several significant alterations to its policing methods. Hence, several critics questioned the effectiveness of Polri’s current method. This study will examine the pros and cons of the new policing scheme taken by Polri based on literature review of previous studies. Some suggestions as an alternative method are also provided in this study to improve Polri’s approach. Implications of these findings for police practitioners and researchers are then discussed.
Digital Language Learning in Higher Education: A Critical Literature Review on Teachers' and Students' Challenges

Higher education is using DLL more. Both teachers and students are used to digital learning. We have several digital learning examples. Teacher and student struggles with digital learning, such as using it, persist. This study reviews five-year-old references on digital learning in higher education. The researchers reviewed the literature on digital learning issues in higher education to determine what lecturers and students encounter in teaching and learning. The results suggest that teachers and students encounter issues including readiness to use them. Teachers and students struggle with technology access in different places, thus they should be discussed.
Assessing the Impact of Mobile Applications on Student Engagement in ICT and Computer Science Education

This paper investigates the impact of mobile applications on student engagement in the realms of Information and Communication Technology (ICT) and Computer Science Education. As the integration of mobile applications in educational settings becomes increasingly prevalent, understanding their influence on student engagement is crucial for optimizing learning experiences. The study employs a [mention research design] to assess the effectiveness of selected mobile applications aligned with the curriculum. Data analysis involves [mention specific methods], focusing on measuring and evaluating student engagement levels. The results reveal [highlight key findings], shedding light on the implications for enhancing ICT and computer science education. This research contributes to the existing literature by addressing gaps and providing insights into the practical use of mobile applications in educational settings.
Benefits and Challenges of Mobile-Learning Brought to Student Learning Outcomes in Higher Education: A Systematic Review from 2014-2023

The development of technology has brought new development opportunities to education, in other words, mobile and remote learning have become an indispensable part of various schools. In addition, the impact of mobile and remote learning on students has attracted attention from all sectors of society. Mobile learning has been utilized in the process of teaching and learning in higher education, leading to various impacts on student learning outcomes. Many researchers have conducted empirical studies to explore how mobile learning impact student outcome in higher education institutions. To facilitate the use and design of mobile learning and improve teaching and learning in the digital age, there is a urgent need to review existing literature and identify benefits and challenges that ML lead to student learning outcomes. This study uses systematic literature review (SLR) to analyse 355 articles from Scopus and wos. Mobile learning bring benefit as follows: Providing Flexibility and Accessibility; Improving learning effectiveness;Developing internal motivation and positive attitude; Enhancing student engagement. On the other hand, mobile learning cause several challenges: current functions failed to complete leaning and teaching outcomes; Distracting user from knowledge learning; leading to vision impairment. I suggest further researcher to identify how ML influence teachers and teaching process.
Augmented Reality in 4D Flashcard: The Effects in Teaching Speaking Skill

The use of augmented reality of 4D flashcard is one of the media that supports teaching English, especially in speaking skills, it can also increase students' confidence and interest in learning. The purpose of this study was to determine whether the use of augmented reality in 4D flashcard can improve students ' speaking skills. This study used a pre-experimental method with one group pre-test and post-test design. The sample of this study was Class XI MIPA 3 consisting of 34 people with classroom random sampling techniques. This research instrument was a test of speaking skills. The results of this study showed that there was an increase in the students’ average score. The pre-test score of students (55.37) is greater than the post-test (71.03). In the significance level p (5%) and T-test value of 2.03 is greater than T-table 16.46 (2.03 ° 16.46). Thus, it can be concluded that the use of augmented reality of 4D flashcard students were able to improve students’ speaking skills. So, the null hypothesis (H0) is rejected, and the alternative hypothesis (Ha) is accepted.
The Stoic Distinction between Syllogisms and Subsyllogisms

Abstract This paper aims to explain the distinction between syllogisms and subsyllogisms in Stoic logic. Subsyllogisms replace at least one premise in a syllogism with a premise that is, according to Galen and Alexander, equipollent to the respective syllogistic premise. This equipollence is not synonymy of meaning between two linguistic expressions, but obtains between two propositions when they are true or false by the same standard. Subsyllogistic premises are simple propositions that are equipollent to the non-simple premises of the respective syllogisms. For subsyllogistic premises that replace syllogistic premises consist of predicates combining with cases rather than of connectives or negations governing propositions. Because of this difference in their premises, subsyllogisms have a different logical form than syllogisms and are not formally valid.
Teaching Model Development of English Speaking Skill Using Story Telling in Junior High School

The research aim is to describe the problem of speaking ability in junior high school needs to be done to observe the development of students'' learning difficulties in current speaking skills.The type of research is a class action research descriptive quantitative. The population of this research is class VIII teacher at Junior High School state three Binjai. Based on the results of the pre-test, the pre-test mean score was 66,26 and the mean score in the post-test was 86,93. It can be seen that the students'' skill in speaking by using storytelling technique increased. From these calculations, it can be inferred that there was a difference of students'' scores before and after receiving the treatment. The affect storytelling used single story telling is from score minimum pre-test 30 to score post test is 82 and score maximal pre-test 65 and post-test is 82 it is mean the research is succeed and have affect to speaking skill. The improving from the research is when using the single story telling model, the results obtained increased by approx. 49%. Based on the data analysis, the researcher found that storytelling technique can improve students’ skill in speaking. As the result from the pre-test and post-test mean scores which were given. The improvement of mean score was 66,26 to 86,93.It means that there is significant difference of achievement between the students who were taught by using storytelling technique and the students who were taught without storytelling technique. The data also showed that students felt that storytelling technique could help them in speaking. Most of them also responded that they attempt to use storytelling technique in their daily speaking.
Sliders Provide Added Value

A move to sliding-head turning has proven to be a game-changer at Nuneaton-based subcontractor Oaston Engineering
Implementasi Sistem Monitoring Alat Pengering Biji Kopi Berbasis IoT (Internet of Things)

Indonesia holds the third position in global coffee bean supply, with a 3.3% increase in demand in 2021 according to ICO data. In line with ICO Resolution 407, coffee bean quality must be high, indicated by a 12.5% moisture content through drying processes. Mechanical drying is faster than traditional methods, thus becoming the focus of this research. This study implements an IoT-based monitoring system for coffee bean drying equipment. The aim is to create and implement a monitoring system for temperature (0°C - 70°C) and electrical energy consumption (kWh) in coffee bean drying, displayed on the ThingSpeak dashboard. Test results show that the temperature monitoring system using DHT22 sensors at the inlet and outlet of the rotary dryer tube has an average error of 2.1%. The energy monitoring system using PZEM-004T has a 0% energy measurement error. These results indicate a reliable monitoring system that enables remote monitoring via the internet. Furthermore, the study tests manual (on/off) and fuzzy logic control methods to achieve 12% moisture content in coffee beans. The fuzzy logic control method demonstrates better temperature stability and 11.2% cost savings in operational expenses. This research benefits coffee farmers by facilitating efficient monitoring of the bean drying process, and recommends the use of the fuzzy logic control method for stable temperature and lower operational costs.
Implementation Of Death Crime Executions for Class I Narcotics Distributors

The enactment of Law Number 35 of 2009 concerning Narcotics, types of Psychotropics class I and class II as stated in the attachment to Law Number 5 of 1997 concerning Psychotropics have been moved to Narcotics class I in Law Number 35 of 2009 concerning Narcotics and the attachment regarding types of Psychotropics class I and class II in Law Number 5 of 1997 concerning Psychotropic Substances are revoked and declared invalid. With this figure, the level of narcotics use in Indonesia is the largest in Asia. Indonesia is considered a drug emergency, the process of executing the death penalty does not have a deterrent effect on drug dealers or smugglers. The problem is, how to carry out the execution of the death penalty for class I narcotics dealers and what are the obstacles to not immediately carrying out the death penalty for class I narcotics dealers. The research method used is Empirical Normative Legal Research. In conclusion: The death penalty imposed by a court in a general court or military court environment is carried out by being shot to death. This provision does not reduce existing provisions in the criminal procedural law regarding carrying out court decisions. Based on Law No. 35 of 2009 concerning Narcotics. And the factors that cause obstacles in the implementation of the death penalty include legislative factors (legal substance), law enforcement factors, means and facilities factors, and community factors.
Emergency sign language recognition from variant of convolutional neural network (CNN) and long short term memory (LSTM) models

Sign language is the primary communication tool used by the deaf community and people with speaking difficulties, especially during emergencies. Numerous deep learning models have been proposed to solve the sign language recognition problem. Recently. Bidirectional LSTM (BLSTM) has been proposed and used in replacement of Long Short-Term Memory (LSTM) as it may improve learning long-team dependencies as well as increase the accuracy of the model. However, there needs to be more comparison for the performance of LSTM and BLSTM in LRCN model architecture in sign language interpretation applications. Therefore, this study focused on the dense analysis of the LRCN model, including 1) training the CNN from scratch and 2) modeling with pre-trained CNN, VGG-19, and ResNet50. Other than that, the ConvLSTM model, a special variant of LSTM designed for video input, has also been modeled and compared with the LRCN in representing emergency sign language recognition. Within LRCN variants, the performance of a small CNN network was compared with pre-trained VGG-19 and ResNet50V2. A dataset of emergency Indian Sign Language with eight classes is used to train the models. The model with the best performance is the VGG-19 + LSTM model, with a testing accuracy of 96.39%. Small LRCN networks, which are 5 CNN subunits + LSTM and 4 CNN subunits + BLSTM, have 95.18% testing accuracy. This performance is on par with our best-proposed model, VGG + LSTM. By incorporating bidirectional LSTM (BLSTM) into deep learning models, the ability to understand long-term dependencies can be improved. This can enhance accuracy in reading sign language, leading to more effective communication during emergencies.
The application of business intelligence system based on big data in e-commerce data analysis

In the face of the rapid development of modern science and technology, in order to ensure that the commercial level is in line with The Times, we need to change the traditional operation mode, and fully apply the science and technology to the e-commerce data analysis. Nowadays, driven by the era of big data development, social process, bring new changes to daily life, consumption, such as electricity is a new product, as the latest business model in modern society, has an important impact on market development, want to ensure electricity enterprises can meet the demand of social development, then from the perspective of electricity data analysis, effectively grasp the market changes, so as to more effective to carry out subsequent work, to fundamentally improve the comprehensive competitiveness of electricity enterprises in the modern market. In view of this, in order that the article wants to ensure the smooth progress of the e-commerce data analysis work, it should start with the business intelligence system under the background of big data, and combine it to ensure the steady development of the e-commerce industry.
The Optimized Deployment of Service Function Chain Based on Reinforcement Learning

With the rapid development and application of technologies such as artificial intelligence, the Internet of Things, and cloud computing, data is showing explosive growth. In order to address the rising energy consumption due to the increasing number of devices in the traditional network architecture, software-defined networking and network function virtualization have been proposed. In this paper, we propose a reinforcement learning model based on actor-critic architecture. The service function chain deployment problem is mathematically modeled, and minimizing the total service function chain delay is taken as the optimization objective. The experimental results demonstrate that the service function chain deployment algorithm proposed in this paper is improved in terms of total system latency.
An Analysis of the Mean Chart Under OC Function for Correlated Data

In this paper, we determine and illustrate the effects of correlation between the observations on the operating characteristics curve, Type-I error and Average Run length. In addition, for different correlated coefficient the control limits have been developed. To study the effect of correlated observations the OC curves, Type-I error, ARL and factor A have been worked out using various equation and values are given in Tables 1 to 4. To give a visual comparison of OC function and ARL, curves have been drawn in Figures 1 to 6. It is found that correlation between observations seriously affected the OC, Type-I error, ARL and factor A for the mean chart when standards are known. When the center line and control limits are based on the large value. Thus, it will be healthy contribution in manufacturing process which tracks important product characteristics in industry.
Research on the Development of a Conceptual Framework for Core Values in National Curriculum through Future Society Prediction

This study aims to address the importance of core value education required in the curriculum according to the changing times, and to explore and develop a core value concept word system for the curriculum at the national level curriculum. As a research method, first, the core value concept words used in the 2022 revised curriculum documents were frequency analyzed to derive important core value concept words. Then, we analyzed the headlines of the hexagonal promotion tasks in the main work report documents of each government department using frequency analysis and topic modeling techniques to identify trends, and generated scenarios for predicting the future society using ChatGPT and finally classified them according to STEEP. The future society prediction scenarios classified by STEEP were matched with the core value concept words in the 2022 revised curriculum document and presented systematically in terms of society and individuals. As a result of the study, 30 core value concept words including “respect” were derived from the 2022 revised curriculum, and “industry, expansion, and promotion” were important in the headlines of the key initiatives of each government ministry's major work report. Words such as “education, culture, and marine,” which represent the characteristics of the government's major work report but also the characteristics of each ministry, were also included in the high frequency range, confirming that it can be meaningful to derive future scenario topics from the headlines of the key initiatives of the government's major work report. There were 10 future society prediction scenarios generated using ChatGPT, and after classifying them according to STEEP, we developed a core value concept word system consisting of a total of 30 words divided into society and individual aspects. The core value conceptual language system will contribute to the activation and systematization of core value education in elementary and secondary schools, and will be the basis for connecting with liberal arts education at the university level.
Intelligent Trajectory for Mobile Element in WSNs with Obstacle Avoidance

In wireless sensor networks (WSNs), mobile sink-driven data acquisition can mitigate hotspot issues, which further increases WSN efficiency, such as throughput, lifetime, and energy efficiency, while reducing delay and packet loss. Recently, most mobile sink algorithms have focused on efficient paths, and few consider obstacles in the network environment. Nevertheless, constructing an obstacle-aware trajectory in a WSN is challenging. In this context, this paper proposes a bug algorithm based on an obstacle-aware intelligent trajectory (CSOBUG) for a mobile sink to acquire data from sensor nodes in WSNs efficiently with the help of cat swarm optimization (CSO). The proposed CSOBUG algorithm has two phases: selecting visiting points and constructing a trajectory. A CSO-based clustering approach is used to select visiting points, and a bug algorithm is used to select a trajectory. Comparing CSOBUG with existing techniques, it is found that CSOBUG is less computationally intensive than the existing techniques. As well as outperforming traditional methods based on multiple performance metrics, the CSOBUG achieves superior results in a variety of scenarios.