Reviewerly/exHarmony huggingface dataset:
Performance Analysis of Solar Panels in Tropical Region: A Study Case in Surakarta Indonesia

The performance of solar panels affects the utilization of solar energy for daily life. This study aims to carry out the measurement of the performance of solar panels in Surakarta City is located between 110 ° 45 '15" and 110 ° 45" 35" East Longitude and between 7 ° 36" and 7 ° 56" South Latitude. Research used solar panels, current sensors, voltage sensors, temperature sensors, solar irradiance sensors, humidity sensors, Arduino and Labview. The solar panels 20 WP is used in the experiment. The measurement results obtained that the maximum energy value per day produced is 165 Wh and a minimum of 76.8 Wh with an average of 109.1 Wh. Temperature measurements were carried out in the range 37.2 0 C to 41.0 0C which is the normal temperature for PV operations. The average irradiation measurement is 1834.3 W/m2 while the average humidity is 32.5%. The relationship between energy and temperature, energy with solar irradiance and energy with humidity find using Pearson Product Moment Correlation (PPMC). The result show that the effect of temperature and solar irradiance were more significant than humidity.
Opini Masyarakat Twitter terhadap Kandidat Bakal Calon Presiden Republik Indonesia Tahun 2024

Registration for the 2024 presidential candidates began at the end of 2023, but the euphoria of the supporters of the 2024 presidential candidates began to be felt from the beginning of 2022. Several survey institutions released public opinions regarding several prospective 2024 presidential candidates. One of the approaches taken in the survey was by conducting direct interviews with the public. However, political dynamics can change the results of political surveys at great expense. Public opinion about the 2024 presidential candidates cannot only be acquired through direct interviews. Public opinion acquisition can also be done through social media such as Twitter. This article aims to find out public opinion on the candidates for the 2024 presidential candidate on Twitter social media. This article uses a Twitter dataset and data analysis tools using orange data mining. The crawling dataset was carried out using the hashtags #capres2024 and #presiden2024 and the keywords anies baswedan, prabowo subianto and ganjar pranowo with 10,000 tweet data in content written in Indonesian. Text preprocessing includes transformation, tokenization, filtering and normalization applied to data before analysis is carried out with topic modeling and sentiment towards the presidential candidates. The results of the word cloud analysis show a very high level of popularity for candidate Ganjar Pranowo, but the results of the sentiment analysis show that Ganjar Pranowo has a negative sentiment.
Flood Risk Mapping Using GIS and Multi-Criteria Analysis at Nanga Pinoh West Kalimantan Area

Flood is one of the disasters that often hit various regions in Indonesia, specifically in West Kalimantan. The floods in Nanga Pinoh District, Melawi Regency, submerged 18 villages and thousands of houses. Therefore, this study aimed to map flood risk areas in Nanga Pinoh and their environmental impact. Secondary data on the slope, total rainfall, flow density, soil type, and land cover analyzed with the multi-criteria GIS analysis were used. The results showed that the location had low, medium, and high risks. It was found that areas with high, prone, medium, and low risk class are 1,515.95 ha, 30,194.92 ha, 21,953.80 ha, and 3.14 ha, respectively. These findings implied that the GIS approach and multi-criteria analysis are effective tools for flood risk maps and helpful in anticipating greater losses and mitigating the disasters.
A Stateful Multi-Context Aware Design Using OpenAI's GPT (Towards Digital Sentience)

Natural language processing has come a long way since it was first conceived, and projects like OpenAI's GPT have created a lot of renewed interest in the technology. While these kinds of systems are great at creating short pieces of information based on a prompt, they have severe limitations, and come nowhere close to general intelligence or digital sentience. Still, OpenAI's system allows for the integration of robust prompt completion in third party applications. Using their API, it may be possible to add layers of functionality that create a system that can keep track of information from multiple contexts and continuously process it in a way which at least mirrors consciousness. To determine how successful this system is, existing tests from psychology, such as the NEO PI-R and the MMPI-2 can be utilized. This paper outlines the overall process to accomplish this task.
Integrating Technology into Education: Students' Attitudes toward Online Learning

The increasing spread of the COVID-19 encouraged learning systems to switch from traditional to online learning. It has brought significant problems and difficulties for students. The swift shift to fully online learning demands some adaptation. Students must learn to adapt their abilities because of the increasing use of technology in education. This study explored students' attitudes towards online learning and the reasons for their attitudes. A survey of 191 students from four State Islamic universities in Aceh was conducted online. A descriptive research framework was chosen, and a survey approach was used to collect data to gain knowledge of the situation and answer research questions. Students showed a positive attitude and satisfaction toward online learning during Covid-19. Even they realized how to handle technological tools applied during teaching and learning. Integrating technology into education does not challenge students as technical support and facilitates education to be easier. Keeping up with technology and infrastructural upgrades is vital to support online learning. The recent study has certain limitations. The small number of participants leads to incomplete data. Therefore, it is necessary to include more people to examine education in general.
Parallel DBSCAN Clustering Algorithm Using Hadoop Map-reduce Framework for Spatial Data

Data clustering is the first step for future applications of big data analysis. It is a driving model for Artificial Intelligence and Machine Learning architectures. Processing large volumes of data in faster mode is a big challenge in these applications. which requires fast and efficient algorithms for handling big data. Parallel clustering algorithms are one promising design, which increases the speed of handling such big data. In this paper, a parallel algorithm for clustering a spatial dataset called the P-DBSCAN algorithm is implemented using Hadoop map-reduce framework. This research paper signifies the improvement for data clustering in data analytic applications. The new P-DBSCAN algorithm is executed over generated dataset. The result of this parallel algorithm is compared with existing DBSCAN algorithm to show improvement of runtime performance. This work offers an increase in the performance of execution time. In addition, the outcome of P-DBSCAN shows how to resolve the scalability problem of a large data set.
Development of Interactive Media Based on Augmented Reality for Early Childhood Learning Around the Home

In this age of digitization, it is essential to develop interactive media that may serve as a vehicle for learning while also engaging children. Thus, learning media that includes both real and digital media can be made more exciting and less tedious by making it more fun while still valuing traditional and interactive learning utilizing technology, which is why this is important. This project aims to generate media solutions that early childhood educators and kindergarten teachers can use to assist them in learning and teaching. The media that was created includes Android apps that use Augmented Reality. (AR), technology to make the experience more fun for kids and book media based on the kindergarten curriculum. Subsequently, parents and caregivers can use this media to teach their children about the living room, toilet, and other places based on the images that have been shown. When an Android app scans this picture, it will illustrate animated 3D objects through Augmented Reality. Notwithstanding, the Android app has a free picture coloring option. Equally, it must be supervised by parents or teachers, a practice known as digital parenting. The development and verification results confirm that this medium is suitable for implementation and use in schools and kindergartens.
Factors Affecting the Criminal Behavior among Pakistani Youth: A Case Study of Punjab Province Pakistan

Crime is one of the major problems in Pakistan. Increased incidences of crime across the country are becoming a matter of great concern. It is popular to associate criminal behavior with the poor physical, psychological, social, and economic conditions of the impoverished segment of the population. Poverty, unemployment, and corruption are Pakistan's most significant drivers of youth crimes. Keeping in view all these facts, the main objective of this study was to investigate the factors affecting youth criminal behavior in Punjab, Pakistan. In this research quantitative research approach was used. Primary data was collected through field surveys. A multistage random sampling technique was used for data collection. In the first stage, two districts were selected randomly from central Punjab. In the second stage, district jail Faisalabad and district jail Pakpattan were selected purposively. In the third stage, a sample size of 300 respondents was chosen purposively. A questionnaire was designed as a data collection tool, and collected data were analyzed by using SPSS 25 version. The study's findings indicated that most of the respondents who were involved in crimes were married and between 21 to 25 years old. Univariate analysis revealed that poverty, unemployment, poor socialization, and peer pressure were major causes of crime among youth. Bivariate analysis showed that excessive social media usage and youth unemployment contributed to criminal behavior. So, the present study suggested that Governments and non-governmental organizations (NGOs) should collaborate to enhance awareness and youth empowerment to guarantee that individuals have the necessary skills and training to participate in the labor market and become productive members of society.
Conscious rereading is confirmatory: Evidence from bidirectional self-paced reading

Rereading during sentence processing can be confirmatory, in which case it serves to increase readers' certainty in their current interpretation, or it can be revisionary, in which case it serves to correct a misinterpretation (Christianson, Luke, Hussey, &amp;amp; Wochna, 2017). The distinction is particularly relevant in garden-path sentences, which have been argued to trigger revisionary rereading (Frazier &amp;amp; Rayner, 1982). In two web-based experiments that compare garden-path sentences with other linguistic constructions, we investigate deliberate rereading in the recently-proposed bidirectional self-paced reading (BSPR) paradigm (Paape &amp;amp; Vasishth, 2022). Our results show evidence for selective rereading only in very difficult garden-path sentences. Additionally, our results suggest that conscious, selective rereading is confirmatory: Readers find garden-path sentences less rather than more acceptable after selective rereading, suggesting that they reread either to confirm their initial analysis or to confirm the perceived ungrammaticality of the sentence. We discuss the role of conscious awareness in dealing with different types of linguistic inconsistency.
Ensemble CNN Attention-Based BiLSTM Deep Learning Architecture for Multivariate Cloud Workload Prediction

Cloud computing has drastically changed the nature of computing in recent years. However, despite its countless benefits, it also suffers from some major challenges including autoscaling of resources and high energy consumption resulting inefficient and costly cloud systems. Among these challenges, the auto-scaling of resources has received significant research attention. However, most of the works on auto-scaling utilize the reactive approach on workload fluctuations. Therefore, we develop a deep learning based prediction architecture applying ensemble of attention mechanism (AM) with bi-directional long short-term memory (BiLSTM) and convolution neural network (CNN). Through experimental evaluation using real-time cloud workload traces, the proposed framework reduces RMSE by 8.93% and reduces MAE by 11.43% compared to the existing prediction models.
Government Failures in The Implementation of Effective Contracts

The paper examines the results of reforms in the remuneration system of university lecturers. Two stages of the transformation process have been considered: the transition to the new remuneration system in 2008 and the introduction of effective contracts in 2012. The paper explains how the political and bureaucratic mechanisms of the formation of the remuneration system have changed. We have made an attempt to describe the government failures in the implementation of effective contracts. It is assumed that the new mechanism remains over-regulated and is based on the idea of the local nature of the academic labor market. The imitation regulation is considered to be one of the most important reasons of the state failures. On the one hand, the government manifested the establishment of understandable and achievable indicators, on the other hand, the authorities failed to solve real problems of the production and transfer of the new knowledge. Governmental stakeholders in education are interested in maintaining and further expanding of their functions. Meanwhile, insufficient professionalism in decision-making and short-termism become the reasons for inefficient waste of budgetary resources for the indicators production and elaboration of various of insurance procedures. The study shows that for many universities the achievement of the target salary level is associated with serious difficulties. There are also significant differences in remuneration systems between universities. Interregional differences in the level of wages of university staff create different conditions for investment in the human capital of university lecturers and incentives for interregional staff turnover that weakens the resource potential of universities in a number of regions.
Physico-Chemical Properties of Wetland Soils Affected by Crude Oil Spillage in Niger Delta Area, Nigeria

Loss of soil fertility through loss of soil organic matter, leaching of nutrients, loss of the nutrient-laden topsoil, changes in soil-pH, reduction in cation exchange capacity, salinization, water logging and other forms of soil degradation are major problems associated with agricultural productivity in the oil producing areas of Nigeria. This analysis investigated some selected physico-chemical properties of wetland soils affected by crude oil spillage in Bodo city in the Niger Delta region of Nigeria. Field reconnaissance survey using a handheld Geographic Positioning system (GPS) and survey technique involving random sampling, was used in siting soil profile pits. The unpolluted samples were collected 50 meters away from the polluted site but in the same geographic region and was used as control site. Soil samples were collected based on degree of horizon differentiation and analyzed using routine and special analytical techniques. Soil data were subjected to analysis of variance using Genstat program. Result shows that soil physical properties of the polluted site: moisture content, soil bulk density, and soil texture were highly significant (p=0.01 and 0.05) when compared to the unpolluted site while some chemical soil properties analysed especially soil pH, organic matter, carbon-nitrogen ratio, available phosphorus were affected by crude oil spillage. Results from this study affirm that crude oil can have detrimental effect on soil physico-chemical properties, which implies low soil fertility and thereby affect crop production and increase food insecurity within the study site. Further studies involving more edaphic properties, biotoxic metals and their bioaccessibility in crops growing on waterside affected by crude oil spill will surely enhance knowledge and management of the these highly industrially influenced soils. Also, international and national oil and gas companies should carry out their activities with international best practice.
Strengthening Gender Equality in Small Business and Achieving Sustainable Development Goals (SDGS): Comparative Analysis of Kenya and Nigeria

There is an increasing understanding that Sustainable Development Goals (SDGs) can protect the planet, reduce inequality and tackle poverty. However, many small business owners and entrepreneurs in Africa still see it as a misery. This study aims to determine whether the SDG's goal number five (5) is being used to motivate gender equality among small and medium-sized enterprises in Africa, particularly in Kenya and Nigeria. The study focuses on female entrepreneurs. The target population comprised 110 randomly selected businesses operating in Embakasi East constituency in the Embakasi ward in Nairobi County, Kenya, and Ikeja Local Government in Lagos Mainland of Lagos state Nigeria. The sample size was determined by relying on a prior study on women in business in Africa. The study adopted a qualitative research method, administering open-ended interviews to the respondents, and the response rate was 90.91%. Descriptive statistical analysis was adopted, and the examination of the data demonstrated that a significant number of women working in SMEs are unaware of the SDGs in the two countries despite the United Nations (UN) supporting gender equality. The research concludes that there is still a considerable difference between men and women in SMEs in Africa and the awareness of SDG goals is limited. It is recommended that the management of small businesses, regulators, and policymakers should increase the knowledge of the global goals for more awareness and sustainability adoption in African countries. This can also support sustainable business growth and close the inequality gap in small African businesses
Teaching English by Using Canva: Students’ and Lecturers’ Voice

This research discovers students’ and lecturers’ voice on using Canva in English language teaching. This research employed quantitative descriptive method with 31 English Foreign Language (EFL) students and 5 lecturers. The data are gained from 31 students and 5 lecturers of English Department at IAIN Fattahul Muluk Papua. The students’ and lecturers are given a set of questionnaires to obtain their response on using Canva. After gaining the data, the researcher analysed the students’ and lecturers’ response by counting its frequency and percentage. The findings of this research Indicated that the majority of students and lecturers have positive voice on using Canva in English language teaching based on three indicators that is provided by researcher, those are: usefulness, ease to use, and easy access. This research revealed that Canva is usefulness tool for English language teaching. Canva is also ease of use tool for English language teaching which easy to use, effective, improve teaching and learning process, and easy to distribute. At the end, Canva has easy access because Canva provides everything for teaching and learning process such as video, images, colourful. Besides, Canva becomes an interesting App, and good choice for learning and teaching process.
Perceptions of Postgraduates Majoring in English Education on Speaking Assessment Module for Online Distance Learning (ODL)

Assessment of speaking skills differs from other language skills. The methods of conducting speaking skills are included in the English Assessment Module developed by the researchers from the National University of Malaysia (UKM). The module is designed to cater postgraduates (adult learners) through Online Distance Learning (ODL) program. ODL has become essential in education setting for adult learners as they could manage their learning whilst juggling their career and personal commitments. The covid-19 pandemic has become the starting point for postgraduates to conduct the course remotely according to their preferences of learning. The revolution of education allows adult learners to pursue their Masters. The module includes various types of English language assessments in the context of speaking English as a Second Language (ESL). Hence, eight adult learners were interviewed to give their perceptions towards this newly designed module. This qualitative research method employed a set of semi-structured interview questions and open-ended questions via Google Meet. The findings showed that English Assessment Module; Speaking Assessment is well equipped with comprehensive information and guidelines on how the speaking assessments should be conducted in ESL context. Generally, the findings indicate that the English Assessment Module; Speaking Assessment is suitable for ODL postgraduates (adult learners). This paper also includes the participants’ suggestions to further improve the module. The findings could benefit the online distance course designers in designing better module for adult learners and enable the learners to learn effectively at their own convenience.
Optimal Site Selection Using Geographical Information System (GIS) Based Multi-criteria Decision Analysis (MCDA): A Case Study To Concentrated Solar Power Plants (CSP) In Brazil

Optimal site selection using multi-criteria decision analysis (MCDA) is an important step to support decision makers to locate places that benefit the maximum potential of technology's preconditions. As a new, emerging and renewable technology in Brazil, concentrated solar power (CSP) plays an important role in power generation mix, and it’s crucial to indicate the viability of Brazilian regions to CSP power plants. To achieve this goal, a detailed workflow of multi-criteria analysis based on geographic information system (GIS based AHP) is set in free software, in which criteria are selected from literature, acquired as geospatial data, weighted with parity matrices through online questionnaires filled by experts, processed on QGIS with weighted linear combination (WLC), and the results validated by its AHP consistency, thematic accuracy and comparative analysis with VIKOR and TOPSIS methodologies. As a product, sites are mapped according to viability indices, with higher values in most of Northeast, Central-west and Southeast regions of Brazil, showing good stability by its validation. Thereby, the workflow with free software allows the methodology to be replicated to support decision makers in locating viable and restrictive places for technologies.
Making Traffic a Thing of the Past

New AI technologies are making it possible to autonomously reduce traffic.