Reviewerly/exHarmony huggingface dataset:
Nowcasting of Weather Parameters Impacting Solar PV Output Using Grey System Model

Objectives: To nowcast the weather parameters having a direct impact on the power output of the solar PV installations, with high prediction accuracy and a limited quantity of past data.Methods: In this study, the GM (1,1) model with Fourier series of error residuals has been proposed and used for forecasting the weather parameters namely Ambient temperature, Solar Photo Voltaic Module temperature, and Solar Irradiation.Real-time data has been used for showing the suitability of the proposed model to nowcast the weather parameters.The existing models like Autoregression and Double Exponential Smoothing are applied to the same data to prove the superiority of the GM (1,1) model with Fourier series of error residuals.Findings: It is found that the GM (1,1) model with Fourier series of error residuals is an apt model for nowcasting the weather parameters.The accuracy of the predicted result of this model on the real-time data ascertains the appropriateness of this model for nowcasting.The precision of the prediction accuracy of GM (1,1) with the Fourier series of error residuals model is verified by comparing it with other time series prediction models such as Autoregression and Double Exponential Smoothing algorithms.Novelty: Using GM (1,1) with the Fourier series of error residuals model for nowcasting the weather data is novel when compared with the existing algorithms because for nowcasting the weather parameters with accuracy, many of the existing algorithms require a huge volume of past data and involve complex computation.On the other hand, GM (1,1) with the Fourier series of error residuals model requires only a limited measure of past data and involves simple computation.Moreover, the accuracy of prediction is significantly higher than the other models.
An Evaluative Review of Mobile-assisted L2 Vocabulary Learning Approaches based on the Situated Learning Theory

There is a growing trend of utilizing mobile technology to develop effective contextual vocabulary learning methods based on the situated learning theory (SLT). In spite of substantial research on mobile-assisted vocabulary learning (MAVL), there have been few reviews of MAVL approaches, let alone evaluations of them based on the idea of SLT. To address this research gap, this study evaluated three types of MAVL approaches: (1) mobile message services, (2) vocabulary learning applications, and (3) digital simulation games according to the authenticity principle and characteristics of SLT. The evaluative review included in-depth examinations of two aspects: the extent to which these characteristics are manifested in each approach, and the way in which these characteristics are incorporated into the design of each approach. The result suggests that the MAVL approaches differ significantly, in terms of their authenticity and degree of correspondence to the SLT. This review offers practical implications for the development and improvement of MAVL approaches, as well as important suggestions for future research, all of which are believed to benefit the field of L2 vocabulary acquisition.
COMPARING LEXICAL DENSITY IN TEACHER TALKS: ELEMENTARY SCHOOL AND HIGHER EDUCATION LEVEL

Teacher talk must be specific, clear, concise, and comprehensible for students as the target interlocutors. This study aimed to characterize lexical density in teacher talks of elementary school teachers and university lecturers during teaching. A qualitative descriptive technique was used involving lexico-grammar analysis from an SFL perspective. The subjects of this study were three elementary school teachers (6th-grade teachers) and three university lecturers (English lecturers) who were voluntarily recorded during their teaching time; once for each. Hence, the object of this study is the transcriptions of teacher talks from these six research subjects which were then analyzed using documentation techniques of data analysis namely selection, categorization, classification, identification, and verification. The results show that the lexical density used in elementary school teacher talk is 42.65% (low) and that one employed at the university level is 36.76% (low). Unexpectedly, the rate for elementary school is somewhat higher than that for the university level. This case appears to have an intervening aspect because the elementary school is an international school. It is learned that an educational institution—regardless of its level—with a distinct learning target would certainly influence the lexical density employed in the teachers’ spoken discourse during classes.
ReChain-A Blockchain Network for Review and Rating System

Review and rating is a very important movement for online purchases and also it's an overview of a company's service. The most popular online platform provides a section called reviews and ratings. In this research, a blockchain based technology has been proposed that is fully decentralized but can be implemented inside a centralized system. It has been noticed for a long time that because of the company's image, some people are using it negatively, and fake or paid reviews are very common among them. There are many flaws in conventional systems for review and rating. After finding the flaws, a totally new blockchain network is designed to overcome them. This is a consortium blockchain network that contains hybrid blockchain features. In this proposed model, complexity has been reduced, and it is going to be cost-efficient as well because this decentralized system can be used in any centralized system.
Internet of Things Security Based on Big Data and Deep Learning

As 5G is deployed and applied, a large number of mobile devices have been increasingly deployed on the network. Scenarios such as smartphones, smart car, smart transportation, smart wearable devices, and smart industry are increasingly demanding for networks. And the Internet of Things (IoT), as a new and high technology, will play an important role and generate huge economic benefits. However, IoT security also faces many challenges due to the inherent security vulnerabilities in multiple device interactions and the data also needs more accurate processing. Big data and deep learning have been gradually applied in various industries. Therefore, we have summarized and analyzed the use of big data and deep learning technology to solve the hidden dangers of the IoT security under the consideration of some suggestions and thinking for industry applications.
Playing the Online Games Becomes One of Affecting Factors to Generate the Second Language Acquisition (SLA) for Millennials

This research aims to analyze how playing online games could be one of affecting factors to generate the second language acquisition to millennial. It’s a case study to a child living in multilingual environment where some languages used, they are Indonesian, Sundanese and English. Online games are mostly played by using English as the communication tool which in this research English is the second language comprehended. Some factors such as the participants, solidarity and status among the players affect to the child in comprehending his second language that is English. He switches the language following the topic he’s speaking. That condition guides him to be able to speak English well. His comprehension about lexical English has been coloring his own linguistic repertoire that is Indonesian. Some theories used relating with this research are Sociolinguistics and Second Language Acquisition (SLA). The data are analyzed and described qualitatively. Some results obtained are (1) modelling variety or code choice used, and (2) linguistics constraints found. The modelling variety or code chosen are Indonesian and English where the discourse domain is when the child is playing the online games at home. The situational and linguistic context must be appropriate to the choice of code used in the community. Afterwards some codes chosen, those are Indonesia and English could be constraint linguistically. This conditions show that how playing online games could give good impact for millennials in improving their second language acquisition
An Evaluation of Kiso Moji Goi Course Learning

This study aims to obtain an overview of the results of the evaluation of the implementation of learning which includes methods, materials, media, academic services, and assessing learning outcomes of Basic Japanese Characters and Vocabulary faced by students. This study uses descriptive quantitative research methods, using several research techniques in the form of questionnaires, interviews, and document analysis. Respondents in this study were 45 first-level students of the Japanese Department, Faculty of Humanities, Universitas Komputer Indonesia in the 2021/2022 academic year. The results showed that 82.2% of students stated that they were satisfied with the learning method applied by the lecturer, 51.5% of students stated that the level of material difficulty was in the medium category, 88.9% of students stated that the learning media used by the lecturer was good, 84.4% of students stated that the test used by the lecturer was good carried out according to the material that has been taught, 88.9% of students are satisfied with the academic services provided by the lecturer, 93.4% of students got a good final grade. Therefore, based on the results of the evaluation that has been carried out, it can be concluded that the quality of the implementation of Kiso Moji Goi learning is good. Efforts to improve student learning outcomes, such as by increasing the quantity of the use of project-based learning and problem-based learning methods, are needed.
PENGARUH MEDIA PEMBELAJARAN SOFTWARE PROTEUS TERHADAP HASIL BELAJAR SISWA PADA MATA PELAJARAN PENERAPAN RANGKAIAN ELEKTRONIKA KELAS XI DI SMK NEGERI 1 JETIS

The research was conducted in SMK Negeri 1 Jetis where the learning process requires media so that students can learn independently to support the activities of the practicum. This study uses a learning media that the software proteus. The purpose of this research is: (1) determine differences in student learning outcomes before the application and after the application of learning media software proteus, (2) determine the response of students to the eye pelejaran the application of the electronic circuit. The method of research is Pre-Experimental Design with the shape of the One-Group Pretest-Posttest Design. The technique of data analysis using the t test to determine differences in learning outcomes and student responses using a sheet of the questionnaire. The validation sheet filled by two faculty of Electrical Engineering and one teachers of SMK. This research resulted in the discussion, namely: (1) Differences in learning outcomes of students by using the t test obtained value of 0.000 and the level of significant was set at 0.05 so that the value of 0,000&lt;0,05 means that H0 is rejected and H1 is accepted. So there is a significant difference between the learning outcomes of students before and after the application of learning media software proteus. (2) the Response of students to obtain the average worth 82% of which consists of 3 aspects, namely aspects of interest, the material and the suitability of the efforts of the subjects. So the average is classified in the category of very good for the students ' response to the subjects. Learning Media can be used as effective media so that students do not feel bored with the material being taught.
PENGEMBANGAN APLIKASI ANDROID SEBAGAI MEDIA PEMBELAJARAN BERBASIS ANDROID PADA KOMPETENSI DASAR TROUBLESHOOTING MIKROKONTROLER DI SMKN 1 DRIYOREJO

Many studies discuss android-based learning media, but there is no research that specifically discusses troubleshooting on the Arduino IDE. This study aims to create an android-based learning media product by taking the basic competence of troubleshooting input output in the subjects of Microprocessor and Microcontroller Programming Engineering (TPMM). With the learning media called ArduinoID, it is hoped that students can understand more about troubleshooting Arduino IDE, especially on writing errors. This research is a development research that uses the ADDIE model. The subjects of this study were 66 students of class X TEI SMKN 1 Driyorejo. This research design uses a one group pretest-posttest design to compare the results before and after treatment. ArduinoID learning media development utilizes an android developer site called Kodular. The results showed that the ArduinoID learning media validation results from 2 lecturers and 2 teachers got a validation value of 89.10% with very good criteria. From the students' responses to the ArduinoID learning media, they got a response of 84.70% with the criteria of strongly agreeing. Then, in testing the effectiveness of learning media using IBM SPSS Statistics 23 Software, ArduinoID obtained a significance value (2-tailed) of 0.000 &lt; 0.05. So it can be concluded that there is a significant difference (increase) between learning outcomes in pre-test and post-test data. From the various analyzes that have been carried out, it can be concluded that the ArduinoID application is feasible as a learning medium in class X TEI students at SMKN 1 Driyorejo.
Audio captcha breaking and consequences for human users

On the Internet, humans must repeatedly identify themselves to gain access to information or to use services. To check whether a request is sent by a human being and not by a computer, a task must be solved. These tasks are called CAPTCHAs and are designed to be easy for most people to solve and at the same time as unsolvable as possible for a computer. In the context of automated OSINT, which requires automatic solving of CAPTCHAs, we investigate the solving of audio CAPTCHAs. For this purpose, a program is written that integrates two common speech-to-text methods. The program achieves very good results and reaches an accuracy of about 81 percent. As CAPTCHAs are also an important tool for Internet access security, we also use the results of our attack to make suggestions for improving the security of these CAPTCHAs. We compares human listeners with computers and reveal weaknesses of audio CAPTCHAs.
Predicting positions of flipped bits in robust image hashes

Both robust and cryptographic hash methods have advantages and disadvantages. It would be ideal if robustness and cryptographic confidentiality could be combined. The problem here is that the concept of similarity of robust hashes cannot be applied to cryptographic hashes. Therefore, methods must be developed to reliably intercept the degrees of freedom of robust hashes before they are included in a cryptographic hash, but without losing their robustness. To achieve this, we need to predict the bits of a hash that are most likely to be modified, for example after a JPEG compression. We show that machine learning can be used to make a much more reliable prediction than the approaches previously discussed in the literature.
Decision Support System Against Customer Management Loyalty in Silvi Using SAW Method

Online financial institutions or currently often referred to as Finance Technology (Fintech) are one of the institutions that are developing in the digital and IoT era with official support from OJK. One of them is PT. Kreigan Sentral Teknologi which has the Silvi application for mobile or android users, the system currently running on the Silvi application still has several problems such as errors in calculating the number of customer transactions carried out by management which are still semi-computerized using Microsoft Excel where management spends considerable time time to calculate customer loyalty data. Therefore, to increase customer loyalty in the Silvi application, this research aims to make customers more comfortable and interested in making transactions using the Silvi application where for each customer transaction, the company will provide loyalty in the form of a Silvi balance reward supported by a design customer loyalty management decision support system using the method SAW (Simple Additive Weighting) to make it faster and more effective in calculating the number of customer transactions so that customers are more interested in making transactions. The results of this study are that the system is able to make decisions in determining customer loyalty carried out by company management in processing customer transaction calculations with a 90% success percentage in determining customer loyalty in the Silvi application.
Effectiveness of Video Lessons Using Mobile Learning Technology

Electronics and communication and manufacturing technology are gaining much importance in the new millennium. The advents in electronics and communication technologies have been offering inexpensive, more convenient and more functionality in a single device. The engineering students and teachers can access data and communicate with each other anytime, anywhere, on any device, and any data and network. The researcher has to implement new technology, new ideas, and innovations in the research area of wireless communication and wireless networks. In wireless and mobile communication, to develop these engineering laboratories into virtual labs and study materials in hand (within a Pocket). This research is focused on and related to engineering education research. The quasi-experimental design has been used in this research study to measure the effectiveness of mobile learning using video lessons in engineering education. The questionnaire is used to evaluate the effectiveness of mobile learning for undergraduate engineering students. This paper describes the main study of the research results shows that 506 students of second year engineering students of Electrical and Electronics Engineering (EEE), Electronics and Communication (ECE), and Bio- Medical Engineering (BME) in Chennai, Tamil Nadu, India their usage of wireless communication technology in mobile learning using video lessons. The video lessons used for this study are Electromagnetism which is common for EEE and ECE and Electrocardiography is common for BME and ECE. During the study smart phones, mobile phones and wireless devices, tablet pc, personal digital assistants, etc are used and the duration of the video lesson is 30 minutes. These video lessons can be transmitted using Bluetooth technology in the classroom, library, and corridors during the free hours. Keywords: E-learning, m-learning,
Assessing the influences of e-resources motives on their utilization

The foundation of e-learning is formalized learning delivered via electronic devices like computers, tablets, smart phone, smart gazettes, etc. This makes it possible for everyone to learn round the clock, regardless of their location or other limitations. The learning materials that are available online are known as e-resources. There are several different electronic resources available for the study, including e-books, e-journals, emagazines, e-databases, e-newspapers, e-maps, etc. E-resource availability is always expanding. One need only sit at a console and click to access global information without any physical effort. As we can see, using online resources for a variety of objectives is necessary in today's world. Therefore, while determining their use, it is necessary to learn about the availability of different eresources utilized by students who use online / e-learning and how it impacts them for various reasons. Using the pre-structured questionnaire, data was collected from 250 students, from the Navi Mumbai area who were using e-resources. A theoretical construct was developed based on certain assumptions to explore the relationship between utilization and reasons for using e-resources, viz., time saving, easy to use, and helping to get better grades on the test and examination. The proposed construct was examined using SPSS version- 20. The demographic profile, objectives, and hypothesis were followed while doing the data analysis. The average values of chi-square test results for the reasons (time savings, ease of use, and helping students get better grades in tests and examinations) are calculated. These are found to be 0.016, 0.015, and 0.002 for the first variable (e-learning material), 0.141, 0.016, and 0.001 for the second variable (knowledge enhancement), and 0.182, 0.096, and 0.004 for the third variable (other eresources), respectively. The results of the data analysis shows the linkage between motives/ reasons of e-resources and its utilization. As the nature of education is predicted to become more hybrid in the future, similar research might be conducted to further identify the areas that need development in the realm of e-resources. Keywords—E-resources, Reasons/motives, Utilization, E-learning
Construction of Social Network Big Data Storage Model Under Cloud Computing

In order to better store massive network information data effectively, a cloud computing based method for building a big data storage model for social networks is proposed, which combines cloud computing theory to identify user interest data of social network data, constructs a hierarchical user interest conceptual model, and improves the ability of identifying data interest based on Cloud Computing; According to the process of the impact of network information dissemination, the evaluation algorithm of social network data storage is optimized, and the classification management is carried out based on the calculation results, so as to achieve the goal of classification storage of massive data. Finally, the experiment proves that the model built has high practicability in practical applications.
Migrating to Hyperscale

In the previous chapter, we looked at the types of workloads that would benefit from or require the use of the Azure SQL Database Hyperscale tier. Now that we’re familiar with when Hyperscale will be a good fit for you, we need to review the processes required to migrate an existing database into Hyperscale. This chapter will walk you through the different migration scenarios and identify the migration options available for each. Any database migration should be approached with care, so planning and testing are always recommended. We will run through some approaches that can be used to evaluate Hyperscale with our workload before performing a production migration.
Offline Virtual Chat Bot by Using Natural Language Processing

The establishment of a natural conversation between robots and people is one of the objectives of artificial intelligence (AI). One such creation is the virtual assistant. It has now become a boon for everyone in the 21st century. The improvement has gone up to the capability of becoming a personal companion to humans. Here, introducing a companion namely “CHIT CHAT BOT” will be different in a way from another one as it is holding the capacity to work in offline mode as well. In this work, I will develop a bot for better interactions even in offline mode with the humans which will be responding to you with the desired responses. Currently, it is using the data feeder and responses us in that way, seeking towards its futuristic goals we can enhance its responses by working a lot more on data. Plucking up this idea with its implementation in a unique way can lead to the advanced emergence of technology and a way towards globalization since chatbots are used in all sectors.