Reviewerly/exHarmony huggingface dataset:
Climate Prediction Using RNN LSTM to Estimate Agricultural Products Based on Koppen Classification

The yield of an agricultural process is very important and influential, where the harvest is used as a support for human life both as food and a source of income. Many factors can influence the success of agriculture, such as the climate that is going on around in the surrounding area. The wrong prediction in determining the future climate will cause crop failure due to incompatibility with the type of plant. In this era, many technologies have been able to predict climate, one of which is technology machine learning that has many types and techniques, which machine learning technology has been widely used in predicting many things. This study aims to predict the climate in an area which is intended to determine crop yields based on the Koppen classification, and also the prediction based on several parameters such as temperature, humidity, duration of sun exposure and rainfall. And the results of this study is have a loss of 0.006 and with the MAPE value as an indicator of the percentage error and as an indicator for determining the accuracy of the prediction results, which is 3.29%, which means that it is included in the very accurate category in predicting climate to estimate agricultural yields.
PROPOSALS FOR ADAPTING CURRICULAR CONTENT TO TECHNICAL VOCATIONAL TRAINING PROGRAMS

The article analyzes the subject related to the national curricula implementation for compulsory disciplines at high school component within the Vocational Education and Training (VET) programs. The authors develop some proposals based on arguments regarding the curricula adjustment to the VET programs requirements and needs.
Functioning of an Android app “TNAU Paddy Expert System” and its User’s Feedback Sentiment Analysis

TNAU paddy expert system app is a system that links people and institutions to promote mutual learning and utilize agriculture-related technologies, knowledge and information. The present study expounded the functions of an android app “TNAU paddy expert system”, also it was intended to fi nd out the nature of feedbacks provided by the TNAU paddy expert system app users and to foster the application more for eff ective usage through the feedbacks provided by the users. The feedback and ratings were collected from the TNAU Paddy expert system app (both in English and Tamil version) page in the open-source platform viz., Google play store, a total of 63 reviews and 109 users’ ratings were collected from the application interface present in the Google play store to fi nd out the nature of feedback and the level of satisfaction of the users. Sentiment analysis was carried out with the help of ‘MS Excel 365’ and ‘azure machine learning’ softwares. Then the data was also subjected to factor analysis with the help of Statistical Package for Social Sciences (SPSS) 16.0, to fi nd out the major opinions that were expressed by the TNAU Paddy expert system app users. TNAU Paddy expert system app was the application of scientifi c research which imparts the scientifi cally proven paddy technologies and agricultural practices for the betterment of the farming community, that aids farmers to make right decisions at the needed time and through crop doctor component it helps them by protecting their crop and reducing the time and cost.
Literature Enhances Communication Skills: A Comprehensive Review

Many non-native and native speakers all around the world have proven that English is an international language. It is sometimes referred to as the global language since it is the primary means of communication across countries. In our nation, the usage of English as a common language plays an essential role in education. English learners must place a strong emphasis on the use of communication. The ultimate goal of language instruction is to improve communication skills. Pragmatics is the method in which meaning is transferred through communicating, and linguistic skill is regarded as an instrument for communication. Pragmatic competence is the capacity to comprehend and communicate meanings that are more correct and acceptable for the cultural and social contexts in which communication takes place. Even though English is used at many levels of communication, the speakers must be familiar with a variety of pragmatic components to create coherency and the capacity to react in a variety of scenarios. As a result, one of the key aims in the field of education should be the development of pragmatic ability and also help for future understanding.
Beijing Shayan Kite Display System Based on WebVR

With the rapid development of the internet, virtual reality (VR) technology is widely used in people's lives. It provides people with a brand new way of interaction and is widely utilized in culture, education, military, medicine and other fields. From 2017 to now, with the emergence and evolvement of the WebVR application programming interface (API), realizing virtual reality on the web becomes possible and popular. It has become a focal point because of the advantages such as being lightweight and cross-platform. In this paper, we propose to build a WebVR based Beijing Shayan kite display system. Users can experience the charm of culture well in the virtual world mainly by three-dimensional (3D) modeling technology and WebVR. In order to effectively prove the effect of the WebVR framework and engine, related experiments were carried out. At the same time, this paper first proposed a WebVR based Beijing Shayan kite display system, which has a certain significance for the digital protection of Beijing Shayan kites.
Detection and extraction of digital footprints from the iDrive cloud storage using web browser forensics analysis

STorage as a &lt;span&gt;service (STaaS) allows its subscribers the ability to access their stored data with the use of internet enabled digital devices at anywhere, anyplace and anytime. The easy accessibility of cloud storage with digital devices is one of the major benefits of cloud computing but this benefit can also be exploited by cybercriminals to perform various forms of malicious usages. During forensic investigation, forensic examiners are expected to provided evidence in relation to the malicious usages but the physical inaccessibility to the digital artifacts on the cloud servers, the difficulty in retrieving evidential artifacts from various cloud storage services and the difficulty in obtaining forensic logs from the concerned cloud service providers among other factors make it difficult to perform forensic investigations. This paper provided step by step experimental guidelines to extract digital artifacts from Google Chrome and Internet Explorer from Windows 10 personal computer using iDrive cloud storage as a case study. The study used Nirsoft forensic tool to locate the relevant forensic artifacts and an integrated conceptual digital forensic framework was adopted to carry out the investigation. This study increases the knowledge of client forensics using web browser analysis during cloud storage forensic investigation.&lt;/span&gt;
Sentiment Summarization Learning Evaluation Using LSTM (Long Short Term Memory) Algorithm

Lecturer learning evaluation is a text that contains student reviews related to lecturer learning performance.Learning evaluation is used as a lecturer's self-reflection material to improve the learning services provided in the next lesson.The evaluations are many in number, making it difficult for lecturers to analyze.Sentiment analysis techniques are needed to classify student evaluations.The evaluation that has been classified still leaves a long and convoluted text.Text summarization is one solution to summarize a long text into a dense and informative text.Text summarization is helpful to save time searching for the text's gist.There are two methods in text summarization, extractive and abstractive methods.This study applied an abstract method because the data used was an evaluation of lecturer learning whose reviews were written by students.The algorithm used for sentiment classification and text summarization used the Long Short Term Memory (LSTM) algorithm.The sentiment classification results were evaluated using a confusion matrix, namely testing the model with evaluation data.While the summary results were evaluated using ROUGE, which compared the summary results from the system with a manual summary by experts.In testing the confusion matrix system, the accuracy value was 0.902, and the f-measure value was 0.921.In the Recall-Oriented Understudy for Gisting Evaluation (ROGUE) test, the positive evaluation scored 0.16, and the negative evaluation scored 0.2.The developed tokenizer has not stored the tokens resulting from the training process.As a result, the prediction results when loading the model were not as good as when training was finished.
Methodological approach to the implementation of a ‘‘2+2+2’’ higher education model at a technical university

The paper provides a solution to the task of implementing a “2+2+2” model of higher education while providing the students with an opportunity to choose the direction of training starting from the third year of studies; reviews the process of developing Primary Educational Programs as a complex technical object through the application of a systematic approach; identifies the conditions and restrictions that allow avoiding the destruction of the systematic nature of education, and, therefore, the degradation of its quality; proposes the principles of applying individual educational paths for achieving the target of granting the students with an opportunity to obtain one or more qualifications.
Computer Self-Efficacy, Task Value, Digital Literacy, Online Learning Perceptions on Indonesian University Students’ Learning Satisfaction

This study examines the relationships of student learning satisfaction with computer self-efficacy, task value, digital literacy, and online learning perception on university students in Indonesia.In this context, a structural equation model is proposed by considering studies in the literature.The proposed model is analyzed and discussed considering the literature.A total of 504 university students from Indonesia participated voluntarily in the study.A scale of readiness for e-learning, a self-regulated online learning scale, and a satisfaction survey were used as data collection tools in the study.The influence of online learning perceptions on online learning satisfaction has a coefficient value of 0.557, indicating that the better students' perceptions of online learning, the higher their online learning satisfaction.Then, the influence of computer self-efficacy on perceptions of online learning has a coefficient value of 0.318, which indicates that the better students' confidence in using computers, the better the perception of online learning.Furthermore, the effect of the task value on the perception of online learning has a coefficient value of 0.316 which means that the higher the student's task value, the higher the perception of online learning.Finally, the influence of digital literacy on the perception of online learning has a coefficient value of 0.122 which means that the higher students' digital literacy, the better the perception of online learning.
Rancangan Standar Kompetensi Peran Big Data

The increasing use of big data in various sectors needs to be accompanied by competency standards to ensure the availability of qualified human resources (HR) in the big data field.However, the current national work competency standards in Indonesia have not yet clearly defined competency standards related to big data.This study discusses how to design competency standards for the role of big data.The purpose of this research is to provide a design of competency standards for the role of big data.The method used in this research is literature study and interviews for design validation.The result of this research is the design of competency standards for the role of big data, which consists of 19 (nineteen) units of competence and 9 (nine) kinds of generic competencies.
A video auditing system for display-based voting machines

The use of general-purpose computers as touch-screen voting machines has created several difficult auditing problems.If voting machines are compromised by malware, they can adapt their behavior to evade testing and auditing, and paper trails are achieved through printing devices under the untrusted machine's control.In this paper we outline and exhibit a prototype of a device that audits a voting machine through screen capture, sampling the HDMI signal passed from the computer to the display.This is achieved through a standard that requires a compliant voting machine to display signal markers on the summary pages before a vote is cast; compliance is enforced via alerts to the voter with a visual and audible signal while the screen is captured and archived.This direct feedback to the voter prevents a compromised machine from failing to invoke the device.We discuss the design and prototype of this system and possible avenues for attack on it.
Overview of Ownership and Access of Latrines with Spatial Applications in Kalumbuk Village of Kuranji Health Center Work Area Year 2020

The National Community Based Total Sanitation Strategy (STBM) is an integrated action to reduce the incidence of diarrhea and improve Indonesian people's hygiene and quality of life.Toilet ownership and use is one indicator of the Clean and Healthy Behavior (PHBS) program in the household setting.This study aims to determine access, ownership and spatial ownership of restrooms in the working area of the Kuranji Community Health Center, especially Kalumbuk in digital form.To establish 100% ODF in the Kalumbuk Kelurahan, the Kuranji Community Health Center.This type of research is descriptive.The population is 201 families in Kalumbuk Sub-district, the Kuranji Community Health Center, Kuranji District, Padang City in the 01 Community Pillars and the 02 Community Pillars.Digitizing techniques are used to determine the distribution of pit latrine and latrine access.In the results of this study, 75% of families had restrooms in Rukun Warga 01, and Rukun Warga 02 as many as 89% of families had a toilet.All residents in Kalumbuk Urban Village in the 01 Community Pillars and the 02 Community Pillars have access to the toilet 100%.Spatial data of people who already have a toilet are marked with a blue dot.Those who have access to the bathroom are marked with a purple dot with classification to the Mosque / Mushalla, and Red is a family that has access to the house of relatives/sharing.on the Spatial Map of the Distribution of Latrine Ownership and Access in Kalumbuk Village, the Work Area of the Kuranji Health Center in 2020
Machine learning-based sentiment analysis of Twitter data

The paper analyzes the views of Twitter users on the COVID-19 corona virus pandemic based on machine learning algorithms. The role of sentiment analysis increased with the advent of the social network era and the rapid spread of microblogging applications and forums. Social networks are the main sources for gathering information about users’ thoughts on various themes. People spend more time on social media to share their thoughts with others. One of the themes discussed on social networking platforms Twitter is the COVID-19 corona virus pandemic. In the paper, machine learning methods as Naive Bayes (NB), Support Vector Machine (SVM), Random Forest (RF), Neural Network (NN) are used to analyze the emotional “color” (positive, negative, and neutral) of tweets related to the COVID-19 corona virus pandemic. The experiments are conducted in Python programming using the scikit-learn library. A tweet database related to the COVID-19 corona virus pandemic from the Kaggle website is used for experiments. The RF classifier shows the highest performance in the experiments.
Review of Semantic Priming Research Applied in Second Language (L2) Acquisition

This paper synthesizes and evaluates semantic priming research applied in second language research.It first provides the definitions of semantic priming and its types.Then the relationship between semantic priming research and second language research is discussed.The empirical studies concerning semantic priming in second language research are elaborated from two aspects: studies outside China and in mainland China.Finally, the implications and suggestions for future studies will be drawn from the analysis.
Operation and maintenance of irrigation sluice gates in tertiary canals

Kasemen District, Serang City, was one of the irrigation areas that experienced drought and became the focus of this community service. The lack of irrigation water is one of many factors that cause agricultural land in Kasemen District to switch functions. With the existence of several PKM activities such as field surveys, socialization, counseling on the operation and maintenance of irrigation sluice gates, it aims to increase community knowledge in the operation and maintenance of irrigation sluice gates. This activity encourages residents to be more concerned about river sustainability so that Cibomo Village's water needs can be met. The irrigation sluice gates are maintained as a result of this activity, and the Karya Tani Group's understanding of sluice gate operations and maintenance improves. Local residents are expected to become more concerned about the irrigation area environment as a result of the Karya Tani Group's increased understanding, particularly regarding the pattern of operation and maintenance of sluice gates.
Psychopathic personality disorder and cybercriminality: an outline of the issue

The rapid development of information and communication technologies has created a new dimension in interpersonal relationships, which is commonly called cyberspace. Structural features of cyberspace such as anonymity, the lack of non-verbal indicators of interaction, their asynchrony, a sense of impunity and the lack of specific norms of conduct cause that the behavior of some people online may differ significantly from their behavior in real life. Individuals with psychopathic personality disorder can use cyberspace for criminal activities such as cyberbullying, trolling, digital piracy, cybervandalism or data theft. This is a very significant problem, as some researchers predict that as digital communication develops, ‘cyberpsychopaths’ will become the dominant form of criminals. Currently, there is a lack of research on the relationship between the structural features of cyberspace and the expression of psychopathic personality traits and their role in committing cybercrimes.
The transcendentality of the humanities

The article regards the principal aspects by which cognition in the humanities is different from that in natural sciences. If the task of transcendental philosophy is the analysis of general conditions of our experience, such status can be prescribed to all disciplines that study human as a subject. General conditions of experience determine our experience even when we make them the object of analysis. Marx’s and Manheim’s sociology of knowledge is used as an example to show that sociology of knowledge as a study of the dependence of social ideas on social interests remains inside the domain of its own laws. This fact gives us the opportunity to treat it not as an objective science, but rather as hermeneutics. Its main purpose is not to unmask other people’s ideological illusions. So­ciology of knowledge is rather a way of self-understanding, which affords us to pay at­tention to our own possible ideological bias. Structuralism and cognitive sciences as at­tempts at a scientific analysis of humans and society try to ignore the transcendental na­ture of their conclusions. If some fundamental structure underlies all our intellectual ac­tivity, it should control the perspective that structuralists take on it as well. If our self is an illusion formed by the objective neuronic dynamics, as cognitivists assert, they lose the right to reason in first person, to put goals of developing our consciousness in a par­ticular direction. As long as we study the man and society in the humanities, our knowl­edge has a transcendental status. The humanities do not study some object that is external to us. They do not give us technical knowledge or technological recipes. Their goal is to make our self-understanding deeper.
A Novel Multi-Attribute Authority Based Encryption for Controlling Access to Cloud Data

Cloud computing has changed the way IT department are working with respect to outsourcing data and having controlled access to the data. In the new computing paradigm that supports on-demand services, the storage service became an attractive service for many cloud users. When data is outsourced to cloud, there is an issue of giving controlled access to the cloud data. Many schemes came into existence. Some of the schemes focus on auditing, provable data possession and proof of irretrievability. Some other schemes threw light into the access control on the cloud data. While giving privileges to accessing data attribute based encryption has achieved significant fine-grained control over the data. In this paper we propose a methodology that can allow controlled access to cloud data with multi-attribute authority based encryption. The multi-attribute based approach is used to make the scheme robust. Moreover the proposed approach is aimed at prevention of identity leakage and also achieves anonymity as well. We built a prototype application that demonstrates the proof of concept. The empirical results revealed that the proposed method improves access control significantly.
School Dropout Reduction Program (S-DORP) in secondary schools of Ticao Cluster, Masbate Province

This study aimed to determine the effectiveness of School Dropout Reduction Program (S-DORP) of Secondary Schools in Ticao Cluster, Masbate Province.The descriptive-survey method was used to determine the status and effectiveness of S-DORP in terms of dropout rate, repetition rate and promotion rate and problems encountered.The instruments used were documentary analysis, survey questionnaire, and unstructured interview.The statistical tools utilized were frequency count, percentage, ranking and weighted mean.It involved a total enumeration of 168 respondents.It revealed that for three school years (2012-2013, 2013-2014, 2014-2015) implementation of S-DORP, eight secondary schools have established a varying trend of dropout rate, a decreasing trend of repetition rate and an increasing trend of promotion rate.The level of effectiveness of S-DORP in terms of dropout rate, repetition rate and promotion rate were evaluated as effective by the parents, teachers, students and school heads.The major difficulties encountered in achieving a zero dropout and repetition rates and 100% promotion rate were the lack of attention given to S-DORP and SARDO (student-at-risk of dropping out) and large number of students.It is highly recommended that the Department of Education should extensively re-orient S-DORP so that the standard zero-dropout, zerorepetition and 100% promotion rates may fully realized.The difficulties encountered should be given utmost intervention through provision of additional classrooms, involvement and participation of stakeholders in planning, developing, and implementation of S-DORP through meetings, forum and assembly.The proposed Repetition, Promotion and Dropout Rates (RepProd) Program has to be considered for implementation.
The Role of Social Media Technology in the Library: A Study

Social media has a significant influence on allowing paradigm shifts in the way we interact and distribute information. It provides a bunch of internet-based applications and platforms that promote and facilitate information exchange. Libraries may utilise social media to interact with their patrons and provide improved service delivery. Social media has the ability to build significantly stronger links between libraries and their patrons, regardless of where users are located or how they learn about and use library services and resources. Social Media Technology (SMT) has created new doors for libraries and library users all across the world.