Reviewerly/exHarmony huggingface dataset:
School Performance Measurement Based on Business Architecture

School performance measurement is the process of collecting, processing, analyzing and interpreting data about the quality of work carried out by school members in carrying out their main tasks and roles. Measuring the performance of an organization will encourage the achievement of objectives in the organization. A performance measurement system must be built so that the information obtained is as much and as accurate as possible. Business architecture is a formal representation and tools as well as information for business professionals in assessing, changing and designing a business. Business modeling will show the relationship of organizational behavior with the information needed, and the relationships that occur within the organizational structure, so that business architecture is the main thing that must be completely defined before continuing on to the next stage. To encourage schools to achieve goals and design business strategies that are in line with the objectives, this research will propose a system for measuring school performance based on business architecture.
CDˆ2CR: Co-reference resolution across documents and domains

Cross-document co-reference resolution (CDCR) is the task of identifying and linking mentions to entities and concepts across many text documents.Current state-of-the-art models for this task assume that all documents are of the same type (e.g.news articles) or fall under the same theme.However, it is also desirable to perform CDCR across different domains (type or theme).A particular use case we focus on in this paper is the resolution of entities mentioned across scientific work and newspaper articles that discuss them.Identifying the same entities and corresponding concepts in both scientific articles and news can help scientists understand how their work is represented in mainstream media.We propose a new task and English language dataset for cross-document cross-domain co-reference resolution (CD 2 CR).The task aims to identify links between entities across heterogeneous document types.We show that in this cross-domain, cross-document setting, existing CDCR models do not perform well and we provide a baseline model that outperforms current state-of-the-art CDCR models on CD 2 CR.Our data set, annotation tool and guidelines as well as our model for cross-document cross-domain co-reference are all supplied as open access open source resources.
Aplikasi Android untuk Monitoring Lahan Pertanian secara Realtime Berbasis Internet of Things

The development of technology is very helpful in agriculture by using the internet to get the information we need. The problem that farmers think of is that they cannot easily and quickly get information in the form of light intensity, precipitation, soil pH, soil moisture, soil temperature, humidity and air temperature. When farmers get the information they need from agricultural land, they usually get information through the internet so they are considered less efficient as it is quite time consuming. To solve this problem, a system is designed using the research and development method (RnD). A new Android-based application that can display data in text and graphics that are more easily accessible to farmers. This study creates an Android-based mobile application based on tests using the Android interface to display information about agricultural land conditions and display graphical data that is updated every 5 minutes.&#x0D; &#x0D; Keywords— Land monitoring, Agriculture, IoT, Android Mobile Application
Correction to: A Follow-the-Leader Strategy Using Hierarchical Deep Neural Networks with Grouped Convolutions

A correction to this paper has been published: https://doi.org/10.1007/s42979-021-00629-1
AN ANALYSIS OF USING WHATSAPP TO ENHANCE STUDENTS’ LEARNING OF ADVANCED LISTENING CLASS

Education system has developed rapidly, technology has invaded our life, everyone has smart phone these days, using WhatsApp, Facebook, Twitter, Instagram, Telegram, etc. No one can deny that the generation we teach these days, has become addicted to these applications, for social relationship and fun. This study was conducted in English Departmen especially Advanced Listening class. The population of the study were 32 female and 4 male students from 4st level who were studying English Program. The researcher has used the analytical descriptive method to conduct this study in University of Muhammadiyah Pringsewu. A students’ questionnaire and instructor observation were the tools for collecting the data, results were coded manually and analyzed using SPSS. Almost all study-findings supported using WhatsApp to enhance students learning and enthusiasm, using WhatsApp helped students to develop English skills, enriched their listening and learn from their mistakes, although the study laid out some disadvantages of the experience such as preparing the materials and having discipline class. Keywords: WhatsApp, enhance, experience, language, learning
Mining Key-hackers

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Analysis of Big Data Analytics for Social Media

With the popularity of the Internet and the advent of Web 2.0 technology, data mining has recently emerged as an important area of research. In addition, the development and adoption of social media applications present opportunities and challenges for researchers and professionals. The amount of information that users provide through social media platforms is the result of a combination of their daily data and their daily activities. As a result, a large amount of data called "big data" has recently been studied. A recent review of the project was introduced to get a complete view of the major data analytics sites on social media. We categorize our literature according to major categories. The study also compares the capabilities of key data analysis strategies and their behavioral models. It also describes the application of large-scale data analysis on social media and demonstrates mass reading techniques, methods, and quality characteristics. The challenges of the survey are also explained in key data analysis for social media analysts. General data refers to the process of collecting, organizing, and analyzing big data to obtain a variety of products and other useful data.
The Problems and Countermeasures of Computer Teaching in Higher Vocational Colleges

Society to the requirement of computer teaching, with the development of times and the progress of information technology, a new promotion, therefore, reform of computer teaching in higher vocational colleges must be properly, but also because there are many problems in current computer teaching in colleges and universities, and if the problem is not solved, the effectiveness of the college computer teaching will be affected by a certain, also determines the effect of college computer professional talent training.The computer teaching in higher vocational colleges must pay attention to the problems in the current teaching, so as to find the corresponding solutions.Therefore, this paper mainly focuses on the problems existing in the computer teaching in colleges and universities at present, and puts forward some solutions.
Professional Clustering Based on the Graduates Profile Using K-Means Method

The Information Systems department of Pelita Indonesia Institute of Business and Technology produces graduates with education knowledge to face the professional work, but the majority of students after graduating do not work according to their graduate profiles/educational background. This research aimed to help students in determining the appropriate graduate profile. The proposed system was built using the K-means method for the classification process of graduate profiles; hence, the results can be used as recommended profession to be taken. The data used in this study is the data of students of class 2016, and these results are compared with their current professional record data with the aim of knowing the percentage of professional suitability obtained with the current profession. After this research is tested, the results of the classification of the graduate profile can be obtained where there are 10 students in the administrator database cluster, 11 students of the web design and developer cluster, one student of the cluster information system manager, and 8 students of the cluster system analysis. The percentage of suitability was 43.33%. This program is designed using the PHP programming language.
A New Optimization Based on Parallelizing Hybrid PSOGSA Algorithm

This study suggests a new metaheuristic algorithm for global optimization, based on parallel hybridizing the swarm optimization (PSO) and Gravitational search algorithm (GSA). Subgroups of the population are formed by dividing the swarm’s community. Communication between the subsets can be developed by adding strategies for the mutation. Twenty-three benchmark functions are used to test its performance to verify the feasibility of the proposed algorithm. Compared with the PSO, GSA, and parallel PSO (PPSO), the findings of the proposed algorithm reveal that the proposed PPSOGSA achieves higher precision than other competitor algorithms.
A Multi-Objective Dragongfly Optimization for Requirement Traceability Establishment

Software traceability is a crucial component of various exact software development process and it is needed for various component certification and approval process in security system. With the tremendous growth of system, traceability is considered as a recent research topic. The traceability is a software development process that is indefinable. Various manufacturers struggle in predicting the appropriate traceability degree for their needs and produce the appropriate set of traceability links. The effort, cost, and discipline have to be maintained with tracking links with the faster development of software systems that are extremely higher. Also, it produces various advantages in practical realization; as it can be either ad-hoc or not properly defined traceability process, produces poor training or lack of effectual tool support. Moreover, the traceability process has to be determined as it can diminish the development effort and to enhance the development process. Generally, traceability research is based on empirical investigations for exploring newer investigational queries or to compute newer tracing methods. Here, this work concentrates on traceability, functional requirements, link establishment. It shows a better trade-off among the prevailing approaches.
PREPARING SCHOOL GRADUATES FOR THE LABOUR MARKET

Despite their determination to work and build their careers, school graduates are not sufficiently prepared to look for work and the opportunities to search a job. In most cases they are well prepared in theory and language and are literate in modern technologies. Their biggest handicap is the lack of practical skills and work experience. At the same time, graduates have to face the challenges of accelerated globalization and digitization. It is necessary to find answers to questions about what professional knowledge, practical skills, attitudes and values will be shaped by today's graduates and how education systems can develop the required knowledge and skills. The ambition of our contribution is to identify the main disparities that must be overcome in order to achieve the goal of the country's economic development strategy, in which the education system must inevitably correspond to the labour market requirements.
A Survey on the security of Cloud Storage System

Distributed computing is an emerging processing tool in software engineering today. Distributed computing is a collection of assets and services provided by a company or the internet. Different figuring approaches, such as matrix processing and dispersed registering, are broadened by distributed computing. Distributed computing is now used in both the modern and academic fields. Cloud encourages its customers by providing virtual assets through the internet. New procedures are emerging as the area of distributed computing expands. As the distributed computing environment grows, so do the security problems for cloud engineers. Since cloud clients save their data in the cloud, a lack of security in the cloud can jeopardise the client's trust. In this paper, we'll look at a few different aspects of cloud protection, such as multi-occupancy, versatility, and usability. We'll also look at current security strategies and techniques for a secure cloud. This paper will allow specialists and experts to consider the different security threats as well as the models and instruments that have been suggested.
RENEWED TRENDS IN HIGHER EDUCATION FOLLOWING COVID-19

The world in general and the organizations in particular has been changed significantly because of Covid-19 pandemic. The higher education institutions haven’t been an exception. The new challenge has triggered a worldwide shift towards online learning and teaching. There is a question of whether the current situation will lead to the overall transformation of higher education institutions to online, digital or blended one. This paper presents the systematic review of official reports where the new trends concept is used in higher education context. The primary goal of this paper is to establish understanding of already listed trends and directions and to contribute to the discussion of a digital transformation of higher education institutions following Covid-19 pandemic for effective teaching and learning. The paper is based on the theoretical research, including literature and official reports review in the context of transformation of higher education following Covid-19. As primary results, the list of new trends in higher education has been made for effective learning and teaching. This study will help higher education institutions to rethink their strategies according to the necessities to respond to the challenges of such rapid digital transformation.
PENGEMBANGAN E-MODUL WRITING FOR PROFESSIONAL CONTEXT BERSTANDAR CEFR BERDASARKAN KARAKTERISTIK PEKALONGAN KOTA KREATIF DUNIA

The development of technology demanded the teaching material to be designed digitally. This study &#x0D; was aimed to develop CEFR (Common European Framework) -standard Writing for Professional &#x0D; Context teaching material in the form of Pekalongan the world creative city e-module. Research &#x0D; and development (R &amp;D) was used in conducting this research. Observasion sheet, questionnaire &#x0D; and interview were used to collect the data. The results showed that E-Model of Writing for &#x0D; professional context was needed by the students. Therefore, the researcher did a plan of developing &#x0D; an e-module. After it was designed, it was validated by the validators for getting the suggestion of &#x0D; the betterment. Finishing the validation process, next the e-module of Writing for Professional &#x0D; Context standardized by CEFR with the characteristic of Pekalongan the World Creative city was &#x0D; revised and published. The title of the e-modul is Let’s Write: Pekalongan the World Creative City. &#x0D; The texts types in this e-modul were written with their social functions, generic structure and &#x0D; linguistic. The content of the texts described Pekalongan as the World Creative City.&#x0D; Keywords: CEFR, e-module, writing, creative
Pengaruh Penggunaan Media Pembelajaran Berbasis Vectorian Giotto terhadap Motivasi dan Hasil Belajar Siswa SDIT Di Kabupaten Oku Timur

Utilization of media learning based on ICT, especially in the eyes of subjects IPA at the level of elementary school can optimize the process of learning the teaching that takes place. This is very relevant when using learning media to convey information. One of the media that can support is Vectorian Giotto. Research objectives This is to explain the effect of using vectoriangiotto based learning media on the motivation and learning outcomes SDIT students in East OKUT. This research is quantitative with a quasi- experimental type. Population and samples were used in the study amounted to 136 students. Data collection techniques: observation, tests, and questionnaires. Data analysis techniques, descriptive statistical techniques and inferential statistical techniques. Descriptive analysis results; The mean scores of motivationand learning outcomes for grade IV were 79.26 and 93.33. results of statistical inferential by using test wilcoxion obtained value Asymp . Sig. (2-tailed) for 0000 is smaller than 0.05, means that there is the influence of the media learning based vectoriangiotto with the results of learning. To see the motivation of students to use the medium of learning obtained a value of 0.000 is smaller than 0.05, which means that there is the influence of the media learning based vectoriangiotto with the motivation to learn.
Scientific rationality, its main characteristics

Scientific rationality, its main characteristics, as well as its types, structure, properties and prerequisites are considered.The article considers scientific cognition in terms of rationality, as well as the significance of interactions between the sciences.
The Protection of Genetic Privacy in Biobanking at International Level

This chapter sketches a baseline level of protection for genetic privacy rights in biobanking, against which legal systems, including the General Data Protection Regulation (GDPR), might be compared. This baseline level of protection is provided via identifying principles dealing with the protection of all types of genetic privacy rights, and rights holders, in biobanking in the international framework. The chapter identifies two types of international principles: common international principles—principles identified in a majority of all biobank-relevant international instruments; and emerging international principles—principles identifiable in a majority of biobank-specific international instruments. It also offers a critical analysis of the protection offered under the international framework. This critique does not aim to undermine the legitimacy of regarding identified international principles as offering a baseline level of protection. Rather, it merely aims to highlight that the protection provided has flaws, and thus should not be regarded as definitive or perfect.
Face Recognition from Video using Threshold based Clustering

Video processing has gained significant attention due to the rapid growth in video feed collected from a variety of domains. Face recognition and summary generation is gaining attention in the branch of video data processing. The recognition includes face identification from video frames and face authentication. The face authentication is nothing but labelling the faces. Face recognition strategies used in image processing techniques cannot be directly applied to video processing due to bulk data. The video processing techniques face multiple problems such as pose variation, expression variation, illumination variation, camera angles, etc. A lot of research work is done for face authentication in terms of accuracy and efficiency improvement. The second important aspect is the video summarization. Very few works have been done on the video summarization due to its complexity, computational overhead, and lack of appropriate training data. In some of the existing work analysing celebrity video for finding association in name node or face node of video dataset using graphical representation need script or dynamic caption details As well as there can be multiple faces of same person per frame so using K- Means clustering further for recognition purpose needs cluster count initially considering total person in the video. The proposed system works on video face recognition and summary generation. The system automatically identifies the front and profile faces of users. The similar faces are grouped together using threshold based a fixed-width clustering which is one of the novel approach in face recognition process best of our knowledge and only top k faces are used for authentication. This improves system efficiency. After face authentication, the occurrence count of each user is extracted and a visual co-occurrence graph is generated as a video summarization. The system is tested on the video dataset of multi persons occurring in different videos. Total 20 videos are consider for training and testing containing multiple person in one frame. To evaluate the accuracy of recognition. 80% of faces are correctly identified and authenticated from the video.
Techniques and Challenges while Applying Machine Learning Algorithms in Privacy Preserving Fashion

Nowadays many different entities collect data of the same nature, but in slightly different environments. In this sense different hospitals collect data about their patients’ symptoms and corresponding disease diagnoses, different banks collect transactions of their customers’ bank accounts, multiple cyber-security companies collect data about log files and corresponding attacks, etc. It is shown that if those different entities would merge their privately collected data in a single dataset and use it to train a machine learning (ML) model, they often end up with a trained model that outperforms the human experts of the corresponding fields in terms of accurate predictions. However, there is a drawback. Due to privacy concerns, empowered by laws and ethical reasons, no entity is willing to share with others their privately collected data. The same problem appears during the classification case over an already trained ML model. On one hand, a user that has an unclassified query (record), doesn’t want to share with the server that owns the trained model neither the content of the query (which might contain private data such as credit card number, IP address, etc.), nor the final prediction (classification) of the query. On the other hand, the owner of the trained model doesn’t want to leak any parameter of the trained model to the user. In order to overcome those shortcomings, several cryptographic and probabilistic techniques have been proposed during the last few years to enable both privacy preserving training and privacy preserving classification schemes. Some of them include anonymization and k-anonymity, differential privacy, secure multiparty computation (MPC), federated learning, Private Information Retrieval (PIR), Oblivious Transfer (OT), garbled circuits and/or homomorphic encryption, to name a few. Theoretical analyses and experimental results show that the current privacy preserving schemes are suitable for real-case deployment, while the accuracy of most of them differ little or not at all with the schemes that work in non-privacy preserving fashion.