Reviewerly/exHarmony huggingface dataset:
THE USE OF SKIMMING STRATEGI TO IMPROVE STUDENTS’ READING COMPREHENSION : A STUDY AT UNIVERSITY OF TIMOR

The objectives of the research were to find out if there was any significant improvement of students’ comprehension in reading through skimming technique.the use of this research is pre-experiment design, based one group pre-test and post-test. The subjects of this research were the second semester students at University of Timor. The result of research showed that score mean post-test is higher of the pre-test. The score mean pre-test is 39.38 up to post-test is 73.50 it means that, after treatment the students has the higher score mean post-test. The result t-test of the students pre-test and pos-test is 13.68, than the result standar deviation of pre-test is 16.79 and than post-test of standar deviation is 11.82. there was a statistically significant improvement of students’ reading comprehension. This suggests that the skimming technique can facilitate the students to improve their reading comprehension.
Adversarially Robust Classifier with Covariate Shift Adaptation.

Existing adversarially trained models typically perform inference on test examples independently from each other. This mode of testing is unable to handle covariate shift in the test samples. Due to this, the performance of these models often degrades significantly. In this paper, we show that simple adaptive batch normalization (BN) technique that involves re-estimating the batch-normalization parameters during inference, can significantly improve the robustness of these models for any random perturbations, including the Gaussian noise. This simple finding enables us to transform adversarially trained models into randomized smoothing classifiers to produce certified robustness to $\ell_2$ noise. We show that we can achieve $\ell_2$ certified robustness even for adversarially trained models using $\ell_{\infty}$-bounded adversarial examples. We further demonstrate that adaptive BN technique significantly improves robustness against common corruptions, while often enhancing performance against adversarial attacks. This enables us to achieve both adversarial and corruption robustness for the same classifier.
MANAJEMEN PASAR TRADISIONAL BERBASIS WEB DI KABUPATEN JEMBRANA

Traditional markets play a very important role in the economic activities of the community, especially for sellers of products of basic necessities produced by small and medium-sized and micro economic actors. The development of information technology as we know it is growing rapidly. It would be very beneficial if the Jembrana district government could take advantage of the current information technology to support the data and information needs of traditional markets in the Jembrana district. This study provides a solution for data processing and information on traditional markets in Jembrana district, namely the traditional web-based market management. With this system, it is hoped that Market Managers in Jembrana Regency can manage and manage the market more professionally with the help of information technology. In addition, this system also serves as information about traditional markets to the public consisting of market location map information, the latest information on market PDs, as well as information on price updates of goods from each market PD in all Jembrana district.
타 문화권 선교사들의 정서적 탈진과 대처방안에 관한 현상학적 연구: Herbert J. Freudenberger와 Christina Maslac의 이론을 중심으로

This study presents a diagnosis of burn-out with the theory of Freudenberger’s “excessive achievement motivation” and Maslac’s “emotional exhaustion” and suggests Howkins and Oswald’s theory as a countermeasure. The dropout ratio of Korean missionaries has increased by 40 percent. The research for missionaries’ dropout was conducted in 1996 and 2015, and 200 missionary care centers were opened. Nevertheless, there were no specific solutions. The missionaries’ dedication caused the burn-out due to the lack of a control ability in relationships. The pressure of the mission field has led to a decrease in the accomplishment of missionaries. As a result, the missionaries were willing to leave the people. The study analyzes the missionaries’ burn-out and suggests an alternative solution.
Formation of Worldwide in the Young Generation

This article summarizes the views of Eastern and Western thinkers on the formation of the worldview of young people, the formation of the development of the scientific worldview. Thus, the formation of the worldview of the younger generation in the age of information technology and the factors that contribute to it are theoretically based.
UCAN: A Learning-based Model to Enhance Poorly Exposed Images

Image enhancement is a critical process in imagebased systems. In these systems, image quality is a crucial factor to achieve a good performance. Scenes with a dynamic range above the capability of the camera or poor lighting are challenging conditions, which usually result in low contrast images, and, with that, we can have the underexposure and/or overexposure problem. In this work, our aim is to restore illexposed images. For this purpose, we present UCAN, a small and fast learning-based model capable to restore and enhance poorly exposed images. The obtained results are evaluated using image quality indicators which show that the proposed network is able to improve images damaged by real and simulated exposure. Qualitative and quantitative results show that the proposed model outperforms the existing models for this objective.
Application and Feasibility Analysis of Proactive Anti-cheating Algorithm Based on ML

Nowadays, most Internet application contents based on modern Internet service providers are realized through human-computer interaction. Therefore, the application scenarios of HCI in life are very wide, and the visual operation path provides great system availability and user-friendliness. And its security is an important fulcrum for service providers (SP) to obtain benefits, or fund transactions between terminals. According to the trigger mechanism of cheating, it is mainly divided into exposure cheating, click cheating, and conversion cheating. Cheating will greatly pollute the network environment and it even violates laws and regulations. Therefore, ISPs are deploying and continuously improving anti-cheat algorithms and mechanisms during the service development stage. The location of these operating mechanisms is generally the network server used by the SP to provide services, and some algorithms and monitoring behaviors significantly increase the load of the server, thereby increasing service costs. Based on machine learning (ML) technology, this paper introduces a feasibility analysis of anti-cheat algorithm for human operation based on object terminal, which is suitable for behavior recognition level and data level. The algorithm learns user behavior through their active participation. It finds the path of the request by combining with packet matching of abnormal behavior characteristic of cheating behavior updated regularly by the service provider. This algorithm also detects cheating behavior through local controller. When the two peers have the same or a high probability of prejudgment after calculation, the server is triggered to actively identify user behavior, using the trust profile to analyze and log the cheating path. The compatibility and friendliness of terminal equipment characteristics and hardware level with AI algorithms in the current environment is helpful to reduce the load caused by the server mounting of the ISP and costs.
HUBUNGAN KUALIFIKASI GURU DENGAN PENGELOLAAN KELAS DALAM PROSES PEMBELAJARAN BAHASA INDONESIA DI SMA NEGERI KABUPATEN KERINCI

The purpose of this study is to determine whether there is a relationship between teacher qualifications and classroom management in the Indonesian language learning process in High School of Kerinci Regency. Based on observations, classroom management of students who are carrying out Field Teaching Practice assignments is very much different from teachers who are experienced in the learning process. This study uses a quantitative approach to the type of ex post facto research. Test requirements analysis used normality and linearity test. Data analysis techniques used normality test and linearity test with calculations using SPSS version 24.00 for windows. The results showed a relationship between teacher qualifications and classroom management in the Indonesian language learning process in High School of Kerinci Regency. It is known that the pearson correlation 0,920 and value sig. (2-tailed) = 0,009 < 0,05. That means teachers who have high qualifications have high grade management abilities; conversely, teachers who have low qualifications will have low classroom management abilities too.
Fraudulent Practices in Dispensing Units and Remedies

Growth of Artificial Intelligence and its rational thought “doing things right” makes handling fraudulent detection practices by implementing Machine Learning and Deep Learning methods. The detection needs to analyze regular patterns with its anomalies that are easy and speedy manner by machine than human cognitive process. The humans perceive and predict suspicious situation but machines analyze and detect. Analyzing regular patterns to anomalies enable machine to detect rationally than human inspections in various data. Hence human cognition capabilities incorporating in machine is trend of technology to prevent fraudulent practice. This work explores re-engineering on discovering fraudulent practice in dispensing unit. Initially short delivering is established, understand dispensing unit in the retail outlet of Petroleum products in responding to short volume, which is used for fraudulent practice and triggering methods. Then explored concepts are structured as theory for the short delivery which is to propose the secure system to prevent fraud.
Symbolic Violence in Children’s Stories: Content Analysis in Bobo Magazine

The upper-class dominates various social spaces in society, including children’s stories. Children’s stories as a means of socializing values also participate in socializing upper-class habitus in the storyline. This study aims to describe the children’s habitus as narrated in short stories published in Bobo magazine. The method used in this study is the quantitative content analysis method and critical discourse analysis. This study’s object is about 174 short stories published in Bobo magazine from January 2019 to August 2020, of which 110 stories were taken randomly as samples. The results show that most of the children’s habitus narrated in the stories were upper-class children’s habitus, reaching out to 87 or 79.1% of all stories. Meanwhile, lower-class children’s habitus was found in 30.9% of all stories. The habitus of upper-class children featured in the story consisting of go on an excursion, luxury living, own electronic goods, own expensive good, wearing nightgowns, reading, and writing. On the other side, the habitus of lower-class children habitus featured in the story consisting of playing traditional games, living in poverty, and doing lower-class work. In conclusion, the upper-class children’s habitus appears more dominantly within short stories in Bobo magazine. This study’s results are expected as recommend to parties related to children’s stories publication to present more balanced stories.
Reccomendations on Selecting The Topic of Student Thesis Concentration using Case Based Reasoning

Case Based Reasoning (CBR) is a method that aims to resolve a new case by adapting the solutions contained in previous cases that are similar to the new case. The system built in this study is the CBR system to make recommendations on the topic of student thesis concentration. This study used data from undergraduate students of Informatics Engineering IST AKPRIND Yogyakarta with a total of 115 data consisting of 80 training data and 35 test data. This study aims to design and build a Case Based Reasoning system using the Nearest Neighbor and Manhattan Distance Similarity Methods, and to compare the results of the accuracy value using the Nearest Neighbor Similarity and Manhattan Distance Similarity methods. The recommendation process is carried out by calculating the value of closeness or similarity between new cases and old cases stored on a case basis using the Nearest Neighbor Method and Manhattan Distance. The features used in this study consisted of GPA and course grades. The case taken is the case with the highest similarity value. If a case doesnt get a topic recommendation or is less than the trashold value of 0.8, a case revision will be carried out by an expert. Successfully revised cases are stored in the system to be made new knowledge. The test results using the Nearest Neighbor Method get an accuracy value of 97.14% and Manhattan Distance Method 94.29%.
What is Quantum Computing and How it Works

Companies such as Intel as a pioneer in chip design for computing are pushing the edge of computing from its present Classical Computing generation to the next generation of Quantum Computing. Along the side of Intel corporation, companies such as IBM, Microsoft, and Google are also playing in this domain. The race is on to build the world’s first meaningful quantum computer—one that can deliver the technology’s long-promised ability to help scientists do things like develop miraculous new materials, encrypt data with near-perfect security and accurately predict how Earth’s climate will change. Such a machine is likely more than a decade away, but IBM, Microsoft, Google, Intel, and other tech heavyweights breathlessly tout each tiny, incremental step along the way. Most of these milestones involve packing more quantum bits, or qubits—the basic unit of information in a quantum computer—onto a processor chip ever. But the path to quantum computing involves far more than wrangling subatomic particles. Such computing capabilities are opening a new area into dealing with the massive sheer volume of structured and unstructured data in the form of Big Data, is an excellent augmentation to Artificial Intelligence (AI) and would allow it to thrive to its next generation of Super Artificial Intelligence (SAI) in the near-term time frame
Perancangan Kebutuhan Jaringan Wifi Untuk Mendukung Proses Belajar Mengajar Pada Universitas Di Era 4.0

Technological developments are so rapid in various fields, one of which is in the field of education. Nowadays we can get information, news, knowledge with the internet. In education, increasing knowledge is very important, with the internet we can get the latest scientific knowledge information from journals, modules, digital books from various parts of the world with just a gatget or laptop. To support these activities, it must be with good technology infrastructure, if the ratio between users and infrastructure is not balanced, conges will occur, where the available bandwidth cannot cover users who are connected to the internet, resulting in slow connections. Currently the WIFI network infrastructure at the University of 17 August 1945 Cirebon needs additional access points and additional bandwidth, because when user is connected to WIFI network increase conges occur, and there are several places that are far from the access point location. in network design there are two modeling were used that calculation of bandwidth capacity based on the number of users with three scenarios aksess speed of 0.5 Mbps, 1 Mbps, 2 Mbps and spacious area. The results obtained from modeling based on user capacity, the required access speed of 141.2 Mbps, 282 Mbps and 565 Mbps.The results obtained are calculated based on the user's capacity, the number of access points is 25 Ap and 14 Ap on the calculation based on the area.
VIII Chessboard problems

67. A large number of relations between the vertices or cells of a chessboard are represented by chess pieces.
Limitations of Applying the Data Compression Method to the Classification of Abstracts of Publications Indexed in Scopus

The paper describes the limitations of applying the method of classification of scientific texts based on data compression to all categories indicated in the ASJC classification used in the Scopus bibliographic database. It is shown that the automatic generation of learning samples for each category is a rather time-consuming process, and in some cases is impossible due to the restriction on data upload installed in Scopus and the lack of category names in the Scopus Search API. Another reason is that in many subject areas there are completely no journals and, accordingly, publications that have only one category. Application of the method to all 26 subject areas is impossible due to their vastness, as well as the initial classification of Scopus. Often in different subject areas there are terminologically close categories, which makes it difficult to classify a publication as a true area. These findings also indicate that the classification currently used in Scopus and SciVal may not be completely reliable. For example, according to SciVal in terms of the number of publications, the category “Theoretical computer science” is in second place among all publications in the subject area “Mathematics”. The study showed that this category is one of the smallest categories, both in terms of the presence of journals and publications with only this category. Thus, many studies based on the use of publications in ASJC may have some inaccuracies.
Psychological and pedagogical foundations for interaction technologies implementation at the university

The technological approach necessitated the development of professional competence of students as the main educational goal. Professional competence is developed only in the process of active activity and constant of students. Therefore, higher education institutions should implement various technologies of in their work, which are today one of the most effective in this process. The purpose of the article is to highlight psychological and pedagogical foundations of technologies implementation at the University. In the article is considered as a basic concept of pedagogical psychology. The authors identified the components of the category interaction and identified educational technologies that are responsible for the development of each component. It is noted that technologies interact with each other and produce a positive effect on the development of professional competence of students, organizing effective process of students’ interaction. A survey of students and teachers on the most suitable, in their opinion, technologies for organization of effective is presented. The received answers allowed allocating technologies which cause interest both at teachers and at students.
D5.3 Report on the First Synchronisation Force Workshop

This is the report of the FAIRsFAIR Synchronisation Force workshop organised in Budapest, Hungary on 25th November 2019 in conjunction with the EOSC Symposium. It highlights the points discussed by stakeholders from the FAIRsFAIR project, EOSC Working Groups, and other associated EOSC representatives including those from (among others) the European Commission, INFRAEOSC5 projects, and the FAIRsFAIR European Group of FAIR Champions. The objective of the workshop was to open dialogue between Synchronisation Force members and relevant stakeholders, to discuss common challenges and priorities, and to begin to evaluate the progress towards and feasibility of reaching common goals.
CoMoGCN: Coherent Motion Aware Trajectory Prediction with Graph Representation.

Forecasting human trajectories is critical for tasks such as robot crowd navigation and autonomous driving. Modeling social interactions is of great importance for accurate group-wise motion prediction. However, most existing methods do not consider information about coherence within the crowd, but rather only pairwise interactions. In this work, we propose a novel framework, coherent motion aware graph convolutional network (CoMoGCN), for trajectory prediction in crowded scenes with group constraints. First, we cluster pedestrian trajectories into groups according to motion coherence. Then, we use graph convolutional networks to aggregate crowd information efficiently. The CoMoGCN also takes advantage of variational autoencoders to capture the multimodal nature of the human trajectories by modeling the distribution. Our method achieves state-of-the-art performance on several different trajectory prediction benchmarks, and the best average performance among all benchmarks considered.
Multisource Data-Driven Visual Analysis of Urban Crowd Travel

Abstract Many functional areas have been formed in the development of the city, and the gathering of taxis can basically reflect the travel situation of the crowd. Combining urban functional areas and taxi GPS data to analyze crowd travel conditions can provide decision support for the construction of smart cities. Therefore, this paper analyzed the travel situation of crowd in Changsha urban area based on multi-source data. First, this paper clusters the distribution of public transit stations in Changsha, and then imports the geographic location information of the cluster centers into the Voronoi diagram in ArcGis to divide the urban area of Changsha. Then the divided areas and Point of interest (POI) data are counted and analyzed to obtain the functionality of each area. Finally, the taxi GPS data is clustered according to the time period, and the cluster center is mapped to the urban functional area, to analyzed the crowd clustering situation of each functional area in Changsha in different time periods.
CLOUD MIGRATION STRATEGY: REVIEW &amp; RECOMMENDED STRATEGY PROCESS MODEL FOR COMMUNICATION AND IT MINISTRY OF AFGHANISTAN

With regard to the increasing spread of information technology in the world, access to this technology is of great importance.Having an appropriate process for migrating, identifying and ranking activities to prepare and perform the migration design in the organization, prevents the failure of the performance in organizations.Today, there are lots of migration processes in review of literature and this will confuse the managers to choose the most appropriate process for their organization.This article studies the presented processes of migration to the cloud computing environment by presenting novel factors.It also attempts to introduce an appropriate framework to select and model the most efficient process on migration to the cloud computing environment.So that organizations do not have a concern to choose the best migration process and IT managers are able to select the appropriate process for their organizations quickly and with no confusion.This paper is intended to introduce a migration strategy process model which best suits for the current situation of communication and IT ministry of Afghanistan.This paper contains an introduction on cloud computing and cloud migration, literature review of the related works done on migration strategies, also includes some information about Afghanistan communication & information technology ministry, A methodology of selecting and modeling recommended migration strategy, modeling the recommended cloud migration strategy process for Afghanistan communication & IT ministry, conclusion and references list.