Reviewerly/exHarmony huggingface dataset:
Monitoring of problems of organization and conduct of pedagogical practice of university students

The authors present the importance of monitoring the state of pedagogical practice as an integral part of the system of future teacher training, as the study of factors that affect the quality of pedagogical practice provides objective information about the real situation, problems and ways to improve practical training. The authors consider the quality of organization and conduct of student practice as one of the priorities of the university, determine the types of pedagogical practice, characterize the stages of its implementation at Nizhyn Mykola Gogol State University. The authors analyzed the research on the problem of improving pedagogical practice. It is noted that researchers focus on intensifying the interaction between higher and secondary education institutions in the process of organizing and conducting pedagogical practice of students, exercising systematic control over the process and results, its development of integration mechanisms that ensure effective interaction of higher education with employers. The article presents the results of the study of the state of practical training of students, carried out by the Center Accreditation and Licensing of Educational Activities, Monitoring the Educational Quality at Nizhyn Mykola Gogol State University. Monitoring of the effectiveness of pedagogical practices shows us the proper level of their passage by students and provides an opportunity to outline the priority tasks as an important educational stage in the formation of a qualified teacher. The authors note that the main task is to improve the curriculum in terms of practical training and identify of the main positions that need to be changed: the content and forms of introductory practice; number of tasks and volumes and forms of reporting; guidance from university teachers.
Internet of Things (IOT)-Data Security Challenges and Solutions

Our everyday life starts with an electronic device with internet connectivity.Today every object of our lives is relying on internet and the powerful data capability which transforms the way we work and live.In this pandemic situation of COVID-19 every company/business/organizations/educational institution and many more are working only with the help of internet connectivity and new emerging technologies.Internet of Things (IoT) is one such technology that has gained as a popular research concept from recent years and it is playing a vital role in the pandemic situation of COVID-19 by incorporating technological, business and social scenarios.As there is an increase in the usage of IoT devices and more IoT ecosystems there by facing many challenges like technical, business, societal and legal.Among the all-Data Security is being the most prominent one.This article discusses different ways the data can be protected on IoT devices by which the enterprises can successfully ensure secure data on IoT devices.
Cross-Lingual BERT Contextual Embedding Space Mapping with Isotropic and Isometric Conditions

Typically, a linearly orthogonal transformation mapping is learned by aligning static type-level embeddings to build a shared semantic space. In view of the analysis that contextual embeddings contain richer semantic features, we investigate a context-aware and dictionary-free mapping approach by leveraging parallel corpora. We illustrate that our contextual embedding space mapping significantly outperforms previous multilingual word embedding methods on the bilingual dictionary induction (BDI) task by providing a higher degree of isomorphism. To improve the quality of mapping, we also explore sense-level embeddings that are split from type-level representations, which can align spaces in a finer resolution and yield more precise mapping. Moreover, we reveal that contextual embedding spaces suffer from their natural properties -- anisotropy and anisometry. To mitigate these two problems, we introduce the iterative normalization algorithm as an imperative preprocessing step. Our findings unfold the tight relationship between isotropy, isometry, and isomorphism in normalized contextual embedding spaces.
On the Importance of Regularisation & Auxiliary Information in OOD Detection.

Neural networks are often utilised in critical domain applications (e.g.~self-driving cars, financial markets, and aerospace engineering), even though they exhibit overconfident predictions for ambiguous inputs. This deficiency demonstrates a fundamental flaw indicating that neural networks often overfit on spurious correlations. To address this problem in this work we present two novel objectives that improve the ability of a network to detect out-of-distribution samples and therefore avoid overconfident predictions for ambiguous inputs. We empirically demonstrate that our methods outperform the baseline and perform better than the majority of existing approaches, while performing competitively those that they don't outperform. Additionally, we empirically demonstrate the robustness of our approach against common corruptions and demonstrate the importance of regularisation and auxiliary information in out-of-distribution detection.
PENGAJARAN SASTRA DI MADRASAH IBTIDAIYYAH

Literature as a lesson in school is material that has an important role to trigger the creativity of students. The reason is that literature has a human side that can add insight and knowledge to readers. Mechanically, the teaching of literature in schools can achieve three main learning abilities, namely affective abilities, cognitive abilities, and psychomotor abilities. Ability is a basic human ability that is related to one's emotions. Cognitive abilities are abilities possessed by humans based on thought. Psychomotor ability is the ability to manage the psychological side to survive various problems. The implementation, literature and language learning is carried out in an integrated manner. BI learning activities in the classroom, students must be trained to use more language to communicate, rather than being required to learn more about language. While the teaching of literature, is intended to improve the ability of students to enjoy, appreciate, and understand literature. Knowledge of literature is only a support in appreciating.
On the subject of serial killer. Psychological assessment from the handwriting

From research conducted since 2010, at the Chair of Forensic Psychopathology directed by prof. Vincenzo Mastronardi of the Sapienza University of Rome and in the context of the teaching of Psychography at the Masters in Criminology and in more scientific fields, the attention focus was addressed, on the research related to the psychographological examination on the subject of Serial Killer (subject of this article ), Sex Offenders, Stalker, Classic Mass Murder, Family Mass Murder, Mothers Figlicide and other criminal phenomenologies with the intent to highlight where existing, characteristics and graphological indices, similar to the various subjects responsible for the same type of crime and therefore possible 'patterns graphological 'to be highlighted as a symptomatic graphic imprint of a certain' behavioral model '. Proceeding with the graphological comparison, albeit between different personality structures, some peculiarities were found such as, for example, the signs that lead to the aggressiveness, a typical distinctive trait among others, of the Serial Assassins, including certain deficits in the affective-sexual area.Interesting what emerged from the aforementioned study. Considering that Psychography is an effective indicator of the personality structure, therefore representing an excellent tool for revealing the deepest dynamics of the individual both at an intrapsychic and interpersonal level, (without any diagnostic hypothesis), writing can be considered as indicated above, an imprint graphics of the "individual psychism" and the percentage of certainty is about 80%, where, however, there is no possibility of simulating or dissimulating, for a series of specific factors. Research in the field of Serial Killers has already oriented towards the tangible manifestation of aggressive instances, significant problems in the affective-sexual sphere, as well as a particularly accentuated narcissistic trait. Serial killings are personal in nature and the application of behavioral analysis by means of the psychographological reading key directs us to understand the deeper dynamics that triggered in the subject, thus also answering some famous questions of criminology such as, for example, why and what led him to commit such crimes.
Argue to Learn: Accelerated Argumentation-Based Learning

Human agents can acquire knowledge and learn through argumentation. Inspired by this fact, we propose a novel argumentation-based machine learning technique that can be used for online incremental learning scenarios. Existing methods for online incremental learning problems typically do not generalize well from just a few learning instances. Our previous argumentation-based online incremental learning method outperformed state-of-the-art methods in terms of accuracy and learning speed. However, it was neither memory-efficient nor computationally efficient since the algorithm used the power set of the feature values for updating the model. In this paper, we propose an accelerated version of the algorithm, with polynomial instead of exponential complexity, while achieving higher learning accuracy. The proposed method is at least 200 times faster than the original argumentation-based learning method and is more memory-efficient.
FLOOD CONTROL OF LAMONG RIVER, GRESIK DISTRICT

&#x0D; &#x0D; &#x0D; &#x0D; Lamong River is located in East Java Province. The discharge of the Lamong River tends to be large, but it cannot be drained properly, so that the river overflows and causes Gresik Regency to experience flooding almost every year.&#x0D; The existing condition of the Lamong River is not able to accommodate the flood discharge. Therefore, it is planned to build a polder in the flood-prone areas of the Lamong River to accommodate the discharge that occurs. Polder on the Lamong River is planned with an entry discharge into the retention pool of 85% using a pump with a suction capacity of 5 m3 / s and 3 m3 / s. The dimensions of the Polder pond used in pond I are 530 m long, 530 m wide, 8 m deep, II pool size 540 m long, 540 m wide, 8 m deep, pool size III is 550 m long, 550 m wide, depth 8.5 m, the size of pool IV is 580 m long, 580 m wide, 9 m deep, for V pool size is 600 m long, 600 m wide, 9 m deep, and for pool VI size is 600 m long, 600 m wide m, 9 m depth. Each pool has 3 sluice gates with a size of 2 m per door with a door opening height of 1.32 m and a drain dimension of 3 m long, a channel width of 8 m, and a channel height of 3.46 m.&#x0D; &#x0D; &#x0D; &#x0D;
그래프마이닝을 활용한 빈발 패턴 탐색에 관한 연구

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.
Multi Agent System for Machine Learning Under Uncertainty in Cyber Physical Manufacturing System

Recent advancements in predictive machine learning has led to its application in various use cases in manufacturing. Most research focused on maximising predictive accuracy without addressing the uncertainty associated with it. While accuracy is important, focusing primarily on it poses an overfitting danger, exposing manufacturers to risk, ultimately hindering the adoption of these techniques. In this paper, we determine the sources of uncertainty in machine learning and establish the success criteria of a machine learning system to function well under uncertainty in a cyber-physical manufacturing system (CPMS) scenario. Then, we propose a multi-agent system architecture which leverages probabilistic machine learning as a means of achieving such criteria. We propose possible scenarios for which our proposed architecture is useful and discuss future work. Experimentally, we implement Bayesian Neural Networks for multi-tasks classification on a public dataset for the real-time condition monitoring of a hydraulic system and demonstrate the usefulness of the system by evaluating the probability of a prediction being accurate given its uncertainty. We deploy these models using our proposed agent-based framework and integrate web visualisation to demonstrate its real-time feasibility.
Blockchain-based zakat collection to overcome the trust issues of zakat payers

Zakat is one of the five pillars in Islamic principles, subject to all qualified Muslims which requires them to contribute a proportion of one of their income or the wealth possession for the welfare of the Muslim community. In Malaysia, Lembaga Zakat is the organization appointed by each state government to manage the zakat transactions. The zakat transactions can be done either through online transactions or over the counter. However, there are issues related to zakat management such as the zakat payers are not satisfied with the zakat distribution, and there are claims for lack of transparency in the zakat management which lead to trust issues among zakat payers to contribute their zakat through Lembaga Zakat. One way to respond to the issues is by having transparency in the zakat transaction by applying a trust model such as blockchain in zakat management. Thus, this project aims to use blockchain technology and its main component, smart contract, as the base of the zakat collection and utilize Ethereum as the platform.
Persepsi Penggunaan Media Pembelajaran Berbasis Online Mahasiswa Pendidikan Geografi Universitas Negeri Semarang Menjelang Pandemi Covid-19/ Perception of the Use of Online-Based Learning Media by Geography Education Students, Semarang State University Ahead of the Covid-19 Pandemic

The occurrence of the COVID-19 outbreak caused a change in the learning system from face-to-face (offline) learning to online-based learning using various types of learning media based on modern and up-to-date technology so that with this occurrence students must try to adapt. The objectives of this study are (1) to describe the types of online learning media used to support the implementation of geography education student lectures, (2) to analyze the strengths and weaknesses of students' favorite online based media based on their perceptions, (3) to formulate appropriate strategies to make effective use of media. online based on the students' perceptions. This research method is a survey with qualitative descriptive data analysis techniques obtained from filling out a closed questionnaire and an open questionnaire using a purposive sample. The questionnaire was filled in by geography education students who experienced the learning process in the even semester (semester 2-6) Semarang State University in 2020 and then described it. Based on the research results, it can be concluded that (1) the online learning media used are WhatsApp Group, Facebook Group, Facebook Live, Website, Zoom, Skype, Discord, Youtube Live, Instagram Live, Google Classroom, Quiz, Telegram Group, Elena, Hangout ( 2) favorite online learning media for geography education students in the even semester of 2020 are Discord, WhatsApp Group, Zoom, Elena, Google Classroom and Instagram live, and 3) strategies to make effective use of online learning media are 1) complementing other potential online learning media and can cover the weaknesses that are owned, 2) first assess and analyze whether the use of the selected online learning media can be implemented with the method or learning model according to the plan. 3) collect data and analyze the dominance of student learning styles as a basis for determining the selection of online learning media.Keywords: Perception; Learning Media; Geography; COVID-19
«ДРУГОЙ» ПОСТКАПИТАЛИЗМ. РЕВОЛЮЦИЯ ЛИЧНОСТИ И НОВАЯ АНТАГОНИСТИЧЕСКАЯ ОБЩЕСТВЕННАЯ ФОРМАЦИЯ

The article considers the transition to a post-capitalist society as a social revolution of personality. The author proves that such a revolution has been taking place for a relatively long time: as a process of the gradual rise of the personaliat – a stratum of popular creative persons (“people with personality”). Simultaneously, it is argued that in the emerging social relations, within which the personaliat dominates, there are all the signs of an antagonistic socioeconomic formation: social production is concentrated on the creation of competitive and excluded goods (personality production); limited resources are involved in the production of the most demanded goods (attention); access to a key limited resource provides significant advantages that contribute to the formation of a ruling class (the personaliat); the “higher” strata exploit the “lower” (“appropriation” and “theft” of personality); the interests of the ruling class are at odds with the interests of the exploited classes. Finally, it is shown that any antagonistic socioeconomic formation is characterized by a multitude of institutional incarnations, and therefore the domination of the personaliat can be challenged by representatives of the impersonaliat who question the normative value of the category of “personality”. DOI: 10.17072/2218-1067-2021-2-27-36
Use of a Blockchain-Based Marketplace to Incentivize Participation in Virtual Clinical Trials

There is an emerging need for advancements in how clinical trials are conducted in the current pandemic situation. Healthcare institutions are moving towards using digital technologies to avoid physical interactions between doctors and clinical trial participants. However, difficulties in recruiting and retaining participants are still prevalent. To overcome this issue, an incentive system that can be trusted by doctors as well as trial participants is required. The authors present a detailed report of Cashish, a blockchain-based incentivization system that rewards trial participants in the form of cryptocurrency tokens that they can utilize in an online marketplace that is also backed by the same blockchain. Usage of blockchain technology to provide research participation incentives eliminates the need for trust systems and ensures transparency between doctors and clinical trial participants, while ensuring participant anonymity.
Analisis Sentimen terhadap Penanggulangan Bencana di Indonesia

Disasters have become a part of human life, whether natural disaster, non-natural disaster or from human error, which is causes fatalities, environmental damages, property losses, or psychological impact, especially in Indonesia. The National Agency for Disaster Countermeasure (BNPB) is the Indonesian board for natural disaster affairs. For each region, Badan Penanggulangan Bencana Daerah (BPBD) as for as the regional disaster management. Social media has become a part of everyday life for people nowdays. The purpose of this research is to find out the public reaction, with classification positive, neutral or negative opinion to the disaster management in Indonesia from Twitter. One text mining method from Natural Processing Language (NLP) is sentiment analysis. Sentiment analysis applied to analyze data with public opinion as the decision-making support. Based on the research, there were 23,53 % positive tweets, 57,35 % neutral tweets and 19,12 % negative tweets. From the result, mostly Indonesian have neutral opinion about the disaster management. The result also displayed in histogram, pie chart and word cloud.
USING DEEPLY-DIGITAL CURRICULA FOR SEAMLESS LEARNING: EMPIRICAL FINDINGS &amp; SCALING UP

Appears in: EDULEARN21 Proceedings Publication year: 2021Page: 3013 (abstract only)ISBN: 978-84-09-31267-2ISSN: 2340-1117doi: 10.21125/edulearn.2021.0640Conference name: 13th International Conference on Education and New Learning TechnologiesDates: 5-6 July, 2021Location: Online Conference
Разработка интегрированных уроков по математике и информатике для учащихся профильных 10-11 классов

The article is based on the experience of teaching mathematics and computer science in professional classes and is devoted to the topic “Interdisciplinary connections of mathematics and computer science using ICT”, presented in the form of integrated lessons. The combination of information technology and innovative pedagogical methods can increase the efficiency and quality of educational, enhance the adaptability of the education system to the levels and characteristics of students' development
교사와 학부모의 교육혁신의 의미찾기와 주체되기에 관한 연구

This study analyzed Interview teachers, parents of innovation school through qualitative research process. It purported to understand how teachers and parents experience educational innovation. Main results were as follows. First, the experiences of education innovation of teachers and parents were derived as two experiences of finding meaning and being a subject. For teachers, ‘innovation is a task’, then gradually becomes ‘a job that changes education’ in the relationship between people, and the concept of education innovation of parents is a conceptualization process in which educational innovation is perceived as ‘something else”. Second, as a result of analyzing the process of becoming a subject, parents often stop at the line of “accepting to be subject of education”, whereas teachers refer to themselves as “the subject with responsibility and burden”. Through this, the reconceptualization of educational innovation, the policy to develop the expertise of each subject of education, and the need for re-examination and support for teachers who are the levers were discussed.
APLIKASI AUGMENTED REALITY PENGENALAN BENDAMUSEUM SULTAN MAHMUD BADARUDDIN II PALEMBANGBERBASIS UNITY

Augmented Reality (AR) is a technology that combines two-dimensionaland three-dimensional virtual objects into a real three-dimensionalenvironment, then projects objects made with this technology to be moreinteresting and interactive when its application, the use of AR in museums isone of the AR implementations in the field of education and entertainment.Sultan Mahmud Badaruddin II (SMB II) Museum in Palembang has a smallaverage number of visitors per month. This is due to the lack of publicawareness to know the culture of their own area and how to explore themuseum is very boring. The purpose of this paper is to make an AR applicationto help visitors get information about collections of objects in the SMB IImuseum easily, with the display information of museum collection objectsmore attractive to visitors and hopefully this application can increase visitorinterest in exploring the SMB II museum. To build this application, Vuforia aimsto register a license from QR Code and Unity 3D to create a 3D design andbuild a museum object recognition application. The output of this applicationin the form of information and visualization of objects in the museum of SultanMahmud Badaruddin II.