Reviewerly/exHarmony huggingface dataset:
Foundations of Bayesian Learning from Synthetic Data.

There is significant growth and interest in the use of synthetic data as an enabler for machine learning in environments where the release of real data is restricted due to privacy or availability constraints. Despite a large number of methods for synthetic data generation, there are comparatively few results on the statistical properties of models learnt on synthetic data, and fewer still for situations where a researcher wishes to augment real data with another party's synthesised data. We use a Bayesian paradigm to characterise the updating of model parameters when learning in these settings, demonstrating that caution should be taken when applying conventional learning algorithms without appropriate consideration of the synthetic data generating process and learning task. Recent results from general Bayesian updating support a novel and robust approach to Bayesian synthetic-learning founded on decision theory that outperforms standard approaches across repeated experiments on supervised learning and inference problems.
STUDI KETINGGIAN KOLAM RETENSI SIMPANG POLDA PALEMBANG UNTUK LANGKAH PENENTUAN KEBIJAKAN

Simpang Polda retention pond is an alternative flood control construction which is designed to temporarily hold exceeding water flow during rainfall in the vicinity of Simpang Polda, in order to avoid or reduce flood in the area. Retention ponds are prone to sedimentation due to garbage and other materials settling down in the bottom of the pond, which in turn causing reduction of total volume of water it can contain. To ensure that the pond has enough volume, depth measurements were done so that the pond can function as intended. Boat robots from previous research in 2019 and 2020 were utilized as the method to measure the depth of the retention pond. The boat robots mapped the depth of the whole pond area with the help of remote control and single beam sensor. Measurement result shows that the Simpang Polda retention pond has an average depth of 2.245 m. Based on this finding it is suggested that the local government water resource management agency (Dinas PUPR Dept. PSDA) to follow up with the appropriate sediment removal procedures to return the pondâ€™s depth back to the original value when it was constructed
НАУКОВІ ЗАСАДИ ЗАСТОСУВАННЯ ТЕХНОЛОГІЙ КОМП’ЮТЕРНОГО МОДЕЛЮВАННЯ У ФАХОВІЙ ПІДГОТОВЦІ УЧИТЕЛІВ ТЕХНОЛОГІЙ

Potential possibilities of teaching methods using computer-based learning tools based on computer modeling technologies, in connection with the emphasis on the technology teacher thinking development, which is three-component in its structure, subject to designing on the basis of pedagogical theory of teaching based on the interconnection and interaction of conceptual, figurative and active components of thinking can provide a higher level of implementation of such traditional requirements as science, visibility, activity and consciousness of learning as well as the unity of educational developmental and educational training functions.
Grouping of Success Levels in E-Learning Learning Factors: Approaches with Machine Learning Algorithm

The purpose of this study is to obtain the results of the modeling process on grouping the results of student learning, and to produce student success rates, while to find the results of the accuracy level of student learning success based on E-Learning with the Support Vectore Machine (SVM) method. In this grouping, there are 5 clusters. Furthermore, the process of counting can be as many as 2 iterations, namely getting the final result in the form of Cluster-1 with a total of 10 students, cluster-2 with a total of 45 students, cluster-3 with a total of 22 students, cluster 4 with a total of 13 students, and the next is cluster-5 with a total of 19 students. Then the results of the resulting process with a total of 5 types of clusters, namely from students who get the highest results to the lowest. In addition, this study also looks for the level of accuracy in e-learning student learning processes using the Support Vectore Machine (SVM) method, the accuracy results obtained are 90.91%, while the AUC results are 82.81%. then the value of the calculated accuracy rate can be classified as accuracy with the predicate result that is good.
Artificial Intelligence and the dark side of management

Ideas about the introduction of Artificial Intelligence (AI) to business are regularly being associated with modern, agile and participative approaches of management and leadership. But in everyday business life the dark side of management continues to remain influential. Leaders that show personality traits like machiavellianism, narcissism, psychopathy and sadism are commonplace. This viewpoint shows that the combination of augmentation and automation that AI can offer makes it technologically feasible to scale dark managerial methods and to eliminate competition. It concludes by recommending further research in support of the Human Movement (Hamel and Zanini, 2018).
Pelaksanaan pembelajaran tematik pada pembelajaran jarak jauh di kelas V

This reseach aims to: (1) describe Thematic Learning in Distance Learning (e-learning) (2) describe the school's efforts to optimize Thematic Learning in Distance Learning (e-learning). This research uses a qualitative approach with a case study method. The research subjects involved were the principal, teachers, students, and parents of grade V SD N Tegalayu No. 96 Surakarta. Research data collection techniques using observation and interviews. The validity of the research data used triangulation techniques. Data were analyzed using an interactive model, consisting of data reduction, data presentation, and drawing conclusions. As a result, Thematic Learning in Distance Learning goes according to schedule. Five days a week. The implementation of learning includes the planning stage, the implementation stage, and the evaluation stage. The conclusions of the researchers are: (1) the implementation of thematic learning in distance learning at SD N Tegalayu No.96 Surakarta has run according to the schedule and (2) Efforts in implementing Thematic Learning in Distance Learning involve the efforts of the principal, teachers, students, and parents of students in improving learning optimization. Keywords : thematic learning, e-learning, distance education
Co-creation of Virtual Reality Re-Usable Learning objectives for 360° video scenarios for the surgical excision of skin lesion

This short paper describes an educational scenario using a 360° video for the surgical excision of a skin lesion. This scenario, developed in the context of the CoViRR Erasmus+ project, offering new insights for the digital integration in learning and teaching.
Meta-Learning for Cross-Domain One-Shot Object Detection

Computer Vision research today is focusing more and more on deep learning, because it is the machine learning paradigm that produces the best results. The main feature is that we can train an end-to-end network both to extract features from the data and to create models able to exploit them to solve certain tasks. In this way there is no need to manually extrapolate the right characteristics from the data to pass to the final model, thus overcoming the problems of shallow approaches and guaranteeing results with a much lower error rate. The main limitation is that deep networks have many parameters and therefore, in order to be trained, they need a large amount of labelled data, which is not always available. Another big problem is that many models are trained from scratch for certain tasks, using a fixed learning algorithm, and this means that they are unusable for other applications. An alternative paradigm that is attracting a lot of interest in research is Meta-Learning, also known as learning to learn. Its goal is to make the network capable of modeling by itself the learning algorithm. In practice, the network is meta-trained on a large number of different subtasks, producing a model ready to be finetuned on a small amount of data and able to generalize to any new task. The focus of this master thesis work is to use Meta Learning for cross-domain analysis. The main challenge in this field is that models trained on a certain domain are mostly unusable on domains never seen before, a problem known as domain shift. More specifically, our objective is to create a visual object detector able to adapt on each test sample before performing predictions. To take advantage of unlabeled target samples it is possible to exploit the power of self-supervised learning by enriching the standard object-detector with the auxiliary objective of recognizing rotations applied to the objects. Since it does not need any manual annotation, this simple second task runs seamlessly on each single test image, helping the network to adapt to the style of the new instance. The core step of this work is to code the logic of meta-learning within the self-supervised rotation task. We build over an existing method that deals with one-shot unsupervised domain adaptation and show that meta-learning allows to adapt more quickly to the various samples, producing good results in the inference phase. In this way we get the best of both worlds and establish the new state-of-the art in detection for social media monitoring and autonomous driving scenarios.
A Creative Library Management in Digital Era in Indonesia from Psychopragmatic Perspective

Library management is a center controlling libraries in a digital era. Libraries need creative managers to get power in carrying out planning, implementation, evaluation, and follow-up using a psychopragmatic perspective. The problems are (1) how creative library management in the digital era in Indonesia is, (2) how to strengthen librarians’ competencies in managing a creative library in the digital era, (3) how to create creative strategies and information technology-based innovation in managing creative libraries in Indonesia, and (4) how the effort of creative library management in understanding characteristics and objectives of library users using the psychopragmatic approach. The method was descriptive qualitative with the psychopragmatic approach. The data collection techniques used interviews, observation, and active participation to obtain the data. They were then analyzed by interactive techniques, in terms of a deductive technique to answer research problems. The result indicates that (1) the creative library management of digital era in Indonesia regarding psychopragmatic perspective is necessarily started by changing library managers’ and librarians’ mindset, (2) strengthening librarians’ soft skills is considered significant in this management, (3) this management certainly needs information technology-based creativity and innovation to provide various information literacies, and (4) this management needs psychopragmatic approach. Therefore, the creative library management in the digital era in Indonesia based on the psychopragmatic perspective is actualized and useful for librarians to support the acceleration of information and knowledge literacies in the industrial revolution 4.0 era.
English Track 학부유학생을 위한 한국어·한국문화 e-LEARNING 수업의 운영 사례 연구

Korean language education should be based on the characteristics and needs of learners. This study is a kind of case report on the design and operation of e-Learning Korean language and Korean culture class for undergraduate international students in English Track. This class has the following characteristics.- Online-based education, parallel with offline class, English Medium Instruction, fixed proportion of Korean culture education, and explicit teaching methods. In this study, 16 weeks of teaching content and process were presented and reported that learners’ perception of this class was generally positive, based on learner survey. Lastly, this study suggested the direction of improvement and expansion of this class in the future.
Mayank Yuvaraj: Cloud Computing in Libraries: Concepts, Tools and Practical Approaches. Berlin: De Gruyter, Saur, 2020 (Current Topics in Library and Information Practice). – XXII, 252 S., Ill. – ISBN 978-3-11-060586-0. € 89,85. Auch erschienen als E-Book (PDF und epub).

Article Mayank Yuvaraj: Cloud Computing in Libraries: Concepts, Tools and Practical Approaches. Berlin: De Gruyter, Saur, 2020 (Current Topics in Library and Information Practice). – XXII, 252 S., Ill. – ISBN 978-3-11-060586-0. € 89,85. Auch erschienen als E-Book (PDF und epub). was published on May 1, 2021 in the journal ABI Technik (volume 41, issue 2).
Telehealth as a health education tool in the fight against the new Coronavirus: a systematic review

INTRODUCTION: The COVID-19 epidemic started in 2019, leading to a World Public Health emergency. As a result, the typical evaluation of patients was limited, resulting in an increased demand for virtual activities, making it necessary to use resources to reach the general population. Telehealth has been a tool widely used in this period to increase the resolution of Primary Care and provide the strengthening of health services and care provided to the population. OBJECTIVE: To analyze the effectiveness of telehealth in the educational health process in combating COVID-19. MATERIAL AND METHODS: The review was initiated by the acronym PECOS. The inclusion criteria were studies published in 2020, descriptive and complete. Exclusion criteria were duplicates, review articles, letters to the editor or articles that do not address the topic. The articles were published in Pubmed, Science Direct, Scopus and Web of Science databases. The StArt tool was used to manage the articles and Zotero, the reference manager. The selected articles underwent quality analysis and risk of bias, based on the Newcastle Ottawa checklist and were sent for data extraction. RESULTS: Several countries have applied telemedicine and obtained favorable results, even though telehealth activities cannot replace contact with the patient, it can serve to reduce the workload of health professionals and offer remote clinical services, such as diagnosis and monitoring. The tool enables case management, intermediate activities, such as health education, premature access to patients, in addition to reaching vulnerable populations. For most patients, the platform can be used for emotional support, counseling and guidance, which includes computerization on prevention, analysis of conducts to be performed and the identification and execution of necessary interventions, in addition to monitoring the health study. Enabling cases that do not require instant treatment to avoid external contact and allow certain empowerment of knowledge by the individuals who are assisted. CONCLUSION: Telehealth became necessary and more used with the worsening of the world situation caused by COVID-19. Although those who use it face some problems, such as lack of necessary structure and lack of experience, the results are positive because it continues to be promising and effective to continue patient care. In addition, it can trigger a paradigm shift in the provision of health services and an alternative support for health education actions.
CLIMATE CHANGE DETECTION DIMENSIONALITY REDUCTION USING HADOOP WITH MAPREDUCE

Big data could be a term refers to a group of enormous quantity of knowledge which needs new technologies to form potential to urge price from it by analysis and capturing methodology. In each facet of human life, weather includes a heap of importance. It’s direct impact on every a part of human society or individuals. Correct analytics of weather collection, storing and process an oversized quantity of weather information is critical. Therefore a climbable information storage platform and economical or effective modification detection algorithms are needed to observe the changes within the setting. An existing or ancient information storage techniques and algorithms don't seem to be applicable to method the big quantity of weather information. within the planned system, a climbable processing framework that's Map-Reduce is employed with a temperature change detection rules that is Spatial accumulative sum algorithm and Bootstrap Analysis algorithm known as (FWRUT-Frequent Weather Record Ultra Metric Tree). This project presents, the big volume of weather information is keep on Hadoop Distributed File System (HDFS) and Map-Reduce rule is applied to calculate the minimum and most of climate parameters. Spatial Autocorrelation based mostly temperature change detection rule is planned to observe the changes within the climate of a selected town.
No-Regret Algorithms for Private Gaussian Process Bandit Optimization

The widespread proliferation of data-driven decision-making has ushered in a recent interest in the design of privacy-preserving algorithms. In this paper, we consider the ubiquitous problem of gaussian process (GP) bandit optimization from the lens of privacy-preserving statistics. We propose a solution for differentially private GP bandit optimization that combines a uniform kernel approximator with random perturbations, providing a generic framework to create differentially-private (DP) Gaussian process bandit algorithms. For two specific DP settings - joint and local differential privacy, we provide algorithms based on efficient quadrature Fourier feature approximators, that are computationally efficient and provably no-regret for popular stationary kernel functions. Our algorithms maintain differential privacy throughout the optimization procedure and critically do not rely explicitly on the sample path for prediction, making the parameters straightforward to release as well.
PENGEMBANGAN APLIKASI PENCARIAN GURU PRIVAT EDITING VIDEO BERBASIS ANDROID

The teacher (educator) is a guide in carrying out the teaching and learning process. Teachers usually have different tasks such as classroom teachers, subject teachers and private teachers. Private teachers usually provide material or teaching specifically to their students not formally like in school. There are types of private teachers according to the expertise of each teacher, one of which is a private video editing teacher. In Bandar Lampung it is very difficult to find information related to private video editing teachers, causing students who want to find private video editing teachers to find it difficult and time consuming. So in this study developed an Android-based application that can make it easier to find private video editing teachers in Bandar Lampung so that the search for private tutors is easier and faster. This application was developed using the extreme programming (XP) system development method where, this method can be in tune with changes in design and features with flexible handling. Based on usability testing, the average value was 82.5%, and it was in the good category.
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Análise de discursos em notícias sobre homofobia, racismo e sexismo em comentários de portais brasileiros de notícias

Posts with defamatory content or hate speech are constantly foundon social media. The results for readers are numerous, not restrictedonly to the psychological impact, but also to the growth of thissocial phenomenon. With the General Law on the Protection ofPersonal Data and the Marco Civil da Internet, service providersbecame responsible for the content in their platforms. Consideringthe importance of this issue, this paper aims to analyze the contentpublished (news and comments) on the G1 News Portal with techniquesbased on data visualization and Natural Language Processing,such as sentiment analysis and topic modeling. The results showthat even with most of the comments being neutral or negative andclassified or not as hate speech, the majority of them were acceptedby the users.
VUT Libraries: Faculty of Applied and Computer Sciences: Reference Management Software/Tools

This guide contains genral library information for the Faculty of Applied and Computer Sciences. Reference management software allows researchers to link to and correctly cite referenced works in their papers.
An Empirical Study of the Effect of IT-enabled Organizational Intangibles on Competitive Advantage and Performance

IT-enabled organizational intangibles have been identified as key drivers of potential business value, mainly superior customer orientation, synergy, and intellectual capital through embedded superior skills in knowledge assets in environmental changes appropriately. This study aims to examine the effect of IT-enabled organizational intangibles on competitive advantage and organizational performance during the time period (2014 - 2019) in the Jordanian banking sector. IT-enabled organizational intangibles of the respective banks can be practiced to generate a competitive advantage and improve performance. Additionally, the study contributes to knowledge by demonstrating how IT-enabled organizational intangibles as a resource could create a competitive advantage in light of the resource-based view (RBV) theory of the firm. Thus, to achieve the research objective, a quantitative approach using a questionnaire was employed to collect data from 16 Jordanian banks; the targeted population is 853 of the Jordanian banks' managers. The empirical results showed that there is a positive impact of IT-enabled organizational intangibles on the competitive advantage and performance through playing enabling functions by promoting/leveraging the organization's resources and capabilities. Another explanation is that in the context given, IT-enabled organizational intangibles are used to fulfill cost and demand synergies and provide flexibility to create competitive value, which in turn responds to market needs quickly.
Private optimization without constraint violations

We study the problem of differentially private optimization with linear constraints when the right-hand-side of the constraints depends on private data. This type of problem appears in many applications, especially resource allocation. Previous research provided solutions that retained privacy but sometimes violated the constraints. In many settings, however, the constraints cannot be violated under any circumstances. To address this hard requirement, we present an algorithm that releases a nearly-optimal solution satisfying the constraints with probability 1. We also prove a lower bound demonstrating that the difference between the objective value of our algorithm's solution and the optimal solution is tight up to logarithmic factors among all differentially private algorithms. We conclude with experiments demonstrating that our algorithm can achieve nearly optimal performance while preserving privacy.
Balancing Task Allocation in Multi-robot Systems Using adpK-Means Clustering Algorithm

Multi-robot systems are becoming more and more significant in industrial, where allocating tasks for every robot in a reasonable way is a tedious process. The current research mainly focused on reducing the distance between robots and tasks while ignoring the balance of workloads between robots. To address the aforementioned issues, this paper proposes an adaptive K-means clustering algorithm (adpK-means) in order to control a team of robots to accomplish all tasks with a good balance and at a minimal cost. Compared with the K-means clustering algorithm, our proposed algorithm has better performance, where through adaptive dynamic scaling of the clustering space in the iterative process, multiple robots can complete missions with well-distributed workloads. The experimental results show that the algorithm effectively reduces the total energy consumption of the entire robot system and ensures that the tasks of robots are comparative.