Reviewerly/exHarmony huggingface dataset:
Ценностное отношение студентов к онлайн образованию в рамках международного научного сотрудничества на современном этапе

The article deals with the problem of forming the value attitude of student youth to the spread of distance formats and digital tools within the framework of international scientific cooperation and intercultural communication. The authors analyze the possibilities of using new forms and methods of online education in the pedagogical process and during international scientific forums (conferences, seminars, colloquia, schools for young scientists). The development of international scientific cooperation in the framework of the digitalization of education is considered within the framework of an axiological approach.
VOLTA: an Environment-Aware Contrastive Cell Representation Learning for Histopathology

In clinical practice, many diagnosis tasks rely on the identification of cells in histopathology images. While supervised machine learning techniques require labels, providing manual cell annotations is time-consuming due to the large number of cells. In this paper, we propose a self-supervised framework (VOLTA) for cell representation learning in histopathology images using a novel technique that accounts for the cell's mutual relationship with its environment for improved cell representations. We subjected our model to extensive experiments on the data collected from multiple institutions around the world comprising of over 700,000 cells, four cancer types, and cell types ranging from three to six categories for each dataset. The results show that our model outperforms the state-of-the-art models in cell representation learning. To showcase the potential power of our proposed framework, we applied VOLTA to ovarian and endometrial cancers with very small sample sizes (10-20 samples) and demonstrated that our cell representations can be utilized to identify the known histotypes of ovarian cancer and provide novel insights that link histopathology and molecular subtypes of endometrial cancer. Unlike supervised deep learning models that require large sample sizes for training, we provide a framework that can empower new discoveries without any annotation data in situations where sample sizes are limited.
Retraction: Mingling Wang, Multi‐data multiple gray clustering analysis based on layered mining for ubiquitous clouds and social internet of things. <scp><i>J Internet Technol Lett</i></scp>. 2020

The above article, first published online on October 23, 2020 Wiley Online Library ( https://onlinelibrary.wiley.com/doi/full/10.1002/itl2.252 ) has been retracted by agreement between the journal Editor‐in‐Chief, Luigi Alfredo Grieco, Department of Electrical and Information Engineering (DEI) Politecnico di Bari, Bari, Italy and Wiley Periodicals, LLC. The retraction has been agreed due to pertinent evidence indicating that the peer review process of this paper was compromised. The accepted letter has gone through an additional evaluation by scientific experts who judge that the quality of those contributions was not in line with the standards of the ITL journal. The editorial office did not receive a response from the authors, and so requested underlying experimental data was not available for evaluation. Accordingly, the editors consider the conclusions of this manuscript invalid.
TRAINING MAKING A DIGITAL POSTER USING THE CANVA APP IN CREATING PROCEDURE TEXT AT PKBM KATIMPUN

Community Learning Center is a non-governmental organization formed by and for the community that is engaged in learning and is located at the village or sub-district level. To equal education, PKBM has a strategic function to serve all school-age children or people who want to go to school but are unable to attend school. Like others, PKBM Katimpun has also carried out its function to serve and provide education for the surrounding community. The presence of PKBM is a forum for carrying out various educational activities that are equivalent to formal schools in general. The problems faced by PKBM Katimpun are the need to increase expertise in the field of technology and information so that students can compete in the work field later. In addition, students also need to improve their academic abilities. In this case, English lessons are one of the subjects that contribute to the development of skills for students in their future work. Therefore, we took the initiative to combine these two targets into one training material which is expected to improve skills in IT as well as the ability to learn and write English texts. This community service activity is intended to provide training to PKBM Katimpun students through two materials, namely the use of the Canva application and learning to write procedure texts in English.
An approach to extend the metadata schema of Zenodo for Cultural Heritage datasets

In this article, we present an approach designed to extend the metadata schema of the Zenodo data management platform to strengthen the FAIRness of the published dataset. We focus on a bottom-up approach starting from a series of datasets ranging from the 3D digitalisation of monuments and sites to the creation of reconstructive records (including the scientific documentation they are based on), to the implementation of digital storytelling and to the development of open source-based web-apps. We propose the simplest possible set of metadata to be included in the Zenodo platform with the possibility, for the community, to adopt and further develop/modify them. This article will describe in detail the formalisation and the digital formats adopted providing the related metadata templates developed within the projects.
DeLone and McLean Model Testing upon The Information System Implementation of New Student Enrolment at Junior High school Level in Pekalongan City

The information technology based Information System in education has been used in responding the change and as a tool in maintaining efficiency and effectiveness, especially for the online system of new student admission (&lt;em&gt;PPDB&lt;/em&gt;). The Pekalongan City Education, since 2014, has developed an online junior high school New Student Admission application. This system was built to handle the process of admitting new students, from registration, selection to announcement of selection result. Even though it has been implemented for 6 years, the measurement of the success of implementing PPDB online has not been carried out. The purpose of researching is to determine the success of implementing the PPDB online information system for junior high school level. The modified DeLone and McLean model was used to measure the success of online &lt;em&gt;PPDB. &lt;/em&gt;Research respondents were all admin and operators of the online PPDB system as many as 92 respondents. The data analysis method for processing variables used linear regression statistical analysis. The test results show that system quality, information quality, service quality, and user satisfaction have a significant and significant effect on net benefits, so that users benefit from the online PPDB information system.
Forecasting JPFA Share Price using Long Short Term Memory Neural Network

To invest or buy and sell on the stock exchange requires understanding in the field of data analysis. The movement of the curve in the stock market is very dynamic, so it requires data modeling to predict stock prices in order to get prices with a high degree of accuracy. Machine Learning currently has a good level of accuracy in processing and predicting data. In this study, we modeled data using the Long-Short Term Memory (LSTM) algorithm to predict the stock price of a company called Japfa Comfeed. The main objective of this journal is to analyze the level of accuracy of Machine Learning algorithms in predicting stock price data and to analyze the number of epochs in forming an optimal model. The results of our research show that the LSTM algorithm has a good level of accurate prediction shown in mape values and the data model obtained on variations in epochs values. All optimization models show that the higher the epoch value, the lower the loss value. Adam's Optimization Model is the model with the highest accuracy value of 98.44%.
Analysis of Mechanisms for Resource Management in IoT: Performance of Mutual Authentication in the Context of Fog and EDGE-Fog Computing

The Internet is now experiencing an unprecedented expansion with the development of connected objects. At its inception the IoT, like any revolution, its objectives were quite limited. Its main objective was to reduce the effort of human data entry in order to allow the storage and automatic processing of the latter. Moreover, objects generate a lot of data that they cannot store or process by themselves, hence the need for external support. This is how Cloud Computing comes to answer this problem, making the success of IoT. This technology guarantees the storage, availability, processing, etc. of data, its integration into the latter is known as "Cloud of Things" CoT. The data generated should not only be stored, but rather processed in order to derive knowledge, decision making. The objective of our work is to analyze mutual authentication management models of IoT devices to optimize resources trying to provide solutions in the face of resource availability. To carry out this work, we analyzed the application areas and the challenges of IoT. Then, we studied IoT security threats. Our work ends with a study and an analysis mechanism of mutual authentication management models of IoT based on uncertificated Authentication mechanisms, Elliptic curve cryptography authentication, Mutual Authentication in the context of Fog Computing.
Challenges in Provision of Digital Information System

This paper is all about the concept of digital information system, digital information system provision, types of digital information system, contribution of digital information system in the development of human society, contribution of digital information system, Use and application of digital devices in literacy in the digital era is currently very important. Therefore, courses or outreach is needed for all people who have an interest in reading to be able to further develop themselves. In every society of today, the use of digital media is an important key in the successful implementation of learning online. There is a need for a quick adjustment to the current place of education. The current situation forces digitization to accelerate.
Face Recognition

In this paper, facial highlights are extricated by consolidating and contrasting different models, and afterward a profound brain organization is developed to prepare and build the consolidated highlights. Along these lines, the upsides of different models can be consolidated to make reference to the acknowledgment exactness. In the wake of getting a model with high precision, we fabricate an item model. This article contrasts the unadulterated client model and the server-client model, investigates the advantages and disadvantages of the two models, and breaks down the different business items that are expected for the server-client model.
The Mediating Effect of Intra-Organizational Social Capital on the Relationship between Team Leadership and Collaborative Value among Ashoka Fellows’ Organizations in Africa

Purpose: The study sought to determine the mediating effect of intra-organizational social capital on the relationship between team leadership and collaborative value among Ashoka fellows’ organizations in Africa&#x0D; Methodology: The study applied pragmatism philosophy to offer several ways to bridge dichotomies in mixed methods approaches to social science. Explanatory sequential mixed-method research design consisting of two distinct phases, namely quantitative and qualitative, was adopted. Both qualitative and quantitative study methods were adopted. In the quantitative study, the target population constituted all the 154 Ashoka Fellows' Organizations working in 19 countries in Africa. Data was collected using a structured questionnaire administered online to the founders (Ashoka Fellows) or the Ashoka Fellows' Organizations' CEOs. One hundred responded by filling out the questionnaire, which translated to a 64.9% response rate. Additionally, qualitative data applied purposive sampling and selected six Ashoka regional team leaders in Africa for in-depth interviews. They all were available for the interviews translating to a 100% response rate. Data analysis techniques combined descriptive and inferential statistics. Statistical Package for Social Sciences and SmartPLS 3 software were used to analyze the collected data.&#x0D; Findings: Results revealed that Intra-organizational Social Capital (IOSC) mediates the relationship between team leadership and collaborative value. Before IOSC mediation, team leadership accounted for 34.1% of collaborative value, with an R2 = 0.341, chi-square X2 (10, N=100) = 99.274, p&lt;.05, SRMR=0.096, Rms-theta = 0.227, and NFI=0.745. After IOSC mediation team leadership accounted for 37.1% of collaborative value, with an R2 = 0.371, chi-square X2 (10, N=100) = 152.934, p&lt;.05, SRMR=0.100. Rms-theta = 0.207 and NFI= 0.707. The null hypothesis was rejected.&#x0D; Unique Contribution to Theory, Practice and Policy: Based on this finding, further research could be a study investigating how teams build their social capital and how intra-organizational social capital can be enhanced to improve teams’ performance. Another recommended study should empirically examine the link between team leadership and collaborative value in other sectors such as private sector organizations and public organizations as well as other regions like Europe or Asia.
Privacy-Preserving Federated Learning Framework using Permissioned Blockchain

Abstract Data is readily available with the growing number of smart and IoT devices. Industries of different sectors follow technological advancement to be benefited from data sharing. However, application-specific data is available in small chunks and distributed across demographics. Additionally, sharing data online brings serious concerns and poses various security and privacy threats. To address these issues, federated learning (FL), a secure and collaborative learning paradigm, would be suitable, which brings the machine learning model to the data owners. Unfortunately, FL is prone to poisoning and inference attacks in presence of malicious users and curious servers. This work proposes a permissioned blockchain based federated learning framework, called PrivateFL (Privacy-Preserving Federated Learning Framework). PrivateFL replaces the central server with a Hyperledger Fabric network, to prevent inference attacks. Further, we propose VPSA (Vertically Partitioned Secure Aggregation) tailored to PrivateFL framework, which performs robust and secure aggregation. PrivateFL facilitates multi-tenancy for learning different machine learning models. Theoretical analysis proves that the system is resistant against inference attacks, even if n -1 peers are compromised. A secure prediction mechanism is also proposed to securely query a global model and protecting its intellectual property rights. Experimental evaluation shows that PrivateFL performs better than the traditional (centralized) learning systems and converges faster, while capable enough to detect malicious updates.
The Identification of Individualized Eye Tracking Metrics in VR Using Data Driven Iterative- Adaptive Algorithm

Eye tracking metrics provide information about cognitive function and basic oculomotor characteristics. There have been many studies analyzing eye tracking signals using different algorithms. However, these algorithms generally are based on the initial setting parameter. This might cause the subjective interpretation of eye tracking analysis. The main aim of this study was to develop a data-driven algorithm to detect fixations and saccades without any subjective settings. Three subjects were included in this study. Eye tracking signal was acquired with the VIVE Pro Eye in virtual reality (VR) environment while subjects were reading a paragraph. The algorithms based on the calculation of threshold were employed to calculate eye metrics including total fixation duration, total fixation number, total saccades number and average pupil diameter. The proposed algorithm, which is based on calculating the initial threshold, based on mean, and standard deviation of eye tracking signal within experiment duration, gave the same results obtained adaptive filtering reported in literature (average fixation duration for three subjects= 11515 ms ± 6951.2, average fixation count for three subjects= 17.33 ± 4.16). On the other hand, our proposed algorithm didn’t use any certain objective parameter as like adaptive filtering. As a conclusion, VIVE Pro Eye may be utilized as an eye movement assessment device, and, the suggested approach might be utilized to analyze objective eye tracking metrics.
SECURE DATA DE-DUPLICATION IN INTERNET OF THINGS USING THRESHOLD CRYPTOGRAPHY AND BLOOM FILTER

In discrepancy, the current system necessitates the use of edge waiters to manage druggies' private keys.Second, it employs searchable public-crucial encryption to ameliorate the safety, effectiveness, and rigidity of data quests.In terms of security, our system ensures the confidentiality of pall data, secure data sharing and searching, and the elimination of a single point of failure.To dispose these problems, we presented a conspiracy -free data de-duplication protocol grounded on a threshold eyeless hand in this design with the help of multiple crucial waiters.It effectively prevents the bushwhackers from using the stolen label to get the whole train to gain train access without authorization.The most significant invention of this design is to use The Chinese memorial Theorem to hide autographs keys, therefore balancing the security enterprises of the pall and customer.still, abstain redundancy from fresh storehouse or communication isn't trivial due to security enterprises.As far as we know, our scheme is the only data de-duplication scheme that satisfies the sematic security of ciphertext and marker.Though ferocious inquiries have been addressed on a coincident cryptosystem for secure data de-duplication, the conflicts amongst functionality, confidentiality, and authority remain unstable.further primarily, although data are blurred under coincident encryption, a violent wordbook attack is still efficient since the whole pseudorandom process relies heavily on plaintexts.As for data power, the download honor, which depends on hash value, may also be infringed due to the same reason.To dispose of these problems, we presented a conspiracy-free data de-duplication protocol grounded on a threshold eyeless hand in this composition.With the help of multiple crucial waiters, the outsourced train and de-duplication marker will be computationally indistinguishable from arbitrary strings.We used the Boom sludge as a tool to apply a evidence of power, icing that the power claims made by druggies are real.It effectively prevents the bushwhacker from using the stolen label to get the whole train to gain train access without authorization.The most significant invention of this composition is to use homomorphism calculation to total and induce partial hand markers, and to introduce a secret sharing medium grounded on The Chinese Remainder Theorem to hide hand keys, therefore balancing the security enterprises of pall and customer.Compared with being schemes, both communication and calculation performances are preferable in our protocol.As far as we know, our scheme is the only data de-duplication scheme that satisfies the semantic security of ciphertext and marker.
Social Media Analysis using Sentiment Analysis on COVID-19 from Twitter

The development of the internet is getting faster, participating in encouraging the emergence of new and innovative information. In filtering the various information that appears, we need a recommended system to perform well for users in today's internet era. A well-performing recommendation system in question is a reliable recommendation algorithm. This algorithm is fundamental to analyzing various information, such as responses on social media based on user behavior data related to the topic of COVID. This data is crawled from tweets on social media Twitter. The data analysis algorithm obtained uses Python, which is then visualized in the form of a diagram. The processed data is user comments on Twitter, and the text data is analyzed using Python, using more than 60000 data sets taken to form visualizations and conclusions. From sentiment analysis, polarity and subjectivity data are obtained to be analyzed, which are negative, neutral, or positive. The result is show positive tweets with 29.2%, negative tweets is 13%, and 57.8% neutral tweets. Lastly, sentiment analysis can help people effectively infer vast and complex data from social media like Twitter.
Improving English Writing Skills through the Application of Audiovisual Media at Senior High School

The author found that there was still a lack of mastery and interest of students in writing English sentences at SMAN 3 Sumbawa Besar. This study aims to explain strategies for using audiovisual media as well as analyze the results of improving English writing skills in the use of audiovisual media. This type of research is descriptive quantitative with the data collection techniques used are observation, English writing skills test and documentation and the analysis technique used is the paired sample t-test. Based on the results of the descriptive statistical analysis test, the average score of pretest and posttest English writing was obtained by students in the control class of 50.88 and 59.56 experienced an increase in scores in the experimental class of 58.68 and 74.85, meaning that there was an increase in English writing skills after the use of audiovisual media. From the analysis of the pretest-postest paired t-test, a result of -35.098 with a sig value was obtained. hitug (2 tailed) 0.000 is smaller than the ttabel 0.05. It was concluded that there was a difference between the pretest and postest scores in the results of English writing skills before using audiovisual media and after using audiovisual media.
Duolingo as A Mobile-Assisted Language Learning: A New Supplementary of Learning Basic English Reading for EFL Students

It is undeniable, that the world of education is affected by technological advances this study discusses the process of using an already developed language learning online software, Duolingo, to supplement learning basic English reading for senior high school EFL students. A mixed approach of qualitative and quantitative data collection is followed in this research paper. The learners that consist of 10 students had used the software online for about 30 days, either on their smartphone or on their personal computer. Based on the questionnaire result survey, the students usually enjoy the learning process because of several factors; such as easiness of its accessibility, its game-based aspect, could discussion of the problem with other players, and interactive features and illustrations. The result of the assessment also conducted by http://efset.org shows that the Duolingo online language learning platform could help the students achieve more from the expected result of the basic English reading target needs to be based on the CEFR assessment standard result, in another fun and also still on the appropriate way for teaching English, especially in English reading. Based on the result, it is essential to consider that using online applications could be one of the appropriate ways and beneficial ways for students to achieve better results in learning, especially in learning the English language.