Reviewerly/exHarmony huggingface dataset:
Skill Verification System using Ethereum

Abstract: Verifying skills is one of the major challenges in hiring new personnel. Companies and academia occasionally struggle to identify a candidate's talents because the credentials abilities that a candidate claims are not immediately verifiable and expensive for examine. For tamper-proof data storage, Blockchains have been proposed in the literature and decentralized talent verification. However, the majority of these schemes center on storing credentials are issued through regular universities for the blockchain. From several solutions that take system of certification itself into consideration, issues like numerous times, issues like (a) scaling with a small staff, (b) homogeneity of scores across numerous evaluators, or (c) extracting sincere effort from the evaluators are unaddressed. We suggest SkillVio, a blockchain-based platform that takes into account the above listed problems. and provide a number of enticing traits. As payment from platform users, such as test takers and employers, the network rewards graders with tokens.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Single Anonymous • Conference submission management system: Morressier • Number of submissions received: 38 • Number of submissions sent for review: 38 • Number of submissions accepted: 33 • Acceptance Rate (Submissions Accepted / Submissions Received × 100): 86.8 • Average number of reviews per paper: 2 • Total number of reviewers involved: 16 • Contact person for queries: Name: Abdul Karim Email: abdulkarim@ulm.ac.id Affiliation: Lambung Mangkurat University
Peningkatan Prestasi Belajar Pai Melalui Metode Demonstrasi pada Siswa Kelas Ia Sd Negeri 025 Cikutra

&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; Student success in learning is influenced by several factors, one of which is the method used by teachers in teaching. In fact, in learning teachers use the classical method, namely lectures, so that students are less active in learning and learning achievement is less satisfactory, therefore it is necessary to use other methods to improve learning achievement. This study is to determine whether the demonstration method can improve student achievement about compulsory prayer material in Class IA students of SD Negeri 025 Cikutra Kota Bandung. This classroom action research uses a demonstration method by demonstrating or demonstrating to students a process, situation that is being studied so that the process of student acceptance of the lesson will be more memorable in depth. This research is a PTK with 2 cycles through 4 stages, namely planning, implementation, observation and reflection. The research was conducted at SD Negeri 025 Cikutra Kota Bandung, with the help of 1 collaborator or colleague, namely Nirmala Ayuningtyas, S.Pd. The subjects of this study were 30 students. The hypothesis proposed is that if the demonstration method can be used properly, it can improve the learning achievement of PAI subject students in grade IA students of SD Negeri 025 Cikutra Kota Bandung. The success indicator is 70% with a KKM of 70. Data collection techniques by observation. Data analysis techniques with formulas to find out the average value and percentage.&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D;
ACQUAINTANCE OF PRESCHOOL CHILDREN WITH WORKS OF PAINTING

The article is devoted to the problem of familiarization of preschool children with works of art. It has been established that works of fine art directly influence the formation of the system of values and meanings in preschool children. Modern and previous studies of the aesthetic development of preschoolers are analyzed. The article compares and reveals the concept of aesthetic education and the peculiarities of education. It was found that the problem of aesthetic education in pedagogy has always been given a lot of attention. In terms of pedagogical leadership, pictorial activity becomes invaluable for the versatile development of the child, his mental and cognitive processes: perception, performance and creativity, which are inseparable unity and are integral parts of the productive artistic and creative activity of preschool children. For a full artistic and aesthetic development personality in the period of preschool childhood, it is necessary to create optimal conditions, emotional comfort and fill the child's life with interesting activity content.
ORGANIZATION OF EDUCATIONAL ACTIVITIES IN THE CONTEXT OF BLENDED LEARNING FOR FUTURE TELECOMMUNICATIONS SPECIALISTS

The article is devoted to the issue of organizing educational activities in the conditions of blended learning for future telecommunications specialists in teaching the disciplines “Switching and Information Distribution Systems” and “Telecommunication and Information Networks”. Due to the pandemic and the Russian invasion of Ukraine, distance and blended learning has become one of the leading trends in education, providing continuous and high-quality education. The author analyzed the experience of Ukrainian researchers in the use of blended learning and ICT tools in higher education institutions. The author describes digital tools and learning platforms used by teachers in the disciplines “Switching and Information Distribution Systems” and “Telecommunication and Information Networks” at the Kyiv Professional College of Communications. The materials in the areas of study of future telecommunications specialists are described in detail. The advantages of using the workbook in teaching the discipline “Telecommunication and Information Networks” are presented. As a result of the survey, which was attended by 50 students majoring in Telecommunications and Radio Engineering, the following advantages of blended learning were identified: flexibility of the process; increased academic performance of students; gaining knowledge in different ways; combination of distance and traditional learning. In an open question, students were asked to indicate what, in their opinion, needs to be changed or improved to improve the blended learning process; the answers were analyzed by the author and singled out into separate positions.
DEVELOPMENT OF A DIGITAL EDUCATIONAL ENVIRONMENT IN CHINA

Current model design research in the field of personalized learning mainly includes three categories: personalized learner model, personalized learning resource recommendation model, and personalized learning path model. The development of a personalized student model mainly depends on the basic information of the student, his interests and preferences, learning style, behavioral characteristics, etc.; and all learner information and data are also used to develop and implement a personalized learning resource recommendation model and an individualized learning path model Essential framework. The learner model is developed through an in-depth analysis of the learner's main attributes, learning process and learning outcomes, and on this basis, a model of the learning path that fits the learner is planned and personalized learning resources are presented. Among the various developed models, the student model occupies the largest share. In the study of personalized learning, different models can be developed that correspond to the individual characteristics and actual needs of students, so as to be more in line with the concept of respecting the individual characteristics of students, thereby contributing to the high-quality development of individualized learning and the overall development of students. We also described the model with tables that are given in the article.
Formation of Social Leadership in the System of Public Safety and Security Through the Use of Modern Modeling Techniques

The main purpose of the article is to study the modeling of the process of formation of social leadership in the system of public safety and security.The object of the study is the system of formation of social leadership in the context of security and safety.The research methodology involves the use of modern technology of multi-level graphical-functional modeling aimed at better reflecting the process of forming social leadership in the system of public safety and security.Based on the results of the study, a number of models were obtained in the article that contribute to a better understanding of the process of forming social leadership in the system of public safety and security.The elements of novelty presented in the results of the study are depicted using a new methodological approach.The prerequisites for this study were to identify a number of problems in the system of formation of social leadership, taking into account security aspects in the region.The strengths of the article are a methodical approach to solving the problem.Weaknesses are a number of emerging limitations.The study has a limitation in the form of not taking into account all aspects of the formation of social leadership in the system of public safety and security.However, in the future, it is necessary to expand the modeling of the formation of social leadership in the system of public safety and security.
Remote sensing object detection based on dilated convolution and multi-scale feature fusion

Aiming at the problem of poor detection results due to the large difference in scale of detection targets and numerous small targets in remote sensing images, a remote sensing target detection algorithm DCB-YOLO based on atrous convolution and multi-scale feature fusion is proposed. Based on the YOLOv5 algorithm, the algorithm designs a bidirectional feature pyramid structure (MDCB-BiFPN) with multi-branch hole convolution. The MDCB-BiFPN structure can better extract and fuse features of different scales, thereby improving the model's ability to detect multi-scale remote sensing targets. The experimental results on the remote sensing public dataset DIOR show that the DCB-YOLO algorithm can better accurately identify remote sensing targets at different scales.
Format preserving encryption of sensitive data in database

We propose a format-preserving encryption scheme that takes the field as the unit of encryption for sensitive data in a database. First of all, we need to obtain the data type and length of plain text, and then convert plain text to an array of integers. Moreover, the proposed scheme in this paper is used to encrypt and decrypt the array of integers. Finally, the data after encryption or decryption is converted to cipher text with the same format as plain text, and then is stored in the database. The proposed scheme first uses ZUC stream cipher to whiten, makes the plain text more confusing, and then uses variable block cipher based on the Lai-Massey structure to encrypt, which increases security while preserving the data format. We present the experimental results of the encryption of sensitive data in a database using AES, FFX, and the proposed format-preserving scheme respectively. The results show that the proposed scheme in the MySql database can be performed correctly and efficiently. And the proposed scheme roughly has the same performance as the AES algorithm. As well as it is approximately 5 times faster than FFX while encrypting 1000 records, the more records, the more efficient it is.
Rejection strategies in American political debates: A Pragma- linguistic Study

This study attempts to investigate the strategies of rejection in the arena of political debates. The main challenge in dealing with rejection strategies pragmatically lies in the idea that rejection is divided into two types: Explicit or Implicit. As such, the study tries to identify the main implicit pragma-linguistic strategies of rejection that the American debaters employ in arguments with their opponents. Furthermore, it highlights these indirect strategies of rejection that have been utilized more frequently by American debaters so as to serve their political agendas. Moreover, the study pinpoints the stage at which the rejection process takes place.&#x0D; Thus, the qualitative study uses an eclectic model primarily based on previous studies conducted in the field of argumentation ( Van Eemeren &amp; Grootendrorst, 2018) to investigate rejection strategies. The study has been concluded that American debaters more frequently employ offensive than defensive tactics to defend their positions and reject those of their opponents. As a result, they make an effort to discredit the opinions of their opponents in a variety of ways such as accusations, insulting, criticizing, denial, and condemning. Moreover, It has been noted that the process of rejecting a standpoint is initiated within the developing stage. Thus, the developing stage can be viewed as the essence of argumentation in which viewpoints are defended or rejected.
Analisis Kerawanan Pada Aplikasi Website Menggunakan Standar OWASP Top 10 Untuk Penilaian Risk Rating

Since 2011, SMA N “ABC” has implemented a web-based information system. The information system is intended as an introduction to information and learning media for students. The system has never been audited and/or tested for security, so the vulnerability is not yet known. To test the security of the SI SMA N “ABC” application, vulnerability scanning and vulnerability assessment were carried out using the Open Web Application Security Project (OWASP) Top 10 Security Risk 2017 and the Open Web Application Security Project (OWASP) Risk Rating Methodology. From the results of scanning vulnerabilities found thirteen vulnerabilities ranging from high to low categories. Based on the assessment of detected vulnerabilities, resulting in a scale of 5.72 for the possibility of vulnerabilities being exploited by attackers and a scale of 3,315 for the impact on business processes at SMA N “ABC”
De-blurring of faces in video based on GAN prior

Until now, the video de-blurring is still a challenging task. In many video de-blurring tasks, high-quality face images in videos is particularly important. However, due to the mutual motion between the camera and the subject during video recording, motion blur often occurs, especially in some frames the blurring of face is particularly serious. But before or after this frame, it may be possible to obtain different local information of the blurred face. For this reason, this paper proposes a new video face de-blurring method based on GAN prior. First, we learn the GAN prior network that generates high-quality face images, and embed it into the whole network as a prior module. Then, residual dense blocks are used in the RNN cell to extract the spatial features of the face in the current frame. In addition, a fusion module is used to fuse the hierarchical features of past and future frames to de-blur the current frame and generate a low quality low fuzzy face. Finally, this face is sent to a trained prior generator to generate a high-quality face. After a series of experiments, the results show that the de-blurring effect of the method we proposed is better than the existing algorithm.
Supplemental Material for The Scientific Structure and Evolution of Trust Within Performance-Oriented Teams Research: A Citation Network Analysis and Critical Review

a URL, doi, or other permanent path for accessing the specified information in a public, openaccess repository, and the specified information must be provided in a format that is time-stamped, immutable, and permanent.Qualifying public, open-access repositories are committed to preserving data, materials, and/or registered analysis plans and keeping them publicly accessible via the web in perpetuity.Examples include the Open Science Framework (OSF) and the various Dataverse networks.Hundreds of other qualifying data/materials repositories are listed at http://re3data.org/.Preregistration of an analysis plan must take place via a publicly accessible registry system (e.g., OSF, ClinicalTrials.govor other trial registries in the WHO Registry Network, institutional registration systems).Personal websites and most departmental websites do not qualify as repositories.
New entanglement-assisted quantum MDS codes derived from cyclic codes

Entanglement-assisted quantum error-correcting codes, which can be seen as a generalization of quantum error-correcting codes, can be constructed from arbitrary classical linear codes by relaxing the self-orthogonality properties and using pre-shared entangled states between the sender and the receiver, and can also improve the performance of quantum error-correcting codes. In this paper, we construct some families of entanglement-assisted quantum maximum-distance-separable codes with parameters $[[\frac{{{q^2} - 1}}{a},\frac{{{q^2} - 1}}{a} - 2d+2 + c,d;c]]_q$, where $q$ is a prime power with the form $q = am \pm \ell$, $a = \frac{{\ell^2} - 1}{3}$ is an odd integer, $\ell \equiv 2\ (\bmod\ 6)$ or $\ell \equiv 4\ (\bmod\ 6)$, and $m$ is a positive integer. Most of these codes are new in the sense that their parameters are not covered by the codes available in the literature.
The Needs Analysis of Teaching Materials for Writing Short Stories Based on Cerpengram Method for Class IX

The advancement of science impacts learning innovations that fulfill the requirements for resolving issues in the field of education. The goal of this project is to find instructional resources for writing short stories that are appropriate for class IX students. This research used a descriptive qualitative methodology to collect data using interviews and questionnaires. The findings indicated that there were constraints and a lack of teaching resources for class IX students at SMP Negeri 24 Kerinci to write short stories. The final results indicate that creative teaching tools based on the Cerpengram technique are required to facilitate comprehension of the subject matter, particularly short story writing abilities. According to the requirements analysis, 100% of students and instructors demand novel teaching resources based on the Cerpengram technique that have been produced in the form of e-modules.
Abstract: Pan-tumor CAnine CuTaneous Cancer Histology (CATCH) Dataset

The identification of tumor regions on cutaneous tissue sections and the subsequent differentiation into individual tumor subtypes are routine tasks for veterinary pathologists. However, manual tumor delineation can be time-consuming and morphological similarities of tumor types can make the subtyping task difficult. Deep learning-based algorithms have been successfully applied for both tasks but require a large amount of annotated data to learn robust representations. Acquiring the annotations necessary to train these algorithms can be time-consuming and requires expert knowledge. Publicly available datasets reduce this annotation overhead and allow for a comparison of image analysis algorithms trained for the task at hand.We published a publicly available dataset of 350 whole slide images (WSIs) of seven different canine cutaneous tumors. These were annotated for the tumor subtypes and additionally six skin tissue classes. Overall, the database includes 12,424 polygon annotations for 13 classes, which exceeds most publicly available datasets in annotation extent and label diversity. In our dataset report, we validated the provided annotations through inter-rater experiments on a subset of the presented dataset, where three pathologists demonstrated high consistency in labeling tissue structures, especially for tumor annotations. Furthermore, we performed a technical validation by first training a deep neural network for tissue phenotyping. The model segmented the WSI into tumor and five skin tissue classes, where we achieved a class-averaged Jaccard coefficient of 0.7047 and a Jaccard coefficient of 0.9044 for tumor in particular. Afterward, we classified the segmented tumor regions into the tumor subtypes and achieved a slide-level accuracy of 0.9857. These baseline results provide a starting point for the development of more advanced algorithms. Previous works have shown that canine and human cutaneous tumors share various histologic patterns, which extends the added value of the presented dataset beyond veterinary pathology [1].
Deep Learning-based Subtyping of Atypical and Normal Mitoses using a Hierarchical Anchor-free Object Detector

Mitotic activity is key for the assessment of malignancy in many tumors. Moreover, it has been demonstrated that the proportion of abnormal mitosis to normal mitosis is of prognostic significance. Atypical mitotic figures (MF) can be identified morphologically as having segregation abnormalities of the chromatids. In this work, we perform, for the first time, automatic subtyping of mitotic figures into normal and atypical categories according to characteristic morphological appearances of the different phases of mitosis. Using the publicly available MIDOG21 and TUPAC16 breast cancer mitosis datasets, two experts blindly subtyped mitotic figures into five morphological categories. Further, we set up a state-of-the-art object detection pipeline extending the anchor-free FCOS approach with a gated hierarchical subclassification branch. Our labeling experiment indicated that subtyping of mitotic figures is a challenging task and prone to inter-rater disagreement, which we found in 24.89% of MF. Using the more diverse MIDOG21 dataset for training and TUPAC16 for testing, we reached a mean overall average precision score of 0.552, a ROC AUC score of 0.833 for atypical/normal MF and a mean class-averaged ROC-AUC score of 0.977 for discriminating the different phases of cells undergoing mitosis.
Analysis of Block-Level Prediction-Error Expansion Approach in Data Encryption

Due to the difficulty and inefficiency of the reserved data hiding approach, several encryption domain-based data (reversible) concealing algorithms have drawbacks such as a low embedding rate and poor resolution of the immediately retrieved data. This article will give complete details about different reserved model approaches for data hiding and proposes a different algorithm for data hiding. By taking advantage of the pixel redundancy inside each block, the technique can incorporate confidential data into 2X2 picture blocks. Our proposed mode extends this idea to the encrypted realm (ABPEE-RDHEI). In order to maintain spatial redundancy for data embedding, to further boost the security level, a stream cipher is then applied to the block-permutated image. The proposed ABPEE-RDHEI can produce marked decrypted images with a high embedding rate and good resolution due to the advanced data combining techniques using iteration and data encryption. ABPEE-RDHEI outperforms a number of state-of-the-art approaches, according to experimental findings and analyses. The ability to forecast an image accurately and insert a message into the image with minimal distortion are two essential components in the field of RDHEI. However, it is difficult to increase forecast accuracy because linear regression prediction is susceptible to outliers. To overcome this issue, this work suggests an RDHEI approach based on an adaptive prediction-error label map.