Reviewerly/exHarmony huggingface dataset:
Detecting the Security Level of Various Cryptosystems Using Machine Learning Models

With recent advancements in multimedia technologies, the security of digital data has become a critical issue. To overcome the vulnerabilities of current security protocols, researchers tend to focus their efforts on modifying existing protocols. Over the last few decades, though, several proposed encryption algorithms have been proven insecure, leading to major threats against important data. Using the most appropriate encryption algorithm is a very important means of protection against such attacks, but which algorithm is most appropriate in any particular situation will also be dependent on what sort of data is being secured. However, testing potential cryptosystems one by one to find the best option can take up an important processing time. For a fast and accurate selection of appropriate encryption algorithms, we propose a security level detection approach for image encryption algorithms by incorporating a support vector machine (SVM). In this work, we also create a dataset using standard encryption security parameters, such as entropy, contrast, homogeneity, peak signal to noise ratio, mean square error, energy, and correlation. These parameters are taken as features extracted from different cipher images. Dataset labels are divided into three categories based on their security level: strong, acceptable, and weak. To evaluate the performance of our proposed model, we have performed different analyses (f1-score, recall, precision, and accuracy), and our results demonstrate the effectiveness of this SVM-supported system. INDEX TERMS Support vector machine (SVM), security analysis, image encryption, cryptosystem.
CONTENTS, PROBLEMS AND DIDACTICAL BASIS OF TEACHING THE SUBJECT "ELECTRIC NETWORKS AND SYSTEMS" IN THE ELECTRONIC EDUCATIONAL ENVIRONMENT

The maximum effectiveness of the process of preparation for the e-learning environment can be achieved only through the coordinated development of psychological, technical, technological, information, legal, methodological and other components of the process. The introduction of modern information and communication technologies into the educational process has led to the creation of a new form of teaching - distance learning - in addition to traditional teaching methods.
Pengaruh Pengenalan Lapangan Persekolahan (PLP), Penguasaan Teknologi Informasi, dan Penguasaan Materi Akuntansi Terhadap Kesiapan Mahasiswa Menjadi Guru Akuntansi Di Era Revolusi Industri 4.0

Readiness to become a teacher in the 4.0 era can grow from various factors, including Introduction to School Fields (PLP), Mastery of Information Technology, and Mastery of Materials. The purpose of this study was to determine the effect of PLP, Mastery of Information Technology, and Mastery of Accounting Materials on Students' Readiness to Become Accounting Teachers in the Era of the Industrial Revolution 4.0. This research is included in the type of quantitative research. The population of this study were students of the 2018 State University of Surabaya Accounting Education Study Program who had participated in PLP II as many as 40 students using the saturated sampling technique. Data collection techniques using a questionnaire questionnaire. The data analysis method used multiple linear regression. The results of the research that have been carried out prove that the Introduction to School Fields (PLP) has a positive and significant effect on student readiness to become accounting teachers in the era of the industrial revolution 4.0, while Mastery of Information Technology and accounting materials has no effect on student readiness to become accounting teachers in the era of the industrial revolution 4.0. Simultaneously the variables of PLP, Mastery of Technology, Mastery of Materials simultaneously affect Students' Readiness to Become Accounting Teachers in Era 4.0.
ROTATION ONLY BUNDLE-ADJUSTMENT FOR THE GENERALIZED CAMERA MODEL AND ITS APPLICATION FOR LARGE-SCALE UNDERWATER IMAGE-SETS

Abstract. The generalized camera model allows handling a broad range of imaging systems for which the common central perspective model no longer applies. While offering greater modeling flexibility, designated orientation procedures need to support its application. In that respect, models that facilitate the computation of the bundle-adjustment solution are imperative as a means to solve the motion and structure of a large set of images. Being non-linear, the bundle adjustment solution requires good initial estimates and the filtering of outlying matches. To facilitate such a solution, we propose in this paper a method for estimating the global rotations of a set of views independent of their translation and the scene structure. This method is then used to improve the robustness, efficiency, and convergence of the solution when used as a refinement to the global rotations. The proposed pipeline is evaluated by experiments on synthetic and real-world data of axial flat-refractive cameras. It shows that the proposed method produces more accurate and optimal initial estimates of the global rotations than the state-of-the-art rotation averaging method.
Web-based Blood Donor Management Information Sytem using Waterfall Method

PMI Labuhanbatu Regency is one of the central PMI branches where there is a division that handles the blood donation process, namely the Blood Transfusion Unit. UTD PMI Labuhanbatu Regency has the duty to serve blood donation activities and provide blood stock for the Labuhanbatu community in need. As a unit that provides blood donors, UTD PMI Labuhanbatu must always be ready to provide the services needed. One of the concerns is the issue of blood stock availability. If there are many people who need blood, then UTD must be ready to serve. If the amount of blood stock is reduced, then people will find it difficult to get blood. For this reason, the issue of blood availability must always be the main concern of UTD PMI Labuhanbatu. This study aims to build a blood donor information system at the PMI Blood Transfusion Unit in Labuhanbatu Regency. The system built applies a web-based framework. The system development applies the Waterall method which includes the process of needs analysis, design, implementation, testing, and maintenance. After designing, implementing and testing, the results obtained are the system has been successfully developed and all designs are in accordance with what is implemented. The conclusion from this research is that the blood donor information system that has been developed at UTD PMI Labuhanbatu Regency has been able to provide convenience for admins and users in managing donor and blood stock management.
feature reduction based LDA with SVM classification on dimensionality reduction for Big Data

Analytics of Big data research has been entering the latest processes of "fast-data", in which every second many Giga Bytes of data arriving towards a massive structure of data. Based on the number, speed, importance, variation, uncertainty and veracity of the collected data, current Big data applications gather dynamic data sources and thus create massive unstructured Big Data. Data sources that are decreased and significant are deemed more valuable than raw, repetitive, unreliable, and noisy data set. A further prospect for reducing the big data whereas the thousands of attributes in large data sets are the cause of the dimensionality which takes infinite computing resources to expose working patterns of information. Not each feature in the generated datasets is essential for the training of computer algorithms. Any characteristics do not influence the effects of the forecast and some may be negligible. The ignorance of this trivial or less important characteristics lowers the pressure on the algorithms of Machine Learning (ML). The MapReduce technology in existing has also been used to decrease dimensionality, but without decreasing irrelevant features it takes all data for a direct reduction, which contributes to lower classification precision.
Structure and Formay of German and Georgian Scientific Texts in the Intercultiral Context

In academic life, the ability to create text is central. Text is the main means of communication that preserves certain cultural codes. The existence of communication problems among scientists in various fields has increased interest in the intercultural context of csintific comminication. In this paper, science is discussed as a communication process and in the influence of the cultural phenomenon on the visual form or structure of scientific texts is shown.Texts linguistics methods ans in-text macrostructure, its structure are used in the research process. Sciencwe is generally a communication process. Scientific texts are the most important part of sceintific communication. The provide us with industry knowledge and help to establish and strenghtenth the academic and research relationships of a certain segment of the scientific community. Formal scientific communication has a special significance in terms of popularization of sceince and development and access of scientific base. The influence of discource and socialcultural factors on sceitific communication, as well as on other types of communication, is very strong, which complicates the wuestion of the existence of a common language among scholars of different cultures. In the article, on the example of analyses of 10 German scientific texts by Irem Atasoy [Atasoy, 2016], which are published in different periodicals at different times, 10 Georgian scientific texts are discussed. Based on the results of the research published in the paper, it can be said that the characteristics of the structure and format of scientific texts in both languages are similar and different, althought objectivity requires that these results can not be generalized, because the research is based on only twenty articles written in a specific language. In the section. But there is no doubt that the most important trend in standardizing the structure of texts in both languages ​​is to promote scientific communication, increase the area of ​​scientific results, arouse trust and interest in science, and help develop problem-solving and identify new developments in research.
An artificial intelligence model to predict 12-month mortality among patients with myocardial infarction

Abstract Funding Acknowledgements Type of funding sources: None. Background Ischemic heart disease and acute myocardial infarction (AMI) are the number one causes of death and disability, affecting around 126 million individuals worldwide [1]. About 30% of all cases of AMI lead to death. According to different sources, 8-20% of people with AMI die within 1 year of the event, and every second patient is rehospitalized [1-2]. Thus, it is necessary to assess the risk and to predict the outcomes during the first admission to the hospital, in order to guide the management and treatment after AMI [2]. Conventional risk rating scales and methods have a lot of drawbacks, so novel approaches such as artificial intelligence (AI) and deep learning (DL) methods have the potential to provide an accurate risk assessment and share decision-making in patients who experienced AMI [3-4]. Purpose To develop and validate a deep-learning-based risk stratification model to predict the 12-months mortality in patients with AMI. Methods A cohort of 250 AMI patients with Killip class I-IV was enrolled in the study. The data was collected on the admission day and a year after the event and included anamnesis as well as the results of the physical and laboratory-instrumental examination (72 values). All patients were randomly divided into 2 groups: the derivation cohort, which consisted of 215 individuals, and the validation cohort consisted of 35 patients. Our model was created using the Python programming language in GoogleColab and it is a convolutional neural network (CNN) with 1 input layer, 4 hidden layers, and 1 output layer consisting of neurons with a sigmoid activation function (Fig. 1). We used MaxAbsScaler for data normalization and Adam for optimization. Also, we calculated the GRACE risk score and compared the performance of the models only for the validation cohort that was not used for the model development. Results We developed our DL-based model using the derivation data during the 30 cycles of work, receiving the maximum value of training accuracy of 96.7%. The mortality risk, calculated by our model for the validation group was compared with real 12-months mortality, and the CNN "lied" only 2 times (Table 1). The test of the validation cohort showed such results of our DL-based model: 94% - accuracy, 71% - sensitivity, 100% - specificity, 100% - positive, and 93% - negative prognostic value. These results significantly outperformed the GRACE scale, which showed 63%, 71%, 54%, 26%, and 94% respectively. Conclusions In summary, we develop and validate a DL-based risk stratification model to predict the 12-months mortality in patients with AMI. The accuracy of the created model is significantly higher than conventional risk scales (GRACE score). Thus, it is proved that algorithms based on deep learning may be more effective to predict mortality and guide the management of cardiac patients.
English Verb “Catch” and Its Related Verbs in Buginese Language: A Comparative Study

Catch verb refers to something being brought into such position. All verbs are transitive verb and specification of locus is obligator and other it is optional. The aims of this research were (1)To identify related Verbs of English “Catch” Verb in Buginese Language. (2) To explain the similarities and differences of English Verb, “Catch” and Its Related Verbs in Buginese Language in terms of semantical and grammatical construction. English data were collected from Corpus of Contemporary American English (COCA), while data of Buginese were obtained from field research through process of observation and in depth interview. Both of the data were analyzed with description and qualitative analysis. The result of this research shows that (1) there is one kind of “Catch” verb that use in English. While, in Buginese language there are eight kinds of “Catch” verbs that different in semantic aspect. They are mattikkeng, mattimang, majjaleppa’, mattado’, marrippung, majjala, mattada, and massero’ (2) The main differences of Verb “Catch” in English and Buginese Language can be seen from clause structure and movement to brought something into such position. From clause structure, In English a NP is followed by VP, while in Buginese is permissible that VP is followed by NP that marked by suffix –I in VP. From movement aspect, divided into three; normal movement, medium movement, and hard movement.
The Role of Personality in Trust in Public Policy Automation

Algorithms play an increasingly important role in public policy decision-making. Despite this consequential role, little effort has been made to evaluate the extent to which people trust algorithms in decision-making, much less the personality characteristics associated with higher levels of trust. Such evaluations inform the widespread adoption and efficacy of algorithms in public policy decision-making. We explore the role of major personality inventories -- need for cognition, need to evaluate, the "Big 5" -- in shaping an individual's trust in public policy algorithms, specifically dealing with criminal justice sentencing. Through an original survey experiment, we find strong correlations between all personality types and general levels of trust in automation, as expected. Further, we uncovered evidence that need for cognition increases the weight given to advice from an algorithm relative to humans, and "agreeableness" decreases the distance between respondents' expectations and advice from a judge, relative to advice from a crowd.
Identifying Surrogate Decision Maker and Code Status Discussions in Advance Care Planning Notes Using Natural Language Processing (GP701)

Conclusion.In this cohort of potentially hospice-eligible blood cancer patients, access to blood transfusion was rated as being most important relative to traditional hospice services.Impact.Innovative hospice delivery models that include access to palliative transfusions have strong potential to increase hospice use for patients with blood cancer.
Science and philosophy in the perspective of development: review of the scientific conference «Worldviews of postneclassical science» (Borisov Readings)

The article provides a brief summary of the presentations of the participants of the All-Russian Scientific Conference with international participation Worldviews of postneclassical science (Borisov Readings), which was held on September 2425, 2021 at the Samara Polytechnic. Particular attention is paid to the substantiation of promising areas of interaction between science and philosophy in the perspective of the knowledge society.
EFEKTIVITAS PELATIHAN PSIKOEDUKASI BERBASIS EXPERIENTIAL LEARNING DALAM MENINGKATKAN PEMAHAMAN MANAJEMEN KELAS GURU SD

Primary schools or Sekolah Dasar (SD) are the foundation of education in Indonesia. There, students are taught basic academic skills such as reading, writing, and counting; thus, professional and competent educators are in need. This research an act of intervention by increasing class management skills of the teachers in Public Elementary School X (Sekolah Dasar Negeri X), West Jakarta. In this research, class management is measured by observation, semi-structured interviews, and pretests. Participants of this research consists of 5 respondents, picked through a nonprobability sampling, with class management skills that are below average. The characteristics of the respondents are men and women aged between 22-43 with less than 10 years of teaching experience. This research utilizes the pretest-posttest experiment while providing psychoeducation based on experiential learning in order to increase the respondent’s class management skills. The data difference test from the pretest and posttest uses paired sample t-test, whereas t= -2.982 and p= 0.041 (0.05) which shows the respondent’s increased understanding of class management after being given 4.1% intervention. Through this research, it is concluded that psychoeducation based on experiential learning is effective in increasing SDN X educator’s class management skills.
Adapting to Learning Services During Covid-19: A Risk Mitigation Review

The purpose of this study was to analyze online learning during the COVID-19 pandemic and its solutions at SDIT Insan Rahayu Rancaekek Bandung. This research uses a qualitative approach with a case study type, the data obtained through interviews, observation, and documentation. This study indicates that the implementation of online learning during the covid-19 pandemic has problems for teachers: weak mastery of information technology devices and limited access to student supervision. Students have problems related to the inactivity of students in participating in learning, limited supporting facilities, and internet network access. Meanwhile, parents have limited time to accompany their children during online learning. These problems can be overcome by increasing the competence of teachers' IT mastery as well as intensive supervision involving the role of parents who are also supervised by the school so that two important roles involved in children's education as well as on the side of assignments that are carried out manually can be completed without any problems.
An Analysis of Segmental Accuracy of Korean for Automated Assessment - With Focus on Chinese, Vietnamese, and Thai Speakers -

This study aims to propose a phonetic transcription and annotation system for automated speaking assessment of Korean. We analyzed the pronunciation errors discovered in the speech data of 2,250 sentences (32,610 words) read by 30 speakers of Chinese, Vietnamese, and Thai. We were able to predict the observed errors based on the comparative analyses between the phonetic and phonological system of Korean and those of the native languages of the learners, and thus suggested using the frequency of errors for the assessment of segmental accuracy. These results are expected to contribute to the on-going discussions of automated assessment of Korean speaking tests and the future development of automated tools for Korean language education.
An efficient hardware implementation of Convolutional Neural Network in detect Breast Cancer Histopathology Image

This paper presents our work on evaluating the effectiveness of a novel deep convolutional neural network architecture (CNN) for classifying breast histology images for cancer risk factors as negative or positive. Also, the hardware structure of the proposed model was successfully synthesized and verified. The results indicate that a CNN trained on a small dataset achieved an overall AUC (Area under ROC Curve - ROC is an acronym for receiver operating characteristic) value of 0.922 across a set of 55505 test images. In addition, the time it takes to classify each image is within 3.8 milliseconds instead of a task that even trained pathologists take hours to complete.
Veterinary Medicine of Empire and Livestock Animals of Colony: Epizootic Control during the Japanese Colonial Period

The Japanese Government General of Korea used colonial Korea as food and military resource for Japan and as a barrier to the livestock infectious diseases from China. Therefore the colonial livestock sanitary policies focused on quarantine-based disease prevention. Unlike colonies in India, Africa, and America, where the European powers formed colonies the Korean Peninsula was close to Japan. The epizootics in Korea created an invisible boundary between the empire and the colony. Colonial livestock animals were considered inferior beings at risk of infection and contamination that needed improvement. Humans in the colony were passively incorporated into the livestock quarantine system. Korean Peninsula served as a test site for new systems such as the double quarantine system and rinderpest immune zone, and technologies developed in Japan, such as the immune serum and vaccines. Japan forcibly transplanted livestock sanitary regulations on the Korean Peninsula but the benefits were limited in enhancing the colony''s capabilities in preventing livestock infectious diseases. Colonial Korea could not secure the necessary veterinarians according to its own needs, nor could it get an opportunity to cultivate related professionals. Therefore, colonial veterinary medicine and livestock sanitary policy were established with limited success in preventing epizootics during the colonial period.
The Effect of Reading &amp; Writing Literacy Awareness Elementary Education Teachers on the Reading and Writing Literacy Ability of High-Grade Students

The background of this research is the low reading literacy ability of high grade students in Banjarmasin. The low reading ability is thought to have an effect on student achievement. This is indicated by the results of student learning achievement which is still low. The aims of the study were; 1) to determine the reading literacy ability; 2) to determine the level of learning achievement; and 3) to determine the effect of reading literacy ability on the learning achievement of high-class students in Banjarmasin. The research design used survey quantitative research with research samples of high-class students in Banjarmasin. Data analysis using simple linear regression test. The results showed that; 1) students' reading literacy ability was quite adequate at 67.53%; 2) student learning achievement was classified as very good at 81%; and 3) there was a significant effect of 5.4% between reading literacy ability and achievement student learning.