Reviewerly/exHarmony huggingface dataset:
UPAYA GURU BK MENGEMBANGKAN RENCANA PILIHAN KARIR SISWA MELALUI LAYANAN INFORMASI KELAS XI SEMESTER GENAP MADRASAH ALIYAH DAARUL MA’ARIF BANJAR NEGERI NATAR LAMPUNG SELATAN TAHUN PELAJARAN 2018/2019

This research is a qualitative study on IPS XI grade 2 students of Aliyah Daarul Ma'arif Banjar Negeri Natar Lampung, numbering 27 students. To develop a career choice plan for students at each information service meeting, a career choice plan is observed at the end of each meeting in the form of a statement that matches the career choice plan indicators. This indicator of qualitative success is if the career choice plan of students experiences an increase in the development of each information service meeting with indicators of research achievement which before being provided with information services is only 16.2%. From the observations it can be seen that there is an increase in the development of students' career choice plans from the first meeting with an average of 19.9%, the meeting II increases with an average of 23.9%, and the meeting III increases with an average of 27.3 % thus it can be concluded that There is an increase in the development of students' career choice plans through information services in even semester XI students of Aliyah Daarul Ma'arif Banjar Negeri Natar Madrasah, South Lampung 2018/2019.
Sistem Informasi Transaksi Peminjaman dan Pengembalian Buku Perpustakaan SMK PSM Randublatung

The library acts as a medium and a means to support teaching and learning activities at the school level. Library is one of the facilities provided by schools including the SMK PSM (Pesantren Sabilil Muttaqien) Randublatung which is one of the private schools in Blora. The library is used as a medium to increase and broaden students' insights outside of class hours but the performance of library staff is considered ineffective because they still do data processing manually so that it can cause various problems such as errors, damage and loss of data in library bookkeeping records. Based on these problems the researchers intend to build an information system with the aim of making it easier for staff to process data and be able to make the most of the technological facilities provided by the school. System development is carried out using the waterfall method and in the process of collecting data using interviews, observation and literature study. This information system was created using the Hypertext Preprocessor (PHP) programming language with the Codeigniter Framework. Researchers succeeded in building an information system that can simplify staff performance in managing the library based on the results of tests that have been carried out using the black box method to ensure that the system is running in accordance with its functions and meets user expectations.
LibGuides: Tutorial Storage: Search It

This guide stores tutorials so that librarians can easily access them and incorporate them into their research guides.
A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice?

Given an unsupervised outlier detection task, how should one select a detection algorithm as well as its hyperparameters (jointly called a model)? Unsupervised model selection is notoriously difficult, in the absence of hold-out validation data with ground-truth labels. Therefore, the problem is vastly understudied. In this work, we study the feasibility of employing internal model evaluation strategies for selecting a model for outlier detection. These so-called internal strategies solely rely on the input data (without labels) and the output (outlier scores) of the candidate models. We setup (and open-source) a large testbed with 39 detection tasks and 297 candidate models comprised of 8 detectors and various hyperparameter configurations. We evaluate 7 different strategies on their ability to discriminate between models w.r.t. detection performance, without using any labels. Our study reveals room for progress -- we find that none would be practically useful, as they select models only comparable to a state-of-the-art detector (with random configuration).
A Study on the Activation of Health Care Big Data -Focusing on the Finnish case-

4차산업혁명 시대에 이르러 IoT 의료서비스, 유전자정보를 활용한 정밀의료, AI에 의한 질병의 치료 및 진단이 가능해지면서 각국은 세계 의료시장의 주도권을 확보하기 위하여 전략적으로 보건 의료빅데이터 구축에 앞장서고 있다. 이러한 세계적 흐름에 동참하기 위하여 최근 우리 보건복지부 역시 건강보험공단·심사평가원·질병관리본부·국립암센터로 산재 되어있는 의료데이터를 연계하는 보건의료 빅데이터 활용 플랫폼 시범사업을 시작하였다. 그러나 아직 갈 길은 멀기만 하다. 보건의료 빅데이터의 활용 범위, 방법, 절차, 정보보호 조치 등에 관하여 규정하는 구체적인 법적 근거가 부재 한데다가 규제 완화라는 시대적 흐름에 역행하는 각종 과잉규제가 보건의료 빅데이터의 활용을 어렵거나 불가능하게 하고 있기 때문이다. 또한, 야심차게 시작한 보건의료 빅데이터 활용 플랫폼 시범사업 역시 연구자로 하여금 연구에 필요한 최소 수준의 데이터를 요구할 수 있도록 하고 과도하다고 판단되는 경우 데이터의 제공 자체를 반려하도록 함으로써 데이터 의존도가 높은 AI 딥러닝 알고리즘의 개발에 기여하지 못하는 반쪽자리 빅데이터에 머물고 있다. 데이터 제공 목적 역시 “정책연구, 정보보호기술, 보건의료기술연구, 건강 관련 학술연구” 등으로만 제한되어 있는데 사실상 민간이나 산업적 차원의 보건의료 빅데이터 활용 가능성 자체가 원천적으로 봉쇄됨으로써 빅데이터 활용을 통하여 헬스케어 분야의 혁신을 이루고 있는 선진국과 우리나라 간의 격차는 점점 벌어지고 있는 상황이다. 본 논문은 보건의료 빅데이터를 둘러싼 법적 사회적 쟁점을 살펴보고, 보건의료 빅데이터 활용의 선두주자인 핀란드의 개인보호 법제, 건강 및 사회적 정보의 2차 사용에 관한 법률, 핀젠 프로젝트의 사례를 중심으로 검토, 개선방안을 도출함으로써 향후 우리나라의 보건의료 빅데이터 활성화 방안에 관하여 제언하고자 한다.In the era of the Fourth Industrial Revolution, it is possible to treat and diagnose diseases by IoT medical services, precise medical care using genetic information, and AI. In order to lead the initiative of the global medical market, Countries are striving to build health and medical big data. Recently, the Ministry of Health and Welfare has also started a pilot project for the use of healthcare big data, which links medical data scattered in the Health Insurance Corporation, Review and Assessment Service, Disease Control Headquarters and National Cancer Center. However, there is still a long way to go. This is because there is no specific legal basis for defining the scope, method, procedure, and information protection measures of health care big data. Also, various over regulations that are contrary to the trend of deregulation make it difficult or impossible to use health care big data. In addition, the health care big data platform pilot project does not provide meaningful information for the formation of AI deep learning algorithms by allowing researchers only extremely limited information. The gap between advanced countries and Korea, which are innovating, is widening. This study examines the current state of health care big data use in Korea and its legal and social issues, and suggests the direction for us to move forward for the activation of health care big data by examining the case of Finnish private protection legislation, the second use of health and social information, and the Finzen project.
Leveraging Neural Machine Translation for Word Alignment

The most common tools for word-alignment rely on a large amount of parallel sentences, which are then usually processed according to one of the IBM model algorithms. The training data is, however, the same as for machine translation (MT) systems, especially for neural MT (NMT), which itself is able to produce word-alignments using the trained attention heads. This is convenient because word-alignment is theoretically a viable byproduct of any attention-based NMT, which is also able to provide decoder scores for a translated sentence pair. We summarize different approaches on how word-alignment can be extracted from alignment scores and then explore ways in which scores can be extracted from NMT, focusing on inferring the word-alignment scores based on output sentence and token probabilities. We compare this to the extraction of alignment scores from attention. We conclude with aggregating all of the sources of alignment scores into a simple feed-forward network which achieves the best results when combined alignment extractors are used.
Психологічні особливості прояву агресивності та її змістовне наповнення в юнацькому віці

International scientific and practical conference «Pedagogy and Psychology in the Modern World: the art of teaching and learning» : conference proceedings, February 26–27, 2021. Riga, Latvia : «Baltija Publishing». 444 pages.
Relationship Between Variables of pre- and post-Randomized Questions in Computer-based Tests

Cheating during assessments can be a result of poor physical arrangement of exam settings.In multiple-choice question of computer-based tests (CBT), shuffling items is used to deter students from copying answers from their colleagues.Randomizing questions and shuffling items in multiplechoice questions are meant to set a copying-disabled environment for students.This study aims to statistically verify that shuffling is suitable for preventing cheating using quantitative data.Since object awareness may compromise the effectiveness of a survey method, we used quantitative data from the students' selection of items without them being aware and to further avoid compromising the data.A total of 472 CBT data from two academic semester years of 2013 and 2016 were collected from first-year students enrolled in two exams of Cell Regulation Mechanism and Basic Human Structure.Participants data collected from test score, multiple-question selection number, and seat number.The question item number of each student was compared with the item selection of five nearby students seated in different positions.Item selection data from students enrolled in Basic Human Structure exam compared to five nearby colleagues showed a correlation coefficient of less than 0.8, indicating that there were no cases of cheating confirmed.In the case of Cell Regulation Mechanism exam, by ignoring the front seat position, (considered limitation of this study) the measurement of comparing individual students to five nearby colleagues showed a correlation coefficient above 0.8 among 13 students (n=13), about 5.8% of total students, meaning 5% of students either cheat or selected items based on their knowledge.Practically, by simply looking at the monitor of a colleague, justifying cheating is difficult; however, the measurement of quantitative data produced by the students'selection of items showed that question-shuffling and item randomization reduce cheating among students.The results of this study is also intended to introduce the feeling of a safer environment by justifying that shuffling would deter cheating.
On the self-dual codes invariant under an automorphism of type 11-(8,0)

We study self-dual codes (SD) over GF(2) with 8 cycles of length 11 in the decomposition of its automorphism and minimum weight at least 16. The main method we use is by Huffman and Yorgov and is for constructing SD codes having an automorphism of order p for a prime p > 2. We prove that [8],[4] SD codes over F210 such that their preimage is a binary code with minimum weight 20 does not exist. By restricting the matrices of the subcode to have symmetric or circulant submatrix in their systematic form, we have found many new Hermitian self-dual codes over F210. Those newly found Hermitian codes allow us to constructed 468062 new binary SD [88,44,16] doubly-even codes.
“ANDERSSEIN” IN MODERN PHYSICS: EXIT TO TRANSCENDENT

The work is devoted to the problem of the transcendent in modern physics. It is shown that the theory of relativity, but above all quantum mechanics, indicate the existence of a different mode of reality. It is with this “otherness” that the paradoxical flow of time observed in modern physics is connected.
스페인어 인상 구문(Spanish raising construction) 연구

This paper aims to explore the properties of raising and hyper raising constructions and to provide appropriate analysis for them. In this paper, we have proposed a novel analysis of raising and hyper raising constructions, based on the Phase cancellation proposed by Chomsky(2015). More specifically, we have proposed for the raising construction that T to C movement forms a structure [T [T C]], which causes CP to lose its phasehood and allows a subject DP to continue moving to main clause. One of the consequences obtained from this analysis is that raising verbs such as parecer/seem do not subcategorize TP(=IP), but CP. We have also proposed for the hyper raising construction that T moves to C too, but in this case, C forms a structure [C [C T]], based on the fact that this construction should have a lexical complementizer que/that. Under this hypothesis, we have accounted for the difference in grammaticality between Spanish and English hyper raising construction.
Linear Complementary Dual Codes Over $$\mathbb {Z}_2\mathbb {Z}_4$$

In this paper, we show that a linear code $$\mathcal {C}$$ of type $$(\alpha , \beta ; \gamma , \delta ; \kappa )$$ with $$\gamma \ne \kappa $$ over $$\mathbb {Z}_2\mathbb {Z}_4$$ generated by a matrix G is not an LCD code. When $$\gamma = \kappa $$ , we prove that the determinant of $$G_dG_d^\top $$ is a multiple of 2 and later obtain condition on G for which C is LCD or not. Finally, we shown an application of LCD codes in cryptography.
REMOTE AIR TRAFFIC CONTROL (ATC) TUTORING ASSISTANT TOOL

This paper is to introduce the remote ATC simulation tutoring assistant tool, E-tutoring tool for short, which aims to solve the problem of lack of instructors for managing ATC simulation training and adhering to restrictions such as COVID-19 social distancing requirements. The ratio of students to the instructor in the ATC simulation room is currently 6 to 1. One instructor must observe 4 students who are simultaneously doing an ATC simulation exercise. The maximum capacity of this course is 30 students per semester. By using the E-tutoring tool, we aim to mirror the students’ real-time practice scenario to a remote computer screen that can be observed by a remote ATC instructor. At the same time, the ATC instructor can communicate with the students to help them improve their practical skills. There are several benefits to applying the E-tutoring tool. Firstly, the remote instructor is not required to be present on campus, which results in huge benefits for instructors who live far from the campus and where the tutoring time needs to be very flexible, or in situations where COVID social distancing rules apply and it is not feasible to allow instructors to be in a limited space with students. In addition, the availability of increased numbers of remote instructors means that the number of student enrolments can be increased. Secondly, the teaching of ATC skills requires a lot of engagement with ATC instructors. With the E-tutoring tool, each student will receive more personalized attention and they will consequently be motivated to learn and perform better, have a better learning experience. Thirdly, such innovation in blended and online education aligns with the future of education and will result in high-quality teaching, cost-effectiveness and improved efficiency. Last but not least, some experimental results will be presented to show the output of the application of E-tutoring tool. In conclusion, the development of the E-tutoring tool will have a very positive impact on the current air space management course and offer more enrolment opportunities for students without compromising the quality of this course.
Wallet Contracts on Ethereum -- Identification, Types, Usage, and Profiles

In the area of blockchains, a wallet is anything that manages the access to cryptocurrencies and tokens. Off-chain wallets appear in different forms, from paper wallets to hardware wallets to dedicated wallet apps, while on-chain wallets are realized as smart contracts. Wallet contracts are supposed to increase trust and security by being transparent and by offering features like daily limits, approvals, multiple signatures, and recovery mechanisms. The most prominent platform for smart contracts in general and the token ecosystem im particular, and thus also for wallet contracts is Ethereum. Our work aims at a better understanding of wallet contracts on Ethereum, since they are one of the most frequently deployed smart contracts. By analyzing source code, bytecode, and execution traces, we derive usage scenarios and patterns. We discuss methods for identifying wallet contracts in a semi-automatic manner by looking at the deployed bytecodes and the on-chain interaction patterns. We extract blueprints for wallets and compile a ground truth. Furthermore, we differentiate characteristics of wallets in use, and group them into six types. We provide numbers and temporal perspectives regarding the creation and use of wallets. For the 40 identified blueprints, we compile detailed profiles. We analyze the data of the Ethereum main chain up to block 11,500,000, mined on December 22, 2020.
Neo-Orientalist Approaches in XR (Extended Reality) Applications

Being one of the most prominent reflections of intercultural interaction, orientalism is the West's description of the East according to its own beliefs and understanding. This concept also includes the alienation and isolation of the human while trying to define 'the others'. The digital culture has searched for alternative realities and identities visible through virtual worlds controlled by the individual. This search for identity has led to the transformation of a fictional and shallow imagination into a cultural commodity through various stereotypes, just like in orientalism. Extended reality is one of the new oases of neo-orientalism as a research subject that combines the concepts of virtual and augmented reality. The increasing fusion between the human mind and machines radically changes the way people are born, live, learn, work, produce, dream, discuss, or die. This research aims to interpret the effects of transformation of information in XR technologies within the axis of neo-orientalism perspective through new individual experiences.
Method of neural network recognition of falsified images

Methods for generating images falsified using Deepfake technologies and methods for detecting them are considered. A method for detecting falsified images is proposed, based on the joint use of an ensemble of convolutional neural models, the Attention mechanism and a Siamese network learning strategy. The ensembles of models were formed in different ways (using two, three or more components). The result was calculated as the average value of the AUC and LogLoss indices from all the models included in the ensemble. This approach improves the accuracy of convolutional neural network classifiers for detecting static and dynamic images created using Deepfake technologies.
Development of Site Evaluation Criteria for Woodland Burial Grounds

The demand for National Woodland Burial Grounds is expected to increase as interest in natural burial, including woodland burial, is increasing.This study was performed to provide evaluation criteria applying weighting factors to the evaluation for location selection.Through literature review, location selection evaluation factors for forest facilities, similar to forest welfare facilities, were reviewed and analyzed.As a result of the analysis, 74 preliminary evaluation criteria were selected.Based on the results, three expert groups (public servants in central and local governments and other public agencies in charge of forest welfare facility, related field researchers, and civil experts) reviewed the preliminary evaluation factors.Evaluation factors were classified into two categories, 6 sub-categories, and 22 segments.The selected evaluation factors were layered for the second preference survey.They were classified into Forest Environment and Human Environment, and those categories were further classified into three categories.Then they were further classified into segments.After segmentation, the experts who participated in the first survey checked the differences in the significance of the layered factors by utilizing AHP.The site evaluation criteria table was prepared using the evaluation criteria and the significance of each layer.In order to apply it to the candidate sites, 10 sites including the existing National Woodland Burial Grounds and 9 candidate sites considered in the previous studies were compared and analyzed including Ulju County Ulsan City, Suncheon City Jeollanam-do and Janggun-myeon Sejeong City.
Recognizing Actions in Videos from Unseen Viewpoints.

Standard methods for video recognition use large CNNs designed to capture spatio-temporal data. However, training these models requires a large amount of labeled training data, containing a wide variety of actions, scenes, settings and camera viewpoints. In this paper, we show that current convolutional neural network models are unable to recognize actions from camera viewpoints not present in their training data (i.e., unseen view action recognition). To address this, we develop approaches based on 3D representations and introduce a new geometric convolutional layer that can learn viewpoint invariant representations. Further, we introduce a new, challenging dataset for unseen view recognition and show the approaches ability to learn viewpoint invariant representations.
LIBRARIES OF SCIENTIFIC INSTITUTIONS OF THE NATIONAL ACADEMY OF SCIENCES OF UKRAINE IN THE CONDITIONS OF DIGITALIZATION

The priority for the national library and information industry is to unite the efforts of the professional community in the formation of an integrated national information environment. Using of integrated information resources leads to improved quality of products and services; effective implementation of innovations leads to economic benefits, contributes to the development of the national cultural space. At the present stage, the only way for the libraries of scientific institutions of the National Academy of Sciences of Ukraine to be active is the introduction of information technologies and the creation of telecommunication environment, which significantly expands the traditional library activity.
Prediction of User Loyalty Using the Naive Bayes Method in the "Goprint" Online Printing Marketplace

Goprint is an Online Printing Marketplace that connects printing services with users who want to print documents quickly without the need to queue. In the span of time from April 2019 to September 2019 it was found that the number of Goprint users reached 407 users, 24 partners, and 256 orders. From transactions that have been carried out by users, not a few orders are often canceled due to ineffective Goprint features or poor partner performance. This causes Goprint users to feel dissatisfied with the services provided by the Goprint application.&#x0D; The Naive Bayes algorithm is one of the algorithms used for classification or grouping of data, but can also be used for decision making. With this algorithm and the problems that occur, the authors make a system to predict the loyalty of Goprint users to anticipate users who stop leaving Goprint because they are not satisfied or loyal users. The data used as training data is 20 and testing data is 10. From the test results it is found that the value of precision is 80%, 100% recall, and 90% accuracy.
Model Checking Quantum Automata

Quantum systems are modelled as different mathematical structures, depending on their nature and complexity. This chapter considers one of the simplest (discrete-time) models of quantum systems, namely quantum automata. It introduces a way of describing linear-time (dynamic) properties of quantum systems and presents several algorithms for checking certain linear-time properties of quantum automata, for example, invariants and reachability.
Browser-Based Data Processing

Now that you understand the basics of web development, this chapter introduces two JavaScript (JS) libraries: p5.js and ml5.js. The chapter also delves deeper into JS features and syntax related to various problem-solving and application-development implementations. It then discusses various ways to use graphics and machine learning (ML) application processing interface (API) methods to actualize artificial intelligence (AI) in the browser.