Reviewerly/exHarmony huggingface dataset:
Sistem Informasi Peminjaman dan Pengembalian Rekam Medis Rawat Inap Berbasis Web di RSUD Haji Surabaya

The recording, borrowing and returning of medical record documents at the Haji Hospital in Surabaya still uses a manual borrowing expedition book in the filing section. The medical record documents returned are not in accordance with the SOP (Standard Operating Procedure) and SPM (Minimum Service Standard) of the hospital. The purpose of this study was to design and create a web-based information system for borrowing and returning medical records at the Haji Hospital in Surabaya. The method used in this research is waterfall. The stages of the waterfall method are requirements analysis, system design, system creation and system testing. Data collection was done by interview, observation, and documentation. The result of this research is a web-based information system for borrowing and returning medical records. Suggestions for the Haji Hospital of Surabaya are expected to be able to use a web-based information system for borrowing and returning medical records to facilitate the electronic recording process, speed up reporting and reduce the incidence of delays.
Correction: “Viewing Mobile Health Technology Design Through the Lens of Amplification Theory”

[This corrects the article DOI: 10.2196/31069.].
BRAZILIANS' PERSPECTIVE ON CRYPTOCURRENCIES

The advance in science and technology combined with the development of the Internet offers new options for the use of money. Economic agents are beginning to lose physical contact with money and carry out transactions through electronic channels. The debate on the subject is of international relevance and foresees the manifestation of the monetary authority, which shows the importance of the subject. This paper sought to present the theories of demand for cryptocurrencies, discuss the perspective of Brazilians in relation to digital assets, and show the role of cryptocurrencies in the current economy. This study aimed to identify how the growth in demand for cryptocurrencies can impact the financial system and the globalized economy. The methodology employed is bibliographical, documental, and field research on the monetary evolution and the perspective of Brazilians in relation to crypto assets. Based on the online questionnaire conducted with 170 respondents who answered about what they understand by digital assets, it was observed that most of them are not used to the theme in question, however, there is a great interest in learning. It is concluded that compared to sovereign currencies, cryptocurrency meets monetary demand in isolation, in each context and period.
COINTEGRATION RELATIONSHIP BETWEEN CRYPTO COINS AND BIST100: ARDL LIMIT TEST APPROACH

In this study, it’s aimed to determine the cointegration relationship between cryptocurrencies and BIST 100. For this purpose, the BIST 100 index closing score for a total of 1001 business days between 01.01.2018 and 31.12.2021 and the prices of the five cryptocurrencies (Bitcoin, Ethereum, Binance Coin, TETHER, Cardano) with the highest market value as of 31.12.2021. A data set was created and analyzed with the ARDL bounds test model. Before the ARDL bounds test, the extent to which the variables are stationary was tested with the Extended Dickey Fuller (ADF) unit root test. Accordingly, the variables used in the study showed stationarity at the first difference. Then, with the F bounds test, it was tested whether there was a cointegration relationship between the variables. As a result of the boundary test applied to 12 different models, it was seen that there was no cointegration relationship between cryptocurrencies and BIST 100.
Paraconsistent Logic Programming in Three and Four-Valued Logics

Abstract From the interaction among areas such as Computer Science, Formal Logic, and Automated Deduction arises an important new subject called Logic Programming. This has been used continuously in the theoretical study and practical applications in various fields of Artificial Intelligence. After the emergence of a wide variety of non-classical logics and the understanding of the limitations presented by first-order classical logic, it became necessary to consider logic programming based on other types of reasoning in addition to classical reasoning. A type of reasoning that has been well studied is the paraconsistent, that is, the reasoning that tolerates contradictions. However, although there are many paraconsistent logics with different types of semantics, their application to logic programming is more delicate than it first appears, requiring an in-depth study of what can or cannot be transferred directly from classical first-order logic to other types of logic. Based on studies of Tarcisio Rodrigues on the foundations of Paraconsistent Logic Programming (2010) for some Logics of Formal Inconsistency ( LFI s), this thesis intends to resume the research of Rodrigues and place it in the specific context of LFI s with three- and four-valued semantics. This kind of logics are interesting from the computational point of view, as presented by Luiz Silvestrini in his Ph.D. thesis entitled “A new approach to the concept of quase-truth” (2011), and by Marcelo Coniglio and Martín Figallo in the article “Hilbert-style presentations of two logics associated to tetravalent modal algebras” [ Studia Logica (2012)]. Based on original techniques, this study aims to define well-founded systems of paraconsistent logic programming based on well-known logics, in contrast to the ad hoc approaches to this question found in the literature. Abstract prepared by Kleidson Êglicio Carvalho da Silva Oliveira. E-mail : kecso10@yahoo.com.br URL : http://repositorio.unicamp.br/jspui/handle/REPOSIP/322632
Exploring the Relationship between Student Achievement and Extrovert School Leadership

This study aims at exploring the relationship between extrovert school leadership and their academic performance in terms of student academic achievement.The key research objectives involve to identify secondary school leadership as extrovert or introvert and to determine the academic performance.The study adopts positivist paradigm, uses survey method and follows a co relational research design.Two adapted questionnaires of Eysenck (1967) and Stronge (2011) are used to investigate the extroversion⁄ introversion personality traits and academic performance of secondary school principals respectively.Population of the study comprises 32 secondary school principals and 471 teachers of working in Federal Government Educational Institutions (FGEIs).Sample is selected using random sampling technique and it comprises 270 subjects including 32 secondary school principals and 238 teachers.Pearson correlation is applied using SPSS (Version 21.0) to find out relationship between the personality trait of extroversion and academic performance.The study reveals that majority of extrovert school principals' focus to improve overall learning environment of the school.They are found to be positively correlated with their academic performance.The study recommends that the school principals should be provided proper awareness about the desired performance standards.Principals should be encouraged to adopt positive personality trait of extroversion in order to enhance student academic achievement
THE USE OF QUESTION ANSWER-RELATIONSHIP (QAR) STRATEGY ON IMPROVING STUDENTS’ READING COMPREHENSION AT SMAN 1 JATITUJUH

Abstract. The objectives of this research are to find out whether or not there is a significant of difference between the Reading Comprehension of the Twelfth Grade Students of SMAN 1 Jatitujuh taught before and after using the Question-Answer Relationship (QAR) strategy. The method in this study was quantitative. The subject of this research is students in XII MIPA 1. The research instrument used by the writer is a test (pre-test and post-test) The result of this research, it was found that of the reading comprehension of the twelfth-grade students of SMAN 1 Jatitujuh before being taught by using QAR strategy was sufficient, the mean is 69.71. Meanwhile of the reading comprehension of the twelfth grade students of SMAN 1 Jatitujuh after being taught by QAR strategy was categorized good, the mean is 85. Moreover, the calculation of the t-count, the score is 11.867 was higher than t-table, score is 2.032 (11.867 &gt; 2.032) in level significance 5%. Based on the result above, it could be concluded that Question Answer Relationship (QAR) strategy could improve reading comprehension of the twelfth grade students of SMAN 1 Jatitujuh. In addition, the subjects also responded positively the implementation of QAR strategy.
The Use of Linguistic Features in Indonesian Students’ Texts at Hungarian Universities

Students enrolled in a higher level of education may face challenges in producing assignments, including writing an essay. They need to present appropriate linguistic features in the text to demonstrate their writing quality. Comparing linguistic features during university study is one fundamental aspect of administering writing quality and showing student writing development. The topic presented in this study describes an initial statistical analysis and the frequency of linguistic features in the texts produced by Indonesian graduate students enrolled at Hungarian universities. This study proposed two research questions: 1) How frequently do pre-selected linguistic features appear in the texts of Indonesian graduate students? 2) How do these features appear in a paired T-test statistical analysis? Seven MSc and MA graduate students took part in the study to meet the goal. They are students at three different universities in Hungary, which all have a Social Science Faculty. During their second-year studies, fourteen essays with a minimum text length of 2000 words were collected. The findings revealed an increase in conjunctions, adjectives, abstract nouns, concrete nouns, noun phrases, expanded noun phrases, active verbs, verb phrases, and passive forms. Meanwhile, the frequency of linguistic features such as prepositions, definite articles, indefinite articles, noun clauses, adverbial clauses, and adjective clauses decreased. In addition, both the rise of nine linguistic features and the decrease of six features in the second semester are not statistically significant.
Open-Source Datasets for Recommender Systems Analysis

There are different traditional and nontraditional datasets available to investigate the performance of recommender systems. This article focuses on the different datasets required for the investigation of recommender systems.
Adversarial Zoom Lens: A Novel Physical-World Attack to DNNs

Although deep neural networks (DNNs) are known to be fragile, no one has studied the effects of zooming-in and zooming-out of images in the physical world on DNNs performance. In this paper, we demonstrate a novel physical adversarial attack technique called Adversarial Zoom Lens (AdvZL), which uses a zoom lens to zoom in and out of pictures of the physical world, fooling DNNs without changing the characteristics of the target object. The proposed method is so far the only adversarial attack technique that does not add physical adversarial perturbation attack DNNs. In a digital environment, we construct a data set based on AdvZL to verify the antagonism of equal-scale enlarged images to DNNs. In the physical environment, we manipulate the zoom lens to zoom in and out of the target object, and generate adversarial samples. The experimental results demonstrate the effectiveness of AdvZL in both digital and physical environments. We further analyze the antagonism of the proposed data set to the improved DNNs. On the other hand, we provide a guideline for defense against AdvZL by means of adversarial training. Finally, we look into the threat possibilities of the proposed approach to future autonomous driving and variant attack ideas similar to the proposed attack.
Data hiding to the image with bit plane slicing and double XOR

Data hiding is done in different environments and with different techniques, and applications in this area attract a lot of attention. In data hiding, the method of securing the data in the image by hiding data is one of the steganography methods. Bit Plane Slicing, one of the techniques applied in image steganography, is a reliable technique applied on images such as data hiding or compression, which allows us to operate on some special bits by separating each pixel that makes up the image into planes. This technique is aimed to provide high image quality and data security. In this study, two encryption layers and a concealment stage are proposed. Here, the bit planes of the three channels of the color image were first extracted using the BPS technique. The message to be hidden later was encrypted using a double XOR operation using binary representation and a secret key (extracted from the MSB). Then, the stream of encrypted bits is hidden in the cover image using the least significant bit plane. Well-known evaluation criteria such as MSE, PSNR, and histogram distribution were calculated to ensure the quality of the proposed method. Experimental results show that the proposed method has acceptable results and maintains the security of confidential text messages.
A glance at blockchain technology and cryptocurrencies as an application

Blockchain technology, which includes cryptocurrencies such as Bitcoin, Ethereum,…etc [1,2] which has been evaluated as an investment tool by many people all over the world in recent years, needs to be examined in details, both mathematically and conceptually [8,9]. In fact, it can be said that blockchain technology, which is characterized as an accounting system and database based on distributed ledgers in its most basic form, is extremely secure in terms of copying data or attacking. For this reason, we can say that technology has a more effective security mechanism than any central state-of-the-art authoritative system used today. However, as it is almost impossible to bring all of the security, speed and cost parameters to their full extend in a system at the same time, as in any cryptosystem, the security parameter from the distributed ledger structure in blockchain technology adversely affects the speed and cost parameters. In this article, we discuss the cryptographic working principles of cryptocurrencies, which is an application field of blockchain technology, together with blockchain technology and the features and structures of the blocks contained.
SC-Ques: A Sentence Completion Question Dataset for English as a Second Language Learners

Sentence completion (SC) questions present a sentence with one or more blanks that need to be filled in, three to five possible words or phrases as options. SC questions are widely used for students learning English as a Second Language (ESL). In this paper, we present a large-scale SC dataset, \textsc{SC-Ques}, which is made up of 289,148 ESL SC questions from real-world standardized English examinations. Furthermore, we build a comprehensive benchmark of automatically solving the SC questions by training the large-scale pre-trained language models on the proposed \textsc{SC-Ques} dataset. We conduct detailed analysis of the baseline models performance, limitations and trade-offs. The data and our code are available for research purposes from: \url{https://github.com/ai4ed/SC-Ques}.
DEVELOPMENT OF LECTORA-BASED LEARNING MEDIA IN BASIC CULINARY COURSES TO IMPROVE STUDENT LEARNING OUTCOMES IN THE CULINARY STUDY PROGRAM AT UNIMED

The aim of this study was to develop learning media for basic culinary course. The study type is study and development using the 4D model, namely define, design, develop, and disseminate. The subjects of this study were 3 media experts, 3 content experts, and 23 students of the culinary education study program. Data collection technique used a questionnaire. Data analysis technique used a descriptive method. The results showed that the Lectora based learning media for culinary course according to content experts was in very good category with an average of 97,64 percent. According to media experts, Lectora based learning media was very good with an average of 94,45 percent. According to users, Lectora based learning media was very good with an average of 94,84 percent. Therefore, it can be concluded that the developed Lectora based learning media for basic culinary course is categorized as very good and can be used as independent learning media for students of the Culinary Education Study Program.
Semantics modulo satisfiability with applications: function representation, probabilities and game theory

Abstract In the context of propositional logics, we apply semantics modulo satisfiability—a restricted semantics which comprehends only valuations that satisfy some specific set of formulas—with the aim to efficiently solve some computational tasks. Three possible such applications are developed. We begin by studying the possibility of implicitly representing rational McNaughton functions in Łukasiewicz Infinitely-valued Logic through semantics modulo satisfiability. We theoretically investigate some approaches to such representation concept, called representation modulo satisfiability, and describe a polynomial algorithm that builds representations in the newly introduced system. An implementation of the algorithm, test results and ways to randomly generate rational McNaughton functions for testing are presented. Moreover, we propose an application of such representations to the formal verification of properties of neural networks by means of the reasoning framework of Łukasiewicz Infinitely-valued Logic. Then, we move to the investigation of the satisfiability of joint probabilistic assignments to formulas of Łukasiewicz Infinitely-valued Logic, which is known to be an NP-complete problem. We provide an exact decision algorithm derived from the combination of linear algebraic methods with semantics modulo satisfiability. Also, we provide an implementation for such algorithm for which the phenomenon of phase transition is empirically detected. Lastly, we study the game theory situation of observable games, which are games that are known to reach a Nash equilibrium, however, an external observer does not know what is the exact profile of actions that occur in a specific instance; thus, such observer assigns subjective probabilities to players actions. We study the decision problem of determining if a set of these probabilistic constraints is coherent by reducing it to the problems of satisfiability of probabilistic assignments to logical formulas both in Classical Propositional Logic and Łukasiewicz Infinitely-valued Logic depending on whether only pure equilibria or also mixed equilibria are allowed. Such reductions rely upon the properties of semantics modulo satisfiability. We provide complexity and algorithmic discussion for the coherence problem and, also, for the problem of computing maximal and minimal probabilistic constraints on actions that preserves coherence. Abstract prepared by Sandro Márcio da Silva Preto. E-mail : spreto@ime.usp.br URL: https://doi.org/10.11606/T.45.2021.tde-17062021-163257
Drug Delivery Control Using Iron Oxide Nanoparticles in Three-Dimensional Magnetic Resonance Imaging: A Descriptive Approach

The goal of this chapter is to explain how iron oxide nanoparticles are employed in 3D MRI to control drug distribution. It explains how to use MRI scans to detect and differentiate the cluster intensity produced by Iron oxide nanoparticles (IO-NPs) in order to assess medication delivery efficacy. The infected mouse's calf's eye was injected with IO-NPs linked to macrophages. The situation was difficult due to the limited resolution of MRI and the small size of the IO-NPs. Because of their high intensity in MRI, IO-NPs serve as a marker, allowing us to track the macrophages' progress. The location and amount of IO-NPs propagating into the inflamed mouse leg were calculated using an image processing approach. To choose the region of interest, a fuzzy Clustering technique was used (ROI). The detection and extraction of IO-NPs in MRI images were done using a 3D model of the femoral area. The obtained results show that the proposed strategy is effective in improving the control process of targeted drug delivery. It aids in therapy optimization and opens up a viable new research avenue for nanomedicine applications.
Parallel implementation of CNOT$^{\text{N}}$ and C$_k$NOT$^N$ gates via  homonuclear and heteronuclear F\"{o}rster interactions of Rydberg atoms

We analyze the schemes of high-fidelity multiqubit CNOT$^{\text{N}}$ and C$_k$NOT$^N$ gates for alkali-metal neutral atoms used as qubits. These schemes are based on the electromagnetically induced transparency and Rydberg blockade, as proposed by M. M\"{u}ller et al. [PRL 102, 170502 (2009)]. In the original paper the fidelity of multi-qubit CNOT$^{\text{N}}$ gate based on Rydberg blockade was limited by the interaction between target atoms, and by the coupling laser intensity. We propose overcoming these limits by using strong asymmetric homonuclear and heteronuclear dipole-dipole interactions via F\"{o}rster interactions between the control and target atoms, while the target atoms remain coupled by weaker van der Waals interaction. We have optimized the gate performance in order to achieve higher fidelity, while keeping coupling laser intensity as small as possible in order to improve the experimental feasibility of the gate schemes. We also considered optimization of schemes of C$_k$NOT$^N$ gates, where the fidelity is also affected by the relation between the control-control, control-target and target-target interaction energies. Our numeric simulations confirm that the fidelity of CNOT$^4$ gate (single control and four target atoms) can be up to $98.5\%$ and the fidelity of C$_2$NOT$^2$ (two control and two target atoms) is up to $99.3\%$ for the conditions which are experimentally feasible.
Ability to Predict Melanoma Within 5 Years Using Registry Data and a Convolutional Neural Network: A Proof of Concept Study

Research relating to machine learning algorithms, including convolutional neural networks, has increased during the past 5 years. The aim of this pilot study was to investigate how accurately a convolutional neural network, trained on Swedish registry data, could perform in predicting cutaneous invasive and in situ melanoma (CMM) within 5 years. A cohort of 1,208,393 individuals was used. Registry data ranged from 4 July 2005 to 31 December 2011, predicting CMM between 1 January 2012 and 31 December 2016. A convolutional neural network with one-dimensional convolutions with respect to time was trained using healthcare databases and registers. The algorithm was trained on 23,886 individuals. Validation was performed on a holdout validation set including 6,000 individuals. After training and validation, the convolutional neural network was evaluated on a test set (1,000 individuals with an CMM occurring within 5 years and 5,000 without). The area under the receiver-operating characteristic curve was 0.59 (95% confidence interval (95% CI) 0.57-0.61). The point on the receiver-operating characteristic curve where sensitivity equalled specificity had a value of 56% (sensitivity 95% CI 53-60% and specificity 95% CI 55-58%). Albeit at an early stage, this pilot investigation demonstrates potential usefulness for machine learning algorithms in predicting melanoma risk.