Reviewerly/exHarmony huggingface dataset:
Implementasi Algoritma Rabin-Karp pada Pendeteksian Plagiarisme

Plagiarism is a crime and a scourge of science. To avoid plagiarism in scientific articles, as in the case of this research, string-matching methods can be used. This study aims to implement the Rabin-Karp Algorithm in detecting plagiarism in scientific writing based on the level of text similarity. The Rabin-Karp algorithm was chosen for this research problem because previous studies revealed that the Rabin-Karp premise is to separate the hash value of the input string from the text substring. Assuming they are the same, the character check is performed one more time, and if not, moves the substring aside. The main part of this computation exhibit is successfully calculating the hash of the substring when applied. This research is quantitative. The stages of this research flow were carried out by testing the implementation of the Rabin-Karp algorithm. Based on the calculation above, the percentage of similarity between Test Sentence 1 and Test Sentence 2 is 77.96%. Referring to previous studies, the Winnowing algorithm was found to be better at detecting text similarities than the Rabin-Karp algorithm. This is shown in the results of the similarity detection test of 30 paper documents as test data with the results of the average percentage value. Rabin-Karp Algorithm 41.41% and Winnowing Algorithm 35.15%. This study shows that the Rabin-Karp Algorithm does not work optimally in detecting text similarity, so further research needs additional methods to calculate a good level of similarity to optimize the performance of the Rabin-Karp Algorithm.
Information Analysis of Historically Significant Territories at Various Time Stages of their Development

The paper describes: a structural scheme for representing knowledge about a historically significant territory, providing a formalized informational description of a three-dimensional space model; procedural model for determining the values of the characteristics of a virtual space object; the procedure for creating a realistic virtual model of a historically significant territory, according to which conclusions should be drawn about the development of Its development; carried out Informational analysis of inaccurate data from various primary sources using fuzzy set theory. The technology of creating a virtual historical space using the developed information-logical model and software environments 3DVista Virtual Tour Pro, Twinmotion is described. As a result, a virtual tour has been obtained, which can be used for various purposes: remote consideration of issues related to objects of historical reconstruction; teaching schoolchildren, students; passing educational quests.
A Study of Korean Conditional Imperatives

The aim of this study was to investigate the concept and scope of Korean conditional imperatives and provide a comprehensive examination of the category. In Chapter 2, I argued for the usefulness of explaining conditional imperatives through a prototype theoretical approach. Conditional imperatives were defined as a broad concept of 'Imperatives interpreted in the sense of a condition or assumption.' Chapter 3 delved into a meticulous exploration of the process through which conditional imperatives acquired the meaning of a condition. We have shown that the 'then' implication arises from the relationship between the conditional and the subsequent sentence, and that the high frequency of this construction has led to the conventionality of the implication and the regularization of the interpretation of the condition. Furthermore, it was revealed that conditional sentences represent the "background circumstances that enable the speaker's subsequent actions or judgments contained in the subsequent sentence." By uttering a conditional imperatives, the speaker prompts the hearer to assume the content of the proposition, which has the effect of strongly expressing the speaker's conviction or commitment. This research sheds light on the specific features of Korean conditional imperatives as a linguistic phenomenon wherein the form of a command conveys the meaning of a condition. Although this study focused solely on Korean, further meticulous investigations are warranted to examine the commonalities and divergences between conditional imperatives in other languages, with the goal of uncovering universal principles underlying conditional imperatives worldwide.
Attention in a Family of Boltzmann Machines Emerging From Modern Hopfield Networks

Abstract Hopfield networks and Boltzmann machines (BMs) are fundamental energy-based neural network models. Recent studies on modern Hopfield networks have broadened the class of energy functions and led to a unified perspective on general Hopfield networks, including an attention module. In this letter, we consider the BM counterparts of modern Hopfield networks using the associated energy functions and study their salient properties from a trainability perspective. In particular, the energy function corresponding to the attention module naturally introduces a novel BM, which we refer to as the attentional BM (AttnBM). We verify that AttnBM has a tractable likelihood function and gradient for certain special cases and is easy to train. Moreover, we reveal the hidden connections between AttnBM and some single-layer models, namely the gaussian–Bernoulli restricted BM and the denoising autoencoder with softmax units coming from denoising score matching. We also investigate BMs introduced by other energy functions and show that the energy function of dense associative memory models gives BMs belonging to exponential family harmoniums.
On Implementing Open World Semantic Differencing for Class Diagrams.

Semantic difference analyses support engineers in understanding model-changes on the semantic level and thereby assist change management in Model Driven Development (MDD).A semantic differencing operator for Class Diagrams (CDs) compares two input models based on their legal instances and outputs object structures that are permitted by the first but not the second input-CD.Under the closed-world assumption only instances of explicitly-modeled elements are permitted.This closed-world approach may be less suited for semantic refinement checking in early design phases, where new elements are added to a CD in order to refine it.Instead, an open-world approach can be utilized.In this paper, we outline, evaluate and compare two approaches for extending CDDiff, an existing closed-world semantic differencing operator for CDs, to an open-world operator: The first approach reduces the open-world problem to a bounded search via Alloy.The second approach transforms the input-CDs and reduces the open-world problem to closed-world semantic differencing.It also allows for combining open-and closed-world interpretations of model-elements.
Learning Symbolic Model-Agnostic Loss Functions via Meta-Learning

In this paper, we develop upon the emerging topic of loss function learning, which aims to learn loss functions that significantly improve the performance of the models trained under them. Specifically, we propose a new meta-learning framework for learning model-agnostic loss functions via a hybrid neuro-symbolic search approach. The framework first uses evolution-based methods to search the space of primitive mathematical operations to find a set of symbolic loss functions. Second, the set of learned loss functions are subsequently parameterized and optimized via an end-to-end gradient-based training procedure. The versatility of the proposed framework is empirically validated on a diverse set of supervised learning tasks. Results show that the meta-learned loss functions discovered by the newly proposed method outperform both the cross-entropy loss and state-of-the-art loss function learning methods on a diverse range of neural network architectures and datasets. We make our code available at * <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">retracted</i> *.
Machine Learning Approach to Classify Breast Tissues: A Case Study Using Six-classed Breast Tissue Data

The present study investigates the effectiveness of six Machine Learning (ML) algorithms in classifying the breast tissue dataset generated using the electrical impedance spectroscopy method. This study used the breast tissue dataset available at the UCI machine learning repository, consisting of 106 spectral records with ten variables. The data were partitioned into train and test datasets. Sixty six percentage of data was allocated for the train dataset and balance for the test dataset. Six ML algorithms were tested for effectiveness using accuracy, Cohen’s Kappa, sensitivity and specificity. The results revealed that the backpropagation algorithm (BPN) produced the highest accuracy and Kappa compared to other machine learning algorithms in classifying the six-classed breast tissue dataset. Both Support Vector Machine (SVM) and K-Nearest Neighbors (KNN) produced the second-highest accuracy and Kappa. The C5.0 decision tree algorithm takes the third level. The fourth and fifth levels of accuracy are Probabilistic Neural Network (PNN) and Learning Vector Quantization (LVQ), respectively. The sensitivity of all classes by the classification of BPN was more than eighty percentage, which is higher than other machine learning algorithms. The specificity of all classes predicted by BPN was more than ninety six percentage and was comparatively at the highest level than other machine learning algorithms. Therefore, the study concludes that the backpropagation algorithm will effectively classify the six classed breast tissue data.
Full Issue

Africa Research Bulletin: Economic, Financial and Technical SeriesVolume 60, Issue 5 p. I-I Full Issue Full Issue First published: 11 July 2023 https://doi.org/10.1111/j.1467-6346.2023.11121.xAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Volume60, Issue5July 2023Pages I-I RelatedInformation
Students’ Attitude Towards Online English Language learning during COVID-19 Outbreak in the North Asia: a Case Study of North-Eastern Federal University

This article aimed to identify the attitudes of undergraduate students towards online English language learning in the North-Eastern Federal University, Russia.The questionnaire was conducted using Google form.The sample included 303 undergraduate EFL students.The research subjects are the students of Institute of Engineering and Technology, Institute of Mathematics and Information Sciences and Automobile and Road College.The research tools were questionnaire and Chi-square test.The data were interpreted in terms of three parameters: by gender, by place of residence and by academic achievement.By gender 180 respondents were male, while 123 were female.The number of rural students is 125 students, whereas urban students make up 178.The majority of students (65,7 %) are B grade students, 16,2 % of students are A grade students, 18,2 % of students are С grade students.The results of the study revealed that students have a favourable attitude to online learning.In particular, female students were statistically detected to have a more complimentary attitude to online learning than male students.In contrast, the statistics did not discover the preference of online learning by the place of residence.As it was also shown that academic performance did not affect the preference of online learning.The challenges faced by students are slow Internet connection, non-comprehension of learning material, lack of effort and interest, and lack of personal space.In addition, this study revealed the unpreparedness of university network infrastructure and its technological capacity for conducting online classes.The study discovered that students prefer an equal mix of online and face-to-face instruction.
The Issues and Logic in the Development of Elective Subjects of 2022 History Curriculum

This Article observed the issues and logic which is raised in the process in developing history electives of 2022 curriculum 「World History」, 「East Asian History Trip」, 「The Modern World on Historical Inquiry」, and analyzed how they were applied in the final curriculum draft. The outline of the history curriculum was prepared based on basic research called 「Study on Composition Plan」 and 「Study on Restructuring」. In these studies, it was decided to leave 「World History」 as a general elective, and the existing 「East Asian History」 was proposed to reduce content elements and contain the value of peace and coexistence, and the 「The Modern World on Historical Inquiry」 that combines history inquiry and modern history was conceived as a fusion elective. Finally, the content system of the electives was established through the 「Study on Draft Development」. 「World History」 was composed in the form of combining regional history and communication history and emphasizing specific topics for each unit. It was intended to ensure the differentiation from the middle school 「History」, and utilize the advantages of regional history and communication history. In addition, 「East Asian History Trip」 expanded the scope of East Asia from Northerneast to Southeast Asia in consideration of its relevance to the present, while introducing the element of trip to feel it familiar for students to study. Finally, the 「The Modern World on Historical Inquiry」 was organized to approach the tasks left in the modern world in historical context. It is important to review the pros and cons found in the content system of these electives. But I'd like to emphasize that it is also important that the discussion of the curriculum should be continued from now on, and the next curriculum should be derived based on here.
Using Affine Combinations of BBOB Problems for Performance Assessment

Benchmarking plays a major role in the development and analysis of optimization algorithms. As such, the way in which the used benchmark problems are defined significantly affects the insights that can be gained from any given benchmark study. One way to easily extend the range of available benchmark functions is through affine combinations between pairs of functions. From the perspective of landscape analysis, these function combinations smoothly transition between the two base functions.
Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions

In a seminal paper in 2013, Witt showed that the (1+1) Evolutionary Algorithm with standard bit mutation needs time (1 + o (1))n ln n/p1 to find the optimum of any linear function, as long as the probability p1 to flip exactly one bit is Θ(1). In this paper we investigate how this result generalizes if standard bit mutation is replaced by an arbitrary unbiased mutation operator. This situation is notably different, since the stochastic domination argument used for the lower bound by Witt no longer holds. In particular, starting closer to the optimum is not necessarily an advantage, and OneMax is no longer the easiest function for arbitrary starting positions.
Using the Powtoon Application as A Learning Media in Elementary School

In the world of education, the role of learning media is very necessary for students. The development of the times demands that humans are more progressive, thus students are required to find information independently from the results of interactions with the learning environment. Learning media is used to streamline the distribution of messages as a result of which there is a safe learning place. In fact, the use of learning media is still very minimal. This type of research is research and development using also applying the 4D model. The use of this learning media can make it easier for students to understand in teaching and learning activities. Through the Powtoon application, teachers can make it easier to develop learning media for students. The Powtoon application is an online animated video device that is relatively simple to use and can be used by teachers as well as students in teaching and learning.
Research on the Intention to Use and Influential Factors of Mixed Reality Software in Art Education

Recently in the rapid development of science and technology has diversified the forms of digital technology applications in the field of cultural education, and numerous scholars have extensively discussed the application of digital technology in cultural products. In this study, by integrating the Technology Acceptance Model, the Information System Success Model, and the Use and Gratification Theory, a theoretical model of influential factors on the intention to use mixed reality products was constructed. The conclusions drawn from data analysis are as follows: information quality has a positive impact on perceived usefulness and perceived ease of use; system quality does not have a positive correlation with perceived usefulness and perceived ease of use; use satisfaction does not have a positive correlation with perceived usefulness and perceived ease of use; perceived usefulness and perceived ease of use both have a positive impact on usage attitude; perceived ease of use has a positive impact on usage attitude. Based on these findings, considerations and suggestions for the design of mixed reality software in art education are proposed.
Rainfall Forcasting in Medan City Using Singular Spectrum Analysis (SSA)

Singular spectrum analysis is a time series analysis that can be used for data that has seasonal effects. Rainfall is one example that has a seasonal effect. High rainfall has an impact on natural disasters such as floods. Medan city is the capital city of North Sumatra province which has quite high rainfall and is a lowland area, so it has the potential for flooding. Rainfall forecasting can be done as disaster mitigation. The forecasting method used is SSA. The MAPE forecasting accuracy value obtained is 15.7% and the tracking signal is within tolerance limits so that it can be concluded that the forecasting is done well.
Improving Students’ Vocabulary Achievement by Using Twitter and Instagram Multimedia

This study attempts to improve students’ achievement in vocabulary by using Twitter and Instagram multimedia. This study was conducted by using classroom action research. The subject of the research was class VIII-2 SMP FREE METHODIST 2 Medan which consisted of 40 students. The research was conducted in two cycles, cycle I of four meeting and cycle II consisted of two meetings. The instruments for collecting data were quantitative data namely vocabulary test and qualitative data namely, observation sheet and questionnaire. .Based on quantitative data, in vocabulary test, students score kept improving in every test of vocabulary. The finding of this is Twitter and Instagram multimedia can improve the students’ vocabulary achievement. It can be prove from the calculation of test in both of cycles. The mean of pre test is 59. The students who got higher than 75 is 10%. The mean of post test cycle I is 75,75 and students who got higher than 75 is 26 students 65%. Te post test average on post test is 89,5, all of them 100% got higher than standard minimum. There is an improvement of the application of twitter and instagram multimedia to teach vocabulary in eight grade of SMP FREE METHODIST 2 Medan. Based on observation sheet and questionnaire sheet it was found that the students were active and enthusiastic in learning vocabulary by using twitter and instagram multmedia. The result of the research showed that twitter and instagram multimedia significantly improved students.&#x0D; Keywords: Vocabulary Achievement, Twitter, Instagram
EDUVISTA 2.0 “THE FUTURE WAY OF LEARNING”

A direct or indirect real-world representation of an environment whose components are augmented by computer produced information, ideally across many sensory modalities, is what virtual and augmented reality (AR) is all about. Augmented reality is a type of reality that is augmented digitally by the presence of virtual items in our range of vision. The basic goal of augmented reality is to incorporate elements of the digital world into a person's imagination of the actual world. This is accomplished by the integration of immersive sensations that are viewed as natural features of an environment, rather than simply displaying data. The application will mostly benefit pupils who are learning. Students can learn through interacting with virtual objects and learning materials, and by assisting students in actively interacting in the lab while completing various experiments in order to boost their understanding and learning rather than reading. Augmented Reality is a breakthrough technology that could considerably ease execution of complex operations. Augmented Reality mixes virtual and actual reality, making available to the user new tools to ensure efficiency in the transfer of knowledge for several processes and in several environments. Various solutions based on Augmented Reality have been proposed by the research community: particularly in maintenance operations Augmented Reality tools have offered new perspectives and have promised dramatic improvements. On the other side Augmented Reality is an extremely demanding technology and, at the present day, it is still affected by serious flaws that undermine its implementations in the industrial context.
Cryptoassets – Perspectives of Accountancy Recognition in the Technological Era

The growth of the cryptoassets phenomena, along with the lack of applicable accounting rules, offers difficult issues for financial reporting specialists in Romania. Therefore, handling the accounting of cryptoassets requires a detailed understanding of both cryptoassets technology and operation, as well as key accounting concepts. In the absence of steps made to control this sort of transactions through accounting standards, holders of cryptoassets are unable to apply the proper accounting treatment for the activity in which they are involved. The regulatory international framework for cryptoassets needs to be consistent and standards should be developed to safeguard holders. The European Economic and Social Committee believes it is important to treat non-financial products based on blockchain technology as physical assets, and not as financial instruments, following the principle of "same activity, same risk, same rules". Others, argue that digital currencies should be recorded as: cash equivalents or cash, inventories, financial or intangible assets. As a result, the purpose of this article is to overview the accounting treatment perspectives given by the IFRS in comparison with the Order of the minister of public finance no.1802/2014 regarding the possible treatments of cryptoassets. Furthermore, the authors believe this article can contribute to accounting research by providing a direction to accounting regulators. Based on the review of specialised literature, existing standards and legislation, the paper indicates that the relevant accounting approaches to cryptoassets are as intangible assets, stock or fixed assets held for sale. However, they could also be seen as means of payment, like foreign currency, even if they do not meet the characteristics of cash. The perspectives on the taxation of cryptoassets are provided by analysing the types of taxes and the VAT regime applicable to cryptoassets, according to the Romanian Fiscal Code, the existing ANAF rules and the VAT Directive at European level. At the same time, the authors analysed and presented certain statistical data, such as the market capitalisation of cryptoassets, the degree of acceptance and the usage degree of cryptocurrencies worldwide, which show that there is a tendency to increase their use.