Reviewerly/exHarmony huggingface dataset:
An evaluation of the effectiveness of e-learning in the context of the Corona pandemic in the public schools of the Northern Jordan Ghour: دراسة تقييمية لفاعلية التعليم الإلكتروني في ظل جائحة كورونا في المدارس الحكومية التابعة للواء الأغوار الشمالية بالأردن

This study was aimed at assessing the effectiveness of e-learning in the context of the Corona pandemic in the public schools of the Northern Jordan Ghour, and used the descriptive analytical curriculum, and the study sample consisted of (184 students, 68 teachers, 58 guardian, 15 educational supervisors and 15 school principals) from the Directorate of Education of the Northern Jordan Ghour. The results of the study revealed that the evaluation of the effectiveness of e-learning in the context of the Corona crisis from the point of view of teachers was (medium) with mathematical average (3.39 out of 5), and the evaluation of the effectiveness of e-learning in the context of the Corona crisis from the point of view of students was (medium) with mathematical average (2.98). Assessing the effectiveness of e-learning in the context of the Corona crisis from the point of view of public-school principals and educational supervisors was (medium) with an average of (3.14) and an assessment of the effectiveness of e-learning in the context of the Corona crisis from the point of view of parents was (high) with a mathematical average (3.51). It also found that there were no statistically significant differences at the level of (α≤0.05) an evaluation study of the effectiveness of e-learning under the Corona pandemic in the Northern Ghour Public Schools due to gender change. The researcher recommended working on establishing the infrastructure for the use of e-learning techniques, and holding training courses for teachers, supervisors, school principals, students and parents on e-learning. Parents need to be aware of the importance of using technology to enrich the learning process to ensure the successful use of e-learning techniques, and the need for preventive and supervisory education, while promoting the values of self-education among learners.
Meningkatkan Keterampilan Literasi Informasi dalam Pembelajaran Sejarah Menggunakan Metode Double Loop Problem Solving (DLPS)

Information literacy skills in history learning are important skills to be developed. This research is motivated by the low information literacy skills of students in learning history. These indications can be seen from the ability to analyze the connectedness of historical events and the ability to process student information. Based on these problems, the researchers formulated several problems that were taken in the study including: first, how to plan history learning using the Double Loop Problem Solving (DLPS) method through E-Learning. Second, how to apply history learning using the Double Loop Problem Solving (DLPS) method through E-Learning. Third, how to improve information literacy skills using the Double Loop Problem Solving (DLPS) method in learning history through E-Learning. [F1] Fourth, How to overcome obstacles in using the Double Loop Problem Solving (DLPS) method in history learning through E-Learning. This study aims to improve students' information literacy skills in learning history. This study uses the research design of Kemmis and McTaggart which includes planning, implementation, observation, and reflection. The researched aspects of information literacy skills are recognizing needed information, accessing relevant information, selecting and comparing information from different sources, evaluating appropriate information, organizing and using information efficiently, combining and constructing information into knowledge. new, and communicating and reflecting information. Based on the results of research conducted, the use of Double Loop Problem Solving (DLPS) can improve students' information literacy skills in learning history. In the first cycle the average percentage is 50.4%, the second cycle is 60%, and the third cycle is 82.8%.
The Death of the AI Author

Much of the second-generation literature on AI and authorship asks whether an increasing sophistication and independence of generative code should cause us to rethink embedded assumptions about the meaning of authorship, arguing that recognizing the authored nature of AI-generated works may require a less profound doctrinal leap than has historically been suggested. In this essay, we argue that the threshold for authorship does not depend on the evolution or state of the art in AI or robotics. Instead, we contend that the very notion of AI-authorship rests on a category mistake: it is not an error about the current or potential capacities, capabilities, intelligence or sophistication of machines; rather it is an error about the ontology of authorship. Building on the established critique of the romantic author figure, we argue that the death of the romantic author also and equally entails the death of the AI author. We provide a theoretical account of authorship that demonstrates why claims of AI authorship do not make sense in terms of 'the realities of the world in which the problem exists.' (Samuelson, 1985) Those realities, we argue, must push us past bare doctrinal or utilitarian considerations of originality, assessed in terms of what an author must do. Instead, what they demand is an ontological consideration of what an author must be. The ontological question, we suggest, requires an account of authorship that is relational; it necessitates a vision of authorship as a dialogic and communicative act that is inherently social, with the cultivation of selfhood and social relations as the entire point of the practice. Of course, this ontological inquiry into the plausibility of AI-authorship transcends copyright law and its particular doctrinal conundrums, going to the normative core of how law should — and should not — think about robots and AI, and their role in human relations.
‘Cyber’ – the ‘digital’ gold for Nigerian criminals

Powerful and sophisticated criminal syndicates based in Nigeria have extensive networks reaching into the Western Hemisphere, Europe, Russia, and the newly independent states, Southeast and Southwest Asia, Australia, and other countries in Africa. This chapter looks to determine if the movement of Nigerian criminals online may strengthen or weaken this relationship. It briefly examines the political–criminal nexus, tracing it through the evolution over the last 100 years of four crime types which are synonymous with Nigeria. It examines if online Nigerian organised criminals and criminality hold the same mantle as they do in the offline world, and if so, will try to assess what this might mean for Nigeria, its people, and Nigerian OC in Nigeria. The 1980s are often suggested to be the period when Nigerian OC established itself both home and abroad. Corruption is synonymous with Nigeria and has been for decades, predating independence in the 1960s.
Flexible Supplier Selection of WASPAS based on Hesitant Cloud Language

To ensure the continuity and stability of the supply chain under the sudden crisis, flexible supplier selection has taken up an important position in the operation decision of enterprises. Considering the differences of different expert decision-making and decision-making results that contain fuzziness, randomness and hesitation, the flexible supplier selection was studied by using the method of combining hesitant fuzzy language with normal cloud model and hesitant cloud linguistic term set was established. The weights were calculated according to the decision quality and aggregated with the evaluation results. Finally, WASPAS was used for scheme sorting to select the best supplier. The validity and applicability of the model were verified by a case study, which provided a scientific basis for enterprise decision makers to avoid interruption risk.
Factors Affecting Blockchain Technology Application in the Logistics Industry: An Empirical Study Based on Chinese Listed Companies

Purpose - Blockchain technology can authentically record and transmit the flow of funds, logistics, and information as well as optimize resource utilization, compress intermediate links, and improve the overall efficiency of the logistics industry. Analyzing how blockchain is applied in the logistics industry and identifying the factors affecting blockchain technology application are the main purpose of this research paper. Design/Methodology/Approach - ased on the panel data, this paper utilizes a binary choice model to analyze the influencing factors affecting the blockchain technology application at the micro-level of logistics listed companies in China. Findings - This paper is an empirical study on the application of blockchain technology in the logistics industry. This study shows that a company’s size, ownership structure, and employee education level are critical factors that have a significant influence on the company’s application of blockchain technology. Research Implications - Through the literature study, it can be understood that blockchain technology is being applied by various drivers related to the improvement of corporate performance and competitiveness in the logistics industry. In addition, this empirical study shows that the polarization of competitiveness within the industry can be deepened as digital transformation technologies such as blockchain are introduced mainly by large companies. At the same time, it can be seen that the flexibility of decision-making structures and the securing of high-quality human resources are important for the introduction of innovative technologies.
Information-theoretic generalization bounds for black-box learning algorithms

We derive information-theoretic generalization bounds for supervised learning algorithms based on the information contained in predictions rather than in the output of the training algorithm. These bounds improve over the existing information-theoretic bounds, are applicable to a wider range of algorithms, and solve two key challenges: (a) they give meaningful results for deterministic algorithms and (b) they are significantly easier to estimate. We show experimentally that the proposed bounds closely follow the generalization gap in practical scenarios for deep learning.
An Analytical Reasoning Framework for Visual Analytics Representation

Analytical Reasoning is the foundation of visual analytics, assisted via interactive and dynamic visualization representation. The main concern of visual analytics is the analytics process itself, it is important to facilitate the human mental space during the analysis process by embedding the analytical reasoning in the visual analytics representation. This paper aims to introduce and describe the essential analytical reasoning features within visual analytics representation. The framework describes analytical reasoning features from three parts of visual analytics representation which are higher-level structure, interconnection and lower-level structure. For higher-level structure, we proposed the features of big picture, analytics goal and insights through storytelling to ensure the analytics output becomes knowledge and applicable to facilitate the business decision. For interconnection, the features of trend, pattern and relevancy induce a relationship between higher and lower-level structures. Finally, analytical reasoning features for lower-level structure are quite straightforward which are benchmarking, ranking, decluttering, clueing and filtering. It is hoped that this framework could help to shed some light in terms of understanding analytical reasoning features that can facilitate the business decision.
Natural Language Processing through the Subtractive Mountain Clustering Algorithm - A Medication Intake Chatbot

In this work, the subtractive mountain clustering algorithm has been adapted to the problem of natural languages processing in view to construct a chatbot that answers questions posed by the user. The implemented algorithm version allosws for the association of a set of words into clusters. After finding the centre of every cluster — the most relevant word, all the others are aggregated according to a defined metric adapted to the language processing realm. All the relevant stored information (necessary to answer the questions) is processed, as well as the questions, by the algorithm. The correct processing of the text enables the chatbot to produce answers that relate to the posed queries. Since we have in view a chatbot to help elder people with medication, to validate the method, we use the package insert of a drug as the available information and formulate associated questions. Errors in medication intake among elderly people are very common. One of the main causes for this is their loss of ability to retain information. The high amount of medicine intake required by the advanced age is another limiting factor. Thence, the design of an interactive aid system, preferably using natural language, to help the older population with medication is in demand. A chatbot based on a subtractive cluster algorithm is the chosen solution.
Jackson-type theorem on approximation by non-stationary periodic wavelets

In this paper, sufficient conditions on non-stationary periodic wavelet systems to provide good approximation properties of wavelet expansions are established. The approximation error is estimated in terms of modulus of continuity in [Formula: see text]-spaces.
Semantic-aware Representation Learning Via Probability Contrastive Loss

Recent feature contrastive learning (FCL) has shown promising performance in unsupervised representation learning. For the close-set representation learning where labeled data and unlabeled data belong to the same semantic space, however, FCL cannot show overwhelming gains due to not involving the class semantics during optimization. Consequently, the produced features do not guarantee to be easily classified by the class weights learned from labeled data although they are information-rich. To tackle this issue, we propose a novel probability contrastive learning (PCL) in this paper, which not only produces rich features but also enforces them to be distributed around the class prototypes. Specifically, we propose to use the output probabilities after softmax to perform contrastive learning instead of the extracted features in FCL. Evidently, such a way can exploit the class semantics during optimization. Moreover, we propose to remove the $\ell_{2}$ normalization in the traditional FCL and directly use the $\ell_{1}$-normalized probability for contrastive learning. Our proposed PCL is simple and effective. We conduct extensive experiments on three close-set image classification tasks, i.e., unsupervised domain adaptation, semi-supervised learning, and semi-supervised domain adaptation. The results on multiple datasets demonstrate that our PCL can consistently get considerable gains and achieves the state-of-the-art performance for all three tasks.
Definition Modelling for Appropriate Specificity.

Definition generation techniques aim to generate a definition of a target word or phrase given a context. In previous studies, researchers have faced various issues such as the out-of-vocabulary problem and over/under-specificity problems. Over-specific definitions present narrow word meanings, whereas under-specific definitions present general and context-insensitive meanings. Herein, we propose a method for definition generation with appropriate specificity. The proposed method addresses the aforementioned problems by leveraging a pre-trained encoder-decoder model, namely Text-to-Text Transfer Transformer, and introducing a re-ranking mechanism to model specificity in definitions. Experimental results on standard evaluation datasets indicate that our method significantly outperforms the previous state-of-the-art method. Moreover, manual evaluation confirms that our method effectively addresses the over/under-specificity problems.
Towards Incremental Transformers: An Empirical Analysis of Transformer Models for Incremental NLU

Incremental processing allows interactive systems to respond based on partial inputs, which is a desirable property e.g. in dialogue agents. The currently popular Transformer architecture inherently processes sequences as a whole, abstracting away the notion of time. Recent work attempts to apply Transformers incrementally via restart-incrementality by repeatedly feeding, to an unchanged model, increasingly longer input prefixes to produce partial outputs. However, this approach is computationally costly and does not scale efficiently for long sequences. In parallel, we witness efforts to make Transformers more efficient, e.g. the Linear Transformer (LT) with a recurrence mechanism. In this work, we examine the feasibility of LT for incremental NLU in English. Our results show that the recurrent LT model has better incremental performance and faster inference speed compared to the standard Transformer and LT with restart-incrementality, at the cost of part of the non-incremental (full sequence) quality. We show that the performance drop can be mitigated by training the model to wait for right context before committing to an output and that training with input prefixes is beneficial for delivering correct partial outputs.
외국인 대학원생의 학술적 글쓰기에 나타난 바꿔 쓰기 양상 연구 -한국인 대학원생과의 비교를 중심으로-

This study suggests ways for paraphrasing education to foreign graduate students by comparing the patterns between Korean graduate students and foreign graduate students on paraphrasing in academic writing. To this end, this study conducted an experiment and interview to analyze paraphrasing patterns in the academic writing of Korean and foreign graduate students. The experiment results showed that Korean and foreign graduate students used paraphrasing in words, sentences, and paragraphs. However, foreign graduate students had a different pattern of changing a word than Korean graduate students and used awkward or incorrect sentences when they used combinations of paraphrasing types. Meanwhile, the interview results showed that foreign graduate students had difficulty using paraphrasing in academic writing, and the paraphrasing process was more challenging to write than to read. Moreover, they focused on using appropriate vocabulary, grammar, and expressions rather than the overall structure or content. Consequently, this study proposed helpful education directions for enhancing the paraphrasing skills in academic writing of foreign graduate students. (Korea University)
Лінгвокомунікативні риси текстів статусів соціальних мереж

The article has been devoted to the study of the peculiarities of status texts observed within the social network webpages, as the linguistic research on network media communication is turning into one of the most promising areas for the development of humanitarian knowledge. Extralinguistic parameters of modern electronic media are characterized by multimedia features i.e. they represent different types of verbal texts, together with photos, pictures and other visual images. Such type of presentation is known as creolized texts. Written virtual communication on the Internet presupposes the ability to present the information in a compressed way. Varieties of the Internet communication give way to new types of communicative situations in which new genres appear. Structure, style, content and the type of the target audience differentiate peculiar Internet genres. Considering the problem of genre differentiation, foreign linguistics first confronts two key genres: news and views. In our opinion, status texts are able to combine different functions, from informative to entertaining, depending on the intention of the author of the webpage. The most striking representatives of texts that embody the essential features and characterize how they are perceived in the mind of a person and associated with the mode of his knowledge and experience, are small format texts. A status text as a subtype small format texts possess the characteristics of intertextuality, special pragmatic functionality, formal and semantic self-sufficiency, thematic certainty and completeness. The communicative potential of status texts is several times greater than a simple personal message. It is viewed as a small format text proclaiming the major opinion, the most important event, or some other important, interesting or amusing in the opinion of a webpage user. To attract attention to their webpage site, users resort to various communication techniques, which have been differentiated in the article. As a status text is intended to create a special impression on the webpage visitor it may be compared, in our opinion, with advertising slogans and image advertisements. The communicative-functional orientation of status texts allows to consider them as universal elements of Internet communication.
Naturalness Evaluation of Natural Language Generation in Task-oriented Dialogues using BERT

This paper presents an automatic method to evaluate the naturalness of natural language generation in dialogue systems.While this task was previously rendered through expensive and time-consuming human labor, we present this novel task of automatic naturalness evaluation of generated language.By fine-tuning the BERT model, our proposed naturalness evaluation method shows robust results and outperforms the baselines: support vector machines, bi-directional LSTMs, and BLEURT.In addition, the training speed and evaluation performance of naturalness model are improved by transfer learning from quality and informativeness linguistic knowledge.
The 7-Round Subspace Trail-Based Impossible Differential Distinguisher of Midori-64

This paper analyzes the subspace trail of Midori-64 and uses the propagation law and mutual relationship of the subspaces of Midori-64 to provide a 6-round Midori-64 subspace trail-based impossible differential key recovery attack. The data complexity of the attack is <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>54.6</mn> </mrow> </msup> </math> chosen plaintexts, and the computational complexity is <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>58.2</mn> </mrow> </msup> </math> lookup operations. Its overall complexity is less than that of the known 6-round truncated impossible differential distinguisher. This distinguisher is also applicable to Midori-128 with a secret <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <mi>S</mi> </math> -box. Additionally, utilizing the properties of subspaces, we prove that a subspace trail-based impossible differential distinguisher of Midori-64 contains at most 7 rounds. This is 1 more than the upper bound of Midori-64’s truncated impossible differential distinguisher which is 6. According to the Hamming weights of the starting and ending subspaces, we classify all 7-round Midori-64 subspace trail-based impossible differential distinguishers into two types and they need <math xmlns="http://www.w3.org/1998/Math/MathML" id="M4"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>59.6</mn> </mrow> </msup> </math> and <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5"> <msup> <mrow> <mn>2</mn> </mrow> <mrow> <mn>51.4</mn> </mrow> </msup> </math> chosen plaintexts, respectively.