Reviewerly/exHarmony huggingface dataset:
Mixed Reality-based Outdoor Training System to Improve Football Player Performance

With the development of ICT technology, various technologies that can improve players’ performance in the sports field are being developed. In particular, immersive technology can be implemented in virtual space for various situations that are difficult to implement without space-time constraints. In this paper, we propose MR-based outdoor training system to improve football player performance. This proposed system is developed via Unity3D and MRTK and designed suitable for Microsoft HoloLens 2. This system allows users to switch freely and facilitates iterative analysis and prediction. We expect that this system can improve the user’s performance to analyze the situation.
BHGAN: A Hierarchical Graph Network Based on Feature Enhancement

Recently, with the development of deep learning techniques, text classification methods have achieved remarkable results. However, the existing work usually models the entire text, less consideration is given to the hierarchical relationship between the texts, and the internal relationship between the preceding and following sentences is ignored. To address this issue, in this paper, we propose a hierarchical graph network model BHGAN based on BERT and utilizing graph attention network to model the hierarchical relationship of texts. When modeling, the semantic features are enhanced by the output of the intermediate layer of BERT, and the relationship between the whole sentence and the sub-sentence is used to construct a hierarchical graph network corresponding to each layer of BERT. The multi-level hierarchical relationship diagram we established not only considers the semantics of each layer, but also the hierarchical relationship of the text. The experimental results show that the BHGAN model exhibits competitive results on the dataset.
Investigating the Use of Mobile Learning in Saudi Higher Education: The Perspective of Undergraduate Students

People’s life has been significantly affected due to the COVID-19 epidemic. This includes society, business, health, economic, and education fields. The purpose of this research is to investigate the use of mobile learning (m-learning) based on perceptions of higher education students in Saudi Arabia. The study analyzed the views on m-learning technologies and the utilization patterns of handheld devices for teaching and learning. It also considered the influence of demographic factors namely, gender, age, subject specialization, and the average smartphone usage. The challenges and obstacles hindering access to e-learning content have also been investigated. The study adopts a quantitative research design. The research questionnaire was administrated randomly to a sample of students comprised of males and females and from different departments across a public university in Saudi Arabia. Overall, the findings show the significant impact of smart devices on the educational process, but there are still many barriers that prevent the successful application of such technologies. The analysis provided valuable insights to design, pilot, and deploy future large-scale m-learning projects in higher education institutions in Saudi Arabia and other Middle Eastern nations.
Cyber security-based Multikey Management System in Cloud Environment

The revolutionary expansion in processing and storing mechanisms through the internet has given rise to affordable and powerful computing features. These qualities have been enhanced as a result of this growth. Computing in the cloud is an emerging technology that provides users with the ability to access data storage facilities as well as application access facilities in an online setting. This approach presents an almost infinite number of chances and difficulties. In light of this, ensuring the safety of one’s data and preventing the accumulation of duplicate or otherwise identical information in the cloud are both highly critical concerns that must be handled. As a result, a method known as deduplication was created to cut down on the amount of data in the identical storage system. In this investigation, a unique approach for removing repetitive or duplicate data from cloud servers, which will also help reduce the amount of internet access and storage space needed, has been presented. The results of the experiments show that the suggested system not only offers a higher level of protection for the data that is stored in stored in the cloud but also addresses the primary issues of rent systems.
Lewis Carroll’s Almost Diagrammatic Logic Notation

There is growing literature on the employment of diagrams to ease logical reasoning. Less is said about the visual properties of symbolic notations. It is, for instance, no coincidence that most notations offered for implication are asymmetrical to reflect the asymmetry of the operator itself. Hence, the symbol is self-interpreting in that its appearance suggests a property of the object it stands for. In this paper, we discuss a compositional notation, invented by Lewis Carroll in 1884, which suggests relations between propositions. Carroll is known for designing both symbolic and diagrammatic notations for logic. Although his theory was rooted in the “old” logic, he championed a thorough use of notations in the Boolean style that was spreading in his time. In the notation we are considering here, Carroll represents simple propositions, and then their symbols are combined to form compound propositions. An interesting outcome of this design, based on the visualization of the composition of propositions, is that the layout exhibits relations between propositions. For instance, a proposition is shown to be subaltern to another if the symbol of the former is contained by the symbol of the latter. In this paper, we consider the guiding principles for the design of this notation and the extent to which it visually conveys relations between propositions.
Inference in Nineteenth-Century British Logic

I trace the development of implication as an inference operator using as the starting point the ideas primarily of R. Whately, W. Hamilton, and in added material, also J. S. Mill, before discussing the work of the transitional logicians, A. De Morgan and G. Boole on these topics. Although not appreciated until the first third of the twentieth century, Boole’s fundamental law of thought, x2 = x, initiated an analysis of how the algebra of logic differs from ordinary algebra, and subsequently, gave rise to a new inference rule, resolution. In an added section, I provide a roadmap of this development and then discuss the relevant views of four prominent but underappreciated nineteenth-century British logicians, W.E. Johnson, J.N. Keynes, E.E.C. Jones, and H. MacColl, as well as those of the more influential logicians, W.S. Jevons and J. Venn, closing with a section on “implication as inference” where I explore some key ideas of B. Russell and sketch the work of D. Hilbert, P. Hertz, and G. Gentzen who together are responsible for the development of the modern ideas leading to the mechanization of inference schemes.
What Does a Concept Entail?

Conceptual entailment is the process through which a conclusion is drawn from one or several concepts. In its simplest form, it takes the form of an inference that can be deduced from a set of characteristic features attached to the concept. This characteristic set therefore plays a role analogous to that of a conditional base. The framework of non-monotonic inference relations leads to the rigorous definition of some basic notions used in concept analysis and allows in this domain the establishment of some original and non-trivial results.
Is Logic Exceptional?

We examine in which sense logic can be considered as exceptional. We start by emphasizing the difference between Logic as reasoning and logic as the science of reasoning, an essential distinction to launch the discussion. We then investigate if reasoning itself can be seen as exceptional, in particular an exceptional feature of human beings, and next if the science of reasoning can be regarded as exceptional. This study is further extended on the one hand by discussing the relativity and universality of logic and on the other hand by stressing the dialectical interaction between logic and metalogic, the interdisciplinary and transdisciplinary character of logic.
A Contrastive Corpus Study on Lexical Features of the English Translation of the Report of the 20th and 19th CPC National Congress

As the channel spreads the Chinese voice and promotes Chinese culture, the status of political document translation is self-evident with the deepening of global communication. Taking the English translation of the reports of the 20th and the 19th CPC National Congress as examples, this paper makes a contrastive study of their lexical features in a corpus-based way. With the assistance of corpus analysis software such as AntConc, TagAnt and WordSmith4.0, the author investigates TTR (type-token ratio), lexical density, average sentence length, high-frequency words, and keywords between two reports. It is found that the report of the 20th CPC Nation Congress has more diversified and native expressions with fewer words used, which provides a guiding significance for the English translation of political documents.
Age group classification based on Bins of Gradients over Gradient Hessianspace facial images

Visitors to the museum may have varying levels of interest, language and comprehension depending on their age. Here, a common computer-aided addressing system cannot describe effectively without considering their nature. Hence the efficient assessment of whole facial skin details is an important role in facial age group classification. To address this issue, Bins of Gradients over Gradient Hessianspace (BOGGH) is proposed. Here we first compute gradient space for the detected face and then apply Hessian filter to obtain imprinted edge and curve details. Second, over the gradient Hessianspaced facial images, Bins of Gradients (BOG) technique is applied in multiple directions chosen. Finally, the age features of the facial images are then trained and classified using RBF-based SVM technique. The proposed BOGGH method achieves the classification rate of 99.39% for the FGNET database and 99.72% for the MORPH database which is superior than other existing methods.
Performability Evaluation and Sensitivity Analysis of a Video Streaming on Demand Architecture

In urban air mobility (UAM), video streaming platforms have gained significant attention from media companies due to their growing necessity for on-demand video streaming services-as-you-go in flights. Video streaming services can provide constant data transactions in a huge amount, especially in its operational digital twin (ODT). As a result, the ability to provide a satisfactory user experience through video streaming platforms is critical and complex. This requires continuously operating services while handling numerous user requests for near real-time video streaming. At the same time, high-quality video with high resolution and minimal interruptions is often expected. Therefore, the availability and performance (i.e., performability) of the Back-End video streaming infrastructure are crucial parameters for these platforms. However, evaluating novel video-on-demand architectures in real-world scenarios can be costly due to the numerous parameters involved. Analytical models, such as stochastic Petri nets (SPNs), can serve as an alternative in this complex scenario as they can be used to analyze systems during the design process. In this study, we developed a set of SPN models to assess the performance of a video-on-demand system. These models were designed to illustrate and to evaluate a video-on-demand architecture while considering performance. We had a base SPN model as well as three enhanced variants available. The extended models were generated using the Design of Experiments (DoE) technique and sensitivity analysis results. The DoE identified the factors with the greatest impacts on performance, and the most significant factor interactions. Redundancy strategies were applied to the extended models to increase the availability of the most important components. This redundancy increased the availability of “9 s” from three to five. It is worth noting that this study can help the designers of video streaming systems, to plan and to optimize their ideas based on the provided models.
Analysis of Kernel Matrices via the von Neumann Entropy and Its Relation to RVM Performances

Kernel methods have played a major role in the last two decades in the modeling and visualization of complex problems in data science. The choice of kernel function remains an open research area and the reasons why some kernels perform better than others are not yet understood. Moreover, the high computational costs of kernel-based methods make it extremely inefficient to use standard model selection methods, such as cross-validation, creating a need for careful kernel design and parameter choice. These reasons justify the prior analyses of kernel matrices, i.e., mathematical objects generated by the kernel functions. This paper explores these topics from an entropic standpoint for the case of kernelized relevance vector machines (RVMs), pinpointing desirable properties of kernel matrices that increase the likelihood of obtaining good model performances in terms of generalization power, as well as relate these properties to the model's fitting ability. We also derive a heuristic for achieving close-to-optimal modeling results while keeping the computational costs low, thus providing a recipe for efficient analysis when processing resources are limited.
Normalization in the simply typed -calculus

Abstract In this paper, in connection with the program of extending the Curry–Howard isomorphism to classical logic, we study the $\lambda \mu$ -calculus of Parigot emphasizing the difference between the original version of Parigot and the version of de Groote in terms of normalization properties. In order to talk about a satisfactory representation of the integers, besides the usual $\beta$ -, $\mu$ -, and $\mu '$ -reductions, we consider the $\lambda \mu$ -calculus augmented with the reduction rules $\rho$ , $\theta$ and $\varepsilon$ . We show that we need all of these rules for this purpose. Then we prove that, with the syntax of Parigot, the calculus enjoys the strong normalization property even when we add the rules $\rho$ , $\theta$ , and $\epsilon$ , while the $\lambda \mu$ -calculus presented with the more flexible de Groote-style syntax, in contrast, has only the weak normalization property. In particular, we present a normalization algorithm for the $\beta \mu \mu '\rho \theta \varepsilon$ -reduction in the de Groote-style calculus.
A New Approach of Evaluating the Security Against Differential and Linear Cryptanalysis and Its Applications to Serpent, NOEKEON and ASCON

Abstract In recent years, Mixed-Integer Linear Programming (MILP)-based automatic tools have played a significant role in providing security evaluations of symmetric-key primitives. Differential and linear cryptanalysis are the two most important cryptographic techniques. Although some methods have conducted a great effort in exploiting MILP-aided tools in searching for differential (linear) characteristics, traditional methods still suffer from primitives with strong diffusion layers and large sizes, such as NOEKEON. Typically, searching for differential (linear) characteristics of such primitives is difficult, and the corresponding MILP models are too heavy to be solved efficiently. To this end, we propose a simple yet efficient approach to employ MILP to evaluate the security against differential and linear cryptanalysis of such primitives. The core of our approach is to reduce the complex problem to a set of simpler subproblems and obtain the optimal solution of the complex problem by combining all the subproblems. A subproblem is equivalent to searching for all differential (linear) characteristics with a fixed number of active S-boxes in each round. Furthermore, we design an elaborate algorithm consisting of three MILP-aided methods to solve various subproblems and adopt some techniques to improve efficiency further. Applying our new algorithm to three SPN primitives Serpent, NOEKEON and ASCON, we obtain the tightest security bounds against differential and linear cryptanalysis for all three primitives so far and find improved differential and linear characteristics for Serpent and NOEKEON. For Serpent, we improve the upper bound of the maximum probability of 7-round differential characteristics from $2^{-71}$ to $2^{-76}$ and find for the first time 7-round differential characteristics. For NOEKEON, our results show that there is no 9-round (10-round) differential (linear) characteristic with a probability (correlation) higher than $2^{-128}$ ($2^{-64}$), whereas it needs 10 rounds (11 rounds) according to the previous results. In addition, we find an 8-round (9-round) differential (linear) characteristic with a probability (correlation) of $2^{-127}$ ($2^{-60}$). For ASCON permutation, we provide for the first time an upper bound of the maximum probability (correlation) of 5-round differential (linear) characteristics as $2^{-70}$ ($2^{-33}$).
Detecting Stepping-Stone Intrusion and Resisting Intruders’ Manipulation via Cross-Matching Network Traffic and Random Walk

Attackers can exploit compromised hosts to launch attacks over the Internet. This protects an intruder, placing them behind a long connection chain consisting of multiple compromised hosts. Such attacks are called stepping-stone intrusions. Many algorithms have been proposed to detect stepping-stone intrusions, but most detection algorithms are weak in resisting intruders’ session manipulation, such as chaff-perturbation. This paper proposes a novel detection algorithm: Packet Cross-Matching and RTT-based two-dimensional random walk. Theoretical proof shows network traffic cross matching can be effective in resisting attackers’ chaff attack. Our experimental results over the AWS cloud show that the proposed algorithm can resist attackers’ chaff attacks up to a chaff rate of 100%.
On the Implementation of a Blockchain-Assisted Academic Council Electronic Vote System

The digitisation of administrative tasks and processes is a reality nowadays, translating into added value such as agility in process management, or simplified access to stored data. The digitisation of processes of decision-making in collegiate bodies, such as Academic Councils, is not yet a common reality. Voting acts are still carried out in person, or at most in online meetings, without having a real confirmation of the vote of each element. This is particularly complex to achieve in remote meeting scenarios, where connection breaks or interruptions of audio or video streams may exist. A new digital platform was already previously proposed. It considered decision-making, by voting in Academic Councils, to be supported by a system that guarantees the integrity of the decisions taken, even when meeting online. Our previous work mainly considered the overall design. In this work, we bettered the design and specification of our previous proposal and describe the implemented prototype, and validate and discuss the obtained results.
Efficient Embedding of Strategic Attribute Grammars via Memoization

Strategic term re-writing and attribute grammars are two powerful programming techniques widely used in language engineering. The former relies on strategies to apply term re-write rules in defining large-scale language transformations, while the latter is suitable to express context-dependent language processing algorithms. These two techniques can be expressed and combined via a powerful navigation abstraction: generic zippers. This results in a concise zipper-based embedding offering the expressiveness of both techniques.
Towards a Reflection for Effect Handlers

A reflection is a relationship between compiling and decompiling functions. This concept has been studied as a means to ensure correctness of compilers, in particular, those for languages featuring control effects. We aim to develop a reflection for algebraic effects and handlers. As a first step towards this goal, we investigate what we obtain by following the existing recipe for control operators. We show that, if we use the simplest CPS translation as the compiling function, we can prove most but not all theorems required of a reflection. From this result, we identify two conditions of the CPS translation that would lead to a reflection for effect handlers.
Semantic Transformation Framework for Rewriting Rules

Semantics-preserving source-to-source program transformations, such as optimization and refactoring, are essential for software development. Such transformations are often defined by rewriting rules describing which part of a program must be replaced with which subprogram. The main obstacle to designing a transformation is to prove its semantics preservation. Rewriting-rule-based frameworks alleviate this difficulty by giving proof guidelines or automating the proofs. Unfortunately, each framework is applicable to a restricted set of transformations due to a fixed definition of semantics preservation. Cousot and Cousot’s semantic transformation framework resolves this problem by leaving a space for its users to define a proper semantics preservation property. However, the framework does not exploit the characteristic of rewriting rules and fails to ease the proofs. In this work, we define a semantic transformation framework tailored to rewriting rules by refining Cousot and Cousot’s framework. Our framework facilitates modular proofs by providing syntax-directed guidelines and theorems that simplify proofs. We show the versatility of our framework by proving the semantics preservation of six well-known transformations.
DISCURSIVE STRATEGIES OF IDEOLOGICAL REPRESENTATIONS IN POLITICAL SPEECHES: A CRITICAL DISCOURSE ANALYSIS OF SELECTED SPEECHES OF KWAME NKRUMAH

To win political power, political actors sometimes adopt linguistic and rhetorical strategies that enable them to communicate effectively with their audience. This makes the study of the language of politics an interesting academic exercise. This study, therefore, attempted a critical discourse analysis of selected speeches of Dr. Kwame Nkrumah to investigate the role of language in creating ideology and sustaining power as well as ideological discursive structures in political speeches. The study specifically investigated linguistic expressions which carry these ideological colourations in the speeches under review. The study employed the qualitative research approach and textual analysis as the design. The purposive sampling method was used to select five speeches of Dr. Kwame Nkrumah, and the analysis was done thematically. The study employed the theoretical frameworks of Fairclough’s CDA and Van Dijk’s socio-cognitive approach to analyse the speeches. The study revealed that the ideologies were carried out through these discursive structures: evidentiality, pronouns, agency, metaphor, intertextuality, rhetorical question, and strong modal of obligation. The study further revealed that the discursive structures produce and sustain power and unequal power relations between Nkrumah and his audience. The study afforded much evidence to conclude that politics is a game that can be successfully played through a skillful deployment of language. The study, therefore, concludes that the speeches that were analysed were used as a means of establishing, maintaining, and sustaining power and asymmetrical power relations.&lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0261/a.php" alt="Hit counter" /&gt;&lt;/p&gt;