Reviewerly/exHarmony huggingface dataset:
Digital crimes: concept, typology, signs

The article is devoted to the analysis of theoretical provisions on the concept of crimes committed using computer, digital and other technologies. The study is an analysis of scientific approaches of scientists, the provisions of international documents, legislation of the Russian Federation to the terms that denote the criminal use of digital technologies in the commission of crimes. In addition, the article contains approaches to the typology of the group of crimes under consideration. The author focuses on the lack of a single concept that reflects the essence of crimes committed using modern technologies in the analyzed legal acts and the theory of criminal law. The article as a result of the research contains an indication of the need to create and apply the generalizing concept of there is, since modern technologies are rapidly being incorporated into the mechanism of committing crimes. The author suggests the term «digital crimes» and designates its advantages. The article also contains signs of the specified group of crimes and the author’s typology of digital crimes.
A dynamic core evolutionary clustering algorithm based on saturated memory

Abstract Because the number of clustering cores needs to be set before implementing the K-means algorithm, this type of algorithm often fails in applications with increasing data and changing distribution characteristics. This paper proposes an evolutionary algorithm DCC, which can dynamically adjust the number of clustering cores with data change. DCC algorithm uses the Gaussian function as the activation function of each core. Each clustering core can adjust its center vector and coverage based on the response to the input data and its memory state to better fit the sample clusters in the space. The DCC algorithm model can evolve from 0. After each new sample is added, the winning dynamic core can be adjusted or split by competitive learning, so that the number of clustering cores of the algorithm always maintains a better adaptation relationship with the existing data. Furthermore, because its clustering core can split, it can subdivide the densely distributed data clusters. Finally, detailed experimental results show that the evolutionary clustering algorithm DCC based on the dynamic core method has excellent clustering performance and strong robustness.
Neural Arabic singular-to-plural conversion using a pretrained Character-BERT and a fused transformer

Abstract Morphological re-inflection generation is one of the most challenging tasks in the natural language processing (NLP) domain, especially with morphologically rich, low-resource languages like Arabic. In this research, we investigate the ability of transformer-based models in the singular-to-plural Arabic noun conversion task. We start with pretraining a Character-BERT model on a masked language modeling task using 1,134,950 Arabic words and then adopting the fusion technique to transfer the knowledge gained by the pretrained model to a full encoder–decoder transformer model, in one of the proposed settings. The second proposed setting directly fuses the output Character-BERT embeddings into the decoder. We then analyze and compare the performance of the two architectures and provide an interpretability section in which we track the features of attention with respect to the model. We perform the interpretation on both the macro and micro levels, providing some individual examples. Moreover, we provide a thorough error analysis showing the strengths and weaknesses of the proposed framework. To the best of our knowledge, this is the first effort in the Arabic NLP domain that adopts the development of an end-to-end fused-transformer deep learning model to address the problem of singular-to-plural conversion.
A Problems and Tasks of the Regulations on Opening 'Subjects' in Schools through Comparison of Laws and National Curriculum on 'Subjects' Regulations in Korea and Japan

[Purpose] The purpose of this study is to present problems and tasks for our subject regulations by comparing the laws and regulations of the national curriculum for Korean and Japanese subjects.&#x0D; [Methods] In this study, literature analysis, comparison of subject- related matters, and legal interpretation methods were used.&#x0D; [Results] As a result of this study, the legal systems of Korea and Japan and the fact that subjects could be opened in the national curriculum were similar. Japan had limitations in granting authority to high schools, but there were differences in granting authority to open subjects as well as subjects. In addition, Japan suggests that the name, goal, content, and number of units of the subject should be determined based on the school-level educational goals in the opening of the subject, and the subject should be determined based on the subject goals. However, in the case of Korea, the national curriculum only grants the right to open subjects without such a basis, and terms such as subjects, subject matters are mixed, so discussions and tasks were requested. Such tasks were sought through discussions on the classification of concepts of subjects and subject matters, violation of the legal system of the right to open subjects, the possibility of time allocation of subjects to the time dividend of the national curriculum, and the possibility of additional achievement standards.&#x0D; [Conclusion] As a result of the discussion, in using terms of subjects, subject matters, it was necessary to prepare subject names, goals, contents, and hours based on educational goals by elementary and secondary school. In addition, it was necessary to prepare the subject name, goal, content, and number of hours based on the goal of the subjects used as a higher concept. Otherwise, separate guidelines should be prepared to present directions for the opening of subject matters in the educational field. This is because it is closely related to establishing the scope and sequence of the curriculum.
Multi-key homomorphic encryption with tightened RGSW ciphertexts without relinearization for ciphertexts product

Most previous RLWE-based multi-key homomorphic encryptions (MKHEs) need to perform complex relinearization operations on ciphertext products to complete the evaluation of circuits of bounded polynomial depth. In this process, many intermediate ciphertexts or keys are needed for computing, resulting in inefficient computing and redundant storage. We propose a more efficient RLWE-based MKHE without relinearization operations to squeeze the storage space provided for homomorphic computation. Firstly, a controllable factor is introduced into the party's ciphertexts, delineating the ciphertext as a component-like factor in preparation for concatenate operations. Secondly, we construct a tightened RGSW ciphertext extension algorithm that can be directly applied to the party's original ciphertext. The extended ciphertext no longer needs to be converted, so any conversion keys are no longer required. Again, by combining the concatenate and bit decomposition techniques, we construct new matching homomorphic computation algorithms, which ensure that the ciphertext product or sum is consistent in morphology with the extended ciphertext. The homomorphic multiplication algorithm allows the resultant ciphertext to directly participate in the next round of homomorphic operations without relinearization. Finally, we propose a specific RLWE-based MKHE scheme and provide the decryption process. Our analysis shows that our scheme guarantees IND-CPA security and performs efficient homomorphic computations correctly without relinearization operations.
Elite-centered artificial bee colony algorithm with extended solution boundary

To improve the performance of Artificial Bee Colony (ABC) algorithm, we propose a novel approach (named ESOABC-EC&ACS). First, the existence of solutions outside the constrained region (ESO) is designed to explore the possibility of the search helped by these solutions, which facilitates exploring the boundary of the constrained region and obtaining optimal solutions faster. Then, an elite-centered search equation is proposed to balance exploration and exploitation. Finally, adaptive bee colony scaling is constructed to help convergence. Our approach is the combination of these three techniques. The experimental results demonstrate that ESOABC-EC&ACS outperforms other ABC variants and some non-ABC meta-heuristic algorithms on most of the test functions in terms of solution quality. And the proposed heuristic factor for the dynamic weapon target assignment problem can improve the optimization performance. The ESO is the first universal strategy proposed for the survival of solutions outside the constraint region (out-of-bounds) generated when solving various problems directly, which causes extended solution boundary and affects the exploration of the constrained region boundary.
Structuring Spectra in Electroacoustic Music

This article describes the ways in which the spectra of electroacoustic music compositions can be structured coherently. It begins by describing the straightjacket that composers and listeners are constrained by when using the concept of ‘source bonding’ and how this needs to be discarded for effective listening. It then describes the concept of spectral merging and how ideas of musical timbre are formed, and finally discusses the many ways that spectra can be structured with both harmonic and inharmonic components. Examples are given from the author’s own music and other well-known works in the literature of electroacoustic music.
Efficient human 3D localization and free space segmentation for human-aware mobile robots in warehouse facilities

Real-time prediction of human location combined with the capability to perceive obstacles is crucial for socially-aware navigation in robotics. Our work focuses on localizing humans in the world and predicting the free space around them by incorporating other static and dynamic obstacles. We propose a multi-task learning strategy to handle both tasks, achieving this goal with minimal computational demands. We use a dataset captured in a typical warehouse environment by mounting a perception module consisting of a Jetson Xavier AGX and an Intel L515 LiDAR camera on a MiR100 mobile robot. Our method, which is built upon prior works in the field of human detection and localization demonstrates improved results in difficult cases that are not tackled in other works, such as human instances at a close distance or at the limits of the field of view of the capturing sensor. We further extend this work by using a lightweight network structure and integrating a free space segmentation branch that can independently segment the floor space without any prior maps or 3D data, relying instead on the characteristics of the floor. In conclusion, our method presents a lightweight and efficient solution for predicting human 3D location and segmenting the floor space for low-energy consumption platforms, tested in an industrial environment.
V-shaped neural network structure based on multi-scale features for image denoising

Due to the good performance of deep learning, more and more image denoising methods incorporating deep learning are implemented, including fixed-scale-based methods and multi-scale-based methods. It is easy for fixed-scale-based neural networks to achieve a better denoising performance when their depth is increased, whereas feature extraction of multiple scales from images can be obtained using multi-scale-based neural networks. In this work, a multi-scale image denoising method has been proposed which is mainly based on fixed-scale but combines the method of obtaining feature information from shallow image sampling. We propose a diamond-shaped module and a V-shaped subnetwork for extracting the features of images obtained from shallow sampling and improve the up-sampling and down-sampling units to obtain a better sampling effect. Densely connecting images of same size in MSDN can solve the problem of gradient vanishing since increasing the depth of the network and shallow image sampling prevent the loss of image details due to excessive sampling. Experiments show that our method can efficiently retain the image details during image denoising, and this method is especially helpful for preserving minute image details as compared to the other state-of-the-art denoising algorithms.
Insights from lexical and syntactic analyses of a French for academic purposes assessment

With the objective of improving writing assessment of language instruction, we examine the lexical and syntactic features in two corpora of high and low scoring French texts of the Test du Certificat de Compétence en Langue Seconde (Second Language Certification Test; TCCLS) at the University of Ottawa (uOttawa). We first situate the test in its local context, demonstrating how our research objectives are born from specific needs to improve student outcomes. We then describe our creation of two corpora of high and low performing test takers, followed by lexical bundle (LB) analyses (Phase 1) and further linguistic complexity analyses with a French-language tool (Phase 2). Results indicate that high level writers used more LBs and borrowed more text from the prompt than low level writers. In addition, specific elements of linguistic complexity were identified, suggesting high level writers produced texts that were lexically richer and more syntactically advanced. We discuss the importance of these findings in improving our writing instruction, as well as the challenges of adapting tools and approaches traditionally associated with English to French.
Application of the Hough Transform to Dispersion Control of Overlapping Particles and Their Agglomerates

The dispersion control of micro- and nanoparticles by their images is of great importance for ensuring the specified properties of the particles themselves and materials based on them. The aim of this article was to consider the possibilities of using the Hough transform for dispersion control of overlapping particles and their agglomerates. Analysis of the application of the Hough transform for overlapping particles and their agglomerates showed the following. The particularities of the conventional implementation lead to the preferred registration of large particles, the shift of the centers of overlapping particles, and the distortion of the size values. To use the Hough transform correctly, fine-tuning of all its parameters is required. To automate this process, the dependences of the number and size of particles recorded in the image on the parameters of the Hough transform was investigated. The studies were carried out on test images with a known number and size of particles. The results showed that when the threshold parameters of the Hough transform change, the number of detected particles stabilizes near their optimal values. When the size range of particles detected by the Hough transform changes, the histogram of the particle size distribution changes. In this case, the optimal width of the range is determined by the most stable extremes of the histogram. The maximum center-to-center distance is set at least half of the optimal range. The configuration algorithm is described and implemented. It implies repeatedly running the Hough transform with different combinations of parameters. The algorithm includes stages of coarse and fine-tuning, which allows to getting closer to the optimal parameters. The efficiency of the algorithm has been confirmed on test and real images. Tests have shown that the errors in determining the size and number of particles of the multi-pass Hough transform are on the same level or exceed these indicators for analog methods.
MLPs Are All You Need for Human Activity Recognition

Convolution, recurrent, and attention-based deep learning techniques have produced the most recent state-of-the-art results in multiple sensor-based human activity recognition (HAR) datasets. However, these techniques have high computing costs, restricting their use in low-powered devices. Different methods have been employed to increase the efficiency of these techniques; however, this often results in worse performance. Recently, pure multi-layer perceptron (MLP) architectures have demonstrated competitive performance in vision-based tasks with lower computation costs than other deep-learning techniques. The MLP-Mixer is a pioneering pureMLP architecture that produces competitive results with state-of-the-art models in computer vision tasks. This paper shows the viability of the MLP-Mixer in sensor-based HAR. Furthermore, experiments are performed to gain insight into the Mixer modules essential for HAR, and a visual analysis of the Mixer’s weights is provided, validating the Mixer’s learning capabilities. As a result, the Mixer achieves F1 scores of 97%, 84.2%, 91.2%, and 90% on the PAMAP2, Daphnet Gait, Opportunity Gestures, and Opportunity Locomotion datasets, respectively, outperforming state-of-the-art models in all datasets except Opportunity Gestures.
What Does It Meme? English–Spanish Codeswitching and Enregisterment in Virtual Social Space

This project investigates English–Spanish codeswitching in internet memes posted to the Facebook page, We are mitú (mitú), and analyzes how lexical insertions and quotatives contribute to the enregisterment of linguistic patterns and the construction of collective identity among U.S. Latinx millennials in virtual social spaces. Data include instances of lexical insertion (n = 280) and quotative mixed codes (n = 114) drawn from a collected corpus of 765 image–text memes. The most frequent lexical insertions included food items (e.g., elote and pozole), kinship terms (e.g., abuelita and tía), and culturally specific artifacts or practices (e.g., quinceañera and lotería), which reflect biculturalism and rely on a shared set of references for the construction of a group identity. Additionally, the quotatives in the data construct Spanish-speaking characterological figures that enregister a particular brand of U.S. Latinx millennial identity that includes being bilingual, having Spanish-speaking parents, and having strong ties to Latinx culture. Overall, this work highlights not only internet memes as a vehicle for enregisterment, but also, and more importantly, how the language resources employed within them work to enregister linguistic and cultural norms of U.S. Latinx millennials, and thereby, play a role in identity construction in virtual social spaces.
Modifying the AES Algorithm by Improving the Add Round Key Stage

This study offers a new adjustment to the Advanced Encryption Standard (AES) in order to assure a high degree of security. This is achieved by replacing the binary (XOR) operation with a new (Xo) operation in each add-round-key stage. The Xo operation generated an extra six randomly selected control keys determined by six state tables (2, 4, 6, 8, 10, and 12) produced from the addition operation in the Galois Field GF (2^2 ,2^4 ,2^6 , 2^8, 2^10 and 2^12 ) in order to boost the algorithm's unpredictability. In the suggested method, an adversary requires at least probabilities of keys to break the message; hence, it improves the difficulty of the original AES against brute force attacks. also enhances the performance of additional security metrics, such as NIST tests, compared to the original AES. Consequently, this replacement, including the use of six keys in both the encryption and decryption processes, offers a new level of security and a higher degree of resistance to data breaches. The novelty of the proposed (Xo) technique lies in the construction of GF tables ( 2^6 , 2^10 and 2^12) to be used in the encryption and decryption process for the first time, as well as the approach utilized to create the code for it.
Velocity measurement of moving target based on rotating mirror high speed camera

A rotating mirror high-speed imaging system can capture and track moving targets, obtaining high-resolution images of targets and it is suitable for capturing high-speed moving targets. Therefore, we propose a target velocity measurement method based on a rotating mirror high-speed camera. Since this system is based on monocular camera capture, traditional binocular vision-based visual velocity measurement methods are no longer applicable. We reconstruct the homography matrix of the plane where the target is located, calculate the virtual difference map of the target’s feature points, and reconstruct the three-dimensional (3D) coordinates of the feature points on the moving target. Then, based on calibration data, the actual 3D coordinates of the target are calculated, and the target’s motion speed is calculated using the frame rate of the camera. This method achieves 3D reconstruction of feature points of moving targets solely based on a monocular perspective and is highly suitable for a rotating camera model, allowing for continuous measurement of the motion speed of the target and observation of speed variations, expanding the range of velocity observation for high-speed moving targets. The experiment shows that this method has the advantages of low requirements for the field, simple construction of experimental equipment, and high robustness. It can still measure the speed of the target with high accuracy under relatively simple conditions. The average relative error of displacement measurement experiment using this method is 2.03%, which shows the feasibility and accuracy of this method. We believe it has significant application value for measuring the speed of high-speed moving targets.
Chinese CSUQ: Cross-Cultural Adaptation and Evaluation of Measurement Properties

AbstractThe Computer System Usability Questionnaire is one of the most popular standardized usability questionnaires used to assess the perceived usability of computer software, and it has been rigorously translated into multiple languages. This article aims to complete the cross-cultural adaptation of CSUQ in a Chinese environment and examine the psychometric characteristics. We used the forward–backward translation method to complete the initial translation, and designed the psychometric experiment according to the measurement properties required by the consensus-based standards for the selection of health measurement instruments (COSMIN). The COSMIN risk of bias checklist and updated criteria for good measurement properties were used to examine the Chinese CSUQ. The results demonstrated good performance of the Chinese CSUQ in content validity, internal structure and the remaining measurement properties. The results of the factor analysis revealed a three-factor structure, as well as any discrepancy between the Chinese CSUQ and its original version. Therefore, the Chinese CSUQ can be used confidently by Chinese usability practitioners and also serve as an effective alternative to other standardized usability scales. Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Philosophy and Social Science Foundation of Hunan Province [21YBA015].Notes on contributorsYuhui WangYuhui Wang is a researcher of the Industrial Design Department, Central South University. He is focused on usability theory, user experience and product design.Yahan XieYahan Xie is a Ph.D student of Academy of Art and Design, Tsinghua University. Her current research include usability assessment, cross-culture study and cognitive behavior.Yu QiaoYu Qiao is an associate professor of the industrial design department, Central South University. Her research interest is virtual reality and user experience.Zhaohui XiaZhaohui Xia is an assistant professor, is currently working at the National CAD Support Software Engineering Research Center, HUST. His research covers software engineering, mechanical design and computer aided design.Yanying ChenYanying Chen is an associate professor of the industrial design department, Central South University. Her research covers design management, user experience, art philosophy.