Reviewerly/exHarmony huggingface dataset:
Frequency and Spatial Domain-Based Approaches for Recognition of Indian Sign Language Gestures

Authors:
raw_author_name: B V Poornima
raw_author_name: S Srinath

Abstract: Objectives: The objective of this paper is to introduce and demonstrate an innovative approach for the recognition of Indian sign language gestures, with a focus on bridging communication gap between the deaf and hearing communities. The goal is to contribute to the development of effective tools and technologies that facilitate seamless communication between individuals using sign language and the people with no knowledge about sign language. Methods: The methodology consists of three key steps. First, data pre-processing involves resizing and contours extraction. Next, feature extraction employs Fourier descriptors for frequency domain analysis and gray-level-co-occurrence matrix for spatial domain analysis. Finally, various machine learning models including SVM, Random Forest, Logistic Regression, K-Nearest Neighbor and Naive Bayes are trained on a standard dataset. Findings: In our controlled experimental setup, we applied a diverse set of machine learning classifiers to evaluate the proposed approach for gesture recognition. Among the classifiers tested, K-Nearest Neighbors demonstrated the highest accuracy, achieving 99.82%. To validate the robustness of our approach, we employed k-fold cross-validation with 5 folds. Novelty: This study presents an innovative method for sign language recognition by employing a dual-domain fusion strategy that prominently emphasizes the frequency domain. Through the integration of Fourier descriptors, the research conducts a detailed frequency domain analysis to characterize the contour shapes of sign language gestures. The synergy with gray-level co-occurrence matrix texture features in the spatial domain analysis, contributes to the creation of a comprehensive feature vector. The proposed approach ensures a thorough exploration of gesture features, there by advancing the precision and efficacy of sign language recognition. Keywords: Indian Sign Language (ISL), Sign Language Recognition (SLR), Frequency domain, Spatial domain, Fourier descriptors, Gray level co­occurrence matrix (GLCM), K­ Fold
A Crypto Yield Model for Staking Return

Authors:
raw_author_name: Julien Riposo
raw_affiliation_string: Index Research & Design, EMEA, London Stock Exchange Group, London EC4M 7LS, UK

Abstract: We introduce a model that derives a metric to answer the question: what is the expected gain of a staker? We calculate the rewards as the staking return in a Proof-of-Stake (PoS) consensus context. For each period of block validation and by a forward approach, we prove that the interest is given by the ratio of the average staking gain to the total staked coins. Some additional PoS features are considered in the model, such as slash rate and Maximal Extractable Value (MEV), which marks the originality of this approach. In particular, we prove that slashing diminishes the rewards, reflecting the fact that the blockchain can consider stakers to potentially validate incorrectly. Regarding MEV, the approach we have sheds light on the relation between transaction fees and the average staking gain. We illustrate the developed model with Ethereum 2.0 and apply a similar process in a Proof-of-Work consensus context.
Coherent control of two Jaynes–Cummings cavities

Authors:
raw_author_name: L. O. Castaños-Cervantes
raw_affiliation_string: Tecnologico de Monterrey, School of Engineering and Sciences, 14380, Mexico City, Mexico
raw_author_name: Lorenzo M. Procopio
raw_affiliation_string: Weizmann Institute of Science, Rehovot, 7610001, Israel
raw_author_name: Marco Enríquez
raw_affiliation_string: Tecnologico de Monterrey, School of Engineering and Sciences, 01389, Santa Fe, Mexico

Abstract: We uncover new features on the study of a two-level atom interacting with one of two cavities in a coherent superposition. The James-Cummings model is used to describe the atom-field interaction and to study the effects of quantum indefiniteness on such an interaction. We show that coherent control of the two cavities in an undefined manner allows novel possibilities to manipulate the atomic dynamics on demand which are not achievable in the conventional way. In addition, it is shown that the coherent control of the atom creates highly entangled states of the cavity fields taking a Bell-like or Schrödinger-cat-like state form. Our results are a step forward to understand and harness quantum systems in a coherent control, and open a new research avenue in the study of atom-field interaction exploiting quantum indefiniteness.
Rancang Bangun Aplikasi Pengolahan Data Barang Inventaris Berbasis Mobile di Bidang Pemuda dan Olahraga

Authors:
raw_author_name: Muhamad Alda

Abstract: Inventory processing is an item data management activity carried out through a shopping budget or donations. This application is designed to provide easy access and speed in recording, managing and monitoring inventory in real-time. The aim of this research is to produce an Inventory Application at the Sergai Youth and Sports Office which can be used to process inventory data to make it more effective and accurate. This research uses data collection methods, namely interviews and literature studies, and for application development methods using the waterfall method. The results of this research obtained a system that is useful for processing inventory item data that will be used at the Youth and Sports Sector Office of DISPORAPARBUD SERGAI.
Exploring students’ immersive VR experiences as resources for collaborative meaning making and learning

Authors:
raw_author_name: Kenneth Silseth
raw_affiliation_string: Department of Education, University of Oslo, Oslo, Norway
raw_author_name: Rolf Steier
raw_affiliation_string: Department of Primary and Secondary Teacher Education, Oslo Metropolitan University, Oslo, Norway
raw_author_name: Hans Christian Arnseth
raw_affiliation_string: Department of Education, University of Oslo, Oslo, Norway

Abstract: Abstract By adopting a situated and interactional approach, we explore students’ immersive VR experiences as resources for collaborative meaning making and learning. We draw on data from a project in which teachers and researchers co-developed a learning design for upper secondary students involving immersive VR technology. In this learning design, students viewed a cinematic VR film where they encountered different people telling personal stories about exclusion and discrimination, followed by reflective group dialogues with their teacher about their experiences in this environment. Through a detailed interaction analysis of these dialogues, we identify four dimensions that characterize students’ meaning making: (1) the feeling of taking part in conversations, (2) attending to bodily expressions of others, (3) students’ own bodily responses, (4) teacher guidance. We discuss how the findings from our analysis contribute to the field of CSCL, and which also have implications for instructional work that includes the use of immersive VR environments.
Beyond images: an integrative multi-modal approach to chest x-ray report generation

Authors:
raw_author_name: Serge Sharoff
raw_affiliation_string: School of Languages, University of Leeds, United Kingdom
raw_author_name: Nishant Ravikumar
raw_affiliation_string: Center for Computational Imaging & Simulation Technologies in Biomedicine, School of Computing, University of Leeds, United Kingdom
raw_author_name: Alejandro F. Frangi
raw_affiliation_string: Alan Turing Institute, United Kingdom; Medical Imaging Research Centre, KU Leuven, Belgium

Abstract: Image-to-text radiology report generation aims to automatically produce radiology reports that describe the findings in medical images. Most existing methods focus solely on the image data, disregarding the other patient information accessible to radiologists. In this paper, we present a novel multi-modal deep neural network framework for generating chest x-rays reports by integrating structured patient data, such as vital signs and symptoms, alongside unstructured clinical notes. We introduce a conditioned cross-multi-head attention module to fuse these heterogeneous data modalities, bridging the semantic gap between visual and textual data. Experiments demonstrate substantial improvements from using additional modalities compared to relying on images alone. Notably, our model achieves the highest reported performance on the ROUGE-L metric compared to relevant state-of-the-art models in the literature. Furthermore, we employed both human evaluation and clinical semantic similarity measurement alongside word-overlap metrics to improve the depth of quantitative analysis. A human evaluation, conducted by a board-certified radiologist, confirms the model’s accuracy in identifying high-level findings, however, it also highlights that more improvement is needed to capture nuanced details and clinical context.
Dual-Mode Encryption for UC-Secure String OT from Learning with Errors

Authors:
raw_author_name: Momeng Liu
raw_affiliation_string: Henan Key Laboratory of Network Cryptography Technology, Zhengzhou, China; Shaanxi Key Laboratory of Clothing Intelligence, School of Computer Science, Xi’an Polytechnic University, Xi’an, China
raw_author_name: Yupu Hu
raw_affiliation_string: State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an, China
raw_author_name: Huiwen Jia
raw_affiliation_string: Key Laboratory of Information Security, School of Mathematics and Information Science, Guangzhou University, Guangzhou, China
raw_author_name: Wen Gao
raw_affiliation_string: School of Cyberspace Security, Xi’an University of Posts and Telecommunications, Xi’an, China
raw_author_name: Baocang Wang
raw_affiliation_string: State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an, China

Abstract: Universal composability (UC) is a primary security flavor for designing oblivious transfer (OT) due to its advantage of arbitrary composition. However, the study of UC-secure OT over lattices is still far behind compared with constructions over prequantum assumptions. Relying on the learning with errors (LWE) assumption, Quach proposes a dual-mode encryption scheme (SCN’20) for deriving a two-round OT whose security is provably UC-secure in the common reference string (CRS) model. Due to its use of a randomized rounding function proposed by Benhamouda et al. (PKC’18), this OT can only be limited to transmitting single-bit messages. Therefore, conducting trivial repetitions of Quach’s OT when transmitting multibit strings would be very costly. In this work, we put forward a modified dual-mode encryption cryptosystem under the decisional LWE assumption, from which we can derive a UC-secure string OT with both full-fledged dual-mode security and better efficiency on transmitting strings. The key technique we adopt is a key reconciliation scheme proposed by Jiang et al. (PKC’20), which is utilized to extend the single-bit symmetric encryption key (produced by the aforementioned rounding function) to a multibit case. Through a comprehensive performance analysis, we demonstrate that our proposal can indeed strike a balance between security and efficiency.
Effects of detuning on entropic uncertainty bound and quantum correlations in dissipative environments

Authors:
raw_author_name: Maryam Hadipour
raw_author_name: Soroush Haseli

Abstract: Abstract One of the fundamental arguments in quantum information theory is the uncertainty principle. According to this principle, two incompatible observables cannot be measured with high precision at the same time. In this work, we will use the entropic uncertainty relation in the presence of quantum memory. Considering a dissipative environment, the effects of the detuning between the transition frequency of a quantum memory and the center frequency of a cavity on entropic uncertainty bound and the quantum correlation between quantum memory and measured particle will be studied. It is shown that by increasing the detuning, quantum correlation is maintained. As a result, due to the inverse relationship between the uncertainty bound and quantum correlations, the measurement results are guessed more accurately.
Campus Security

Authors:
raw_author_name: Eric Lyerly

Abstract: An overview of the key topics faced by disability services providers with citations to noteworthy cases, statutes, regulations, and additional sources.
Quantum circuit distillation and compression

Authors:
raw_author_name: Shunsuke Daimon
raw_affiliation_string: Quantum Materials and Applications Research Center, National Institutes for Quantum Science and Technology, 2-12-1 Ookayama, Meguro-ku, Tokyo, 152-8550, JAPAN
raw_author_name: Takahiro Sagawa
raw_affiliation_string: Department of Applied Physics, The University of Tokyo, Bunkyo-ku, Tokyo, JAPAN
raw_author_name: Naoki Yamamoto
raw_affiliation_string: Department of Applied Physics and Physico-Informatics, Keio University Faculty of Science and Technology Graduate School of Science and Technology, Yokohama, Kanagawa, JAPAN
raw_author_name: Eiji Saitoh
raw_affiliation_string: Department of Applied Physics, The University of Tokyo, Bunkyo-ku, Tokyo, JAPAN

Abstract: Abstract Quantum coherence in a qubit is vulnerable to environmental noise. When long quantum calculation is run on a quantum processor without error correction, the noise causes fatal errors and messes up the calculation. Here, we propose quantum-circuit distillation to generate quantum circuits that are short but have enough functions to produce an output similar to that of the original circuits. The distilled circuits are less sensitive to the noise and can complete calculation before the quantum coherence is broken. We created a quantum-circuit distillator by building a reinforcement learning model, and applied it to the inverse quantum Fourier transform (IQFT) and Shor’s quantum prime factorization. The obtained distilled circuit allows correct calculation on IBM-Quantum processors. By working with the distillator, we also found a general rule to generate quantum circuits approximating the general $n$-qubit IQFTs. The quantum-circuit distillator offers a new approach to improve performance of noisy quantum processors.
Dual interactive Wasserstein generative adversarial networks optimized with hybrid Archimedes optimization and chimp optimization algorithm‐based channel estimation in OFDM

Authors:
raw_author_name: S. K. Mydhili
raw_affiliation_string: Department of Electronics and Communication Engineering KGiSL Institute of Technology Coimbatore India

Abstract: Summary Dual interactive Wasserstein generative adversarial networks optimized with hybrid Archimedes optimization and chimp optimization algorithm‐based channel estimation in OFDM (DiWGAN‐Hyb AOA‐COA‐MIMO‐OFDM) is proposed in this manuscript. In OFDM, there is a non‐stationary channel physical appearance during channel estimation (CE). Therefore in this work, Hyb AOA‐COA is employed to enhance the DiWGAN weight parameters. The proposed DiWGAN‐Hyb AOA‐COA‐MIMO‐OFDM technique is executed in network simulator (NS2) tool. The proposed technique attains lower computational cost 99.67%, 92.34%, and 97.45%; lesser bit error rate 98.33%, 83.12%, and 88.96%; and lesser mean square error 93.15%, 79.90%, and 92.88% compared with existing methods, like MIMO‐OFDM system using deep neural network and MN‐based improved AMO model (DNN‐IAMO‐MIMO‐OFDM), MIMO‐OFDM systems using the deep learning and optimization (RBFNN‐PSO‐MIMO‐OFDM), and MIMO‐OFDM systems using hybrid neural network (HNN‐CSI‐MIMO‐OFDM) respectively.
Federated two-stage decoupling with adaptive personalization layers

Authors:
raw_author_name: Hangyu Zhu
raw_affiliation_string: School of Artificial Intelligence and Computer Science, Jiangnan University, 1800 Lihu Road, Wuxi, 214126, Jiangsu, China
raw_author_name: Yuxiang Fan
raw_affiliation_string: School of Artificial Intelligence and Computer Science, Jiangnan University, 1800 Lihu Road, Wuxi, 214126, Jiangsu, China
raw_author_name: Zhenping Xie
raw_affiliation_string: School of Artificial Intelligence and Computer Science, Jiangnan University, 1800 Lihu Road, Wuxi, 214126, Jiangsu, China

Abstract: Abstract Federated learning has gained significant attention due to its groundbreaking ability to enable distributed learning while maintaining privacy constraints. However, as a consequence of data heterogeneity among decentralized devices, it inherently experiences significant learning degradation and slow convergence speed. Therefore, it is natural to employ the concept of clustering homogeneous clients into the same group, allowing only the model weights within each group to be aggregated. While most existing clustered federated learning methods employ either model gradients or inference outputs as metrics for client partitioning to group similar devices together, heterogeneity may still exist within each cluster. Moreover, there is a scarcity of research exploring the underlying reasons for determining the appropriate timing for clustering, resulting in the common practice of assigning each client to its own individual cluster, particularly in the context of highly non-independent and identically distributed (Non-IID) data. In this paper, we introduce a two-stage decoupling federated learning algorithm with adaptive personalization layers named FedTSDP, where client clustering is performed twice according to inference outputs and model weights, respectively. Hopkins amended sampling is adopted to determine the appropriate timing for clustering and the sampling weight of public unlabeled data. In addition, a simple yet effective approach is developed to adaptively adjust the personalization layers based on varying degrees of data skew. Experimental results show that our proposed method has reliable performance on both IID and non-IID scenarios.
Methodological approaches as a scientific basis for creating a pedagogical concept of distance learning organization in higher education institutions

Authors:
raw_author_name: Myroslava Fabian
raw_affiliation_string: Department of English Philology, Uzhhorod National University, Ukraine
raw_author_name: Halyna Bilanych
raw_affiliation_string: Department of Socio-Cultural Activities, Municipal establishment of higher education "Uzhhorod Academy of Culture and Arts " by Transcarpathian regional council, Ukraine

Abstract: The article examines e-learning as a special form of education and a pedagogical system based on the use of digital technologies. The content of the structural components of e-learning at universities is a pedagogical system that includes goals, means of communication, content of educational information, and subjects of the educational process. with guaranteed achievement of results as a system-forming factor. The following features of the means of communication between the subjects of the educational process are taken into account: students, teachers, tutors, specialist experts, resource developers (designers of pedagogical situations) and their functions. Scientific, methodological and technological support for achieving the desired result of e-learning at universities has been built, taking into account the individual needs of students, expanding the functions of teachers and implementing educational information through digitalization. A diagnostic toolkit has been developed for conducting a predictive pedagogical examination to develop, clarify and adjust students’ individual educational trajectories, taking into account expert opinions.
The paradigm of pedagogical innovation as a factor in the development of high-quality education

Authors:
raw_author_name: Aryna Kharkivska
raw_affiliation_string: Associate Professor of the department of theory and methods of preschool education, Municipal Establishment «Kharkiv Humanitarian-Pedagogical Academy» of the Kharkiv Regional Council, Kharkiv, Ukraine
raw_author_name: Nataliia Khmil
raw_affiliation_string: Professor at the Department of Informatics, Municipal Establishment “Kharkiv Humanitarian-Pedagogical Academy“ оf  Kharkiv Regional Council, Kharkiv, Ukraine
raw_author_name: Anton Brilliantov
raw_affiliation_string: Postgraduate student of the Department of Pedagogy, Psychology, Primary Education and Educational Management, Municipal Establishment “Kharkiv Humanitarian-Pedagogical Academy “of Kharkiv Regional Council, Kharkiv, Ukraine

Abstract: The article examined the logistics of pedagogical innovations, representing a mechanism for managing an educational holding that is relevant in the conditions of a postindustrial society in the totality of the conceptual provisions and empirical data that substantiate it. A theoretical justification for the cluster approach in education is given. The concepts of “educational clusters” and levels of clustering have been clarified and are meaningfully determined by educational competencies, educational programs, educational organization and territorial educational clusters. Pedagogical innovations have been substantiated as an essential characteristic of educational clusters, and their typology has been developed based on the cluster approach in education.
Art education as a means of forming cultural identity and civic consciousness

Authors:
raw_author_name: Iryna Zinkiv
raw_affiliation_string: Music Theory Academic Department, Faculty of Musicology, Composition, Vocals and Conducting, National Academy of Music named after Mykola Lysenko, Lviv, Ukraine
raw_author_name: Iryna Konovalova
raw_affiliation_string: Theory and History of Music Department, Department of Music Art, Kharkiv State Academy of Culture, Kharkiv, Ukraine

Abstract: The purpose of the article is to study art education as a means of forming cultural identity and civic consciousness. To achieve this goal, theoretical methods of cognition were used, in particular, the most important methods of analysis, synthesis, and content analysis. The results show that modern technologies are widely used in the field of higher art education. This includes not only technical aspects, but also theoretical and pedagogical approaches to teaching. In modern methods of higher education, the emphasis is on the development of students' personalities, broadening their outlook, skills and abilities. Traditional models of learning that existed before the introduction of distance learning are undergoing significant changes, leading to experimental approaches to teaching in art universities. Particular emphasis is placed on the democratisation of educational processes, digitalisation of art education and the use of computer technology. The desire to ensure unity in diversity, which is a necessary component of modern European integration aimed at overcoming the negative effects of globalisation, is also important. One of the key components of the development of modern higher art education is the use of digital technologies. This allows students to create a significant amount of creative work while studying and include it in their professional portfolio. This approach is particularly relevant in the European labour market. Ukraine's experience in applying modern teaching methods in the field of music is in line with European development trends. At the same time, due to Russian military aggression and obsessive propaganda, there is a need to update research on Ukraine-centric music topics. It is important to emphasise the development of Ukrainian art, the study of the life and legacy of prominent teachers, performers and artists, and the integration of the acquired knowledge into the educational process. The conclusions emphasise that the combination of Ukrainian specificity and modern digitalisation trends creates objective conditions for the development of musicology in Ukraine and its presentation at the international level.