Reviewerly/exHarmony huggingface dataset:
Pedagogical Technology of Teaching as an Aid to Professional Self-Determination of 2nd Year Medical Students of Secondary Vocational Education

Authors:
raw_author_name: Olga O. Andronnikova
raw_author_name: Natalia A. Galuzo
raw_author_name: Marina G. Zhdanova

Abstract: Medical profession two-year training within the framework of secondary vocational education presupposes effective organization of educational activity. The article delves into the results of pedagogical technology of teaching professional communication to 2nd year medical students of secondary vocational education, taking into account the difficulties of their professional development revealed in the study of 2021–2022. The aim of the work is to describe the formation of students’ professional communication skills in the process of solving the contradiction between the level of their communicative competence and the requirement of the profession-al community. Cultural-historical theory of L.S. Vygotsky and his theoretical concept of the sensory period of development are the methodological approach of the study, based on which the authors investigate the profes-sional self-determination of medical students. By analyzing the results of the article the difficulties of training were highlighted: communicative incompetence in professional communication, lack of confidence in meeting the requirements of medical institutions. Thus, the pedagogical technology aims to solve these difficulties by supporting the conditions for students to discuss the results of their learning activities.
Analysis of the Influence of Fund Allocation and Sustainable Academic Efficiency Based on a Transformation of Public Goods in Higher Education

Authors:
raw_author_name: Angel Chang
raw_affiliation_string: Graduate School of Education, Chung Yuan Christian University, Taoyuan City 320314, Taiwan

Abstract: The allocation of funding for higher education typically focuses on competition in neoliberal mechanisms. Surprisingly, much less attention has been paid to considering the effect of fund allocations for sustainable development through public goods purposes in neoliberal contexts. This study aims to examine specific funding schemes and determine the influential factors impacting funding for teaching, research, and public goods transformation. Taking Taiwan’s Higher Education Sprout Project (HESP) as an example, we explored the effect of policy initiatives on public goods transformation towards sustainable development. The data were collected from the Ministry of Education and Scopus databases. First, a regression analysis was conducted to determine which factors influence the effect of funding allocations in academic institutes. Second, we used a logistic regression to detect the effects of the system and the sector. Third, we used partial least square structural equation modeling (PLS-SEM) to explore the causal effects among the selected impact variables on expected outcomes. Finally, we used the bootstrap method to demonstrate the model’s robustness. Our study found that only diversity was shown in private technology groups receiving less HESP funding, while it did not widen the differences in the sector and system in the transformation process. Our findings suggest that funding allocations will not affect teaching and research based on sectors and systems. In contrast, this study demonstrates that transforming public goods through special funding can play a critical role in leading sustainable development in higher education.
Methodologies and Handling Techniques of Large-Scale Information in Decision Support Systems for Complex Missions

Authors:
raw_author_name: George Tsavdaridis
raw_affiliation_string: School of Electrical & Computer Engineering, National Technical University of Athens, 9, Iroon Polytechniou Str., 15772 Athens, Greece
raw_author_name: Constantin Papaodysseus
raw_affiliation_string: School of Electrical & Computer Engineering, National Technical University of Athens, 9, Iroon Polytechniou Str., 15772 Athens, Greece
raw_author_name: Nikolaos V. Karadimas
raw_affiliation_string: Division of Mathematics and Engineering Science, Department of Military Science, Hellenic Army Academy, Evelpidon Avenue, 16673 Athens, Greece
raw_author_name: Athanasios Delis
raw_affiliation_string: School of Electrical & Computer Engineering, National Technical University of Athens, 9, Iroon Polytechniou Str., 15772 Athens, Greece

Abstract: Designing integrating systems for support, real-time monitoring, and executing of complex missions is challenging, since they often fail due to high levels of complexity and overwhelming volume of input data. Past attempts have resorted to “ad hoc” solutions, which face issues of being non-updatable, non-upgradable, and not applicable to similar missions, necessitating a complete redesign and reconstruction of the system. In the national defense and security sector, the impact of this reconstruction requirement leads to significant costs and delays. This study presents advanced methodologies for organizing large-scale datasets and handling complex operational procedures systematically, enhancing the capabilities of Decision Support Systems (DSSs). By introducing Complex Mission Support Systems (CMSSs), a novel SS sub-component, improved accuracy and effectiveness are achieved. The CMSS includes mission conceptualization, analysis, real-time monitoring, control dynamics, execution strategies, and simulations. These methods significantly aid engineers in developing DSSs that are highly user-friendly and operational, thanks to human-reasoning-centered design, increasing performance and efficiency. In summary, the systematic development of data cores that support complex processes creates an adaptable and adjustable framework in a wide range of diverse missions. This approach significantly enhances the overall sustainability and robustness of an integrated system.
Recycling of a quantum field and optimal states for single-qubit rotations

Authors:
raw_author_name: Shanon Vuglar
raw_affiliation_string: Department of Electrical Engineering, John Brown University, Siloam Springs, Arkansas 72761, USA
raw_author_name: Julio Gea-Banacloche
raw_affiliation_string: Department of Physics, University of Arkansas, Fayetteville, Arkansas 72701, USA

Abstract: The authors introduce a protocol to generate the electromagnetic field state that is optimal for controlling a given qubit rotation. The protocol, based on the interaction of the field with ancilla qubits, allows for field ``recycling'' and could potentially reduce error rates and improve energy efficiency in quantum computing schemes.
Spatial Transformation Accelerator with Parallel Data Access Scheme for Sample Reconstruction

Authors:
raw_author_name: Rihards Novickis
raw_affiliation_string: Institute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, Latvia
raw_author_name: Daniels Jānis Justs
raw_affiliation_string: Institute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, Latvia
raw_author_name: Kaspars Ozols
raw_affiliation_string: Institute of Electronics and Computer Science, 14 Dzerbenes St., LV-1006 Riga, Latvia

Abstract: Spatial image transformation is a commonly used component in many image processing pipelines. It enables the correction of optical distortions, image registration onto a common reference plane, electronic image stabilisation, digital zoom, video mosaicking, etc. With the growing tendency to embed image processing in low-power devices, attaining an efficient transformation solution becomes increasingly decisive. Furthermore, interpolation is the key operation in achieving the high quality of the transformed data from the original data. Fortunately, different implementations have already seen several efficiency improvements in recent years. However, interpolation relies on sampling a set of neighbouring points from memory, which has yet to be addressed efficiently for smaller computational platforms with limited memory resources. In this work, we derive a generic mathematical model and circuit design principles for the spatial transformation accelerator design for N-dimensional data. Furthermore, we present an efficient simultaneous access scheme for high-quality signal reconstruction. Finally, the introduced ideas are verified in field programmable gate arrays using one-dimensional and two-dimensional data transformation use cases. The presented solution is able to transform images with sizes ranging from 256 × 256 to 8192 × 8192 and achieves a transfer rate of 275 frames per second with 512 × 512 images.
HYBRID RECOMMENDER FOR VIRTUAL ART COMPOSITIONS WITH VIDEO SENTIMENTS ANALYSIS

Authors:
raw_author_name: Heorhii Kuchuk
raw_affiliation_string: National Technical University "Kharkiv Polytechnic Institute", Kharkiv
raw_author_name: Andrii Kuliahin
raw_affiliation_string: National Aerospace University “Kharkiv Aviation Institute”, Kharkiv

Abstract: Topicality. Recent studies confirm the growing trend to implement emotional feedback and sentiment analysis to improve the performance of recommender systems. In this way, a deeper personalization and current emotional relevance of the user experience is ensured. The subject of study in the article is a hybrid recommender system with a component of video sentiment analysis. The purpose of the article is to investigate the possibilities of improving the effectiveness of the results of the hybrid recommender system of virtual art compositions by implementing a component of video sentiment analysis. Used methods: matrix factorization methods, collaborative filtering method, content-based method, knowledge-based method, video sentiment analysis method. The following results were obtained. A new model has been created that combines a hybrid recommender system and a video sentiment analysis component. The average absolute error of the system has been significantly reduced. Added system reaction to emotional feedback in the context of user interaction with virtual art compositions. Conclusion. Thus, the system can not only select the most suitable virtual art compositions, but also create adaptive and dynamic content, which will increase user satisfaction and improve the immersive aspects of the system. A promising direction of further research may be the addition of a subsystem with a generative neural network, which will create new virtual art compositions based on the conclusions of the developed recommendation system.
Civic Probes: A Method That Embeds Questions of Civic Infrastructure and Participation

Authors:
raw_author_name: Ian G. Johnson
raw_affiliation_string: Newcastle University
raw_author_name: Vasilis Vlachokyriakos
raw_affiliation_string: Newcastle University

Abstract: research-article Open Access Share on Civic Probes: A Method That Embeds Questions of Civic Infrastructure and Participation Authors: Ian G. Johnson Newcastle University Newcastle UniversitySearch about this author , Vasilis Vlachokyriakos Newcastle University Newcastle UniversitySearch about this author Authors Info & Claims InteractionsVolume 31Issue 2March - April 2024pp 22–27https://doi.org/10.1145/3643057Published:28 February 2024Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteView all FormatsPDF
Imagining Sustainable Futures: Expanding the Discussion on Sustainable HCI

Authors:
raw_author_name: Eleonora Mencarini
raw_affiliation_string: Bruno Kessler Foundation
raw_author_name: Valentina Nisi
raw_affiliation_string: University of Lisbon
raw_author_name: Christina Bremer
raw_affiliation_string: Lancaster University
raw_author_name: Chiara Leonardi
raw_affiliation_string: Bruno Kessler Foundation
raw_author_name: Nuno Jardim Nunes
raw_affiliation_string: University of Lisbon
raw_author_name: Jen Liu
raw_affiliation_string: Cornell University
raw_author_name: Robert Soden
raw_affiliation_string: University of Toronto

Abstract: research-article Share on Imagining Sustainable Futures: Expanding the Discussion on Sustainable HCI Authors: Eleonora Mencarini Bruno Kessler Foundation Bruno Kessler FoundationSearch about this author , Valentina Nisi University of Lisbon University of LisbonSearch about this author , Christina Bremer Lancaster University Lancaster UniversitySearch about this author , Chiara Leonardi Bruno Kessler Foundation Bruno Kessler FoundationSearch about this author , Nuno Jardim Nunes University of Lisbon University of LisbonSearch about this author , Jen Liu Cornell University Cornell UniversitySearch about this author , Robert Soden University of Toronto University of TorontoSearch about this author Authors Info & Claims InteractionsVolume 31Issue 2March - April 2024pp 39–43https://doi.org/10.1145/3643493Published:28 February 2024Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Quantum Dueling: An Eﬃcient Solution for Combinatorial Optimization

Authors:
raw_author_name: Letian Tang
raw_affiliation_string: Deparment of Physics, Carnegie Mellon University Mellon College of Science, 5032 Forbes Avene, SMC 1262, Pittsburgh, Pennsylvania, 15213-2617, UNITED STATES
raw_author_name: Haorui Wang
raw_affiliation_string: University of Cambridge, The Old Schools, Trinity Lane, Cambridge, Cambridgeshire, CB2 1TN, UNITED KINGDOM OF GREAT BRITAIN AND NORTHERN IRELAND
raw_author_name: Zhengyang Li
raw_affiliation_string: Department of Physics, Tongji University School of Physics Science and Engineering, Siping Road 1239, Shanghai 210002, China, Shanghai, 200092, CHINA
raw_author_name: Haozhan Tang
raw_affiliation_string: Department of Mathematical Sciences, Carnegie Mellon University Mellon College of Science, 5032 Forbes Avenue, SMC 3249, Pittsburgh, Pennsylvania, 15289, UNITED STATES
raw_author_name: Chi Zhang
raw_affiliation_string: Department of Computer Science, Wuhan University, No.299 Bayi Road, Wuhan, Hubei, 430072, CHINA
raw_author_name: Shujin Li
raw_affiliation_string: Deparment of Physics, Carnegie Mellon University Mellon College of Science, 5032 Forbes Aveue, SMC 2402, Pittsburgh, Pennsylvania, 15289, UNITED STATES

Abstract: Abstract In this paper, we present a new algorithm for generic combinatorial optimization, which we term quantum dueling. Traditionally, potential solutions to the given optimization problems were encoded in a "register" of qubits. Various techniques are used to increase the probability of finding the best solution upon measurement. Quantum dueling innovates by integrating an additional qubit register, effectively creating a "dueling" scenario where two sets of solutions compete. This dual-register setup allows for a dynamic amplification process: in each iteration, one register is designated as the "opponent", against which the other register's more favorable solutions are enhanced through a controlled quantum search. This iterative process gradually steers the quantum state within both registers toward the optimal solution. With a quantitative contraction for the evolution of the state vector, classical simulation under a broad range of scenarios and hyper-parameter selection schemes shows that a quadratic speedup is achieved, which is further tested in more real-world situations. In addition, quantum dueling can be generalized to incorporate arbitrary quantum search techniques and as a quantum subroutine within a higher-level algorithm. Our work demonstrates that increasing the number of qubits allows the development of previously unthought-of algorithms, paving the way for advancement of efficient quantum algorithm design.
Dynamical system design of an air-ground amphibious individual unmanned aerial vehicle

Authors:
raw_author_name: Zhihong Liang
raw_affiliation_string: Shenyang University of Technology (China)

Abstract: At present, most of the individual UAVs<sup>[1]</sup> are mainly flying, and the concealment effect is not good when approaching the enemy in field combat, and it is easy to be found and shot down, and the rotor of the UAV is relatively fragile, and it is also more dangerous to fly in a closed and narrow environment such as indoors. The land-air amphibious individual drone can flexibly switch combat modes, and can carry explosives to conceal itself by changing modes when approaching the enemy in the field. According to a land-air amphibious UAV structure, By establishing the overall dynamical system model, the components of each part of the dynamical system are designed and selected, so that the air mode dynamical system and the ground mode dynamical system can be coordinated and converted, and the specific performance parameters are calculated., and provide a reference for the coordinated design of the ground dynamical system and the air dynamical system of individual UAV in the future.
Online Meta-learned Gradient Norms for Active Learning in Science and Technology

Authors:
raw_author_name: Amanda S Barnard
raw_affiliation_string: School of Computing, Australian National University, Building 145, Science Road, Acton, Australian Capital Territory, 2601, AUSTRALIA

Abstract: Abstract Acquisition of scientific data can be expensive and time-consuming. Active learning is a solution to reduce costs and time by guiding the selection of scientific experiments. Autonomous and automatic identification of the most essential samples to annotate by active learning can also help to mitigate human bias. Previous research has demonstrated that unlabelled samples causing the largest gradient norms of neural network models can promote active learning in classification. However, gradient norm estimation in regression is non-trivial because the continuous one-dimensional output of regression significantly differs from classification. In this study, we propose a new active learning method that uses meta-learning to estimate the gradient norm of the unlabelled sample in regression. Specifically, we use a separate model to be a selector that learns knowledge from the previous active learning results and is used to predict the gradient norms of unlabelled samples. In each active learning iteration, we estimate and select unlabelled samples with the largest gradient norms to annotate. Our method is evaluated on six regression data sets in various domains, which include costly scientific data.
DGCR: depth graph convolution recommendation algorithm integrating social and residual

Authors:
raw_author_name: Haixin Huang
raw_affiliation_string: Shenyang Ligong University (China)

Abstract: Graph neural network technology is widely used in social recommendation system to learn the embedded representation of users and items in the process of user interest graph and user social graph propagation. To solve the existing problems, this paper proposes a depth graph convolution recommendation algorithm (DGCR) that integrates social and residual errors. It uses lightweight graph convolution to carry out convolution propagation for users and items respectively in two graphs about users, and introduces the idea of residual network for deep propagation to prevent over-smoothing. At the same time, a more flexible multi-layer perceptron is used for image fusion to reduce the information gap. Compared with the baseline algorithm on LastFM and Ciao datasets, the experimental results show that DGCR algorithm has a significant improvement in recommendation effectiveness and cold start problems.
Autonomous planning method for intelligent UAV swarm flight path based on swarm policy

Authors:
raw_author_name: Jiaqi Guo
raw_affiliation_string: Shenyang Ligong University (China)
raw_author_name: Xianglong Mu
raw_affiliation_string: Shenyang Ligong University (China)

Abstract: Aiming at the flight path planning problem of intelligent UAVs (swarms), this paper designs a "swarm-type" planning strategy, which improves the distributed spatio-temporal trajectory planning method under special scenarios. According to the spatial distribution of UAVs, the UAV swarm is dynamically divided into a number of groups and isolated UAVs, and a "swarm-type" coordination mechanism is established for UAV trajectory conflicts within each group, and the group planning consists of the improved Efficient Multi-Intelligent Aperture Path Finding (EMAPF) and trajectory co-optimization, which significantly improves the efficiency and safety of the planning. The group planning consists of improved efficient multi-intelligence pathfinding (EMAPF) and joint optimization of trajectories, which significantly improves the planning efficiency and safety.
UAV cluster obstacle avoidance trajectory planning integrating collaborative control design

Authors:
raw_author_name: yongping hao
raw_affiliation_string: Liaoning Key Laboratory of Advanced Manufacturing Technology and Equipment (China); Shenyang Ligong University (China)

Abstract: This paper aims to propose an obstacle avoidance trajectory planning and group collaborative control method for UAV based on intelligent cluster. Based on the RRT obstacle avoidance algorithm, the consistency theory algorithm of group collaborative control strategy is fused, and the coordination and collaboration between UAVs are realized through information exchange and distributed control methods, so as to maintain cluster cooperative flight while avoiding obstacles and complete specific patrol strike tasks. The experimental results show that the algorithm can effectively realize the obstacle avoidance trajectory planning and group collaborative control of UAV, and improve the safety, stability and maneuverability of UAV.
Hardware Study and Implementation of Image Encryption Algorithm Based on a Hyperchaotic Key Generator

Authors:
raw_author_name: Rim Amdouni
raw_affiliation_string: University of Monastir, avenue ibn el jazzar - 5019 monastir, Beja, monastir, 5000, TUNISIA
raw_author_name: Mohamed Ali Hajjaji
raw_affiliation_string: University of Monastir, hh, Monastir, 5000, TUNISIA
raw_author_name: Abdellatif Mtibaa
raw_affiliation_string: University of Sfax, sfax, Sfax, 3029, TUNISIA

Abstract: Abstract In today's interconnected world, digital data transmissions are an integral part of our communication systems. Connected objects are commonly used in digital life, however, they can be vulnerable to hacking and personal data theft due to inadequate security. To address the size and capability limitations of existing embedded devices, lightweight cryptography has been developed. This paper presents a hardware implementation of a lightweight cryptographic method using VHDL and FPGAs to secure digital information, specifically images. The proposed algorithm is a block cipher scheme that operates on blocks of 128-bit length and employs a key generator-based chaos. The cryptosystem includes a whitening operation, random permutation, and key-dependent Substitution box. The proposed hardware implementation of the algorithm was validated using a Xilinx FPGA-Zynq platform and can secure different gray-scale images while maintaining low power usage, a high frequency of 160.6098 MHz, and high throughput of 11314.917 Mbps. The cryptosystem is shown to be effective against statistical and differential attacks, and key sequences are tested using the NIST SP 800-22 test suite. The algorithm's robustness with respect to Shannon's theory and Chaos is discussed, emphasizing its high level of security and performance.&amp;#xD;