Reviewerly/exHarmony huggingface dataset:
Path Planning for Fixed-Wing Unmanned Aerial Vehicles: An Integrated Approach with Theta* and Clothoids

Authors:
raw_author_name: Salvatore Rosario Bassolillo
raw_affiliation_string: Institute for High Performance Computing and Networking of National Research Council (ICAR-CNR), Via Pietro Castellino 111, 80131 Naples, Italy
raw_author_name: Gennaro Raspaolo
raw_affiliation_string: Department of Engineering, University of Campania Luigi Vanvitelli, 81031 Aversa, Italy
raw_author_name: Luciano Blasi
raw_affiliation_string: Department of Engineering, University of Campania Luigi Vanvitelli, 81031 Aversa, Italy
raw_author_name: Egidio D’Amato
raw_affiliation_string: Department of Science and Technology, University of Naples Parthenope, 80143 Napoli, Italy
raw_author_name: Immacolata Notaro
raw_affiliation_string: Department of Engineering, University of Campania Luigi Vanvitelli, 81031 Aversa, Italy

Abstract: Unmanned Aerial Vehicles (UAVs) have emerged as a compelling alternative to manned operations, offering the capability to navigate hazardous environments without risks for human operators. Despite their potential, optimizing UAV missions in complex and unstructured environments remains a pivotal challenge. Path planning becomes a crucial aspect to increase mission efficiency, although it is inherently complex due to various factors such as obstacles, no-fly zones, non-cooperative aircraft, and flight mechanics limitations. This paper presents a path-planning technique for fixed-wing unmanned aerial vehicles (UAVs) based on the Theta* algorithm. The approach introduces innovative features, such as the use of Euler spiral, or clothoids, to serve as connection arcs between nodes, mitigating trajectory discontinuities. The design of clothoids can be linked to the aircraft performance model, establishing a connection between curvature constraints and the specific characteristics of the vehicle. Furthermore, to lower the computational burden, the implementation of an adaptive exploration distance and a vision cone was considered, reducing the number of explored solutions. This methodology ensures a seamless and optimized flight path for fixed-wing UAVs operating in static environments, showcasing a noteworthy improvement in trajectory smoothness. The proposed methodology has been numerically evaluated in several complex test cases as well as in a real urban scenario to prove its effectiveness.
High sensitivity strain measurement on a vibrating saxophone reed using stroboscopic digital image

Authors:
raw_author_name: E Ukshini
raw_affiliation_string: Department of Physics, Laboratory of Biomedical Physics BIMEF, University of Antwerp, Groenenborgerlaan 171, Antwerp, 2020, Belgium
raw_author_name: J Dirckx
raw_affiliation_string: Department of Physics, Laboratory of Biomedical Physics BIMEF, University of Antwerp, Groenenborgerlaan 171, Antwerp, 2020, Belgium

Abstract: Abstract In this paper, we present a study of different optical textures and techniques to apply very fine, non-specular reflecting random speckle texture, which makes it possible to measure surface strains with a sensitivity better than 0.01 % strain on a vibrating object. The method is based on triggered stroboscopic digital image correlation, which is able to obtain time-resolved full-field measurements of displacement and strain fields. The method is demonstrated on reeds of the saxophone to investigate their role in sound production and playability. Such high-sensitivity measurements allow the detection of subtle effects, such as artefacts on synthetic saxophone reeds caused by the production process.
The influence of Ohmic noise on the dynamics of three-spin open quantum system

Authors:
raw_author_name: Muhammad Javed
raw_author_name: Atta ur Rahman

Abstract: Abstract The dynamics of open quantum systems under decoherence effects remain a hotly debated topic in the case of the practical deployment of quantum information processing. In this regard, we examine how the three-qubit mixed state is affected by changes in the cut-off frequency of the Ohmic spectral density in a harmonic reservoir. Specifically, the degree of quantum memory-assisted entropic uncertainty (QMA-EU), along with the entanglement, coherence, and purity of the system, is to be demonstrated. A thorough exercise is done to investigate any underlying relationship between the three-qubit quantum characteristics. We show that a harmonic reservoir controlled by Ohmic noise prevails a monotonic-like decay in the current case where, sooner or later, the state becomes completely disentangled, decoherent, and mixed. The QMA-EU has always been found to have an increasing function causing the quantum resourcefulness to be reduced. Although, there is no pathway to avoid the Ohmic noise consequences and complete decay, however, we provided parameterization which would lead to prolonged preservation of quantum correlations with time. Finally, we provide various settings for the tuning of cut-off frequency regarding the Ohmic type bath and state parameters on the initial as well as final levels of quantum features.
Initial correlations in open quantum systems are always detectable

Authors:
raw_author_name: Iman Sargolzahi
raw_affiliation_string: Department of Physics, University of Neyshabur, Neyshabur 9319774446, Iran

Abstract: Consider an open quantum system which interacts with its environment. Assuming that the experimenter has access only to the system, an interesting question is whether it is possible to detect initial correlations between the system and the environment by performing measurements only on the system. Various methods have been proposed to detect correlations by local measurements on the system. After reviewing these methods, we will show that initial correlations between the system and the environment are always detectable. In particular, we will show that one can always find a unitary evolution, for the whole system-environment, such that the trace distance method, proposed to witness correlations locally, succeeds. We also find the condition for existence of the optimal unitary evolution, for which the entire correlation is locally detectable. Next, we address the case where the system and the environment interact through a time-independent Hamiltonian. For this case we will see that if the initial correlation can be detected locally at some time $t$, then it can be detected for almost all the other times too. On the other hand, we see that one can find cases for which initial correlations between the system and the environment always remain undetectable even though the unitary evolution, generated by the Hamiltonian, is not factorized.
Avoided level crossings with exponentially closing gaps in quantum annealing

Authors:
raw_author_name: Arthur Braida
raw_affiliation_string: Eviden QuantumLab, 78340 Les Clayes-sous-Bois, France; Laboratoire d'Informatique Fondamentale d'Orléans (LIFO), Université d'Orléans, 45067 Orléans, France
raw_author_name: Simon Martiel
raw_affiliation_string: Eviden QuantumLab, 78340 Les Clayes-sous-Bois, France
raw_author_name: Ioan Todinca
raw_affiliation_string: Laboratoire d'Informatique Fondamentale d'Orléans (LIFO), Université d'Orléans, 45067 Orléans, France

Abstract: This paper explores the phenomenon of avoided level crossings in quantum annealing, a promising framework for quantum computing that may provide a quantum advantage for certain tasks. Quantum annealing (QA) involves letting a quantum system evolve according to the Schr\"odinger equation, with the goal of obtaining the optimal solution to an optimization problem through measurements of the final state. However, the continuous nature of quantum annealing makes analytical analysis challenging, particularly with regard to the instantaneous eigenenergies. The adiabatic theorem provides a theoretical result for the annealing time required to obtain the optimal solution with high probability, which is inversely proportional to the square of the minimum spectral gap. Avoided level crossings can create exponentially closing gaps, which can lead to exponentially long running times for optimization problems. In this paper, we use a perturbative expansion to derive a condition for the occurrence of an avoided level crossing during the annealing process. We then apply this condition to the MaxCut problem on bipartite graphs. We show that no exponentially small gaps arise for regular bipartite graphs, implying that QA can efficiently solve MaxCut in that case. On the other hand, we show that irregularities in the vertex degrees can lead to the satisfaction of the avoided level crossing occurrence condition. We provide numerical evidence to support this theoretical development, and discuss the relation between the presence of exponentially closing gaps and the failure of quantum annealing.
Minimality, Necessity and Sufficiency for Argumentation and Explanation

Authors:
raw_author_name: AnneMarie Borg
raw_affiliation_string: Department of Information and Computing Sciences, Utrecht University, Netherlands
raw_author_name: Floris Bex
raw_affiliation_string: Department of Information and Computing Sciences, Utrecht University, Netherlands; Tilburg Institute for Law, Technology, and Society, Tilburg University, Netherlands

Abstract: We discuss explanations for formal (abstract and structured) argumentation – the question whether and why a certain argument or claim can be accepted (or not) under various extension-based semantics. We introduce a flexible framework, which can act as the basis for many different types of explanations. For example, we can have simple or comprehensive explanations in terms of arguments for or against a claim, arguments that (indirectly) defend a claim, the evidence (knowledge base) that supports or is incompatible with a claim, and so on. We show how selection based on necessity and sufficiency can be captured in our basic framework and discuss a real-life application.
Advances on similarity via transversal intersection of manifolds

Authors:
raw_author_name: Zhongshan Li
raw_affiliation_string: Department of Math & Stat, Georgia State University, Atlanta, GA 30303, USA
raw_author_name: Jiamin Pan
raw_affiliation_string: Department of Math & Stat, Georgia State University, Atlanta, GA 30303, USA
raw_author_name: Zheng Yang
raw_affiliation_string: Department of Math & Stat, Georgia State University, Atlanta, GA 30303, USA

Abstract: Let A be an n×n real matrix. As shown in the recent paper “The bifurcation lemma for strong properties in the inverse eigenvalue problem of a graph”, Linear Algebra Appl. 648 (2022), 70–87, by S.M. Fallat, H.T. Hall, J.C.-H. Lin, and B.L. Shader, if the manifolds MA={G−1AG:G∈GL(n,R)} and Q(sgn(A)) (consisting of all real matrices having the same sign pattern as A), both considered as embedded submanifolds of Rn×n, intersect transversally at A, then every superpattern of sgn(A) also allows a matrix similar to A. Those authors introduced a condition on A (in terms of certain linear matrix equations) equivalent to the above transversality, called the nonsymmetric strong spectral property (nSSP). In this paper, this transversality property of A is characterized using an alternative, more direct and convenient condition, called the similarity-transversality property (STP). Let X=[xij] be a generic matrix of order n whose entries are independent variables. The STP of A is defined as the full row rank property of the Jacobian matrix of the entries of AX−XA at the zero entry positions of A with respect to the nondiagonal entries of X. This new approach makes it possible to take better advantage of the combinatorial structure of the matrix A, and provides theoretical foundation for constructing matrices similar to a given matrix while the entries have certain desired signs. In particular, several important classes of zero-nonzero patterns and sign patterns that require or allow this transversality property are identified. Examples illustrating many possible applications (such as diagonalizability, number of distinct eigenvalues, nilpotence, idempotence, semi-stability, eigenvalues and their algebraic and geometric multiplicities, Jordan canonical form, minimal polynomial, and rank) are provided.
A robust phase unwrapping method for phase shifting coding high-frequency color fringe projection profilometry

Authors:
raw_author_name: Bingwei Zhang
raw_affiliation_string: Fujian Key Laboratory of Special Energy Manufacturing, Huaqiao University, Xiamen, 361021, China; Xiamen Key Laboratory of Digital Vision Measurement, Huaqiao University, Xiamen, 361021, China
raw_author_name: Kaiyong Jiang
raw_affiliation_string: Fujian Key Laboratory of Special Energy Manufacturing, Huaqiao University, Xiamen, 361021, China; Xiamen Key Laboratory of Digital Vision Measurement, Huaqiao University, Xiamen, 361021, China
raw_author_name: Junyi Lin
raw_affiliation_string: Fujian Key Laboratory of Special Energy Manufacturing, Huaqiao University, Xiamen, 361021, China; Xiamen Key Laboratory of Digital Vision Measurement, Huaqiao University, Xiamen, 361021, China
raw_author_name: Ping Lu
raw_affiliation_string: Fujian Key Laboratory of Special Energy Manufacturing, Huaqiao University, Xiamen, 361021, China; Xiamen Key Laboratory of Digital Vision Measurement, Huaqiao University, Xiamen, 361021, China

Abstract: Phase unwrapping is one of the key problems in fringe projection profilometry (FPP). How to achieve unambiguous fringe step order to perform phase unwrapping with few patterns still face a major challenge. We propose a robust phase unwrapping method by using a pair of encoded color fringe patterns, one is a conventional three-step phase-shifting color fringe pattern with equal phase shifts, another is added an additional phase shift valve t(k) to the former, in which t(k) is related to the order of fringe periods. A single-valued solution function for t(k) is constructed and used to determine the unique fringe order. Besides, multiplexing this pair of fringes can help denoise the extracted wrapped phase to improve the accuracy. The simulation and experimental results proved that the proposed method can achieve unambiguous phase unwrapping for high-frequency fringe patterns. The proposed method is also applicable for isolated objects.
Connection-density-aware satellite-ground federated learning via asynchronous dynamic aggregation

Authors:
raw_author_name: Zhuo Xu
raw_affiliation_string: Department of Computer Science and Technology, Shantou University, Shantou 515063, Guangdong, China; School of Computer Science, Wuhan University, Wuhan 430072, Hubei, China
raw_author_name: Mengqing Jin
raw_affiliation_string: Department of Computer Science and Technology, Shantou University, Shantou 515063, Guangdong, China
raw_author_name: Jian Lin
raw_affiliation_string: Department of Computer Science and Technology, Shantou University, Shantou 515063, Guangdong, China
raw_author_name: Yuelong Liu
raw_affiliation_string: Department of Computer Science and Technology, Shantou University, Shantou 515063, Guangdong, China
raw_author_name: Jianlong Xu
raw_affiliation_string: Department of Computer Science and Technology, Shantou University, Shantou 515063, Guangdong, China
raw_author_name: Zhi Xiong
raw_affiliation_string: Department of Computer Science and Technology, Shantou University, Shantou 515063, Guangdong, China
raw_author_name: Hao Cai
raw_affiliation_string: Department of Computer Science and Technology, Shantou University, Shantou 515063, Guangdong, China

Abstract: With the development of space technology, the use of satellites for Earth observation is becoming more and more common. Among them, low-earth orbit (LEO) satellites have received a lot of attention because of their short return period and low cost. However, traditional satellite systems are unable to process data in orbit due to technical limitations and can only transmit massive amounts of data with useless information back to ground stations and then perform calculations, putting a tremendous strain on downstream bandwidth. Additionally, there are data walls between satellite affiliates, which makes it difficult to share and use data. To address the lack of data processing capabilities and data barriers in conventional satellite systems, as well as to effectively use satellite resources and enhance worldwide collaboration, we proposed a connection density-aware satellite-ground federated learning (FL) framework. According to this structure, satellites serve as workers in federated learning, analyzing data and transmitting the parameters to ground stations for aggregation. The ground station senses the satellite’s connection density during the aggregation process and implements a dynamic aggregation approach for the downstream parameters. Experiments based on real image datasets and on a simulated satellite network validate the effectiveness of the method in terms of execution efficiency and accuracy.
Machine learning and deep learning for user authentication and authorization in cybersecurity: A state-of-the-art review

Authors:
raw_author_name: Jamin Rahman Jim
raw_affiliation_string: Department of Computer Science, American International University-Bangladesh, Dhaka-1229, Bangladesh
raw_author_name: Md Mohsin Kabir
raw_affiliation_string: Department of Computer Science & Engineering, Bangladesh University of Business & Technology, Dhaka-1216, Bangladesh
raw_author_name: M.F. Mridha
raw_affiliation_string: Department of Computer Science, American International University-Bangladesh, Dhaka-1229, Bangladesh

Abstract: In the continuously developing field of cyber security, user authentication and authorization play a vital role in protecting personal information and digital assets from unauthorized use. As the field of cyber security expands, traditional user authentication and authorization approaches are not enough to prevent unauthorized access to personal information. Therefore, Machine Learning and Deep Learning models are introduced in cybersecurity. To assist researchers and cybersecurity experts in their research endeavours, a comprehensive and informative study is required covering the state-of-the-art advancements. Therefore, this research aimed to explore the field of Machine Learning and Deep Learning-based user authentication and authorization. More specifically, this paper intends to explore the diverse application domains of Machine Learning and Deep Learning-based user authentication and authorization. The paper also analyzes the commonly used datasets, pre-processing methods and Machine Learning and Deep Learning algorithms in user authentication and authorization. After that, this study conducts a thorough and detailed examination of some state-of-the-art articles' results and experimental details to enhance comprehension of the present advancements. Finally, the study engages in a comprehensive discussion concerning the various challenges encountered and outlines potential avenues for future research. This systematic review provides an all-encompassing overview of Machine Learning and Deep Learning-based user authentication and authorization, covering its application domains, models, analysis of state-of-the-art results, challenges, and research directions. It serves as a valuable resource for interdisciplinary studies.
Knowledge Distillation via Token-level Relationship Graph based on the Big Data technologies

Authors:
raw_author_name: Shuoxi Zhang
raw_affiliation_string: School of Computer Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, Hubei, China
raw_author_name: Hanpeng Liu
raw_affiliation_string: School of Computer Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, Hubei, China
raw_author_name: Kun He
raw_affiliation_string: School of Computer Science and Technology, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan, 430074, Hubei, China

Abstract: In the big data era, characterized by vast volumes of complex data, the efficiency of machine learning models is of utmost importance, particularly in the context of intelligent agriculture. Knowledge distillation (KD), a technique aimed at both model compression and performance enhancement, serves as a pivotal solution by distilling the knowledge from an elaborate model (teacher) to a lightweight, compact counterpart (student). However, the true potential of KD has not been fully explored. Existing approaches primarily focus on transferring instance-level information by big data technologies, overlooking the valuable information embedded in token-level relationships, which may be particularly affected by the long-tail effects. To address the above limitations, we propose a novel method called Knowledge Distillation with Token-level Relationship Graph (TRG) that leverages token-wise relationships to enhance the performance of knowledge distillation. By employing TRG, the student model can effectively emulate higher-level semantic information from the teacher model, resulting in improved performance and mobile-friendly efficiency. To further enhance the learning process, we introduce a dynamic temperature adjustment strategy, which encourages the student model to capture the topology structure of the teacher model more effectively. We conduct experiments to evaluate the effectiveness of the proposed method against several state-of-the-art approaches. Empirical results demonstrate the superiority of TRG across various visual tasks, including those involving imbalanced data. Our method consistently outperforms the existing baselines, establishing a new state-of-the-art performance in the field of KD based on big data technologies.
Investigating the behavioural intentions of museum visitors towards VR: A systematic literature review

Authors:
raw_author_name: Li YiFei
raw_affiliation_string: Faculty of Applied and Creative Arts, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia
raw_author_name: Mohd Kamal Othman
raw_affiliation_string: Faculty of Cognitive Sciences and Human Development, Universiti Malaysia Sarawak, Kota Samarahan, Sarawak, Malaysia

Abstract: This study investigates the behavioural intentions of museum visitors towards Virtual Reality (VR) technology, spanning the years 2010–2023. It evaluates literature quality, explores research theories, and identifies trends. Findings indicate that most museum visitors hold positive attitudes towards VR, necessitating further research on generational perspectives. Quantitative research methods dominate (77.8%), with 38.9% employing the Technology Acceptance Model (TAM) or its extensions. Key influencing factors include perceived usefulness, information quality, perceived ease of use, and psychological cognition. The study underscores the importance of comprehending generational differences among museum visitors and advocates for adopting comprehensive theoretical models in future research within the museum domain. This research contributes to understanding how museum visitors engage with VR technology, emphasising nuanced approaches considering generational variations and recommending more inclusive theoretical frameworks.