Reviewerly/exHarmony huggingface dataset:
“Below 58 BPM,” involving real-time monitoring and self-medication practices in music performance through IoT technology

Authors:
raw_author_name: Nicoló Merendino
raw_affiliation_string: CSC - Department of Information Engineering, University of Padova, Italy
raw_author_name: Antonio Rodà
raw_affiliation_string: CSC - Department of Information Engineering, University of Padova, Italy
raw_author_name: Raul Masu
raw_affiliation_string: Computational Media and Arts, Hong Kong University of Science and Technology (GZ), China

Abstract: The project presented in this paper illustrates the design process for the development of an IoT system that monitors a specific bio-metric parameter (heart rate) in real time and provides feedback for an opera singer, as well as adding effects that manipulate the sounds emitted by the body during a self-healing practice. This allows the singer to rest and alternate opera singing techniques (which is very demanding) with other less demanding singing techniques and even a self-healing session in case of necessity during a performance. The case study presented in this paper has been developed with and for Eleonora Amianto, an opera singer who suffered from a carotid aneurysm. We performed an idiographic design process, closely collaborating with Eleonora, and developed a wearable IoT that suited her health and artistic needs. In the design of the system, we explore the intersection between self-healthcare and performative arts, focusing on the use of an Internet of Musical Things (IoMusT) system to implement medical prevention and treatment practices in an art performance. The system is developed using open-source tools, allowing for easy replication and improvement, as well as reducing risks of obsolescence and costs of updating. We complement a formal evaluation session with field notes collected during the design phase. We could observe a positive effect of the system on Eleonora's practice and its potential applications within different performative scenarios.
An analysis of register variances between China and the US in international communications

Authors:
raw_author_name: Guo Zhen
raw_affiliation_string: National Research Centre for Foreign Language Education, Beijing Foreign Studies University

Abstract: Translation of international communications plays an important role in facilitating the spread of a country’s voice and shaping its national image. This study employs multidimensional analysis to analyze China’s interpretation of international communications and compares it with the speeches from the White House press conferences to uncover the register variances between the two. The findings reveal that China and the U.S. differ in 4 dimensions and 46 individual linguistic features. The former is more informational with explicit written features and can be categorized into the register of learned exposition; the latter is more interactive and persuasive with prominent features of colloquialism, belonging to the register of involved persuasion. Through comparison with the source language, we find that the differences between the two are influenced by multiple factors such as source language, interpreting process, and political considerations. In conclusion, the interpretation of China’s international communications is a “third language code” with distinctive features from the language used by the U.S. in the political scenario, reflecting a meticulous, responsible but less interactive national image. These findings could shed light on the interpreting strategies adopted by government interpreters and further improve the effectiveness of international communications.
Evolutionary Reinforcement Learning: Hybrid Approach for Safety-Informed Fault-Tolerant Flight Control

Authors:
raw_author_name: Erik-Jan van Kampen
raw_affiliation_string: Delft University of Technology, 2600 GB Delft, The Netherlands

Abstract: Recent research in artificial intelligence potentially provides solutions to the challenging problem of fault-tolerant and robust flight control. This paper proposes a novel Safety-Informed Evolutionary Reinforcement Learning algorithm (SERL), which combines Deep Reinforcement Learning (DRL) and neuroevolution to optimize a population of nonlinear control policies. Using SERL, the work has trained agents to provide attitude tracking on a high-fidelity nonlinear fixed-wing aircraft model. Compared to a state-of-the-art DRL solution, SERL achieves better tracking performance in nine out of ten cases, remaining robust against faults and changes in flight conditions, while providing smoother action signals.
Self-Prompting Tracking: A Fast and Efficient Tracking Pipeline for UAV Videos

Authors:
raw_author_name: Zhixing Wang
raw_affiliation_string: Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China; School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
raw_author_name: Gaofan Zhou
raw_affiliation_string: Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
raw_author_name: Jinzhen Yao
raw_affiliation_string: Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
raw_author_name: Jianlin Zhang
raw_affiliation_string: Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
raw_author_name: Qiliang Bao
raw_affiliation_string: Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
raw_author_name: Qintao Hu
raw_affiliation_string: Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China

Abstract: In the realm of visual tracking, remote sensing videos captured by Unmanned Aerial Vehicles (UAVs) have seen significant advancements with wide applications. However, there remain challenges to conventional Transformer-based trackers in balancing tracking accuracy and inference speed. This problem is further exacerbated when Transformers are extensively implemented at larger model scales. To address this challenge, we present a fast and efficient UAV tracking framework, denoted as SiamPT, aiming to reduce the number of Transformer layers without losing the discriminative ability of the model. To realize it, we transfer the conventional prompting theories in multi-model tracking into UAV tracking, where a novel self-prompting method is proposed by utilizing the target’s inherent characteristics in the search branch to discriminate targets from the background. Specifically, a self-distribution strategy is introduced to capture feature-level relationships, which segment tokens into distinct smaller patches. Subsequently, salient tokens within the full attention map are identified as foreground targets, enabling the fusion of local region information. These fused tokens serve as prompters to enhance the identification of distractors, thereby avoiding the demand for model expansion. SiamPT has demonstrated impressive results on the UAV123 benchmark, achieving success and precision rates of 0.694 and 0.890 respectively, while maintaining an inference speed of 91.0 FPS.
Gaming using different hand gestures using artificial neural network

Authors:
raw_author_name: Prema S
raw_affiliation_string: Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology
raw_author_name: G Deena
raw_affiliation_string: SRM Institute of Science and Technology
raw_author_name: Hemalatha D
raw_affiliation_string: Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology
raw_author_name: Aruna K B
raw_affiliation_string: S. A. Engineering College
raw_author_name: Hashini S
raw_affiliation_string: Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

Abstract: INTRODUCTION: Gaming has evolved over the years, and one of the exciting developments in the industry is the integration of hand gesture recognition.&#x0D; OBJECTIVES: This paper proposes gaming using different hand gestures using Artificial Neural Networks which allows players to interact with games using natural hand movements, providing a more immersive and intuitive gaming experience.&#x0D; METHODS: Introduces two modules: recognition and analysis of gestures. The gesture recognition module identifies the gestures, and the analysis module assesses them to execute game controls based on the calculated analysis.&#x0D; RESULTS: The main results obtained in this paper are enhanced accessibility, higher accuracy and improved performance.&#x0D; CONCLUSION: To communicate with any of the traditional systems, physical contact is necessary. In the hand gesture recognition system, the same functionality can be interpreted by gestures without requiring physical contact with the interfaced devices.
The development of aesthetic experience through virtual and augmented reality

Authors:
raw_author_name: Cong Zhou
raw_affiliation_string: Teacher Education College, Hunan City University, Yiyang, Hunan, China
raw_author_name: JianQi Li
raw_affiliation_string: Teacher Education College, Hunan City University, Yiyang, Hunan, China

Abstract: Abstract Emerging technological innovations offer the potential for experiential engagement through virtual scenarios, yet the viability of this approach for educational purposes remains significantly underexplored. This study aims to assess the feasibility of Augmented Reality (AR) and Virtual Reality (VR) technologies in providing users with aesthetic experiences when visiting digital exhibitions. A total of 190 students participated in this investigation. The control group visited traditional exhibits at the Palace Museum in Beijing. This group underwent a survey to evaluate their acquired aesthetic experience. In contrast, the experimental group, comprising 96 students, engaged with VR/AR scenarios at the Palace Museum in Beijing. Accordingly, students in the experimental group were also surveyed to evaluate both their aesthetic experiences and, additionally, their user experiences. The survey results unveiled significant distinctions in aesthetic experiences between students in the control and experimental groups. Moreover, there were notable correlations between individual variables related to user and aesthetic experiences within the experimental group. Furthermore, the study revealed disparities in both user and aesthetic experiences among male and female students. The findings have implications for aesthetic education teachers and officials in the context of developing sound strategies for providing aesthetic experiences to their students. This information is also of interest to employees of museums, exhibitions, and other cultural facilities, who are interested in holding or hold digital exhibitions.
Complete characterization of a class of permutation trinomials in characteristic five

Authors:
raw_author_name: Markus Grassl
raw_affiliation_string: International Centre for Theory of Quantum Technologies, University of Gdansk, Gdansk, Poland
raw_author_name: Ferruh Özbudak
raw_affiliation_string: FENS, Sabancı University, Ístanbul, Turkey
raw_author_name: Buket Özkaya
raw_affiliation_string: Institute of Applied Mathematics, Middle East Technical University, Ankara, Turkey
raw_author_name: Burcu Gülmez Temür
raw_affiliation_string: Department of Mathematics, Atılım University, Ankara, Turkey

Abstract: Abstract In this paper, we address an open problem posed by Bai and Xia in [2]. We study polynomials of the form $$f(x)=x^{4q+1}+\lambda _1x^{5q}+\lambda _2x^{q+4}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>f</mml:mi> <mml:mrow> <mml:mo>(</mml:mo> <mml:mi>x</mml:mi> <mml:mo>)</mml:mo> </mml:mrow> <mml:mo>=</mml:mo> <mml:msup> <mml:mi>x</mml:mi> <mml:mrow> <mml:mn>4</mml:mn> <mml:mi>q</mml:mi> <mml:mo>+</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> <mml:mo>+</mml:mo> <mml:msub> <mml:mi>λ</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:msup> <mml:mi>x</mml:mi> <mml:mrow> <mml:mn>5</mml:mn> <mml:mi>q</mml:mi> </mml:mrow> </mml:msup> <mml:mo>+</mml:mo> <mml:msub> <mml:mi>λ</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:msup> <mml:mi>x</mml:mi> <mml:mrow> <mml:mi>q</mml:mi> <mml:mo>+</mml:mo> <mml:mn>4</mml:mn> </mml:mrow> </mml:msup> </mml:mrow> </mml:math> over the finite field $${\mathbb F}_{5^{k}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>F</mml:mi> <mml:msup> <mml:mn>5</mml:mn> <mml:mi>k</mml:mi> </mml:msup> </mml:msub> </mml:math> , which are not quasi-multiplicative equivalent to any of the known permutation polynomials in the literature. We find necessary and sufficient conditions on $$\lambda _1, \lambda _2 \in {\mathbb F}_{5^{k}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mi>λ</mml:mi> <mml:mn>1</mml:mn> </mml:msub> <mml:mo>,</mml:mo> <mml:msub> <mml:mi>λ</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:mo>∈</mml:mo> <mml:msub> <mml:mi>F</mml:mi> <mml:msup> <mml:mn>5</mml:mn> <mml:mi>k</mml:mi> </mml:msup> </mml:msub> </mml:mrow> </mml:math> so that f ( x ) is a permutation monomial, binomial, or trinomial of $${\mathbb F}_{5^{2k}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>F</mml:mi> <mml:msup> <mml:mn>5</mml:mn> <mml:mrow> <mml:mn>2</mml:mn> <mml:mi>k</mml:mi> </mml:mrow> </mml:msup> </mml:msub> </mml:math> .
Detecting multiple coexisting emotions from public emergency opinions

Authors:
raw_author_name: Shouqiang Sun
raw_affiliation_string: School of Information Management, Wuhan University, China
raw_author_name: Ting ting Li
raw_affiliation_string: School of Information Management, Wuhan University, China

Abstract: To detect multiple coexisting emotions from public emergency opinions, this article proposes a novel two-stage multiple coexisting emotion-detection model. First, the text semantic feature extracted through bidirectional encoder representation from transformers (BERT) and the emotion lexicon feature extracted through the emotion dictionary are fused. Then, the emotion subjectivity judgement and multiple coexisting emotion detection are performed in two separate stages. In the first stage, we introduce synthetic minority oversampling technique (SMOTE) to enhance the balance of data distribution and select the optimal classifier to recognise opinion texts with emotion. In the second stage, the label powerset (LP)-SMOTE is proposed to increase the number of the minority category samples, and multichannel emotion classifiers and the decision mechanism are employed to recognise different types of emotions and determine the final coexisting emotion labels. Finally, the Weibo data about coronavirus disease 2019 (COVID-19) are collected to verify the effectiveness of the proposed model. Experiment results indicate that the proposed model outperforms state-of-the-art models, with the F1_macro of 0.8532, the F1_micro of 0.8333, and the hamming loss of 0.0476. The emotion detection results are conducive to decision-making for public emergency departments.
An empirical study of the personality factors and individual characteristics of older adult participation in third age education

Authors:
raw_author_name: Sheng-Xiong Wu
raw_affiliation_string: Institute of Community Education Research, The Open University of Fujian, Fuzhou, China

Abstract: In China, the innovative development of education for older people is an important response to the aging population, and an important way to meet the spiritual, cultural, and social needs of older people. Current academic research mainly focuses on the social factors that affect the participation of older people in education and there are few empirical studies on the individual psychological characteristics of older adult learning behavior. This study takes a positive psychology approach to the exploration of the factors influencing the participation of older adults in education in a number of universities of the Third Age in Fujian Province, China. The study is based on curriculum preferences and frequency of participation in extracurricular activities. The results show that the personality traits of extraversion and neuroticism, as well as gender, age, level of educational attainment, and family economic status significantly affect frequency of participation in extracurricular activities and the curriculum preferences of older learners. The results of this study suggest that we can strengthen personality matching to promote the learning enthusiasm of older people in education, and adhere to the demand-oriented to promote the Third age education curriculum personalized. Furthermore, we should increase the scope for popularizing Third age education, improve the accessibility of education for the older people, accelerate the integration of older adult education with the Internet, innovate the form of older adult education, and then promote the development of customized curricula.
An Iris Image Super-Resolution Model Based on Swin Transformer and Generative Adversarial Network

Authors:
raw_author_name: Xiaodong Zhu
raw_affiliation_string: College of Computer Science and Technology, Jilin University, Changchun 130012, China; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
raw_author_name: Haifeng Jiang
raw_affiliation_string: College of Software, Jilin University, Changchun 130012, China; Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China

Abstract: The process of iris recognition can result in a decline in recognition performance when the resolution of the iris images is insufficient. In this study, a super-resolution model for iris images, namely SwinGIris, which combines the Swin Transformer and the Generative Adversarial Network (GAN), is introduced. SwinGIris performs quadruple super-resolution reconstruction for low-resolution iris images, aiming to improve the resolution of iris images and thereby improving the recognition accuracy of iris recognition systems. The model utilizes residual Swin Transformer blocks to extract depth global features, and the progressive upsampling method along with sub-pixel convolution is conducive to focusing on the high-frequency iris information in the presence of more non-iris information. In order to preserve high-frequency details, the discriminator employs a VGG-style relative classifier to guide the generator in generating super-resolution images. In experimental section, we enhance low-resolution (56 × 56) iris images to high-resolution (224 × 224) iris images. Experimental results indicate that the SwinGIris model achieves satisfactory outcomes in restoring low-resolution iris image textures while preserving identity information.
Event-Based Guidance and Incremental Control with Application to Fixed-wing Unmanned Aerial Vehicle Perched Landing Maneuvers

Authors:
raw_author_name: Yansui Song
raw_affiliation_string: School of Automation, Northwestern Polytechnical University, Xi’an, 710072, China
raw_author_name: Chenggang Tao
raw_affiliation_string: Chengdu Aircraft Design and Research Institute, Chengdu, 610041, China
raw_author_name: Zhen He
raw_affiliation_string: College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China
raw_author_name: Bin Xu
raw_affiliation_string: School of Automation, Northwestern Polytechnical University, Xi’an, 710072, China

Abstract: Abstract Considering the nonlinearity and unknown dynamics of fixed-wing unmanned aerial vehicles in perched landing maneuvers, an event-based online guidance and incremental control scheme is proposed. The guidance trajectory for perched landing must be dynamically feasible therefore an event-based trapezoidal collocation point optimization method is proposed. Introduction of the triggering mechanism for the rational use of computing resources to improve PL accuracy. Furthermore, a filter-based incremental nonlinear dynamic inverse (F-INDI) control with state transformation is proposed to achieve robust trajectory tracking under high angle of attack (AOA). The F-INDI uses low-pass filters to obtain incremental dynamics of the system, which simplifies the design process. The state transformation strategy is to convert the flight-path angle, AOA and velocity into two composite dynamics, which avoids the sign reversal problem of control gain under high AOA. The stability analysis shows that the original states can be controlled only by controlling the composite state. Simulation results show that the proposed scheme achieves high perched landing accuracy and a reliable trajectory tracking control.
PrecisionLymphoNet: Advancing Malignant Lymphoma Diagnosis via Ensemble Transfer Learning with CNNs

Authors:
raw_author_name: Kumaresan Perumal
raw_affiliation_string: School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore 632014, India
raw_author_name: Muhammad Fazal Ijaz
raw_affiliation_string: School of IT and Engineering, Melbourne Institute of Technology, Melbourne, VIC 3000, Australia
raw_author_name: Chiranji Lal Chowdhary
raw_affiliation_string: School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore 632014, India

Abstract: Malignant lymphoma, which impacts the lymphatic system, presents diverse challenges in accurate diagnosis due to its varied subtypes—chronic lymphocytic leukemia (CLL), follicular lymphoma (FL), and mantle cell lymphoma (MCL). Lymphoma is a form of cancer that begins in the lymphatic system, impacting lymphocytes, which are a specific type of white blood cell. This research addresses these challenges by proposing ensemble and non-ensemble transfer learning models employing pre-trained weights from VGG16, VGG19, DenseNet201, InceptionV3, and Xception. For the ensemble technique, this paper adopts a stack-based ensemble approach. It is a two-level classification approach and best suited for accuracy improvement. Testing on a multiclass dataset of CLL, FL, and MCL reveals exceptional diagnostic accuracy, with DenseNet201, InceptionV3, and Xception exceeding 90% accuracy. The proposed ensemble model, leveraging InceptionV3 and Xception, achieves an outstanding 99% accuracy over 300 epochs, surpassing previous prediction methods. This study demonstrates the feasibility and efficiency of the proposed approach, showcasing its potential in real-world medical applications for precise lymphoma diagnosis.