Reviewerly/exHarmony huggingface dataset:
Super-resolution reconstruction of underwater polarized images with a fused attention mechanism

Authors:
raw_author_name: Liying Lang
raw_affiliation_string: Center for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China; Hebei Key Laboratory of Advanced Laser Technology and Equipment, Tianjin 300401, China
raw_author_name: Jinghan Zhang
raw_affiliation_string: Center for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China; Hebei Key Laboratory of Advanced Laser Technology and Equipment, Tianjin 300401, China
raw_author_name: Yajun Pang
raw_affiliation_string: Center for Advanced Laser Technology, Hebei University of Technology, Tianjin 300401, China; Hebei Key Laboratory of Advanced Laser Technology and Equipment, Tianjin 300401, China

Abstract: The polarization imaging technique leverages the disparity between target and background polarization information to mitigate the impact of backward scattered light, thereby enhancing image quality. However, the imaging model of this method exhibits limitations in extracting inter-image features, resulting in less-than-optimal outcomes in turbid underwater environments. In recent years, machine learning methodologies, particularly neural networks, have gained traction. These networks, renowned for their superior fitting capabilities, can effectively extract information from multiple images. The incorporation of an attention mechanism significantly augments the capacity of neural networks to extract inter-image correlation attributes, thereby mitigating the constraints of polarization imaging methods to a certain degree. To enhance the efficacy of polarization imaging in complex underwater environments, this paper introduces a super-resolution network with an integrated attention mechanism, termed as SRGAN-DP. This network is a fusion of an enhanced SRGAN network and the high-performance deep pyramidal split attention (DPSA) module, also proposed in this paper. SRGAN-DP is employed to perform high-resolution reconstruction of the underwater polarimetric image dataset, constructed specifically for this study. A comparative analysis with existing algorithms demonstrates that our proposed algorithm not only produces superior images but also exhibits robust performance in real-world environments.
Application solutions of highway freight information systems based on quantum communication

Authors:
raw_author_name: Wenliang Tang
raw_affiliation_string: East China Jiao Tong University, Nanchang City, Jiangxi Province, China

Abstract: Abstract To improve the security of data transmission in the highway freight information system, this study is an application plan for the highway freight information system based on quantum communication. This solution is based on quantum communication technology to encrypt and transmit key sensitive data [1] ; it realizes unified management of quantum keys through the quantum key cloud terminal and provides key services for the highway freight information system; it realizes access to the system through the quantum key cloud service platform. The secure use of mobile terminal quantum keys improves the overall security of the road freight information system. This scheme uses the quantum encryption key generated only once, effectively protecting the entire system's security. The quantum key management server and quantum key cloud platform defined in this plan manage terminals and quantum keys respectively, and jointly produce and distribute quantum keys with the help of other hardware facilities and software to provide secure transmission of key information.
CROWD MANAGEMENT DURING MASS EVENTS

Authors:
raw_author_name: Jarosław Struniawski

Abstract: Mass events organized in Poland in recent years, including sports, entertainment, as well ascultural and social (religious) gatherings, have been consistently gaining popularity, as reflectedin the large number of participants. This is undoubtedly due to the attractiveness of the events onone hand and the positive assessment of the safety level during these events on the other. Yet itis crucial to recognize that beyond their positive aspects, mass events frequently present specificchallenges and threats. Unpredictable and irrational behaviour among participants can result froma variety of factors, posing risks to their health and lives as well as that of bystanders and property.Effective managing of these situations is a genuine challenge for governmental authorities,services and responsible entities. This challenge stems from comprehensive preparatory andorganizational measures designed to prevent crisis situations and, if they occur, promptly regaincontrol. This study aims to present a model of organizational-procedural solutions and explorethe application of modern information technologies to enhance participant safety during massevents. The research methodology involved a comprehensive analysis of scientific, industry, andlegal materials. Additionally, valuable insights were drawn from the author’s first-hand experiencegained through direct observations while fulfilling official duties in ensuring the safety of massevents during real incidents in Poland.
Data-based approach for time-correlated closures of turbulence models

Authors:
raw_author_name: J. Domingues Lemos
raw_affiliation_string: Universidade Federal do Rio de Janeiro, Rua Antônio Barros de Castro, 119 Cidade Universitária, Rio de Janeiro, RJ 21941-853, Brazil
raw_author_name: A. A. Mailybaev
raw_affiliation_string: Instituto Nacional de Matematica Pura e Aplicada, Estrada Dona Castorina, 110 Jardim Botânico, Rio de Janeiro, RJ 22460-320, Brazil

Abstract: Developed turbulent motion of fluid still lacks an analytical description despite more than a century of active research. Nowadays, phenomenological ideas are widely used in practical applications, such as small-scale closures for numerical simulations of turbulent flows. In the present paper, we use a shell model of turbulence to construct a closure intended to have a solid theoretical background and to capture intrinsic probabilistic features of turbulence. Shell models of turbulence are dynamical deterministic systems used to model energy cascade and other key aspects of the Navier-Stokes such as intermittency. We rescale the variables of the Sabra model in a way which leads to hidden symmetries and universal distributions. We then use such fine distributions to write closures, i.e., missing expressions for some of the Sabra variables. Our closures rely on approximating probability density functions using a Gaussian mixture model, which makes them probabilistic by nature and allows us to write time-correlated closures. We also provide a framework where other machine learning tools can be employed with reduced black-box aspects.
Security issues of the gold industry chain based on smart blockchain in the context of the Internet of Things

Authors:
raw_author_name: Jifei Zheng
raw_affiliation_string: School of Earth Sciences and Resources, China University of Geosciences, Beijing, 100083, China
raw_author_name: Lei Chen
raw_affiliation_string: Shandong Geological Survey Institute, Jinan, 250013, China
raw_author_name: Xiao Li
raw_affiliation_string: Shandong Gold Group CO, LTD, Jinan, 250100, China
raw_author_name: Shouting Zhang
raw_affiliation_string: School of Earth Sciences and Resources, China University of Geosciences, Beijing, 100083, China

Abstract: Abstract The purpose is to solve the safety production and management problems of the gold Industrial Chain and give early warning of the safety situation of the gold Industrial Chain. According to the theory of industrial chain security governance and the basic situation of the gold Industrial Chain, this work establishes a gold Industrial Chain model based on smart blockchain and system dynamics (SD), and discusses the application of the gold Industrial Chain in the Internet of Things (IoT) environment. The overall goal of the application of IoT technology to the safety management of intelligent gold mines is to take the gold mine production demand as the driving force. The digitalization of production, electromechanical, safety, dispatching, and other information realizes intelligent digital perception, assists decision-making, guides the safety management of gold mining operations, continuously improves the operation efficiency of the gold mining industry, and drives the development of the industry. Finally, it takes the resource reserve of China’s gold industry from 2011 to 2021 as the research data introduces the weighting method to assess the security situation of China’s gold Industrial Chain from 2011 to 2021. The safety performance of China's environmental industry chain is evaluated through the detailed introduction of the basic information of the gold Industrial Chain. The result shows that the security situation of China’s gold Industrial Chain from 2011 to 2021 shows an overall growth trend, 88.42% higher than in 2014. The security situation of China’s gold Industrial Chain from 2011 to 2021 positively impacted the opening of the domestic gold market and entering the international gold market, improving the security level of China’s gold Industrial Chain. In this work, a gold Industrial Chain security model based on smart blockchain and SD is established to solve the safety problem of the gold Industrial Chain, which can improve the safety level of the gold industry and promote its sustainable development.
Covering Hierarchical Dirichlet Mixture Models on binary data to enhance genomic stratifications in onco-hematology

Authors:
raw_author_name: Daniele Dall’Olio
raw_affiliation_string: IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italia
raw_author_name: Amin T. Turki
raw_affiliation_string: Department of Hematology and Oncology, Marienhospital University Hospital, Ruhr-University Bochum, Bochum, Germany; Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany
raw_author_name: Claudia Sala
raw_affiliation_string: Department of Medical and Surgical Sciences—DIMEC, University of Bologna, Bologna, Italy
raw_author_name: Matteo G. Della Porta
raw_affiliation_string: Comprehensive Cancer Center, IRCCS Humanitas Clinical and Research Center and Department of Biomedical Sciences, Humanitas University, Milan, Italy
raw_author_name: Enrico Giampieri
raw_affiliation_string: Department of Medical and Surgical Sciences—DIMEC, University of Bologna, Bologna, Italy
raw_author_name: Gastone Castellani
raw_affiliation_string: Department of Medical and Surgical Sciences—DIMEC, University of Bologna, Bologna, Italy

Abstract: Onco-hematological studies are increasingly adopting statistical mixture models to support the advancement of the genomically-driven classification systems for blood cancer. Targeting enhanced patients stratification based on the sole role of molecular biology attracted much interest and contributes to bring personalized medicine closer to reality. In onco-hematology, Hierarchical Dirichlet Mixture Models (HDMM) have become one of the preferred method to cluster the genomics data, that include the presence or absence of gene mutations and cytogenetics anomalies, into components. This work unfolds the standard workflow used in onco-hematology to improve patient stratification and proposes alternative approaches to characterize the components and to assign patient to them, as they are crucial tasks usually supported by a priori clinical knowledge. We propose (a) to compute the parameters of the multinomial components of the HDMM or (b) to estimate the parameters of the HDMM components as if they were Multivariate Fisher’s Non-Central Hypergeometric (MFNCH) distributions. Then, our approach to perform patients assignments to the HDMM components is designed to essentially determine for each patient its most likely component. We show on simulated data that the patients assignment using the MFNCH-based approach can be superior, if not comparable, to using the multinomial-based approach. Lastly, we illustrate on real Acute Myeloid Leukemia data how the utilization of MFNCH-based approach emerges as a good trade-off between the rigorous multinomial-based characterization of the HDMM components and the common refinement of them based on a priori clinical knowledge.
Untouchable them: the effect of chatbot gender on angry customers

Authors:
raw_author_name: Min Zhang

Abstract: Purpose This study explores how chatbot gender and symbolic service recovery may improve the satisfaction of angry customers in the context of service failures. It provides a strategy for companies to deploy chatbots effectively in customer anger. Design/methodology/approach This research relies upon a systematic literature review to propose three hypotheses, and we recruit 826 participants to examine the effect of chatbot gender on angry customers through one lab study and one field study. Findings This research shows that female chatbots are more likely to increase the satisfaction of angry customers than male chatbots in service failure scenarios. In addition, symbolic recovery (apology vs. appreciation) moderates the effect of chatbot gender on angry customers. Specifically, male (vs. female) chatbots are more effective in increasing the satisfaction of angry customers when using the apology method, whereas female (vs. male) chatbots are more effective when using the appreciation method. Originality/value The rapid advancements in artificial intelligence technology have significantly enhanced the effectiveness of chatbots as virtual agents in the field of interactive marketing. Previous research has concluded that chatbots can reduce negative customer feedback following a service failure. However, these studies have primarily focused on the level of chatbot anthropomorphism and the design of conversational texts, rather than the gender of chatbots. Therefore, this study aims to bridge that gap by examining the effect of chatbot gender on customer feedback, specifically focusing on angry customers following service failures.
IHIBE: A Hierarchical and Delegated Access Control Mechanism for IoT Environments

Authors:
raw_author_name: Masahiro Mambo
raw_affiliation_string: Institute of Science and Engineering, Kanazawa University, Kanazawa 920-1192, Japan

Abstract: Ensuring authorized access control in the IoT is vital for privacy and safety protection. Our study presents the novel IHIBE framework, which combines IOTA (a distributed ledger technology) with hierarchical identity-based encryption (HIBE), thereby enhancing both IoT security and scalability. This approach secures access tokens and policies while reducing the computational demand on data owners. Our empirical findings reveal a significant performance gap, with access rights delegation on the Raspberry Pi 4 exceeding those on AWS by over 250%. Moreover, our analysis uncovers optimal identity policy depths: up to 640 identities on AWS and 640 on the Raspberry Pi 4 for systems with higher tolerable delays, and 320 identities on AWS versus 160 on the Raspberry Pi 4 for systems with lower tolerable delays. The system shows practical viability, exhibiting insignificant operational time differences compared to Zhang et al.’s schemes, particularly in access rights verification processes, with a minimal difference of 33.35%. Our extensive security assessment, encompassing scenarios like encrypted token theft and compromise of authority, affirms the efficacy of our challenge-response and last-word challenge (LWC) mechanisms. This study underscores the importance of platform choice in IoT system architectures and provides insights for deploying efficient, secure, and scalable IoT environments.
The effect of metaverse on L2 vocabulary learning, retention, student engagement, presence, and community feeling

Authors:
raw_author_name: Ferdi Çelik
raw_affiliation_string: Ondokuz Mayıs University, Samsun, Türkiye
raw_author_name: Meltem Huri Baturay
raw_affiliation_string: Konya Food and Agriculture University, Konya, Türkiye

Abstract: Abstract This study investigates the multifaceted impacts of Metaverse Based Language Teaching on high school L2 vocabulary learning and retention, engagement, community feeling, and diverse dimensions of presence, namely social, cognitive, teaching, and overall presence. Adopting a quasi-experimental design, the study provides an in-depth controlled trial. The participants in this study consist of 86 (43 male, 43 female) high school English language learners in Türkiye, who are assigned to two groups. The control group uses traditional instructional technologies while the experimental group engages with metaverse technology. The lessons are based on social constructivist theory for both groups. Pre- and post-tests are employed to quantitatively assess vocabulary learning and retention and reveal substantial improvements in both areas. A series of carefully selected psychometric scales capture core aspects of engagement, community feeling, and presence. The findings reveal increased levels of engagement and a sense of presence, and connectedness within the language learning community, which confirms the efficacy of the MBLT. However, the improvement in social presence does not reach statistical significance. Cumulatively, the findings of this research transcend mere quantifiable improvements in vocabulary learning and retention. They reveal a holistic transformation of the language learning experience by emphasizing the significance of social interactions and digital embodiment in high school second language education through metaverse. The research highlights the metaverse’s potential in shaping the future of language education, reimagining traditional paradigms, and proposing a new era of immersive, interactive, and transformative pedagogy.
Content Based Recommendation System on Netflix Data

Authors:
raw_author_name: Dr. Deepti Sharma
raw_affiliation_string: Professor, Department of Information Technology, JIMS, Sec-5, Rohini, Delhi, India.
raw_author_name: Dr. Deepshikha Aggarwal
raw_affiliation_string: Professor, Department of Information Technology, JIMS, Sec-5, Rohini, Delhi, India.
raw_author_name: Dr. Archana B. Saxena
raw_affiliation_string: Professor, Department of Information Technology, JIMS, Sec-5, Rohini, Delhi, India.

Abstract: After pandemic, OTT platforms are the most common platform to provide entertainment to users. Among all platforms, Netflix has become most the popular one. Data visualization of Netflix data can provide valuable insights and benefits in many ways like understanding viewer preferences, content optimization, personalized recommendation, quality and content performance evaluation, fraud detection to name a few. This research provides exploratory data visualization and provide a content based recommendation system on Netflix data as in real world applications, company uses these recommendation system algorithms to determine which system are better to improve users’ engagement of the platform.
Vigilance in infectious disease emergencies: Expanding the concept

Authors:
raw_author_name: Christopher Mayes
raw_affiliation_string: School of Humanities and Social Science, Deakin University, Australia
raw_author_name: Chris Degeling
raw_affiliation_string: Australian Centre for Health Engagement, Evidence and Values (ACHEEV), School of Health and Society, University of Wollongong, Australia

Abstract: In their 2010 book, Lorna Weir and Eric Mykhalovskiy conceptualised the role of vigilance in unknown and emerging infectious disease threats. Theirs is a macro-level account which draws on empirical data to describe vigilance as a set of technical and political arrangements that govern collection, analysis, interpretation and communication of data as it pertains to unknown threats. In this paper we expand their work to detail a conceptual analysis of the role of vigilance at the micro-level during periods of high infectious disease threat. Our data are daily press conferences and associated non-discursive tools in New South Wales (NSW), Australia during times of heightened COVID-19 risk. This paper is a conceptual analysis that draws on theories of vigilance and related concepts to show how a key aspect of vigilance is making previously unseen threats visible or present. Communications formulated and encouraged three types of vigilance as a set of governing relations: institutional or authority-based; individual outward-facing; and individual inward-facing. We also describe the relationship between vigilance and related concepts that are used in response to anticipated public threats. Authority based vigilance involved contact tracing and policing of movement and behaviours. In individual outward facing vigilance people were asked to be alert to, analyse, and react to risk in their immediate environment. Inward facing vigilance required people to gather and react to information about their own behaviours and within their own bodies. There was a relationship between different types of vigilance; as risk increased and authority-based vigilance was less successful in containing the spread of infection, individual vigilance had a stronger role to play. This extension of vigilance at the micro-level sees some of the same unintended consequences as Weir and Mykhalovskiy describe at the global level, particularly in how burdens are inequitably distributed and experienced.
Immersive Realities: A Comprehensive Guide from Virtual Reality to Metaverse

Authors:
raw_author_name: Preet Kawal Singh DHILLON
raw_affiliation_string: Woosong University
raw_author_name: Hasan TINMAZ
raw_affiliation_string: Woosong University

Abstract: This comprehensive literature review explores the diverse landscape of immersive realities, offering a thorough examination of key technologies from Virtual Reality (VR) to the emerging and innovative concept of the Metaverse. The article concentrates the nuances of Extended Reality (XR), Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), providing an in-depth understanding of their individual functionalities, applications, and evolving interplay. The paper also mentions about wearable technologies which play key role in the realization of these immersive realities. The article begins by explaining the fundamental principles of each immersive reality, tracing their technological evolution and highlighting distinctive features that define their user experiences. It then navigates through the complex intersections and synergies between these immersive technologies, shedding light on how they collectively contribute to shaping the future of digital interaction. The paper unfolds how the journey of immersive realities lead to the Metaverse which is relatively a novel paradigm that transcends individual immersive realities, creating a unified, interconnected digital space. The exploration of the Metaverse encompasses its conceptual foundations, potential societal impacts, and the fusion of various immersive technologies within this evolving ecosystem. With an inclusive approach, this paper caters to both novices and seasoned professionals in the field, offering insights into the practical applications associated with different immersive realities. By fostering a comprehensive understanding of these technologies, the paper aims to empower readers to navigate and contribute to the dynamic landscape of immersive realities.