Reviewerly/exHarmony huggingface dataset:
Quasi-Dense Matching for Oblique Stereo Images through Semantic Segmentation and Local Feature Enhancement

Authors:
raw_author_name: Guobiao Yao
raw_affiliation_string: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430070, China; School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China
raw_author_name: Jin Zhang
raw_affiliation_string: School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China
raw_author_name: Jianya Gong
raw_affiliation_string: School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430070, China
raw_author_name: Fengxiang Jin
raw_affiliation_string: College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
raw_author_name: Qingqing Fu
raw_affiliation_string: School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan 250101, China

Abstract: This paper proposes a quasi-dense feature matching algorithm that combines image semantic segmentation and local feature enhancement networks to address the problem of the poor matching of image features because of complex distortions, considerable occlusions, and a lack of texture on large oblique stereo images. First, a small amount of typical complex scene data are used to train the VGG16-UNet, followed by completing the semantic segmentation of multiplanar scenes across large oblique images. Subsequently, the prediction results of the segmentation are subjected to local adaptive optimization to obtain high-precision semantic segmentation results for each planar scene. Afterward, the LoFTR (Local Feature Matching with Transformers) strategy is used for scene matching, enabling enhanced matching for regions with poor local texture in the corresponding planes. The proposed method was tested on low-altitude large baseline stereo images of complex scenes and compared with five classical matching methods. Results reveal that the proposed method exhibits considerable advantages in terms of the number of correct matches, correct rate of matches, matching accuracy, and spatial distribution of corresponding points. Moreover, it is well-suitable for quasi-dense matching tasks of large baseline stereo images in complex scenes with considerable viewpoint variations.
Extended Reality as an Educational Resource in the Primary School Classroom: An Interview of Drawbacks and Opportunities

Authors:
raw_author_name: José María Fernández-Batanero
raw_affiliation_string: Department of Teaching and Educational Organization, University of Sevilla, 41013 Sevilla, Spain
raw_author_name: Marta Montenegro-Rueda
raw_affiliation_string: Department of Teaching and Educational Organization, University of Sevilla, 41013 Sevilla, Spain
raw_author_name: José Fernández-Cerero
raw_affiliation_string: Department of Teaching and Educational Organization, University of Sevilla, 41013 Sevilla, Spain
raw_author_name: Eloy López-Meneses
raw_affiliation_string: Department of Education and Social Psychology, Pablo de Olavide University, 41013 Sevilla, Spain

Abstract: The use of Extended Reality in Primary Education classrooms has emerged as a transformative element that enhances the teaching and learning process of students. In this context, examining the various effects that this tool can generate is essential to identify both the opportunities and limitations that teachers face when incorporating this technology into their practices. The aim of this research is to analyse the impact of the use of Extended Reality as an educational resource in Primary Education, focusing on teachers’ perceptions. The information was collected through semi-structured interviews with 36 active teachers in Primary Education. The analysis of the data obtained identifies the benefits and functionalities offered by the implementation of Extended Reality in Primary Education classrooms, as well as the uncertainties and concerns that teachers have with the implementation of Extended Reality. The results highlight the significant opportunities that Extended Reality offers in the teaching–learning process, provided that teachers are adequately trained. Furthermore, this study offers valuable recommendations to guide future teachers and researchers in the successful integration of this technology into the educational process.
Rainfall's Symphony: Understanding its Influence on Communication Systems in Nigeria

Authors:
raw_author_name: Obiseye Obiyemi
raw_author_name: Katleho Moloi

Abstract: This study investigates the significant issue of rain-induced signal attenuation in satellite communication, specifically focusing on television receive-only (TVRO) stations operating in the Ku band across diverse Nigerian locations. Utilizing a comprehensive dataset of point rain rate distribution and the ITU rain attenuation model, the study comprehensively assesses how rainfall impacts signal quality. The findings highlight that southern regions consistently display high decibel (dB) values, indicating increased susceptibility to signal disruptions during heavy rainfall, while a comparative analysis between two key satellites, EUTELSAT 36B and INTELSAT 20, consistently favors the former in terms of signal resilience during adverse weather conditions. In contrast, northern regions generally exhibit lower dB values, suggesting a higher degree of signal resilience during rainfall events. These insights underscore the importance of considering location-specific and satellite-specific factors when designing satellite communication systems, emphasizing the need for robust infrastructure and strategic satellite selection to mitigate the effects of rain-induced attenuation. This study provides valuable guidance to engineers and service providers, enabling them to make informed decisions to minimize signal disruptions and enhance overall network reliability, particularly in regions susceptible to rain-induced attenuation.
Paintings in naked-eye virtual reality: a parallax view between the surface and volumetric depth

Authors:
raw_author_name: Yiwen Wang
raw_affiliation_string: School of English for Specific Purposes, Beijing Foreign Studies University, Beijing, China
raw_author_name: Huiyu Zhang
raw_affiliation_string: School of Journalism and Communication, Peking University, Beijing, China

Abstract: Abstract This article explores a subgenre of naked-eye virtual reality (VR) video that features two-dimensional paintings in a three-dimensional space and is circulated on the Chinese video streaming website Bilibili. In contrast to traditional VR, which requires the spectator to wear a head-mounted display, naked-eye VR offers a stereoscopic view on the screen, eliminating the need for VR glasses. The apparent incongruity between the screen’s physical flatness and the volumetric depth of the painting becomes even more pronounced when the naked-eye VR image emphasises the painting’s inherent two-dimensionality. Employing an interdisciplinary humanities’ method that connects media archaeology, film studies, art history, and the field of science, technology, and society, this paper delves into this distinctive juxtaposition between the painting’s flatness and the volumetric depth characteristic of naked-eye VR, a subgenre that remains mostly uncharted in the field of film and media studies. Taking a media archaeological perspective, this paper introduces a parallax media history, suggesting that the aesthetics of VR can be traced not only to the stereoscope but also to scroll paintings, which are paradoxically defined by their flat compositions. In addition, naked-eye VR references pictorial traditions by generating a spatial illusion that leads spectators to feel as if they are delving beneath the surface of a painting, transitioning from spatial extensivity on the x-y axis to perceived depth along the z-axis. This oscillation between surface and depth is engendered by the horizontal parallax rooted in binocular disparity, thereby positioning naked-eye VR as a “parallax media.” In analysing the illusion created by naked-eye VR, this paper proposes a paradigmatic shift in the framework of media study from conceiving of an image as a mirror to experiencing it as a door, representing the oscillation between volumetric depth and two-dimensional surface.
The visual content of neural networks as a return to the third-order simulacrum

Authors:
raw_author_name: Aleksandra Vladimirovna Pankratova

Abstract: This article is part of a larger study of design as a cultural phenomenon. In this part of the study, the author examines the process that is currently taking place in the semiotic structure of design, associated with the active introduction of neural networks into the creation of visual content. Artificial intelligence products stylistically take the design away from the fourth-order simulacrum (from the flat design style) and return the design to using the third-order simulacrum as the main iconic form.The object of the research is the transformation of the semiotic design system. The subject of the study is a return to the third–order simulacrum in modern design. The purpose of the study is to show and try to explain how in modern design there is a return to the use of a third-order simulacrum. The research method is a semiotic analysis of modern design based on the methodology of R. Barth's semiotic analysis. The study is also based on J. Baudrillard's theory of semiosis in hyperreality and three orders of simulacra. The author sees the philosophical justification of the art of neural networks in the concept of flat ontologies. The study of the semiotic structure of design allows us to see that the logic of design development carries this phenomenon through successive stages of semiosis associated with a decrease in meaning and a diminution of being. In its development, the design consistently uses first index signs, a second-order simulacrum, then a third-order simulacrum as the main sign form. Nowadays, the main iconic form in design has become a fourth-order simulacrum. Next, design had to either end as a profession and phenomenon, or move into a new cultural paradigm that was not related to simulation. However, unexpected transformations have begun to occur in design, due to the active involvement of non–human agents - neural networks – in the creation of visual content. Neural network products are a typical example of a third-order simulacrum. Thanks to the use of neural networks, modern design finally acquires the vector of transhumanism and closes in simulation.
IFE-net: improved feature enhancement network for weak feature target recognition in autonomous underwater vehicles

Authors:
raw_author_name: Lei Cai
raw_affiliation_string: School of Artificial Intelligence, Henan Institute of Science and Technology, Xinxiang, PR China
raw_author_name: Yuejun Li
raw_affiliation_string: School of Information Engineering, Henan Institute of Science and Technology, Xinxiang, PR China
raw_author_name: Haojie Chai
raw_affiliation_string: School of Artificial Intelligence, Henan Institute of Science and Technology, Xinxiang, PR China

Abstract: Abstract The recognizing underwater targets is a crucial component of autonomous underwater vehicle patrols and detection efforts. In the process of visual image recognition in real underwater environment, the spatial and semantic features of the target often appear to different degrees of loss, and the scarcity of specific types of underwater samples leads to unbalanced data on categories. This kind of problem makes the target features appear weak and seriously affects the accuracy of underwater target recognition. Traditional deep learning methods based on data and feature enhancement cannot achieve ideal recognition effect. Based on the above difficulties, this paper proposes an improved feature enhancement network for weak feature target recognition. Firstly, a multi-scale spatial and semantic feature enhancement module is constructed to extract the feature information of the extraction target accurately. Secondly, this paper solves the influence of target feature distortion on classification through multi-scale feature comparison of positive and negative samples. Finally, the Rank &amp; Sort Loss function was used to train the depth target detection to solve the problem of recognition accuracy under highly unbalanced sample data. Experimental results show that the recognition accuracy of the proposed method is 2.28% and 3.84% higher than that of the existing algorithms in the recognition of underwater fuzzy and distorted target images, which demonstrates the effectiveness and superiority of the proposed method.
Genre: generative multi-turn question answering with contrastive learning for entity–relation extraction

Authors:
raw_author_name: Lulu Wang
raw_affiliation_string: School of Computer Science and Technology, Xinjiang University, Urumqi, 830046, China
raw_author_name: Kai Yu
raw_affiliation_string: School of Information Science and Engineering, Yanshan University, Qinhuangdao, 066004, China
raw_author_name: Aishan Wumaier
raw_affiliation_string: School of Computer Science and Technology, Xinjiang University, Urumqi, 830046, China
raw_author_name: Peng Zhang
raw_affiliation_string: Beijing Zhipu Huazhang Technology Co., Ltd., Beijing, 100084, China
raw_author_name: Tuergen Yibulayin
raw_affiliation_string: Xinjiang Laboratory of Multi-Language Information Technology, Xinjiang University, Urumqi, 830046, China
raw_author_name: Xi Wu
raw_affiliation_string: School of Information Science and Engineering, Yanshan University, Qinhuangdao, 066004, China
raw_author_name: Jibing Gong
raw_affiliation_string: School of Information Science and Engineering, Yanshan University, Qinhuangdao, 066004, China
raw_author_name: Maihemuti Maimaiti
raw_affiliation_string: Xinjiang Laboratory of Multi-Language Information Technology, Xinjiang University, Urumqi, 830046, China

Abstract: Abstract Extractive approaches have been the mainstream paradigm for identifying overlapping entity–relation extraction. However, limited by their inherently methodological flaws, which hardly deal with three issues: hierarchical dependent entity–relations, implicit entity–relations, and entity normalization. Recent advances have proposed an effective solution based on generative language models, which cast entity–relation extraction as a sequence-to-sequence text generation task. Inspired by the observation that humans learn by getting to the bottom of things, we propose a novel framework, namely GenRE, Generative multi-turn question answering with contrastive learning for entity–relation extraction. Specifically, a template-based question prompt generation first is designed to answer in different turns. We then formulate entity–relation extraction as a generative question answering task based on the general language model instead of span-based machine reading comprehension. Meanwhile, the contrastive learning strategy in fine-tuning is introduced to add negative samples to mitigate the exposure bias inherent in generative models. Our extensive experiments demonstrate that GenRE performs competitively on two public datasets and a custom dataset, highlighting its superiority in entity normalization and implicit entity–relation extraction. (The code is available at https://github.com/lovelyllwang/GenRE ).
Analysis of Coordination Mechanisms during Collaborative Problem-Solving on an Interactive Tabletop Display

Authors:
raw_author_name: Valérie Maquil
raw_affiliation_string: Luxembourg Institute of Science and Technology, 5 Avenue des Hauts-Fourneaux, 4362, Esch-sur-Alzette, Luxembourg
raw_author_name: Hoorieh Afkari
raw_affiliation_string: University of Luxembourg, Porte Des Sciences 11, 4366, Esch-sur-Alzette, Luxembourg
raw_author_name: Béatrice Arend
raw_affiliation_string: University of Luxembourg, Porte Des Sciences 11, 4366, Esch-sur-Alzette, Luxembourg
raw_author_name: Svenja Heuser
raw_affiliation_string: University of Luxembourg, Porte Des Sciences 11, 4366, Esch-sur-Alzette, Luxembourg
raw_author_name: Patrick Sunnen
raw_affiliation_string: University of Luxembourg, Porte Des Sciences 11, 4366, Esch-sur-Alzette, Luxembourg

Abstract: Abstract Coordination is an important aspect of group work. Previous studies have shown how collocated multi-user interfaces, such as interactive tabletops, support coordination by providing a shared space that enhances workspace awareness. However, only little is known about the coordination processes that occur during problem-solving on such shared devices and how the design of features and interaction techniques can impact coordination behaviour. In this paper we analyse users’ coordination mechanisms during joint manipulation tasks in Orbitia, an interactive tabletop-based problem-solving activity. The proposed design integrates a series of “breaches” seeking to challenge participants’ collaboration by confronting them to different limitations. We report on a case study with five groups of three users ( N = 15), jointly solving tasks while facing different challenges related to the activity interface and the environment. By analysing 135 min of video material along with their transcripts, we identified nine different coordination mechanisms that relate to either coordination of information or coordination of actions. By exploring the occurrences of these mechanisms, we found that sharing unsolicited task-relevant information is a common coordination behaviour that can be observed at interactive tabletops, and that with breaches, more explicit coordination in the form of direct requests, orders, or shadowing is used.
A novel Cosine-Cosine chaotic map-based video encryption scheme

Authors:
raw_author_name: Sweta Kumari
raw_affiliation_string: Department of Computer Engineering, National Institute of Technology, Kurukshetra, India
raw_author_name: Mohit Dua
raw_affiliation_string: Department of Computer Engineering, National Institute of Technology, Kurukshetra, India
raw_author_name: Shelza Dua
raw_affiliation_string: Department of Electronics and Communication Engineering, National Institute of Technology, Kurukshetra, India
raw_author_name: Deepti Dhingra
raw_affiliation_string: Department of Computer Engineering, National Institute of Technology, Kurukshetra, India

Abstract: Abstract The surge in online activities has led to the increasing popularity of sharing video data across diverse applications, including online education tutorials, social networking, video calling, and OTT platforms. Encryption prevents unauthorized access to the transmitted data over unreliable channels. The well-known features of chaos theory such as random behaviour, unpredictability, and initial parameters dependency facilitate its use in cryptography. Many security issues are faced by chaos-based cryptosystems because of their less complexity. Hence, a new Cosine-Cosine chaotic map characterized by intricate chaotic behaviour is designed in the current study. Additionally, we formulate an original video encryption scheme employing this Cosine-Cosine chaotic map. The encryption process involves five steps, beginning with the segmentation of the original video into frames based on its frame rate. In the second phase, a 384 bits pseudorandom key is generated that is further divided into three subkeys of 128 bits each. The novel Cosine-Cosine chaotic map-based sequence is generated. In the fourth step, red, green, and blue components are encrypted using the pseudorandom key and the chaotic sequence. In the last step, we combine encrypted frames to get cipher video. The security analysis validates that the proposed encryption protects against eavesdropping.
The Serbian Sign Language Alphabet: A Unique Authentic Dataset of Letter Sign Gestures

Authors:
raw_author_name: Mladen Radaković
raw_affiliation_string: Information Technology School—ITS, 11000 Belgrade, Serbia
raw_author_name: Marina Marjanović
raw_affiliation_string: Faculty of Technical Sciences, Singidunum University, 11000 Belgrade, Serbia
raw_author_name: Valentin Kuleto
raw_affiliation_string: Information Technology School—ITS, 11000 Belgrade, Serbia
raw_author_name: Milena P. Ilić
raw_affiliation_string: Information Technology School ITS—Belgrade, LINK Group Belgrade, Faculty of Contemporary Arts Belgrade, University Business Academy in Novi Sad, 11000 Belgrade, Serbia

Abstract: Language barriers and the communication difficulties of individuals with developmental disabilities are two major causes of communication problems that societies worldwide encounter. A particularly challenging group is hearing-impaired people who have difficulties with communication, reading, writing, learning, and social interactions, which have a substantial impact on their quality of life. This article focuses on detailing a Serbian Sign Language alphabet database and the method for creating it in order to provide a foundation for answering the various societal challenges of persons who use the Serbian language. In front of a computer camera, 41 people performed Serbian Sign Language sign movements that replicated the Serbian alphabet for this study’s aims. Hand and body key points were identified using the recorded video clips, and the numerical values of the identified key points were then stored in a database for further processing. In total, 8.346 video clips of people making recognized hand gestures were gathered, processed, classed, and archived. This paper provides a thorough technique that may be applied to comparable tasks and details the process of constructing a dataset based on Serbian Sign Language alphabet signs. This dataset was created using custom-made Python 3.11 software. Data regarding dynamic video clips that capture entire subject movement were incorporated into this dataset to fill in the gaps in other similar efforts based on static photographs. Thus, the purpose of this investigation is to employ innovative technology to support the community of hearing-impaired people in areas such as general inclusion, education, communication, and empowerment.
Modern Trends in Multi-Agent Systems

Authors:
raw_author_name: Ivana Budinská
raw_affiliation_string: Institute of Informatics, Slovak Academy of Sciences, 845 07 Bratislava, Slovakia
raw_author_name: Ladislav Hluchý
raw_affiliation_string: Institute of Informatics, Slovak Academy of Sciences, 845 07 Bratislava, Slovakia
raw_author_name: Agostino Poggi
raw_affiliation_string: Department of Engineering and Architecture, University of Parma, 43124 Parma, Italy

Abstract: The term “multi-agent system” is generally understood as an interconnected set of independent entities that can effectively solve complex and time-consuming problems exceeding the individual abilities of common problem solvers [...]
Removing Coding and Inter Pixel Redundancy in Image Compression

Authors:
raw_author_name: Anitha S
raw_affiliation_string: Govindammal Aditanar College for Women
raw_author_name: Kavitha J
raw_affiliation_string: Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology

Abstract: The digital image plays an important role in today’s digital world. Storing and transmitting digital images efficiently is a challenging job. There are lots of techniques for reducing the size of digital pictures. This paper adapts the following method. The digital technique is separated into high and low resolutions. The low intensity and high intensity pixels single-handedly is dense and decompressed using three diverse algorithms to hit upon out the occurrence of low down intensity pixels in the picture. Totally six algorithms are experienced by means of benchmark images and the most excellent scheme is selected for concluding compression. A Comparison is made between the results obtained using these techniques and those obtained using JPEG 2000.