Reviewerly/exHarmony huggingface dataset:
Lossless data hiding technique reducing cover data size for compressed videos

Authors:
raw_author_name: Xuefei Li
raw_affiliation_string: Hokkaido University, Faculty of Information Science and Technology, Media Creation Methodology Laboratory, Sapporo, Japan (Japan)
raw_author_name: Seok Kang
raw_affiliation_string: Hokkaido University, Faculty of Information Science and Technology, Media Creation Methodology Laboratory, Sapporo, Japan (Japan)
raw_author_name: Yuji Sakamoto
raw_affiliation_string: Hokkaido University, Faculty of Information Science and Technology, Media Creation Methodology Laboratory, Sapporo, Japan (Japan)

Abstract: In recent years, multimedia techniques have rapidly advanced. Video discs with massive storage capacities exemplify widely used multimedia storage mediums. However, online multimedia services face strict storage limits, and compression rates impact streaming quality. This poses a dilemma—data hiding risks exceeding storage limits and affecting the quality of video streams. To address this, we propose a lossless data hiding technique focusing on cover data size. The technique embeds new data into compressed cover video data, decreasing data size post-embedding. Extraction requires no key. In addition, the processing time is short enough that the technique can be used in real-time applications. We verified the technique through experiments with MPEG-2 videos. Video data size decreased after hiding data, and quality degradation remained acceptable. Results confirm the technique's efficacy.
KDP-Net: An Efficient Semantic Segmentation Network for Emergency Landing of Unmanned Aerial Vehicles

Authors:
raw_author_name: Zhiqi Zhang
raw_affiliation_string: School of Computer Science, Hubei University of Technology, Wuhan 430068, China; State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
raw_author_name: Shao Xiang
raw_affiliation_string: State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
raw_author_name: Lu Wei
raw_affiliation_string: School of Information Science and Engineering, Wuchang Shouyi University, Wuhan 430064, China

Abstract: As the application of UAVs becomes more and more widespread, accidents such as accidental injuries to personnel, property damage, and loss and destruction of UAVs due to accidental UAV crashes also occur in daily use scenarios. To reduce the occurrence of such accidents, UAVs need to have the ability to autonomously choose a safe area to land in an accidental situation, and the key lies in realizing on-board real-time semantic segmentation processing. In this paper, we propose an efficient semantic segmentation method called KDP-Net for characteristics such as large feature scale changes and high real-time processing requirements during the emergency landing process. The proposed KDP module can effectively improve the accuracy and performance of the semantic segmentation backbone network; the proposed Bilateral Segmentation Network improves the extraction accuracy and processing speed of important feature categories in the training phase; and the proposed edge extraction module improves the classification accuracy of fine features. The experimental results on the UDD6 and SDD show that the processing speed of this method reaches 85.25 fps and 108.11 fps while the mIoU reaches 76.9% and 67.14%, respectively. The processing speed reaches 53.72 fps and 38.79 fps when measured on Jetson Orin, which can meet the requirements of airborne real-time segmentation for emergency landing.
Twitter’s pulse on hydrogen energy in 280 characters: a data perspective

Authors:
raw_author_name: Deepak Uniyal
raw_affiliation_string: Centre for Data Science, School of Computer Science, Queensland University of Technology, Brisbane, QLD, Australia
raw_author_name: Richi Nayak
raw_affiliation_string: Centre for Data Science, School of Computer Science, Queensland University of Technology, Brisbane, QLD, Australia

Abstract: Abstract Uncovering the public discourse on hydrogen energy is essential for understanding public behaviour and the evolving nature of conversations over time and across different regions. This paper presents a comprehensive analysis of a large multilingual dataset pertaining to hydrogen energy collected from Twitter spanning a decade (2013–2022) using selected keywords. The analysis aims to explore various aspects, including the temporal and spatial dimensions of the discourse, factors influencing Twitter engagement, user engagement patterns, and the interpretation of conversations through hashtags and ngrams. By delving into these aspects, this study offers valuable insights into the dynamics of public discourse surrounding hydrogen energy and the perceptions of social media users.
TSE-GAN: strain elastography using generative adversarial network for thyroid disease diagnosis

Authors:
raw_author_name: Anping Song
raw_affiliation_string: School of Computer Engineering and Science, Shanghai University, Shanghai, China
raw_author_name: Xuehai Ding
raw_affiliation_string: School of Computer Engineering and Science, Shanghai University, Shanghai, China
raw_author_name: Ren Wang
raw_affiliation_string: Department of Ultrasound Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China

Abstract: Over the past 35 years, studies conducted worldwide have revealed a threefold increase in the incidence of thyroid cancer. Strain elastography is a new imaging technique to identify benign and malignant thyroid nodules due to its sensitivity to tissue stiffness. However, there are certain limitations of this technique, particularly in terms of standardization of the compression process, evaluation of results and several assumptions used in commercial strain elastography modes for the purpose of simplifying imaging analysis. In this work, we propose a novel conditional generative adversarial network (TSE-GAN) for automatically generating thyroid strain elastograms, which adopts a global-to-local architecture to improve the ability of extracting multi-scale features and develops an adaptive deformable U-net structure in the sub-generator to apply effective deformation. Furthermore, we introduce a Lab-based loss function to induce the networks to generate realistic thyroid elastograms that conform to the probability distribution of the target domain. Qualitative and quantitative assessments are conducted on a clinical dataset provided by Shanghai Sixth People’s Hospital. Experimental results demonstrate that thyroid elastograms generated by the proposed TSE-GAN outperform state-of-the-art image translation methods in meeting the needs of clinical diagnostic applications and providing practical value.
Modified Playfair for Text File Encryption and Meticulous Decryption with Arbitrary Fillers by Septenary Quadrate Pattern

Authors:
raw_author_name: S. Kumarganesh
raw_affiliation_string: Department of ECE, Knowledge Institute of Technology, Salem, Tamil Nadu, India
raw_author_name: C. Venkatesan
raw_affiliation_string: Department of ECE, Dr. Mahalingam College of Engineering and Technology, Coimbatore, Tamil Nadu, India
raw_author_name: K. Martin Sagayam
raw_affiliation_string: Department of ECE, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India
raw_author_name: Hien Dang
raw_affiliation_string: Department of Mathematics and Computer Science, Molloy University, Rockville Centre, NY, USA

Abstract: Abstract Cryptography secures data and serves to ensure the confidentiality of records. Playfair is a cryptographic symmetrical algorithm that encrypts statistics based on key costs. This secret is shared with an authorized person to retrieve data. In the conventional pattern, there is an area complexity and deficiency in letters, numbers, and special characters. This hassle has been overcome in previous studies by editing pattern dimensions. The fillers used throughout the enciphering were not eliminated during the retrieval process, which resulted in the indiscrimination of the retrieved statistics. The proposed method uses a separate quadrate pattern that strengthens the Playfair cipher and guarantees that the fillers are eliminated to ensure the authentic retrieval of records. The fillers indiscriminate and strengthen the set of rules in opposition to brute force and avalanche impact. The proposed algorithm was evaluated with a minimal change in the key, and was found to have an avalanche effect between 65% and 93.7%. The encrypted document is further encoded using the Lempel–Ziv–Markov chain algorithm (LZMA) to provide compressed second-level secured text with a compression ratio of 0.75 for a file size of 100 KB. The pattern was designed to subsidize the integrated characters found on the keyboard.
Being on the inside: a research methodology for data collection within the inner circle of the domain of video game translation/localization in Thailand

Authors:
raw_author_name: Koraya Techawongstien
raw_affiliation_string: Research Institute for Languages and Cultures of Asia, Mahidol University, Nakhon Pathom, Thailand

Abstract: Purpose The Thai video game domain has witnessed substantial growth in recent years. However, many games enjoyed by Thai players are in foreign languages, with only a handful of titles translated/localized into the Thai locale. Some Thai video game enthusiasts have taken on the role of unofficial translators/localizers, contributing to a localization domain that accommodates both official and unofficial translation/localization efforts. This general review paper aims to outline the author's experiences in collecting data within the domain of video game translation/localization in Thailand. Design/methodology/approach Using a descriptive approach, this general review paper employs the netnography method. It sheds light on the complexities of video game translation/localization in Thailand and incorporates semi-structured interviews with a snowball sampling technique for the selection of participants and in-game data collection methods. Findings The netnography method has proved instrumental in navigating the intricacies of this evolving landscape. Adopting the netnography method for data collection in this research contributes to establishing more robust connections with the research sites. “Inside” professionals and individuals play a significant role in data gathering by recommending additional sources of information for the research. Originality/value While netnography is conventionally applied in the market and consumer research, this paper demonstrates its efficacy in unraveling the dynamics of video game translation/localization in Thailand.
Impact factor analysis affecting the operation of asset lifecycle by using asset information modeling and blockchain technology

Authors:
raw_author_name: Azzam Raslan
raw_affiliation_string: Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China
raw_author_name: Ali Cheshmehzangi
raw_affiliation_string: Department of Architecture and Built Environment, University of Nottingham Ningbo China, Ningbo, China
raw_author_name: Dave Towey
raw_affiliation_string: School of Computer Science, University of Nottingham Ningbo China, Ningbo, China
raw_author_name: Walid Tizani
raw_affiliation_string: Department of Civil Engineering, University of Nottingham, Nottingham, UK
raw_author_name: Georgios Kapogiannis

Abstract: Purpose Currently, owners find it difficult to manage their assets throughout their project life cycle. The fact that asset information models (AIMs) are mandatory as deliverables for building information modeling-driven projects makes it a key requirement for the client to understand in detail those factors affecting asset operation. Hence, because the Kingdom of Saudi Arabia is the most significant market in the Middle East, this study aims to investigate those factors where blockchain and AIMs could impact the asset management (AM) life cycle. Design/methodology/approach Researchers used a hypothesis-based approach over a systematic literature review and a workshop (descriptive statistics) to understand the current challenges in AM. Later, a second workshop was run to understand the impact factor analysis affecting the operation of the asset life cycle by using asset information modeling and blockchain technology over a multiquantitative method. Findings Results found that factors affecting the operation of assets could be the improvement of trust and stakeholder’s influences; the availability of handover process products’ accurate data; manufacturers providing detailed product models; increasing the speed of preparing holistic and integrated AM systems; improving collaboration between stakeholders; and returning clients’ investments faster. Originality/value Understanding the factors affecting AM life cycle based on the utilization of AIMs and blockchain then allows investors and their team members to work in a secure and collaborative environment that helps them to pre-identify certain risks and improve decision-making in a more effective way, as is required by ISO55000.
Enhanced Security in Public Key Cryptography: A Novel Approach Combining Gaussian Graceful Labeling and NTRU Public Key Cryptosystem

Authors:
raw_author_name: S Kavitha
raw_affiliation_string: Vels University
raw_author_name: K Sivaranjani
raw_affiliation_string: Sri Eshwar College of Engineering

Abstract: This research explores an encryption system that combines the Nth-degree Truncated Polynomial Ring Unit (NTRU) public key cryptosystem with Gaussian Graceful Labeling. This process assigns distinct labels to a graph's vertices, resulting in successive Gaussian integers. The NTRU method offers enhanced security and efficient key exchange. The communication encryption process depends on integers P, a, and b, with P being the largest prime number in the vertex labeling. The original receivers are the vertex labeling with the largest prime number coefficient, while all other receivers receive messages from the sender. A polynomial algebraic mixing system and a clustering principle based on the abecedarian probability proposition are used in NTRU encryption and decryption. The choice of relatively prime integers p and q in NTRU plays a role in the construction of polynomial rings used for encryption and decryption, with specific choices and properties designed to ensure scheme security.
How body postures affect gaze control in scene viewing under specific task conditions

Authors:
raw_author_name: Daniel Backhaus
raw_affiliation_string: Department of Psychology, University of Potsdam, Karl-Liebknecht-Str. 24-25, Potsdam, 14476, Germany
raw_author_name: Ralf Engbert
raw_affiliation_string: Department of Psychology, University of Potsdam, Karl-Liebknecht-Str. 24-25, Potsdam, 14476, Germany

Abstract: Gaze movements during visual exploration of natural scenes are typically investigated with the static picture viewing paradigm in the laboratory. While this paradigm is attractive for its highly controlled conditions, limitations in the generalizability of the resulting findings to more natural viewing behavior have been raised frequently. Here, we address the combined influences of body posture and viewing task on gaze behavior with the static picture viewing paradigm under free viewing as a baseline condition. We recorded gaze data using mobile eye tracking during postural manipulations in scene viewing. Specifically, in Experiment 1, we compared gaze behavior during head-supported sitting and quiet standing under two task conditions. We found that task affects temporal and spatial gaze parameters, while posture produces no effects on temporal and small effects on spatial parameters. In Experiment 2, we further investigated body posture by introducing four conditions (sitting with chin rest, head-free sitting, quiet standing, standing on an unstable platform). Again, we found no effects on temporal and small effects on spatial gaze parameters. In our experiments, gaze behavior is largely unaffected by body posture, while task conditions readily produce effects. We conclude that results from static picture viewing may allow predictions of gaze statistics under more natural viewing conditions, however, viewing tasks should be chosen carefully because of their potential effects on gaze characteristics.
Semantic search as extractive paraphrase span detection

Authors:
raw_author_name: Jenna Kanerva
raw_affiliation_string: TurkuNLP, Department of Computing, University of Turku, Turku, Finland
raw_author_name: Li-Hsin Chang
raw_affiliation_string: TurkuNLP, Department of Computing, University of Turku, Turku, Finland
raw_author_name: Teemu Vahtola
raw_affiliation_string: Department of Digital Humanities, Faculty of Arts, University of Helsinki, Helsinki, Finland
raw_author_name: Mathias Creutz
raw_affiliation_string: Department of Digital Humanities, Faculty of Arts, University of Helsinki, Helsinki, Finland
raw_author_name: Filip Ginter
raw_affiliation_string: TurkuNLP, Department of Computing, University of Turku, Turku, Finland

Abstract: Abstract In this paper, we approach the problem of semantic search by introducing a task of paraphrase span detection, i.e. given a segment of text as a query phrase, the task is to identify its paraphrase in a given document, the same modelling setup as typically used in extractive question answering. While current work in paraphrasing has almost uniquely focused on sentence-level approaches, the novel span detection approach gives a possibility to retrieve a segment of arbitrary length. On the Turku Paraphrase Corpus of 100,000 manually extracted Finnish paraphrase pairs including their original document context, we find that by achieving an exact match of 88.73 our paraphrase span detection approach outperforms widely adopted sentence-level retrieval baselines (lexical similarity as well as BERT and SBERT sentence embeddings) by more than 20pp in terms of exact match, and 11pp in terms of token-level F-score. This demonstrates a strong advantage of modelling the paraphrase retrieval in terms of span extraction rather than commonly used sentence similarity, the sentence-level approaches being clearly suboptimal for applications where the retrieval targets are not guaranteed to be full sentences. Even when limiting the evaluation to sentence-level retrieval targets only, the span detection model still outperforms the sentence-level baselines by more than 4 pp in terms of exact match, and almost 6pp F-score. Additionally, we introduce a method for creating artificial paraphrase data through back-translation, suitable for languages where manually annotated paraphrase resources for training the span detection model are not available.
Differentially private Riemannian optimization

Authors:
raw_author_name: Andi Han
raw_affiliation_string: University of Sydney, Sydney, Australia
raw_author_name: Bamdev Mishra
raw_affiliation_string: Microsoft, Hyderabad, India
raw_author_name: Pratik Jawanpuria
raw_affiliation_string: Microsoft, Hyderabad, India
raw_author_name: Junbin Gao
raw_affiliation_string: University of Sydney, Sydney, Australia

Abstract: Abstract In this paper, we study the differentially private empirical risk minimization problem where the parameter is constrained to a Riemannian manifold. We introduce a framework for performing differentially private Riemannian optimization by adding noise to the Riemannian gradient on the tangent space. The noise follows a Gaussian distribution intrinsically defined with respect to the Riemannian metric on the tangent space. We adapt the Gaussian mechanism from the Euclidean space to the tangent space compatible to such generalized Gaussian distribution. This approach presents a novel analysis as compared to directly adding noise on the manifold. We further prove privacy guarantees of the proposed differentially private Riemannian (stochastic) gradient descent using an extension of the moments accountant technique. Overall, we provide utility guarantees under geodesic (strongly) convex, general nonconvex objectives as well as under the Riemannian Polyak-Łojasiewicz condition. Empirical results illustrate the versatility and efficacy of the proposed framework in several applications.
Research on multi-image encryption method based on image scaling and ghost imaging

Authors:
raw_author_name: Yiqiang Zhang
raw_author_name: Leihong Zhang

Abstract: Abstract Optical information processing technology itself is characterized by high speed and parallelism, while the wavelength of light is short and the loading information capacity is large. Therefore, optical encryption is of great significance in the field of image encryption. For multi-image encryption, a multi-image encryption system (ISK-MGI) based on image scaling and ghost imaging is proposed in this paper. In the encryption process, image scaling is used to embed the image information to be encrypted into the artifact image to achieve the first step of artifact encryption; then the ghost imaging encryption is used to encrypt any of the artifact images and the intensity sequence obtained from the barrel detector is used as the cipher text; the integration property of Fourier transform is used to obtain the modulation patterns of other artifact images as the key. The feasibility, security and robustness of the scheme are verified by experiments and simulations. The scheme not only solves the image information crosstalk problem of multi-image encryption, but also has high security. Each image in this method has a primary public key and a secondary private key, which solves the potential risk of sharing public keys and provides a new idea for optical information encryption.
Semantics of Belief Change Operators for Intelligent Agents

Authors:
raw_author_name: Kai Sauerwald
raw_affiliation_string: Fakultät für Mathematik und Informatik, FernUniversität in Hagen, Künstliche Intelligenz, 58084, Hagen, Germany

Abstract: Abstract This paper summarises several contributions to the theory of belief change by the authors’ dissertation thesis. First, a relational characterization of belief revision for Tarskian logics is considered, encompassing first-order predicate logic, description logic, modal logics and many monotonic logics with model-theoretic semantics. Those logics where total preorders are the standard semantics for revision are characterized. The second contribution considered is a theory of belief revision that builds upon the idea that agents are limited in what the outcome of a revision is. Furthermore, advancements in principles for iterated belief contraction given in the thesis are outlined.