Article
Computer Science, Artificial Intelligence
Fayaz Ali Dharejo, Iyyakutti Iyappan Ganapathi, Muhammad Zawish, Basit Alawode, Moath Alathbah, Naoufel Werghi, Sajid Javed
Summary: The resource-limited nature of underwater vision equipment affects underwater robotics and ocean engineering tasks. Super-resolution methods, particularly using Vision Transformers (ViTs), have emerged to enhance low-resolution underwater images. However, ViTs face challenges in handling severe degradation in underwater imaging. In contrast, Multi-scale ViTs (MViTs) overcome these challenges by preserving long-range dependencies through evolving channel capacity. This study proposes a novel algorithm, SwinWave-SR, for efficient and accurate multi-scale super-resolution for underwater images.
INFORMATION FUSION
(2024)
Article
Computer Science, Theory & Methods
Andrea Agiollo, Enkeleda Bardhi, Mauro Conti, Nicolo Dal Fabbro, Riccardo Lazzeretti
Summary: This paper proposes an anonymous-by-design FL framework based on NDN, which addresses the security and privacy issues in FL. With a custom communication protocol, the framework achieves anonymity and privacy requirements while improving communication efficiency.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Artificial Intelligence
Pedro Nuno Leite, Andry Maykol Pinto
Summary: This article introduces a hybrid underwater imaging system that retrieves tri-dimensional information from harsh maritime conditions. It demonstrates two fusion algorithms that combine dense and accurate representations from point clouds and Light Stripe Ranging (LSR). Evaluation shows improved output point clouds and robust performance in dealing with degraded input information.
INFORMATION FUSION
(2024)
Article
Computer Science, Theory & Methods
Ritam Ganguly, Yingjie Xue, Aaron Jonckheere, Parker Ljung, Benjamin Schornstein, Borzoo Bonakdarpour, Maurice Herlihy
Summary: This paper presents a centralized runtime monitoring technique for distributed systems, which verifies the correctness of distributed computations by exploiting bounded-skew clock synchronization. By introducing a progression-based formula rewriting scheme and utilizing SMT solving techniques, the metric temporal logic can be monitored and the probabilistic guarantee for verification results can be calculated. Experimental results demonstrate the effectiveness of this technique in different application scenarios.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2024)
Article
Computer Science, Theory & Methods
Qiao-Long Huang, Ke Ye, Xiao-Shan Gao
Summary: This paper presents a new deterministic algorithm and a probabilistic algorithm for accelerating matrix multiplication over Q, especially for skew-polynomial-sparse input matrices or products.
JOURNAL OF SYMBOLIC COMPUTATION
(2024)
Article
Computer Science, Theory & Methods
Tim Breitenbach, Shrikanth Malavalli Divakar, Lauritz Rasbach, Patrick Jahnke
Summary: With the trend towards multi-socket server systems, the demand for RAM per server has increased, resulting in more DIMM sockets per server. RAM issues have become a dominant failure pattern for servers due to the probability of failure in each DIMM. This study introduces an ML-driven framework to estimate the probability of memory failure for each RAM module. The framework utilizes structural information between correctable (CE) and uncorrectable errors (UE) and engineering measures to mitigate the impact of UE.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Prayag Tiwari, Lailei Zhang, Zhiguo Qu, Ghulam Muhammad
Summary: This paper proposes a Quantum Fuzzy Neural Network (QFNN) for sentiment and sarcasm detection in social media. The QFNN combines Classical and Quantum Neural Networks (QNN) with fuzzy logic and utilizes complex numbers to capture sentimental and sarcastic features. The experiments show that QFNN outperforms other methods and exhibits excellent robustness and expressibility.
INFORMATION FUSION
(2024)
Article
Computer Science, Theory & Methods
Carlos Ansotegui, Eduard Torres
Summary: This paper presents an incomplete algorithm for efficiently constructing Covering Arrays with Constraints of high strength. The algorithm mitigates memory blow-ups and reduces run-time consumption, providing a practical tool for Combinatorial Testing.
JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING
(2024)
Article
Computer Science, Artificial Intelligence
Xinli You, Fujun Hou, Francisco Chiclana
Summary: This study aims to develop a reputation-based trust model for establishing trust relationships among experts in a group decision-making framework. The research achieves this by defining a trust credibility measure, designing direct trust feedback, and proposing a global reputation model.
INFORMATION FUSION
(2024)
Correction
Computer Science, Hardware & Architecture
Peter L. Bartlett, Philip M. Long
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Artificial Intelligence
Helena Liz-Lopez, Mamadou Keita, Abdelmalik Taleb-Ahmed, Abdenour Hadid, Javier Huertas-Tato, David Camacho
Summary: Generative deep learning techniques have been widely discussed in the public, but the slow progress in applying these techniques to counter disinformation is concerning. With the ease and credibility of manipulating multimedia content, developing effective forensic techniques becomes invaluable. This survey comprehensively describes modern manipulation and forensic techniques, focusing on their applications in video, audio, and multimodal fusion. The classification of manipulation techniques and the generation of datasets using generative techniques are provided for forensic purposes. The review and comparative analysis of forensic techniques from 2018 to 2023, as well as the comparison of end-to-end forensic tools for end-users, are presented. Clear trends and challenges, such as multilinguality, multimodality, and improving data quality, are identified for future research in an ever-changing adversarial environment.
INFORMATION FUSION
(2024)
Article
Computer Science, Theory & Methods
F. Brogi, S. Bna, G. Boga, G. Amati, T. Esposti Ongaro, M. Cerminara
Summary: This paper analyzes the impact of reduced precision on the computational performance and accuracy of computational fluid dynamics. The results show that reducing precision can significantly improve computational speed, but attention must be paid to maintaining the quality and convergence of computed solutions.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Editorial Material
Computer Science, Theory & Methods
Kiho Lim, Christian Esposito, Tian Wang, Chang Choi
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Renhao Lu, Weizhe Zhang, Qiong Li, Hui He, Xiaoxiong Zhong, Hongwei Yang, Desheng Wang, Zenglin Xu, Mamoun Alazab
Summary: Federated Learning allows collaborative training of AI models with local data, and our proposed FedAAM scheme improves convergence speed and training efficiency through an adaptive weight allocation strategy and asynchronous global update rules.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Theory & Methods
Haroon Wahab, Irfan Mehmood, Hassan Ugail, Javier Del Ser, Khan Muhammad
Summary: Wireless capsule endoscopy (WCE) is a revolutionary diagnostic method for small bowel pathology. However, the manual analysis of WCE videos is cumbersome and the privacy concerns of WCE data hinder the adoption of AI-based diagnoses. This study proposes a federated learning framework for collaborative learning from multiple data centers, demonstrating improved anomaly classification performance while preserving data privacy.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2024)
Article
Computer Science, Hardware & Architecture
Flavia Bonomo-Braberman, Nick Brettell, Andrea Munaro, Daniel Paulusma
Summary: This article discusses the convexity and mim-width of bipartite graphs, and it proves that for certain families of graphs 7-t, the 7-t-convex graphs can be solved in polynomial time for NP-complete problems. It also explores the bounded and unbounded mim-width of 7-t-convex graphs for different sets 7-t.
JOURNAL OF COMPUTER AND SYSTEM SCIENCES
(2024)
Article
Computer Science, Artificial Intelligence
Shray Pathak, Shreya Sharma, Abhishek Banerjee, Sanjeev Kumar
Summary: The urgency to protect natural water resources in a sustainable manner has increased as water scarcity and global climate change worsen. Stormwater harvesting is considered the most environmentally friendly approach to alleviate strain on freshwater resources. This study introduces a robust method that considers technical and socioeconomic aspects to evaluate the potential for stormwater harvesting. The method effectively identifies and assesses suitable areas for implementing stormwater harvesting and incorporates input from water experts in the decision-making process.
Article
Computer Science, Theory & Methods
Dekel Tsur
Summary: This paper proposes algorithms for 2-CLUB CLUSTER VERTEX DELETION and 2-CLUB CLUSTER EDGE DELETION problems. The algorithms have running times of O*(3.104k) and O*(2.562k) respectively, and were obtained using automated generation of branching rules. These results improve upon previous algorithms for the same problems.
THEORETICAL COMPUTER SCIENCE
(2024)
Article
Computer Science, Theory & Methods
Tong Kang, Leifan Yan, Long Ye, Jun Li
Summary: This note solves an open problem proposed in the paper Kang et al. (2023) [9] by demonstrating the linearity of set-valued pan-integrals based on a fuzzy measure and the operations pair (+, center dot) through the subadditivity of the fuzzy measure. It also provides an example to show the necessity of the subadditivity condition for the linearity of set-valued pan-integrals. Furthermore, it introduces the pan-integral of set-valued functions based on a fuzzy measure and pan-operations pair (circle plus, circle times).
FUZZY SETS AND SYSTEMS
(2024)
Article
Computer Science, Theory & Methods
Daniel Berend, Liat Cohen, Omrit Filtser
Summary: The Tower of Hanoi puzzle has been a fascination for mathematicians and theoretical computer scientists for over a century. By using graph theory, we can study connectivity, shortest paths, and other properties of the Hanoi puzzle. Additionally, the Hanoi graphs are related to interesting structures such as the Sierpinski gasket and Gray codes.
THEORETICAL COMPUTER SCIENCE
(2024)
