Article
Computer Science, Information Systems
Weibei Fan, Jianxi Fan, Zhijie Han, Peng Li, Yujie Zhang, Ruchuan Wang
Summary: This paper mainly studies the fault tolerant Hamiltonian properties of a faulty locally exchanged twisted cube, LeTQ(s, t) - (f(v) + f(e)), proving that for s > 2, t > 3, and s <= t, an LeTQ(s, t) can tolerate up to s - 1 faulty vertices and edges when embedding a Hamiltonian cycle. Furthermore, it is also proven that there is a Hamiltonian path between any two distinct fault-free vertices in a faulty LeTQ(s, t) with up to (s - 2) faulty vertices and edges. The results demonstrate that LeTQ(s, t) is (s - 1)-Hamiltonian and (s - 2)-Hamiltonian-connected, achieving optimal (s - 1)-fault-tolerant Hamiltonicity and (s - 2) fault-tolerant Hamiltonian connectivity.
FRONTIERS OF COMPUTER SCIENCE
(2021)
Article
Computer Science, Hardware & Architecture
Kung-Jui Pai, Ro-Yu Wu, Sheng-Lung Peng, Jou-Ming Chang
Summary: This paper investigates the construction of multiple edge-disjoint Hamiltonian cycles (EDHCs) in a crossed cube network and evaluates the performance of data broadcasting. The results show that multiple EDHCs can be constructed in the crossed cube network, significantly improving the success rate and latency of edge fault-tolerant data broadcasting.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Mathematics, Applied
Huifeng Zhang, Xirong Xu, Ziming Wang, Qiang Zhang, Yuansheng Yang
Summary: This paper focuses on the fault-tolerant Hamiltonian connectivity of the augmented cube AQ(n) and proves properties related to weak vertex-pairs and fault-free Hamiltonian paths in AQ(n). The paper provides an optimal and sharp result without restrictions on each vertex.
Article
Computer Science, Theory & Methods
Hongbin Zhuang, Xiao-Yan Li, Jou-Ming Chang, Dajin Wang
Summary: This paper proposes an efficient fault-tolerant Hamiltonian path embedding algorithm for enhancing the fault-tolerant capacity of k-ary n-cubes. A new conditional fault model named Partitioned Edge Fault model (PEF model) is introduced. Experimental and comparative results show that the algorithm significantly improves the edge fault tolerance compared to known results.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2023)
Article
Mathematics
Kung-Jui Pai
Summary: This paper discusses the applications of edge-disjoint Hamiltonian cycles (EDHC) in locally twisted cubes (FLTQ) and crossed cubes (FCQ) with the center at the origin, including parallel data broadcasting and edge fault-tolerance in network communications. Three EDHCs are constructed in FLTQ(5) and FCQ(5) using the technique of edge exchange. It is proved that there are three EDHCs in FLTQ(n) and FCQ(n) when n≥6 based on their recursive structures. The data broadcasting performance of three EDHCs in FLTQ(n) and FCQ(n) is evaluated by simulation for 5≤n≤9, considering multiple faulty edges occurring randomly.
Article
Mathematics
Fatemeh Keshavarz-Kohjerdi, Alireza Bagheri
Summary: This paper investigates the Hamiltonian path and cycle problems and proves that every 3-connected solid supergrid graph is Hamiltonian-connected, and every 2-connected solid supergrid graph is Hamiltonian. It also provides linear-time algorithms for computing Hamiltonian cycles and paths in these graphs.
BULLETIN OF THE MALAYSIAN MATHEMATICAL SCIENCES SOCIETY
(2023)
Article
Computer Science, Theory & Methods
Yuxing Yang, Lingling Zhang
Summary: The paper investigates the conditions for the existence of a Hamiltonian path in faulty k-ary n-cube networks. It is proven that a Hamiltonian path exists through a linear forest in the network when the paths in the linear forest do not have the target nodes as internal or end nodes.
IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
Dongqin Cheng
Summary: This paper investigates the properties of the n-dimensional locally twisted cube LT Q(n). It is proved that for any node x in LT Q(n), there exist multiple edge-disjoint cycles that intersect with each LT Q(n-2)(alpha beta).
THEORETICAL COMPUTER SCIENCE
(2022)
Article
Computer Science, Hardware & Architecture
Hongbin Zhuang, Xiao-Yan Li, Jou-Ming Chang, Cheng-Kuan Lin, Ximeng Liu
Summary: This article proposes the concept of the partitioned fault model and explores the fault tolerability of interconnection networks using novel indicators. The research results demonstrate the optimality of these indicators in terms of the number of edge faults tolerated.
IEEE TRANSACTIONS ON COMPUTERS
(2023)
Article
Computer Science, Hardware & Architecture
Lina Ba, Hailun Wu, Heping Zhang
Summary: This research explores the connectivity parameter of networks and introduces the concepts of structure connectivity and substructure connectivity of graphs. By computing the specific structure connectivity of n-dimensional folded hypercubes and augmented cubes, improved results are obtained compared to existing findings.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Theory & Methods
Yuxing Yang, Jing Li
Summary: This paper investigates properties of n-dimensional hypercubes and proves the existence of Hamiltonian paths or cycles in specific conditions for Q(n)-F-v-F-e and its subgraphs.
THEORETICAL COMPUTER SCIENCE
(2021)
Article
Mathematics
Xiaoling Ma, Yang Wu, Mingquan Zhan, Hong-Jian Lai
Summary: The text presents proofs of key results in graph theory, regarding the properties of N-free line graphs under certain conditions.
DISCRETE MATHEMATICS
(2021)
Article
Mathematics
Alen Vegi Kalamar, Tadej Zerak, Drago Bokal
Summary: Kuratowski showed that K3,3 and K5 are the only two nonplanar graphs, while Robertson and Seymour extended the finiteness of the set of forbidden minors. Siran and Kochol demonstrated the existence of infinitely many k-crossing-critical graphs. Recently, Bokal, Oporowski, Richter, and Salazar characterized 2-crossing-critical graphs completely.
Article
Computer Science, Information Systems
Mingzu Zhang, Wenhuan Ma, Tianlong Ma
Summary: This research explores the relationship between edge disjoint paths connecting disconnected subgraphs and the extra edge connectivity in a graph, based on the Menger theorem. By studying the augmented cube, it is observed that the extra edge connectivity exhibits a concentration behavior for exponentially large values of g, and for specific values in the cube. The exact values of the extra edge connectivity in the augmented cube are determined by specific formulas and exhibit sharp upper and lower bounds. Additionally, the study also involves finding exponential edge disjoint paths with edge faults in the augmented cube.
Article
Computer Science, Hardware & Architecture
Yuxing Yang
Summary: H is a Cartesian product graph composed of even cycles and paths. The first multiplier is an even cycle with a minimum length of 4, and the second multiplier is a path with at least two nodes or an even cycle. H is an equitable bipartite graph, with special cases including the torus, column-torus, and even k-ary n-cube. An algorithm is introduced to construct a Hamiltonian path connecting two different nodes u and v in the partite set of H not containing a specific node w.
Article
Computer Science, Information Systems
Xia Liang, Jie Guo, Peide Liu
Summary: This paper investigates a novel consensus model based on social networks to manage manipulative and overconfident behaviors in large-scale group decision-making. By proposing a novel clustering model and improved methods, the consensus reaching is effectively facilitated. The feedback mechanism and management approach are employed to handle decision makers' behaviors. Simulation experiments and comparative analysis demonstrate the effectiveness of the model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiang Li, Haiwang Guo, Xinyang Deng, Wen Jiang
Summary: This paper proposes a method based on class gradient networks for generating high-quality adversarial samples. By introducing a high-level class gradient matrix and combining classification loss and perturbation loss, the method demonstrates superiority in the transferability of adversarial samples on targeted attacks.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Lingyun Lu, Bang Wang, Zizhuo Zhang, Shenghao Liu
Summary: Many recommendation algorithms only rely on implicit feedbacks due to privacy concerns. However, the encoding of interaction types is often ignored. This paper proposes a relation-aware neural model that classifies implicit feedbacks by encoding edges, thereby enhancing recommendation performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jaehong Yu, Hyungrok Do
Summary: This study discusses unsupervised anomaly detection using one-class classification, which determines whether a new instance belongs to the target class by constructing a decision boundary. The proposed method uses a proximity-based density description and a regularized reconstruction algorithm to overcome the limitations of existing one-class classification methods. Experimental results demonstrate the superior performance of the proposed algorithm.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Hui Tu, Shifei Ding, Xiao Xu, Haiwei Hou, Chao Li, Ling Ding
Summary: Border-Peeling algorithm is a density-based clustering algorithm, but its complexity and issues on unbalanced datasets restrict its application. This paper proposes a non-iterative border-peeling clustering algorithm, which improves the clustering performance by distinguishing and associating core points and border points.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Long Tang, Pan Zhao, Zhigeng Pan, Xingxing Duan, Panos M. Pardalos
Summary: In this work, a two-stage denoising framework (TSDF) is proposed for zero-shot learning (ZSL) to address the issue of noisy labels. The framework includes a tailored loss function to remove suspected noisy-label instances and a ramp-style loss function to reduce the negative impact of remaining noisy labels. In addition, a dynamic screening strategy (DSS) is developed to efficiently handle the nonconvexity of the ramp-style loss.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Raghunathan Krishankumar, Sundararajan Dhruva, Kattur S. Ravichandran, Samarjit Kar
Summary: Health 4.0 is gaining global attention for better healthcare through digital technologies. This study proposes a new decision-making framework for selecting viable blockchain service providers in the Internet of Medical Things (IoMT). The framework addresses the limitations in previous studies and demonstrates its applicability in the Indian healthcare sector. The results show the top ranking BSPs, the importance of various criteria, and the effectiveness of the developed model.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Tao Tan, Hong Xie, Liang Feng
Summary: This paper proposes a heterogeneous update idea and designs HetUp Q-learning algorithm to enlarge the normalized gap by overestimating the Q-value corresponding to the optimal action and underestimating the Q-value corresponding to the other actions. To address the limitation, a softmax strategy is applied to estimate the optimal action, resulting in HetUpSoft Q-learning and HetUpSoft DQN. Extensive experimental results show significant improvements over SOTA baselines.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Chao Yang, Xianzhi Wang, Lina Yao, Guodong Long, Guandong Xu
Summary: This paper proposes a dynamic transformer-based architecture called Dyformer for multivariate time series classification. Dyformer captures multi-scale features through hierarchical pooling and adaptive learning strategies, and improves model performance by introducing feature-map-wise attention mechanisms and a joint loss function.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Xiguang Li, Baolu Feng, Yunhe Sun, Ammar Hawbani, Saeed Hammod Alsamhi, Liang Zhao
Summary: This paper proposes an enhanced scatter search strategy, using opposition-based learning, to solve the problem of automated test case generation based on path coverage (ATCG-PC). The proposed ESSENT algorithm selects the path with the lowest path entropy among the uncovered paths as the target path and generates new test cases to cover the target path by modifying the dimensions of existing test cases. Experimental results show that the ESSENT algorithm outperforms other state-of-the-art algorithms, achieving maximum path coverage with fewer test cases.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Shirin Dabbaghi Varnosfaderani, Piotr Kasprzak, Aytaj Badirova, Ralph Krimmel, Christof Pohl, Ramin Yahyapour
Summary: Linking digital accounts belonging to the same user is crucial for security, user satisfaction, and next-generation service development. However, research on account linkage is mainly focused on social networks, and there is a lack of studies in other domains. To address this, we propose SmartSSO, a framework that automates the account linkage process by analyzing user routines and behavior during login processes. Our experiments on a large dataset show that SmartSSO achieves over 98% accuracy in hit-precision.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Renchao Wu, Jianjun He, Xin Li, Zuguo Chen
Summary: This paper proposes a memetic algorithm with fuzzy-based population control (MA-FPC) to solve the joint order batching and picker routing problem (JOBPRP). The algorithm incorporates batch exchange crossover and a two-level local improvement procedure. Experimental results show that MA-FPC outperforms existing algorithms in terms of solution quality.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Guoxiang Zhong, Fagui Liu, Jun Jiang, Bin Wang, C. L. Philip Chen
Summary: In this study, we propose the AMFormer framework to address the problem of mixed normal and anomaly samples in deep unsupervised time-series anomaly detection. By refining the one-class representation and introducing the masked operation mechanism and cost sensitive learning theory, our approach significantly improves anomaly detection performance.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Jin Zhou, Kang Zhou, Gexiang Zhang, Ferrante Neri, Wangyang Shen, Weiping Jin
Summary: In this paper, the authors focus on the issue of multi-objective optimisation problems with redundant variables and indefinite objective functions (MOPRVIF) in practical problem-solving. They propose a dual data-driven method for solving this problem, which consists of eliminating redundant variables, constructing objective functions, selecting evolution operators, and using a multi-objective evolutionary algorithm. The experiments conducted on two different problem domains demonstrate the effectiveness, practicality, and scalability of the proposed method.
INFORMATION SCIENCES
(2024)
Article
Computer Science, Information Systems
Georgios Charizanos, Haydar Demirhan, Duygu Icen
Summary: This article proposes a new fuzzy logistic regression framework that addresses the problems of separation and imbalance while maintaining the interpretability of classical logistic regression. By fuzzifying binary variables and classifying subjects based on a fuzzy threshold, the framework demonstrates superior performance on imbalanced datasets.
INFORMATION SCIENCES
(2024)