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2024 International Conference on Distributed Systems, computer Networks and Cybersecurity, ICDSCNC 2024

作者： Sathiyapriya, V. Devi, K. Nethra Deepa, S. Marimuthu, M. Manikandan, P. Prabu, S. Knowledge Institute of Technology Department of Computer Science and Engineering Kakapalayam India Gnanamani College of Technology Department of Artificial Intelligence and Data Science Namakkal India Vellore Institute of Technology School of Computer Science and Engineering Chennai India Srm Institute of Science and Technology School of Computing Tiruchirappalli India

ISBN: (纸本)9798350375442

Pancreatic cancer poses a significant challenge in early detection and treatment due to its malignant nature within the digestive tract. Recent studies, such as those conducted by the Pancreatic Cancer Action Network, predict that pancreatic cancer will rank as the world's second leading cause of cancer-related deaths in 2020. Various methods have been explored in the literature to segment pancreatic tumors and detect lesions from CT images, crucial for assessing severity. One such method is the Min-Max segmentation algorithm, which effectively removes the jaundiced sclera region from affected eyes by analysing color gradients, offering more feasible and discriminative solutions. Additionally, the utilization of Whale Optimized feature-based selection aids in extracting optimal features for optimization purposes. Through an analysis of different classification algorithms and the implementation of a suggested technique for achieving optimum solutions and maximum accuracy, the proposed work is structured into two phases. Phase I involves pre-processing and artifact removal, followed by segmentation, while Phase II focuses on feature extraction, feature selection, and classification. The initial step of pre-processing the image facilitates pixel location using intensity measures, crucial for accurate tumor segmentation and minimizing false detection. Ultimately, the proposed approach aims to design and develop an optimal feature selection strategy for classifying pancreatic cancer tumors in PET/CT images, resulting in increased classification efficiency 92% and improved cancer tumor detection rates with compare other existing approaches. © 2024 IEEE.

关键词： computerized tomography

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Optimizing Coverage in Wireless Sensor Networks Using the Tumbleweed Algorithm

Journal of Network Intelligence

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Journal of Network intelligence 2025年第1期10卷 250-261页

作者： Zhang, Mengfei Chu, Shu-Chuan Liu, Nengxian Huang, Kuan-Chun Pan, Jeng-Shyang College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China College of Computer and Data Science Fuzhou University Fuzhou350108 China Department of Industrial and Systems Engineering Chung Yuan Christian University Taoyuan320314 Taiwan School of Artificial Intelligence Nanjing University of Information Science and Technology Nanjing210044 China Department of Information Management Chaoyang University of Technology Taichung41349 Taiwan

Wireless sensor networks (WSNs) have found extensive applications across various fields, significantly enhancing the convenience in our daily lives. Hence, an in-creasing number of researchers are directing their attention toward the performance of sensor nodes, with a particular emphasis on addressing the coverage challenges in WSNs. Node coverage plays a crucial role in determining the detection performance of WSNs, making it imperative to attain maximum coverage with a given number of sensor nodes. This paper applies the Tumbleweed Algorithm (TA) to the coverage problem in WSNs and validates its effectiveness through simulation experiments. The results demonstrate its unique advantages in global search and avoiding local optima, providing a new solution for the WSN coverage problem and offering valuable references for future research and practical applications. The TA algorithm simulates the lifecycle of tumbleweed from seedling to mature plant and includes the concept of growth cycles. This paper compares the TA algorithm with PSO, GWO, DE, BOA, SCA, and AOA, setting different numbers of wireless sensor nodes and varying sensing radii for the experiments. The experimental results show that the TA algorithm significantly improves coverage rates under various configurations and consistently outperforms other commonly used algorithms. © 2025, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Sensor nodes

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Security and Privacy in Solar Insecticidal Lamps Internet of Things:Requirements and Challenges

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 58-73页

作者： Qingsong Zhao Lei Shu Kailiang Li Mohamed Amine Ferrag Ximeng Liu Yanbin Li the College of Artificial Intelligence Nanjing Agricultural UniversityNanjing 210031 the State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023 the State Key Laboratory of Cryptology Beijing 100878China IEEE the School of Engineering University of LincolnLincoln LN67TSUK the Artificial Intelligence and Digital Science Research Center Technology Innovation InstituteMasdar City 9639UAE the College of Computer and Data Science Fuzhou UniversityFuzhou 350108China

Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security *** issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.

关键词： Challenges Internet of Things(IoT) privacy and security security requirements solar insecticidal lamps(SIL)

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Crowd Recognition Based on the Fusion of Multi-model Collaboration

Crowd Recognition Based on the Fusion of Multi-model Collabo...

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2024 International Conference on Remote Sensing, Mapping, and Image Processing, RSMIP 2024

作者： Jin, Guanghao Wang, Yuqing Wang, Jieying Zhao, Junhua Hui, Du Song, Qingzeng School of Artificial Intelligence Beijing Polytechnic Beijing China School of Computer Science and Technology Tiangong University Tianjin China

ISBN: (纸本)9781510680012

Crowd recognition by the deep learning is important to the management of campus or classroom, which include the technologies of object detection and face detection. In the crowd recognition case, the detection of anomaly samples plays key role like the person with no face or the opposite case. This study focuses on the cooperation of object detection model YOLOv8 and the advanced facial detection model SCNet, which is to find the anomaly samples. We try to provide a valuable insight into the research of object detection and facial recognition tasks in the field of computer vision, which is to provide useful guidance for further promoting the improvement of crowd recognition. © 2024 SPIE.

关键词： Face recognition

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Exploring HDBSCAN for Effort-Aware Defect Prediction: A Density-Based Clustering Method 6

Exploring HDBSCAN for Effort-Aware Defect Prediction: A Dens...

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6th International Conference on Frontier Technologies of Information and computer, ICFTIC 2024

作者： Zhou, Hao Chen, Xiaoxiao Ma, Bizheng Li, Yanhui School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China School of Computer Wuhan Qingchuan University Wuhan China

ISBN: (纸本)9798331541750

This study explores the application of HDBSCAN, a density-based unsupervised clustering method, in effort-aware defect prediction (EADP). Unlike traditional methods, HDBSCAN dynamically identifies defect clusters and removes noise points without requiring predefined parameters. Experiments on the PROMISE dataset demonstrate that HDBSCAN outperforms several supervised and unsupervised methods in metrics such as IFA and PMI@20%, reducing testing resource waste and improving early defect detection. However, its performance on pof B@20% is slightly inferior to certain state-of-the-art supervised methods. These results indicate that HDBSCAN is an efficient alternative for EADP and suitable for defect prediction tasks. © 2024 IEEE.

关键词： Defect density

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Tackling Non-Stationarity in Reinforcement Learning via Causal-Origin Representation 41

Tackling Non-Stationarity in Reinforcement Learning via Caus...

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41st International Conference on Machine Learning, ICML 2024

作者： Zhang, Wanpeng Li, Yilin Yang, Boyu Lu, Zongqing School of Computer Science Peking University China Center for Statistical Science Peking University China School of Data Science Fudan University China Beijing Academy of Artificial Intelligence China

In real-world scenarios, the application of reinforcement learning is significantly challenged by complex *** existing methods attempt to model changes in the environment explicitly, often requiring impractical prior knowledge of *** this paper, we propose a new perspective, positing that non-stationarity can propagate and accumulate through complex causal relationships during state transitions, thereby compounding its sophistication and affecting policy *** believe that this challenge can be more effectively addressed by implicitly tracing the causal origin of *** this end, we introduce the Causal-Origin REPresentation (COREP) *** primarily employs a guided updating mechanism to learn a stable graph representation for the state, termed as causal-origin *** leveraging this representation, the learned policy exhibits impressive resilience to *** supplement our approach with a theoretical analysis grounded in the causal interpretation for non-stationary reinforcement learning, advocating for the validity of the causal-origin *** results further demonstrate the superior performance of COREP over existing methods in tackling non-stationarity *** code is available at https://***/PKURL/COREP. Copyright 2024 by the author(s)

关键词： Reinforcement learning

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LegoDroid: flexible Android app decomposition and instant installation

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science China(Information sciences) 2023年第4期66卷 155-173页

作者： Yi LIU Yun MA Xusheng XIAO Tao XIE Xuanzhe LIU School of Computer Science Peking University Key Laboratory of High Confidence Software Technologies(Peking University) Ministry of Education Institute for Artificial Intelligence Peking University Department of Computer and Data Sciences Case Western Reserve University

Current mobile applications(apps) have become increasingly complicated with increasing features that are represented on the graphical user interface associated with application programming interfaces(APIs) to access backend functionality and data. Meanwhile, apps suffer from the “software bloat” in volume. Some app features may be redundant, with respect to those features(from other apps) that the users already desirably and frequently use. However, the current app release model forces users to download and install a full-size installation package rather than optionally choosing only their desired features. Large-size apps can not only increase the local resource consumption, such as CPU, memory, and energy, but also inevitably compromise the user experience, such as the slow load time in the app. In this article, we first conduct an empirical study to characterize the app feature usage when users interact with Android apps,and surprisingly find that users access only a very small subset of app features. Based on these findings,we design a new approach named Lego Droid, which automatically decomposes an Android app for flexible loading and installation, while preserving the expected functionality with a fast and instant app load. With such a method, a slimmer bundle will be downloaded and host the target APIs inside the original app to satisfy users' requirements. We implement a system for Lego Droid and evaluate it with 1000 real-world Android apps. Compared to the original full-size apps, apps optimized by Lego Droid can substantially improve the load time by reducing the base bundle and feature bundles by 13.06% and 10.93%, respectively,along with the app-package installation size by 44.17%. In addition, we also demonstrate that Lego Droid is quite practical with evolving versions, as it can produce substantial reusable code to alleviate the developers' efforts when releasing new app versions.

关键词： performance software bloat instant installation mobile applications program analysis

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A boundary evidence controlled level set inference method for nuclei instance segmentation in histopathology images

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Multimedia Tools and Applications 2024年 1-31页

作者： Vatani, Amir Song, Jie Xiao, Liang School of Computer Science and Engineering Nanjing University of Science and Technology Jiangsu Nanjing210094 China College of Automation & College of Artificial Intelligence Nanjing University of Posts and Telecommunications Jiangsu Nanjing210023 China

Periodic B-spline (PBS) has been a successfully used technique in histopathology image segmentation. However, it is limited when dealing with multi-instance objects in real-world biomedical applications. Moreover, its segmentation results are quite sensitive to the initial settings of the model and highly depend on the selection of control points. To address these issues and boost the canonical PBS to a new level of adaptive fitting, we present Level-Set B-Spline (LSBS), a novel definition of nuclear contour inference that employs B-splines under the energy minimization of a variational level set functional, which can promote each other. To this end, we adopt a two-stage approach: The first stage solves the marker detection and image segmentation problem and the second stage solves the joint modeling of the missing contour and the latent shape. To do so, we propose the use of modified concavity measurement and optimal boundary-to-marker association as an efficient basis for computing a periodic set of knots to drive the LSBS. For any probe image, our approach enables to analysis of free-lying and overlapping cell nuclei with weak boundaries. We demonstrated the superiority of the proposed LSBS by evaluating it on various datasets, including the challenging TCGA KIRC and Kumar nuclei, where the consistently state-of-the-art performances were achieved for comparison against state-of-the-art image analysis-based methods. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image segmentation

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Online Network Intrusion Detection Based on Self-Encoder Integration 24

Online Network Intrusion Detection Based on Self-Encoder Int...

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3rd International Conference on Signal Processing, computer Networks and Communications, SPCNC 2024

作者： Sun, Dongxu Li, Peng Pei, Lina Wei, Chuhang Co. Ltd. Hebei Shijiazhuang China School of School of Artificial Intelligence and Data Science Hebei University of Technology Tianjin China

ISBN: (纸本)9798400710834

With the development of information technology, network security problems have intensified, and the performance enhancement of network intrusion detection systems has attracted much attention In this paper, we propose an online system based on self-encoder integration that utilizes deep learning to improve detection accuracy and robustness Neural networks are popular for their ability to learn complex patterns, but training resources are in high demand and existing supervised schemes require expert labeling and regular updates. Therefore, this paper introduces Kitsune, which uses unsupervised, efficient online self-encoder integration to distinguish between normal and abnormal traffic and is optimized to improve detection efficiency In this paper, we experimentally validate that the optimized Kitsune achieves improvements in accuracy, recall, false-positive rate, false-negative rate. © 2024 Copyright held by the owner/author(s).

关键词： Network intrusion

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Text Reasoning Chain Extraction for Multi-Hop Question Answering

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Tsinghua science and technology 2024年第4期29卷 959-970页

作者： Pengming Wang Zijiang Zhu Qing Chen Weihuang Dai School of Data Science and Artificial Intelligence Wenzhou University of TechnologyWenzhou 325035China School of Computer Science and also with Institute of Intelligent Information ProcessingSouth China Business CollegeGuangdong University of Foreign StudiesGuangzhou 510545China School of Psychology Jiangxi Normal UniversityNanchang 330022China also with School of Science East China Jiaotong UniversityNanchang 330013China Institute of Intelligent Information Processing South China Business CollegeGuangdong University of Foreign StudiesGuangzhou 510545China

With the advent of the information age, it will be more troublesome to search for a lot of relevant knowledge to find the information you need. Text reasoning is a very basic and important part of multi-hop question and answer tasks. This paper aims to study the integrity, uniformity, and speed of computational intelligence inference data capabilities. That is why multi-hop reasoning came into being, but it is still in its infancy, that is, it is far from enough to conduct multi-hop question and answer questions, such as search breadth, process complexity, response speed, comprehensiveness of information, etc. This paper makes a text comparison between traditional information retrieval and computational intelligence through corpus relevancy and other computing methods. The study finds that in the face of multi-hop question and answer reasoning, the reasoning data that traditional retrieval methods lagged behind in intelligence are about 35% worse. It shows that computational intelligence would be more complete, unified, and faster than traditional retrieval methods. This paper also introduces the relevant points of text reasoning and describes the process of the multi-hop question answering system, as well as the subsequent discussions and expectations.

关键词： intelligent computing multi-hop quiz text reasoning document retrieval text complex network

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