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Automated Colonic Polyp Detection and Classification Enabled Northern Goshawk Optimization with Deep Learning

computers, Materials & Continua 2023年第5期75卷 3677-3693页

作者： Mohammed Jasim Mohammed Jasim Bzar Khidir Hussan Subhi R.M.Zeebaree Zainab Salih Ageed Engineering College Al-Kitab UniversityKirkukIraq Information System Engineering Department Erbil Technical Engineering CollegeErbil Polytechnic UniversityErbilIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq

The major mortality factor relevant to the intestinal tract is the growth of tumorous cells(polyps)in various *** specifically,colonic polyps have a high rate and are recognized as a precursor of colon cancer *** is the conventional technique for detecting colon polyps,and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss *** automated diagnosis of polyps in a computer-aided diagnosis(CAD)method is implemented using statistical ***,Deep Learning,particularly throughConvolution Neural networks(CNN),is broadly employed to allowthe extraction of representative *** manuscript devises a new Northern Goshawk Optimization with Transfer Learning Model for Colonic Polyp Detection and Classification(NGOTL-CPDC)*** NGOTL-CPDC technique aims to investigate endoscopic images for automated colonic polyp *** accomplish this,the NGOTL-CPDC technique comprises of adaptive bilateral filtering(ABF)technique as a noise removal process and image pre-processing ***,the NGOTL-CPDC model applies the Faster SqueezeNet model for feature extraction purposes in which the hyperparameter tuning process is performed using the NGO ***,the fuzzy Hopfield neural network(FHNN)method can be employed for colonic poly detection and classification.A widespread simulation analysis is carried out to ensure the improved outcomes of the NGOTL-CPDC *** comparison study demonstrates the enhancements of the NGOTL-CPDC model on the colonic polyp classification process on medical test images.

关键词： Biomedical imaging artificial intelligence colonic polyp classification medical image classification computer-aided diagnosis

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Robust Human Interaction Recognition Using Extended Kalman Filter

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computers, Materials & Continua 2024年第11期81卷 2987-3002页

作者： Tanvir Fatima Naik Bukht Abdulwahab Alazeb Naif Al Mudawi Bayan Alabdullah Khaled Alnowaiser Ahmad Jalal Hui Liu Faculty of Computing&Artificial Intelligence Air UniversityIslamabad44000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Engineering College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Cognitive Systems Lab University of BremenBremen28359Germany

In the field of computer vision and pattern recognition,knowledge based on images of human activity has gained popularity as a research *** recognition is the process of determining human behavior based on an *** implemented an Extended Kalman filter to create an activity recognition system *** proposed method applies an HSI color transformation in its initial stages to improve the clarity of the frame of the *** minimize noise,we use Gaussian *** of silhouette using the statistical *** use Binary Robust Invariant Scalable Keypoints(BRISK)and SIFT for feature *** next step is to perform feature discrimination using Gray *** that,the features are input into the Extended Kalman filter and classified into relevant human activities according to their definitive *** experimental procedure uses the SUB-Interaction and HMDB51 datasets to a 0.88%and 0.86%recognition rate.

关键词： Pattern recognition geometric features activity recognition full-body texture

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Towards Human-Like Machine Comprehension: Few-Shot Relational Learning in Visually-Rich Documents 30

Towards Human-Like Machine Comprehension: Few-Shot Relationa...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Wang, Hao Li, Tang Chu, Chenhui Zhu, Nengjun Wang, Rui Zhu, Pinpin School of Computer Engineering and Science Shanghai University China Graduate School of Informatics Kyoto University Japan Department of Computer Science and Engineering Shanghai Jiao Tong University China

ISBN: (纸本)9782493814104

Key-value relations are prevalent in Visually-Rich Documents (VRDs), often depicted in distinct spatial regions accompanied by specific color and font styles. These non-textual cues serve as important indicators that greatly enhance human comprehension and acquisition of such relation triplets. However, current document AI approaches often fail to consider this valuable prior information related to visual and spatial features, resulting in suboptimal performance, particularly when dealing with limited examples. To address this limitation, our research focuses on few-shot relational learning, specifically targeting the extraction of key-value relation triplets in VRDs. Given the absence of a suitable dataset for this task, we introduce two new few-shot benchmarks built upon existing supervised benchmark datasets. Furthermore, we propose a variational approach that incorporates relational 2D-spatial priors and prototypical rectification techniques. This approach aims to generate relation representations that are more aware of the spatial context and unseen relation in a manner similar to human perception. Experimental results demonstrate the effectiveness of our proposed method by showcasing its ability to outperform existing methods. This study also opens up new possibilities for practical applications. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Variational techniques

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Incorporation of Two-Fold Trust in Group Recommender system to Handle Popularity Bias

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SN computer science 2024年第2期5卷 1-15页

作者： Richa Bedi, Punam Gupta, Shivani Kumar, Ranjeet Department of Computer Science and Engineering Birla Institute of Technology Mesra Jharkhand Ranchi India Department of Computer Science University of Delhi Delhi New Delhi India School of Computer Science Engineering and Technology Vellore Institute of Technology Tamilnadu Chennai India School of Electronics Engineering Vellore Institute of Technology Tamilnadu Chennai India

In recent years, there has been a rise in work which focuses on various issues of recommender systems other than accuracy. Popularity bias is one factor that causes the list of recommendations to deviate from the user’s expectation and causes biased list to generate. This paper proposed an approach that handles the popularity bias in trust aware group recommender system using trust propagation. The proposed work considers two factors, novelty and serendipity, to evaluate the presence of bias. By incorporating trust, along with novelty, diversity, and unexpectedness, the diverse list of recommendation that maintains accuracy should be generated. Trust propagation combines trustworthy user’s opinion indirectly involves enhancing the accuracy. The trust propagation and randomness in trust propagation ensures the trade-off between the accuracy and bias of the recommendations. A prototype is developed using the tourism dataset and compared using traditional approach of recommendation using various accuracy measures and coverage. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd 2024.

关键词： Diversity Novelty Popularity bias Recommender system Relevancy

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Graph Contrastive Learning for Truth Inference 40

Graph Contrastive Learning for Truth Inference

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Liu, Hao Liu, Jiacheng Tang, Feilong Li, Peng Chen, Long Yu, Jiadi Zhu, Yanmin Gao, Min Yang, Yanqin Hou, Xiaofeng Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong East China Normal University School of Data Science and Engineering Shanghai China Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai China University of Aizu School of Computer Science and Engineering Japan Simon Fraser University School of Computing Science Canada

ISBN: (纸本)9798350317152

Crowdsourcing has become a popular paradigm for collecting large-scale labeled datasets by leveraging numerous annotators. However, these annotators often provide noisy labels due to varying expertise. Truth inference aims to infer accurate consensus labels from noisy crowdsourced annotations. Existing approaches rely heavily on hand-engineered assumptions or ground truth data, limiting their applicability. To address this, we propose GOVERN, a graph contrastive learning framework for truth inference without such external supervision. GOVERN employs a novel graph data augmentation strategy to generate views capturing worker coordination patterns. A contrastive objective then encourages invariant representations across views, enabling the discovery of features related to the hidden consensus. Further, a label correction method based on k-nearest neighbors refines noisy pseudo-labels to supervise model training. Comprehensive experiments on 9 real-world datasets demonstrate that GOVERN outperforms state-of-the-art truth inference techniques. © 2024 IEEE.

关键词： Crowdsourcing

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Faithful geometric measures for genuine tripartite entanglement

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Physical Review A 2024年第1期110卷 L010402-L010402页

作者： Xiaozhen Ge Lijun Liu Yong Wang Yu Xiang Guofeng Zhang Li Li Shuming Cheng Department of Control Science and Engineering Department of Applied Mathematics The Department of Mathematics and Computer Science State Key Laboratory for Mesoscopic Physics School of Physics Frontiers Science Center for Nano-optoelectronics and Collaborative Innovation Center of Quantum Matter Shanghai Institute of Intelligent Science and Technology Institute for Advanced Study

We present a faithful geometric picture for genuine tripartite entanglement of discrete, continuous, and hybrid quantum systems. We first find that the triangle relation Ei|jkα≤Ej|ikα+Ek|ijα holds for all subadditive bipartite entanglement measure E, all permutations under parties i,j,k, all α∈[0,1], and all pure tripartite states. Then, we rigorously prove that the nonobtuse triangle area, enclosed by side Eα with 0<α≤1/2, is a measure for genuine tripartite entanglement. Finally, it is significantly strengthened for qubits that given a set of subadditive and nonsubadditive measures, some state is always found to violate the triangle relation for any α>1, and the triangle area is not a measure for any α>1/2. Our results pave the way to study discrete and continuous multipartite entanglement within a unified framework.

关键词： Entanglement measures Quantum correlations in quantum information Quantum correlations, foundations & formalism Resource theories

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IoT Threat Mitigation: Machine Learning-Assisted Heavy Hitter Detection in P4-Enabled Networks 5

IoT Threat Mitigation: Machine Learning-Assisted Heavy Hitte...

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5th CPSSI International Symposium on Cyber-Physical systems (Applications and Theory), CPSAT 2024

作者： Hooshangi-Naghani, Mehrdad Rezaei, Negar Dolati, Mahdi Khonsari, Ahmad Rastegar, Seyed Hamed Sharif University of Technology Department of Computer Engineering Tehran Iran University of Tehran School of Electrical and Computer Engineering Iran School of Computer Science Tehran Iran Shiraz University School of Electrical and Computer Engineering Shiraz Iran

ISBN: (纸本)9798331529284

The Internet of Things (IoT) is crucial in various sectors, making IoT networks prime targets for denial of service attacks. Detecting heavy hitters-primary sources of such attacks-is essential for network security. We address this in IoT gateway networks, where direct traffic measurement faces privacy and scalability issues. Existing methods like sampling and sketch-based approaches suffer from information loss and inflexibility. We propose a two-step scheme: a Convolutional Neural Network (CNN) selects relevant gateways, followed by a tomography-based approach to identify heavy hitters. Our data collection framework uses SNMP and P4 technologies for enhanced flexibility and accuracy. Extensive numerical evaluations demonstrate the proposed algorithm's effectiveness in accurately identifying heavy hitters, despite potential estimation errors in the tomography method. © 2024 IEEE.

关键词： Convolutional neural networks

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Node Coverage and Connectivity Optimization in Heterogeneous Wireless Sensor Networks Using Improved Flower Pollination Algorithm 4

Node Coverage and Connectivity Optimization in Heterogeneous...

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4th International Conference on Ubiquitous Computing and Intelligent Information systems, ICUIS 2024

作者： Mahankali, Saritha Kesavan, R. Kalaiselvan, S.A. Saveetha School of Engineering Simats Department of Computer Science & Engineering Chennai India Vardhaman College of Engineering Department of Computer Science & Engineering Telangana India Rajalakshmi Engineering Department of Artificial Intelligence & Machine Learning Chennai India

ISBN: (纸本)9798331529635

Wireless sensor networks (WSNs) rely on energy-conserving routing protocols due to the limited power and communication capabilities. The LEACH protocol has seen extensive usage despite its homogeneous network foundation, leads inadequate signal coverage. To solve the issue, this research proposes an improved flower pollination algorithm (IFPA) improves flower pollination algorithm (FPA) addresses issues with slow convergence and local optima. This research presents an enhanced clustering technique that may be utilized in heterogeneous sensor networks. Its main feature is the ability to adjust the status of data transmission. Once the observed information intensity above the predefined threshold, the data transmission connection is initiated and data is sent to the sink by the cluster heads, which filter the perceived information. Otherwise, cluster nodes keep track of the data and wait for the next batch of nodes to provide data. The good news is that the simulation results show a network lifespan that is several times longer than the LEACH protocol. The IFPA method stands out because it increases coverage rates while drastically decreasing the cost of deploying networks. As a result, the suggested method might find many uses, helping to lower costs and improve the performance of wireless sensor networks. © 2024 IEEE.

关键词： Sensor nodes

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Security and Privacy Challenges in SDN-Enabled IoT systems: Causes, Proposed Solutions,and Future Directions

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computers, Materials & Continua 2024年第8期80卷 2511-2533页

作者： Ahmad Rahdari Ahmad Jalili Mehdi Esnaashari Mehdi Gheisari Alisa A.Vorobeva Zhaoxi Fang Panjun Sun Viktoriia M.Korzhuk Ilya Popov Zongda Wu Hamid Tahaei Institute of Artificial Intelligence Shaoxing UniversityShaoxing312000China Department of Computer Engineering Gonbad Kavous UniversityGonbad-e Kavus49717-99151Iran Faculty of Computer Engineering K.N.Toosi University of TechnologyTehran196976-4499Iran Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Secure Information Technologies Department National Research University ITMOSt.Petersburg197101Russia School of Electrical and Computer Engineering Shiraz UniversityShiraz71946–84334Iran Department of Computer Science and Engineering Islamic Azad UniversityDamavand***Iran Department of R&D Shenzhen BKD Co.Ltd.Shenzhen518000China

Software-Defined Networking(SDN)represents a significant paradigm shift in network architecture,separating network logic from the underlying forwarding devices to enhance flexibility and centralize ***-rently,the Internet of Things(IoT)connects numerous devices to the Internet,enabling autonomous interactions with minimal human ***,implementing and managing an SDN-IoT system is inherently complex,particularly for those with limited resources,as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN *** findings of this study underscore the primary security and privacy challenges across application,control,and data planes.A comprehensive review evaluates the root causes of these challenges and the defense techniques employed in prior works to establish sufficient secrecy and privacy *** investigations have explored cutting-edge methods,such as leveraging blockchain for transaction recording to enhance security and privacy,along with applying machine learning and deep learning approaches to identify and mitigate the impacts of Denial of Service(DoS)and Distributed DoS(DDoS)***,the analysis indicates that encryption and hashing techniques are prevalent in the data plane,whereas access control and certificate authorization are prominently considered in the control plane,and authentication is commonly employed within the application ***,this paper outlines future directions,offering insights into potential strategies and technological advancements aimed at fostering a more secure and privacy-conscious SDN-based IoT ecosystem.

关键词： Security privacy-preserving software-defined network internet of things

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Improving Information Delivery Effectiveness and Efficiency Using WebVR Technology 23

Improving Information Delivery Effectiveness and Efficiency ...

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8th International Conference on Sustainable Information engineering and Technology, SIET 2023

作者： Pratama, Ardiyan Nur Akbar, Muhammad Aminul Pinandito, Aryo Informatics Engineering Department Universitas Brawijaya Faculty of Computer Science Indonesia Information System Department Universitas Brawijaya Faculty of Computer Science Indonesia

ISBN: (纸本)9798400708503

In this digital era, attracting new students from outside the region to enter a college or university is difficult. This problem can be solved with good marketing and information dissemination techniques. Information is a type of data that has been processed and organized so that it has relevant meaning for the recipient. Useful information can be used to help make decisions, gain new knowledge, or solve problems. One medium for providing information is by using videos that can be uploaded to YouTube for dissemination. However, problems arise when the information depends on the point of view of the video content creator, who may not provide enough information sought by users in their videos. Virtual reality (VR) technology can be pursued as one of the solutions to overcome the lack of detail and control in videos for users to get the expected information. One of the technologies in VR that allows people to explore a three-dimensional virtual world on a web platform is the 360° WebVR technology. Since users have full control over what can be seen using WebVR, it is expected that this technology can assist users in getting deeper and detailed information related to their needs. This study aims to determine the effectiveness and efficiency of using YouTube videos and WebVR in distributing information and delivering detailed information to users. The results show that WebVR technology has the potential to provide greater control over more detailed information to users who use it, in contrast to traditional two-dimensional video playback technology. © 2023 ACM.

关键词： Virtual reality

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