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IEEE International Conference on Systems, Man and Cybernetics

作者： Fengqi Hao Shulei Zhu Dexin Ma Xiangjun Dong Hoiio Kong Xia Liu Chunhua Mu Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center (National Supercomputer Center in Jinan) Qilu University of Technology (Shandong Academy of Sciences) Jinan China Faculty of Data Science City University of Macau Macau China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Communication College Qingdao Agricultural University Qingdao China National Engineering Laboratory of Wheat and Maize/Key Laboratory of Biology and Genetic Improvement of Maize in Northern Yellow-huai River Plain Ministry of Agriculture Maize Research Institute Shandong Academy of Agricultural Sciences Jinan China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

The seedling stage is important in the growth and development of maize, and it is also a critical period that affects maize yield and quality. Accurately recognizing this stage of maize is challenging, as current maize seedling detection methods struggle with small sizes and complex environments. This paper proposes a rapid maize seedling detection method that emphasizes spatial feature extraction in the receptive field and cross-dimensional interaction—receptive field triplet attention YOLO (RFT-YOLO). First, we design a convolutional module for cross-dimensional information interaction within the receptive field. Second, we introduce an advanced selective fusion network, which boosts the multi-scale fusion capability of small object features while reducing the GFLOPs of the model. Additionally, we employ Inner-IoU to diminish sensitivity to positional biases of small objects and expedite the convergence of the loss function. Finally, we create a dataset of maize seedlings to conduct our experiments. Experimental results demonstrate that the RFT-YOLO significantly enhances performance, reducing the number of parameters by 35.3% and GFLOPs by 14.24%, compared to the baseline model. Moreover, the mean average precision (mAP) improves from 89.6% to 91.5%. These improvements confirm the model's effectiveness in detecting maize seedlings.

关键词： YOLO Sensitivity Accuracy Semantics Feature extraction Complexity theory data mining Cybernetics Convergence

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Combining deep generative models and multi-lingual pretraining for semi-supervised document classification

arXiv

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arXiv 2021年

作者： Zhu, Yi Shareghi, Ehsan Li, Yingzhen Reichart, Roi Korhonen, Anna Language Technology Lab University of Cambridge United Kingdom Department of Data Science & AI Monash University Australia Department of Computing Imperial College London United Kingdom Faculty of Industrial Engineering and Management Technion IIT

Semi-supervised learning through deep generative models and multi-lingual pretraining techniques have orchestrated tremendous success across different areas of NLP. Nonetheless, their development has happened in isolation, while the combination of both could potentially be effective for tackling task-specific labelled data shortage. To bridge this gap, we combine semi-supervised deep generative models and multi-lingual pretraining to form a pipeline for document classification task. Compared to strong supervised learning baselines, our semi-supervised classification framework is highly competitive and outperforms the state-of-the-art counterparts in low-resource settings across several languages. Copyright © 2021, The Authors. All rights reserved.

关键词： Information retrieval systems

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Covert Communications with Enhanced Physical Layer Security in RIS-Assisted Cooperative Networks

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IEEE Transactions on Wireless Communications 2025年

作者： Li, Xingwang Liu, Musen Dang, Shuping Luong, Nguyen Cong Yuen, Chau Nallanathan, Arumugam Niyato, Dusit Henan Polytechnic University School of Physics and Electronic Information Engineering Jiaozuo454003 China Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Jiaozuo Key Laboratory of Crow-Sensing Network Jiaozuo454003 China University of Bristol School of Electrical Electronic and Mechanical Engineering BristolBS8 1UB United Kingdom Phenikaa University Faculty of Computer Science Hanoi12116 Viet Nam Nanyang Technological University Singapore School of Electrical and Electronics Engineering 639798 Singapore Queen Mary University of London School of Electronic Engineering and Computer Science London United Kingdom Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of Nanyang Technological University Singapore College of Computing and Data Science 639798 Singapore

Reconfigurable intelligent surface (RIS) and ambient backscatter communication (AmBC) technologies are recognized for their programmability and high energy efficiency respectively, which will be the key parts of the future sixth generation (6G) mobile communication technology. The combination of the two technologies can improve communication security by reducing the probability of detection and decoding through enhanced transmission and backscatter transmission in different communication slots. In this paper, a dual-function RIS that supports cooperative relaying for covert communications is proposed. It operates in different communication slots (enhanced transmission slot and backscatter slot), but the performance is affected by phase errors due to function switching. A source covertly communicates with an intended destination via the help of RIS and cooperative relay. There is an illegal monitor aims to detect and eavesdrop the covert message. For this system, the outage probability (OP), intercept probability (IP), and detection error probability (DEP) in different communication slots are derived to examine the system reliability and security. Moreover, the system security probability (SSP) is proposed, and a block coordinated ascent (BCA)-based iterative algorithm is used to jointly optimize the power allocation coefficients to maximize the SSP. Simulation results show that increasing the number of elements can improve the security performance and mitigate the negative impact of RIS phase errors. © 2002-2012 IEEE.

关键词： Mobile telecommunication systems

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Distinguishing unitary gates on the IBM quantum processor

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science China(Information sciences) 2019年第7期62卷 210-216页

作者： Shusen LIU Yinan LI Runyao DUAN School of Data and Computer Science Sun Yat-sen University Centre for Quantum Software and Information Faculty of Engineering and Information TechnologyUniversity of Technology Sydney Centrum Wiskunde & Informatica and Research Center for Quantum Software Institute for Quantum Computing

An unknown unitary gate, which is secretly chosen from several known ones, can always be distinguished perfectly. In this paper, we implement such a task on IBM's quantum processor. More precisely,we experimentally demonstrate the discrimination of two qubit unitary gates, the identity gate and the 2/3π-phase shift gate, using two discrimination schemes — the parallel scheme and the sequential scheme. We program these two schemes on the ibmqx4, a 5-qubit superconducting quantum processor via IBM cloud,with the help of the QSI modules. We report that both discrimination schemes achieve success probabilities at least 85%.

关键词： quantum experiment IBM quantum computer software-aided quantum experiment sequential schemes for unitary discrimination parallel schemes for unitary discrimination

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Hybrid AI- and Blockchain-Powered Secure Internet Hospital Communication and Anomaly Detection in Smart Cities

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Processes 2025年第5期13卷 1466-1466页

作者： Xiaofeng Wang Xiaoguang Yue Noshina Tariq Ahthasham Sajid College of Management Shenzhen University Shenzhen 518060 China Department of Artificial Intelligence and Data Science National University of Computer and Emerging Sciences Islamabad 44000 Pakistan Department of Information Security and Data Science Riphah Institute of Systems Engineering Riphah International University Islamabad 46000 Pakistan Faculty of Computing and Informatics Multimedia University Cyberjaya 63100 Malaysia

Internet of Things (IoT) devices have revolutionized real-time monitoring and distant patient care in smart cities’ healthcare systems. However, this advancement has come with several issues, such as data security, scalability, operational efficiency, and fault tolerance. Previous approaches are not well suited to the real-time processing of IoT data in healthcare, given the low latency, high throughput, and effective anomaly detection needed for such a task. Given these challenges, this paper proposes a hybrid Artificial Intelligence (AI)- and blockchain-based IoT governance framework for Internet hospitals using Proof-of-Authority (PoA) in smart cities. It encompasses application of the enhanced RSA for secure data transmission, real-time anomaly detection through the Isolation Forest algorithm, and a private blockchain architecture designed for high scalability. It effectively detects tampering and replay attacks to minimize illegitimate and unauthorized access or manipulation of patients’ data. The proposed framework achieves relatively significant improvements over a state-of-the-art baseline model. It has cut the transaction response time by 50%, doubled the Throughput Per Second (TPS), and attained a 100% detection performance in anomalies. Comparative analysis reveals its linear scalability with increasing workload, ensuring consistent performance under varying transaction volumes. This study’s findings highlight the proposed framework’s potential to mitigate key issues in IoT-enabled Internet hospitals in smart cities.

关键词： anomaly detection blockchain distributed role-based access control electronic health records internet hospital internet of things isolation forest algorithm smart cities proof-of-authority Rivest–Shamir–Adleman (RSA)

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Virtual Reality: A Survey of Enabling Technologies and its Applications in IoT

arXiv

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arXiv 2021年

作者： Hu, Miao Luo, Xianzhuo Chen, Jiawen Lee, Young Choon Zhou, Yipeng Wu, Di School of Computer Science and Engineering Sun Yat-sen University Guangzhou510275 China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou510006 China Department of Computing Faculty of Science and Engineering Macquarie University SydneyNSW2109 Australia

Virtual Reality (VR) has shown great potential to revolutionize the market by providing users immersive experiences with freedom of movement. Compared to traditional video streaming, VR is with ultra high-definition and dynamically changes with users’ head and eye movements, which poses significant challenges for the realization of such potential. In this paper, we provide a detailed and systematic survey of enabling technologies of virtual reality and its applications in Internet of Things (IoT). We identify major challenges of virtual reality on system design, view prediction, computation, streaming, and quality of experience evaluation. We discuss each of them by extensively surveying and reviewing related papers in the recent years. We also introduce several use cases of VR for IoT. Last, issues and future research directions are also identified and discussed. Copyright © 2021, The Authors. All rights reserved.

关键词： Virtual reality

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PlantMWpIDB: a database for the molecular weight and isoelectric points of the plant proteomes

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Scientific Reports 2022年第1期12卷 1-7页

作者： Mohanta, Tapan Kumar Kamran, Muhammad Shahzad Omar, Muhammad Anwar, Waheed Choi, Gyu Sang Natural and Medical Sciences Research Center University of Nizwa Nizwa 616 Oman Department of Computer Science and IT The Islamia University of Bahawalpur Bahawalpur Pakistan Department of Data Science Faculty of Computing The Islamia University of Bahawalpur Bahawalpur Pakistan Department of Information and Communication Engineering Yeungnam University 214-1 Gyeongsan-si 712-749 South Korea

The molecular weight and isoelectric point of the proteins are very important parameters that control their subcellular localization and subsequent function. Although the genome sequence data of the plant kingdom improved enormously, the proteomic details have been poorly elaborated. Therefore, we have calculated the molecular weight and isoelectric point of the plant proteins and reported them in this database. A database, PlantMWpIDB, containing protein data from 342 plant proteomes was created to provide information on plant proteomes for hypothesis formulation in basic research and for biotechnological applications. The Molecular weight and isoelectric point (pI) are important molecular parameters of proteins that are useful when conducting protein studies involving 2D gel electrophoresis, liquid chromatography-mass spectrometry, and X-ray protein crystallography. PlantMWpIDB provides an easy-to-use and efficient interface for search options and generates a summary of basic protein parameters. The database represents a virtual 2D proteome map of plants, and the molecular weight and pI of a protein can be obtained by searching on the name of a protein, a keyword, or by a list of accession numbers. The PlantMWpIDB database also allows one to query protein sequences. The database can be found in the following link https://***/. The individual 2D virtual proteome map of the plant kingdom will enable us to understand the proteome diversity between different species. Further, the molecular weight and isoelectric point of individual proteins can enable us to understand their functional significance in different species. © 2022, The Author(s).

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Email Spam Classification Based on Deep Learning Methods: A Review

Iraqi Journal for Computer Science and Mathematics

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Iraqi Journal for Computer science and Mathematics 2025年第1期6卷

作者： Tusher, Ekramul Haque Ismail, Mohd Arfian Raffei, Anis Farihan Mat Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pekan26600 Malaysia Center of Excellence for Artificial Intelligence & Data Science Universiti Malaysia Pahang Al-Sultan Abdullah Lebuhraya Tun Razak Gambang26300 Malaysia

Email spam is a significant issue confronting both email consumers and providers. The evolution of spam filtering has progressed considerably, transitioning from basic rule-based filters to more sophisticated machine learning algorithms. Deep learning has become a potent collection of techniques for addressing intricate issues such as spam classification in recent times. A thorough literature evaluation is required to have a comprehensive overview of the current research on utilizing deep learning methods for email spam classification. This review aims to identify the various deep learning techniques used for email spam, their effectiveness, and areas for future research. By synthesizing the outcomes of pertinent studies, this review delineates the strengths and drawbacks of various approaches, offering valuable insights into the challenges that must be tackled to enhance the precision and efficacy of email spam classification. © 2025 The Author(s).

关键词： Deep learning

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Randomizing hypergraphs preserving degree correlation and local clustering

arXiv

引用

arXiv 2021年

作者： Nakajima, Kazuki Shudo, Kazuyuki Masuda, Naoki Department of Mathematical and Computing Science Tokyo Institute of Technology Japan Department of Mathematics State University of New York Buffalo United States Computational and Data-Enabled Science and Engineering Program State University of New York Buffalo United States Faculty of Science and Engineering Waseda University Japan

Many complex systems involve direct interactions among more than two entities and can be represented by hypergraphs, in which hyperedges encode higher-order interactions among an arbitrary number of nodes. To analyze structures and dynamics of given hypergraphs, a solid practice is to compare them with those for randomized hypergraphs that preserve some specific properties of the original hypergraphs. In the present study, we propose a family of such reference models for hypergraphs, called the hyper dk-series, by extending the so-called dk-series for dyadic networks to the case of hypergraphs. The hyper dk-series preserves up to the individual node’s degree, node’s degree correlation, node’s redundancy coefficient, and/or the hyperedge’s size depending on the parameter values. Furthermore, we numerically find that higher-order hyper dk-series more accurately preserves the shortest path length and degree distribution of the one-mode projection of the original hypergraph, which the method does not intend to preserve. We also apply the hyper dk-series to numerical simulations of epidemic spreading and evolutionary game dynamics on empirical social hypergraphs. We find that the hyperedge’s size affects these dynamics more than any of the node’s properties and that the node’s degree correlation and redundancy in the empirical hypergraphs promote cooperation. Copyright © 2021, The Authors. All rights reserved.

关键词： Redundancy

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Application of MOOC and Virtual Simulation Experiment in Experimental Teaching of Mechanical Design

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Forest Chemicals Review 2021年第JULY-AUGUST期2021卷 318-329页

作者： Han, Shaoyong Zhan, Jingchun Wang, Zhen School of Information Engineering and Technology Changzhou Institute of Industry Technology Jiangsu Changzhou China School of Computing Faculty of Engineering Universiti Teknologi Malaysia Johor Johor Bahru Malaysia School of Data Science and Artificial Intelligence Wenzhou University of Technology Zhejiang Wenzhou China

The mechanical design experiment is a comprehensive experimental course that can cultivate the preliminary engineering practice ability of machinery students. Due to the high requirements for students' basic knowledge and ability of comprehensive application of knowledge, teaching is difficult and the teaching effect is general. This paper uses the MOOC teaching method, a new network-based teaching model, to study the experimental teaching of mechanical design and the construction of virtual simulation experiment teaching system under the new situation. Firstly, analyze the advantages in experimental teaching of mechanical design under virtual simulation experiment. Secondly, it puts forward suggestions for constructing the virtual simulation experiment teaching system of mechanical design, and discusses the advantages of the combination of MOOC and virtual simulation experiment technology, opportunities and reforms under the new situation. Lastly, it can be concluded that by using MOOC and virtual simulation experiments can break through the limitations of traditional teaching and improve teaching. This paper applies the MOOC and virtual simulation experiment to the experimental teaching of mechanical design, can not only improve the teaching of teachers, but also cultivate the practical ability and thinking innovation ability of machinery students. With the advantages of MOOC and virtual simulation experiments, it provides better opportunities and challenges for the teaching of mechanical design. © 2021 Kriedt Enterprises Ltd. All Rights Reserved.

关键词： Teaching

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