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Monocular 3D object detection with Pseudo-LiDAR confidence sampling and hierarchical geometric feature extraction in 6G network

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Digital Communications and Networks 2023年第4期9卷 827-835页

作者： Jianlong Zhang Guangzu Fang Bin Wang Xiaobo Zhou Qingqi Pei Chen Chen School of Electronic Engineering Xidian UniversityXi'an710071China School of Computer Science and Technology College of Intelligence and ComputingTianjin UniversityTianjin300000China School of Telecommunications Engineering Xidian UniversityXi'an710071China

The high bandwidth and low latency of 6G network technology enable the successful application of monocular 3D object detection on vehicle *** 3D-object-detection-based Pseudo-LiDAR is a low-cost,lowpower solution compared to LiDAR solutions in the field of autonomous ***,this technique has some problems,i.e.,(1)the poor quality of generated Pseudo-LiDAR point clouds resulting from the nonlinear error distribution of monocular depth estimation and(2)the weak representation capability of point cloud features due to the neglected global geometric structure features of point clouds existing in LiDAR-based 3D detection ***,we proposed a Pseudo-LiDAR confidence sampling strategy and a hierarchical geometric feature extraction module for monocular 3D object *** first designed a point cloud confidence sampling strategy based on a 3D Gaussian distribution to assign small confidence to the points with great error in depth estimation and filter them out according to the ***,we present a hierarchical geometric feature extraction module by aggregating the local neighborhood features and a dual transformer to capture the global geometric features in the point ***,our detection framework is based on Point-Voxel-RCNN(PV-RCNN)with high-quality Pseudo-LiDAR and enriched geometric features as *** the experimental results,our method achieves satisfactory results in monocular 3D object detection.

关键词： Monocular 3D object detection Pseudo-LiDAR Confidence sampling Hierarchical geometric feature extraction

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Stereoselective recognition of morphine enantiomers by μ-opioid receptor

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National science Review 2024年第3期11卷 183-191页

作者： Yibo Wang Van A.Ngo Xiaohui Wang Laboratory of Chemical Biology Changchun Institute of Applied ChemistryChinese Academy of Sciences Advanced Computing for Life Sciences and Engineering Group Science Engagement Section National Center for Computational Sciences Oak Ridge National Lab School of Applied Chemistry and Engineering University of Science and Technology of China Beijing National Laboratory for Molecular Sciences

Stereospecific recognition of chiral molecules plays a crucial role in biological systems. The μ-opioid receptor（MOR） exhibits binding affinity towards（-）-morphine, a well-established gold standard in pain management, while it shows minimal binding affinity for the（+）-morphine enantiomer, resulting in a lack of analgesic activity. Understanding how MOR stereoselectively recognizes morphine enantiomers has remained a puzzle in neuroscience and pharmacology for over half-a-century due to the lack of direct observation techniques. To unravel this mystery, we constructed the binding and unbinding processes of morphine enantiomers with MOR via molecular dynamics simulations to investigate the thermodynamics and kinetics governing MOR's stereoselective recognition of morphine enantiomers. Our findings reveal that the binding of（-）-morphine stabilizes MOR in its activated state, exhibiting a deep energy well and a prolonged residence time. In contrast,（+）-morphine fails to sustain the activation state of ***, the results suggest that specific residues, namely D1142.50and D1473.32, are deprotonated in the active state of MOR bound to（-）-morphine. This work highlights that the selectivity in molecular recognition goes beyond binding affinities, extending into the realm of residence time.

关键词： stereoselective recognition thermodynamics and kinetics residence time morphine enantiomers μ-opioid receptor

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Intelligent patient monitoring through hybrid consensus algorithm based blockchain technology

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Multimedia Tools and Applications 2025年第18期84卷 19579-19600页

作者： Priyadharshini, A. Nithiya, S. Archana, H.A. Jaganathan, Subash Chandra Bose School of Engineering and Technology Bangaluru India Department of Computing Technology SRM Institute of Science and Technology Kattankulathur603203 India Department of Agronomy SRM College of Agricultural Science Chengalpattu603201 India School of Computing Science Engineering and Artificial Intelligence VIT Bhopal University Bhopal-Indore Highway Kothrikalan Madhya Pradesh Sehore466114 India

This research aims to integrate IoT with blockchain technology to securely manage and monitor sensitive patient health data in critical care environments, thereby improving the reliability and efficiency of patient monitoring systems. A hybrid blockchain architecture is employed to store ICU patient data securely, linking each patient's information with their respective doctors' details. This system operates without third-party intermediaries, ensuring trusted communication channels between patients and doctors. The blockchain ensures authorized access and secure transmission of medical histories and treatment plans, even allowing for remote care by doctors outside hospital premises. The integration of blockchain technology with IoT devices facilitates rapid and secure data transmission, enhancing the speed and accuracy of critical care delivery. The decentralized nature of blockchain ensures data integrity and prevents unauthorized access, while the hybrid approach allows for efficient and trusted collaboration among healthcare professionals. By harnessing the power of hybrid blockchain technology, this system not only safeguards sensitive medical information but also improves the overall quality of critical care through timely and informed medical intervention. The proposed solution holds the promise of reducing patient mortality rates by ensuring secure, efficient, and collaborative healthcare delivery. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Blockchain

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Topological phase transitions and Majorana zero modes induced by the periodic potential in an antiferromagnetic chain

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Communications in Theoretical Physics 2023年第8期75卷 156-162页

作者： K W Shen Q Chen College of Physics and Mechanical&Electrical Engineering Jishou UniversityJishou 416000China School of Computational Science and Electronics Hunan Institute of EngineeringXiangtan 411104China

We investigate the topological properties of an antiferromagnetic(AFM)chain with an on-site periodic potential,considering the intrinsic spin–orbit coupling and an external Zeeman field along with the *** results indicate that Majorana zero modes(MZMs)can be observed by adjusting the strength of the periodic *** have calculated the energy spectrum,the wave-function and transport properties,and all these results support the existence of MZMs in the AFM ***,multiple topological phase transitions occur as the strength of the periodic potential changes,and several regions support MZMs.

关键词： AFM chain Majorana zero modes topological phase transitions periodic potential

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A Domain Decomposition Method for Nonconforming Finite Element Approximations of Eigenvalue Problems

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Communications on Applied Mathematics and Computation 2025年第2期7卷 606-636页

作者： Qigang Liang Wei Wang Xuejun Xu School of Mathematical Science Tongji UniversityShanghai200092China Key Laboratory of Intelligent Computing and Applications(Tongji University) Ministry of EducationShanghai200092China LSEC Institute of Computational Mathematics and Scientific/Engineering ComputingAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China

Since the nonconforming finite elements(NFEs)play a significant role in approximating PDE eigenvalues from below,this paper develops a new and parallel two-level preconditioned Jacobi-Davidson(PJD)method for solving the large scale discrete eigenvalue problems resulting from NFE discretization of 2mth(m=1.2)order elliptic eigenvalue *** a spectral projection on the coarse space and an overlapping domain decomposition(DD),a parallel preconditioned system can be solved in each iteration.A rigorous analysis reveals that the convergence rate of our two-level PJD method is optimal and *** results supporting our theory are given.

关键词： PDE eigenvalue problems Nonconforming finite elements(NFEs) Preconditioned Jacobi-Davidson(PJD)method Overlapping domain decomposition(DD)

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Parameter-efficient fine-tuning of pre-trained code models for just-in-time defect prediction

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Neural computing and Applications 2024年第27期36卷 16911-16940页

作者： Abu Talib, Manar Bou Nassif, Ali Azzeh, Mohammad Alesh, Yaser Afadar, Yaman Department of Computer Science College of Computing and Informatics University of Sharjah Sharjah United Arab Emirates Department of Computer Engineering College of Computing and Informatics Sharjah United Arab Emirates King Hussein School for Computing Sciences Princess Sumaya University for Technology Amman Jordan

Software engineering workflows use version control systems to track changes and handle merge cases from multiple contributors. This has introduced challenges to testing because it is impractical to test whole codebases to ensure each change is defect-free, and it is not enough to test changed files alone. Just-in-time software defect prediction (JIT-SDP) systems have been proposed to solve this by predicting the likelihood that a code change is defective. Numerous techniques have been studied to build such JIT software defect prediction models, but the power of pre-trained code transformer language models in this task has been underexplored. These models have achieved human-level performance in code understanding and software engineering tasks. Inspired by that, we modeled the problem of change defect prediction as a text classification task utilizing these pre-trained models. We have investigated this idea on a recently published dataset, ApacheJIT, consisting of 44k commits. We concatenated the changed lines in each commit as one string and augmented it with the commit message and static code metrics. Parameter-efficient fine-tuning was performed for 4 chosen pre-trained models, JavaBERT, CodeBERT, CodeT5, and CodeReviewer, with either partially frozen layers or low-rank adaptation (LoRA). Additionally, experiments with the Local, Sparse, and Global (LSG) attention variants were conducted to handle long commits efficiently, which reduces memory consumption. As far as the authors are aware, this is the first investigation into the abilities of pre-trained code models to detect defective changes in the ApacheJIT dataset. Our results show that proper fine-tuning improves the defect prediction performance of the chosen models in the F1 scores. CodeBERT and CodeReviewer achieved a 10% and 12% increase in the F1 score over the best baseline models, JITGNN and JITLine, when commit messages and code metrics are included. Our approach sheds more light on the abilities of l

关键词： Forecasting

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Delay-CJ:A novel cryptojacking covert attack method based on delayed strategy and its detection

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Digital Communications and Networks 2023年第5期9卷 1169-1179页

作者： Guangquan Xu Wenyu Dong Jun Xing Wenqing Lei Jian Liu Lixiao Gong Meiqi Feng Xi Zheng Shaoying Liu Big Data School Qingdao Huanghai UniversityQingdao266427China College of Intelligence and Computing Tianjin UniversityTianjin300350China School of Computing Macquarie UniversityNSW2109Australia Graduate School of Advanced Science and Engineering Hiroshima UniversityJapan

Cryptojacking is a type of resource embezzlement attack,wherein an attacker secretly executes the cryptocurrency mining program in the target host to gain *** has been common since 2017,and in fact,it once became the greatest threat to network *** better prove the attack ability the harm caused by cryptojacking,this paper proposes a new covert browser-based mining attack model named Delay-CJ,this model was deployed in a simulation environment for *** on the general framework of cryptojacking,Delay-CJ adds hybrid evasion detection techniques and applies the delayed execution strategy specifically for video websites in the prototype *** results show that the existing detection methods used for testing may become invalid as result of this *** view of this situation,to achieve a more general and robust detection scheme,we built a cryptojacking detection system named CJDetector,which is based on cryptojacking process ***,it identifies malicious mining by monitoring CPU usage and analyzing the function call *** system not only effectively detects the attack in our example but also has universal *** recognition accuracy of CJDetector reaches 99.33%.Finally,we tested the web pages in Alexa 50K websites to investigate cryptojacking activity in the real *** found that although cryptojacking is indeed on the decline,it remains a part of network security threats that cannot be ignored.

关键词： Cryptojacking Evasion techniques Delayed strategy Cryptocurrency mining Behavior-based detection

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SMART AGRICULTURE: INTEGRATING AIR QUALITY MONITORING WITH DEEP LEARNING FOR PROCESS OPTIMIZATION*

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Scalable computing 2025年第3期26卷 1005-1016页

作者： Shobana, J. Subramanian, A Venkata Balamurugan, P. Perumal, Sivakumar Sankari, V. Eldho, K.J. Nareshkumar, R. Department of Data Science and Business Systems School of Computing College of Engineering and Technology SRM Institute of Science and Technology Tamilnadu Kattankulathur India Department of Computer Science and Engineering GITAM University Bengaluru India Department of Computer Science and Engineering J N N Institute of Enginering India Saveetha university Chennai India Department of Computer Science and Engineering Sasi Institute of Technology and Engineering Andhra Pradesh Tadepalligudem India Department of Artificial Intelligence and Data Science K.Ramakrishnan College of Engineering Kariyamanickam Rd Tamil Nadu Samayapuram India PG and Research Department of Computer Science Mary Matha Arts and Science College Kerala Mananthavady India Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Tamilnadu Kattankulathur India

Modernization and intense industrialization have led to a substantial improvement in people’s quality of life. However, the aspiration for achieving an improved quality of life results in environmental contamination. A primary consequence of environmental degradation is air pollution, resulting from rising levels of poisonous chemicals in the atmosphere, which may induce detrimental health conditions in humans. It is harmful to both humans and agriculture. Given that the effects of air pollution on plants may not be readily apparent, it is important to analyse the necessary data and compute the outcomes. Farmers prioritise on pests and plant diseases, frequently neglecting the detrimental impacts of air pollution. Some plant species can withstand high amounts of pollution from suspended particulate matter and accumulated gases, while others are more susceptible to harm. Therefore, plants’ reaction to air pollution is influenced by the kind of harmful compounds, their levels, and the plant’s susceptibility to them. The LSTM +CNN Proposed Ensemble method may be used to analyse the impact of air pollution on agriculture by examining trends in crop production over time and predicting which crop is more resistant based on the pollution data. The initiative created for this aim may assist farmers in determining the most suitable crop to cultivate in their fields to minimize the impact of air pollution on agricultural yield. The findings show deep learning algorithms correctly predict hourly pollutant concentrations such as carbon monoxide, sulphur dioxide, nitrogen dioxide, ground-level ozone, and particulate matter 2.5, along with the hourly Air Quality Index (AQI) for California. A proposed model used test RMSE values as a measure to evaluate prediction performance, achieving the best possible results. © 2025 SCPE.

关键词： Nitrogen oxides

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Designing for Security: A Model for Aged Users’ Mobile Banking Applications in South Africa 1

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3rd International Conference on Advances in computing Research, ACR 2025

作者： Goronga, Rumbidzai Da Veiga, Adéle Lotriet, Hugo School of Computing College of Science Engineering and Technology University of South Africa Pretoria South Africa

ISBN: (数字)9783031876479

ISBN: (纸本)9783031876462

Aged users face unique challenges as they use mobile banking applications, and financial institutions must adapt and include security in the design of mobile banking applications to cater to the unique needs of this demographic. Aging can result in physical challenges and disabilities that impact the use of mobile banking applications;however, these are not the only factors that could affect the usage of mobile banking applications by aged users. Multiple security factors need to be considered. By segmenting the aged by physical impairments and challenges, mobile banking application design possibilities for the aged are not fully realized. This paper proposes a conceptual model for mobile banking applications for aged users in South Africa. The conceptual model is derived from an analysis of current literature and is founded on the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2), which may provide insights for designing secure mobile banking applications for aged users. A scoping literature review was carried out using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, which involved the analysis of a total of 15 articles. The review of the existing literature indicated that limited research existed that examined the factors that impact the security of mobile banking applications for aged users in South Africa. Therefore, the conceptualized model could serve as a reference for the investigation of aged users’ perceptions of the security of mobile banking applications, which could inform the design of secure mobile banking applications for aged users. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Computer aided design

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Precise trajectory tracking of mecanum-wheeled omnidirectional mobile robots via a novel fixed-time sliding mode control approach

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Control Theory and Technology 2024年第4期22卷 596-611页

作者： Zhe Sun Zhipeng Li Hao Xie Yunjun Zheng Jinchuan Zheng Bo Chen College of Information Engineering Zhejiang University of TechnologyHangzhou310023China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthorn3122VICAustralia School of Mechanical Engineering Hefei University of TechnologyHefei230009AnhuiChina

This paper proposes a novel fixed-time sliding mode control approach for trajectory-tracking tasks of a mecanum-wheeled omnidirectional mobile ***,the idea of two-phase attractors is introduced into the domain of sliding mode control,and a new fixed-time sliding surface is ***,according to this sliding surface,a new type of nonsingular fast terminal sliding mode control algorithm is designed for the omnidirectional mobile robot,which can realize a fast fixed-time convergence *** stability of the control system is proven scrupulously,and a guideline for control-parameter tuning is ***,experiments are implemented to test the trajectory-tracking performance of the *** results demonstrate the superiority of the proposed sliding surface and the corresponding control scheme in comparison with benchmark controllers.

关键词： Omnidirectional mobile robot Trajectory tracking Sliding mode control Fixed-time convergence

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