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Advancements in Computing (ICAC), International Conference on

作者： A.A.B. Amarasinghe G G.M.H. Gamagedara S Pitigala K.K H.D.A. Subawickrama E Kavinga Yapa Abeywardena Kanishka Yapa Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398106

With the rising competition among pharmaceutical companies, the current drug supply chain market has become more competitive with high-quality product segments. The rapid growth of internet pharmacies has made it more difficult to standardize drug safety throughout in complex distributed supply chain networks. There is a high chance of introducing counterfeit drugs which are almost the same as the original pharmaceuticals. Due to the lack of transparency the possibility of tampering with drugs in the current manual and web-based pharmaceutical systems is extremely high. Throughout the past recent years, these counterfeit drugs were recognized as the one of major worldwide problems. This situation is worse in developing countries. The unavailability of verifying the legitimacy of drug suppliers and poor mechanisms to trace the drugs were identified as critical points that need to be resolved. SUPPLYDECK comes as a solution for the critical scenario mentioned. This solution addresses the above problems using blockchain technology, as a distributed digital ledger that ensures transparency, traceability, and security. This can show promise for solving some global supply chain management problems using smart contracts and user authentication along with IoT technology and machine learning concepts that are critically examined with this potential application.

关键词： Drugs Supply chain management Supply chains Smart contracts Manuals Machine learning Companies

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Attribute Based Federated-Reinforcement Learning Approach for Drone Authorization 1

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3rd International Conference on Machine Intelligence and Smart Systems, MISS 2023

作者： Rao, K. Rajesh Pradhan, Tribikram Krishna Prakasha, K. Bosch Global Software Technologies Private Ltd. Robert Bosch Bangalore560030 India Department of Computer Science and Engineering Tezpur University Assam Tezpur784028 India Department of Information and Communication Technology Manipal Institute of Technology MAHE Manipal576104 India

ISBN: (数字)9783031317231

ISBN: (纸本)9783031317224

Drones have become a vital part of the technology-driven world we live in today. From using it for delivering our day-to-day items to high grade military purposes, drones have spread their demands to various sectors of the economy. However, a little exploration has been done when it comes to talking about their security. Security generally comprises two aspects: authentication and authorization. While authentication is more to do with confirming the users with who they say they are, authorization is when the user’s permissions to access a resource is examined and a decision to approve or deny the access is taken by the system. This paper discusses authorization in detail using reinforcement learning and federated learning. The model is trained on a synthetic dataset, and is evaluated based on progressive validation loss (PVL), F1-Score, and a new metric called Permit Score. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Federated learning

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DPA-2:a large atomic model as a multitask learner

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npj Computational Materials 2024年第1期10卷 185-199页

作者： Duo Zhang Xinzijian Liu Xiangyu Zhang Chengqian Zhang Chun Cai Hangrui Bi Yiming Du Xuejian Qin Anyang Peng Jiameng Huang Bowen Li Yifan Shan Jinzhe Zeng Yuzhi Zhang Siyuan Liu Yifan Li Junhan Chang Xinyan Wang Shuo Zhou Jianchuan Liu Xiaoshan Luo Zhenyu Wang Wanrun Jiang Jing Wu Yudi Yang Jiyuan Yang Manyi Yang Fu-Qiang Gong Linshuang Zhang Mengchao Shi Fu-Zhi Dai Darrin M.York Shi Liu Tong Zhu Zhicheng Zhong Jian Lv Jun Cheng Weile Jia Mohan Chen Guolin Ke Weinan E Linfeng Zhang Han Wang AI for Science Institute BeijingP.R.China DP Technology BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingP.R.China State Key Lab of Processors Institute of Computing TechnologyChinese Academy of SciencesBeijingP.R.China University of Chinese Academy of Sciences BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking UniversityBeijingP.R.China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboP.R.China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of SciencesNingboP.R.China School of Electronics Engineering and Computer Science Peking UniversityBeijingP.R.China Shanghai Engineering Research Center of Molecular Therapeutics&New Drug Development School of Chemistry and Molecular EngineeringEast China Normal UniversityShanghaiP.R.China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine and Department of Chemistry and Chemical BiologyRutgers UniversityPiscatawayNJUSA Department of Chemistry Princeton UniversityPrincetonNJUSA College of Chemistry and Molecular Engineering Peking UniversityBeijingP.R.China Yuanpei College Peking UniversityBeijingP.R.China School of Electrical Engineering and Electronic Information Xihua UniversityChengduP.R.China State Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchunP.R.China Key Laboratory of Material Simulation Methods&Software of Ministry of Education College of PhysicsJilin UniversityChangchunP.R.China International Center of Future Science Jilin UniversityChangchunP.R.China Key Laboratory for Quantum Materialsof Zhejiang Province Department of PhysicsSchool of ScienceWestlake UniversityHangzhouP.R.China Atomistic Simulations Italian Institute of TechnologyGenovaItaly State Key Laboratory of Physical Chemistry of Solid Surface iChEMCollege of Chemistry and Chemical EngineeringXiame

The rapid advancements in artificial intelligence(AI)are catalyzing transformative changes in atomic modeling,simulation,and ***-driven potential energy models havedemonstrated the capability to conduct large-scale,long-duration simulations with the accuracy of ab initio electronic structure ***,the model generation process remains a bottleneck for large-scale *** propose a shift towards a model-centric ecosystem,wherein a large atomic model(LAM),pretrained across multiple disciplines,can be efficiently fine-tuned and distilled for various downstream tasks,thereby establishing a new framework for molecular *** this study,we introduce the DPA-2 architecture as a prototype for ***-trained on a diverse array of chemical and materials systemsusing a multi-task approach,DPA-2demonstrates superior generalization capabilities across multiple downstream tasks compared to the traditional single-task pre-training and fine-tuning *** approach sets the stage for the development and broad application of LAMs in molecular and materials simulation research.

关键词： DPA establishing thereby

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Design and Implementation of a Peak Picking System for MVT Digitizer

Design and Implementation of a Peak Picking System for MVT D...

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IEEE Symposium on Nuclear science (NSS/MIC)

作者： H. Lao Q. Liu Y. Ling W. Hu Y. Liu B. Ge Y. Li H. Yu Q. Xie Department of Electronic Engineering and Information Science USTC HeFei China Biomedical Engineering Department HUST WuHan China Institute of Artificial Intelligence USTC HeFei China Shenzhen Laboratory of IC Design for IOT College of Computer Science and Software Engineering Shenzhen University ShenZhen China

Multi-Voltage Threshold (MVT) digitizer is a well-known integrated digital signal processing method for new radiation detection technology in Positron Emission Tomography (PET) imaging. However, MVT may face challenges in selecting appropriate threshold voltages for scintillation pulses with a wide range of energy spans, which can limit the PET signal reconstruction performance in terms of energy and time. To address this issue, we propose incorporating peak information into the MVT method. Traditional methods of obtaining peaks using discrete components result in unacceptable high costs and power consumption, particularly in practical PET multi-channel applications. In this paper, we propose a novel 36-channel peak acquisition system chip for MVT digitizers using multi-channel multiplexing technology. We also preliminarily evaluate the multiplexed Analog to Digital Converter (ADC) performance of our design. This provides a basis for the implementation of Peak Picking-MVT in clinical PET detectors. This is expected to have a positive impact on other scintillator-based applications.

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Voice Enabled Intelligent Programming Assistant

Voice Enabled Intelligent Programming Assistant

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Advancements in Computing (ICAC), International Conference on

作者： Ravindu Wataketiya Navinda Chandrasiri Ramesh Kithsiri Hirush Malwatta Madhuka Nadeeshani Samanthi Siriwardana Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398106

In modern era where software development is of vital importance, software developers are challenged with conditions like Repetitive Strain Injury (RSI) which hinders their ability to work effectively. Furthermore, people with difficulties with using their hands also find it challenging to program in the traditional manner. As a solution, coding with one’s voice has been experimented with, but current solutions lack interactivity and are harder to use and setup leaving much room for improvement in this domain. In this research work, by using input classifier models with accuracies over 90%, intent classifiers with accuracies over 70%, code parsing and various human computer interaction techniques, we developed a conversationally interactive, programming language agnostic, easy to setup and easy to use Voice Coding Assistant. This will potentially help a global audience of programmers to achieve their goals and improve productivity and lead a healthier life. We have named the system thus developed, “Venic”.

关键词： Productivity Human computer interaction computer languages Computational modeling Programming Lead software

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A Two-Branch Fine-Grained Model Based on Attention Learning for Vehicle Recognition

SSRN

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SSRN 2023年

作者： Zhang, Xiaorui Sun, Wei Sun, Xun School of Computer and Software Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science & Technology Nanjing210044 China Wuxi Research Institute Nanjing University of Information Science & Technology Wuxi214100 China School of Automation Nanjing University of Information Science & Technology Nanjing210044 China

Attentional mechanisms are very effective in fine-grained vehicle recognition tasks. However, existing methods employs traditional probability to obtain attention and do not focus on the quality of attention learning. Therefore, a two-branch attention learning network is proposed in this paper. The proposed network uses ResNet-50 as the feature extraction network and introduces a improved attention module on the main branch to enhance the representation ability of discriminative regions of the vehicles. The other branch uses counterfactual causality to improve the quality of attention learning, and effectively guides the training process of the network through the supervision of loss function. The Meta-ACON activation function is also employed to select the activation neurons adaptively, thus enhancing the forward propagation of the network. Extensive experiments on the Stanford Cars dataset show that the method has excellent performances. © 2023, The Authors. All rights reserved.

关键词： Chemical activation

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Joint inference of multiple graphs from matrix polynomials

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The Journal of Machine Learning Research 2022年第1期23卷 3302-3336页

作者： Madeline Navarro Yuhao Wang Antonio G. Marques Caroline Uhler Santiago Segarra Department of Electrical and Computer Engineering Rice University Houston TX Institute for Interdisciplinary Information Sciences Tsinghua University and Shanghai Qi Zhi Institute Haidian District Beijing China Department of Signal Theory and Communications King Juan Carlos University Madrid Spain Department of Electrical Engineering & Computer Science Department of Institute for Data Systems and Society Massachusetts Institute of Technology Cambridge MA

Inferring graph structure from observations on the nodes is an important and popular network science task. Departing from the more common inference of a single graph, we study the problem of jointly inferring multiple graphs from the observation of signals at their nodes (graph signals), which are assumed to be stationary in the sought graphs. Graph stationarity implies that the mapping between the covariance of the signals and the sparse matrix representing the underlying graph is given by a matrix polynomial. A prominent example is that of Markov random fields, where the inverse of the covariance yields the sparse matrix of interest. From a modeling perspective, stationary graph signals can be used to model linear network processes evolving on a set of (not necessarily known) networks. Leveraging that matrix polynomials commute, a convex optimization method along with sufficient conditions that guarantee the recovery of the true graphs are provided when perfect covariance information is available. Particularly important from an empirical viewpoint, we provide high-probability bounds on the recovery error as a function of the number of signals observed and other key problem parameters. Numerical experiments demonstrate the effectiveness of the proposed method with perfect covariance information as well as its robustness in the noisy regime.

关键词： network topology inference graph signal processing spectral graph theory multi-layer graphs network diffusion processes

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MADP-IIME: malware attack detection protocol in IoT-enabled industrial multimedia environment using machine learning approach

MADP-IIME: malware attack detection protocol in IoT-enabled ...

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作者： Pundir, Sumit Obaidat, Mohammad S. Wazid, Mohammad Das, Ashok Kumar Singh, Devesh Pratap Rodrigues, Joel J. P. C. Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun 248 002 India College of Computing and Informatics University of Sharjah UAE with King Abdullah II School of Information Technology The University of Jordan Amman 11942 Jordan University of Science and Technology Beijing Beijing 100083 China Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad 500 032 India Federal University of Piauí (UFPI) PI Teresina 64049-550 Brazil Instituto de Telecomunicações Covilhã 6201-001 Portugal

Internet of Things (IoT) is one of the fastest-growing technologies. With the deployment of massive and faster mobile networks, almost every daily-use item is connected to the Internet. IoT-enabled industrial multimedia environment is used for the collection and analysis of different types of multimedia data (i.e., images, videos, audios, etc.). This multimedia data is generated by various types of smart devices like drones, robots, smart controller, smart surveillance system which are deployed for the industrial monitoring and control. The multimedia data is generated in the enormous amount which can be considered as the big data. This data is further utilized in various types of business needs for example, chances of fire accidents in the industrial plant, overall machine health, etc., which can be predicted through the application of big data analytics. Therefore, IoT-enabled industrial multimedia environment is very helpful to the concerned authorities as they come to know the important information in advance. However, all the smart devices are connected and controlled through the Internet. It further causes severe threats to the communication happens in an IoT-enabled industrial multimedia environment. It is vulnerable to various types of attacks such as replay, man-in-the-middle, impersonation, secret information leakage, sensitive information modification, and malware injection (i.e., mirai). Therefore, it is important to prevent the communication of such an environment against the different types of possible attacks. These days, the attacks performed by botnets (i.e., malware attacks such as mirai and reaper) have drawn attention to the researchers. Under the influence of such attacks, the communication of IoT-enabled industrial multimedia environment is disrupted. Moreover, the attackers may also control the smart devices remotely and can change their functionalities. Hence, we need some robust mechanism to detect the presence of the malware attacks in such

关键词： Internet of things

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Smart UML - Assignment Management Tool for UML Diagrams

Smart UML - Assignment Management Tool for UML Diagrams

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Advancements in Computing (ICAC), International Conference on

作者： D.N.H Weerasinghe K.A.T Thiwanka H.B.C Jayasith P.A.D Onella Natalie U.U. Samantha Rajapaksha Anuradha Karunasena Department of Computer Science and Software Engineering Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Information Technology Faculty of Computing Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398106

The great majority of manual processes have been automated in the current day. Nonetheless, there is no reliable approach for evaluating UML diagrams for plagiarism and correctness. Unified Modeling Language (UML) provides the basis for UML diagrams. UML Diagrams are typically used to graphically express a system’s stakeholders, activities, objects, and classes to get a deep knowledge of a particular system. UML diagrams are widely used by industry experts as well as beginners. Class diagrams and use case diagrams are the most commonly used diagrams in UML. Though most computer science-related students get assessed in UML modelling, diagram plagiarism isn’t considered in most exams since it’s a tedious task to perform. The proposed system automates capturing details in UML diagram components and generating a model answer from the given question scenario to compare the diagrams and calculate the plagiarism percentage with the correction percentage.

关键词： Industries Plagiarism Computational modeling Unified modeling language Manuals Stakeholders Reliability

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Free-space Continuous-variable Quantum Secret Sharing

arXiv

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arXiv 2025年

作者： Yang, Fangli Chang, Liang Qiu, Daowen Pan, Minghua Xiong, Wanjun Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin541004 China Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic Technology Guilin541004 China

Free-space quantum cryptography has the potential to enable global quantum communication. However, most existing continuous-variable quantum secret sharing (CV-QSS) schemes rely on fiber channels. In this paper, we present a CV-QSS protocol designed for free-space transmission and construct models of crucial parameters, including channel transmittance, excess noise, and interruption probability, thus deriving the bound of the secret key rate. In particular, we provide a multi-source excess noise model for free-space CV-QSS based on the local local oscillator (LLO) scheme and a straightforward optimization of the noise. Furthermore, our research considers the impact of atmospheric turbulence on the protocol. Simulation results demonstrate that the intensification of atmospheric turbulence adversely affects the aforementioned crucial parameters, leading to a significant reduction in the key rate. However, our protocol shows its capability to securely share secrets over a distance of exceeding 60 km among five participants in the presence of turbulence with Cn2 = 1 × 10−15m−2/3, while maintaining a high key rate of approximately 0.55 bit/pulse over a distance of 10 km across twenty participants. These findings suggest that efficient CV-QSS in free space is indeed achievable. This research may serve as a reference for the design and optimization of the practical CV-QSS system. Copyright © 2025, The Authors. All rights reserved.

关键词： Atmospheric turbulence

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