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Enabling end-to-end digital carbon emission tracing with shielded NFTs

Energy Informatics 2022年第1期5卷 1-21页

作者： Babel, Matthias Gramlich, Vincent Körner, Marc-Fabian Sedlmeir, Johannes Strüker, Jens Zwede, Till FIM Research Center University of Bayreuth Wittelsbacherring 10 Bayreuth95447 Germany Branch Business and Information Systems Engineering of Fraunhofer FIT Wittelsbacherring 10 Bayreuth95447 Germany

In the energy transition, there is an urgent need for decreasing overall carbon emissions. Against this background, the purposeful and verifiable tracing of emissions in the energy system is a crucial key element for promoting the deep decarbonization towards a net zero emission economy with a market-based approach. Such an effective tracing system requires end-to-end information flows that link carbon sources and sinks while keeping end consumers’ and businesses’ sensitive data confidential. In this paper, we illustrate how non-fungible tokens with fractional ownership can help to enable such a system, and how zero-knowledge proofs can address the related privacy issues associated with the fine-granular recording of stakeholders’ emission data. Thus, we contribute to designing a carbon emission tracing system that satisfies verifiability, distinguishability, fractional ownership, and privacy requirements. We implement a proof-of-concept for our approach and discuss its advantages compared to alternative centralized or decentralized architectures that have been proposed in the past. Based on a technical, data privacy, and economic analysis, we conclude that our approach is a more suitable technical backbone for end-to-end digital carbon emission tracing than previously suggested solutions. © 2022, The Author(s).

关键词： Carbon

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Minimally Disruptive Cooperative Lane-change Maneuvers

arXiv

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arXiv 2023年

作者： Chalaki, Behdad Tadiparthi, Vaishnav Mahjoub, Hossein Nourkhiz D'Sa, Jovin Moradi-Pari, Ehsan Armijos, Andres S. Chavez Li, Anni Cassandras, Christos G. Ann ArborMI48103 United States The Division of Systems Engineering Center for Information and Systems Engineering Boston University BrooklineMA02446 United States

A lane-change maneuver on a congested highway could be severely disruptive or even infeasible without the cooperation of neighboring cars. However, cooperation with other vehicles does not guarantee that the performed maneuver will not have a negative impact on traffic flow unless it is explicitly considered in the cooperative controller design. In this letter, we present a socially compliant framework for cooperative lane-change maneuvers for an arbitrary number of CAVs on highways that aims to interrupt traffic flow as minimally as possible. Moreover, we explicitly impose feasibility constraints in the optimization formulation by using reachability set theory, leading to a unified design that removes the need for an iterative procedure used in prior work. We quantitatively evaluate the effectiveness of our framework and compare it against previously offered approaches in terms of maneuver time and incurred throughput disruption. © 2023, CC BY-NC-ND.

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Learning Feasibility Constraints for Control Barrier Functions

Learning Feasibility Constraints for Control Barrier Functio...

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European Control Conference (ECC)

作者： Wei Xiao Christos G. Cassandras Calin A. Belta Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology Division of Systems Engineering and Center for Information and Systems Engineering Boston University Brookline MA USA

It has been shown that optimizing quadratic costs while stabilizing affine control systems to desired (sets of) states subject to state and control constraints can be reduced to a sequence of Quadratic Programs (QPs) by using Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs). In this paper, we employ machine learning techniques to ensure the feasibility of these QPs, which is a challenging problem, especially for high relative degree constraints where High Order CBFs (HOCBFs) are required. To this end, we propose a sampling-based learning approach to learn a new feasibility constraint for CBFs; this constraint is then enforced by another HOCBF added to the QPs. The accuracy of the learned feasibility constraint is recursively improved by a recurrent training algorithm. We demonstrate the advantages of the proposed learning approach to constrained optimal control problems with specific focus on a robot control problem and on autonomous driving in an unknown environment.

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GemmaWithLoRA: A New Approach to Click Fraud Detection

GemmaWithLoRA: A New Approach to Click Fraud Detection

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2024 IEEE International Conference on Communications, Computing, Cybersecurity and Informatics, CCCI 2024

作者： Dai, Bingzhou Wang, Lei Zhao, Xiaoyong Guo, Yu Obaidat, Mohammad S. School of Information Management Beijing Information Science & Technology University Beijing China Information Systems Institute Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Information Science & Technology University Beijing China Beijing Advanced Innovation Center for Materials Genome Engineering and Shunde Innovation School University of Science and Technology Beijing China King Abdullah II School of Information Technology University of Jordan School of Engineering Amity University School of Computing SRM University Amman Jordan

ISBN: (纸本)9798350349832

With the rapid development of artificial intelligence technology, pre-Trained large language models (LLMs) have demonstrated their powerful application potential in various fields. Click fraud is a serious issue in the digital advertising ecosystem, especially in the pay-per-click (PPC) model, where fraudulent activities significantly undermine the effectiveness of ads and pose security risks. While many traditional fraud detection methods have achieved relatively good accuracy, they still face poor generalization and extensive feature engineering issues. This paper explores using LLMs for click fraud detection by leveraging the powerful feature extraction capabilities and superior generalization performance of the Gemma-2b model, combined with LoRA fine-Tuning technology. Extensive experiments on the TalkingData2017 dataset showed that accuracy was achieved at 83°/0, demonstrating the effectiveness of LLMs in click fraud detection tasks. © 2024 IEEE.

关键词： Crime

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All-Polarization-Maintaining L-Band Fiber Ring Laser Mode-Locked by Nonlinear Polarization Rotation

All-Polarization-Maintaining L-Band Fiber Ring Laser Mode-Lo...

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2023 Asia Communications and Photonics Conference/2023 International Photonics and Optoelectronics Meetings, ACP/POEM 2023

作者： Ye, Guanyu Chow, Kin Kee Dai, Maolin Shirahata, Takuma Yamashita, Shinji Set, Sze Yun Research Center for Advanced Science and Technology The University of Tokyo Tokyo Japan Manchester Metropolitan University Department of Engineering Manchester United Kingdom The University of Tokyo Department of Electrical Engineering and Information Systems Tokyo Japan

We report the first all-polarization maintaining (all-PM) nonlinear polarization rotation (NPR) mode-locked fiber ring laser in the all-anomalous dispersion regime. The laser generates pulses at 1575 nm with a 5 nm sp... 详细信息

ISBN: (纸本)9798350312614

关键词： all-polarization maintaining fiber laser mode-locked nonlinear polarization rotation

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Performance of AI-Empowered Anti-Jamming Communications under Hardware Impairments

Performance of AI-Empowered Anti-Jamming Communications unde...

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2024 IEEE Middle East Conference on Communications and Networking, MECOM 2024

作者： Arif, Muhammad Shahzad Muhaidat, Sami Argyriou, Antonios Sofotasios, Paschalis C. Khalifa University Department of Computer and Information Engineering Abu Dhabi United Arab Emirates Khalifa University KU 6G Center Department of Computer and Information Engineering Abu Dhabi United Arab Emirates Carleton University Department of Systems and Computer Engineering Ottawa Canada University of Thessaly Department of Electrical and Computer Engineering Volos Greece Khalifa University KU C2PS and 6G Center Department of Computer and Information Engineering Abu Dhabi United Arab Emirates Tampere University Department of Electrical Engineering Tampere Finland

ISBN: (纸本)9798350376715

The present contribution quantifies the effect of Hardware Imperfections (HWI) on Artificial Intelligence (AI)empowered anti-jamming wireless communication scenarios. To that end, we consider an AI-empowered wireless link that employs reinforcement learning (RL) to counteract reactive jamming attacks. It is shown that contrary to the common belief that HWI always degrade the performance of wireless systems, our findings reveal that imperfections in the jammer's spectrum sensing capability can actually enhance its effectiveness against AI-empowered anti-jamming wireless communications. Extensive simulations demonstrate that a non-ideal reactive jammer with detection errors (e.g., false alarms and miss-detections) can perform significantly better than an ideal reactive jammer while using the same jamming resources. This improvement is attributed to the randomness induced in jamming patterns due to sensing errors, which distorts the learning process of the antijamming AI agent resulting in a considerable reduction in the anti-jamming capability of the AI-empowered wireless link. © 2024 IEEE.

关键词： Jamming

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Research on Collision Avoidance Path Planning of Dual Manipulator Robot Based on Fusion Algorithm

Research on Collision Avoidance Path Planning of Dual Manipu...

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2022 International Conference on Automation, Robotics and Computer engineering, ICARCE 2022

作者： Sun, Chenyang Liu, Xiangjun Shen, Runjie Tongji University College of Electronic and Information Engineering Shanghai China Tongji University Sino-German Center of Intelligent Systems College of Electronic and Information Engineering Shanghai China

ISBN: (纸本)9781665475488

When a dual manipulator robot performs handling operations in a complex space, it is important to plan a collision avoidance path to the target point quickly and accurately. In order to solve the problems of local minimum and high sampling randomness of traditional path planning algorithms, a new fusion algorithm is proposed for global path planning of a dual manipulator robot. First, an improved artificial potential field (IAPF) method is mentioned for path planning in the start and target point areas. Then, for the local minimum problem, an improved RRT algorithm (IRRT) based on the ϵ-greedy sampling target biasing strategy and repeated iterative update strategy is fused to reduce the randomness of random tree growth, and explore an optimal path that grows toward the target as much as possible for jumping out of the local minimum area. The URDF model file of the dual manipulator robot is created, and simulation experiments of path planning are conducted based on the Rviz visualization tool under Ros system, which proves the effectiveness of the fusion algorithm. © 2022 IEEE.

关键词： Motion planning

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Advanced Security Approach for Building Secure Containerized Manufacturing Digital Twins

Advanced Security Approach for Building Secure Containerized...

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2024 IET International Conference on engineering Technologies and Applications, ICETA 2024

作者： Lin, Yu-Chuan Chiu, Po-Kai Suryajaya, Benny Department of Computer Science and Information Engineering Chinese Culture University Taipei Taiwan Institute of Manufacturing Information and Systems National Cheng Kung University Tainan Taiwan Intelligent Manufacturing Research Center National Cheng Kung University Tainan Taiwan

ISBN: (纸本)9781837242672

In the era of digital transformation, containerized systems and digital twins are vital technologies in intelligent manufacturing. Our previous research, the Implementation Framework of Digital Twins for Intelligent Manufacturing (IF-DTiM), lacks comprehensive security features[1]. To address this critical gap, we propose the Advanced Security Approach for Building Secure Containerized Manufacturing Digital Twins (ASABS-CMDT), integrating automated tools for detecting vulnerabilities, container image creation, and secure digital signing, all within DevSecOps practices. Case studies show that ASABS-CMDT significantly enhances system security and reduces development time, offering valuable insights for practitioners in intelligent manufacturing. © The Institution of engineering & Technology 2024.

关键词： Smart manufacturing

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Brain Tumor Diagnosis Using Sparrow Search Algorithm Based Deep Learning Model

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Computer systems Science & engineering 2023年第2期44卷 1793-1806页

作者： G.Ignisha Rajathi R.Ramesh Kumar D.Ravikumar T.Joel Seifedine Kadry Chang-Won Jeong Yunyoung Nam Department of Computer Science and Business Systems Sri Krishna College of Engineering and TechnologyCoimbatore641008India Department of Information Technology Sri Krishna College of TechnologyCoimbatore641008India Department of Electronics and Communication Engineering Kings Engineering CollegeChennai602117India Department of Electronics and Communication Engineering R.M.K.Engineering CollegeChennai601206India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Medical Convergence Research Center Wonkwang UniversityIksanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Recently,Internet of Medical Things(IoMT)has gained considerable attention to provide improved healthcare services to *** earlier diag-nosis of brain tumor(BT)using medical imaging becomes an essential task,auto-mated IoMT and cloud enabled BT diagnosis model can be devised using recent deep learning *** this motivation,this paper introduces a novel IoMT and cloud enabled BT diagnosis model,named *** IoMTC-HDBT model comprises the data acquisition process by the use of IoMT devices which captures the magnetic resonance imaging(MRI)brain images and transmit them to the cloud ***,adaptive windowﬁltering(AWF)based image preprocessing is used to remove *** addition,the cloud server executes the disease diagnosis model which includes the sparrow search algorithm(SSA)with GoogleNet(SSA-GN)*** IoMTC-HDBT model applies functional link neural network(FLNN),which has the ability to detect and classify the MRI brain images as normal or ***ﬁnds useful to generate the reports instantly for patients located in remote *** validation of the IoMTC-HDBT model takes place against BRATS2015 Challenge dataset and the experimental analysis is car-ried out interms of sensitivity,accuracy,and speciﬁ*** experimentation out-come pointed out the betterment of the proposed model with the accuracy of 0.984.

关键词： Internet of medical things healthcare brain tumor disease classiﬁcation deep learning metaheuristics

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HiFi-Sim: A High-Fidelity Simulation Platform for Intelligence Assessment of USV 9

HiFi-Sim: A High-Fidelity Simulation Platform for Intelligen...

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9th International Conference on Computer and Communications, ICCC 2023

作者： Liu, Ziyu Xue, Zhenfeng Huang, Tao Chen, Zhuo Liu, Yong Huzhou University School of Information Engineering Huzhou313000 China Huzhou Institute of Zhejiang University Intelligent Perception and Control Center Huzhou313098 China Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China Cssc Systems Engineering Research Institute Beijing100094 China

ISBN: (纸本)9798350317251

The Unmanned Surface Vessel (USV) is one of important equipments for river and marine activities. During the development stage, full process simulation plays a key role due to the coupling relationship between the USV sub-systems. Nonetheless, there are few open source platforms available in the community, and existing ones are outdated and not suitable for intelligent evaluation. Thus, we propose this paper to promote our platform, a simulation platform for USV. The biggest feature lies in its high fidelity, mainly manifested in the following aspects. First, a great deal of effort was put into building the river scenes in Unity, where the lighting and rendering characteristics can be well guaranteed. Second, the input and output controls are achieved through Robot Operating System (ROS), which is test-friendly for personnel engaged in unmanned system development. Third, we have developed and imported a large number of sensor plugins in Unity to ensure various types of sensor data, including multiple cameras and LiDARs, and that is vital for evaluating intelligent algorithms of USV. Integration between ROS and Unity is achieved through TCP/IP communication, facilitating data transfer via topic-based mechanisms. Environmental impacts are also taken into account by including water wave, wind and rain scripts in Unity3D. We have conduced some representative experiments of USV to verify its effectiveness, including direct LiDAR odometry and water segmentation. © 2023 IEEE.

关键词： Robot Operating System

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