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15th International Conference Management of Large-Scale System Development, MLSD 2022

作者： Medennikov, Viktor Flerov, Yuri Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Information and Computing Systems Department Moscow Russia

ISBN: (数字)9781665497015

ISBN: (纸本)9781665497015

The paper discusses the methods that may be used to set up a science-based digital ecosystem for agriculture;these methods are based on the ideas proposed by A. Kitov and Academician V. Glushkov about a national automated information system (NAIS) for information collection and processing for accounting, planning, and management in the national economy, and substantiated by mathematical modeling. We focus on the need to ontologically integrate two basic digital ecosystem platforms: one for production and another for research and education. © 2022 IEEE.

关键词： Agriculture

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Vidhya: A Virtual Tutor for Enhancing English Education in Rural Areas of India 10

Vidhya: A Virtual Tutor for Enhancing English Education in R...

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10th International Conference on Signal Processing and Communication, ICSC 2025

作者： Anand, Sruthy Reddy, Kasa Amareswar Reddy, Pitti Abhiram Srinivas, Chandolu Shanmukha Rao, Sethuraman N Center for Wireless Networks & Applications (WNA) Amrita Vishwa Vidyapeetham Amritapuri India School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798331511890

In the new age of artificial intelligence (AI) and digitalisation, English proficiency is a very significant need for any individual to strive in this digital world. In this work, the authors focus on developing an online virtual English tutor bot called 'Vidhya'. This platform aims to provide an accessible and interactive English learning platform for students aged 13 to 18 from rural areas of India. The platform is designed to improve the speaking and writing skills of learners at their own pace of learning. The platform is designed in several levels which give the user a similar experience to playing a game with levels. This is introduced to make the user feel achievement and motivation to use the system. The system gives students the freedom to make mistakes and repeat the process until they learn and gain a retention threshold to move to the next level. The software platform is intended to support the rural Indian student community in learning English and propel them to pursue their academic and employment opportunities. The design features an intelligent feedback system wherein the software listens to the learners and provides feedback to them pointing out where they have to improve. © 2025 IEEE.

关键词： Deep learning Education Personalised Education Personalised-feedback Rural India Voicebot

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Abnormal developmental trajectories under multimodal brain networks in ASD 16

Abnormal developmental trajectories under multimodal brain n...

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16th ICME International Conference on Complex Medical Engineering, CME 2022

作者： Li, Zhifeng Yang, Yanli Niu, Yan Guo, Min Taiyuan University of Technology Brain Science and Intelligence Computing Research Center Department of Information and Computer Taiyuan030024 China

ISBN: (纸本)9781665496995

Purpose: Emerging evidence suggests structural and functional brain networks are disrupted during the development of ASD patients. As the importance of age in ASD has been firmly established, children and young adults with ASD constitute a high-risk population. Due to the limitations of single-site sample data, this study proposed and applied two methods to investigate the abnormal development of connectome tissue in adolescents with ASD affected by age at multiple *** and Methods: A total of 140 subjects were included in our study, including 76 ASD patients and 64 normal controls. All the data of the subjects were obtained from the public dataset ABIDE II website and contain simultaneously structural DTI data, T1-weighted data, and resting-state fMRI data. In this paper, we first used graph theory to analyze and reconstruct the anatomical structure and functional brain network and then explored the abnormal brain regions of ASD patients with age from two perspectives: SC-Proportion and SC-FC ***: It was found that ASD showed age-related abnormalities in the whole brain compared with the NC group, and SC-FC Coupling values of ASD were significantly higher than those of NC in childhood but decreased significantly with age. We further found that the abnormal changes in whole-brain Coupling values were mainly caused by the abnormal development of RC and Local tissues. In addition, we found abnormal development of RC tissues in ASD at the structural ***: The present study showed that the anatomical RC tissue development in ASD patients was abnormal at the whole brain level. This finding suggests that the brain anatomy of the RC system is affected in high-risk children and adolescents, reflecting one of the connectome characteristics of developmental risk in ASD patients. © 2022 IEEE.

关键词： Tissue

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Smart Energy Management System Using Machine Learning

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computers, Materials & Continua 2024年第1期78卷 959-973页

作者： Ali Sheraz Akram Sagheer Abbas Muhammad Adnan Khan Atifa Athar Taher M.Ghazal Hussam Al Hamadi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Science COMSATS University IslamabadLahore CampusLahore54000Pakistan School of Information Technology Skyline University CollegeSharjah1797United Arab Emirates Network and Communication Technology Lab Center for Cyber SecurityFaculty of Information Science and TechnologyUniversiti Kebangsaan MalaysiaBangiSelangor43600Malaysia College of Engineering and IT University of DubaiDubaiUnited Arab Emirates

Energy management is an inspiring domain in developing of renewable energy ***,the growth of decentralized energy production is revealing an increased complexity for power grid managers,inferring more quality and reliability to regulate electricity flows and less imbalance between electricity production and *** major objective of an energy management system is to achieve optimum energy procurement and utilization throughout the organization,minimize energy costs without affecting production,and minimize environmental *** energy management is an essential and complex subject because of the excessive consumption in residential buildings,which necessitates energy optimization and increased user *** address the issue of energy management,many researchers have developed various frameworks;while the objective of each framework was to sustain a balance between user comfort and energy consumption,this problem hasn’t been fully solved because of how difficult it is to solve *** inclusive and Intelligent Energy Management System(IEMS)aims to provide overall energy efficiency regarding increased power generation,increase flexibility,increase renewable generation systems,improve energy consumption,reduce carbon dioxide emissions,improve stability,and reduce energy *** Learning(ML)is an emerging approach that may be beneficial to predict energy efficiency in a better way with the assistance of the Internet of Energy(IoE)*** IoE network is playing a vital role in the energy sector for collecting effective data and usage,resulting in smart resource *** this research work,an IEMS is proposed for Smart Cities(SC)using the ML technique to better resolve the energy management *** proposed system minimized the energy consumption with its intelligent nature and provided better outcomes than the previous approaches in terms of 92.11% accuracy,and 7.89% miss-rate.

关键词： Intelligent energy management system smart cities machine learning

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EEiF: Efficient Isolated Forest with e Branches for Anomaly Detection 24

EEiF: Efficient Isolated Forest with e Branches for Anomaly ...

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24th IEEE International Conference on Data Mining, ICDM 2024

作者： Zhang, Yifan Xiang, Haolong Zhang, Xuyun Xu, Xiaolong Fan, Wei Zhang, Qin Qi, Lianyong School of Software Nanjing University of Information Science and Technology China Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services China School of Computing Macquarie University Australia University of Oxford Uffield Department of Women's & Reproductive Health United Kingdom College of Computer Science and Software Engineering Shenzhen University China Faculty of Science and Engineering China

ISBN: (纸本)9798331506681

Anomaly detection is a popular research topic in Artificial Intelligence and has been widely applied in network security, financial fraud detection, and industrial equipment failure detection. Isolation forest based methods are the base algorithms to detect anomalies in these scenarios for their simplicity and efficiency, which has been further exploited with multi-folk trees and learning mechanisms to realize the optimal isolation forest for high detection accuracy. However, the optimal isolation forest is time-consuming with the learning mechanisms, resulting in the task failing of time-constrained applications. Moreover, the original optimal isolation forest fails to construct the optimal tree structure restricted by the time complexity. To address the above challenges, we propose an efficient anomaly detection method called EEIF, which realizes the real e-folk structure of the optimal isolation forest in our practical algorithm design. Specifically, we design a distribution that perfectly matches the e-branch theory to construct the optimal isolation forest. Then, we design an FR clustering scheme to achieve fast training of the isolation forest with learning to hash and provide related proofs of accuracy and efficiency. Besides, a parallel algorithm is integrated into our method to reduce prediction time. Finally, extensive experiments are conducted on a large amount of real-world datasets and the results demonstrate that our method significantly improves efficiency while ensuring effectiveness, compared with the state-of-the-art methods. © 2024 IEEE.

关键词： Anomaly Detection Efficient FR clustering Parallel Algorithm

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GenRec: unifying video generation and recognition with diffusion models 24

GenRec: unifying video generation and recognition with diffu...

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Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Zejia Weng Xitong Yang Zhen Xing Zuxuan Wu Yu-Gang Jiang Shanghai Key Lab of Intell. Info. Processing School of CS Fudan University and Shanghai Collaborative Innovation Center of Intelligent Visual Computing Department of Computer Science University of Maryland

ISBN: (纸本)9798331314385

Video diffusion models are able to generate high-quality videos by learning strong spatial-temporal priors on large-scale datasets. In this paper, we aim to investigate whether such priors derived from a generative process are suitable for video recognition, and eventually joint optimization of generation and recognition. Building upon Stable Video Diffusion, we introduce GenRec, the first unified framework trained with a random-frame conditioning process so as to learn generalized spatial-temporal representations. The resulting framework can naturally supports generation and recognition, and more importantly is robust even when visual inputs contain limited information. Extensive experiments demonstrate the efficacy of GenRec for both recognition and generation. In particular, GenRec achieves competitive recognition performance, offering 75.8% and 87.2% accuracy on SSV2 and K400, respectively. GenRec also performs the best on class-conditioned image-to-video generation, achieving 46.5 and 49.3 FVD scores on SSV2 and EK-100 datasets. Furthermore, GenRec demonstrates extraordinary robustness in scenarios that only limited frames can be observed. Code will be available at https://***/wengzejia1/GenRec.

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Energy-efficient and Secure Wireless Communication for Telemedicine in IoT

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computer Systems science & Engineering 2022年第12期43卷 1111-1130页

作者： Shital Joshi S.Manimurugan Ahamed Aljuhani Umar Albalawi Amer Aljaedi Department of Computer Science Oklahoma State UniversityOklahomaUSA College of Computing and Information Technology University of TabukTabuk71491Saudi Arabia Industrial Innovation and Robotics Center University of TabukTabukSaudi Arabia

The Internet of Things (IoT) represents a radical shifting paradigm fortechnological innovations as it can play critical roles in cyberspace applications invarious sectors, such as security, monitoring, medical, and environmental sectors,and also in control and industrial applications. The IoT in E-medicine unleashedthe design space for new technologies to give instant treatment to patients whilealso monitoring and tracking health conditions. This research presents a systemlevel architecture approach for IoT energy efficiency and security. The proposedarchitecture includes functional components that provide privacy managementand system security. Components in the security function group provide securecommunications through Multi-Authority Ciphertext-Policy Attributes-BasedEncryption (MA-CPABE). Because MA-CPABE is assigned to unlimited devices,presuming that the devices are reliable, the user encodes data with AdvancedEncryption Standard (AES) and protects the ABE approach using the solutionsof symmetric key. The Johnson’s algorithm with a new computation measure isused to increase network lifetime since an individual sensor node with limitedenergy represents the inevitable constraints for the broad usage of wireless sensornetworks. The optimal route from a source to destination turns out as the cornerstone for longevity of network and its sustainability. To reduce the energy consumption of networks, the evaluation measures consider the node’s residualenergy, the number of neighbors, their distance, and the link dependability. Theexperiment results demonstrate that the proposed model increases network lifeby about 12.25% (27.73%) compared to Floyd–Warshall’s, Bellman–Ford’s,and Dijkstra’s algorithms, lowering consumption of energy by eliminating thenecessity for re-routing the message as a result of connection failure.

关键词： Energy-efficiency energy consumption Internet of Things telemedicine wireless sensor networks

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The influence of culture on creativity in ideation: a review

The influence of culture on creativity in ideation: a review

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2024 International Design Society Conference, Design 2024

作者： Gong, Zhengya Gonçalves, Milene Nanjappan, Vijayakumar Georgiev, Georgi V. Center for Ubiquitous Computing University of Oulu Finland Department of Design Organisation and Strategy Faculty of Industrial Design Engineering Delft University of Technology Netherlands School of Computer Science and Information Technology University College Cork Ireland

The relationship between culture and creativity has sparked the interest of researchers for decades. Although researchers have attempted to establish a connection between culture and creativity, the precise relationship between the two remains ambiguous. The current paper examined extant literature on the subject matter and synthesized the relations between culture and creativity in ideation over the past twenty years. The present study expounds upon the utilized samples, measures implemented to assess creativity and culture, and the study results. © 2024 Proceedings of the Design Society. All rights reserved.

关键词： Behavioral research

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Securing Consumer IoT Swarms Using Graph Transformers and SRAM for Firmware Attestation 22

Securing Consumer IoT Swarms Using Graph Transformers and SR...

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22nd IEEE Consumer Communications and Networking Conference, CCNC 2025

作者： Kohli, Varun Kohli, Bhavya Aman, Muhammad Naveed Sikdar, Biplab National University of Singapore Department of Electrical and Computer Engineering Singapore Center for Machine Intelligence and Data Science Indian Institute of Technology Bombay India School of Computing University of Nebraska-Lincoln United States

ISBN: (纸本)9798331508050

Consumer Internet of Things (IoT) networks have gained widespread popularity due to their convenience, automation, and security provisions in personal and home environments. Ubiquitous resource-constrained devices, however, are plagued with security issues that often arise from firmware-related issues and their propagated effects. While various studies on firmware attestation are available, they require firmware copies, specific hardware, and complex computation on the IoT device. This paper presents a study on the application of Graph Transformer Networks (GTN) in verifying the firmware integrity of consumer IoT swarms using SRAM as an attestation feature. The proposed method achieves an overall 0.99 accuracy on authentic samples from development and physical twin networks, 0.99 on malware, and 0.97 on propagated misbehavior at a ∼ 10-4 second inference latency on a laptop CPU. © 2025 IEEE.

关键词： computer viruses

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Advancing general robotic manipulation with multimodal foundation models: An embodied AI paradigm

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science China(Technological sciences) 2025年第5期68卷 290-292页

作者： Shifeng HUANG He WANG Xing ZHOU Wenkai CHEN Haibin YANG Jianwei ZHANG Department of Mechanical and Aerospace Engineering Hong Kong University of Science and TechnologyHong Kong 999077China Foshan Institute of Intelligent Equipment Technology Foshan 528234China Foshan Huashu Robot Co. Ltd.Foshan 528234China Center on Frontiers of Computing Studies(CFCS) School of Computer SciencePeking UniversityBeijing 100871China Beijing Academy of Artificial Intelligence Beijing 100084China Department of Informatics Universität HamburgHamburg 20146Germany

Can current robotic technologies truly replicate the full scope and intricacies of human labour?In practice,the adoption of robots remains limited,especially in open,unstructured environments commonly encountered in everyday scenarios such as services,healthcare,agriculture,construction,and numerous other *** the perspective of general robotic manipulation,the challenges arise from three factors.(1)High operational barriers:human operators are obliged to master specialized robotic programming languages and gain a deep understanding of the tasks at *** tasks need to be broken down into action-level robotic programs,which results in high labour costs.(2)Limited autonomous task execution:robots lack the capability to independently plan and execute actions required to achieve the target *** limitation renders them unsuitable for deployment in open,unstructured environments that demand sophisticated interaction and seamless collaboration with humans.

关键词： multimodal foundation models autonomous task execution robotic manipulationthe general robotic manipulation robotic programming language embodied AI operational barriers robotic technologies

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