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2012 3rd national conference on emerging trends and applications in computer science, NCETACS-2012

ISBN: (纸本)9781457707483

The proceedings contain 32 papers. The topics discussed include: energy optimization in ZigBee using prediction based shortest path routing algorithm;software for performance prediction and matching of tractor-implement system;virtualized remote web desktop towards a faster web cloud operating system;pilot assisted channel estimation technique for Alamouti STBC- MISO and MIMO set-up with BPSK and QPSK modulation;innovative feature set for retinopathic analysis of diabetes and its detection;a novel association rule mining mechanism in wireless sensor networks;intellectual ability planning for intelligent tutoring system in computer science engineering education abstract;design of a semi-automatic annotation model of speech signal with reference to Bodo language;blocking artifacts suppression in wavelet transform domain using local wiener filtering;and an investigation of workload descriptor based scheduling in grid employing GridGain.

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Proceedings - 2011 2nd national conference on emerging trends and applications in computer science, NCETACS-2011

Proceedings - 2011 2nd National Conference on Emerging Trend...

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2011 2nd national conference on emerging trends and applications in computer science, NCETACS-2011

ISBN: (纸本)9781424495818

The proceedings contain 28 papers. The topics discussed include: attacking embedded systems through fault injection;estimation of MIMO channels using complex time delay fully recurrent neural network;coding and adaptive equalization assisted MRC in wireless channels;gene expression data clustering analysis: a survey;efficient data compression using character replacement through generated code;thmip- a novel mobility management scheme using fluid flow model;navigational approach for mobile robots;design optimization of loop antenna using competitive learning ANN;embedded security for internet of things;image texture classification using artificial neural network (ANN);a model for detection, classification and identification of spam mails using decision tree algorithm;privacy preserving C4.5 using gini index;and fault detection time: an important parameter of test case sequencing for regression testing.

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Proceedings - 2011 2nd national conference on emerging trends and applications in computer science, NCETACS-2011: Preface

Proceedings - 2011 2nd National Conference on Emerging Trend...

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Proceedings - 2011 2nd national conference on emerging trends and applications in computer science, NCETACS-2011 2011年

作者： Warpakma, I. St. Anthony's College Shillong Meghalaya India

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Proceedings - 2013 1st International conference on emerging trends and applications in computer science, ICETACS 2013

Proceedings - 2013 1st International Conference on Emerging ...

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2013 1st International conference on emerging trends and applications in computer science, ICETACS 2013

ISBN: (纸本)9781467352505

The proceedings contain 48 papers. The topics discussed include: talent acquisition & transformation ? a new paradigm;on the study of GRBF and polynomial kernel based support vector machine in web logs;design of low power comparator circuit based on reversible logic technology;a novel steganography technique through variable bit maniputation;nuclei segmentation from breast cancer histology images;double-gate junctionless transistor for low power digital applications;reconstruction of speech signal using empirical mode decomposition based glottal source extraction;recurrent neural network based approach to recognize Assamese fricatives using experimentally derived acoustic-phonetic features;performance evaluation of task assignment algorithms in cube-based multiprocessor systems;and effect of noise on electro absorption modulator (EAM) and Optimization - used for optical communication.

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Proceedings - 2017 International conference on computer, Control, Informatics and its applications: emerging trends In Computational science and Engineering, IC3INA 2017

Proceedings - 2017 International Conference on Computer, Con...

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5th International conference on computer, Control, Informatics and its applications, IC3INA 2017

ISBN: (纸本)9781538639788

The proceedings contain 30 papers. The topics discussed include: cubic spline interpolation for large regular 3d grid in cylindrical coordinate;investigation on the feature activation method in a hierarchical concatenation network;the Indonesian e-commerce governance challenges in addressing the penetration of global user generated commerce platforms;performance improvement of multicore processor using genetic algorithm;multi feature fusion using deep belief network for automatic pap-smear cell image classification;classification of thyroid nodules based on analysis of margin characteristic;feature transformations for robust speech recognition in reverberant conditions;applying agile methods in designing an earthquake and landslide early warning system application for Android;comparative analysis of discrete-time plug-in multi periods repetitive control using different internal models;GPU-accelerated protein sequence alignment for Jamu prediction;and interface modeling for mobile learning using Kansei engineering and analytical hierarchy process.

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Intelligent integrated sensing and communication:a survey

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science China(Information sciences) 2025年第3期68卷 5-46页

作者： Jifa ZHANG Weidang LU Chengwen XING Nan ZHAO Naofal AL-DHAHIR George K.KARAGIANNIDIS Xiaoniu YANG School of Information and Communication Engineering Dalian University of Technology College of Information Engineering Zhejiang University of Technology School of Information and Electronics Beijing Institute of Technology Department of Electrical and Computer Engineering The University of Texas at Dallas Department of Electrical and Computer Engineering Aristotle University of Thessaloniki

Integrated sensing and communication (ISAC) is a promising technique to increase spectral efficiency and support various emerging applications by sharing the spectrum and hardware between these functionalities. However, the traditional ISAC schemes are highly dependent on the accurate mathematical model and suffer from the challenges of high complexity and poor performance in practical scenarios. Recently, artificial intelligence (AI) has emerged as a viable technique to address these issues due to its powerful learning capabilities, satisfactory generalization capability, fast inference speed, and high adaptability for dynamic environments, facilitating a system design shift from model-driven to data-driven. Intelligent ISAC, which integrates AI into ISAC, has been a hot topic that has attracted many researchers to investigate. In this paper, we provide a comprehensive overview of intelligent ISAC, including its motivation, typical applications, recent trends, and challenges. In particular, we first introduce the basic principle of ISAC, followed by its key techniques. Then, an overview of AI and a comparison between model-based and AI-based methods for ISAC are provided. Furthermore, the typical applications of AI in ISAC and the recent trends for AI-enabled ISAC are reviewed. Finally, the future research issues and challenges of intelligent ISAC are discussed.

关键词： artificial intelligence deep learning deep reinforcement learning federated learning generative artificial intelligence integrated sensing and communication machine learning transfer learning

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Silk Fibroin-Based Biomemristors for Bionic Artificial Intelligence Robot applications

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ACS NANO 2025年第18期19卷 17173-17198页

作者： Yang, Chuan Wang, Hongyan Wang, Kun Cao, Zelin Ren, Fenggang Zhou, Guangdong Chen, Yuanzheng Sun, Bai Southwest Jiaotong Univ Sch Phys Sci & Technol Key Lab Adv Technol Mat Minist Educ Chengdu 610031 Sichuan Peoples R China Xi An Jiao Tong Univ Frontier Inst Sci & Technol FIST Interdisciplinary Res Ctr Frontier Sci & Technol Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Natl Local Joint Engn Res Ctr Precis Surg & Regene Affiliated Hosp 1 Xian 710061 Shaanxi Peoples R China Southwest Univ Coll Artificial Intelligence Brain inspired Comp & Intelligent Control Chongqin Chongqing 400715 Peoples R China

In the emerging fields of flexible electronics and bioelectronics, protein-based materials have attracted widespread attention due to their biocompatibility, biodegradability, and processability. Among these materials, silk fibroin (SF), a protein derived from natural silk, has demonstrated significant potential in biomedical applications such as medical sensing and bone tissue engineering, as well as in the development of advanced biosensors. This is primarily due to its highly ordered beta-sheet structure, mechanical properties, and processability. Furthermore, SF-based memristors provided a material choice for producing flexible wearable, and even implantable bioelectronic devices, which are expected to advance intelligent health monitoring, electronic skin (e-skin), brain-computer interface (BCI), and other frontier bioelectronic technologies. This review systematically summarizes the latest research progress in SF-based memristors concerning structural design, performance optimization, device integration, and application prospects, particularly highlighting their potential applications in neuromorphic computing and memristive sensors. Concurrently, we objectively analyzed the challenges currently faced by SF-based memristors and prospectively discussed their future development trends. This review provides a theoretical foundation and technological roadmap for biomaterials-based memristor devices, aiming to realize applications in flexible electronics and bioelectronics.

关键词： natural biomaterials biomemristor artificialintelligence neuromorphic computing artificialneural network silk fibroin resistive switching flexible electronics

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Decoding the future: exploring and comparing ABE standards for cloud, IoT, blockchain security applications

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Multimedia Tools and applications 2025年第13期84卷 12299-12327页

作者： Singamaneni, Kranthi Kumar Yadav, Kusum Aledaily, Arwa N. Viriyasitavat, Wattana Dhiman, Gaurav Kaur, Amandeep Department of Computer Engineering and Technology Chaitanya Bharathi Institute of Technology T.S Gandipet Hyderabad500075 India College of Computer Science and Engineering University of Ha’il Hail Saudi Arabia Business Information Technology Division Department of Statistics Faculty of Commerce and Accountancy Chulalongkorn University Bangkok Thailand School of Sciences and Emerging Technologies Jagat Guru Nanak Dev Punjab State Open University Patiala India Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon Chitkara Centre for Research and Development Chitkara University Himachal Pradesh 173212 India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Division of Research and Development Lovely Professional University Phagwara India Centre of Research Impact and Outcome Chitkara University Punjab Rajpura140417 India MEU Research Unit Middle East University Amman Jordan

Data security poses a significant challenge in cloud computing, the Internet of Things (IoT), and blockchain applications. Attribute-Based Encryption (ABE) has emerged as a promising cryptographic solution for secure data sharing and access management in these contexts. This research article focuses on enhancing security in cloud, IoT, and blockchain applications through a comprehensive examination and comparison of various ABE standards. The study begins with an in-depth literature review on ABE requirements, offering insights into the evolving landscape, challenges, and trends. This review serves as the foundation for the research, which aims to compare ABE standards based on cryptographic techniques, encryption/decryption processes, and access control rules, considering criteria like flexibility, efficiency, scalability, and security. Statistical analyses complement the comparative study, generating empirical data on ABE standard performance. Key metrics, including key size, storage overhead, encryption/decryption time, and computational complexity, are considered to identify trends and draw meaningful conclusions. The research also explores use cases for different ABE models within blockchain, IoT, and cloud computing applications, pinpointing scenarios where specific ABE models excel. The study contributes to advancing access control and secure data-sharing technologies in specified domains, aiding researchers, practitioners, and developers in selecting the most appropriate encryption method. By systematically outlining advantages and disadvantages of various Cipher Text ABE standards, the research facilitates informed decision-making. Additionally, practical use cases ensure alignment between ABE models and the distinctive traits and requirements of each domain, expanding the toolset for enhancing data security in blockchain, IoT, and cloud computing applications. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springe

关键词： Internet of things

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Systematic review on machine learning and computer vision in precision agriculture: applications, trends, and emerging techniques

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ENGINEERING applications OF ARTIFICIAL INTELLIGENCE 2025年 148卷

作者： Kuan, Y. N. Goh, K. M. Lim, L. L. Tunku Abdul Rahman Univ Coll Fac Engn & Technol Dept Elect & Elect Engn Jalan Genting Klang Kuala Lumpur 53300 Malaysia

Machine learning (ML) and computer vision (CV) play a crucial role in precision agriculture (PA) by enabling data-driven solutions that enhance crop yields, resource efficiency, and sustainability. These technologies have transformed PA by addressing complex agricultural challenges through real-time monitoring and predictive analytics. This systematic review aims to investigate the recent advancements in ML and CV methodologies within PA, focusing on crop, harvesting, soil and water management. Guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, the study analyzes 213 articles from the past five years, providing insights into publication trends, key application area, and the distribution of research efforts across various crops and vision data types. The review highlights the predominant use of Convolutional Neural Networks (CNNs) in PA, particularly in crop detection, disease and pest detection, and weed detection. emerging deep learning techniques, such as Vision Transformers (ViTs) and Generative Adversarial Networks (GANs), are also explored for their potential in visual data analysis. Findings show that maize is the most frequently studied crop, Red-Green-Blue (RGB) imagery is the primary vision data type and self-collected datasets are preferred over public ones. Key challenges include limited access to high-quality and diverse datasets, and the need for adaptable solutions across diverse agricultural contexts. By summarizing these advancements and challenges, this review provides direction for future research and highlights opportunities to expand ML and CV applications in sustainable and efficient agricultural practices.

关键词： Machine learning computer vision Precision agriculture Deep learning Convolutional neural networks

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Neural Fields for Multimedia applications (Part-2): trends in Volumetric Videos and 3D Objects 4th

Neural Fields for Multimedia Applications (Part-2): Trends ...

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4th International conference on Smart Multimedia, ICSM 2024

作者： Muraleedharan, Lakshmi Priya Liu, Jian Dutta, Ujjal Kr Choudhury, Anustup Su, Guan-Ming Dolby Technology India Pvt. Ltd. Bengaluru India Dolby Laboratories Inc. Sunnyvale United States

ISBN: (纸本)9783031824746

This survey explores the integration of neural fields in 3D multimedia applications including virtual reality, augmented reality and gaming. The paper reviews methodologies, architectures, and applications providing insights into the efficiency and limitations of these approaches. The conclusion outlines current trends and proposes future directions. This survey serves as a concise guide to understand the application of neural field to 3D multimedia and we discuss those emerging trends and potential future directions in those areas. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： 3D modeling

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