检索结果-内蒙古大学图书馆

17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Meena, Sunil Kumar Singh, Shashank Sheshar Singh, Kuldeep University of Delhi New Delhi Department of Computer Science New Delhi India Thapar Institute of Engineering and Technology Department of Computer Science and Engineering Patiala India

ISBN: (纸本)9798331531195

Influence maximization (IM) is the task of selecting the most influential nodes in the network. IM achieves the goal of spreading information, influencing behaviour, or promoting sales of products. Existing studies in IM focus on maximizing the activated nodes in the static network and neglecting the communities. In this paper, we give a novel ranking-based algorithm that ranks the nodes based on their reachability and diversity. This paper proposes an objective function that considers both diversity and activated nodes to determine the diversity capability of the nodes. The proposed algorithm utilizes previous computation and integrates reachability centrality with the objective function to rank the nodes at a timestamp in a dynamic network. We execute the proposed and benchmark algorithms on five datasets. The experiments show that the suggested algorithm produces superior and competitive outcomes in comparison to the benchmark algorithms. © 2025 IEEE.

关键词： Diversified Influence Maximization Dynamic Networks Influence Maximization Local Reaching Centrality Social Network Analysis

来源：评论

学校读者我要写书评

暂无评论

Identification of Real or Fake Currency Using Semi-supervised Generative Adversarial Networks (SSGANs) 6th

Identification of Real or Fake Currency Using Semi-supervise...

引用

6th International Conference on Computational Intelligence in Pattern Recognition, CIPR 2024

作者： Mukherjee, Anupam Ghosh, Anupam Department of Computer Science & Engineering Siliguri Institute of Technology West Bengal Siliguri India Department of Computer Science & Engineering Netaji Subhash Engineering College West Bengal Kolkata India

ISBN: (纸本)9789819780891

Traditional paper money and contemporary electronic money are two significant forms of exchange. However, due to the new and improved methods that counterfeiters are using, it is now becoming an increasingly important issue. This work suggests a machine-assisted method that has been created to distinguish between fake and real currency. Generative adversarial networks (GANs), a cutting-edge machine learning model, are used for this purpose. To develop a model that can be used for supervised prediction, GANs utilize semi-supervised learning. Semi-supervised learning is an exceptional approach in building a model that is fit for supervised prediction. It offers a multitude of benefits, allowing the training of unlabeled data while achieving highly accurate predictions. In this work, detecting counterfeit money using GANs involves a multi-step methodology that leverages the power of deep learning for accurate identification. Preprocess the data by resizing, normalizing, and augmenting the images to ensure uniformity and improve model generalization. The discriminator minimizes the loss when making correct classifications, while the generator minimizes the loss when the discriminator classifies its generated images as genuine. Indian banknotes were subjected to this procedure. Modern feature identification and image processing techniques were employed to develop the overall strategy of a valid input. The trials demonstrate that a high-precision system may be created to identify real paper money. During the training process, the generator network and the discriminator networks update their loss functions. Once training is complete, the model can accurately identify real money notes from fake ones with an 80% accuracy rate. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Ensuring Trust in Blockchain-Based E-commerce Using Smart Contracts 5th

Ensuring Trust in Blockchain-Based E-commerce Using Smart Co...

引用

5th International Conference on Computing, Communications, and Cyber Security, IC4S 2023

作者： Surendar, P.D. Kumar, Adhithi Satish Pavani, Venkata Azhagiri, M. Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai600089 India

ISBN: (纸本)9789819773701

In the ever-changing realm of e-commerce, building trust is crucial for both customers and sellers. Reputation systems play a vital role in enabling informed decision-making by providing vendor ratings and reviews. Conventional reputation systems are typically inadequate in dealing with contemporary issues including privacy, identity theft, and feedback fraud. In order to address these challenges, we suggest implementing a decentralized reputation system that places a high value on privacy and effectively counters existing risks. Our architecture utilizes two permissioned blockchains, Hyperledger Indy for decentralized identity management through verifiable credentials and Zero Knowledge Proof (ZKP) technology, guaranteeing anonymity and authenticity, and Hyperledger Fabric for executing smart contracts, facilitating intricate business logic. The system incorporates verified vendor identities, transaction feedback tokens, and discount tokens to encourage genuine evaluations. Smart contracts implemented on the Hyperledger Fabric platform provide the security and transparency of the feedback process, hence reducing the occurrence of biased feedback and identity assaults. This technique provides a strong and reliable answer to the issues faced in e-commerce. It ensures the protection of private information and enables the verification of digital identities while maintaining privacy. The implementation of feedback and discount tokens promotes the provision of precise input, mitigating unjust practices and bolstering the dependability and confidence in the system. We demonstrate the effectiveness of our methodology using Zero Knowledge Proofs (ZKP), highlighting its importance in establishing confidence within the context of blockchain. Our system represents a notable advancement in creating a safe, transparent, and reliable e-commerce environment. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

Drug Targets Prediction of Mycobacterium tuberculosis H37Rv Using In Silico Genome Analysis 2

Drug Targets Prediction of Mycobacterium tuberculosis H37Rv ...

引用

2nd International Conference Computational and Characterization Techniques in engineering and sciences, IC3TES 2024

作者： Abhilash Mahapatra, Rajendra Prasad Srm Institute of Science and Technology Faculty of Engineering and Technology Department of Computer Science and Engineering Uttar Pradesh Ghaziabad201204 India

ISBN: (纸本)9798350364699

Mycobacterium tuberculosis, the causal agent of tuberculosis, is a major global health concern. The most widely studied strain for understanding the mechanism of drug resistance is H37Rv. To identify possible therapeutic targets, in silico analyses of Mycobacterium tuberculosis H37Rv genome were carried out. The genome sequence was downloaded from the website of NCBI (National Center for Biotechnology Information). To identify essential genes, the DEG (Database of Essential Genes) was consulted. Additionally, homology searches with the human genome were conducted using BLASTX. Out of a total of 3924 genes, 594 were determined to be essential for Mycobacterium tuberculosis, of which 366 had no sequence similarity to the human genome. Out of 366 genes, 242 potential drug targets have been found after being screened for fictitious and unidentified genes. © 2024 IEEE.

关键词： Genome

来源：评论

学校读者我要写书评

暂无评论

Enhancing Data Aggregation Efficiency: Dynamic Energy-Aware Strategies in Wireless Sensor Networks

Enhancing Data Aggregation Efficiency: Dynamic Energy-Aware ...

引用

2024 International Conference on Smart Devices, ICSD 2024

作者： Agrawal, Navin Kumar Priya, Naincy Sinha, Priyanka Singh, Pranita Jain, Arpit Kumar, Munish GLA University Department of Computer Engineering & Applications U.P. Mathura India Muzaffarpur Institute of Technology Department of Computer Science & Engineering Bihar Muzaffarpur India Government Engineering College Khagaria Department of Computer Science & Engineering India Roorkee Institute of Technology Department of Computer Science and Engineering Roorkee India Koneru Lakshmaiah Education Foundation Department of Computer Science & Engineering Vaddeswaram AP India

ISBN: (纸本)9798350394412

In today's surplus world, wi-fi sensor networks are essential for many systems. This network encapsulates sensor nodes powered by irreplaceable batteries, preserving a fixed topology for displaying specific locations. Their efficiency makes it crucial for large data packages. Wireless sensor networks continuously analyze physical factors such as temperature, pressure, ambient soft, sunlight and humidity, dominating the process Energy consumption monitoring is a key task in this area. To address this framework, this paper proposes a different approach: a modified controlled, privacy-controlled approach to record collection. The method aims to reduce redundant sensitivity, thus increasing system lifetime by reducing the frequency of data transfer between nodes and large sinks A comparative study with existing methods shows how the proposed method is effective. Performance findings show that the proposed bundling method (MEBPP) provides high packet transmission values while consuming less power and extending network lifetime. © 2024 IEEE.

关键词： Data aggregation

来源：评论

学校读者我要写书评

暂无评论

Intense Triad Defender for End-User Security in Cyber Physical System 2

Intense Triad Defender for End-User Security in Cyber Physic...

引用

2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Sheryl Sharon, G. Maranco, M. Nidhya, R. Sivakumar, M. Coimbatore Institute of Technology Department of Computer Science and Engineering Coimbatore641014 India SRM Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Networking and Communications Kattankulathur603203 India Madanapalle Institute of Technology and Science Department of Computer Science and Engineering Andhra Pradesh Madanapalle India

ISBN: (数字)9798350365269

ISBN: (纸本)9798350365269

The rapid advancement of technology has undoubtedly brought comfort to humanity, but it also necessitates robust authentication measures to ensure security in the ever-expanding e-world. This research aims to address the critical aspects of security, focusing on end-user authentication. The proposed solution incorporates multiple factors, including location-based authentication, text-based authentication with enhanced encryption standards, and facial recognition authentication. Location-based authentication serves to restrict access geographically, mitigating the risk of impersonation by enforcing strict geographic limits on facility access. Strong text passwords, utilizing a unique algorithm with a classic salt method, add an extra layer of complexity for potential attackers, making it challenging to compromise user credentials. The incorporation of facial recognition technology acts as a deterrent against non-human entities attempting unauthorized access. Leveraging deep learning and API servers ensures precision and scalability in the model, enhancing its effectiveness in real-world scenarios. These multi-factor authentication techniques collectively contribute to a secure, reliable, and forward-looking solution to address the evolving landscape of digital security threats. In adhering to the age-old adage "prevention is better than cure,"the research emphasizes the importance of proactive measures to safeguard against potential security breaches. © 2024 IEEE.

关键词： Network security

来源：评论

学校读者我要写书评

暂无评论

An Approach to Radiotherapy Treatment Planning based on Machine Learning Algorithms 4

An Approach to Radiotherapy Treatment Planning based on Mach...

引用

4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Divya, Komati Bhargavi, C.H. Abirami, M. Arjun, Ponnaganti Padmaja, Pabbathi Dhanwanth, Batini Panimalar Institute of Technology Department of Computer Science and Engineering Chennai India Department of Computer Science and Engineering Chennai India St.Peter's Institute Of Higher Education And Research Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350385793

Customizing radiation treatments for each patient is a formidable obstacle in the fight against cancer. Because they rely on human intervention and generalization, traditional methods often provide less-than-ideal results and unwanted side effects. Utilizing patient-specific anatomical and tumor-specific data, this research analyzes the revolutionary possibilities of machine learning for planning radiation therapy. The goal of this research work is to forecast radiation doses, identify tumor boundaries, and reduce the exposure to healthy tissue using Deep Learning (DL), Support Vector Machine (SVM) and Random Forest (RF) models. Radiation planners must prioritize data heterogeneity, model interpretability, and clinical validation if machine learning has to be widely used. Improved patient outcomes and quality of life may be achieved via the use of Machine Learning (ML) to improve the radiation efficacy and accuracy, as shown in this research study that synthesizes existing research. © 2024 IEEE.

关键词： Radiotherapy

来源：评论

学校读者我要写书评

暂无评论

A Multi Model Deep Learning Framework for Sarcasm Detection in Regional Social Media: An Overview 1

A Multi Model Deep Learning Framework for Sarcasm Detection ...

引用

1st International Conference on AIML-Applications for engineering and technology, ICAET 2025

作者： Bhadgale, Anilkumar M. Maheswari, M. Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350355611

Sarcasm detection in social media is a challenging task due to its inherent reliance on contextual cues, tone, and cultural nuances. In recent years, multi-model deep learning frameworks have emerged as a powerful approach for addressing these challenges, particularly in regional social media, where language variations and local idiomatic expressions complicate the detection process. This survey explores the latest developments in multi-model deep learning frameworks for sarcasm detection, focusing on their application in regional social media. The survey begins by reviewing foundational techniques in sarcasm detection, including traditional machine learning approaches that rely on handcrafted features. These methods, although effective in certain contexts, often fail to capture the subtleties of sarcasm in informal, region-specific languages. The advent of deep learning has led to significant advancements, particularly through models like Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformers. These architectures, combined with Natural Language Processing (NLP) techniques, have enhanced the ability to identify sarcasm through text analysis. However, single-modal approaches focusing solely on text fail to fully capture sarcasm's multimodal nature, especially on platforms where users often express themselves through a combination of text, images, emojis, and video. This has led to the development of multi-model frameworks that integrate various data modalities, such as text, image, and user behaviour, to better understand the context of sarcastic expressions. In regional social media, where local language and cultural symbols play a crucial role, these multi-model approaches prove even more valuable. This survey highlights key multi-model frameworks, emphasizing their use in regional settings. By examining datasets, model architectures, and evaluation metrics, the survey underscores the importance of combining textual and non-textual

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhanced Web based Multi-Platform E-voting Solution 5

Enhanced Web based Multi-Platform E-voting Solution

引用

5th International Conference on Smart Electronics and Communication, ICOSEC 2024

作者： Nallapareddy, Anusha Swapna, T. Shanmugam, Sundaramurthy Shabu, Jany Refonaa, J. Hyderabad India G Narayanamma Institute of Technology and Science Department of Computer Science and Engineering Hyderabad India Srm Institute of Science and Technology Department of Computing Technologies Chennai India Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331504403

In democratic nations such as India, the act of voting is a basic right that grants individuals the power to choose their leaders. Traditionally, voting has typically taken place at specific locations called polling booths, either in centralized or distributed. Every Indian citizen above 18 years of age has the right to vote and participate in choosing their representatives. Voters go to the polling booths where they can cast their votes under the observation of authorized individuals. However, this traditional voting system has various challenges such as low voter turnout and instances of fraudulent voting. To address these issues, a secure multi-platform E-Voting system is proposed in this research, developed using the Flutter framework and Firebase backend services. The system aims to verify each voter before they can cast their vote, employing multiple levels of verification. The proposed application consists of an administrator (admin) interface and a voter interface. The admin interface allows for the addition of elections, candidates, and constituencies, while the voter interface requires voters to register, log in, and cast their vote. The verification process includes One Time Password (OTP) authentication, face recognition, fingerprint verification, and validation through government-issued identification cards. Two commonly used identification cards in India are the Aadhaar card and the Permanent Account Number (PAN) card, which are unique to each citizen. By utilizing this proposed online voting application, eligible voters can conveniently cast their votes from anywhere in the world, using internet-connected devices like mobile phones or tablets. The primary objectives of the proposed system are to increase voter turnout and reduce instances of fraudulent voting. Furthermore, conducting elections through this application also helps reduce the required workforce. © 2024 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Recent Advances in Single-Atom Catalysts for Photoelectrocatalytic Water Splitting

引用

Carbon Energy 2025年第4期7卷 114-142页

作者： Jiao Yang Xiaoyang Zheng Syed Shoaib Ahmad Shah Chao Wang Xueyao Li Zhishuo Yan Lishan Peng Key Laboratory of Rare Earths Ganjiang Innovation Academy Chinese Academy of Sciences Institute of Applied Physics and Materials Engineering University of Macau Department of Mechanical Engineering Graduate School of Engineering The University of Tokyo Department of Chemistry School of Natural Sciences National University of Sciences and Technology Department of Chemistry University of Connecticut School of Rare Earths University of Science and Technology of China Department of Electrical and Computer Engineering North Dakota State University

Hydrogen is a highly promising energy carrier because of its renewable and clean qualities. Among the different methods for H2production, photoelectrocatalysis（PEC） water splitting has garnered significant interest, thanks to the abundant and perennial solar energy. Single-atom catalysts（SACs）, which feature well-distributed atoms anchored on supports, have gained great attention in PEC water splitting for their unique advantages in overcoming the limitations of conventional PEC ***, we comprehensively review SAC-incorporated photoelectrocatalysts for efficient PEC water splitting. We begin by highlighting the benefits of SACs in improving charge transfer, catalytic selectivity, and catalytic activity, which address the limitations of conventional PEC reactions. Next, we provide a comprehensive overview of established synthetic techniques for optimizing the properties of SACs, along with modern characterization methods to confirm their unique structures. Finally, we discuss the challenges and future directions in basic research and advancements, providing insights and guidance for this developing field.

关键词： hydrogen production photoelectrocatalysis single-atom catalysts water splitting

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：