检索结果-内蒙古大学图书馆

15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024

作者： Kulkarni, Mayuri Shahade, Makarand Mahajan, Deep Nikam, Bhavesh Badgujar, Rushikesh Sharma, Piyush SVKM's Institute of Technology Department of Computer Engineering Dhule India

ISBN: (纸本)9798331300579

The Decentralized technology 'Blockchain' has some point Centralization in terms of Remote Procedure Call Mechanism. Relying on centralized RPC (Remote Procedure Call) is risky and running a node can be expensive, time consuming and more complex making it extremely inaccessible for most of the users. Web3 companies must spend huge expenses on maintaining their infrastructure and fault-tolerant operation. The Lightning Sidebridge is Based on the core Infrastructure of Blockchain & Decentralized RPC Load Balancing. Lightning Sidebridge (Load Balancer) is a decentralized RPC Gateway service that provides more secure and reliable access to the blockchain. Lightning Sidebridge is a decentralized network of nodes that are responsible for validating transactions and blocks. The network is secured using a various Consensus mechanism such as Proof of Stake and reputation systems. Lightning Sidebridge is designed to distribute requests across a network of Decentralized RPC nodes to avoid failure and errors. The system (Load Balancer) sits between Decentralized applications and Blockchain RPC Layer. It is designed to distribute the requests amongst a cluster of public RPC nodes. The Proposed system can reroute specific requests to another active RPC endpoint automatically if node that is currently in use goes down. Implemented nodes are hardened and secured for various attacks and continuously monitored for security vulnerabilities. as Current RPC Network is Centralized, the Proposed system is more focused on Decentralized RPC Gateway and enabling potential of decentralized node validation services in fortifying blockchain accessibility and security. © Grenze Scientific Society, 2024.

关键词： Decentralized control

来源：评论

学校读者我要写书评

暂无评论

A CNN and HBA Based Approach for Grape Disease Identification 4

A CNN and HBA Based Approach for Grape Disease Identificatio...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Vishnuvarthan, K. Renugadevi, R. Santhi, S. Kit - Kalaignarkarunanidhi Institute of Technology Department of Computer Science and Engineering Coimbatore India

ISBN: (纸本)9798331523923

Grapes are among the most extensively cultivated fruit crops globally, with over 10,000 varieties. They serve as a significant economic resource for many nations due to their diverse applications, including wine production, fresh juice consumption, raisin production, and juice manufacturing. However, grape diseases pose a severe threat to the viticulture industry, leading to substantial financial losses and a decline in wine quality. Manual evaluation is the foundation of traditional disease detection techniques, which are error-prone in addition to saving time. This highlights the need for an automated system capable of analyzing plant health, identifying diseases, and addressing undernourishment efficiently and reliably. Accurate disease diagnosis and timely control measures are crucial for mitigating these challenges. Many scholars have studied various algorithms such as CNN, SVM, Neural Networks, Random Forests, etc., yet each has disadvantages. So we have proposed an automated deep learning-based approach that integrates the Honey Badger Algorithm (HBA) with Convolutional Neural Networks (CNN) for the detection of grape diseases. A phenomenal 95% accuracy rate was attained by the prototype after it was trained on a dataset of 10,000 photos. Its performance was evaluated across various grape varieties and environmental conditions, demonstrating its robustness and adaptability. © 2025 IEEE.

关键词： Wine

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Approach for Detecting Fake Images Using Texture Variation Network

引用

Inteligencia Artificial 2023年第72期26卷 1-14页

作者： Haseena, S. Saroja, S. Shri Dharshini, D. Nivetha, A. Department of Information Technology Mepco Schlenk Engineering College India Department of Computer Applications National Institute of Technology Trichy India

Face manipulation technology is rapidly evolving, making it impossible for human eyes to recognize fake faces in photos. Convolutional Neural Network (CNN) discriminators, on the other hand, can quickly achieve high accuracy in distinguishing fake from real face photos. In this paper, we investigate how CNN models distinguish between fake and real faces. According to our findings, face forgery detection heavily relies on the variation in the texture of the images. As a result of the aforementioned discovery, we propose a deep texture variation network, a new model for robust face fraud detection based on convolution and pyramid pooling. Convolution combines pixel intensity and pixel gradient information to create a stationary representation of composition difference information. Simultaneously, multi-scale information fusion based on the pyramid pooling can prevent the texture features from being destroyed. The proposed deep texture variation network outperforms previous techniques on a variety of datasets, including Faceforensics++, DeeperForensics-1.0, Celeb-DF, and DFDC. The proposed model is less susceptible to image distortion, such as JPEG compression and blur, which is important in this field. © IBERAMIA and the authors.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Remember This Event That Year? Assessing Temporal Information and Understanding in Large Language Models

Remember This Event That Year? Assessing Temporal Informatio...

引用

2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024

作者： Beniwal, Himanshu Patel, Dishant Kowsik Nandagopan, D. Ladia, Hritik Yadav, Ankit Singh, Mayank Department of Computer Science and Engineering Indian Institute of Technology Gandhinagar India

ISBN: (纸本)9798891761681

Large Language Models (LLMs) are increasingly ubiquitous, yet their ability to retain and reason about temporal information remains limited, hindering their application in real-world scenarios where understanding the sequential nature of events is crucial. Our study experiments with 12 state-of-the-art models (ranging from 2B to 70B+ parameters) on a novel numerical-temporal dataset, TempUN, spanning from 10,000 BCE to 2100 CE, to uncover significant temporal retention and comprehension limitations. We propose six metrics to assess three learning paradigms to enhance temporal knowledge acquisition. Our findings reveal that open-source models exhibit knowledge gaps more frequently, suggesting a trade-off between limited knowledge and incorrect responses. Additionally, various fine-tuning approaches significantly improved performance, reducing incorrect outputs and impacting the identification of 'information not available' in the generations. The associated dataset and code are available at https://***/lingoiitgn/TempUN. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Advancing Data Sovereignty in Distributed Environments: An In-Depth Exploration of Data Localization Challenges

Advancing Data Sovereignty in Distributed Environments: An I...

引用

2024 International Conference on computer, Electronics, Electrical engineering and their Applications, IC2E3 2024

作者： Kancharla, Jaganmohan Reddy Madhu Kumar, S.D. National Institute of Technology Department of Computer Science & Engineering Calicut India

ISBN: (纸本)9798350388534

Data localization in distributed computing has gotten a lot of attention because it has the potential to improve data sovereignty, make sure regulations are followed, and make data easier to access. However, this practice also brings forth a multitude of challenges and threats to cybersecurity, data privacy, and overall information security. In this comprehensive survey paper, we delve into the complex landscape of challenges and threats associated with data localization in distributed computing environments. We explore the intricate interplay between data localization, distributed infrastructure, cybersecurity, and privacy concerns. This paper provides an in-depth analysis of various challenges such as regulatory compliance, data integrity, authentication, and access control, along with potential threats like data breaches, insider attacks, and unauthorized access. Furthermore, we investigate the state-of-the-art security mechanisms, encryption techniques, privacy-preserving methods, and access control strategies that researchers and practitioners have developed to address these challenges. Through this survey, we aim to provide a comprehensive overview of the critical issues surrounding data localization within cloud computing and shed light on the emerging trends and potential solutions that can pave the way for secure and privacy-aware data localization practices. © 2024 IEEE.

关键词： Data integrity

来源：评论

学校读者我要写书评

暂无评论

Software Fault Localization using CNN-LSTM Model 15

Software Fault Localization using CNN-LSTM Model

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Singh, Vishwank Vikram Bisi, Manjubala National Institute of Technology Department of Computer Science and Engineering Warangal India

ISBN: (纸本)9798350370249

Software fault localization is a critical task which identify the faulty statements in a program. Traditional fault localization techniques are unable to capture complex relationships within program execution data. In recent years, Convolutional Neural Networks (CNNs) has shown promise in enhancing fault localization performance. In this paper, we propose a CNN-LSTM model for software fault localization. We perform extensive experiments on four programs and observe that proposed CNN-LSTM model consistently outperforms existing methods, achieving higher accuracy and reliability in localizing software faults. © 2024 IEEE.

关键词： CNN LSTM MBFL SBFL

来源：评论

学校读者我要写书评

暂无评论

Enhancing Occluded Face Recognition Through Device-Edge Collaboration and Cross-Domain Feature Fusion with Heatmaps 3

Enhancing Occluded Face Recognition Through Device-Edge Coll...

引用

3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Prasanth, Ashwin Annie Micheal, A. Department of Computer Science & Engineering Sathyabama Institute of Science & Technology Chennai India

ISBN: (纸本)9798331527549

Face recognition under occlusion presents a persistent challenge in computer vision, primarily due to difficulties in capturing and effectively integrating visible and obscured facial features. This paper introduces a novel device-edge collaborative framework that advances occluded face recognition through an innovative cross-domain feature fusion technique. Our method employs a software-generated, occlusion-aware heatmap created from standard visible-light images, which emphasizes key facial landmarks even when regions of the face are partially covered. This heatmap provides a complementary data layer that enhances traditional visible facial features, allowing the cross-domain feature fusion process to synthesize a more comprehensive set of features for reliable recognition under occlusion. The combined feature set leverages both visible and simulated heatmap information to improve model robustness, even in complex occlusion scenarios. Additionally, a delay-optimized task scheduling method is applied on the edge, ensuring efficient resource allocation, faster processing, and minimal latency. Although this project is ongoing, preliminary evaluations indicate the potential effectiveness of this approach, with expected outcomes to include high recognition accuracy and reduced latency. This framework provides a scalable solution for occluded face recognition by integrating complementary data sources without requiring specialized hardware. © 2025 IEEE.

关键词： Face recognition

来源：评论

学校读者我要写书评

暂无评论

Customer Segmentation using Clustering Techniques: Data-Driven Approach to Enhance Marketing Strategy 5

Customer Segmentation using Clustering Techniques: Data-Driv...

引用

5th International Conference on Sustainable Communication Networks and Application, ICSCNA 2024

作者： Sakthi Priya, G. Vignesh Saravanan, K. Hemalatha, B. Karthika, R. Kavya Srinidhi, B. Ramco Institute of Technology Department of Computer Science and Engineering Rajapalayam India

ISBN: (数字)9798331530013

ISBN: (纸本)9798331530013

Customer segmentation is a vital strategy for businesses seeking to enhance their marketing efforts and optimize resource allocation. This research focuses on segmenting customers using the Mall Customer Segmentation dataset, which includes demographic and behavioral attributes such as age, gender, annual income, and spending score. The work begins with data preprocessing, involving the handling of missing values, encoding of categorical variables, and scaling of numerical features to prepare the data for analysis. Following preprocessing, exploratory data analysis (EDA) is conducted to visualize feature distributions and relationships, providing insights into the data's structure. The core of the research involves applying various clustering algorithms-K-Means, Hierarchical Clustering, and DBSCAN-to identify distinct customer segments. The optimal number of clusters is determined through methods like the Elbow Method and Silhouette Score. The clusters are then evaluated for quality, and their characteristics are analyzed to understand different customer segments. This segmentation enables businesses to their marketing strategies, enhance customer satisfaction, and make data-driven decisions based on customer behavior insights and demographics. © 2024 IEEE.

关键词： Sales

来源：评论

学校读者我要写书评

暂无评论

Analysing for Impact of Neutral Sentiments for Enhancing Quality of Services 2

Analysing for Impact of Neutral Sentiments for Enhancing Qua...

引用

2nd IEEE International Conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Ranjan, Roop Singh, Ranjeet Shukla, Roshan Buddha Institute of Technology Department of Computer Science and Engineering Gorakhpur India

ISBN: (纸本)9798350368109

Sentiment analysis (SA) is an intellectual process of extracting a user's views. Social media is gaining prominence in public transit agencies for communication strategies and daily management. In recent years, web documents are identified as an important source of reviewing individual opinions. Researchers using these social networking platforms are producing a high rate of increase in interest in methods for automatically extracting and analysing opinions from web documents such as for weblogs, customer reviews, movies and public services etc. This paper is an attempt to perform an evaluation of public opinion for the Quality of Services of two very popular public transportations in North India. Opinions of public have been collected in form of tweets for a specific time. An approach based on fuzzy logic and machine learning is introduced to solve the tweets extraction that is used for classification. The impact of neutral tweets is discussed. Results show that the performance of road transport is better than the transport through railway services and neutral tweets play a significant role in emotion analysis of the system. © 2024 IEEE.

关键词： Tweets

来源：评论

学校读者我要写书评

暂无评论

Vision Aid For Blind People Using YOLOV8 2

Vision Aid For Blind People Using YOLOV8

引用

2nd International Conference on Networking, Embedded and Wireless Systems, ICNEWS 2024

作者： More, Priyanka Sangamkar, Satvik Vishwakarma Institute Of Information Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350367461

This assistive system for the visually impaired integrates real-time YOLOv8 object detection with distance estimation and text-to-speech conversion, empowering users with enriched environmental awareness. Leveraging robust datasets and architectures, it identifies over 90 everyday objects amidst clutter while concurrently approximating object proximity through trigonometric translations of size metrics. Audio cues enunciate recognized items and distances in real time for accessibility. This combination of precise visual recognition, spatial metrics, and assistive feedback holds promise for enhanced mobility, independence, and safety during navigation for visually impaired individuals. © 2024 IEEE.

关键词： Vision aids

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：