检索结果-内蒙古大学图书馆

2024 International Conference on Knowledge engineering and Communication Systems, ICKECS 2024

作者： Srivastava, Supriya Kaur, GeetKiran Himank Singla, Sanjay Chandigarh University Dept. of Computer Science & Engineering Mohali140413 India Chandigarh University Dept. of Computer Science & Engineering Gharuan India

ISBN: (纸本)9798350359688

Nowadays due to increasing cases of evidence alteration the need of a robust evidence protection system is increasing rapidly. This paper presents an innovative solution that combines the InterPlanetary File System (IPFS) with blockchain technology to enhance the security, immutability, and transparency of evidential data obtained from crime *** proposed system initiates by utilizing IPFS, a decentralized and distributed file storage protocol, to securely store multimedia evidence, such as photographs. The content-addressed nature of IPFS guarantees tamper-resistant storage, making it an ideal choice for preserving the integrity of sensitive evidentiary materials. The IPFS addresses obtained from IPFS are then embedded within the blockchain, establishing a decentralized and verifiable link between the evidence and its storage location. We use multi-signature wallet to upload the data on blockchain so that we can make it more secure and monitored about who is uploading evidence state data. To verify links and integrity of evidence usage we set up a system of periodical updates of state of evidence whenever accessed. These updates serve as a mechanism to record the state of the evidence at different points in time, adding an additional layer of reliability and accountability. © 2024 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Generating High-Quality Distributed Representations of Words Using Wiktionary and Sentence-BERT 16

Generating High-Quality Distributed Representations of Words...

引用

16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024

作者： Nishiura, Ryota Tsuchiya, Seiji Watabe, Hirokazu Graduate School of Science and Engineering Doshisha University Dept. of Information and Computer Science Kyotanabe Kyoto Japan Doshisha University Faculty of Science and Engineering Dept. of Intelligent Information Engineering and Science Kyotanabe Kyoto Japan

ISBN: (纸本)9798350377903

We propose an improved method to generate high-quality distributed representations of words. In our previous paper, we introduced a novel method to obtain distributed representations of words with BERT using Wiktionary as semantic sources of words. The previous method outperformed a Wrd2Vec model in a word similarity task, while there still had to be some room to improve in term of semantic accuracy. In this paper, our new method introduces one of Sentence-BERT models to text-embed the semantic sources instead of the original BERT model. We demonstrate that our proposed method outperforms both our previous method and the Word2Vec model in the tasks. © 2024 IEEE.

关键词： Embeddings

来源：评论

学校读者我要写书评

暂无评论

Automated Identification of Pneumonia Employing Convolution Neural Networks and the VGG-16 Model 1

Automated Identification of Pneumonia Employing Convolution ...

引用

1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Srivastava, Anamika Gupta, Anuj Kaushik, Deepti Gupta, Neha Chadha, Shikha Chauhan, Rosey Noida Institute Of Engineering Technology Dept. of Computer Science & Engineering Gerater Noida India Sharda Unviersity Dept. of Computer Science & Engineering Gerater Noida India School of Engineering and Technology IIMT University Dept. of Computer Science and Engineering U.P Meerut India ABES Engineering College Dept. of Computer Science UP Ghaziabad India

ISBN: (纸本)9798350353648

Pneumonia, an inflammatory lung disease, impacts the small air sacs known as alveoli and is typically caused by the bacteria Streptococcus pneumonia. Symptoms commonly include a combination of productive or dry cough, chest pains, difficulty breathing, and fever. In India, where Covid-19 is prevalent, community-acquired pneumonia (CAP) poses a significant risk factor for mortality, accounting for one-third of fatalities, as reported by the World Health Organization (WHO).Diagnosing and predicting the outcome of pneumonia typically involves examining chest imaging radiographs of patients exhibiting clinically similar symptoms (e.g., fever, dyspnea, cough, and sputum production). Therefore, the development of an automated method for pneumonia detection could offer valuable advantages, particularly in remote regions, facilitating prompt treatment. Deep learning (DL) models enable the analysis of various chest radiographs, with Convolutional Neural Networks (CNNs) receiving considerable attention in disease classification. Leveraging features learned. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Automated Road Extraction in Urban and Rural Regions from Remote Sensing Imagery with U-Net and ResNet-Based Architectures 1

Automated Road Extraction in Urban and Rural Regions from Re...

引用

1st IEEE International Conference on Advances in Computing, Communication and Networking, ICAC2N 2024

作者： Sharma, Palvi Kumar, Rakesh Gupta, Meenu Obaid, Ahmed J. Chandigarh University Dept. of Computer Science & Engineering Punjab India Chandigarh University Dept. of Computer Science & Engineering Punjab India University of Kufa Faculty of Computer Science and Mathematics Najaf Iraq National University of Science and Technology College of Technical Engineering Dhi Qar Iraq

ISBN: (纸本)9798350356816

Accurate road extraction from Remote Sensing Imagery (RSI) is crucial for various applications, including urban planning, navigation, and disaster response. This study investigates automated road extraction in rural, semi-urban and urban regions using deep learning architectures, specifically UNet and Deep Residual U-Net (ResNet) models. We leverage High-Resolution Satellite Imagery (HRSI) to train and validate our models, focusing on the distinct characteristics and challenges presented by urban and rural environments. Our methodology involves comprehensive data preprocessing and augmentation techniques to enhance model robustness. We evaluate the performance of both architectures using metrics and achieved an accuracy of 90.29%, recall of 80.95%, precision of 74.89%, and F1- score of 77.80% for the Deep Residual U-Net. Experimental results demonstrates that while both models perform well, the Deep Residual U-Net exhibits superior accuracy and generalization, particularly in complex urban landscapes. © 2024 IEEE.

关键词： Urban planning

来源：评论

学校读者我要写书评

暂无评论

INTEGRATION OF STORAGE INSTALLATIONS AT ACTIVE CONSUMER IN THE PRESENCE OF PHOTOVOLTAIC INSTALLATIONS

UPB Scientific Bulletin, Series C: Electrical Engineering an...

引用

UPB Scientific Bulletin, Series C: Electrical engineering and computer science 2025年第1期2025卷 415-431页

作者： Oprea, Niculae Porumb, Radu Faculty of Power Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Dept. of Power Engineering National University of Science and Technology POLITEHNICA Bucharest Romania

The EU has offered new roles and responsibilities to the active consumer in order to control the generation and use of electrical energy, seeing it as an opportunity towards sustainable development for future generations. We investigated the operational characteristics of photovoltaic panels and storage installations for two users during the analyzed intervals and developed reasonable hypotheses considering the type of grid connection. The results provide interesting perspectives for decision-makers regarding the option to become active consumers. They once again demonstrate the feasibility of storage installations and the importance of optimizing consumption through various technologies. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： active consumers energy transition renewable sources storage installations

来源：评论

学校读者我要写书评

暂无评论

A Comprehensive Analysis on Skin Cancer Classification Using Transfer Learning 3

A Comprehensive Analysis on Skin Cancer Classification Using...

引用

3rd International Conference on Advancement in Electrical and Electronic engineering, ICAEEE 2024

作者： Renu, Israt Zerin Haque, Md. Momenul Paul, Subrata Kumer Mou, Mahmuda Shirin Rahman, Md Nahid Gupta, Sudipta Sen Paul, Rakhi Rani Rabindra Maitree University Dept. of Computer Science and Engineering Kushtia7000 Bangladesh Qadirabad Dept. of Computer Science and Engineering Dayarampur Natore6431 Bangladesh University of Rajshahi Dept. of Computer Science and Engineering Rajshahi6205 Bangladesh

ISBN: (纸本)9798350388282

Skin cancer, a prevalent and potentially life-threatening disease, necessitates accurate and timely diagnosis for effective treatment. In addressing this critical healthcare challenge, this research proposes a novel approach to skin cancer classification. The study identifies the need for enhanced diagnostic accuracy and introduces a solution by integrating the efficiency of transfer learning, specifically utilizing the EfficientNet V2 architecture. The proposed methodology leverages pre-trained convolutional neural networks (CNNs) to extract high-level features from dermatological images, which are subsequently input into a sophisticated classifier, forming a robust framework for precise skin cancer classification. The research employs a diverse dataset comprising 3297 images sourced from the publicly available Skin Cancer ISIC archive dataset, ensuring comprehensive coverage of benign and malignant skin lesions. During the training phase, the proposed EfficientNet V2 transfer learning approach outperforms conventional methods, achieving an impressive accuracy of 84%, surpassing both Inception V3 (82%) and a generic CNN model (81%). Interpretability analysis is conducted to elucidate the decision-making process of the EfficientNet V2 model, providing insights into the key features influencing its predictions. This transparency is crucial for building trust in the model's recommendations and facilitating its seamless integration into clinical workflows. The EfficientNet V2 transfer learning approach emerges as a promising and effective solution for advancing skin cancer classification systems, contributing significantly to the ongoing efforts to improve diagnostic accuracy in dermatology. © 2024 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

A Transformer-Based Model for Image Caption Generation with Memory Enhancement

A Transformer-Based Model for Image Caption Generation with ...

引用

2024 IEEE International Women in engineering (WIE) Conference on Electrical and computer engineering, WIECON-ECE 2024

作者： Ome, Shadika Afroze Azhar, Tanvir Asaduzzaman East Delta University Dept. of Computer Science & Engineering Chattogram Bangladesh Chittagong University of Engineering & Technology Dept. of Computer Science & Engineering Chattogram Bangladesh

ISBN: (纸本)9798331535476

This study proposes a convolution-free transformer-based method for generating accurate descriptions of images. A Vision Transformer is utilized as the primary encoder, replacing traditional CNN, and a Meshed Memory Transformer is integrated for generating captions. The Vision Transformer splits images into fixed-size patches for extracting visual features, which are further processed by a memory-augmented encoder to integrate prior knowledge. It ensures key features are preserved and reused and the meshed decoder combines the text embedding with the outputs from each encoding layer to generate more contextually rich and accurate captions compared to conventional approaches. The model's performance is evaluated on the Flickr30K and the MSCOCO datasets, demonstrating that the Meshed Memory architecture in our approach improves both the image encoding and caption generation step. Our model outperforms the conventional 'CNN-LSTM' models and 'CNN-Transformer' methods, achieving a 1.02% improvement in METEOR and 1.31% in SPICE on the MSCOCO dataset. Additionally, on the Flickr30k dataset, our approach exhibits superior performance across most metrics, notably a 6.37% increase in the METEOR score. © 2024 IEEE.

关键词： Encoding (symbols)

来源：评论

学校读者我要写书评

暂无评论

The Stability and Computational Complexity Analysis of Tree-seed Algorithm for Frequency-Constrained 10-bar Truss Problem 5

The Stability and Computational Complexity Analysis of Tree-...

引用

5th IEEE International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2024

作者： Cinar, Ahmet Cevahir Nur Erman, Kadriye Selçuk University Faculty of Technology Dept. of Computer Engineering Konya Turkey Kirikkale University Faculty of Engineering and Natural Sciences Dept. of Computer Engineering Kirikkale Turkey

ISBN: (纸本)9798350352863

Optimization studies in truss problems produce different results according to different optimization conditions, which leads to significant changes in the results obtained. This paper presents a comprehensive analysis of the Tree-Seed Algorithm (TSA) in solving the frequency-constrained 10-bar truss optimization problem, a well-known benchmark in structural engineering characterized by its complex, non-linear, and multi-modal design space. The TSA, inspired by natural processes of tree growth and seed dispersion, is evaluated in the truss problem for its stability, computational efficiency, and ability to find optimal solutions. Through rigorous testing involving 51 independent runs, the TSA consistently achieves optimal solutions with a mean objective function value of 554.4549 and a standard deviation of 1.4049. The algorithm demonstrates rapid convergence, typically within 100 iterations. The design parameters of the frequency-constrained 10-bar truss optimization problem were found by TSA within stability. These findings highlight the TSA's effectiveness and reliability, establishing it as a robust tool for tackling complex engineering optimization problems and suggesting its potential for broader applications in structural optimization. © 2024 IEEE.

关键词： Trusses

来源：评论

学校读者我要写书评

暂无评论

Chestnut(Castanea Sativa) Varieties Classification with Harris Hawks Optimization based Selected Features and SVM

Chestnut(Castanea Sativa) Varieties Classification with Harr...

引用

2024 International Conference on Advances in Computing, Communication, Electrical, and Smart Systems, iCACCESS 2024

作者： Yurdakul, Mustafa Atabaş, Irfan Taşdemir, Şakir Kirikkale University Engineering Faculty Computer Engineering Dept. Kirikkale Turkey

ISBN: (纸本)9798350350289

Chestnut(Castanea sativa) is a nutritious food with a hard outer shell. It is also used in different sectors for various purposes. Chestnut is a commercial product that is in demand worldwide due to its multi-purpose use. In order to determine the market value of chestnuts, it is necessary to classify it according to its types. With classical methods, people classify it manually. However, this method is tiring and error prone. In this study, for classifying chestnut varieties, features were extracted from chestnut images using various feature extraction methods. The extracted features were combined and classified with Linear, Poly and Radial Basis Function(RBF) kernels of Support Vector Machine(SVM). The combined handcrafted features and RBF kernel achieved an accuracy of 94.28%, precision of 93.83%, recall of 93.98%, F1-Score of 93.84%, and AUC of 99.25%. Furthermore, the most relevant features were selected using Arithmetic Optimization, Harris Hawks and Sooty Tern algorithms. The Harris Hawks Optimization selected features and RBF kernel showed the best classification performance with an accuracy of 95.84%, precision of 95.56%, recall of 95.51%, F1-score of 95.46% and AUC of 99.45%. © 2024 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

A STUDY ON STRUCTURE OF WIND VELOCITY DISTRIBUTION AND CORRESPONDING PRESSURE DEFICIT CHARACTERISTICS UNDER THE TORNADO-LIKE WIND FLOW AFFECTED BY SURFACE ROUGHNESS

Journal of Structural and Construction Engineering

引用

Journal of Structural and Construction engineering 2025年第827期90卷 15-26页

作者： Kikitsu, Hitomitsu Okuda, Yasuo Takadate, Yuki Building Department National Institute for Land and Infrastructure Management Japan Dept. of Architecture Faculty of Science and Engineering Setsunan University Japan Dept. of Structural Engineering Building Research Institute Japan

In this study, PIV and wind pressure experiments were carried out under tornado-like wind flow affected by surface roughness. The authors discussed the effects of swirl ratio and roughness density on the velocity field and the pressure deficit characteristics near the surface. It was confirmed that the velocity field structure gradually transitioned by changing swirl ratio and roughness density. Next, the pressure deficit characteristics showed that the measured pressure was the lowest when the roughness density was 0.014 at any swirl ratio. In the above discussion, the models on the radial velocity distribution and the pressure deficit distribution were proposed. © 2025 Architectural Institute of Japan. All rights reserved.

关键词： Wind stress

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：