检索结果-内蒙古大学图书馆

2024 International Symposium on Networks, computers and Communications, ISNCC 2024

作者： Preetha Evangeline, D. Sahu, Atma R. Anandhakumar, P. Siva Subramaniya Nadar College of Engineering Dept. of Information Technology Tamil Nadu Kalavakkam India Coppin State University Dept. of Mathematics and Computer Science BaltimoreMD United States Madras Institute of Technology Anna University Dept. Of Information Technology Tamil Nadu India

ISBN: (纸本)9798350364910

Ubiquitous artificial intelligence (AI) is considered one of the key services in 6G systems. AI services typically rely on deep neural networks (DNN) requiring heavy computation. Hence, to support ubiquitous AI, it is crucial to provide a solution for offloading or distributing computational burden due to DNN, especially at end devices with limited resources. This paper proposes an optimization framework for assigning the tasks of DNN layer computations to computing resources in the network, to reduce the inference latency. To this end, we propose a layered graph model with which simple conventional routing jointly solves the problem of selecting nodes for computation and paths for data transfer between nodes. The proposed framework is applied to derive algorithms for minimizing the end-to-end inference latency. The numerical evaluations show that our new formulation can find a solution for DNN inference job distribution much faster than the existing formulation and that our algorithms can select computing nodes and data paths adaptively to the computational attributes of given DNN inference jobs. © 2024 IEEE.

关键词： Computation offloading

来源：评论

学校读者我要写书评

暂无评论

Classification of Diabetes using the Biologically Plausible Network of Spiking Neurons 1

Classification of Diabetes using the Biologically Plausible ...

引用

1st International Conference on Machine Learning, computer Systems and Security, MLCSS 2022

作者： Hussain, Irshed Thounaojam, Dalton Meitei Dept. of Computer Science & Information Technology Bhubaneswar India National Institute of Technology Silchar Dept. of Computer Science & Engineering Silchar India

ISBN: (纸本)9781665454933

Diabetes is a disease that is becoming more common everywhere every day. The increased blood sugar level caused it to start. This sort of illness may be chronic and manifest when the patient's body is unable to produce enough insulin or fails to use it. The numerous computer or electronic-based systems were identified using various categorisation strategies for predicting and diagnosing diabetes. The 'third generation' of the neural network, i.e., the Spiking Neural Network (SNN), is getting much attention in the research community due to the akin dynamics of biological neurons, energy efficiency, and computational power. SNN is the future for bridging the gap between neuroscience and the Machine Learning (ML) community. The power of SNN can be beneficial in classifying diseases in medical science. This paper's experimentation is done on automatic diabetes prediction. We have observed that the SNN produces significantly superior results in terms of accuracy, computational cost and biological plausibility than that of the state-of-the-arts through careful experimentation on the Pima Indian Diabetes dataset drawn from the Kaggle. The proposed model of SNN uses the SpiFoG learning algorithm, an efficient, biologically plausible supervised learning algorithm, to train SNN models using a metaheuristic approach that uses genetic algorithm (elitist floating-point type) with a hybrid crossover along with the dynamics of the neuron model, and random delay in the synapse model. © 2022 IEEE.

关键词： Neurons

来源：评论

学校读者我要写书评

暂无评论

Implementing a Novel Blockchain Algorithm for Enhanced Data Integrity in Cloud Systems 2

Implementing a Novel Blockchain Algorithm for Enhanced Data ...

引用

2nd IEEE International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2024

作者： Balaji, V. Ambika, S. Varshadevi, S. Rajasekaran, R. Thalapathi Sangeetha, J. Chennai India E.G.S.Pillay Engineering College Department of Information Technology Tamil Nadu Nagapattinam India Grt Institute of Engineering and Technology Dept. of Computer Science and Engineering Tamil Nadu Tiruttani India Saveetha School of Engineering SIMATS Dept. of Computer Science and Engineering Chennai India Sri Venkateswara College of Engineering and Technology Thiruvalluvar Tirupachur India

ISBN: (纸本)9798350384277

Keeping data safe and sound in cloud systems is important. So, new ways need to be found so private information can't get changed or seen without permission by wrong people. This research gives a new blockchain method to make data reliability better in cloud systems. We show how our suggested method is better and more useful than others in keeping data safe. We do this by doing a deep study and comparing with other ways that are currently used. When we look at how many transactions a system can handle, the time it takes for things to happen and its ability to grow bigger without problems, our suggested method does better than other solutions in Comparing Performance. It handles 1000 transactions each second, with a time delay of only 10 milliseconds. It can work well for up to one hundred nodes on the network while still showing it's efficient and able to keep growing bigger over time. The Data Comparison shows that our suggested way is very good at finding out false information, and it can find 98% of this. Besides, it quickly recovers data with a downtime of only 2 hours. This makes it different from old ways by making sure data can't be changed and there are strong checks on who did what. Security Check shows our new plan works well. It stops people spending money twice, stands up against cheating tactics and keeps a strong Byzantine Fault Tolerance (BFT) at 99.9%. The Proof of Stake agreement is both easy on energy and safe. Security of smart contracts is also talked about, to make them safer. © 2024 IEEE.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

Virtual Reality Based Medical Training Simulator and Robotic Operation System

Virtual Reality Based Medical Training Simulator and Robotic...

引用

2022 International Conference on Recent Progresses in science, engineering and Technology, ICRPSET 2022

作者： Rahman, Md. Mustafizur Ishmam, Md Fatin Hossain, Md. Tanvir Haque, Md. Emdadul Dept. of Information and Communication Engineering Bangladesh University of Rajshahi Dept. of Computer Science and Engineering Rajshahi6205 Bangladesh

ISBN: (纸本)9798350332704

In the medical sector learning about the human body and practicing surgeries, the medical students need a real human body which is very costly. Repeatedly practice or undone after practice is almost impossible with the human body. Human anatomy, physiology, etc. subjects are very hard to understand and learn from books and images. Learning surgery on living humans is sometimes unethical and trainee surgeons has to struggle to learn rare surgeries. To solve these problems we use virtual reality (VR) to build a medical training simulator that can provide medical students better understanding and learning about the human body through 3D models of the body. Students can get an interactive learning experience and see how organs work from the molecular level and perform several operations. Since this is a simulation everything a new learner will do can be undone and re-practiced. On the other hand skilled surgeons are not available in all places in the country especially in remote places. A patient who needs the critical surgical treatment has to travel to a city to take the treatment by the expert surgeons. To solve this problem in this project we also connect a robot to our VR based system. A skilled surgeon can operate in the virtual environment from a distant place using the robot. The vision system of the robot can be realized by the surgeon through VR headset and he or she feels like, he or she is present there. Surgeons can control the robotic hands and tools necessary to perform the surgery from the remote place. This will reduce the trouble of patients traveling from remote places to city area for surgery. We implement the demo system in the lab and show some results which indicate the applicability of the proposed system. © 2022 IEEE.

关键词： Robotic surgery

来源：评论

学校读者我要写书评

暂无评论

Interactive Visualization System of 3-D digital Elevation Model For Mountain Collapse Simulation 8

Interactive Visualization System of 3-D digital Elevation Mo...

引用

8th International Conference on Applied System Innovation, ICASI 2022

作者： Yeh, Shih-Ching Hu, Hsuan Sheng, Shao-Rong Wu, Yi-Ru National Central University Dept. of Computer Science and Information Engineering Taiwan National Tsing Hua University Dept. of Computer Science Taiwan

ISBN: (纸本)9781665496506

In this paper, we create a multi-type interactive visualization system that integrates virtual reality, mixed reality, and web browsers. To enhance the immersive experience, we design a hand gesture control system to operate the visualization webpage. In addition, the system uses real-life Three-Dimensional(3D) digital evaluation model data from Geographic information System(GIS) to build a terrain model in a 3D environment and simulate a mountain collapse situation. Visualizing the terrain model is done with the aid of the game engine Unity3D. Using a game engine as a simulator for surface geological processes represents a novel approach to computation. We also provide an interface to recreate a new terrain model easily and quickly. © 2022 IEEE.

关键词： Data visualization

来源：评论

学校读者我要写书评

暂无评论

Hybrid Quantum Approximate Optimization Algorithm (HQAOA) for Efficient Blockchain Transaction Scheduling 3

Hybrid Quantum Approximate Optimization Algorithm (HQAOA) fo...

引用

3rd International Conference on Intelligent Systems, Advanced Computing, and Communication, ISACC 2025

作者： Paul, Soumyadip Chakraborty, Sarit Government College of Engg. & Ceramic Technology Dept. Of Information Technology WB Kolkata700010 India Government College of Engineering and Leather Technology Dept. of Computer Science and Engineering WB Kolkata700106 India

ISBN: (纸本)9798331523893

Quantum technology offers a transformative approach to solving complex computational challenges in decentralized systems, particularly in blockchain transaction scheduling. Efficient transaction scheduling is critical in distributed ledger systems, which often face challenges like dynamic transaction loads. This work proposes a novel approach namely Hybrid Quantum Approximate Optimization Algorithm (HQAOA) which combines Multi-Agent QAOA (MA-QAOA) and Adaptive Layer QAOA (AL-QAOA) to provide a robust solution to such issues. HQAOA leverages a decentralized optimization framework where multiple agents, each representing a node in the network, optimize local transaction scheduling while considering global constraints. Additionally, HQAOA adapts to varying transaction loads by dynamically adjusting the number of quantum layers for each agent, ensuring computational efficiency under different conditions. Such dynamic layer adjustment mechanisms mitigate the adverse effects of quantum noise and ensures optimal performance in scenarios with fluctuating transaction loads. In contrast to traditional QAOA, which struggles with noise and scaling issues, HQAOA provides improved performance by balancing the complexity of the problem with available quantum resources. Experimental results signify the future potential of HQAOA to outperform QAOA, particularly in noisy environments and irregular transaction conditions. This work demonstrates the potential of HQAOA to optimize blockchain transaction scheduling in decentralized systems. © 2025 IEEE.

关键词： Qubits

来源：评论

学校读者我要写书评

暂无评论

Fingerprint generation and authentication though Adaptive convolution generative adversarial network (ADCGAN) 7

Fingerprint generation and authentication though Adaptive co...

引用

7th International Multi-Topic ICT Conference: IMTIC 2023

作者： Mustafa, Syed Muhammad Nabeel Zehra, Syeda Sundus Baber, Alina Siddiqui, Maria Andleeb Ned University of Engineering and Technology Dept. of Computer Science & Information Technology Karachi Pakistan Sir Syed University of Engineering and Technology Dept of Software Engineering Karachi Pakistan

ISBN: (纸本)9798350338461

Fingerprints are crucial in identification of humans. The uniqueness of finger prints makes it an interesting subject. Fingerprints are termed as a technique used to define, assess, and quantify a person's physical and behavioral property. Deep learning has made its application in all the major fields such as natural language processing, computer vision and speech processing. Deep learning has also found its application in the important subject of fingerprint synthesis and biometric. The ever-growing complexity of fingerprint authentication issues, from cellphone authentication to airport security systems, seems to be best handled by these models. In recent years, deep learning-based models have been used more and more to raise the accuracy of various fingerprint recognition systems. The persuasive capacity of Generative Adversarial Networks (GANs) to generate believable instances can be credibly taken from an existing distribution of samples. GAN exhibits exceptional performance on data generation-based tasks and also encourages study in privacy and security. In this work, using Adaptive Deep Convolution Generative Adversarial Networks (ADCGAN), we develop a model that generates and authenticate the fingerprints. A Socofing dataset was trained on ADGAN model. The model gave 92% accuracy. The conduct of fingerprint research has been made possible due to ADGAN, without restrictions related to the confidential nature of biometric data. © 2023 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Book Recommendation System using R Programming - A Comparative Study. 4

Book Recommendation System using R Programming - A Comparati...

引用

4th International Conference on Innovative Practices in Technology and Management, ICIPTM 2024

作者： Sandhiya, B. Meera, K.N. Broumi, Said Amrita School of Engineering Dept. of Computer Science and Engineering Amrita Vishwa Vidyapeetham Bengaluru India Amrita School of Engineering Dept. of Mathematics Amrita Vishwa Vidyapeetham Bengaluru India Faculty of Science Ben m'Sik University of Hassan Ii Laboratory of Information Processing Casablanca Morocco

ISBN: (纸本)9798350307757

A Recommendation System (also known as Recommender System) is built for the purpose of recommending similar items to the user based on their interest. The item can be anything like movies, music, books, songs, etc. Many famous platforms such as Netflix and YouTube also use recommendation system. This paper focuses on comparing and studying the performance of the Recommender System for books that uses various different techniques such as k-means Clustering, PCA, Feature Selection, etc. © 2024 IEEE.

关键词： Recommender systems

来源：评论

学校读者我要写书评

暂无评论

Staging of Different Tumor by Utilizing Laser Guidance (@405 nm) in CT Scan Images Along with Statistical Analysis

引用

Lasers in engineering 2025年第4-6期59卷 309-325页

作者： Amjad, M. Ullah, H. Siddique, M.A. Majid, M.A. Aleem, A. Akhtar, M. Gilanie, G. Abdullah-Al-Wadud, M. Farhan, M. Akram, A. Batool, Z. Nazir, A. Biophotonics Imaging Techniques Laboratory Institute of Physics The Islamia University of Bahawalpur 63100 Pakistan Department of Computer Science Faculty of Computing The Islamia University of Bahawalpur Bahawalpur Pakistan Dept. of Software Engineering College of Computer and Information Sciences King Saud University Riyadh11543 Saudi Arabia School of Earth Sciences and Engineering Hohai University Nanjing China

Early detection of lung cancer, liver cancer (HCC), and pancreatitis is crucial for effective treatment. This study assessed the use of laser guidance CT scans for diagnosis and staging. 26 patients of CT scan which were collected from BVH and civil hospital Bahawalpur, Pakistan. Visible light with a 405 nm wavelength is used. Results showed staging of lung cancer (2 at stage 1, 2 at stage 2, 3 at stage 4) and HCC (stages 1 to 4a). Pancreatic diseases detected included acute pancreatitis (44%), chronic pancreatitis (22%), gallstones (22%), and pancreatic tumors (11%). Alkaline phosphatase, SGOT, and blood urea levels were notably elevated in all three cancers compared to controls. CT scans show promise in identifying cancer stages and diagnosing pancreatitis, aiding in tailored treatment. Statistical analysis shows that alkaline phosphatase emerges as a potential biomarker for these conditions. ©2025 Old City Publishing, Inc.

关键词： Image analysis

来源：评论

学校读者我要写书评

暂无评论

A System to Track Fabricated Content in Social media using Machine Learning Approach

A System to Track Fabricated Content in Social media using M...

引用

2024 IEEE International Conference on Recent Advances in science and engineering Technology, ICRASET 2024

作者： Hegde, Ramakrishna Soumyasri, S.M. Shivashankara, S. Kavyashree, M.K. Pemula, Rambabu Harshitha, M. Vidyavardhaka College of Engineering Affiliated to Visvesvaraya Technological University Dept. of Computer Science and Engineering Mysuru India Vidya Vikas Institute of Engineering and Technology Affiliated to Visvesvaraya Technological University Dept. of Computer Applications Mysuru India Kr Pete Krishna Govt. Engg. College Dept. of Computer Science and Engineering Krishnarajapet Mandya India Sjce Jssstu Mysore India Vidya Jyothi Institute of Technology Dept. of Artificial Intelligence Hyderabad India Vidya Vikas Institute of Engineering and Technology Dept.of Information Science and Engg. Mysore India

ISBN: (纸本)9798350388602

In today's society, when the internet is pervasive, everyone gets their news from a variety of online sources. information can swiftly reach millions of users in a short amount of time due to the growing usage of social media sites like Facebook, Twitter, and others. Fake news has far-reaching effects, ranging from swaying election outcomes in favor of particular politicians to fostering prejudiced viewpoints. The primary platforms for disseminating fake news are Instagram, WhatsApp, and numerous other social media platforms. By presenting a machine learning-based fake news detection algorithm, this work provides a remedy. This model needs fictitious data that was gathered from multiple information sources. Data is extracted using web analytics, which is mostly used to build datasets. Real data sets and fake data sets are the two primary categories into which the data is separated. Random forest, logistic regression, decision trees, KNN, and gradient boosting are the classifiers used to classify the data. The data is categorized as true or false data based on the version that was received. The user will be able to determine whether or not the information on the website is fraudulent based on this. © 2024 IEEE.

关键词： Adversarial machine learning

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：