检索结果-内蒙古大学图书馆

第41届中国控制会议

作者： Saifei Ma Jin Tang Zerui Li Kun Li Wenjun Lv School of Computer Science and Technology Anhui University Institute of Artificial Intelligence Hefei Comprehensive National Science Center Anhui Key Laboratory of Multimodal Cognitive Computing Anhui University Institute of Advanced Technology University of Science and Technology of China Department of Automation University of Science and Technology of China

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In recent years,the traditional well logging interpretation method manually operated by experts has shown some problems,such as low efficiency and poor results,facing the challenges of high dimension,diversity and complexity of current logging *** the progress of artificial intelligence,its effectiveness and efficiency in logging interpretation have gradually attracted researchers' ***,the uncertainty of logging process necessitates the preprocess of collected logging data before employing the artificial intelligence ***,an intelligent well logging interpretation system is designed and developed in this *** the logging data anomalies may include data repetition,null value,etc.,a specific preprocessing module is designed in the system to tackle the data anomalies,so as to ensure that the data input into the algorithms is correct and *** governance can effectively enhance the effectiveness of data,so it is used to guide the design and implementation of logging interpretation ***,user mode and debug mode are designed to solve the problem of cross functional conflict in data governance.

关键词： System Development Logging Interpretation Data Governance Artificial Intelligence

来源：评论

学校读者我要写书评

暂无评论

MMCo-Clus - An Evolutionary Co-clustering Algorithm for Gene Selection (Extended abstract) 39

MMCo-Clus - An Evolutionary Co-clustering Algorithm for Gene...

引用

39th IEEE International Conference on Data Engineering, ICDE 2023

作者： Cui, Laizhong Acharya, Sudipta Mishra, Sumit Pan, Yi Huang, Joshua Zhexue Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Queen's University School of Computing ON Canada Indian Institute of Information Technology Department of Cse Assam Guwahati India Chinese Academy of Sciences Shenzhen Institute of Advanced Technology China

ISBN: (纸本)9798350322279

Dimensionality reduction through feature selection becomes inevitable to overcome the problem of the Curse of dimensionality. In this article, we propose a feature (gene) selection method for high dimensional gene expression (GE) data through a Multi-objective optimization-based Multi-view Co-Clustering algorithm (named MMCo-Clus). A thorough comparative analysis with existing feature selection algorithms using external/internal evaluation metrics supports our proposed method's potency. © 2023 IEEE.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Simulate the Machine Learning Algorithm to Organize the CRAHN Network System 3

Simulate the Machine Learning Algorithm to Organize the CRAH...

引用

3rd International Conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Prabakaran, P. Chandra Sekhar Reddy, L. Ravikumar, L.V.D. Verma, Manish Kumar School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Department of Computer Applications Chennai India Hyderabad Medchal India Shri Vishnu Engineering College for Women Department of Information Technology Bhimavaram India Lovely Professional University Department of Psychology Phagwara India

ISBN: (纸本)9798350330724

Using available channels in a wireless spectrum, cognitive radio (CR) may automatically adjust transmission settings to optimize radio operational behaviour. To function properly, a CR ad hoc network (CRAHN) has to be dynamically capable construct autonomous and decentralized networks without negatively impacting licensed main user (PU) systems. For this reason, an effective spectrum necessitates a system structure based on artificial intelligence. This research provides a model for network planning, learning, and dynamic configuration that is based on a distributed autonomous CRAHN network system that uses reinforcement learning. The proposed optimization techniques for spectrum sensing, ad hoc network design, and context-aware signal categorization are all derived from the system model and are based on machine learning. The cognitive and detection engines may be used to examine the spectrum utilization and neighbour network status in the immediate area. To adapt to the ever-changing nature of the wireless environment, the suggested policy engine may generate network operating policies, identify policy conflicts, and infer the best course of action. Together with the erudition engine, whereby apply the recommended machine-learning methods, the decision engine arrives at the best possible settings for the CRAHN. In addition, guarantee peaceful cohabitation with surrounding systems to have excellent signal context recognition ability. © 2023 IEEE.

关键词： Ad hoc networks

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Alzheimer's Detection: Hybrid Deep Learning Models in Experimental Analysis and Insights

Revolutionizing Alzheimer's Detection: Hybrid Deep Learning ...

引用

International Conference on Trends in Electronics and Informatics (ICEI)

作者： A. Praveena Y. Kalpana Department of Computer Science Vel's Institute of Technology & advanced Studies Chennai Tamil Nadu India Dept of Applied computing and Emerging Technologies Vels Institute of Science Technology & Advanced Studies Chennai Tamil Nadu India

ISBN: (数字)9798331544607

ISBN: (纸本)9798331544614

The detection and diagnosis of Alzheimer's Disease (AD) are critically important due to the increasing prevalence of the condition, especially among aging populations. This study investigates the enhancement of AD detection through hybrid deep learning models, utilizing a dataset from Kaggle comprising images categorized into four stages: Mild Demented, Very Mild Demented, Non-Demented, and Moderate Demented. We developed two innovative models: the FusionTree Classifier (FTC) and the FusionNet Integrator (FNI). The FTC combines Random Forest and Bagging techniques to reduce variance and overfitting, achieving an impressive accuracy of 96.78%. This hybrid approach leverages the strengths of ensemble learning methods, enhancing robustness and reliability in classification tasks. On the other hand, the FNI integrates VGG's powerful feature extraction capabilities with the classification strength of Support Vector Machines (SVMs), effectively identifying complex image patterns and achieving an even higher accuracy of 97.41 %. By combining convolutional neural networks (CNNs) for feature extraction with SVMs for classification, FNI capitalizes on the strengths of both techniques, demonstrating superior predictive accuracy compared to traditional methods. These advancements hold significant promise for improving diagnostic accuracy and patient outcomes in AD and other neurological conditions. The methodologies proposed in this study offer a reliable framework for early detection, which is crucial for timely intervention and management of the disease.

关键词： Support vector machines Deep learning Analytical models Accuracy Feature extraction Data models Alzheimer's disease Random forests Bagging Overfitting

来源：评论

学校读者我要写书评

暂无评论

Design of AED Based Drone to Deliver the Medical Kit on an Emergency Basis 3

Design of AED Based Drone to Deliver the Medical Kit on an E...

引用

3rd International Conference on Advancement in Electronics and Communication Engineering, AECE 2023

作者： Nagarani, P. Ahmad, Mohd Wazih Shalini, R. Singh, Pavitar Parkash Cvr College of Engineering Department of Emerging Technologies Hyderabad India Shri Ram Murti Smarak College of Engineering and Technology Department of Computer Science and Engineering Bareilly India Vels Institute of Science Technology and Advanced Studies Department of Bca & It School of Computing Sciences Chennai India Lovely Professional University Department of Management Phagwara India

ISBN: (纸本)9798350330724

Access to reliable modes of transportation is essential. Postal delivery to multi-million-dollar freight transports, practically everything is linked to its connections. Wheeled motor vehicles and manned aeroplanes are now the only options for transporting medical supplies at times of urgent need, which may be expensive, time-consuming, and often impossible if the emergency site is far. Drones are a game-changer in the medical industry because they can transfer vital supplies like blood and medical equipment. Unfortunately, given the state of the art, the drone's battery life is a constraint that may slow down the delivery process. This article details the research into the mechanisms designed for drones to increase their battery life and efficiently deliver first aid supplies. The drone's system safely delivers and drops medical supplies, reducing the drone's takeoffs and landings. The primary goal of this research is to develop a device that can safely transport medical equipment to its destination and then carefully unload it there. Results showed the system could safely transport and deploy first aid supplies during flight and landing. © 2023 IEEE.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Hybrid Signal Integrity Modeling and Analysis of Heterogeneous Integrated System With Neuromorphic Darwin Chip

IEEE Transactions on Signal and Power Integrity

引用

IEEE Transactions on Signal and Power Integrity 2024年 3卷 37-46页

作者： Chen, Quankun Ma, Hanzhi Li, Da Tao, Tuomin Tan, Shurun Liu, En-Xiao Schutt-Aine, Jose Li, Er-Ping Zhejiang University Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems and Applications College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang University University of Illinois at Urbana-Champaign Institute Haining314400 China A∗star Institute of High Performance Computing Singapore138632 Singapore University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL61820 United States

This article introduces a comprehensive approach for designing and analyzing signal integrity in heterogeneous integrated systems that incorporate neuromorphic Darwin chips. The proposed integrated system architecture includes a neuromorphic Darwin chip, digital signal processing unit, microcontroller unit, field programmable gate arrays, and coding and decoding modules to encode and reconstruct analog spiking signals. The study evaluates the encoding module and the heterogeneous integration structure and conducts signal integrity analysis. To achieve optimal signal integrity performance, the article proposes a novel binocular eye diagram analysis technique. This innovative approach guides the encoding algorithm modification and improves the overall system performance. This research is the first to combine joint field-circuit simulation, heterogeneous integration modeling, and signal integrity analysis of the Darwin neuromorphic chip, and it is expected to serve as a valuable reference for future studies on similar systems. © 2022 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Securing Distributed Database Using Elongated RSA Algorithm 7

Securing Distributed Database Using Elongated RSA Algorithm

引用

7th International Conference on advanced computing and Communication Systems, ICACCS 2021

作者： Radhakrishnan, Sangeetha Akila, A. Vels Institute of Science Technology and Advanced Studies School of Computing Sciences Department of Computer Science Chennai India

ISBN: (纸本)9781665405201

Securing data, management of the authorised access of the user and maintaining the privacy of the data are some of the problems relating with the stored data in the database. The security of the data stored is considered as the major concern which is to be managed in a very serious manner as the users are sensitive about their shared data. The user's data can be protected by the process of cryptography which is considered as the conventional method. advanced Encryption Standard (AES), Data Encryption Standard(DES), Two Fish, Rivest Shamir Adleman Algorithm (RSA), Attribute Based Encryption (ABE), Blowfish algorithms are considered as some of the cryptographic algorithms. These algorithms are classified into symmetric and asymmetric algorithms. Same key is used for the encryption and decoding technique in symmetric key cryptographic algorithm whereas two keys are used for the asymmetric ones. In this paper, the implementation of one of the asymmetric algorithm RSA with the educational dataset is done. To secure the distributed database, the extended version of the RSA algorithm is implemented as the proposed work. © 2021 IEEE.

关键词： Cryptography

来源：评论

学校读者我要写书评

暂无评论

Secure Data Embedding in Digital Images: Enhancing Covert Communication with LSB-Based Techniques

Secure Data Embedding in Digital Images: Enhancing Covert Co...

引用

3rd International Conference on Machine Learning and Data Engineering, ICMLDE 2024

作者： Babu, Tina Nair, Rekha R. Rajesh, M.T. Kishore, S. Department of Computer Science and Engineering School of Advanced Computing Alliance University Bengaluru India Department of Computer Science and Engineering Dayananda Sagar University Bengaluru India Nitte Institute of Professional Education Karnataka Mangalore India

Information security and the ability to convey secret messages have been necessities since the dawn of civilization. Various media forms, such as photos, audio files, and videos, offer a conducive environment for concealing information that is invisible to the human eye in the current digital era by taking advantage of superfluous or unused data bits. This hidden information can be used for secret communication or as a way to include more messages into a single file, which will minimize the quantity of data that needs to be sent. In order to encode and store messages within the RGB pixels of a cover image (canvas image) without causing visual distortion, two methods are shown in this study. Both approaches split the message into separate segments, which are then translated into 8-bit binary values. These values are then encrypted using a straightforward symmetric exclusive OR (XOR) encryption key, and the message is encoded in the canvas image by changing the pixel value's least significant bit (LSB). The first approach encodes the secret message from top to bottom and left to right by sequentially storing it beginning with the top-left pixel. By encoding the message bits into the cover image pixels at random, the second technique reduces the susceptibility of the concealment to analysis. By using redundant data in digital media, these approaches can hide information while preserving the original visual integrity. This makes them an effective and safe way to communicate covertly or embed data into a single file, which maximizes data transmission. © 2025 The Author(s).

关键词： Sensitive data

来源：评论

学校读者我要写书评

暂无评论

Transfer Learning with ResNet50 for Robust Traffic Sign Recognition: Addressing Challenges in Lighting, Occlusion, and Class Imbalance

Transfer Learning with ResNet50 for Robust Traffic Sign Reco...

引用

IT Innovation and Knowledge Discovery (ITIKD), International Conference on

作者： Rekha R Nair Kishore S Nandana Santhosh Tina Babu H Ramamoorthy Department of Computer Science and Engineering Alliance School of Advanced Computing Alliance University Bengaluru India Department of Computer Applications Nitte Institute of Professional Education Nitte (Deemed to be University) Mangalore India

ISBN: (数字)9798350355468

ISBN: (纸本)9798350355475

The efficacy of deep learning models, specifically Convolutional Neural Networks (CNNs), in accurately recog- nizing and clas- sifying a diverse range of traffic signs. The research utilizes a meticulously curated dataset obtained from Kaggle, comprising annotated images labeled with corresponding ClassIds representing various traffic sign categories. The moti- vation behind this work stems from the critical need for robust and reliable traffic sign recognition systems, which play a vital role in enhancing safety, efficiency, and enabling autonomy in transportation systems. Through systematic experimentation and rigorous validation, the study assesses the performance of CNN models across various evaluation metrics, shedding light on the effectiveness of these deep learning architectures in accurately discerning nuanced visual cues present in traffic sign imagery. Furthermore, the research explores the challenges posed by factors such as variations in lighting conditions, occlusions, and class imbalances, proposing potential mitigation strategies. The proposed methodology utlized transfer learning model ResNet50 which achieved accuracy of 92

关键词： Visualization Technological innovation Systematics Transfer learning Lighting Transportation Safety Convolutional neural networks Reliability Residual neural networks

来源：评论

学校读者我要写书评

暂无评论

Identification of Key Genes as Potential Drug Targets for Gastric Cancer

引用

Tsinghua science and Technology 2023年第4期28卷 649-664页

作者： Md.Tofazzal Hossain Md.Selim Reza Yin Peng Shengzhong Feng Yanjie Wei Center for High Performance Computing Joint Engineering Research Center for Health Big Data Intelligent Analysis TechnologyShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100049China Department of Statistics Bangabandhu Sheikh Mujibur Rahman Science and Technology UniversityGopalganj 8100Bangladesh Guangdong Provincial Key Laboratory for Genome Stability and Disease Prevention and Regional Immunity and Diseases Department of PathologyShenzhen UniversityShenzhen 518060China

Gastric cancer(GC)is one of the most common cancers and ranks the third in cancer mortality all over the *** goal of this study was to identify potential hub-genes,highlighting their functions,signaling pathways,and candidate drugs for the treatment of GC *** used publicly available next generation sequencing(NGS)data to identify differentially expressed(DE)*** top DE genes were mapped to STRING database to construct the protein-protein interaction(PPI)network and top hub genes were selected for further *** found a total of 1555 DE genes with 870 upregulated and 685 downregulated genes in *** selected the top 400(200 upregulated and 200 downregulated)genes to construct a PPI network and extracted the top 15 hub *** gene ontology(GO)term and kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analyses of the 15 hub genes exposed some important functions and signaling pathways that were significantly associated with GC *** survival analysis of the hub genes disclosed that the lower expressions of the three hub genes CDH2,COL4A1,and COL5A2 were associated with better survival of GC *** three genes might be the candidate biomarkers for the diagnosis and treatment of ***,we considered 3 key proteins(genomic biomarkers)(COL4A1,CDH2,and CO5A2)as the drug target proteins(receptors),performed their docking analysis with the 102 meta-drug agents,and found Everolimus,Docetaxel,Lanreotide,Venetoclax,Temsirolimus,and Nilotinib as the top ranked 6 candidate drugs with respect to our proposed target proteins for the treatment against GC ***,the proposed drugs might play vital role for the treatment against GC patients.

关键词： gastric cancer hub genes candidate genes molecular docking candidate drugs

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：