检索结果-内蒙古大学图书馆

IEEE Transactions on Artificial Intelligence 2024年第2期5卷 672-683页

作者： Ranjan, Priyesh Khan, Pritam Kumar, Sudhir Das, Sajal K. Department of Computer Science Missouri University of Science and Technology RollaMO65409 United States Department of Electrical Engineering Indian Institute of Technology Patna Patna801106 India

With the enhanced usage of artificial-intelligence-driven applications, the researchers often face challenges in improving the accuracy of data classification models, while trading off the complexity. In this article, we address the classification of time-series data using the long short-term memory (LSTM) network while focusing on the activation functions. While the existing activation functions, such as sigmoid and tanh, are used as LSTM internal activations, the customizability of these activations stays limited. This motivates us to propose a new family of activation functions, called log-sigmoid, inside the LSTM cell for time-series data classification and analyze its properties. We also present the use of a linear transformation (e.g., log tanh) of the proposed log-sigmoid activation as a replacement of the traditional tanh function in the LSTM cell. Both the cell activation and recurrent activation functions inside the LSTM cell are modified with log-sigmoid activation family while tuning the log bases. Furthermore, we report a comparative performance analysis of the LSTM model using the proposed and the state-of-the-art activation functions on multiple public time-series databases. © 2023 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

A Novel Approach on Medical Health Record Management System Using Blockchain

A Novel Approach on Medical Health Record Management System ...

引用

International Conference on Intelligent Systems and Networks, ICISN 2024

作者： Swetha, M.S. Muneshwara, M.S. Madihalli, Amurtha T. Bhardwaj, Anand Ananya Solanki, Vijender Kumar Department of Information Science and Engineering BMS Institute of Technology and Management Bengaluru India Department of Computer Science and Engineering BMS Institute of Technology and Management Bengaluru India Department of Computer Science and Engineering Stanley College of Engineering & Technology for Women Telangana Hyderabad India

ISBN: (纸本)9789819755035

Blockchain technology has garnered significant attention across industries, offering advantages such as enhanced security, privacy, and decentralization. The healthcare sector, with its stringent requirements for data security and privacy, stands to benefit from blockchain’s transformative potential. This paper introduces a novel framework that utilizes Ethereum’s blockchain and IPFS for secure and decentralized management of Electronic Health Records (EHRs). Ethereum provides a trustless platform for executing smart contracts, while IPFS ensures secure data storage with cryptographic identifiers. The framework, called SecureMed, incorporates key components like Ethereum’s programmable blockchain, smart contracts written in Solidity, and IPFS for off-chain scaling. Its architecture consists of user, blockchain, and IPFS layers, granting patients and doctors varying levels of access. Smart contracts govern EHR operations, emphasizing roles and access control. Performance evaluation demonstrates promising results in terms of execution time, throughput, and latency, affirming the system’s suitability for decentralized EHR management. SecureMed addresses security, privacy, and scalability concerns, aligning with the evolving needs of the healthcare industry. As blockchain technology continues to mature, our framework serves as a practical guide for implementing a secure and scalable blockchain-based EHR system, presenting a pathway towards a resilient and efficient healthcare information management infrastructure. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain Decentralized Electronic Health Record Smart contract

来源：评论

学校读者我要写书评

暂无评论

Generating Time-Series Data Using Generative Adversarial Networks for Mobility Demand Prediction

引用

computers, Materials & Continua 2023年第3期74卷 5507-5525页

作者： Subhajit Chatterjee Yung-Cheol Byun Department of Computer Engineering Jeju National UniversityJeju-si63243Korea Department of Computer Engineering Major of Electronic EngineeringJeju National UniversityInstitute of Information Science&TechnologyJeju63243Korea

The increasing penetration rate of electric kickboard vehicles has been popularized and promoted primarily because of its clean and efficient *** kickboards are gradually growing in popularity in tourist and education-centric *** the upcoming arrival of electric kickboard vehicles,deploying a customer rental service is *** to its freefloating nature,the shared electric kickboard is a common and practical means of *** plans for shared electric kickboards are required to increase the quality of service,and forecasting demand for their use in a specific region is *** demand accurately with small data is *** data is necessary for training machine learning algorithms for effective *** generation is a method for expanding the amount of data that will be further accessible for *** this work,we proposed a model that takes time-series customers’electric kickboard demand data as input,pre-processes it,and generates synthetic data according to the original data distribution using generative adversarial networks(GAN).The electric kickboard mobility demand prediction error was reduced when we combined synthetic data with the original *** proposed Tabular-GAN-Modified-WGAN-GP for generating synthetic data for better prediction *** modified The Wasserstein GAN-gradient penalty(GP)with the RMSprop optimizer and then employed Spectral Normalization(SN)to improve training stability and faster ***,we applied a regression-based blending ensemble technique that can help us to improve performance of demand *** used various evaluation criteria and visual representations to compare our proposed model’s *** data generated by our suggested GAN model is also *** TGAN-Modified-WGAN-GP model mitigates the overfitting and mode collapse problem,and it also converges faster than previous GAN models for synthetic data creation.

关键词： Machine learning generative adversarial networks electric vehicle time-series TGAN WGAN-GP blend model demand prediction regression

来源：评论

学校读者我要写书评

暂无评论

Adaptive Malware Detection In Windows Portable Executables (Wpes) 4

Adaptive Malware Detection In Windows Portable Executables (...

引用

4th IEEE Asian Conference on Innovation in technology, ASIANCON 2024

作者： Sathish, A. Babu, N. Bhavani, M. Divya, K. Jhoshna, B. Hemavathi, T. Siddharth Institute of Engineering & Technology Department of Computer Science and Engineering Andra Pradesh India

ISBN: (纸本)9798350354218

It's crucial to comprehend the characteristics of malware variants that enable them to elude malware detection methods as they are created with the intention of avoiding detection by means of a variety of evasion strategies. It is done by a framework designed to generate undetectable malware samples on Windows executable files by incorporating various techniques such as adding benign sections and obfuscating code. Creating undetectable malware variants using a framework can successfully evaded numerous anti-malware programs, showing significantly higher evasiveness than both the original malware and a previously suggested solution. By examining various perturbations and their efficacy, our results contribute to the improvement of malware detection algorithms by providing a better knowledge of the categories to which more evasive malware variants may belong and how they might be created. To create anti-malware programmed that are capable of successfully identifying malware varieties that have not been observed before, experimental findings and observations would be helpful. © 2024 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

An intrusion detection system using ranked feature bagging

引用

International Journal of Information technology (Singapore) 2024年第2期16卷 1213-1219页

作者： Azhagiri, M. Rajesh, A. Karthik, S. Raja, K. Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai India Department of Computer Science and Engineering Jain University Bangalore India Department of IT College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai India

An Intrusion Detection System monitors the network for any malicious attacks. It is an ideal tool for protecting extensive business networks from any kind of attack. In this paper, an Intrusion Detection System using Bagging and ranked features has been proposed. The sample datasets for training the ensemble of classifiers in the bagging approach are obtained by generating subsets of the features ranked according to their importance in the classification process. OneR algorithm has been used to rank the features. The decision tree has been used as the base classifier in the bagging approach. The proposed system was able to predict attacks with an accuracy of 99.71% with a minimal number of features and outperformed other similar approaches discussed in the literature. © The Author(s), under exclusive licence to Bharati Vidyapeeth's institute of computer Applications and Management 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s);author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

关键词： Bagging CIC-IDS 2017 dataset Decision tree Ensemble Feature selection Intrusion detection system OneR feature selection

来源：评论

学校读者我要写书评

暂无评论

Motion Detection in Real-Time Surveillance Using Two Frame Differencing 1

引用

8th International Conference on Information and Communication technology for Competitive Strategies, ICTCS 2023

作者： Biswas, Tamal Bhattacharya, Diptendu Rudrapal, Dwijen Roy, Srijan Mandal, Gouranga National Institute of Technology Agartala Department of Computer Science and Engineering Tripura Agartala India National Institute of Technology Agartala Department of Computer Science and Engineering Tripura Agartala India National Institute of Technology Agartala Department of Computer Science and Engineering Tripura Agartala India National Institute of Technology Agartala Department of Computer Science and Engineering Tripura Agartala India Vellore Institute of Technology Andhra Pradesh India

ISBN: (数字)9789819702107

ISBN: (纸本)9789819702091

This research article delves into the creation of a real-time system for detecting motion, particularly for surveillance purposes. The proposed approach relies on computer vision algorithms to analyze live video streams captured by a camera. By scrutinizing these feeds, the algorithms can discern alterations within the scene, specifically identifying objects in motion. The primary aim is to ensure that this system functions in real time, thereby furnishing instantaneous insights to security personnel. The paper expounds on the different steps integral to motion detection, encompassing procedures like background subtraction, foreground segmentation, and object tracking. To validate the system’s effectiveness, an evaluation is conducted using a collection of actual surveillance videos. The findings underscore the system’s capability to accurately detect moving objects across diverse scenarios. The article concludes by contemplating the system’s potential applications, which span security setups, traffic supervision, and ecological monitoring. The focal technique utilized in this study is Frame Differencing, a means of detecting object motion. This approach is adept at distinguishing moving objects within a given environment. In conjunction with this method, the paper emphasizes the viability of background subtraction to further enhance Frame Differencing, thereby augmenting its precision and efficacy. Upon applying this method to a camera, it is discerned that luminosity has a significant impact on the minimal value. Notably, a minimal value of 35 is identified as the most favorable choice. Here, threshold value 35 is selected because we have seen in our experiment that 35 gives the optimal result with our algorithm. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

A Collaborative Approach for Secured Routing in Mobile Ad-Hoc Network

引用

Intelligent Automation & Soft Computing 2023年第2期35卷 1337-1351页

作者： W.Gracy Theresa A.Gayathri P.Rama Department of Computer Science and Engineering Panimalar Institute of TechnologyChennai600123Tamil NaduIndia Department of Information Technology Vellore Institute of TechnologyVellore632014Tamil NaduIndia Department of Computer Science and Engineering Loyola Institute of TechnologyChennai600123Tamil NaduIndia

Mobile computing is the most powerful application for network com-munication and connectivity,given recent breakthroughs in theﬁeld of wireless networks or Mobile Ad-hoc networks(MANETs).There are several obstacles that effective networks confront and the networks must be able to transport data from one system to another with adequate *** most applications,a frame-work must ensure that the retrieved data reﬂects the transmitted *** driv-ing to other nodes,if the frame between the two nodes is deformed in the data-link layer,it must be *** link-layer protocols immediately disregard the frame and enable the high-layer protocols to transmit it *** other words,because of asset information must be secured from threats,information is a valu-able *** MANETs,some applications necessitate the use of a network method for detecting and blocking these *** a secure intrusion detection system in the network,which provides security to the nodes and route paths in the network,is a major difﬁculty in *** on the network can jeopardize security issues discovered by the intrusion detection system engine,which are then blocked by the network’s intrusion prevention *** bringing the Secure Intrusion Detection System(S-IDS)into the network,a new technique for implementing security goals and preventing attacks will be *** Secure Energy Routing(SER)protocol for MANETs is introduced in this *** protocol addresses the issue of network security by detecting and preventing attacks in the *** data transmission in the MANET is forwarded using Elliptical Curve Cryptography(ECC)with an objective to improve the level of *** Simulator–2 is used to simulate the network and experiments are compared with existing methods.

关键词： Mobile ad-hoc network(MANET) intrusion detection system secure energy routing(SER) elliptical curve cryptography(ECC) security

来源：评论

学校读者我要写书评

暂无评论

Unmasking offensive content: a multimodal approach with emotional understanding

引用

Multimedia Tools and Applications 2025年 1-24页

作者： Singh, Gopendra Vikram Ghosh, Soumitra Firdaus, Mauajama Ekbal, Asif Bhattacharyya, Pushpak Department of Computer Science and Engineering Indian Institute of Technology Patna Bihta Bihar Patna801103 India Fondazione Bruno Kessler Povo Trento38123 Italy University of Alberta Edmonton Alberta Canada Department of Computer Science and Engineering Indian Institute of Technology Bombay Powai Maharashtra Mumbai400076 India

The widespread use of social media has brought people from all over the world closer, but it has also become a platform for spreading hate, offensive content, and misinformation. Various forms of media, such as text, images, audio, and video, are used to disseminate information. In this paper, we tackle the task of identifying offensive and non-offensive text in the context of women’s harassment, considering the intensity of the offense. We propose a novel approach that leverages sentiment and emotion, including their intensity, to enhance the performance of this task. To facilitate our research, we constructed a large-scale dataset called the Women and Child-related Sentiment and Emotion-Aware offensive dataset (WCSEoff) to aid in identifying offensive content. Furthermore, we develop a multi-task model that not only detects whether images contain offensive or non-offensive content and quantifies the intensity of offensiveness as the primary task but also classifies the sentiment and emotions present, along with their respective intensities, as the auxiliary task. By adopting this multitasking framework, we achieve a performance improvement of over 7% compared to approaches that do not incorporate sentiment and emotion analysis. Code and data will be available at https://***/~ai-nlp-ml/***#MOSAIC. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Innovative Approach for Early Heart Disease Prediction: Gaussian Mixture Model and K-Nearest Neighbour 3

Innovative Approach for Early Heart Disease Prediction: Gaus...

引用

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

作者： Surendran, R. Anandaraj, B. Deepa, P. Mageshwari, M. Balamurugan, K.S. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering Madnapalle Institute of Technology & Science Andhra Pradesh Madanapalle India Department of Computer Science and Engineering Panimalar Engineering College Chennai India Department of Computer science and engineering Karpaga Vinayaga College of Engineering and Technology Tamil Nadu Chengalpattu India Department of Electronics and communication engineering Karpaga Vinayaga College of Engineering and Technology Tamil Nadu Chengalpattu India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

An Electrocardiogram (ECG) contributes significantly to early diagnosis and classification of heart diseases, arrhythmia which means irregular heart rate. Regrettably, the process became difficult due to asymmetric and minimal amplitude from recordings of ECG and cannot do the extraction from multiple signals. By using machine learning technology, it can classify and extract multiple samples, but cannot extract the data features from complex data structures. To overcome the limitations, previously introduced metaheuristic optimization (MHO) to improve the classification and extraction. Proposed a method which supports and K-Nearest Neighbour (KNN) Gaussian Mixture Model (GMM) algorithms for determine the abnormalities, predicting cardiac events, and improve diagnostic accuracy. As a result, this can help us to get results more quickly and accurately with sensitivity 99.7% and accuracy 99.2%, for helping healthcare professionals in diagnosing arrythmias, myocardial infarction and any other heart conditions. © 2025 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Decision Tree Based Key Management for Secure Group Communication

引用

computer Systems science & engineering 2022年第8期42卷 561-575页

作者： P.Parthasarathi S.Shankar Department of Computer Science and Engineering Bannari Amman Institute of TechnologySathyamangalam638401India Department of Computer Science and Engineering Hindusthan College of Engineering and TechnologyCoimbatore641032India

Group communication is widely used by most of the emerging network applications like telecommunication,video conferencing,simulation applications,distributed and other interactive *** group communication plays a vital role in case of providing the integrity,authenticity,confidentiality,and availability of the message delivered among the group members with respect to communicate securely between the inter group or else within the *** secure group communications,the time cost associated with the key updating in the proceedings of the member join and departure is an important aspect of the quality of service,particularly in the large groups with highly active ***,the paper is aimed to achieve better cost and time efficiency through an improved DC multicast routing protocol which is used to expose the path between the nodes participating in the group *** this process,each node constructs an adaptive Ptolemy decision tree for the purpose of generating the contributory *** of the node is comprised of three keys which will be exchanged between the nodes for considering the group key for the purpose of secure and cost-efficient group *** rekeying process is performed when a member leaves or adds into the *** performance metrics of novel approach is measured depending on the important factors such as computational and communicational cost,rekeying process and formation of the *** is concluded from the study that the technique has reduced the computational and communicational cost of the secure group communication when compared to the other existing methods.

关键词： Key generation adaptive Ptolemy decision tree cost reduction secure group communication

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：