检索结果-内蒙古大学图书馆

6th World Conference on Smart Trends in Systems, Security and Sustainability, WS4 2022

作者： Adebiyi, Marion Enwere, Miracle Nmesomachi Shekari, Abenego Adebiyi, Ayodele Osang, Francis B. Department of Computer Science College of Pure and Applied Sciences Landmark University Kwara State Omu-Aran Nigeria Ogun State Ota Nigeria Department of Computer and Information Sciences College of Science and Technology Covenant University Ogun State Ota Nigeria Landmark University SDG4: Quality Education Kwara State Omu-Aran Nigeria Department of Computer Science National Open University of Nigeria Abuja Nigeria

ISBN: (纸本)9789811976599

Deep learning (DL) is an actively growing domain of machine learning owing to the proliferation of big data in multifaceted fields of study. Widespread in literature, there are multiple reports on the implementation of long short-term memory network (LSTM)-based models in the field of bioinformatics for the analysis of the vast amount of genomic data. Genomic data is quintessentially a contiguous stretch of unspaced characters that correspond to the nucleotides adenine (A), guanine (G), cytosine (C), and thymine (T) known as deoxyribonucleic acid (DNA). The DNA sequence must be converted to formats readable by LSTM algorithms run on computers, a process known as digitization. This paper aims to uncover and elucidate the various techniques for digitization in studies that apply LSTM for predictive and classification problems as it relates genomics. We hope this paper would serve as a template for assessing pre-processing techniques for suitability in future studies involving deep learning. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning (DL) Digitization Feature extraction Genomics Long short-term memory (LSTM) network Pre-processing Recurrent neural network (RNN)

来源：评论

学校读者我要写书评

暂无评论

Addressing the Rising Challenge of Malware Innovative Detection and Mitigation Techniques

Addressing the Rising Challenge of Malware Innovative Detect...

引用

2024 International Conference on Communication, computer sciences and Engineering, IC3SE 2024

作者： Balaram, A. Umashankari, E. Dutt, Amit Bharadwaj, Garima Revathi, V. Albawi, Ali Mlr Institute Of Technology Department Of Computer Science And Engineering Telangana Hyderabad India Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India Lovely Professional University Phagwara India Amity Business School Amity University Greater Noida India New Horizon College Of Engineering Department Of Applied Sciences Bangalore India College Of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq

ISBN: (纸本)9798350366846

This research talks about Hybrid Anomaly Detection (HAD), a complex technology for finding and stopping malware. There are four different methods to apply the approach. The following are a few examples: EDR, DBA, TIS, and EML. The goal of the ablation specialists is to enhance the HAD structure in whatever way possible. With a success rate of 99.5% and only one false positive, DBA starts monitoring the process the second it starts. EML makes the system more flexible and useful by finding malware using probability estimates and weighted voting. TIS protects against new threats and motivates people to work together by sharing and prioritizing threat information. EDR is all about computer security by evaluating and reducing risks. The ablation study focuses on how well each algorithm can identify things, how flexible it is, how well it can work with others, and how safe it keeps endpoints safe. Since these algorithms work well together, the HAD framework offers a complete answer that performs better than other approaches in many ways. This study suggests a good way for everyone to work together to fight modern computer risks, which will improve cybersecurity. © 2024 IEEE.

关键词： Malware

来源：评论

学校读者我要写书评

暂无评论

Deep Broad Learning for Emotion Classification in Textual Conversations

引用

Tsinghua science and technology 2024年第2期29卷 481-491页

作者： Sancheng Peng Rong Zeng Hongzhan Liu Lihong Cao Guojun Wang Jianguo Xie Center for Linguistics and Applied Linguistics and Laboratory of Language Engineering and ComputingGuangdong University of Foreign StudiesGuangzhou 510006China Guangdong Provincial Key Laboratory of Nanophotonic Functional Materials and Devices South China Normal UniversityGuangzhou 510006China School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou 510006China Modern Education Technology Center Guangdong University of Foreign StudiesGuangzhou 510006China

Emotion classification in textual conversations focuses on classifying the emotion of each utterance from textual *** is becoming one of the most important tasks for natural language processing in recent ***,it is a challenging task for machines to conduct emotion classification in textual conversations because emotions rely heavily on textual *** address the challenge,we propose a method to classify emotion in textual conversations,by integrating the advantages of deep learning and broad learning,namely *** aims to provide a more effective solution to capture local contextual information(i.e.,utterance-level)in an utterance,as well as global contextual information(i.e.,speaker-level)in a conversation,based on Convolutional Neural Network(CNN),Bidirectional Long Short-Term Memory(Bi-LSTM),and broad *** experiments have been conducted on three public textual conversation datasets,which show that the context in both utterance-level and speaker-level is consistently beneficial to the performance of emotion *** addition,the results show that our proposed method outperforms the baseline methods on most of the testing datasets in weighted-average F1.

关键词： emotion classification textual conversation Convolutional Neural Network(CNN) Bidirectional Long Short-Term Memory(Bi-LSTM) broad learning

来源：评论

学校读者我要写书评

暂无评论

EuropeanLawAdvisor: An open source search engine for European laws

EuropeanLawAdvisor: An open source search engine for Europea...

引用

2024 IEEE International Conference on Big Data, BigData 2024

作者： Russo, Raffaele Russo, Diego Orlando, Gian Marco Romano, Antonio Riccio, Giuseppe Gatta, Valerio La Postiglione, Marco Moscato, Vincenzo University of Naples Federico II Department of Electrical Engineering and Information Technology via Claudio 21 80125 Naples Italy Northwestern University Department of Computer Science McCormick School of Engineering and Applied Science 2233 Tech Dr Evanston IL 60208 United States

ISBN: (纸本)9798350362480

Legal Artificial Intelligence has emerged as an essential field, focusing on AI technologies that facilitate various legal tasks and alleviate the workload of legal professionals. Despite advancements in Legal Artificial Intelligence, there remains a critical gap in systems that can provide both comprehensive and contextually accurate retrieval tailored to the intricate structure of EU legislation. We propose EuropeanLawAdvisor, an efficient and user-friendly legal information retrieval system designed to deliver tailored responses to legal queries. This system utilizes open-source Large Language Models within a Retrieval-Augmented Generation framework, facilitating precise and relevant information retrieval. The system employs a robust retrieval approach that integrates multi-match, k-nearest neighbors, hybrid methods, and TF-IDF search strategies across both complete documents and segmented text indexes, ensuring comprehensive retrieval for diverse query types. The implementation of the framework has demonstrated significant improvements in the accuracy and relevance of responses to EU legal queries, enhancing both the retrieval of relevant legal documents and the generation of precise responses. We show that EuropeanLawAdvisor, leveraging open-source models like Phi3-mini-3B and LLaMa-3-8B, achieves competitive Faithfulness and Relevance compared to GPT-4-Turbo. The performance gap narrows significantly in zero-shot scenarios, and our approach outperforms GPT-4-Turbo in the percentage of answered questions. We publicly release our code on GitHub: https://***/raffaele-russo/EuropeanLawAdvisor. © 2024 IEEE.

关键词： Nearest neighbor search

来源：评论

学校读者我要写书评

暂无评论

Leveraging Information-Centric Edge Computing in Private 5G Cellular Networks via the W3C Web of Things

Leveraging Information-Centric Edge Computing in Private 5G ...

引用

Consumer Communications and Networking Conference, CCNC IEEE

作者： Jan Romann Hugo Hakim Damer T M Rayhan Gias Olaf Bergmann Department of Electrical Engineering and Computer Science Faculty of Technology University of Applied Sciences Emden/Leer Emden Germany

ISBN: (数字)9798331508050

ISBN: (纸本)9798331508067

In this paper, we present an architecture for the deployment of an edge computing system based on Named Data Networking (NDN) as part of a private 5G network. Our proposed architecture integrates IP-based and non-IP-based components using the W3C Web of Things (WoT) standards, including a Thing Description Directory (TDD). Our results highlight the potential of both edge computing and WoT concepts for private 5G deployments but also reveal several standardization gaps that need to be closed to make effective use of the new technologies.

关键词： Cellular networks 5G mobile communication W3C computer architecture Service-oriented architecture Standards Edge computing

来源：评论

学校读者我要写书评

暂无评论

Use of IOT in computer Control Using Hand Gesture Using AT Mega 328 over the Cloud

Use of IOT in Computer Control Using Hand Gesture Using AT M...

引用

International Conference on ICT in Business Industry & Government (ICTBIG)

作者： Ishwarlal Rathod Kunal Rathod Neha Gupta Computer Science and Information Technology Symbiosis University of Applied Sciences Indore India Computer Science and Engineering Acropolis Institute of Technology and Research Indore India

In the realm of remote control, my preference is computer manipulation through hand gestures. Recent strides in technology showcase the feasibility of using manual gestures on Arduino platforms, facilitated by cloud computing. A Wi-Fi-based hand gesture computer control system was developed using an ESP-01 Wi-Fi module and an Arduino microcontroller, enabling remote control and monitoring without geographical constraints or time limitations. The ESP8266 Wi-Fi module played a crucial role in establishing wireless communication with an Android application (S Remote) for transmitting commands to regulate domestic appliances. The AT mega 328 AVR series Microcontroller R3, lacking built-in Wi-Fi, required the ESP-01 Wi-Fi module for wireless communication and programming. The Arduino IDE facilitated programming, incorporating ESP-01 and LCD components. Hand gesture-controlled robots and PC/laptop hand gesture control systems, both utilizing Arduino technology, exemplify similar applications. The Human Machine Interface (HMI) concept involves physical components and software enabling communication between users and machines. HMI devices, including LED indicators and touch screens, traditionally use keyboards and mice. This research implemented a hand gesture controller using Arduino technology, specifically for web browser features, video playback, and VLC media player audio adjustments. The ESP-01 Wi-Fi module, configured via AT instructions through a UART serial connection, played a key role in integrating a hand gesture system for effective computer control. Users can perform actions like playing or pausing videos and adjusting audio amplitude within the VLC media player solely through manual gestures.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Agent-Based Modeling and Simulation for Transmission Dynamics and Surveillance of Dengue: Conceptual and Design Model 16

Agent-Based Modeling and Simulation for Transmission Dynamic...

引用

16th IEEE AFRICON, AFRICON 2023

作者： Pascoe, Luba Nyambo, Devotha Godfrey Bradshaw, Karen Clemen, Thomas School of Computational and Communication Science and Engineering Nelson Mandela African Institution of Science and Technology Arusha Tanzania United Republic of Rhodes University Grahamstown South Africa Hamburg University of Applied Sciences Department of Computer Science Hamburg20099 Germany

ISBN: (纸本)9798350336214

African countries need to strengthen surveillance and control of arboviral diseases such as dengue due to increased outbreaks and spread of arboviruses. Climatic, socio-environment, and ecological variables influence the spread of dengue fever in Sub-Saharan Africa. This paper presents an Agent-Based conceptual and design model for dengue fever developed using the Multi-Agent Research and Simulation (MARS) framework. The study analyzes dengue fever's spatial distribution and identifies the causal relationship between the disease and its climatic and environmental variables. Agent-based modeling (ABM) was used to comprehend the spatial patterns of variation to determine the ecological association between the observed spatio-temporal variations in dengue fever. The domain and design model of an ABM for the surveillance of dengue fever is presented based on the Overview, Design Concepts, and Details (ODD) protocol. Model input parameters and input data for the study area are also presented. The dengue ABM can be adopted and reused for modeling other diseases and other complex problems from different domains while ensuring that their unique characteristics and appropriate modifications are considered to ensure the model's validity and relevance to the new context. © 2023 IEEE.

关键词： Autonomous agents

来源：评论

学校读者我要写书评

暂无评论

Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

引用

computers, Materials & Continua 2023年第3期74卷 5607-5623页

作者： Abdallah Elhigazi Abdallah Mosab Hamdan Shukor Abd Razak Fuad A.Ghalib Muzaffar Hamzah Suleman Khan Siddiq Ahmed Babikir Ali Mutaz H.H.Khairi Sayeed Salih Faculty of Engineering Future UniversityKhartoum 10553Sudan Faculty of Computing and Informatics Universiti Malaysia SabahKota Kinabalu88400Malaysia Information Assurance and Security Research School of ComputingUniversiti Teknologi MalaysiaJohor81310Malaysia School of Psychology and Computer Science University of Central LancashirePreston PR12HEUK Deaptement of Management Information Systems College of Administrative ScienceApplied Science UniversityAl Eker623Bahrain Deaptement of Information Technology College of Computer and Information SciencesKing Saud UniversityRiyadh11461Saudi Arabia

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 *** to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate ***,the security design of the wireless structure is vulnerable to versatile *** example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false *** security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world *** paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks *** proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the *** scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in *** proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related *** experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

关键词： 802.11 media access control(MAC) wireless local area network(WLAN) artificial neural network denial-of-service(DoS)

来源：评论

学校读者我要写书评

暂无评论

Classifying Arabian Gulf Tweets to Detect People's Trends: A case study 9

Classifying Arabian Gulf Tweets to Detect People's Trends: A...

引用

9th International Conference on Social Networks Analysis, Management and Security, SNAMS 2022

作者： Balhaf, Khaled Darwish, Omar Rawashdeh, Emad Awad, Mohammad Abu Darweesh, Dirar Tashtoush, Yahya Rawashdeh, Saif Department of Computer Science Jordan University of Science and Technology Irbid Jordan Information Security and Applied Computing Eastern Michigan University Ypsilanti United States

ISBN: (纸本)9798350320480

Recently, media and business companies are utilizing social media to reach a large set of users to maximize the amount of gained profit. Actually, these companies are looking for the best ways to satisfy their user's requirements. It is very difficult to understand these requirements because of the large set of users on social media like Twitter. For this reason, the goal of our research project is to build a classifier that can detect Arabian trends among Gulf area Twitter users. The new built classifier can assist these companies to deliver the convenient products and media contents like photos and videos according to users' trends. By using our own designed Java-based tool, we have collected a significant dataset of tweets. Also, two experiments of tweet classification have been implemented to compare the effects of balanced and imbalanced training data and to measure the effect of data size on the accuracy of classifiers. In both experiments, Support Vector Machine (SVM), K-Nearest Neighbors (KNN) and Naïve Bayes algorithms are used as classifiers. The first experiment uses small, imbalanced data sets and four classes of data, which are Sport, Politics, Islam and Culture. The Light and Root Stemmers were used with each classifier. The best outcome achieved in our research project by utilizing a Naïve Bayes algorithm with the Light Stemmer technique. It achieved an accuracy reaching 76.27%. In the second experiment, we used a balanced large data set with the same classifiers. In addition, we have added one more class to the new data set which is Economics. The experimental results showed that the best accuracy (81.17%) is obtained by using SVM with the Light Stemmer method. The Light Stemmer achieved the best outcomes for all classifiers since almost all of the tweets were written in dialects. © 2022 IEEE.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Navigating Cloud Security: Developing Privacy-Aware Architectures for Service Industry Data Protection 5th

Navigating Cloud Security: Developing Privacy-Aware Architec...

引用

5th Doctoral Symposium on Computational Intelligence, DoSCI 2024

作者： Guan, Qing Goyal, S.B. Rajawat, Anand Singh Ibrahim, A.Z.M. City Graduate School City University Petaling Jaya46100 Malaysia Nanchang Normal College of Applied Technology Nanchang China Faculty of Information Technology City University Petaling Jaya46100 Malaysia School of Computer Science and Engineering Sandip University Nashik India

ISBN: (纸本)9789819760350

With the advancement of technology, the digital age is exploding, which poses significant challenges to cloud data control and privacy. How to find a middle ground between data privacy protection and technological innovation? In this research paper, in order to conduct comprehensive research in the fields of cloud security and privacy, we will explore the biodiversity of clouds. The study chose a mixed method research strategy, which requires the use of multiple methods to investigate the research question and provide a richer and more complete set of questions at hand. Conducted research interviews with subject matter experts to raise my research questions;a literature review and case study were conducted to present my preliminary survey questions. Active data protection measures include the widespread use of static data encryption and access restrictions. The report concludes by introducing practices related to cloud privacy, based on real-life case studies of companies that have successfully applied these guidelines, primarily in the healthcare and financial services industries. The research provides a comprehensive investigation into privacy-aware architectures for cloud-based data processing in the services sector, aiming to identify challenges, propose solutions, and offer actionable recommendations to enhance data privacy and security. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Cloud security

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：