检索结果-内蒙古大学图书馆

8th IEEE International Conference for Convergence in Technology, I2CT 2023

作者： Magoo, Chandni Singh, Manjeet J.C. Bose University of Science and Technology Department of Computer Science and Engineering Faridabad India Manav Rachna University Department of Computer Science and Technology Faridabad India Department of Computer Science and Applications J.C. Bose University of Science and Technology India

ISBN: (纸本)9798350334012

Chatbots are basically designed to imitate any human interaction to automate interaction and support. Numerous benefits of chatbots has led to its increased usage by different organizations to provide essential assistance to its various customers. The current interactive systems are mainly developed from two main concepts namely NLP and Machine Learning. Despite of this, there are certain challenges and limitations of current chatbots. In this paper we will review some of the current chatbots with their limitations and highlight some of the errors identified through survey analysis of different chatbots of some companies like Airtel, Vodafone and Jio etc. A survey is done to analyze the chatbots on various metrics. © 2023 IEEE.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Transformer Embedding-Based Model for Malicious DGA-Generated Domain Detection 16

A Transformer Embedding-Based Model for Malicious DGA-Genera...

引用

16th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2024

作者： Yerima, Suleiman Y. Vinod, P. Shaalan, Khaled The British University in Dubai Faculty of Engineering and It Dubai United Arab Emirates Cochin University of Science and Technology Department of Computer Applications Kerala Kochi682022 India The British University in Dubai Department of Computer Science Dubai United Arab Emirates

ISBN: (纸本)9798331505264

Domain Generation Algorithms (DGA) techniques are frequently used by cybercriminals to make malware more evasive by generating thousands of fake domain names that prevent established security solutions from effectively discovering or disrupting attacks. The proliferation of DGA has increased the difficulty of distinguishing genuine domains from fake ones, thus necessitating the investigation of new approaches to improve detection efficiency. Therefore, in this paper we propose a method for detecting malicious DGA domain names based on the Generative Pre-Trained Transformer (GPT) Large Language Model (LLM). Our approach utilizes GPT to learn dense vector representations with the aim of enabling more effective detection of the malicious domains by machine learning algorithms. The system is implemented and evaluated using a publicly available dataset and compared to widely-used techniques such TF-IDF, Bag-of-Words, N-grams, word2vec as well as to two variants of BERT. The results of our experiments demonstrates the superiority of the GPT-based technique over the others, with the best performance recorded by the XGboost classifier achieving the highest accuracy of 93.1% compared to the other machine learning algorithms. © 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

Word Segmentation and Sandhi Resolution on Ayurveda Classical Scriptures 6

Word Segmentation and Sandhi Resolution on Ayurveda Classica...

引用

6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Amrita Varshini, E.R. Nair, Jayashree Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India Department of Computer Science and Applications Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (纸本)9798350398496

Sanskrit is one of the oldest of the Indo-Aryan languages which has an abundant amount of texts in literature. One of the main sources of these Sanskrit texts is the textbooks written about the field of Ayurveda, the ancient Indian medical system. However, proper computational systems for processing this language are bare. A very challenging part of processing the Sanskrit language is the task of Sandhi resolution, which means the splitting of phonetically merged words. This study mainly focuses on this complex task of joint compound splitting and Sandhi resolution in Sanskrit specific to Ayurveda texts. This paper also surveys and compares all the existing research on Sandhi resolution in Sanskrit. In this work, an Ayurvedic dataset is compiled from some popular Ayurvedic texts, and a performance analysis of the state-of-the-art word segmentation model is carried out using this dataset. © 2023 IEEE.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

Novel Recoverable Audio Mosaic Technique Using Segmental and Hierarchical Permutations

引用

IEEE Internet of Things Journal 2024年第3期11卷 4857-4871页

作者： Tsai, Morris C.-H. Huang, Scott C.-H. Wu, Hsiao-Chun National Tsing Hua University Department of Electrical Engineering Hsinchu30013 Taiwan Louisiana State University School of Electrical Engineering and Computer Science Baton RougeLA70803 United States Yuan Ze University Innovation Center for AI Applications Chungli32003 Taiwan

Mosaic is a prevalent signal-processing approach to hide or protect critical information from users. The conventional mosaic schemes simply abolish or add artificial noise to the original signal content a sender wants to conceal. Thus, they are not recoverable simply by use of a key which can be represented as a very short sequence compared to the concealed signal content. In this work, we extend our previous effort in recoverable image mosaicing to design a novel audio mosaicing approach using hierarchical permutations. Besides, we establish the mathematical relationship between the popular signal-quality metric, namely, signal-to-noise ratio (SNR), and our previously proposed signal-destructuring metric, namely, Kullback-Leibler divergence of discrete cosine transform (DCT-KLD), so that the mosaicing or signal-destructuring effect in terms of DCT-KLD and the general signal-quality measure in terms of SNR can be translated into each other. As a result, one can easily judge if the mosaicked signal reaches the concealability which is equivalent to the maximum SNR to eliminate the intelligibility of an utterance. The new relationship between DCT-KLD and SNR we develop can thus be very useful to qualify an audio mosaic method without any need of human listening test. © 2014 IEEE.

关键词： Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

An Intellectual Diffused Configuration for High-Level Edge Network Elasticity 3

An Intellectual Diffused Configuration for High-Level Edge N...

引用

3rd International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2023

作者： Karthigeyan, A. Sathish Kumar, M. Ali Sabah, Hawraa Fouad, Laith Abbas Alwan, Adil Fouad, Laith Hindustan Institute of Technology & Science Department of Computer Applications Chennai India Hindustan Institute of Technology and Science Department of Computer Applications Chennai India National University of Science and Technology Collage of Engineering Dhi Qar Iraq Al-Farahidi University Medical Laboratory Techniques Department Baghdad Iraq

ISBN: (纸本)9798350399264

The Network Distribution System is a rapid evolution of the Internet of Everything (IOE). This system enabled the deployment of new solutions that reduce low-latency edge applications close to cloud servers and resilient edge applications to edge networks close to IoT devices. The network edge must make intelligent decisions that require fast response times and a wide range of edge application requirements. It also requires a heterogeneous dynamic edge network with constrained resources. Increasing the edge network capacity level increases the frequency and latency of many edge devices such as smart cars, robots, and smart IoT devices. With dynamic edge response time, applications automatically adapt to resilience requirements. This paper describes the role of edge networks. It also employs a lightweight, self-adapting, decentralised mechanism for deploying edge applications. It explains optimization methods for edge applications based on IoT technology. Finally, this paper increases the performance of smart waste management system by using the elasticity by reducing the latency of edge network. © 2023 IEEE.

关键词： Elasticity

来源：评论

学校读者我要写书评

暂无评论

Predictive Maintenance Model Using Hybrid Procedure of Improved Quantum Cat Swarm Optimisation for Asset Management in Industry 4.0

Predictive Maintenance Model Using Hybrid Procedure of Impro...

引用

International Conference on Data Analytics and Management, ICDAM 2023

作者： Kanchana, S. Rajan, Dhivya Mahaveerakannan, R. Sagar, K. V. Daya Subramanian, P. Rajakumar, B. Department of Computer Science Faculty of Science and Humanities SRM Institute of Science and Technology Tamil Nadu Kattankulathur603203 India Department of Computer Applications CMR Institute of Technology Bengaluru India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India Department of Electronics and Computer Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram India Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of AI & DS JNN Institute of Engineering Chennai Periyapalayam Highway Tamil Nadu Thiruvallur601102 India

ISBN: (纸本)9789819965465

Contemporary manufacturing system design centres on the Industry 4.0 paradigm. A versatile platform secondary the efficient optimisation of manufacturing-related activities, such as predictive keep, is necessary for the successful mixing of cutting-edge technologies like the (IoT), cyber-physical schemes, computing. Predictive maintenance research that already exists often either develops a model without taking maintenance decisions into account or seeks to optimise maintenance in the light of the degradation replicas of the already-known scheme. With the use of predictive maintenance, a company's owner can make decisions like fixing or replacing a failing part of the manufacturing line before it actually fails. Because of this, Industry 4.0 necessitates efficient asset management in order to maximise the distribution of duties and the accuracy of predictive maintenance models. To address the issue of predictive maintenance in fog computing, this paper proposes an enhanced version of the quantum cat swarm optimisation (QCSO) algorithm by combining the quantum bit (Q-bit) and the cat swarm procedure (CSO) and updating the cats based on the quantum rotation angle site. Finally, the (MR) worth is chosen based on the sum of times the procedure is run. FogWorkflowsim uses simulated real-time datasets to evaluate the forecasting performance of QCSO and other existing models. The outcomes prove that the projected method is superior to the currently used predictive maintenance resource allocation methods. In comparison to the approximately 91% to 95% accuracy achieved by previous models, the proposed model has an accuracy of 96%, respectively. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Transforming Agricultural Supply Chains: The Power of Blockchain Technology 3

Transforming Agricultural Supply Chains: The Power of Blockc...

引用

3rd International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Mohammed, Shehu Singh, Arun Kumar, Gotte Ranjith Lovely Professional University School of Computer Applications Phagwara India Lovely Professional University Department of Computer Science and Engineering Phagwara India Sr University School of Cs & Ai Department of Cse Telangana Warangal506371 India

ISBN: (纸本)9798331515911

Implementing blockchain technology in agricultural supply chains has the potential to revolutionize and increase transparency, efficiency and trust between all parties. A variation of the white paper discussed how blockchain can be a transformative tech in addressing major challenges especially on traceability, fraud prevention and sustainability on agriculture. Blockchain (for those hearing about this for the first time) can provide a system where every step of even complex supply chains is perfectly recorded, enabling transactions to take place in a secure way and offering transparency, immutability, accountability. Case studies and real-world examples showcased throughout the paper depict how blockchain could enhance operational efficiencies, boost food safety, authenticate products, and cut waste across agriculture. While very promising, the implementation of blockchain technology in agriculture is not without its own issues;this includes obligatory industry standards as well as highly costly technical implementations. The paper also highlights the potential for blockchain to contribute to sustainable agriculture by allowing better tracking of environmental footprints and ethical sourcing. In summary, we propose that the flexibility of blockchain technology renders it an ideal approach to revolutionizing supply chains in the agriculture sector, as we continue down a trajectory towards increased levels of visibility and productivity with improved environmental outcomes. This paper contributes towards a more comprehensive understanding of the role of blockchain in scenario-based selection as it addresses both opportunities and challenges due to adoption of block chain which gives technology and agriculture a new future(directions). © 2025 IEEE.

关键词： Sustainable agriculture

来源：评论

学校读者我要写书评

暂无评论

Analysis and Evaluation of Bio-Inspired Algorithmic Framework, Potential Application in Cloud/Multi-Cloud Environment 5

Analysis and Evaluation of Bio-Inspired Algorithmic Framewor...

引用

5th IEEE International Conference on Cybernetics, Cognition and Machine Learning applications, ICCCMLA 2023

作者： Kaur, Ramanpreet Anand, Divya Kaur, Upinder Verma, Sahil School of Computer Applications Lovely Professional University Phagwara India Baba Farid College Department of Computer Application Bathinda India School of Computer Science and Engineering Lovely Professional University Phagwara India Akal University Talwandi Sabo Department of Computer Science Bathinda India CGC Department of Computer Science and Engineering Mohali India

ISBN: (纸本)9798350338287

Cloud computing allows web-based services to use a variety of reasonably priced services or resources, removing the requirements of centralized knowledge access. There are many provocations available in cloud computing and multi-cloud, so bio-inspired algorithms frequently used to handle particular problems such as load imbalance, resource equipping, and performance optimization. Bio-inspired algorithms have a proclivity for spontaneously resolving a wide range of challenges by giving optimum solutions. The ability has an impact on how bio-inspired algorithms are used to tackle the crucial issues in cloud computing. This study presents a comprehensive review of bio-inspired methods for resolving and optimizing solutions in multi-cloud. ACO, GA, PSO, FPA, BA and COSMIC bio inspired techniques are considered based on cost, scalability, fault tolerance, security, energy consumption, and throughput. ACO is secure and having capability of fault tolerance, PSO is fast but less secure and costly than others. Thus, FPA has a better capability than others for various parameters. FPA is better in security, cost, fault tolerance and energy consumption © 2023 IEEE.

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

Efficient Optimal Routing Algorithm Based on Reward and Penalty for Mobile Adhoc Networks

引用

computers, Materials & Continua 2023年第4期75卷 1331-1351页

作者： Anubha Ravneet Preet Singh Bedi Arfat Ahmad Khan Mohd Anul Haq Ahmad Alhussen Zamil S.Alzamil Department of Computer Applications I.K.G.Punjab Technical UniversityKapurthala144601PunjabIndia Research and Development I.K.G.Punjab Technical UniversityKapurthala144604PunjabIndia Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Mobile adhoc networks have grown in prominence in recent years,and they are now utilized in a broader range of *** main challenges are related to routing techniques that are generally employed in *** Adhoc system management,on the other hand,requires further testing and improvements in terms of *** routing protocols,such as Adhoc On-Demand Distance Vector(AODV)and Dynamic Source Routing(DSR),employ the hop count to calculate the distance between two *** main aim of this research work is to determine the optimum method for sending packets while also extending life time of the *** is achieved by changing the residual energy of each network ***,in this paper,various algorithms for optimal routing based on parameters like energy,distance,mobility,and the pheromone value are ***,an approach based on a reward and penalty system is given in this paper to evaluate the efficiency of the proposed algorithms under the impact of *** simulation results unveil that the reward penalty-based approach is quite effective for the selection of an optimal path for routing when the algorithms are implemented under the parameters of interest,which helps in achieving less packet drop and energy consumption of the nodes along with enhancing the network efficiency.

关键词： Routing optimization reward penalty mobility energy throughout pheromone

来源：评论

学校读者我要写书评

暂无评论

Deep Learning for Precision Medicine: Advancing Personalized Treatment Plans in Oncology

Deep Learning for Precision Medicine: Advancing Personalized...

引用

2025 IEEE International Conference on Computational, Communication and Information Technology, ICCCIT 2025

作者： Shrivastava, Anurag Kotiyal, Arnav Jain, Alok Devi, V.S Anusuya Rao, Bolleddu Devananda Bansal, Saloni Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamil Nadu Chennai India Graphic Era Deemed to Be University Department of Computer Science & Engineering Dehradun India Lovely Professional University Phagwara India New Horizon College of Engineering Department of Applied Sciences Bangalore India MLR Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India GLA University Department of Computer Engineering and Applications Mathura India

ISBN: (纸本)9798331512965

A new approach to cancer care, precision medicine tailors treatments to each patient's specific genetic, molecular, and clinical characteristics. In order to analyze complicated, high-dimensional data and create individualized treatment plans, deep learning - a potent subfield of AI - has arisen as a game-changing tool in this area. Discover how deep learning methods are being used in precision oncology to improve cancer diagnosis, prognosis, and treatment planning in this groundbreaking article. A few examples of notable developments are the use of CNNs to medical image tumor identification and segmentation, RNNs to treatment outcome prediction, and LSTM models to patient survival. More effective and less harmful treatments are possible because too deep learning models that integrate multimodal data, such as genetic sequences, histopathological pictures, and electronic health records. These models can detect new biomarkers and forecast how different medications will affect individual patients. The clinical translation of deep learning models is hindered by a number of obstacles, despite these encouraging improvements. Problems including data scarcity, unequal distribution of classes, and unintelligibility are major roadblocks. Also, to make sure these models are accurate and reliable, they need to be standardized and validated thoroughly before they can be used in clinical processes. Fostering trust and acceptance in therapeutic contexts also requires addressing ethical problems, such as data security, possible biases in algorithmic predictions, and patient privacy. This work offers a thorough analysis of existing approaches, delves into the difficulties and moral concerns, and suggests avenues for further study to improve the use of deep learning in precision oncology. Personalized treatment regimens, made possible by deep learning, have the potential to revolutionize cancer care by vastly increasing patient outcomes. © 2025 IEEE.

关键词： Electronic health record

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：