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Leveraging Transformer Networks for Enhanced Conversational AI 7

Leveraging Transformer Networks for Enhanced Conversational ...

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7th international conference on Contemporary computing and informatics, IC3I 2024

作者： Behl, Vivek Bibhu, Vimal Noida International University Department of Computer Science and Engineering Uttar Pradesh Greater Noida India

ISBN: (纸本)9798350350067

This paper presents a comprehensive study on leveraging transformer networks for enhanced conversational AI, show casing their superiority over traditional models such as LSTM, GRU, and GRU BiRNN decoders. The architectural enhancement, improvement by RBF kernel and the proposed transformer model used by the OpenSubtitles 2018 dataset, contextually and legibly suitable replies generated by significant advancements. Critical developments demonstrate incomprehension of 4.58, appreciably descending from 7.568 earned by the GRU BiRNN decipherer with ELU activation, and training time diminishing substantially. The prototype's Sparse Categorical Cross-Entropy (SCCE) training costs are Streamlined to 0.14 and 0.192, appropriately. Proved by its originality and efficacity, both acoustic-aware modes and textual modes are handled by the system effectively. There are different types of conversational AI applications, but this study indicates the potential transformer-based architectures to surpass traditional RNN-based models and clear the way for upcoming improvements concerning real-time adaptive learning, personalized user interactions, and multimodal inputs. © 2024 ieee.

关键词： Conversational AI GRU BiRNN Incomprehension Sparse Categorical Cross-Entropy (SCCE) Transformer Networks

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Real Time Gas Alert Leakage System using Arduino and NodeMCU 6

Real Time Gas Alert Leakage System using Arduino and NodeMCU

引用

6th international conference on Mobile computing and Sustainable informatics, ICMCSI 2025

作者： Gurupriya, M. Umesh Raghav, P. Pavan Nikhith, S. Bhargav Reddy, P. Rohit, K.C. Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India Standard Chartered Global business Services Bengaluru India

ISBN: (纸本)9798331522667

Today, gas leakage has become a common problem in both industrial and household sectors as it can cause explosions, fires, and toxic exposures. The real time gas alert system ensures that gas leaks are not only detected but also transfer alerts so that risks are reduced and lives can be saved. The system involves an Arduino board that is already connected to a gas sensor. From there, the sensor information stays sent to a NodeMCU module which connected to the internet and sends alerts to users through the Blynk app and email once gas emission conforms to particular standards over a certain duration. Furthermore, if the intensity of the gas surpasses the threshold for a specific time period, the system activates the sending of the alarm through an automated procedure. The system presents a very good solution to gas leakage and gas positioning in a sight plan in regions where gas safety is of greater concern. © 2025 ieee.

关键词： Chemical sensors

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Construction of Ontology Graphs in a Cyber Security Framework (OCSF) 6

Construction of Ontology Graphs in a Cyber Security Framewor...

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6th international conference on Contemporary computing and informatics, IC3I 2023

作者： Pandey, Rajendra P. Jebaraj, Solomon College of Computing Science and Information Technology Teerthanker Mahaveer University Uttar Pradesh Moradabad India University Karnataka Bangalore India

ISBN: (纸本)9798350304480

The paper develops ontology for cyber security to provide information from huge collection of structured and unstructured web data. It deals with identification of several aspects related to cyber security including vulnerability, attacks identification, virus, snort alerts and many more. Therefore, it is mandatory to develop cyber security knowledge graph by incorporating the use of ontologies and reasoning rules. © 2023 ieee.

关键词： attacks Cyber security ontology reasoning rules worm

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Analysis of Density-Based Methods for Selecting Cluster Heads 2

Analysis of Density-Based Methods for Selecting Cluster Head...

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2nd ieee international conference on Advances in computing, Communication and Applied informatics, ACCAI 2023

作者： Maravarman, M. Babu, S. Pitchai, R. Srm Institute of Science and Technology School of Computing Department of Computing Technologies Tamil Nadu Kattangulathur India B v Raju Institute of Technology Department of Computer Science and Engineering Telangana Narsapur India

ISBN: (纸本)9798350315905

It is one of the most significant things that can be done to make a Wireless Sensor Networks(WSNs) last for a longer period of time, and one of those things is to reduce the amount of power that each sensor node in the network consumes. Not only does the total number of clusters have a significant bearing on the effectiveness of the network as a whole, but so does the physical location of the Cluster Heads (CHs). Using a method referred to as sensor node clustering, The objective of the study is to do this by utilising density-based clustering algorithms in order to select the cluster head. The application of a sophisticated method known as density-based clustering is one of the techniques that can be employed to move closer to achieving this objective. Density-based algorithms are those that make use of the concept of density to locate groupings of data that share similar properties despite the fact that they differ in size, shape, and density from one another. While selecting a Cluster head, one should give careful consideration to how well it can distribute loads and accommodate growth. In this research, researchers examine a number of different cluster head selection strategies for WSNs that are based on density and compare and contrast them using a variety of parameters. © 2023 ieee.

关键词： Energy utilization

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GemmaWithLoRA: A New Approach to Click Fraud Detection

GemmaWithLoRA: A New Approach to Click Fraud Detection

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2024 ieee international conference on Communications, computing, Cybersecurity and informatics, CCCI 2024

作者： Dai, Bingzhou Wang, Lei Zhao, Xiaoyong Guo, Yu Obaidat, Mohammad S. School of Information Management Beijing Information Science & Technology University Beijing China Information Systems Institute Beijing Advanced Innovation Center for Materials Genome Engineering Beijing Information Science & Technology University Beijing China Beijing Advanced Innovation Center for Materials Genome Engineering and Shunde Innovation School University of Science and Technology Beijing China King Abdullah II School of Information Technology University of Jordan School of Engineering Amity University School of Computing SRM University Amman Jordan

ISBN: (纸本)9798350349832

With the rapid development of artificial intelligence technology, pre-Trained large language models (LLMs) have demonstrated their powerful application potential in various fields. Click fraud is a serious issue in the digital advertising ecosystem, especially in the pay-per-click (PPC) model, where fraudulent activities significantly undermine the effectiveness of ads and pose security risks. While many traditional fraud detection methods have achieved relatively good accuracy, they still face poor generalization and extensive feature engineering issues. This paper explores using LLMs for click fraud detection by leveraging the powerful feature extraction capabilities and superior generalization performance of the Gemma-2b model, combined with LoRA fine-Tuning technology. Extensive experiments on the TalkingData2017 dataset showed that accuracy was achieved at 83°/0, demonstrating the effectiveness of LLMs in click fraud detection tasks. © 2024 ieee.

关键词： Crime

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Energy Aware Federated Learning with Application of Activity Recognition

Energy Aware Federated Learning with Application of Activity...

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2023 ieee international conference on Dependable, Autonomic and Secure computing, 2023 international conference on Pervasive Intelligence and computing, 2023 international conference on Cloud and Big Data computing, 2023 international conference on Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2023

作者： Thakur, Dipanwita Guzzo, Antonella Fortino, Giancarlo University of Calabria Dept. of Informatics Modeling Electronics and Systems Rende Italy University of Calabria Department of Informatics Modeling Electronics and Systems Rende Italy

ISBN: (纸本)9798350304602

Human activity recognition (HAR) based on smart devices is gaining increasing attention from the pervasive computing research community due to its wide application in smart healthcare. Modern deep learning models for recognizing human activities rely heavily on sensor data to attain great accuracy. However, leveraging data gathered from smart devices to train such models in a data center results in significant energy consumption and potential privacy violations. By merging numerous local models that are trained on data coming from various clients, federated learning can be used to address the aforementioned problems. By creating a federated learning-based convolutional neural network (CNN) model, which is trained on both public and real-world datasets, we analyze federated learning (FL) to train a human activity identification classifier and compare its performance to centralized learning. The global model achieves accuracy comparable to centralized learning when trained using federated learning on skewed datasets. Additionally, we discover that the selection of clients is a significant problem and suggest a federated learning algorithm that selects the maximum number of clients to increase the convergence rate and model correctness of FL. © 2023 ieee.

关键词： Ubiquitous computing

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A Forward Chaining Expert System for Personalized Programming Language Selection

A Forward Chaining Expert System for Personalized Programmin...

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2024 international conference on Innovation and Intelligence for informatics, computing, and Technologies, 3ICT 2024

作者： Sholihin, Andi Hidayati, Shintami Chusnul Department of Informatics Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (纸本)9798331533137

Choosing the right programming language is a critical decision for beginners in computer science because it greatly influences their learning experience and future opportunities. This paper presents an expert system designed to assist novices in selecting a programming language that aligns with their preferences and project requirements. The proposed system uses the forward chaining method, a robust approach to expert system development. It draws on comprehensive developer survey data from Stack Overflow, focusing on the top ten most popular programming languages. Our methodology involved formulating evaluative questions to create a decision-making framework supported by a rule-based table, which served as the foundation for the system’s knowledge base. Implemented in Python, the expert system achieved a relevance score of 90%, demonstrating its effectiveness in simplifying the programming language selection process for beginners. ©2024 ieee.

关键词： Expert systems

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An Investigation into the Perception of Gen Z Students in Higher Education towards Gamification Techniques in Learning computing Subjects

An Investigation into the Perception of Gen Z Students in Hi...

引用

2024 international Visualization, informatics and Technology conference, IVIT 2024

作者： Chong, Mien May Subramanian, Preethi Ting, Mary Ying, Lau Joe Asia Pacific University of Technology and Innovation School of Computing Kuala Lumpur Malaysia

ISBN: (纸本)9798350354447

This study examines how gamification techniques can improve the learning experience for Generation Z students in university-level computing courses. It explores game-based learning methods to tackle challenges like engagement and effective problem-solving in computer programming education. Through a survey of students across different academic disciplines, the research finds a clear preference for interactive and rewarding learning approaches, highlighting the potential benefits of gamification in education. The study underscores gamification's role in enhancing student motivation and academic performance, while also identifying opportunities for refining gamification strategies in educational settings. © 2024 ieee.

关键词： Contrastive Learning

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Security Analysis and Improvement of Authenticated Key Agreement Protocol for Remote Patient Monitoring IoMT

Security Analysis and Improvement of Authenticated Key Agree...

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2024 ieee international conference on Communications, computing, Cybersecurity and informatics, CCCI 2024

作者： Gautam, Deepika Thakur, Garima Obaidat, Mohammad S. Hsiao, Kuei-Fang Kumar, Pankaj Central University of Himachal Pradesh Srinivasa Ramanujan Department of Mathematics HP Dharamshala176215 India School of Computer and Communication Engineering University of Science and Technology Beijing China School of Computing SRM University Department of Computational Intelligence TN Kattankulathur India School of Engineering The Amity University UP 201301 India

ISBN: (纸本)9798350349832

The Internet of Medical Things (IoMT) is a network of medical devices, hardware infrastructure, and software that accumulates real-Time data through remote monitoring and minimizes doctor-patient interaction, enhancing the quality of remedies. However, the facile availability and accessibility of data over the web have given rise to serious information security and credibility issues in the IoMT. Recently, Chen et al. [1] proposed a provably secure authenticated key agreement protocol for remote patient monitoring in IoMT. However, after revisiting their scheme, we found security flaws such as user impersonation, ephemeral secret leakage attacks, denial-of-service attacks, and session key disclosure attacks. Therefore, this paper presents cryptanalysis as well as an improvement of Chen et al. 's scheme that strives to furnish protocols with robust security in opposition to the mentioned attacks. The security and effectiveness are displayed through informal analysis and evaluation with other existing state-of-The-Art metrics like computational and commu-nication cost. At last, the findings project the superiority of the proposed improved scheme. © 2024 ieee.

关键词： Authentication Protocol

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Work-in-progress: Security of Public-Key Schemes in the Quantum computing Era - A Literature Review

Work-in-Progress: Security of Public-Key Schemes in the Quan...

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2023 ieee international Black Sea conference on Communications and Networking, BlackSeaCom 2023

作者： Redkins, Boriss Kuzminykh, Ievgeniia Ghita, Bogdan King's College London Department of Informatics London United Kingdom School of Engineering Computing and Mathematics University of Plymouth Plymouth United Kingdom

ISBN: (纸本)9798350337822

Quantum computers, although still in the theoretical stage, conceptually have the power to break many current cryptosystems, including public-key schemes., for example, RSA (Rivest, Shamir., Adleman), elliptic-curve cryptography (ECC), and ElGamal. NIST specialists and national governments believe that existing cryptography algorithms will become vulnerable to brute force analysis by the end of the decade and agree that measures should be taken before then to ensure the secrecy of current and future algorithms. In this context, information security, including confidentiality and integrity, must be considered. This paper provides a systematic literature review on whether existing public-key schemes have the necessary complexity and solution space to resist a quantum computer. The discussion will focus on a quantum computer's negative 'real-world' impact and examine existing post-quantum algorithms, then provide analysis across two selected dimensions. Finally, we summarise the latest trends and gaps in post-quantum cryptography and provide the security analysis of NIST's last round finalists. © 2023 ieee.

关键词： Public key cryptography

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