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共 23629 条记录，以下是111-120 订阅

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Continual Learning Techniques to Reduce Forgetting: A Comparative Study

Continual Learning Techniques to Reduce Forgetting: A Compar...

引用

Computational Intelligence, Communication technology and Networking (CICTN), international conference on

作者： Neeraj Poonam Nandal Department of Computer Science & Engineering Manav Rachna International Institute of Research and Studies Faridabad Haryana India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

A key aspect of artificial intelligence is continual learning. The capacity of a model to incrementally learn from a new task and adapt to it without losing the previous knowledge. A fundamental challenge that comes to successful continual learning is catastrophic forgetting; while learning a new task the model forgets the previously learned tasks. Various approaches to mitigate forgetting and enhance continual learning have been discussed across benchmark datasets such as MNIST, CIFAR- 10, and Permuted MNIST. we focus mainly on replay, regularization, and modular architecture-based methods to prevent forgetting. Regularization methods penalize the significant change in parameters during the learning of new tasks while maintaining crucial parameters of previously completed tasks. Replay-based methods store samples of earlier tasks in explicit memory or generate pseudo-samples with the help of generative models. Modular architecture-based methods partition the neural architecture into task-specific modules to prevent interference between tasks, to effectively address catastrophic forgetting. This paper presents a comparative study of the key continual learning methods that reduce catastrophic forgetting. The findings demonstrate the trade-offs between different methods. We examine the efficiency and effectiveness of each method and propose a hybrid technique to prevent catastrophic forgetting. Our comparative analysis emphasizes the significance of choosing the best method depending on the specific requirement of the learning environment, the task complexity, and resource constraints.

关键词： Continuing education Adaptation models Interference computer architecture Benchmark testing communications technology Complexity theory Artificial intelligence Computational intelligence

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Integrating Simulation Budget Management into Drum-Buffer-Rope: A Study on Parametrization and Reducing Computational Effort 2nd

Integrating Simulation Budget Management into Drum-Buffer-Ro...

引用

2nd Decision Science Alliance international Summer conference, DSA ISC 2024

作者： Bokor, Balwin Seiringer, Wolfgang Altendorfer, Klaus Department for Production and Operation Management University of Applied Sciences Upper Austria Wehrgrabenstraße 1 Steyr4400 Austria

ISBN: (纸本)9783031782374

In manufacturing, a bottleneck workstation frequently emerges, complicating production planning and escalating costs. To address this, Drum-Buffer-Rope (DBR) is a widely recognized production planning and control method that focuses on centralizing the bottleneck workstation, thereby improving production system performance. Although DBR is primarily focused on creating a bottleneck schedule, the selection of planning parameters is crucial, as they significantly influence the scheduling process. Conducting a comprehensive full factorial enumeration to identify the ideal planning parameters requires substantial computational effort. Simulation Budget Management (SBM) offers an effective concept to reduce this effort by skipping less promising parameter combinations. This publication introduces a method for integrating SBM into multi-stage multi-item DBR planned and controlled production system with limited capacity, aimed at determining the optimal planning parameters. Furthermore, we conduct a simulation study to analyze the effects of different production system environments, i.e., varying levels of shop load and process uncertainty, on both the performance and parameterization of DBR and the efficacy of SBM. Our results show significant reduction in simulation budget for identifying optimal planning parameters compared to traditional full factorial enumeration. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Budget control

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The GraphRAG-Driven Automated Analysis Method for Coal Mine Dispatch Room Calls 2nd

The GraphRAG-Driven Automated Analysis Method for Coal Mine ...

引用

2nd international conference on Applied Intelligence, ICAI 2024

作者： Sun, Quan Zhang, Ronghua Liu, Yingchun Liu, Zemeng Liu, Jueting Chen, Wei CHN ENERGY Investment Group Guoshen Company Shangyuquan Coal Mine Shanxi Hequ China Research Center of Mine Digitization Ministry of Education School of Computer Science China University of Mining and Technology Jiangsu Xuzhou China Jiangsu Xinshi Technology Co. Ltd. Jiangsu Xuzhou China

ISBN: (纸本)9789819619061

During coal mine production, dispatch room phone recordings contain a wealth of critical information, but existing analytical methods are limited in fully extracting their value. To address this, this paper proposes an automated analysis method based on GraphRAG technology, aiming to conduct event correlation analysis on the speech recognition transcripts from the coal mine dispatch room. This approach enables more efficient identification and resolution of potential safety hazards, thereby improving overall mine safety. Experimental results demonstrate that this method significantly enhances the accuracy and timeliness of hazard identification, showing broad application prospects. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Coal mines

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Automating Talent Acquisition Assisted by Resume Parsing System for Enhanced Job Matching

Automating Talent Acquisition Assisted by Resume Parsing Sys...

引用

Computational Intelligence, Communication technology and Networking (CICTN), international conference on

作者： Geetesh Gautam Dolly Sharma Vijit Chaturvedi Computer Science and Engineering Amity University Uttar Pradesh Noida India Amity Business School Amity University Uttar Pradesh Noida India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

Artificial intelligence has vast potential in resume parsing and human resource management. It aids in proliferating information and data sources, improving software's data management capabilities, and designing intricate and advanced algorithms. Al is changing the way firms hire and users interact with one another. This paper explores the development of a resume parsing system using the RoBERTa model to enhance job matching in talent acquisition. Traditional resume screening processes are time-consuming and prone to human error. Automated systems, although available, often require resumes to follow a specific format. This research presents a novel approach utilizing RoBERTa to parse resumes in various formats, thereby increasing the efficiency and accuracy of the talent acquisition process. The methodology includes the design and implementation of the system, followed by an evaluation of its performance. Results indicate significant improvements in processing time and matching accuracy. The implications of these findings suggest that organizations, regardless of size, can benefit from integrating such a system into their HR processes.

关键词： Accuracy Automation Soft sensors Design methodology Resumes Organizations Chatbots communications technology Human resource management Computational intelligence

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Analytical Insight into Cutting-Edge Image Captioning for Advanced ChatGPT Functionality 2nd

Analytical Insight into Cutting-Edge Image Captioning for Ad...

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2nd international conference on Business Data Analytics, ICBDA 2023

作者： Manisha Kumar, Avadhesh Yadav, Dileep Kumar School of Computer Science Engineering Galgotias University Greater Noida India SCSET Bennett University Greater Noida India

ISBN: (纸本)9783031807770

At present, Artificial intelligence (AI) and Machine learning (ML) algorithm contribute to transforming the technology environment. Specifically, the development of chatbots has been on a rapid-fire overhead in recent years. The Image captioning with ChatGPT is most growing field for text generating for the future. In recent years, the innovation of virtual assistants has boomed with ChatGPT becoming an increasingly popular language model of artificial intelligence. This work evaluates the principles, goals, and problems of ChatGPT in the present study. This study explores the technology's background, growth, and development, along with its applications. In addition, we will look at the benefits of connecting information by ChatGPT in image processing and content writing that the image exposes. However, we believe that ChatGPT will contribute to improving human-AI interaction and bridging scientific gaps by focusing on various research and development opportunities, such as energy conservation, privacy, and security, expanding its scope to other technologies like robotics and computer vision, deep learning, and ML. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： ChatGPT model computer vision NLP

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AI in Building Systems for Perpetual Monitoring and control of ESG Practices 2nd

AI in Building Systems for Perpetual Monitoring and Control ...

引用

2nd international conference on Artificial Intelligence: Towards Sustainable Intelligence, AI4S 2024

作者： Aylani, Amit Rao, Madhuri Thampi, G.T. Thadomal Shahani Engineering College Mumbai Bandra India

ISBN: (纸本)9783031813689

The need for inter-governmental protocols on climate change, world trade agreements, and increased awareness of human rights and sustainability issues has made it imperative for corporations globally to adopt environmental, social, and governance (ESG) practices at a faster rate. This paper highlights the key areas where digital and artificial intelligence can be successfully combined to address these demands. As the importance of ESG and sustainability issues grows, organization are actively seeking out advanced technological solutions to tackle intricate problems. The research methodology used in this paper incorporates a framework, highlighting how technology can address complex issues in data collection and contribute to sustainable practices. The results suggest that AI technology has the potential to greatly improve ESG practices in different areas. It can help organizations enhance their corporate governance by automating compliance monitoring, assessing risks, and providing decision support systems. This paper investigates artificial intelligence technology in creating and implementing an architectural solution for environmental, social, and governance practices, providing a strong foundation for further exploration and application. By using artificial intelligence and IoT, organizations can better align themselves with sustainable development goals and ESG reporting. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Climate change

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Analyzing the Hybrid Electric Vehicle's Performance for Automatic Acceleration control 2nd

Analyzing the Hybrid Electric Vehicle's Performance for Auto...

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2nd international conference on Emerging Wireless Technologies and Sciences, ICEWTS 2024

作者： Charyulu, M.L.N. Sailaxmi, M. Kushwah, Vivek Singh Gandipet Telangana Hyderabad500075 India

ISBN: (纸本)9783031878855

Hybrid electric vehicles primarily revolve around improving fuel efficiency, reducing emissions, addressing environmental concerns, and offering a more accessible transition toward electric mobility while leveraging existing automotive technology. HEVs are designed to combine the benefits of traditional internal combustion engines (ICE) with those of electric propulsion systems, in heightened total vehicle performance, decreased emissions, and increased fuel efficiency. The development of a driver, electric powertrain, and vehicle model for a hybrid electric vehicle. Examine the conduct of the Plot the real velocity power distribution curves for the car throughout a US06 drive cycle. Examine the fuel consumption and operation of the battery, ultracapacitor, and fuel cell as well. By converting to power gearbox via the motor and turning off the engine, the HEV resolves the issue. In this manner, no fuel will be used when the vehicle is idle, producing no exhaust emissions. A significant benefit of hybrid electric vehicles (HEVs) is their ability to operate entirely on electricity when the fuel tank runs empty while the engine is running. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Hybrid vehicles

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Securing Software Defined Networks from Packet Injection Attacks: A Framework for Detection and Prevention

Securing Software Defined Networks from Packet Injection Att...

引用

Computational Intelligence, Communication technology and Networking (CICTN), international conference on

作者： Laboni Dolai Partha Maity Tannishtha Jana Pritam Sadhu Tinku Adhikari Sandipan Ghosal Computer Science and Engineering Techno International New Town Kolkata India Information Technology Techno International New Town Kolkata India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

Software Defined Networking (SDN) has changed how networks are managed by splitting the control and data layers, allowing for centralized control and flexible network setups. SDN increases programmability, flexibility, and agility but also presents serious security risks, especially with regard to packet injection attacks. These attacks specifically target the central SDN controller, which serves as a single point of failure, by taking advantage of security flaws in the SDN architecture. Attackers can send unauthorized packets into the network, causing communication issues, damaging data accuracy, and thereby leads to Denial-of-Service (DoS) attack. This paper examines the threat landscape of packet injection attack in SDN environments, with a focus on the OpenFlow protocol, which serves as a communication bridge between the control and data planes. We explore how attackers create fake hosts to get around traditional security defences. The research also provides a novel and efficient solution to cater this attack. The solution is compared with the existing state-of-the art solutions to ensure its accuracy and efficiency. We show, by direct observation, how these methods strengthen SDN security against packet injection attacks, improve network reliability, and provide a safe and dependable network environment.

关键词： Protocols Accuracy Scalability Prevention and mitigation Threat assessment Real-time systems Software reliability Software measurement Software defined networking Systematic literature review

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Hot Topic Extraction in Microblog Based on Hashtags 2nd

Hot Topic Extraction in Microblog Based on Hashtags

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2nd international conference on Applied Intelligence, ICAI 2024

作者： Feng, Xue Zhang, Can Pan, Yijie Computer School Beijing Information Science and Technology University Beijing China Eastern Institute for Advanced Study Eastern Institute of Technology Ningbo China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9789819619061

Hot topic extraction in microblog has received great interests during recent years. Traditionally, there are two different frameworks for this task, one being based on supervised learning, and the other being based on unsupervised learning, which typically exploits clustering or topic models for the task. Actually, the construction of large-scaled annotated corpus for supervised learning is extremely difficult, thus most work exploits unsupervised learning. In this paper, unsupervised learning is used. Different from previous work, the hashtags labeled by microblog authors are used as the key information to improve the performance of hot topic extraction. Finally, the experiment demonstrate that this information is highly useful for hot topic extraction in microblog. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Self-supervised learning

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Enhanced Coffee Bean Defect Detection Using Super-Resolution GANs and Deep Learning

Enhanced Coffee Bean Defect Detection Using Super-Resolution...

引用

Computational Intelligence, Communication technology and Networking (CICTN), international conference on

作者： S. Prabu P.S. Thanigaivelu S. Poonkodi M. Anand Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai TamilNadu India

ISBN: (数字)9798331530389

ISBN: (纸本)9798331530396

Image Super-Resolution (SR) is a key challenge in computer vision, focusing on enhancing low-resolution images while preserving details. This paper presents a novel method using Generative Adversarial Networks (GANs) for improving image quality, specifically targeting coffee bean defect detection. The proposed SR-GAN model includes a generator that upscales low-resolution inputs and a discriminator that differentiates between generated high-resolution images and real ones. Trained on a coffee bean dataset, the model optimizes loss functions to balance perceptual quality and fidelity, capturing subtle defects like cracks and discolorations. Enhanced images are processed by two Convolutional Neural Networks (CNNs): one identifies broad defect categories, such as defective black beans, brown beans, broken beans and non-defective high-quality beans. This layered approach ensures more precise defect identification and classification, overcoming limitations of previous methods that struggled with subtle defects. Performance evaluations show that SR-GAN and CNN significantly outperforms existing models in resolution enhancement and classification accuracy, offering a robust solution for improving quality control in coffee production.

关键词： Deep learning Performance evaluation Image quality computer vision Computational modeling Superresolution Quality control Production Convolutional neural networks Defect detection

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