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Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Cuddapah Anitha Dalia Al-Tarazi GD. Vignesh A. Vinotha Vasuki Jayant Giri M. Dinesh Department of Computer Science and Engineering School of Computing Mohan Babu University Erstwhile Sree Vidyanikethan Engineering College Tirupati India Department of Architecture Engineering Faculty of Engineering Zarqa university Zarqa Jordan College of Engineering University of Business and Technology Jeddah Saudi Arabia Department of Electronics and Communication Engineering St. Joseph's College of Engineering Chennai India Department of Computer Science and Engineering J.P. College of Engineering Tenkasi India Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur India Division of Research and Development Lovely Professional University Phagwara India Department of VLSI Microelectronics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Background: Vehicular Ad Hoc Networks (VANETs) play a crucial role in intelligent transportation by facilitating communication between vehicles and vehicles with infrastructure-based models. They encounter problems such as significant movement, overcrowding, and loss of data. This research presents a novel deep reinforcement learning-based resource allocation and congestion optimization (DRLRCO) framework aimed at improving communication efficiency and high reliability using an effective learning process. Method Used: The DRLRCO framework employs agent-based learning to ensure precise data transmission, AdMAC Protocol for dynamic packet delivery, and Congestion-Aware Chicken Swarm Optimization (CSO) to enhance network performance. Result: The DRLRCO framework surpasses reinforcement learning models for comprehensive testing. Significant enhancements involve improved accuracy, reduced data loss, minimized overhead, increased throughput, and shorter average delays for real-time communication. Conclusion: The DRLRCO framework successfully tackles congestion and data loss in vehicular communication. Future studies might involve Artificial Intelligence (AI) for traffic forecasting, experimentation among high-speed vehicles and investigating blockchain for enhanced security.

关键词： Vehicular ad hoc networks Routing Throughput Synchronization Resource management Dedicated short range communication Particle swarm optimization Artificial intelligence Vehicle dynamics Testing

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Application of machine learning techniques to predict patient’s satisfaction of indoor environmental quality in Jordanian hospitals

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 13673-13681页

作者： Ali, Hikmat H. Abdullah, Malak Wedyan, Musab Department of Architecture Jordan University of Science and Technology Irbid Jordan Department of Computer Science Jordan University of Science and Technology Irbid Jordan

The indoor environment is an integral part of the hospital design since it impacts patients’ health, well-being, and healing process. Although the machine learning approach has been widely adopted in many fields, limited studies applied the machine learning approach to indoor environmental quality (IEQ) in hospitals and the impact of the room type on patients’ satisfaction with IEQ. Accordingly, the current study aims to bridge this gap using the machine learning approach. The research used mixed design methods to assess indoor environmental quality. The data was gathered using self-reported data and field monitoring of environmental parameters inside patients’ rooms. King Abdullah University Hospital (KAUH) was used to represent hospitals in Jordan. Machine learning proceeded in several stages, starting from prepossessing, training the algorithms, and testing the results. The experiments were conducted with the same dataset for training and testing and evaluated using the same classification metrics using Python programming language. Besides, the most important features were conducted using Random Forest regardless of room type, in each room type, and each category of IEQ between room types. The present findings confirmed a variation in the essential features. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Hospitals

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Emerging methodologies in multiple sequence alignment using high throughput data

Emerging methodologies in multiple sequence alignment using ...

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作者： Guzman, Francisco M. Ortuño Rojas, I. Pomares, H. Urquiza, J.M. Florido, J.P. Department of Computer Architecture and Computer Technology University of Granada Spain

ISBN: (纸本)9783642199134

New computational methodologies are increasingly being demanded in Bioinformatics due to the amount of data provided by high-throughput experiments. One of these approaches is multiple sequence alignment since feature integration is necessary to obtain more accurate and faster alignments. Alignments of nucleotide and protein sequences can help us to understand tasks like biological functions or structures in these molecules. Recent applications tend to use more available data that represent similarity among sequences: homologies, structures, functions, domains, motifs, etc. Thus, we present a review of current methods in multiple sequence alignments and their improvements integrating accurately and efficiently these heterogeneous data. © 2011 Springer-Verlag Berlin Heidelberg.

关键词： Throughput

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An IMS-Learning Design editor for a higher education blended learning scenario

An IMS-Learning Design editor for a higher education blended...

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8th IEEE International Conference on Advanced Learning Technologies, ICALT 2008

作者： Rocío, García-Robles Laura, Ferrer Daniel, Cagigas Computer Architecture and Technology Department University of Seville

ISBN: (纸本)9780769531670

The IMS-Learning Design has been developed to support the creation of reusable and pedagogically neutral learning scenarios and content. Although it is especially suitable for eLearning, there is a lot of interest on using it in higher education blended learning scenarios. However there are some related key issues which must be managed such as cultural bias and the need for expensive human resources to design and develop specification compliant units of learning. They can be addressed by the design of ad-hoc editors supporting concrete learning design units of learning. We suggest some solutions to overcome these limitations, based on our experience designing the user interface of an IMS-LD compliant editor, GDUS+. We also explain our user centering approach, and give some conclusions about the benefits of using IMS-LD. © 2008 IEEE.

关键词： Electronic learning Cultural differences Machine learning Educational technology computer science education User interfaces Collaborative software computer architecture Human resource management Concrete

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Scalable selective re-execution for EDGE architectures

Scalable selective re-execution for EDGE architectures

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作者： Desikan, Rajagopalan Sethumadhavan, Simha Burger, Doug Keckler, Stephen W. Computer Architecture and Technology Laboratory Department of Computer Sciences University of Texas Austin Computer Architecture and Technology Laboratory Department of Electrical and Computer Engineering University of Texas Austin

Pipeline flushes are becoming increasingly expensive in modern microprocessors with large instruction windows and deep pipelines. Selective re-execution is a technique that can reduce the penalty of mis-speculations by re-executing only instructions affected by the mis-speculation, instead of all instructions. In this paper we introduce a new selective re-execution mechanism that exploits the properties of a dataflow-like Explicit Data Graph Execution (EDGE) architecture to support efficient mis-speculation recovery, while scaling to window sizes of thousands of instructions with high performance. This distributed selective re-execution (DSRE) protocol permits multiple speculative waves of computation to be traversing a dataflow graph simultaneously, with a commit wave propagating behind them to ensure correct execution. We evaluate one application of this protocol to provide efficient recovery for load-store dependence speculation. Unlike traditional dataflow architectures which resorted to single-assignment memory semantics, the DSRE protocol combines dataflow execution with speculation to enable high performance and conventional sequential memory semantics. Our experiments show that the DSRE protocol results in an average 17% speedup over the best dependence predictor proposed to date, and obtains 82% of the performance possible with a perfect oracle directing the issue of loads. Copyright 2004 ACM.

关键词： Pipeline processing systems

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Assessing disruptive potential of retail central bank digital currency and influence of design considerations: An open innovation approach in Thailand

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Journal of Open Innovation: technology, Market, and Complexity 2025年第1期11卷

作者： Wathahong, Thanwa Ratanabanchuen, Roongkiat Israsena Na Ayudhya, Praima Tientanopajai, Kitt Technology Management and Innopreneurship Program Graduate School Chulalongkorn University Phayathai Road Bangkok 10330 Thailand Department of Banking and Finance Chulalongkorn Business School Chulalongkorn University Phayathai Road Bangkok 10330 Thailand Department of Industrial Design Faculty of Architecture Chulalongkorn University Phayathai Road Bangkok 10330 Thailand Department of Computer Engineering Faculty of Engineering Khon Kaen University Mittraphap Road Khon Kaen 40002 Thailand

Monetary authorities globally have studied central bank digital currency (CBDC) for wholesale and retail applications since the 1990s. Besides countering private cryptocurrencies' influence, central banks have also explored other benefits of CBDC, such as improving their financial oversight, enhancing digital payment systems, and reducing transaction fees and friction. For several years, the Bank of Thailand has also invested in research and development of CBDC, including retail use cases. However, an optimized design for an official launch of a retail CBDC in Thailand has yet to be determined, resembling fragmented progress observed among other central banks. This research has leveraged disruptive innovation theory to provide a fresh perspective on retail CBDC as potentially disruptive financial innovations. Additionally, it has proposed an open innovation-based methodology to determine industry preferences concerning twelve design considerations for retail CBDC and their impact on nine indicators of disruptive innovation. Data has been collected and analyzed from 98 respondents outside the Bank of Thailand, all possessing relevant expertise or experience in electronic payments. Crosstab and logistic regression analyses have indicated that retail CBDC in Thailand could embark on a disruptive innovation trajectory by adhering to defined design choices. Significantly, entering a new detached market has been identified as the most promising entry point, accompanied by explicit recommendations on nine out of twelve design considerations. © 2025 The Authors

关键词： CBDC Central bank digital Currency Disruptive innovation Open Innovation Retail

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Trainbow: a new trusted virtual machine based platform

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中国高等学校学术文摘·计算机科学 2010年第1期4卷 47-64页

作者： Yuzhong SUN Yongbing HUANG Yunwei GAO Haifeng FANG Ying SONG Lei DU Kai ZHANG Hongyong ZANG Yaqiong LI Yajun YANG Ran AO Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China Graduate University of Chinese Academy of Sciences Beijing 100190China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China Graduate University of Chinese Academy of Sciences Beijing 100190China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China Department of Computer Science and Technology Xi'an Jiaotong University Xi'an 710049China Key Laboratory of Computer System and Architecture Institute of Computing TechnologyChinese Academy of Sciences Beijing 100190China Graduate University of Chinese Academy of Sciences Beijing 100190China

Currently, with the evolution of virtualization technology, cloud computing mode has become more and more popular. However, people still concern the issues of the runtime integrity and data security of cloud computing platform, as well as the service efficiency on such computing platform. At the same time, according to our knowledge, the design theory of the trusted virtual computing environment and its core system software for such network-based computing platform is at the exploratory stage. In this paper, we believe that efficiency and isolation are the two key proprieties of the trusted virtual computing environment. To guarantee these two proprieties, based on the design principle of splitting, customizing, reconstructing, and isolation-based enhancing to the platform, we introduce TRainbow, a novel trusted virtual computing platform developing by our research *** the two creative mechanisms, that is, capacity flowing amongst VMs and VM-based kernel reconstructing, TRainbow provides great improvements (up to 42%) in service performance and isolated reliable computing environment for Internet-oriented, large-scale, concurrent services.

关键词： Computing platform virtual machine capacity service computing trust chain isolation

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Customization of the text-to-image diffusion model by fine-tuning for the generation of synthetic images of cyanobacterial blooms in lentic water bodies

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Expert Systems with Applications 2025年 287卷

作者： Fredy Barrientos-Espillco Gonzalo Pajares José A. López-Orozco Eva Besada-Portas Department of Computer Architecture and Automation University Complutense of Madrid 28040 Madrid Spain Institute for Knowledge Technology University Complutense of Madrid 28040 Madrid Spain

Cyanobacterial blooms emerge unpredictably on the surface of lentic water bodies, posing both ecological threats and public health risks. To effectively monitor these events, this study introduces the use of Machine Vision Systems (MVS) integrated into Autonomous Surface Vehicles (ASVs). These ASVs are capable of autonomous and safe navigation, enabling them to detect cyanobacterial blooms while avoiding obstacles. Convolutional Neural Networks (CNNs) are employed for early detection and continuous monitoring, but their effectiveness hinges on access to large, high-quality training datasets. Due to the sporadic and uncontrollable nature of bloom occurrences, acquiring sufficient real-world images for training and validating CNN models is a significant challenge. To overcome this, the Stable Diffusion XL (SDXL) text-to-image generative model is utilized to produce realistic synthetic images, ensuring a sufficient dataset for training. However, SDXL alone struggles to accurately depict cyanobacterial blooms. To address this limitation, DreamBooth is used to fine-tune SDXL with a small set of real bloom-specific image patches. To ensure the diversity of the synthetic dataset, detailed prompts for SDXL are generated using a Large Language Model (LLM). The combination of SDXL fine-tuning with LLM-driven prompts design applied to environmental monitoring and autonomous navigation in lentic environments represents the core innovation of this work. A dual-task CNN model is then trained on the synthetic dataset to simultaneously detect blooms and obstacles. Experimental results demonstrate the effectiveness and novelty of the proposed approach, showing improvements of up to 15.74% in object detection and 6.48% in semantic segmentation compared to the baseline dataset.

关键词： Artificial intelligence Machine vision systems Text-to-image generation Fine-tuning Large language model Convolutional neural networks Autonomous surface vehicles Cyanobacterial blooms

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Two-level Hash/Table approach for metadata management in distributed file systems

Two-level Hash/Table approach for metadata management in dis...

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作者： Díaz, Antonio F. Anguita, Mancia Camacho, Hugo E. Nieto, Erik Ortega, Julio Department of Computer Architecture and Computer Technology University of Granada Granada Spain

AbFS is a distributed file system that makes it possible to efficiently share the inexpensive devices attached to the commodity computers of a cluster. The implementation of AbFS offers high-performance metadata management by combining hashing and tables in several levels, hierarchical structures and caches, and by combining the attributes and the namespace in the same structure. No additional layers are needed to implement caches because AbFS uses the Linux metadata caches, inode and dentry, to implement them. Along with the description of the proposed implementation for metadata management and the comparison with other implementations, this work provides experimental results to evaluate its performance obtained with a prototype made from scratch at kernel level. AbFS experimental results show that the implementation proposed is capable to manage files and directories with high performance. © 2012 Springer Science+Business Media, LLC.

关键词： Metadata

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Surface modelling with radial basis functions neural networks using virtual environments

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9th International Work-Conference on Artificial Neural Networks, IWANN 2007

作者： Loápez, Miguel Aángel Pomares, Heáctor Damas, Miguel Diáaz-Estrella, Antonio Prieto, Alberto Pelayo, Francisco De La Plaza Hernaández, Eva Mariáa Department of Computer Architecture and Computer Technology University of Granada Department of Electronic Technology University of Maálaga

ISBN: (纸本)9783540730064

Modelling capabilities of Radial Basis Function Neural Networks (RBFNNs) are very dependent on four main factors: the number of neurons, the central location of each neuron, their associated weights and their widths (radii). In order to model surfaces defined, for example, as y = f(x,z), it is common to use tri-dimensional gaussian functions with centres in the (X,Z) domain. In this scenario, it is very useful to have visual environments where the user can interact with every radial basis function, modify them, inserting and removing them, thus visually attaining an initial configuration as similar as possible to the surface to be approximated. In this way, the user (the novice researcher) can learn how every factor affects the approximation capability of the network, thus gaining important knowledge about how algorithms proposed in the literature tend to improve the approximation accuracy. This paper presents a didactic tool we have developed to facilitate the understanding of surface modelling concepts with ANNs in general and of RBFNNs in particular, with the aid of a virtual environment. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Neural networks

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