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共 25762 条记录，以下是131-140 订阅

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Multi-Objective Task Scheduling in Cloud Environments using Dynamic Velocity-Adaptive Particle Swarm Optimization

Multi-Objective Task Scheduling in Cloud Environments using ...

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2024 OPJU International technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Kumar, Ravi Vardhan, Manu Natinal Institute of Technology Dept. of Computer Science and Engineering Raipur India

ISBN: (纸本)9798350373783

In the realm of cloud computing, tackling the multi-objective task scheduling problem means finding the best way to assign tasks to virtual machines, taking into account conflicting goals like minimizing execution time, load balance and cost. This intricate task demands smart algorithms to strike a balance between these competing objectives, ensuring the most efficient use of resources and meeting user expectations in the cloud. Different optimization techniques, such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO), have been explored to handle this challenge and optimize task scheduling in the cloud environment. In classical PSO, particles can move at varying speeds in each iteration. In this study, we apply Velocity Stagnation Particle Swarm Optimization (VSPSO) variants where velocity stagnation applied during particles movement. This approach provides particles with a third movement option, enabling them to maintain the same velocity as in the previous iteration. VSPSO has a greater capacity to balance the exploration and exploitation. VSPSO adjusts the initial term of the PSO velocity equation to prevent premature convergence. Furthermore, the population of VSPSO is split into two swarms to ensure *** the inherent capabilities of PSO, VSPSO algorithm dynamically updates particle velocities to attain 5-6% total execution time 6-10% reduced cost and optimal balance load. Through meticulous comparisons with other algorithms, including Genetic Algorithm and Ant Colony Optimization, this study scrutinizes the effectiveness of our enhanced PSO approach. The overarching goal is to push the boundaries of multi-objective task scheduling in cloud computing by attaining minimal execution time, reduce cost and optimal balance load on each virtual machines. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Latency-Aware Cell Deletion in Link Scheduling for 6TiSCH Networks 16

Latency-Aware Cell Deletion in Link Scheduling for 6TiSCH Ne...

引用

16th International Conference on COMmunication Systems and NETworkS, COMSNETS 2024

作者： Tapadar, Karnish N A Khatua, Manas Tamarapalli, Venkatesh Indian Institute of Technology Guwahati Dept. of Computer Science and Engineering India

ISBN: (纸本)9798350383119

The 6TiSCH standard uses IEEE 802.15.4 Time Slotted Channel Hopping (TSCH) as a MAC layer protocol. TSCH cell scheduling determines packet transmission schedules in terms of timing and channel allocation. The Minimal Scheduling Function (MSF) and the 6P protocol facilitate schedule management dynamically. MSF involves a decision-making process to add/delete one cell at a time from the current schedule to adapt the schedule to modified traffic rate. The cell deletion is accomplished by randomly selecting one of the scheduled cells between two communicating nodes. However, random cell deletion can elevate end-to-end latency and energy consumption. Therefore, this paper proposes a Latency-aware Cell Deletion (LCD) mechanism to minimize associated average end-to-end latency and energy consumption. Simulations using the 6TiSCH simulator verified that in an 80-node network, compared to the standard MSF and another benchmark scheme IMSF, LCD achieved a substantial 44.40% and 42.39% reduction in end-to-end latency, respectively. © 2024 IEEE.

关键词： 6TiSCH Network Adaptive Link Scheduling Link Scheduling Minimal Scheduling Function

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Analysis of Interferograms with Arbitrary Phase Shifts Based on 3D-Trajectory Analysis 25

Analysis of Interferograms with Arbitrary Phase Shifts Based...

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25th IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2024

作者： Skorokhodov, Fedor A. Kazakov, Evgeniy G. Ilinykh, Sergey P. Dept. of Computer Technology Novosibirsk State Technical University Novosibirsk Russia

ISBN: (纸本)9798350389234

Optical interferometry is widely used in many branches of science and technology. The major problem of optical interferometry is to calculate the phase of the fringe pattern (interferogram) at each of its points. Recently, algorithms based on phase shifting have been used to solve this problem. The trajectory approach to the analysis of interferograms is known, in which the elliptical trajectory of interference signals (Lissajous figure) is transformed to a circular one. However, this approach requires finding the coefficients of the elliptic equation and its invariants with high accuracy, which presents certain technical difficulties. Also, this approach has a significant disadvantage - when stretching the ellipse to a circle, noise amplification occurs. A new approach is proposed that eliminates these difficulties. The approach is based on trajectory analysis of interference signals, which transforms the elliptical trajectory of interference patterns to a circular trajectory by projecting the points of the elliptical section of a 3D spatial shape onto the plane of the circular section. This transformation converts the elliptic trajectory into a circular one, which makes it possible to perform phase recovery using known formulas that do not explicitly contain the values of the phase shifts. The accuracy of phase calculation of different algorithms (algorithm based on the phase recovery formula for three fringe patterns, existent trajectory analysis algorithm and the proposed trajectory analysis algorithm) was compared. The experimental research was carried out on the synthesized interferograms with different values of phase shifts inaccuracy. The experimental data show that the phase recovery error for the first two algorithms is proportional to the phase shifts inaccuracy. Proposed algorithm has no such dependence. This allows to use the phase recovery formula for three fringe patterns with arbitrary phase shifts. © 2024 IEEE.

关键词： Interferometry

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Image Recognition-Based Indoor Positioning System Using Federated Learning 100

Image Recognition-Based Indoor Positioning System Using Fede...

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100th IEEE Vehicular technology Conference, VTC 2024-Fall

作者： Yu, Heng-Shao Jhuang, Yu-Chiao Leu, Jenq-Shiou University of Science and Technology Dept. of Electronic and Computer Engineering Taipei Taiwan

ISBN: (纸本)9798331517786

With the advancement of artificial intelligence (AI), indoor positioning systems have become increasingly important for various applications, leading to the development of diverse indoor positioning methods. Among various approaches, image-based indoor positioning methods have demonstrated relatively good positioning accuracy. However, maintaining user privacy continues to be a significant challenge. To tackle this issue, we propose a Federated Learning (FL) approach and develop an FL-based indoor image recognition positioning system. We conducted experiments to validate our method using two real-world datasets and compare the results to a Non-FL approach. Furthermore, we evaluated the accuracy of our method across various communication rounds, the number of client devices, and the amount of data per client device. Our experimental results indicate that the proposed method effectively preserves client privacy while achieving accuracy similar to the Non-FL approach. By employing FedAvg and FedOpt algorithms with the MobileNet model, our system ultimately reaches 94% accuracy. © 2024 IEEE.

关键词： Federated learning

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(In)Correct Smart Contract Specifications 6

(In)Correct Smart Contract Specifications

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6th IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2024

作者： Sorensen, Derek University of Cambridge Dept. of Computer Science and Technology Cambridge United Kingdom

ISBN: (纸本)9798350316742

Poorly specified smart contracts can be vulnerable to attacks on faulty design. Formal methods are currently unable to address these vulnerabilities because they are not vulnerabilities of incorrect code, but of incorrect specification. We are thus in need of a paradigm shift in how we specify and verify smart contracts which allows for a rigorous and accurate notion of a contract specification's correctness. We submit that correctness includes appropriate cryptoeconomic behaviors, which are generally out of scope of a contract's specification. We advocate for an approach to contract specification consisting of contract axiomatization and metaspecification, and illustrate with an example. © 2024 IEEE.

关键词： Smart contract

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Improving Fake News Detection with a Mixture of Experts: Leveraging Sentiment Analysis and Sarcasm Detection as Core Expert Models 6

Improving Fake News Detection with a Mixture of Experts: Lev...

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6th International Conference on Advancements in Computing, ICAC 2024

作者： Gunasekara, Tharindu Thihan, Disira Kodithuwakku, Sansika Dissanayake, Dinuka Fernando, Harinda Vidhanaarachchi, Samitha Sindhujan, Archchana Sri Lanka Institute of Information Technology Malabe Dept. of Software Engineering Sri Lanka Sri Lanka Institute of Information Technology Malabe Dept. of Computer Computer Systems Engineering Sri Lanka University of Surrey Dept. of Computer Science and Electronic Engineering United Kingdom

ISBN: (纸本)9798331517878

Fake news continues to proliferate, posing an increasing threat to public discourse. The paper proposes a framework of a Mixture of Experts, Sentiment Analysis, and Sarcasm Detection experts for improved fake news detection. This approach captures the emotional cues in the text through a Sentiment Analysis expert, which is based on bidirectional encoder representations from Transformers (BERT) models with sentiment vectors generated using SentiWordNet and Integrated Gradients. It combines a sarcasm detection expert based on BERT, recognizing sarcasm and its type to help classify fake news. By fusing these experts through a Mixture of Experts gateway, subtle linguistic cues often found in fake news are more effectively analyzed, leading to improved accuracy in detecting misinformation. Experimental results are presented as 96% for the Sarcasm expert with the BERT base model and 83% for the Sentiment Analysis expert with the distilled version of the BERT (DistilBERT) base model, proving the effectiveness of the proposed approach in beating traditional methods. © 2024 IEEE.

关键词： fake news detection gateway mixture of experts sarcasm detection sentiment analysis

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Advanced Forecasting and Analysis Techniques for Optimizing Website Performance: A Comparative Study of Time Series Models 2

Advanced Forecasting and Analysis Techniques for Optimizing ...

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2nd IEEE International Conference on IoT, Communication and Automation technology, ICICAT 2024

作者： Raikar, Gayathri Harshith, D. Guruprasad, N. Global Academy of Technology Dept. of Computer Science and Engineering Bangalore India Buddha Institute of Technology Computer Science and Engineering Gorakhpur India

ISBN: (纸本)9798350368109

Analyzing website performance is crucial for optimizing a site's functionality, enhancing user engagement, and aligning with business goals. This evaluation focuses on essential metrics such as average engagement time per session, engagement rate, and events per session, which significantly impact user experience and overall business success. Through effective performance analysis, organizations can improve user satisfaction, boost conversion rates, and enhance their profitability and reputation. This paper reviews different approaches for analyzing these key metrics, explores their effects on user behavior and business performance, and offers best practices for optimizing website performance. By employing detailed performance analysis, businesses can make informed decisions and realize their strategic goals in the digital environment. © 2024 IEEE.

关键词： Channel Performance Data Analysis Time Series Forecasting User Engagement Website Performance

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Utilizing Deep Learning Techniques for Categorizing Architectural Heritage Images 2

Utilizing Deep Learning Techniques for Categorizing Architec...

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2nd IEEE International Conference on Advances in Information technology, ICAIT 2024

作者： Pujari, Laxmi Ganamukhi, Pratibha Adur, Sindhu S. Dept. of Master of Computer Application KLE Institute of Technology Hubballi India

ISBN: (纸本)9798350383867

In this research, we address the challenge of manually categorizing architectural heritage images, which is time-consuming and subjective. We propose an automated image classification method using Python and machine learning, specifically deep learning. The system recognizes various architectural features like altars, apses, bell towers, columns, domes, flying buttresses, gargoyles, stained glass, and vaults. Our approach employs a deep learning model trained on annotated images of buildings. Users can upload architectural photos, which are then scaled, converted into a numpy array, and fed into the deep neural network for prediction. The model predicts the architectural category and provides the likelihood of the prediction. The system displays the predicted category together with the actual image, prediction accuracy, and a description of the identified class. Additionally, a bar graph visualizes the class probabilities for better interpretation. The dataset includes 10 categories split into training and testing folders, comprising 5937 and 1434 images, respectively. The evaluation results indicate that DenseNet121 achieved 86.61% accuracy, ResNet50v2 reached 84.24%, and MobileNetv2 achieved 74%. © 2024 IEEE.

关键词： Stained glass

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VGGAE-Net: A Two Stream Ensemble CNN for Diabetes Retinopathy Classification 4

VGGAE-Net: A Two Stream Ensemble CNN for Diabetes Retinopath...

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Girepunje, Shashank Singh, Pradeep National Institute of Technology Dept. of Computer Science and Engineering Raipur India

ISBN: (纸本)9798350349900

Diabetic retinopathy is a retinal disease that leads to vision impairment in people suffering from diabetes mellitus. Early detection of disease requires expert supervision and computer diagnosis systems to avoid vision loss. Diabetic Retinopathy grading is suffering from small lesions and data imbalance problems. In this work, we proposed a VGG based attentive ensemble Network (VGGAE-Net) for the classification of diabetes Retinopathy. We have also utilized the two attention blocks channel attention module and class attention module with extracted feature maps from the CNN. Then their prediction outputs are combined to provide the final output for the classification task. The experiment shows that the ensemble approach of two attention blocks with VGG model gives 96.66% accuracy as compared to the existing recent models. © 2024 IEEE.

关键词： class attention module diabetes retinopathy global attention module

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A multiscale feature extraction feedback network for single image super-resolution

A multiscale feature extraction feedback network for single ...

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2024 International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, AHPCAI 2024

作者： Yang, Dezhi Xie, Qingsong Xiao, Jinjie Dept. School of Computer Science and Technology Shandong Technology and Business University Yantai China

ISBN: (纸本)9781510685840

In conventional single image super-resolution (SISR) models utilizing deep learning, information is generally transmitted in a feedforward fashion. Nonetheless, these models have not fully exploited the feedback mechanism. Drawing inspiration from the feedback process in human vision, we introduce a Multiscale Feature Extraction Feedback Network (MFEFN), which utilizes high-level information to enhance low-level details. In particular, we employ the principles of Recurrent Neural Networks (RNNs) to reintroduce part of the output back into the model as input, thereby optimizing the input feature representations. We design a multiscale feature extraction channel attention feedback module to handle the feedback connections and generate rich detail texture features. Additionally, to address the issue of limited receptive fields and singular convolutional kernels in models, we propose a multiscale feature extraction module to capture detail texture features at different scales. To further enhance the model's cross-channel learning capability, we incorporate a channel attention mechanism. Comprehensive experimental results showcase the proposed MFEFN's superiority over current state-of-the-art methods. © 2024 SPIE.

关键词： Recurrent neural networks

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