检索结果-南通市图书馆

computer Modeling in engineering & sciences 2024年第8期140卷 1711-1728页

作者： Jing-Doo Wang Chayadi Oktomy Noto Susanto Departement of computer science and information engineering Asia UniversityTaichungTaiwanChina Departement of information Technology Universitas Muhammadiyah YogyakartaYogyakartaIndonesia

A significant obstacle in intelligent transportation systems(ITS)is the capacity to predict traffic *** advancements in deep neural networks have enabled the development of models to represent traffic flow ***,accurately predicting traffic flow at the individual road level is extremely difficult due to the complex interplay of spatial and temporal *** paper proposes a technique for predicting short-term traffic flow data using an architecture that utilizes convolutional bidirectional long short-term memory(Conv-BiLSTM)with attention *** studies neglected to include data pertaining to factors such as holidays,weather conditions,and vehicle types,which are interconnected and significantly impact the accuracy of forecast *** addition,this research incorporates recurring monthly periodic pattern data that significantly enhances the accuracy of forecast *** experimental findings demonstrate a performance improvement of 21.68%when incorporating the vehicle type feature.

关键词： Traffic flow prediction sptiotemporal data heterogeneous data Conv-BiLSTM data-centric intra-data

An Encoding-Decoding Framework Based on CNN for circ RNA-RBP Binding Sites Prediction

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Journal of Electronics 2024年第1期33卷 256-263页

作者： Yajing GUO Xiujuan LEI Yi PAN School of computer science Shaanxi Normal University Faculty of computer science and Control engineering Shenzhen Institute of Advanced TechnologyChinese Academy of Sciences department of computer science Georgia State University

Predicting RNA binding protein(RBP) binding sites on circular RNAs(circ RNAs) is a fundamental step to understand their interaction mechanism. Numerous computational methods are developed to solve this problem, but they cannot fully learn the features. Therefore, we propose circ-CNNED, a convolutional neural network(CNN)-based encoding and decoding framework. We first adopt two encoding methods to obtain two original matrices. We preprocess them using CNN before fusion. To capture the feature dependencies, we utilize temporal convolutional network(TCN) and CNN to construct encoding and decoding blocks, respectively. Then we introduce global expectation pooling to learn latent information and enhance the robustness of circ-CNNED. We perform circ-CNNED across 37 datasets to evaluate its effect. The comparison and ablation experiments demonstrate that our method is superior. In addition, motif enrichment analysis on four datasets helps us to explore the reason for performance improvement of circ-CNNED.

关键词： Proteins RNA Neural networks Encoding Robustness Decoding Convolutional neural networks

Hybrid Approach for Cost Efficient Application Placement in Fog-Cloud Computing Environments

同方期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

computers, Materials & Continua 2024年第6期79卷 4127-4148页

作者： Abdulelah Alwabel Chinmaya Kumar Swain department of computer sciences College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia department of computer science and engineering Institute of Management and Information TechnologyCuttackBPUTOdishaIndia

Fog computing has recently developed as a new paradigm with the aim of addressing time-sensitive applications better than with cloud computing by placing and processing tasks in close proximity to the data ***,the majority of the fog nodes in this environment are geographically scattered with resources that are limited in terms of capabilities compared to cloud nodes,thus making the application placement problem more complex than that in cloud *** approach for cost-efficient application placement in fog-cloud computing environments that combines the benefits of both fog and cloud computing to optimize the placement of applications and services while minimizing *** approach is particularly relevant in scenarios where latency,resource constraints,and cost considerations are crucial factors for the deployment of *** this study,we propose a hybrid approach that combines a genetic algorithm(GA)with the Flamingo Search Algorithm(FSA)to place application modules while minimizing *** consider four cost-types for application deployment:Computation,communication,energy consumption,and *** proposed hybrid approach is called GA-FSA and is designed to place the application modules considering the deadline of the application and deploy them appropriately to fog or cloud nodes to curtail the overall cost of the *** extensive simulation is conducted to assess the performance of the proposed approach compared to other state-of-the-art *** results demonstrate that GA-FSA approach is superior to the other approaches with respect to task guarantee ratio(TGR)and total cost.

关键词： Placement mechanism application module placement fog computing cloud computing genetic algorithm flamingo search algorithm

A Deep Learning Approach for Landmines Detection Based on Airborne Magnetometry Imaging and Edge Computing

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

computer Modeling in engineering & sciences 2024年第5期139卷 2117-2137页

作者： Ahmed Barnawi Krishan Kumar Neeraj Kumar Bander Alzahrani Amal Almansour Faculty of Computing and information Technology King Abdulaziz UniversityJeddahSaudi Arabia department of computer science and engineering Thapar Institute of Engineering and TechnologyDeemed to be UniversityPatialaIndia

Landmines continue to pose an ongoing threat in various regions around the world,with countless buried landmines affecting numerous human *** detonation of these landmines results in thousands of casualties reported worldwide ***,there is a pressing need to employ diverse landmine detection techniques for their *** effective approach for landmine detection is UAV(Unmanned Aerial Vehicle)based AirborneMagnetometry,which identifies magnetic anomalies in the local terrestrial magnetic *** can generate a contour plot or heat map that visually represents the magnetic field *** the effectiveness of this approach,landmine removal remains a challenging and resource-intensive task,fraughtwith *** computing,on the other hand,can play a crucial role in critical drone monitoring applications like landmine *** processing data locally on a nearby edge server,edge computing can reduce communication latency and bandwidth requirements,allowing real-time analysis of magnetic field *** enables faster decision-making and more efficient landmine detection,potentially saving lives and minimizing the risks involved in the ***,edge computing can provide enhanced security and privacy by keeping sensitive data close to the source,reducing the chances of data exposure during *** paper introduces the MAGnetometry Imaging based Classification System(MAGICS),a fully automated UAV-based system designed for landmine and buried object detection and *** have developed an efficient deep learning-based strategy for automatic image classification using magnetometry dataset *** simulating the proposal in various network scenarios,we have successfully detected landmine signatures present in themagnetometry *** trained models exhibit significant performance improvements,achieving a maximum mean average precision value of 97.8%.

关键词： CNN deep learning landmine detection magnetometer mean average precision UAV

Feature-Grounded Single-Stage Text-to-Image Generation

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Tsinghua science and Technology 2024年第2期29卷 469-480页

作者： Yuan Zhou Peng Wang Lei Xiang Haofeng Zhang School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing 210044China School of computer science and engineering Nanjing University of Science and TechnologyNanjing 210094China

Recently,Generative Adversarial Networks(GANs)have become the mainstream text-to-image(T2I)***,a standard normal distribution noise of inputs cannot provide sufficient information to synthesize an image that approaches the ground-truth image ***,the multistage generation strategy results in complex T2I ***,this study proposes a novel feature-grounded single-stage T2I model,which considers the“real”distribution learned from training images as one input and introduces a worst-case-optimized similarity measure into the loss function to enhance the model's generation *** results on two benchmark datasets demonstrate the competitive performance of the proposed model in terms of the Frechet inception distance and inception score compared to those of some classical and state-of-the-art models,showing the improved similarities among the generated image,text,and ground truth.

关键词： text-to-image(T2I) feature-grounded single-stage generation Generative Adversarial Network(GAN)

Mobile Crowdsourcing Task Allocation Based on Dynamic Self-Attention GANs

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

computers, Materials & Continua 2024年第4期79卷 607-622页

作者： Kai Wei Song Yu Qingxian Pan School of computer and Control engineering Yantai UniversityYantai264005China School of computer and information science Southwest UniversityChongqing400715China

Crowdsourcing technology is widely recognized for its effectiveness in task scheduling and resource *** traditional methods for task allocation can help reduce costs and improve efficiency,they may encounter challenges when dealing with abnormal data flow nodes,leading to decreased allocation accuracy and *** address these issues,this study proposes a novel two-part invalid detection task allocation *** the first step,an anomaly detection model is developed using a dynamic self-attentive GAN to identify anomalous *** to the baseline method,the model achieves an approximately 4%increase in the F1 value on the public *** the second step of the framework,task allocation modeling is performed using a twopart graph matching *** phase introduces a P-queue KM algorithm that implements a more efficient optimization *** allocation efficiency is improved by approximately 23.83%compared to the baseline *** results confirm the effectiveness of the proposed framework in detecting abnormal data nodes,enhancing allocation precision,and achieving efficient allocation.

关键词： Mobile crowdsourcing task allocation anomaly detection GAN attention mechanisms

Dynamics analysis and cryptographic implementation of a fractional-order memristive cellular neural network model

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Physics B 2024年第4期33卷 418-433页

作者：周新卫蒋东华 Jean De Dieu Nkapkop Musheer Ahmad Jules Tagne Fossi Nestor Tsafack 吴建华 department of information engineering Gongqing CollegeNanchang UniversityJiujiang 332020China School of computer science and engineering Sun Yat-Sen UniversityGuangzhou 511400China department of Electrical engineering and Industrial Computing University Institute of TechnologyDoualaCameroon department of computer engineering Jamia Millia IslamiaNew Delhi 110025India department of Physics Faculty of ScienceUniversity of YaoundeCameroon Electrical engineering department and Industrial Computing of ISTAMA University of DoualaDoualaCameroon

Due to the fact that a memristor with memory properties is an ideal electronic component for implementation of the artificial neural synaptic function,a brand-new tristable locally active memristor model is first proposed in this ***,a novel four-dimensional fractional-order memristive cellular neural network(FO-MCNN)model with hidden attractors is constructed to enhance the engineering feasibility of the original CNN model and its ***,its hardware circuit implementation and complicated dynamic properties are investigated on multi-simulation ***,it is used toward secure communication application *** it as the pseudo-random number generator(PRNG),a new privacy image security scheme is designed based on the adaptive sampling rate compressive sensing(ASR-CS)***,the simulation analysis and comparative experiments manifest that the proposed data encryption scheme possesses strong immunity against various security attack models and satisfactory compression performance.

关键词： cellular neural network memristor hardware circuit compressive sensing privacy data protection

An Attention-Based Approach to Enhance the Detection and Classification of Android Malware

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

computers, Materials & Continua 2024年第8期80卷 2743-2760页

作者： Abdallah Ghourabi department of computer science College of Computer and Information SciencesJouf UniversitySakaka72388Saudi Arabia

The dominance of Android in the global mobile market and the open development characteristics of this platform have resulted in a significant increase in *** malicious applications have become a serious concern to the security of Android *** address this problem,researchers have proposed several machine-learning models to detect and classify Android malware based on analyzing features extracted from Android ***,most existing studies have focused on the classification task and overlooked the feature selection process,which is crucial to reduce the training time and maintain or improve the classification *** current paper proposes a new Android malware detection and classification approach that identifies the most important features to improve classification performance and reduce training *** proposed approach consists of two main ***,a feature selection method based on the Attention mechanism is used to select the most important ***,an optimized Light Gradient Boosting Machine(LightGBM)classifier is applied to classify the Android samples and identify the *** feature selection method proposed in this paper is to integrate an Attention layer into a multilayer perceptron neural *** role of the Attention layer is to compute the weighted values of each feature based on its importance for the classification *** evaluation of the approach has shown that combining the Attention-based technique with an optimized classification algorithm for Android malware detection has improved the accuracy from 98.64%to 98.71%while reducing the training time from 80 to 28 s.

关键词： Android malware malware detection feature selection attention mechanism LightGBM mobile security

Practical cloud storage auditing using serverless computing

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

science China(information sciences) 2024年第3期67卷 33-47页

作者： Fei CHEN Jianquan CAI Tao XIANG Xiaofeng LIAO College of computer science and Software engineering Shenzhen University College of computer science Chongqing University

Cloud storage auditing research is dedicated to solving the data integrity problem of outsourced storage on the cloud. In recent years, researchers have proposed various cloud storage auditing schemes using different techniques. While these studies are elegant in theory, they assume an ideal cloud storage model;that is, they assume that the cloud provides the storage and compute interfaces as required by the proposed schemes. However, this does not hold for mainstream cloud storage systems because these systems only provide read and write interfaces but not the compute interface. To bridge this gap, this work proposes a serverless computing-based cloud storage auditing system for existing mainstream cloud object storage. The proposed system leverages existing cloud storage auditing schemes as a basic building block and makes two adaptations. One is that we use the read interface of cloud object storage to support block data requests in a traditional cloud storage auditing scheme. Another is that we employ the serverless computing paradigm to support block data computation as traditionally required. Leveraging the characteristics of serverless computing, the proposed system realizes economical, pay-as-you-go cloud storage auditing. The proposed system also supports mainstream cloud storage upper layer applications(e.g., file preview) by not modifying the data formats when embedding authentication tags for later auditing. We prototyped and open-sourced the proposed system to a mainstream cloud service, i.e., Tencent Cloud. Experimental results show that the proposed system is efficient and promising for practical use. For 40 GB of data, auditing takes approximately 98 s using serverless computation. The economic cost is 120.48 CNY per year, of which serverless computing only accounts for 46%. In contrast, no existing studies reported cloud storage auditing results for real-world cloud services.

关键词： cloud storage auditing serverless computing object storage usability

Cloud‐based video streaming services:Trends,challenges,and opportunities

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

CAAI Transactions on Intelligence Technology 2024年第2期9卷 265-285页

作者： Tajinder Kumar Purushottam Sharma Jaswinder Tanwar Hisham Alsghier Shashi Bhushan Hesham Alhumyani Vivek Sharma Ahmed I.Alutaibi CSE department JMIETIYamunanagarHaryanaIndia department of information Technology ASETAmity University Uttar PradeshNoidaIndia Tata Communications Limited New DelhiIndia department of information Technology College of Computer and Information SciencesMajmaah UniversityMajmaahSaudi Arabia Amity School of engineering and Technology Amity UniversityPatnaBiharIndia department of computer engineering College of Computers and Information TechnologyTaif UniversityTaifSaudi Arabia department of computer engineering College of Computer and Information SciencesMajmaah UniversityMajmaahSaudi Arabia

Cloud computing has drastically changed the delivery and consumption of live streaming *** designs,challenges,and possible uses of cloud computing for live streaming are studied.A comprehensive overview of the technical and business issues surrounding cloudbased live streaming is provided,including the benefits of cloud computing,the various live streaming architectures,and the challenges that live streaming service providers face in delivering high‐quality,real‐time *** different techniques used to improve the performance of video streaming,such as adaptive bit‐rate streaming,multicast distribution,and edge computing are discussed and the necessity of low‐latency and high‐quality video transmission in cloud‐based live streaming is *** such as improving user experience and live streaming service performance using cutting‐edge technology,like artificial intelligence and machine learning are *** addition,the legal and regulatory implications of cloud‐based live streaming,including issues with network neutrality,data privacy,and content moderation are *** future of cloud computing for live streaming is examined in the section that follows,and it looks at the most likely new developments in terms of trends and *** technology vendors,live streaming service providers,and regulators,the findings have major policy‐relevant *** on how stakeholders should address these concerns and take advantage of the potential presented by this rapidly evolving sector,as well as insights into the key challenges and opportunities associated with cloud‐based live streaming are provided.

关键词： cloud computing video analysis video coding