检索结果-内蒙古大学图书馆

1st International Conference on Cognitive, Green and Ubiquitous Computing, IC-CGU 2024

作者： Jaiprakash, Sahani Pooja Badal, Tapas Gupta, Indrajeet Kumar, Naween School of Computer Science Engineering and Technology Bennett Univarsity Greater Noida India Department of Computer Science and Engineering Bhubaneswar India School of Computer Science Engineering and AI SR Univarsity Warangal India

ISBN: (纸本)9798350361780

As cloud data centres expand and provide more services, they consume more energy and cause challenges for the environment. To address this, there is a focus on energy-saving scheduling approaches in cloud computing. This study proposes a novel method for scheduling workflows in cloud computing that is based on the MaxUtil framework. The proposed method integrates the well-known flower pollination algorithm (FPA), a meta-heuristic algorithm derived from natural phenomena. The suggested scheduling approach aims to reduce energy usage and workflow processing time. The suggested method consists of two stages: (i) job assignment to virtual machines (VMs) that are available, and (ii) task scheduling based on optimal criteria. Extensive research has been undertaken throughout five scientific procedures from diverse domains. Tests on various scientific workflows show that this method performs better than other common scheduling methods like PSO, GSA, and GA in most cases. © 2024 IEEE.

关键词： Virtual machine

来源：评论

学校读者我要写书评

暂无评论

Optimization of Traffic System using Adaptive Response First Come First Serve

Optimization of Traffic System using Adaptive Response First...

引用

2024 International Conference on Signal Processing, Computation, Electronics, Power and Telecommunication, IConSCEPT 2024

作者： Amutha, S. Singh, Dhruv Singh, Shashank Shekhar Jhandial, Anant Gupta Krishna, Kunal School of Computer Science and Engineering Vellore Institute of Technology Chennai India School of Electronics and Communication Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798331540685

In this period of urbanization and adding vehicular traffic, the optimization of business operation systems is consummate to insure both the effectiveness of transportation networks and the safety of commuters. This exploration paper explores the operation of deep literacy ways to revise the field of business operation. By employing the power of deep learning, sensors and timers, our study aims to develop innovative results that ameliorate the delicacy, rigidity, and real- time responsiveness of business control systems. The primary focus of this exploration is to design a comprehensive deep literacy-grounded business operation system that incorporates colorful data sources. By assaying vast quantities of miscellaneous data, the system will acclimatize to dynamic business conditions and offer real- time perceptivity for effective business inflow operation, accident discovery, and traffic relief. The exploration will also explore the integration of machine literacy algorithms for intelligent business signal control, prioritizing green light allocation grounded on real- time demand and business viscosity. The proposed deep literacy result aims to significantly reduce business traffic, minimize trip times, and enhance overall road safety by furnishing optimized business operation strategies. The exploration will concentrate on the practical perpetration of the system in real- world business scripts, with the eventuality to gauge and acclimatize to colorful civic surroundings. This exploration bid seeks to lay the foundation for a future in which business systems seamlessly acclimatize to evolving business patterns, creating safer, more effective transportation networks, and contributing to a sustainable and intelligent civic ecosystem. The proposed dynamic signal control logic is 83.33 % more efficient in utilizing green time compared to the traditional fixed-time system. Estimated reduction in wasted green time is 25%. © 2024 IEEE.

关键词： Traffic signals

来源：评论

学校读者我要写书评

暂无评论

Forecasting Bitcoin Prices Using Deep Learning for Consumer-Centric Industrial Applications

引用

IEEE Transactions on Consumer Electronics 2024年第1期70卷 1351-1358页

作者： Roy, Pradeep Kumar Kumar, Abhinav Singh, Ashish Sangaiah, Arun Kumar Indian Institute of Information Technology Surat Department of Computer Science and Engineering Surat394190 India Motilal Nehru National Institute of Technology Allahabad Department of Computer Science and Engineering Prayagraj211004 India KIIT Deemed to Be University School of Computer Engineering Bhubaneswar751024 India National Yunlin University of Science and Technology International Graduate Institute of AI Douliou64002 Taiwan Lebanese American University Department of Electrical and Computer Engineering Byblos1102-2801 Lebanon

As cryptocurrencies become more popular as investment vehicles, bitcoin draws interest from businesses, consumers, and computer scientists all across the world. Bitcoin is a computer file stored in digital wallet applications where each transaction is secured using strong cryptographic algorithms. It was challenging to forecast the future price of bitcoin due to its nonlinearity and extreme volatility. Several recent classic parametric models have been found with limited accuracy. To address the limitations and fill the existing research gaps, there is a need for a good prediction model which will provide the desired accuracy in the case of uncertainty and dynamism. This research suggested a deep learning-based framework for predicting and forecasting Bitcoin price. The research will be helpful for worldwide consumers and industries to take their decision on whether to invest or not. The research utilizes Yahoo! finance dataset for the period of 01-03-2016 to 26-02-2021 having 1828 samples. The experimental outcomes of the proposed Long Short-Term Memory (LSTM) model outperformed similar deep learning models by securing minimum loss and confirming that it can be used for future price prediction of the cryptocurrencies, which is helpful for the buyer to take their decision. © 1975-2011 IEEE.

关键词： Hidden Markov models

来源：评论

学校读者我要写书评

暂无评论

SMART DRIVING LICENSING SYSTEM AND AUTHORIZATION OF AUTONOMOUS VEHICLE INTEGRATING WIRELESS SENSOR NETWORKS AND IoT

引用

Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2024年第9期83卷 69-85页

作者： Santhakumar, D. Sudhan, M.B. Prasanna, R. Manikandan, S.P. Prathaban, Banu Priya Kanna, Rajesh R. Saravanan, G. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai Ramapuram India Department of Electronics and Communication Engineering SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering Sree Sastha Institute of Engineering and Technology Chennai India Department of Networking and Communications School of Computing SRM Institute of Science and Technology Kattankulathur Chennai India Department of Electronics and Communication Engineering Sri Sairam Institute of Technology Tamil Nadu Chennai India

The advent of autonomous vehicles has revolutionized the automotive industry, offering promising advancements in safety, efficiency, and mobility. To integrate these autonomous vehicles into our society seamlessly, it is imperative to establish a robust licensing system that ensures the safe operation of automated vehicles on public roads. This article presents an effective smart Driving Licensing System (SDLS), a digital framework designed to regulate the existing licensing system and authorize licensing for autonomous vehicles. Through a comprehensive assessment process, the system assesses the drivers and the autonomous vehicle’s ability to navigate various road conditions, respond to dynamic environments, and prioritize safety for passengers and other road users. SDLS integrates high-level security through facial and fingerprint verification for identity verification to preserve licensing data. Hacking and unauthorized access to autonomous vehicles is prevented by robust cybersecurity protocols. The key benefits of SDLS include automated data collection, integration of wireless sensor networks (WSN) and Internet of Things (IoT), smart application processing, real-time license checks, cybersecurity measures, automated testing, and digital certification. The proposed system offers a comprehensive approach to safely integrating autonomous vehicles into our transportation ecosystem. The autonomous vehicles are integrated with antennas at rooftops or into bumpers, depending upon the vehicle design which can be connected with the SDLS for signal communication. Furthermore, the SDLS establishes a framework for continuous monitoring and updates, enabling ongoing assessments to keep pace with evolving technology and safety standards. © 2024 by Begell House, Inc.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Demand-aware mobile bike-sharing service using collaborative computing and information fusion in 5G IoT environment

引用

Digital Communications and Networks 2022年第6期8卷 984-994页

作者： Xiaoxian Yang Yueshen Xu Yishan Zhou Shengli Song Yinchen Wu School of Computer and Information Engineering Shanghai Polytechnic UniversityShanghai201209China School of Computer Science and Technology Xidian UniversityXi'an710126China

Mobile bike-sharing services have been prevalently used in many cities as an important urban commuting service and a promising way to build smart cities,especially in the new era of 5G and Internet-of-Things(IoT)environments.A mobile bike-sharing service makes commuting convenient for people and imparts new vitality to urban transportation *** the real world,the problems of no docks or no bikes at bike-sharing stations often arise because of several inevitable reasons such as the uncertainty of bike *** addition to pure manual rebalancing,in several works,attempts were made to predict the demand for *** this paper,we devised a bike-sharing service with highly accurate demand prediction using collaborative computing and information *** combined the information of bike demands at different time periods and the locations between stations and proposed a dynamical clustering algorithm for station *** carefully analyzed and discovered the group of features that impact the demand of bikes,from historical bike-sharing records and 5G IoT environment *** combined the discovered information and proposed an XGBoost-based regression model to predict the rental and return *** performed sufficient experiments on two real-world *** results confirm that compared to some existing methods,our method produces superior prediction results and performance and improves the availability of bike-sharing service in 5G IoT environments.

关键词： Mobile bike-sharing service Demand prediction Collaborative computing Information fusion 5G IoT

来源：评论

学校读者我要写书评

暂无评论

Global Color-Aware Arbitrary Style Transfer with Discrete Wavelet Transform 20th

Global Color-Aware Arbitrary Style Transfer with Discrete W...

引用

20th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2024

作者： Chen, Bochao Tan, Junhao Li, Xiaoqiang Pei, Songwen School of Computer Engineering and Science Shanghai University Shanghai200444 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

ISBN: (纸本)9789819628292

The purpose of image arbitrary style transfer is to apply a given artistic or photorealistic style to a target content image. While existing methods can effectively transfer style information, the variability in color brightness features between the style and content images can significantly impact the quality of the style transfer. Specifically, traditional arbitrary style transfer relies on an encoder-decoder architecture of spatial-aware neural networks operating in the RGB domain, which typically preserves only local color brightness information and lacks a global color perception compared to the wavelet frequency domain. In this paper, we address the issue of insufficient global color perception in images from the perspective of image enhancement. We propose Global Color-aware Arbitrary Style Transfer with Discrete Wavelet Transform (GCAST), which achieves a balance between the global color characteristics of style images and the local details of content images. Our approach involves an encoder that integrates preliminary feature encoding through cross-layer attention fusion, while the decoder modifies frequency features using a wavelet-based adjustment block. To maintain a balance between content and style in the stylized images, we design a comprehensive loss function that incorporates multiple restoration loss, double style loss, and noise regularization loss. Extensive experiments comparing our method with state-of-the-art techniques demonstrate that our proposed model generates stylized images with superior results in terms of global color perception and human perceptual studies. © IFIP International Federation for Information Processing 2025.

关键词： Decoding

来源：评论

学校读者我要写书评

暂无评论

All-in-one Weather-degraded Image Restoration via Adaptive Degradation-aware Self-prompting Model

引用

IEEE Transactions on Multimedia 2025年 27卷 3343-3355页

作者： Wen, Yuanbo Gao, Tao Li, Ziqi Zhang, Jing Zhang, Kaihao Chen, Ting Chang'an University School of Information Engineering Xi'an China Chang'an University School of Data Science and Artificial Intelligence Xi'an China Australian National University School of Computing CanberraACT Australia Harbin Institute of Technology School of Computer Science and Technology Shenzhen China

Existing approaches for all-in-one weather-degraded image restoration suffer from inefficiencies in leveraging degradation-aware priors, resulting in sub-optimal performance in adapting to different weather conditions. To this end, we develop an adaptive degradation-aware self-prompting model (ADSM) for all-in-one weather-degraded image restoration. Specifically, our model employs the contrastive language-image pre-training model (CLIP) to facilitate the training of our proposed latent prompt generators (LPGs), which represent three types of latent prompts to characterize the degradation type, degradation property and image caption. Moreover, we integrate the acquired degradation-aware prompts into the time embedding of diffusion model to improve degradation perception. Meanwhile, we employ the latent caption prompt to guide the reverse sampling process using the cross-attention mechanism, thereby guiding the accurate image reconstruction. Furthermore, to accelerate the reverse sampling procedure of diffusion model and address the limitations of frequency perception, we introduce a wavelet-oriented noise estimating network (WNE-Net). Extensive experiments conducted on eight publicly available datasets demonstrate the effectiveness of our proposed approach in both task-specific and all-in-one applications. © 1999-2012 IEEE.

关键词： Restoration

来源：评论

学校读者我要写书评

暂无评论

Improving Micro-expression Recognition using Multi-sequence Driven Face Generation

Improving Micro-expression Recognition using Multi-sequence ...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Chen, Yuan Zhong, Chongju Huang, Pinyi Cai, Wangyang Wang, Lei School of Computer Science and Engineering Central South University China School of Computer and Communication Engineering Changsha University of Science and Technology China

ISBN: (纸本)9798350368741

Micro-expression (ME) recognition holds great potential for revealing true human emotions. A significant barrier to effective ME recognition is the lack of sufficient annotated ME video data because MEs are subtle and involuntary facial expressions that are very hard to capture. To address this issue, data augmentation techniques, such as ME migration based on a driven video, have been employed to enrich training samples. Considering that MEs can be complex facial movements involving multiple action unit (AU) changes, we propose a novel ME generation approach that enables the creation of more realistic facial sequences by fusing MEs from multiple videos rather than just single driven video. To enhance the effectiveness of multi-sequence ME transfer, we adapt the thin plate spline motion model and improve traditional face alignment methods to better suit the model, facilitating multi-sequence driven ME generation. In our experiments, we conduct a downstream ME recognition task using models trained on our augmented ME sequences to demonstrate the effectiveness of our approach on the SAMM, SMIC, and CASME II datasets. The results confirm that our proposed approach outperforms state-of-the-art (SOTA) augmentation and generation methods in terms of F1 score and recognition accuracy. © 2025 IEEE.

关键词： face alignment micro-expression generation thin plate spline motion model video fusion

来源：评论

学校读者我要写书评

暂无评论

Improving Security and Performance of Databases Through Single Cache System 4

Improving Security and Performance of Databases Through Sing...

引用

4th International Conference on Blockchain technology and Information Security, ICBCTIS 2024

作者： Ul Haq, Ikram Khan, Salabat Khan, Mansoor Tamsal, Saher School of Computer Science and Technology Southwest University of Science and Technology Mianyang China School of Computer and Information Engineering Qilu Institute of Technology Jinan China School of Intelligent Manufacturing and Control Engineering Qilu Institute of Technology Jinan China University of Agriculture Department of Computer Science Faisalabad Pakistan

ISBN: (纸本)9798331528324

In today's world, connectivity and performance-driven technology are rapidly advancing each year, and new platforms and mechanisms are being utilized to enhance the security and performance of databases and cloud computing, which are trending in the global market. This examination focused on customer information security in cloud computing, i.e., information stockpiling security issues and how to control unapproved access to data by proposing access control;valuable measures were characterized subsequently, and an entrance control show was prescribed. Cloud computing can be described as an innovation that depends on the web and the sharing of resources. It has an adaptable foundation that customers can use with much of a stretch. With its wide event relationship, there are numerous obstacles to continuing with cloud computing because of security issues, mostly considering customer data security. The proposed study helped hesitant clients sensibly continue forward in the cloud while understanding the dangers of cloud computing. The research objective is to examine the security techniques employed in cloud technology to improve its performance by utilizing data mining within a unified cache system. We will apply the Apriori algorithm as a proposed solution to be used in a single cache while considering the security measures in the cloud. The study expects to apply this method to all cloud providers and vendors by entering data into a single cache mechanism that can be extended into different components and implemented using SPSS modelers to improve the security of the database. © 2024 IEEE.

关键词： Cloud security

来源：评论

学校读者我要写书评

暂无评论

UAV Localization with Unreliable Observations in Hostile Underground Environments

引用

Journal of computer Science & technology 2024年第6期39卷 1401-1418页

作者： Peng-Peng Chen Kui-Yuan Zhang Shou-Wan Gao Si-Yi Ren School of Computer Science and Technology China University of Mining and TechnologyXuzhou 221116China Mine Digitization Engineering Research Center Ministry of EducationXuzhou 221116China Shenzhen Research Institute China University of Mining and TechnologyShenzhen 518057China

The accurate and robust unmanned aerial vehicle(UAV)localization is significant due to the requirements of safety-critical monitoring and emergency wireless communication in hostile underground *** range-based localization approaches fundamentally rely on the assumption that the environment is relatively ideal,which enables a precise range for ***,radio propagation in the underground environments may be dramatically influenced by various equipments,obstacles,and ambient *** this case,inaccurate range measurements and intermittent ranging failures inevitably occur,which leads to severe localization performance *** address the challenges,a novel UAV localization scheme is proposed in this paper,which can effectively handle unreliable observations in hostile underground *** first propose an adaptive extended Kalman filter(EKF)based on the fusion of ultra-wideband(UWB)and inertial measurement unit(IMU)to detect and adjust the inaccurate range *** to deal with intermittent ranging failures,we further design the constraint condition by limiting the system ***,the auto-regressive model is proposed to implement the localization in the ranging blind areas by reconstructing the lost ***,extensive simulations have been conducted to verify the *** carry out field experiments in an underground garage and a coal mine based on P440 UWB *** show that the localization accuracy is improved by 16.9%compared with the recent methods in the hostile underground environments.

关键词： unmanned aerial vehicle(UAV)localization Kalman filter ultra-wideband(UWB)observation hostile underground environment

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：