检索结果-内蒙古大学图书馆

1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Gunasundari, R. Balakumar, C. Karpagam Academy of Higher Education Faculty of Arts Commerce Science and Management Department of Computer Applications Tamilnadu Coimbatore India

ISBN: (纸本)9798350359756

Advertising serves as a crucial driver for promoting products and building their brand presence. In contemporary times, online advertising has gained prominence, becoming a burgeoning industry for both product manufacturers and online publishers. Anticipating and catering to user interests and preferences is of paramount importance when determining the types of advertisements to display on a web page to maximize the number of views and clicks. To address this challenge, our research introduces a hybrid model that combines the probabilistic latent class model and a logistic regression classifier. This model operates in two distinct stages. The Probabilistic Latent Class (PLC) model is employed for the initial stage of advertisement viewability prediction. In existing studies, web page attributes, particularly scroll depth and browser behavior, are utilized for this purpose. However, our proposed approach incorporates additional features such as dwell time, scroll depth level, gender, ad type, and viewed status to enhance viewability prediction using the PLC model. In the second stage, we use a Logistic Regression classifier to categorize the gathered ad view data and determine viewability accuracy. The predicted dataset is retrieved from the database and employed for the classification process via Logistic Regression. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Optimizing Railway Traffic management Using Fuzzy Logic-Based Decision-Making Systems 2

Optimizing Railway Traffic Management Using Fuzzy Logic-Base...

引用

2nd International Conference Computational and Characterization Techniques in Engineering and sciences, IC3TES 2024

作者： Kumari, Nalli Vinaya Pradeep Ghantasala, G.S. Sharma R, Rajesh Ananthanagu, U. Vidyullatha, Pellakuri Pandiya, Dileep Kumar Jntuh Malla Reddy Engineering College for Women Department of Computer Science and Engineering Hyderabad India Alliance University Alliance College of Engineering and Design Department of Computer Science and Engineering Bengaluru India Koneru Lakshmaiah Education Foundation Department of Computer Science and Engineering Andhra Pradesh Guntur India Zoominfo Technologies Principl Software Engineer Boston United States

ISBN: (纸本)9798350364699

Railway web page traffic manipulate is a complex and dynamic method that includes making real-time picks based mostly on various uncertain and difficult to understand factors, collectively with fluctuating passenger demand, diverse train schedules, and unpredictable weather conditions. Traditional decision-making strategies often battle to cope with the ones uncertainties, foremost to inefficiencies and potential safety risks. This paper proposes the software program of fuzzy properly judgment-based completely decision-making systems to optimize railway web page traffic manipulate. Fuzzy properly judgment, with its potential to model uncertainty and control difficult to understand data, offers a robust framework for boosting decision-making approaches in railway operations. By simulating various conditions and integrating real-time data, the proposed gadget can dynamically regulate train schedules, manipulate delays, and enhance everyday operational efficiency. The paper may present case studies demonstrating the effectiveness of fuzzy properly judgment in dealing with railway web page traffic, reducing delays, and improving passenger satisfaction. The findings advice that incorporating fuzzy properly judgment into railway web page traffic manipulates systems can purpose greater adaptive and resilient railway operations, ultimately contributing to greater steady and additional reliable rail networks. © 2024 IEEE.

关键词： Efficiency

来源：评论

学校读者我要写书评

暂无评论

Role of cloud computing in management and education

引用

Materials Today: Proceedings 2023年 80卷 3726-3729页

作者： Gupta, Awaneesh Mazumdar, Bireshwar Dass Mishra, Manmohan Shinde, Priyanka P. Srivastava, Surabhi Deepak, A. United Institute of Management Prayagraj India Department of Computer Science &Engineering IERT Prayagraj211002 India Department of Computer Application United Institute of Management Prayagraj211010 India Master of Computer Application Department Government College of Engineering Maharashtra Karad415124 India Koneru Lakshmaiah Education Foundation India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India

In the current day, information and communication technologies are tightly linked to provide ultimate business solutions. Cloud computing is one of these topics that has recently been hotly contested and carefully explored, but still has a lot of room for further research and growth. Technology-assisted learning is becoming more common, with most educational institutions across the globe using learning management systems, content management systems, virtual networks, and virtual machines to enhance student learning. In this day and age, educational institutions are even using private clouds to improve the student experience. Despite the fact that many educational institutions, colleges, and universities have effectively implemented and incorporated instructional technology, many of them still fall short in a variety of areas. The purpose of this research is to investigate the influence of cloud computing technology on educational institutions and corporate management. © 2021

关键词： Cloud computing

来源：评论

学校读者我要写书评

暂无评论

A Wrapping Encryption Based on Double Randomness Mechanism

引用

computers, Materials & Continua 2023年第10期77卷 1143-1164页

作者： Yi-Li Huang Fang-Yie Leu Ruey-Kai Sheu Jung-Chun Liu Chi-Jan Huang Department of Computer Science Tunghai UniversityTaichung40764Taiwan Emergency Response Management Center Ming Chung UniversityTaipei11103Taiwan General Education Center Ming Chuan UniversityTaipei11103Taiwan

Currently,data security mainly relies on password(PW)or system channel key(SKCH)to encrypt data before they are sent,no matter whether in broadband networks,the 5th generation(5G)mobile communications,satellite communications,and so *** these environments,a fixed password or channel key(e.g.,PW/SKCH)is often adopted to encrypt different data,resulting in security risks since thisPW/SKCH may be solved after hackers collect a huge amount of encrypted ***,the most popularly used security mechanism Advanced Encryption Standard(AES)has its own problems,e.g.,several rounds have been *** the other hand,if data protected by the same PW/SKCH at different time points can derive different data encryption parameters,the system’s security level will be then greatly ***,in this study,a security scheme,named Wrapping Encryption Based on Double Randomness Mechanism(WEBDR),is proposed by integrating a password key(or a system channel key)and an Initialization Vector(IV)to generate an Initial Encryption Key(IEK).Also,an Accumulated Shifting Substitution(ASS)function and a three-dimensional encryption method are adopted to produce a set of *** randomness encryption mechanisms are *** first generates system sub-keys and calculates the length of the first pseudo-random numbers by employing IEK for providing subsequent encryption/*** second produces a random encryption key and a sequence of internal feedback codes and computes the length of the second pseudo-random numbers for encrypting delivered messages.A wrapped mechanism is further utilized to pack a ciphertext file so that a wrapped ciphertext file,rather than the ciphertext,will be produced and then transmitted to its *** findings are as *** theoretic analyses and simulations demonstrate that the security of the WEBDR in cloud communication has achieved its practical ***,AES requires 176 times exclusive OR(XOR)operations for both encryption an

关键词： Initial encryption key accumulated shifting substitution three-dimensional operation wrapped ciphertext file

来源：评论

学校读者我要写书评

暂无评论

TCGC: Tweet Classification and Recommendation for Geographical Catastrophes and Events 15th

TCGC: Tweet Classification and Recommendation for Geographic...

引用

15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Aravind Krishnan, A. Deepak, Gerard Santhanavijayan, A. Department of Computer Science and Engineering Manipal Academy of Higher Education Manipal Institute of Technology Bengaluru India Department of Computer Science and Engineering BMS Institute of Technology and Management Karnataka Bengaluru India National Institute of Technology Tiruchirappalli India

ISBN: (纸本)9783031810855

A need for a strategic framework for tweet classification and recommendation has emerged, specifically for geographical catastrophes and events. This paper proposes a semantics-oriented model for disaster tweet classification in which the latent semantic indexing and WikiData are encompassed for topic modelling and auxiliary knowledge addition into the model. Event ontologies highlighting catastrophes also contribute to the information present in the framework. This model encompasses the DT classifier and the transformer classifier in order to classify the dataset and the metadata respectively. The metadata generation also enriches the framework’s knowledge. The framework uses Google’s Knowledge Graph API to generate knowledge graphs and a shuffling agent helps in shuffling the knowledge for diversifying the intermediate solutions. Twitter Semantic Similarity and Adaptive Pointwise Mutual Information (APMI) measures are strong semantics-oriented reasoning models used in the framework for semantic relatedness computation. Animal Migration Optimization which is a metaheuristic optimization framework is also used for the computation of the optimal solution. The paper has a precision of 96.54%, an overall accuracy of 97.02%, and the lowest FDR of 0.04, outperforming all the baseline models considered in this paper. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Knowledge graph

来源：评论

学校读者我要写书评

暂无评论

Novel Double-Damped Tuned AC Filters in HVDC Systems

引用

computers, Materials & Continua 2023年第4期75卷 1467-1482页

作者： Rana Shaheer Mehmood Asif Hussain Usman Ali Muhammad Tariq Mahmood Department of Electrical Engineering University of Management and TechnologyLahore54782Pakistan Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-si16419Gyeonggi-doKorea School of Computer Science and Engineering Korea University of Technology and Education1600ChungjeolnoByeogchunmyunCheonan31253Korea

This paper presents a performance analysis of novel doubledampedtuned alternating current (AC) filters in high voltage direct current(HVDC) systems. The proposed double-damped tuned AC filters offer theadvantages of improved performance of HVDC systems in terms of betterpower quality, high power factor, and lower total harmonic distortion (THD).The system under analysis consists of an 878 km long HVDC transmissionline connecting converter stations at Matiari and Lahore, two major cities inPakistan. The main focus of this research is to design a novel AC filter usingthe equivalent impedance method of two single-tuned and double-dampedtuned AC filters. Additionally, the impact of the damping resistor on the ACchannel is examined. TheTHDof theHVDCsystem with and without currentAC filters was also compared in this research and a double-damped tuned ACfilter was proposed. The results of the simulation represent that the proposeddouble-damped tuned AC filter is far smaller in size, offers better powerquality, and has a much lower THD compared to the AC filters currently inplace in the converter station. The simulation analysis was carried out utilizingpower systems computer-aided design (PSCAD) software.

关键词： Double-damped tuned AC filters harmonics high voltage DC systems long distance transmission power quality total harmonic distortion

来源：评论

学校读者我要写书评

暂无评论

Classification of Unbalanced Data Based on Bayesian Optimal Neural Network Model

Journal of Network Intelligence

引用

Journal of Network Intelligence 2024年第3期9卷 1427-1440页

作者： Ye, Li-Zhu Alkawaz, Mohammed Hazim Johar, Md Gapar Md School of Information Technology and Engineering Guangzhou College of Commerce Guangzhou511363 China School of Graduate Studies Management and Science University 40100 Shah Alam Selangor Malaysia Department of Computer Science College of Education for Pure Science University of Mosul Mosul41002 Iraq Software Engineering and Digital Innovation Center Management and Science University Shah Alam40100 Malaysia

Aiming at the unbalanced problem of big data classification, this paper proposes a classification method of unbalanced data on the ground of Bayesian optimal neural network model. The method firstly uses Optimized Graph Convolutional Network (OGCN) network to carry out message passing mechanism in data graph, designs neural network model with self-attention pooling and mean maximization pooling, and then uses Bayes optimization to update the posterior probability of optimization function by constantly updating the probability model and evaluating the objective function. Effectively solve the problem of speed and optimal solution of hyperparameter optimization in the neural network model. Secondly, the model is used for data set training to obtain the weight of the entire network. Secondly, the unbalanced data is mixed sampling to reduce the number of negative samples. Finally, the capability of the model was verified on the CiteSeer dataset. Experimental results showed that the accuracy rate, accuracy rate and recall rate of the proposed algorithm were 0.974, 0.982 and 0.973, respectively, which effectively improved the accuracy rate, accuracy rate and recall rate of unbalanced data classification compared with other algorithms. © 2024, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Development of Remote Health Monitoring System for Elderly using IoT and WSN 1

Development of Remote Health Monitoring System for Elderly u...

引用

1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Tripathi, Abhishek Sethumadhavan, R. Kiran, Jujaru Sasi Anish, S. Aniankar, Shubham Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamil Nadu India Shri Ramdeobaba College of Engineering and Management Department of Electronics Engineering Nagpur India

ISBN: (纸本)9798350353648

In today's rapidly evolving world, numerous people encounter difficulties in accessing medical services for minor health issues. To tackle this problem, we introduce a robust pulse monitoring system that also checks room temperature and humidity. This system harnesses cutting-edge technology to deliver live health and environmental information directly to medical professionals, allowing them to evaluate a patient's health remotely and offer immediate medical guidance or action. The setup includes essential hardware components like the NodeMCU ESP8266 microcontroller, the DHT11 sensor for temperature and humidity measurement, and a pulse sensor to monitor the patient's heart rate. The data from these sensors is sent to the cloud-based service ThingSpeak using the ThingESP library, making it available for healthcare providers to review and act upon. Moreover, the system incorporates TWILIO, a communication service, to facilitate WhatsApp messaging that alerts healthcare professionals instantly in the event of unusual health or environmental readings. This pioneering approach ensures that individuals can obtain prompt medical support and surveillance from their homes, enhancing proactive health management and ultimately improving health outcomes. © 2024 IEEE.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Implementation of IoT-Enabled Automatic Solar Power Tracking System 1

Implementation of IoT-Enabled Automatic Solar Power Tracking...

引用

1st International Conference on Computing, sciences and Communications, ICCSC 2024

作者： Tripathi, Abhishek Sree, Addepalli Kavya Triveni, Bhimavarapu Rishitha, Alluru Malleswari, Batta Anjankar, Shubham Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamil Nadu India Shri Ramdeobaba College of Engineering and Management Department of Electronics Engineering Nagpur India

ISBN: (纸本)9798350353648

In order to maximize the performance of solar panels, this paper outlines a systematic approach for creating a tracking system for solar power. The solar power tracking system is a hardware/software prototype that helps solar panels automatically align with the sun at the right time to generate the most electricity. Light Dependent Resistor (LDRs) sensors, solar panels, servo motor, and an Arduino UNO microprocessor are the main components included in this system. By increasing their exposure to sunlight throughout the entire day, the system improves the effectiveness and output of solar system. This study describes the solar panels' ability to detect the light and rotate in response to the sun's location. The solar power tracking system prototype has been designated for use in future. In the proposed setup, it is found that at 12:00 noon, the single-axis tracking system achieves approximately 63.64% higher output power efficiency compared to the fixed-tilt system. © 2024 IEEE.

关键词： Servomotors

来源：评论

学校读者我要写书评

暂无评论

Classification of Rice Variant using Deep Learning

Classification of Rice Variant using Deep Learning

引用

2024 IEEE International Conference on Modeling, Simulation and Intelligent Computing, MoSICom 2024

作者： Kumar, K Susheel Verma, Prem Kumari Chaurasia, Subham Singh, Nagendra Pratap Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Department of Information Technology Karnataka Manipal India National Institute of Technology Department of Computer Science and Engineering Punjab Jalandhar India Axis Institute of Technology and Management Department of Computer Science and Engineering Kanpur India

ISBN: (纸本)9798331533311

Rice is a popular crop in the world. This paper has constructed a model using deep Learning for classification. Classification is a critical process in identifying the class of an image. Here, the Rice dataset has been taken to classify the class of rice Breed. Image Classification is a complex process that is affected by various factors. The emphasis is placed on summarizing essential superior class procedures and the strategies used for improving classification accuracy. This paper uses the deep learning approach for classification, such as CNN, and some activation functions, such as ReLu Softmax with Dense layers. The classification process used various domains, such as Machine Learning and deep learning. In this model, five classes of rice breed have been taken and classified with an accuracy of 9 6%. © 2024 IEEE.

关键词： Adversarial machine learning

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：