检索结果-内蒙古大学图书馆

International Conference on Fractional Differentiation and Its Applications (ICFDA)

作者： Suzan J. Obaiys Rabha W. Ibrahim Department of Computer System & Technology Faculty of Computer Science and Information Technology University of Malaya KL Malaysia Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon

The fractional k-symbol Raina function (k-FRF) is convoluted with a class of analytic functions in a complex domain to build a new fractional integral operator (FIO) in this attempt. We research the polynomials produced by the suggested FIO in terms of their geometry and stability. On the basis of the Hadamard product’s characteristics, sufficient criteria are shown (convolution product).

关键词：

来源：评论

学校读者我要写书评

暂无评论

Natural Language Processing Studies in Humancomputer Interaction: A Bibliometric Analysis and Future Research Framework

Natural Language Processing Studies in HumanComputer Interac...

引用

Student Conference on Research and Development (SCOReD)

作者： Farah Syazwani Binti Mohd Rashid Amirrudin Bin Kamsin Nurul Fazmidar Binti Mohd Noor Department of Computer System Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia College of Computing Informatics and Mathematics Universiti Teknologi MARA Shah Alam Selangor Malaysia

ISBN: (数字)9798331510077

ISBN: (纸本)9798331510084

This study conducts a bibliometric analysis of Natural Language Processing (NLP) within Human-computer Interaction (HCI) to identify trends, challenges, and future directions. Analyzing 1,710 SCOPUS-indexed documents (1983-2024) using a PRISMA flowchart, the results show that the United States and China are leading contributors. Key developments include emotion recognition, chatbot interfaces, and speech processing, highlighting NLP’s role in user-centered technologies. Despite growing applications, challenges such as reliability and ethical concerns persist. This analysis emphasizes the need for ethical frameworks and technological advancements to address deployment issues and align NLP innovations with the United Nations Sustainable Development Goals (SDGs). By mapping global research trends, this study provides insights into the transformative potential of NLP in HCI for developing inclusive and responsive systems.

关键词： Ethics Technological innovation Flowcharts Emotion recognition Bibliometrics Market research Reliability Sustainable development Speech processing Research and development

来源：评论

学校读者我要写书评

暂无评论

Harnessing The Power of Random Forest in Predicting Startup Partnership Success 8

Harnessing The Power of Random Forest in Predicting Startup ...

引用

8th International Conference on Informatics and Computing, ICIC 2023

作者： Lukita, Chandra Lutfiani, Ninda Panjaitan, Arop Ria Saulina Bhima Rahardja, Untung Huzaifah, Muhamad Lutfi University of Catur Insan Cendekia Faculty of Information Systems Cirebon Indonesia University of Raharja Faculty of Economics and Business Tangerang Indonesia University of Esa Unggul Faculty of Management Jakarta Indonesia University of Raharja Faculty of System Computer Tangerang Indonesia University of Raharja Faculty of Information Technology Tangerang Indonesia

ISBN: (纸本)9798350342604

Startups are an important element in innovation and economic growth. However, startup failure is very high, so investors, governments, and startups need to predict startup success. This research develops a startup success prediction model based on random forest with multi-layer decision analytics attributes, partnership longevity predictions, importance feature ranking, cross-industry startup evaluations, and ensemble learning benefits. This research uses secondary data from Crunchbase, AngelList, and VentureBeat. The data is processed with data cleaning, feature engineering, and feature selection. The data is divided into training data and testing data with a ratio of 80:20. The training data trains a random forest model with sci-kit-learn in Python. The model is evaluated by accuracy, precision, recall, F1-score, and ROC-AUC. The testing data tested the random forest model and compared it with other models. This study also used SmartPLS to test hypotheses in a variance-based SEM model with PLS path modelling. This study used 370 respondent data for SmartPLS with SmartPLS software. The results show that the random forest model is better than other models in predicting startup success. The model provides information about important features in predicting startup success. SmartPLS results show that all hypotheses are accepted with statistical significance. The model has high explanatory power and predictive power. © 2023 IEEE.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Disentangle Nighttime Lens Flares: Self-supervised Generation-based Lens Flare Removal 39

Disentangle Nighttime Lens Flares: Self-supervised Generatio...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： He, Yuwen Wang, Wei Wu, Wanyu Jiang, Kui Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology China School of Computer Science and Technology Harbin Institute of Technology China

ISBN: (纸本)157735897X

Lens flares arise from light reflection and refraction within sensor arrays, whose diverse types include glow, veiling glare, reflective flare and so on. Existing methods are specialized for one specific type only, and overlook the simultaneous occurrence of multiple typed lens flares, which is common in the real-world, e.g. coexistence of glow and displacement reflections from the same light source. These co-occurring lens flares cannot be effectively resolved by the simple combination of individual flare removal methods, since these coexisting flares originates from the same light source and are generated simultaneously within the same sensor array, exhibit a complex interdependence rather than simple additive relation. To model this interdependent flares’ relationship, our Nighttime Lens Flare Formation model is the first attempt to learn the intrinsic physical relationship between flares on the imaging plane. Building on this physical model, we introduce a solution to this joint flare removal task named Self-supervised Generation-based Lens Flare Removal Network (SGLFR-Net), which is self-supervised without pre-training. Specifically, the nighttime glow is detangled in PSF Rendering Network(PSFR-Net) based on PSF Rendering Prior, while the reflective flare is modelled in Texture Prior Based Reflection Flare Removal Network (TPRR-Net). Empirical evaluations demonstrate the effectiveness of the proposed method in both joint and individual glare removal tasks. © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Luminescent devices

来源：评论

学校读者我要写书评

暂无评论

Machine Learning for Intrusion Detection in Vehicular Ad-hoc Networks (VANETs): A Survey

Machine Learning for Intrusion Detection in Vehicular Ad-hoc...

引用

Emerging Smart Technologies and Applications (eSmarTA), International Conference on

作者： Nesmah A. Al-Khulaidi Ammar T. Zahary Asma A. Al-Shargabi Muneer A. S Hazaa Department of Computer Networks Yemen Academy for Graduate Studies Sana'a Yemen Department of Computer Science Faculty of Computing and IT University of Science and Technology Sana'a Yemen Department of Information Technology College of Computer Qassim University Buraydah Saudi Arabia Department of Computer Science Faculty of Computer and Information System Thamar University Thamar Yemen

ISBN: (数字)9798350354133

ISBN: (纸本)9798350354140

Intrusion Detection systems (IDSs) have become a key security problem due to the increasing number of connected automobiles and the sensitive nature of the data transferred in Vehicular Ad-hoc Networks (VANETs). By keeping an eye on network traffic, spotting questionable activity, and putting countermeasures in place to lessen risks, IDSs protect the integrity and security of VANETs. For VANETs, this study explores the state-of-the-art in machine learning-based IDSs, with a particular emphasis on work released in 2020–2022. We provide a thorough analysis of developments in widely used machine learning methods used for VANET intrusion detection throughout this time. This investigation explores certain machine learning methods that have been recently applied to VANET IDSs. The survey ends with a summary of the current issues and an exploration of potential directions for further investigation.

关键词： Surveys Machine learning algorithms Intrusion detection Vehicular ad hoc networks Machine learning Telecommunication traffic Safety

来源：评论

学校读者我要写书评

暂无评论

An Efficient Hybrid PAPR Reduction for 5G NOMA-FBMC Waveforms

引用

computers, Materials & Continua 2021年第12期69卷 2967-2981页

作者： Arun Kumar Sivabalan Ambigapathy Mehedi Masud Emad Sami Jaha Sumit Chakravarty Kanchan Sengar Department of Electronics and Communication Engineering JECRC UniversityJaipur303905India Center for System Design Chennai Institute of TechnologyIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Electrical and Computer Engineering Kennesaw State UniversityGAUSA

The article introduces Non-Orthogonal Multiple Access(NOMA)and Filter Bank Multicarrier(FBMC),known as hybrid waveform(NOMAFBMC),as two of the most deserving contenders for fifth-generation(5G)*** spectrum access and clampdown of spectrum outflow are unique characteristics of hybrid *** compare the spectral efficiency of Orthogonal Frequency Division Multiplexing(OFDM),FBMC,NOMA,and *** is seen that the hybrid waveform outperforms the existing *** to Average Power Ratio(PAPR)is regarded as a significant issue in multicarrier *** combination of Selective Mapping-Partial Transmit Sequence(SLM-PTS)is an effective way to minimize large peak power *** SLM,PTS,and SLM-PTS procedures are applied to the NOMA-FBMC *** hybrid structure is applied to the existing ***,the correlated factors like Bit Error Rate(BER)and Computational Overhead(CO)are studied and computed for these *** outcome of the work reveals that the NOMA-FBMC waveform coupled with the SLM-PTS algorithm offers superior performance as compared to the prevailing systems.

关键词： 5G NOMA-FBMC SLM-PTS PAPR BER OFDM

来源：评论

学校读者我要写书评

暂无评论

Congestion Control Mechanisms and Techniques in computer Network: A Review

Congestion Control Mechanisms and Techniques in Computer Net...

引用

Data Science and Intelligent Computing (ICDSIC), International Conference on

作者： Ahmed Malik Altameemi Khulood A. Nassar Department of Computer Information System College of Computer Science and Information Technology University of Basrah Basrah Iraq

One of the most important and most pioneering topics in the field of networks is congestion and how to control it or avoid its occurrence because this topic has a huge impact on the network and the quality of service (QoS). Congestion reduces the efficiency of the network and stops the service in many cases. Therefore, there is an urgent need to develop techniques and mechanisms to avoid congestion or reduce its impact to the extent possible to maintain the permanence of data flow in the network. Congestion is avoided at two levels, node and link, by using different techniques, including closed loop or open loop. This paper reviews an explanation of congestion, how it occurs, and its impact on the network, and then shows the mechanisms through which congestion eliminated can be bed or avoided before it occurs. It also reviews a set of algorithms previously used by researchers in various types of networks and compares the performance between them.

关键词： Measurement Fault tolerance Power demand Costs Fault tolerant systems Quality of service Data science

来源：评论

学校读者我要写书评

暂无评论

A belief rule-based fault diagnosis method for Multi-UAVs under missing attribute data

A belief rule-based fault diagnosis method for Multi-UAVs un...

引用

2023 International Conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Zhao, ErKai Hao, MingRui Yang, RuoHan Yue, KeYuan Yu, DeLin Harbin Normal University School of Computer Science and Information Engineering Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Northwestern Polytechnical University School of Electronics and Information Xi'an China Northwestern Polytechnical University School of Mathematics and Statistics Xi'an China

ISBN: (纸本)9798350312492

To reasonably improve the missing attribute data and effectively integrate sample data and uncertain expert knowledge, this paper proposes a new fault diagnosis method based on a belief rule base (BRB). In the case of missing attribute data, the maximum likelihood estimation (MLE) method is used to complete the missing attribute data, and the fault diagnosis method of the multi-UAVs is constructed by using other complete attribute data as the input information of BRB. Finally, the effectiveness of the proposed method is verified by experimental simulation. © 2023 IEEE.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

Few-Shot Gearbox Fault Diagnosis Based on Semi-Supervised Prototypical Network and Contrastive Learning

Few-Shot Gearbox Fault Diagnosis Based on Semi-Supervised Pr...

引用

2023 China Automation Congress, CAC 2023

作者： Cheng, Shulie Liang, Yingjie Ping, Zuowei Liao, Xuechao Wang, Maolin Zhang, Yong School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China Naval University of Engineering National Key Laboratory of Science and Technology on Vessel Integrated Power System Wuhan China School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350303759

Due to the scarcity of labeled faulty data in industrial practice, fault diagnosis models often face challenges related to overfitting and limited accuracy. This article introduces a novel solution to tackle the problem - a fault diagnosis method that leverages a combination of a semi-supervised prototype network and contrastive learning. Firstly, a limited number of labeled samples is employed to construct pairs of positive and negative samples. And the training method of contrastive learning is used to provide appropriate initial parameters for the autoencoder. Secondly, the autoencoder is employed as a feature mapping function within the prototype network and obtains the prototype using a limited number of labeled samples. Finally, a prototype refinement method fine-tunes the prototype through unlabeled data, reducing the impact of anomalous data and obtaining a more stable and accurate prototype. The effectiveness of the proposed method is evaluated using gearbox data as a validation dataset. Through comparative analysis with other methods, the results demonstrate that the proposed approach achieves superior diagnostic accuracy. © 2023 IEEE.

关键词： Failure analysis

来源：评论

学校读者我要写书评

暂无评论

Automated Software Vulnerability Detection via Curriculum Learning

Automated Software Vulnerability Detection via Curriculum Le...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Qianjin Du Wei Kun Xiaohui Kuang Xiang Li Gang Zhao Department of Computer Science and Technology Tsinghua University China National Key Laboratory of Science and Technology on Information System Security China

With the development of deep learning, software vulnerability detection methods based on deep learning have achieved great success, which outperform traditional methods in efficiency and precision. At the training stage, all training samples are treated equally and presented in random order. However, in software vulnerability detection tasks, the detection difficulties of different samples vary greatly. Similar to the human learning mechanism following an easy-to-difficult curriculum learning procedure, vulnerability detection models can also benefit from the easy-to-hard curriculums. Motivated by this observation, we introduce curriculum learning for automated software vulnerability detection, which is capable of arranging easy-to-difficult training samples to learn better detection models without any human intervention. Experimental results show that our method achieves obvious performance improvements compared to baseline models.

关键词：

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：