检索结果-内蒙古大学图书馆

3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Yadav, Rakesh Kumar Mahesh, T.R. Kumar, Ajay Jayadurga, R. Vishal, A. Sood, Gourav Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Master of Business Administration Chennai127 India Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350319125

The application of device learning to actual-time data analysis has the potential to revolutionize the way businesses make decisions. With the capacity to procedure big volumes of data fast and correctly, system learning can provide insights that tell strategic decisions at the same time as promoting information-pushed choice making. This evaluation can assist agencies increase efficiency, lower expenses, and create a more aggressive area. By means of leveraging system learning to higher recognize patron behavior, operational operations, and traits in the market, organizations can create proactive procedures to assume customer wishes and capitalize on opportunities. This paper will discover the capacity advantages of making use of device studying to actual-time records analysis and talk how businesses can satisfactory leverage it. The paper can even speak exceptional varieties of device gaining knowledge of strategies and do not forget some problems businesses need to do not forget before integrating system gaining knowledge of into their records evaluation systems. © 2023 IEEE.

关键词： businesses Evaluation exceptional forget records

来源：评论

学校读者我要写书评

暂无评论

Detecting Speech Disfluencies Using Open-Source Tools in Automatic Feedback Systems for Oral Presentation Training 16

Detecting Speech Disfluencies Using Open-Source Tools in Aut...

引用

16th International Conference on computer Supported Education, CSEDU 2024

作者： Mateo, Willy Eras, Leonardo Carvajal, Giancarlo Domínguez, Federico Information Technology Center Escuela Superior Politecnica Del Litoral ESPOL Guayaquil Ecuador Faculty of Electrical and Computer Engineering Escuela Superior Politecnica Del Litoral ESPOL Guayaquil Ecuador

ISBN: (纸本)9789897586972

In the realm of verbal communication, most common non-clinical speech disfluencies are filler words and filled pauses, which pose challenges for effective oral presentations. Yet their detection is no easy task. This article presents the usage of OpenAI’s Whisper for filled pauses and filler words detection in Spanish oral presentations, including on-the-wild usage with undergraduate students. Preliminary results indicate that Whisper demonstrates promise as a valuable tool to identify a substantial amount of filler words and filled pauses. Despite areas of improvement, Whisper serves as a diagnostic tool for assessing disfluences in oral communication. Copyright © 2024 by SCITEPRESS – Science and technology Publications, Lda.

关键词： Fillers

来源：评论

学校读者我要写书评

暂无评论

An Analysis of the Impact of DNS-Based Authentication on Wireless Network Security 1

An Analysis of the Impact of DNS-Based Authentication on Wir...

引用

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

作者： Gawali, Piyush P. Das, Neeraj Rajesh, A. Shukla, Anupam Sohal, Jagmeet Jayadurga, R. Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Master of Business Administration Chennai127 India

ISBN: (纸本)9798350359756

This paper investigates the effect of DNS-primarily based authentication on wireless network safety. DNS-primarily based authentication is used to authenticate consumer credentials on Wi-Fi networks, generally primarily based upon the Dynamic Host Configuration Protocol (DHCP). The research specializes in checking out the authentication system via numerous simulations, reading the performance and security of the authentication manner. Effects from such studies monitor that the usage of DNS-based total authentication can improve the safety of a Wi-Fi community, specifically in mitigating man-in-the-center assaults. In addition, analysis shows that DNS-based authentication concurrently improves network overall performance using reducing the fee of authentication, decreasing latency, and increasing the scalability of the authentication process. This research suggests that universal, DNS-based authentication is a precious tool to enhance the security of Wi-Fi networks. © 2023 IEEE.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Hybridization of Particle Swarm Optimization and Variable Neighborhood Search for Multi-Site Aggregates Production Planning in the Home Textile Industry 9

Hybridization of Particle Swarm Optimization and Variable Ne...

引用

9th IEEE information technology International Seminar, ITIS 2023

作者： Rizki, Agung Mustika Yuliastuti, Gusti Eka Mahmudy, Wayan Firdaus Tama, Ishardita Pambudi Universitas Pembangunan Nasional 'Veteran' Jawa Timur Faculty of Computer Science Surabaya Indonesia Institut Teknologi Adhi Tama Surabaya Faculty Electrical Engineering and Information Technology Surabaya Indonesia Universitas Brawijaya Faculty of Computer Science Malang Indonesia

ISBN: (纸本)9798350306835

Aggregate production planning is an essential stage in the production process by companies because the planning stage will affect the next stage. It will be crucial if the company has several production branch locations or can be referred to as multi-site. The rules that apply and the parameter values for each production branch will undoubtedly be different from other production branches. This raises problems for the company in addition to uncertain consumer demand problems. This problem is quite complicated and very important to solve. The author resolves the problems faced by the company by applying the proposed method, namely the hybridization of Particle Swarm Optimization (PSO) and Variable Neighborhood Search (VNS). The solution generated by the proposed method proved optimum. © 2023 IEEE.

关键词： Aggregates

来源：评论

学校读者我要写书评

暂无评论

Cost-Effective Resource Allocation in Underwater Fibre Optic Networks Using Bandwidth Optimization 15

Cost-Effective Resource Allocation in Underwater Fibre Optic...

引用

15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Singh, Khushboo Singh, Akhilendra Pratap Janakiraman, V. Dhabliya, Dharmesh Rajendran, Naveen Kumar Singh, Jagtej Vivekananda Global University Department of Computer Science & Engineering Jaipur India Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Technology Department of Information Technology Maharashtra Pune India Faculty of Engineering and Technology Department of Aerospace Engineering Karnataka Bangalore India Chitkara University Institute of Engineering and technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India

ISBN: (纸本)9798350370249

Underwater fiber optic networks have become increasingly widespread to facilitate underwater communique. However, due to their high installation and maintenance expenses, laying out green networks that maximize bandwidth usage is essential. This paper proposes a cost-powerful resource allocation method for underwater fiber optic networks using bandwidth optimization strategies. The proposed methodology consists of 3 most important steps: First, it fashions the network's topology with graph-theoretic algorithms, which optimizes the bandwidth usage to maximize hyperlink efficiency. Moreover, it presents methods to evaluate the effectiveness of the generated topology and decide the ideal network allocation based totally on price estimation. Furthermore, heuristic algorithms assign hyperlink weights to minimize the general price. Eventually, the cost-effectiveness of the proposed approach is evaluated by the usage of simulations done on underwater networks with numerous topologies. Results display that the proposed approach achieves widespread price financial savings over conventional methods. Consequently, the proposed technique may be used to successfully allocate assets in underwater fiber-optic networks. © 2024 IEEE.

关键词： Heuristic algorithms

来源：评论

学校读者我要写书评

暂无评论

Deep CNN Model for Multimodal Medical Image Denoising

引用

computers, Materials & Continua 2022年第11期73卷 3795-3814页

作者： Walid El-Shafai Amira A.Mahmoud Anas M.Ali El-Sayed M.El-Rabaie Taha E.Taha Osama F.Zahran Adel S.El-Fishawy Naglaa F.Soliman Amel A.Alhussan Fathi E.Abd El-Samie Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Alexandria Higher Institute of Engineering&Technology(AIET) AlexandriaEgypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadhSaudi Arabia

In the literature,numerous techniques have been employed to decrease noise in medical image modalities,including X-Ray(XR),Ultrasonic(Us),Computed Tomography(CT),Magnetic Resonance Imaging(MRI),and Positron Emission Tomography(PET).These techniques are organized into two main classes:the Multiple Image(MI)and the Single Image(SI)*** the MI techniques,images usually obtained for the same area scanned from different points of view are used.A single image is used in the entire procedure in the SI *** denoising techniques can be carried out both in a transform or spatial *** paper is concerned with single-image noise reduction techniques because we deal with single medical *** most well-known spatial domain noise reduction techniques,including Gaussian filter,Kuan filter,Frost filter,Lee filter,Gabor filter,Median filter,Homomorphic filter,Speckle reducing anisotropic diffusion(SRAD),Nonlocal-Means(NL-Means),and Total Variation(TV),are ***,the transform domain noise reduction techniques,including wavelet-based and Curvelet-based techniques,and some hybridization techniques are ***,a deep(Convolutional Neural Network)CNN-based denoising model is proposed to eliminate Gaussian and Speckle noises in different medical image *** model utilizes the Batch Normalization(BN)and the ReLU as a basic *** a result,it attained a considerable improvement over the traditional *** previously mentioned techniques are evaluated and compared by calculating qualitative visual inspection and quantitative parameters like Peak Signal-to-Noise Ratio(PSNR),Correlation Coefficient(Cr),and system complexity to determine the optimum denoising algorithm to be applied *** on the quality metrics,it is demonstrated that the proposed deep CNN-based denoising model is efficient and has superior denoising performance over the traditionaldenoising techniques.

关键词： Image enhancement medical imaging speckle noise Gaussian noise denoising filters CNN denoising

来源：评论

学校读者我要写书评

暂无评论

Proposed Biometric Security System Based on Deep Learning and Chaos Algorithms

引用

computers, Materials & Continua 2023年第2期74卷 3515-3537页

作者： Iman Almomani Walid El-Shafai Aala AlKhayer Albandari Alsumayt Sumayh S.Aljameel Khalid Alissa Security Engineering Lab Computer Science DepartmentPrince Sultan UniversityRiyadh11586Saudi Arabia Computer Science Department King Abdullah II School of Information TechnologyThe University of Jordan11942Jordan Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Computer Science Department Applied CollegeImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Computer Science Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia SAUDI ARAMCO Cybersecurity Chair Networks and Communications DepartmentCollege of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia

Nowadays,there is tremendous growth in biometric authentication and cybersecurity ***,the efficient way of storing and securing personal biometric patterns is mandatory in most governmental and private ***,designing and implementing robust security algorithms for users’biometrics is still a hot research area to be *** work presents a powerful biometric security system(BSS)to protect different biometric modalities such as faces,iris,and *** proposed BSSmodel is based on hybridizing auto-encoder(AE)network and a chaos-based ciphering algorithm to cipher the details of the stored biometric patterns and ensures their *** employed AE network is unsupervised deep learning(DL)structure used in the proposed BSS model to extract main biometric *** obtained features are utilized to generate two random chaos *** first random chaos matrix is used to permute the pixels of biometric *** contrast,the second random matrix is used to further cipher and confuse the resulting permuted biometric pixels using a two-dimensional(2D)chaotic logisticmap(CLM)*** assess the efficiency of the proposed BSS,(1)different standardized color and grayscale images of the examined fingerprint,faces,and iris biometrics were used(2)comprehensive security and recognition evaluation metrics were *** assessment results have proven the authentication and robustness superiority of the proposed BSSmodel compared to other existing *** example,the proposed BSS succeeds in getting a high area under the receiver operating characteristic(AROC)value that reached 99.97%and low rates of 0.00137,0.00148,and 3516 CMC,2023,vol.74,no.20.00157 for equal error rate(EER),false reject rate(FRR),and a false accept rate(FAR),respectively.

关键词： Biometric security deep learning AE network 2D CLM cybersecurity and authentication applications feature extraction unsupervised learning

来源：评论

学校读者我要写书评

暂无评论

Performance enhancement of text-independent speaker recognition in noisy and reverberation conditions using Radon transform with deep learning

引用

International Journal of Speech technology 2022年第3期25卷 679-687页

作者： El-Moneim, Samia Abd El-Mordy, Eman Abd Nassar, M.A. Dessouky, Moawad I. Ismail, Nabil A. El-Fishawy, Adel S. El-Dolil, Sami El-Dokany, Ibrahim M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt High Institute of Engineering and Technology Tanta Egypt Department of Computer Science and Engineering Faculty of Electronic Engineering Menoufia University Menouf 32952 Egypt Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Automatic Speaker Recognition (ASR) in mismatched conditions is a challenging task, since robust feature extraction and classification techniques are required. Long Short-Term Memory Recurrent Neural Network (LSTM-RNN) is an efficient network that can learn to recognize speakers, text-independently, when the recording circumstances are similar. Unfortunately, when the recording circumstances differ, its performance degrades. In this paper, Radon projection of the spectrograms of speech signals is implemented to get the features, since Radon Transform (RT) has less sensitivity to noise and reverberation conditions. The Radon projection is implemented on the spectrograms of speech signals, and then 2-D Discrete Cosine Transform (DCT) is computed. This technique improves the system recognition accuracy, text-independently with less sensitivity to noise and reverberation effects. The ASR system performance with the proposed features is compared to that of the system that depends on Mel Frequency Cepstral Coefficients (MFCCs) and spectrum features. For noisy utterances at 25 dB, the recognition rate with the proposed feature reaches 80%, while it is 27% and 28% with MFCCs and spectrum, respectively. For reverberant speech, the recognition rate reaches 80.67% with the proposed features, while it reaches 54% and 62.67% with the MFCCs and spectrum, respectively. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

ChatGPT, Copilot, Gemini, SciSpace and Wolfram versus higher education assessments: an updated multi-institutional study of the academic integrity impacts of Generative Artificial Intelligence (GenAI) on assessment, teaching and learning in engineering

引用

Australasian Journal of engineering Education 2024年第2期29卷 126-153页

作者： Nikolic, Sasha Sandison, Carolyn Haque, Rezwanul Daniel, Scott Grundy, Sarah Belkina, Marina Lyden, Sarah Hassan, Ghulam M. Neal, Peter Faculty of Engineering and Information Sciences University of Wollongong Wollongong Australia School of Science Technology and Engineering University of the Sunshine Coast Sippy Downs Australia School of Professional Practice & Leadership University of Technology Sydney Sydney Australia School of Chemical Engineering University of New South Wales Sydney Australia College Western Sydney University Sydney Australia School of Engineering University of Tasmania Hobart Australia School of Computer Science & Software Engineering University of Western Australia Perth Australia

More than a year has passed since reports of ChatGPT-3.5’s capability to pass exams sent shockwaves through education circles. These initial concerns led to a multi-institutional and multi-disciplinary study to assess the performance of Generative Artificial Intelligence (GenAI) against assessment tasks used across 10 engineering subjects, showcasing the capability of GenAI. Assessment types included online quiz, numerical, oral, visual, programming and writing (experimentation, project, reflection and critical thinking, and research). Twelve months later, the study was repeated using new and updated tools ChatGPT-4, Copilot, Gemini, SciSpace and Wolfram. The updated study investigated the performance and capability differences, identifying the best tool for each assessment type. The findings show that increased performance and features can only heighten academic integrity concerns. While cheating concerns are central, opportunities to integrate GenAI to enhance teaching and learning are possible. While each GenAI tool had specific strengths and weaknesses, ChatGPT-4 was well-rounded. A GenAI Assessment Security and Opportunity Matrix is presented to provide the community practical guidance on managing assessment integrity risks and integration opportunities to enhance learning. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

Revolutionizing Waste Management: Harnessing the Power of IoT 7

Revolutionizing Waste Management: Harnessing the Power of Io...

引用

7th IET Smart Cities Symposium, SCS 2023

作者： Karale, Ankita Rajawat, Anand Singh Goyal, S.B. Computer Engineering Sandip Foundation’s Sandip Institute of Research Center Nashik School of Computer Science & Engineering Sandip University Nashik India Faculty of Information Technology City University Petaling Jaya Malaysia

ISBN: (纸本)9781839539831

Waste management has become a pressing problem in a world that is becoming more and more urbanised. Traditional ways of dealing with trash are usually inefficient and bad, leading to pollution, health problems, and wasted resources. As an answer to these problems, the Internet of Things (IoT) has changed the way trash is handled in a big way. This abstract looks at how smart waste management based on the Internet of Things could totally change the business of garbage disposal. Through a network of sensors and devices, the Internet of Things (IoT) connects trash cans, garbage trucks, and waste processing facilities so that they can be monitored and improved in real time. A smart waste management system that is built on IoT has many benefits. With the real-time information it gives about how much trash is being made, routes for collecting trash can be made more efficient in terms of time and fuel use. This cuts down on the number of times trash needs to be picked up, reduces the amount of greenhouse gases released, and saves money. Sensors in trash cans can also find dangerous or flammable items, so they can be dealt with right away and any problems can be avoided. Also, the Internet of Things makes it possible for predictive analytics, which help waste management officials predict how much trash will be made and use their resources well. Using smart waste sorting methods like optical sensors and machine learning algorithms, recyclable and non-recyclable trash can be correctly found and sorted. This helps people recycle more and puts less pressure on landfills. Smart trash management systems that are based on the Internet of Things (IoT) get more people involved and help them understand. Mobile apps and smart devices can tell a person when their trash will be picked up, where the nearest recycling sites are, and how much trash they make. People are encouraged to act responsibly and throw away trash in ways that are good for the environment. Smart waste management base

关键词： Internet of things

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：