检索结果-内蒙古大学图书馆

Ultra-small amorphous MoS2 decorated reduced graphene oxide for supercapacitor application

Journal of Materials science & Technology 2020年第5期40卷 196-203页

作者： Poulami Hota Milon Miah Saptasree Bose Diptiman Dinda Uttam K.Ghorai Yan-Kuin Su Shyamal K.Saha Department of Materials Science Indian Association for the Cultivation of ScienceJadavpurKolkata700032India Department of Materials Science and Engineering Seoul National UniversitySeoul151-744Republic of Korea Department of Industrial Chemistry and Applied Chemistry Ramakrishna Mission Vidyamandira and Swami Vivekananda Research CenterBelur MathHowrah711202India Green Energy Technology Research Center Kun Shan UniversityTainanTaiwanChina

Amorphous materials have recently gained much attention as electrode materials in supercapacitor application due to the presence of larger amount active sites which can efficiently increase the storage capacity of the *** engineering is an elegant approach to fully utilize the advantages of the amorphous ***,large surface area and high conductivity of reduced graphene oxide(RGO)can efficiently increase the storage capacity of the *** this idea,in the present work,we have successfully synthesized amorphous MoS2 of two different sizes on reduced graphene oxide and thoroughly investigated the supercapacitor behavior of the *** specific capacitance of the composite structures has been found to be largely increased with decreasing size of the amorphous nano *** specific capacitance of amorphous MoS2-RGO composite containing nearly 50 nm of MoS2 found to be 270 F/g whereas when the particle size is reduced to 5–7 nm,value of specific capacitance increases to 460 F/*** large increase in specific capacitance with the tuning of the size of amorphous nano particle has been explained by the presence of a large number of active sulfur edges of ultra-small MoS2 nano structure along with the better charge transport which can effectively increase the storage capacity of the overall *** retention in the capacitance of the material has been found to be 90%after 5000 cycles.

关键词： Supercapacitor Ultrasmall amorphous MoS2 nanoparticles Sulfur edge sites Reduced graphene oxide(RGO) Specific capacitance

来源：评论

学校读者我要写书评

暂无评论

Smart Seed Classification System based on MobileNetV2 Architecture 2

Smart Seed Classification System based on MobileNetV2 Archit...

引用

2nd International Conference on Computing and Information Technology, ICCIT 2022

作者： Hamid, Yasir Wani, Sharyar Soomro, Arjumand Bano Alwan, Ali A. Gulzar, Yonis Abu Dhabi Polytechnic Information Security and Engineering Technology Abudhabi United Arab Emirates International Islamic University Malaysia Kulliyyah of Information and Communication Technology Department of Computer Science Gombak Malaysia College of Business Administration King Faisal University Department of Management Information Systems Al-Ahsa Saudi Arabia School of Theoretical and Applied Science Ramapo College of New Jersey MahwahNJ United States College of Business Administration King Faisal University Department of Management Information Systems Al-Ahsa Saudi Arabia

ISBN: (纸本)9781665436052

The agricultural transformation in the last decade using artificial intelligence has led to significant gains in productivity and profitability. The traditional machine learning approaches present inherent limitations in extracting features and information from image data. Deep learning techniques, particularly CNN's, help to overcome these limitations due to their multi-level architecture. Various deep learning applications in agriculture include crop disease identification, fruit classification, and germination rate monitoring. Seed image analysis is considered a significant task for the preservation of biodiversity and sustainability. This research uses MobileNetV2, a deep learning convolutional neural network (DCNNs) for seed classification. This model has been preferred due to its simple architecture and memory-efficient characteristics. A total of 14 different classes of seeds were used for the experimentation. The results indicate accuracies of 98% and 95% on training and test sets, respectively. © 2022 IEEE.

关键词： Seed

来源：评论

学校读者我要写书评

暂无评论

Bridging the Artificial Intelligence Knowledge and Skill Gaps in Africa: a Case of the 3rd Google Tensorflow Bootcamp and FEDGEN Mini-Workshop

Bridging the Artificial Intelligence Knowledge and Skill Gap...

引用

science, engineering and Business for Sustainable Development Goals (SEB-SDG), International Conference on

作者： Emmanuel Adetiba John S. Wejin Oluwadamilola Oshin Ayodele H. Ifijeh Comfort Lawal Surendra Colin Thakur Ayokunle A. Awelewa Raymond Jules Kala Priscilla O. Ajayi Matthew B. Akanle Faith O. Sweetwiliams Uche Nnaji Emmanuel Owolabi Olabode Idowu-Bismark Gabriel Sobola Department of Electrical and Information Engineering & Covenant Applied Informatics & Communication African Center of Excellene (CApIC-ACE) Covenant University Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban South Africa Department of Electrical and Information Engineering & CApIC-ACE Covenant University Jalingo Nigeria Department of Computer Science Taraba State University Jalingo Nigeria Department of Electrical and Information Engineering & CApIC-ACE Covenant University Ota Nigeria Department of Information Technology and KZN E-Skills Co-Laboratory Durban University of Technology Durban South Africa Department of Electrical and Information Engineering Covenant University Ota Nigeria International University of Grand Bassam Grand Bassam Ivory Coast Center for Systems and Information Services & CApIC-ACE Covenant University Ota Nigeria Department of Computer and Information Science & CApIC-ACE Covenant University Ota Nigeria Smartyou Integral (PTY) LTD Pretoria Gauteng South Africa

ISBN: (数字)9798350358155

ISBN: (纸本)9798350358162

In transiting from one civilization to another, technology has played a vital and positive role. In the 21 st century, one of the digital developments that is paving ways for human life improvement is machine-assisted technology using Artificial Intelligence (AI). Artificial Intelligence has successfully enhanced man’s capacity in solving complex problems and processes. However, as developed nations continue to reap from the adoption of AI in various fields of human endeavors, the continent of Africa has remained behind, especially in AI-based skills and research. Various governments in developing nations have encouraged the adoption of AI, especially in institutions of learning. However, theoretical adoption without practical experience has remained an ineffective way of bridging the digital divide. In this paper we present the outcome of a practical approach to bridging the AI divide among students and researchers in Africa through funding support from the Google TensorFlow College Outreach Award. A 3-day hybrid bootcamp was organized (11 th to 13 th December, 2023) using the Google funding in order to equip postgraduate students and researchers with AI and collaborative research skills. A pre-survey method was employed to ascertain the knowledge level of the bootcamp participants. From the pre-surveyed feedback, training sessions on various AI domains were presented, and participant equipped with practical AI skills using a deployed AI-based cloud programming platform running on the private Federated Genomic Cloud (FEDGEN) infrastructure at Covenant University. A post-survey feedback was used to ascertain the effectiveness of this approach. A comparative analysis of the pre-survey and post-survey reveals a 70% improvement of AI skills among participants. This shows that having continuous training session for students and researchers is an effective method in closing the AI skills gap between developed and developing nations.

关键词： Training Surveys Knowledge based systems Government Genomics Africa Programming

来源：评论

学校读者我要写书评

暂无评论

Recent Advancements in Vehicle to Vehicle Charging

Recent Advancements in Vehicle to Vehicle Charging

引用

International Conference on Power Electronics and Drive Systems (PEDS)

作者： Anindita Golder Kushan Tharuka Lulbadda Tarlochan Sidhu Sheldon S. Williamson Department of Electrical and Computer Engineering Smart Transportation Electrification and Energy Research (STEER) Group Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Ontario Tech-Automotive Center of Excellence (ACE) Faculty of Engineering and Applied Science Ontario Tech University Oshawa ON Canada

More and more electric vehicles and charging stations are penetrating into the power system today which introduce new challenges. As a result, the concept of vehicle to vehicle charging (V2V) is gaining interest. Therefore, it is important to understand the concept of V2V charging. In this paper, some of the recent developments in the area of vehicle to vehicle (V2V) charging are explored.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Tunable Source of Quantum-Correlated Photons with Integrated Pump Rejection in a Silicon CMOS Platform

Tunable Source of Quantum-Correlated Photons with Integrated...

引用

Frontiers in Optics + Laser science 2021, FiO+LS 2021 - Part of Frontiers in Optics, FiO 2021

作者： Fargas Cabanillas, Josep M. Kramnik, Danielius Ramesh, Anirudh Gentry, Cale M. Stojanović, Vladimir Kumar, Prem Popović, Miloš A. Department of Electrical and Computer Engineering Photonics Center Boston University BostonMA02215 United States Department of Electrical Engineering and Computer Science UC Berkeley BerkeleyCA94720 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Department of Electrical Computer and Energy Engineering University of Colorado BoulderCO80309 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

ISBN: (纸本)9781557528209

A wavelength-tunable, silicon photon-pair source based on spontaneous four-wave mixing, integrated with a pump rejection filter in a single, flip-chip packaged CMOS chip, is demonstrated with a coincidence-to-accidentals ratio of 9.1 with no off-chip pump filtering. Frontiers in Optics / Laser science © Optica Publishing Group 2021.

关键词： CMOS integrated circuits

来源：评论

学校读者我要写书评

暂无评论

Fine-Tuning Optimization of Small Language Models: A Novel Graph-Theoretical Approach for Efficient Prompt engineering

Fine-Tuning Optimization of Small Language Models: A Novel G...

引用

IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Venkata Gadiraju Hao-Yu Tsai Hsiao-Chun Wu Manali Singha C.-H. Scott Huang Guannan Liu Shih Yu Chang Yiyan Wu School of Electrical Engineering and Computer Science Louisiana State University Baton Rouge USA Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan Innovation Center for AI Applications Yuan Ze University Chungli Taiwan Institute for Genomic Medicine (IGM) Nationwide Children’s Hospital Columbus USA Department of Applied Data Science San Jose State University San Jose USA Communications Research Centre Ottawa Canada

ISBN: (数字)9798350364262

ISBN: (纸本)9798350364279

In the realm of fine-tuning pre-trained language models in modern prompt engineering, we introduce a novel graph-theoretical approach to address the resource-intensive challenges to the conventional data fine-tuning methods for prompt engineering. Leveraging semantic and contextual prompt relationships, we propose to form a novel prompt graph, which facilitates a new comprehensive representation of prompt similarities. Building upon this new graph structure, our proposed approach can minimize the training time during the fine-tuning process for small language models by identifying and utilizing cliques corresponding to condensed subsets of highly similar prompts. This new strategic reduction in training data can greatly reduce the training time, particularly for resource-constrained applications in practice. Our proposed new approach leads to a significant reduction in the original prompt-graph order and a more focused and streamlined fine-tuning process. This data-reduction strategy demonstrates the potential to enable finetuning language models for prompt engineering with smaller datasets subject to less computational resource. The real run-time analysis for the training process of a small language model GPT2 have been undertaken to show the advantage of our proposed new approach.

关键词： Training Computational modeling Simulation Semantics Training data Data models Prompt engineering

来源：评论

学校读者我要写书评

暂无评论

Image channel as an input method for deep learning ensemble

Image channel as an input method for deep learning ensemble

引用

2021 International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2021

作者： Javokhir, Musaev Nguyen, Ngoc Thanh Hwang, Dosam Yeungnam University Department of Computer Engineering Gyeongsan Korea Republic of Wroclaw University of Science and Technology Department of Applied Informatics Wroclaw50-570 Poland Faculty of Information Technology Nguyen Tat Thanh University Ho Chi Minh City70000 Viet Nam

ISBN: (纸本)9781665436038

The application of computer vision (CV) in many fields is becoming an important factor in development, and the demand for high accuracy CV products is increasing. Therefore, a new method that ensembles three trained models with the same architecture but different inputs is proposed. Each of the different channels of the images were used as input. The first channel of the image was used in the dataset for the first model, the second channel was used for the second model, and the third channel was used for the third model. The classification probabilities were achieved after training three different models with three channels. The model with the highest accuracy was selected as the main model, and it was added to the classification probabilities of certain classes of the main model. Applying this method to the classification task resulted in 75.45% accuracy, while using the entire image for the model resulted in 70.9% accuracy. The advantage of using this ensemble method is that it can be used simultaneously with other ensemble methods and achieves better results. Dividing an image into three different channels than simply using the entire image helps the model learn the image better. © 2021 IEEE.

关键词： Probability

来源：评论

学校读者我要写书评

暂无评论

Comparing SWIPT Techniques for Zero-Energy RIS

Comparing SWIPT Techniques for Zero-Energy RIS

引用

IEEE International Conference on Communications Workshops, ICC

作者： Dimitrios Tyrovolas Vasilis K. Papanikolaou Sotiris A. Tegos Yue Xiao Panagiotis D. Diamantoulakis Sotiris Ioannidis Christos Liaskos George K. Karagiannidis Dept. of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki Greece Dept. of Electrical and Computer Engineering Technical University of Chania Chania Greece School of Information Science and Technology Southwest Jiaotong University Chengdu China Computer Science Engineering Department University of Ioannina Ioannina and Foundation for Research and Technology Hellas (FORTH) Greece Cyber Security Systems and Applied AI Research Center Lebanese American University (LAU) Lebanon

Providing enhanced quality of service (QoS) to support demanding applications in the most energy-efficient way has been identified as a primary objective of future 6G networks. Towards this direction, the concept of programmable wireless environments (PWEs) has emerged, wherein extremely high QoS can be ensured by controlling the wireless propagation through reconfigurable intelligent surfaces (RIS). To meet the demands of 6G networks in terms of energy efficiency, in this paper, zero-energy RISs (ZERISs) are introduced, which harvest the required amount of energy for their operation and then contribute to the PWE conversion. More specifically, we investigate the performance of a ZERIS-assisted communication system in terms of joint energy-data rate outage probability, which quantifies the trade-off between the harvested energy and information transmission, for three distinct simultaneous wireless information and power transfer (SWIPT) methods are investigated, namely power splitting, time switching, and element splitting. Finally, simulation results validate the derived analysis, leading to useful insights for the ZERIS-assisted network regarding which energy harvesting method achieves better performance in terms of joint energy-data rate outage probability.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Mqtt Routing Optimizing Based Intrusion Detection for Internet of Things Using Hybrid Machine Learning

Mqtt Routing Optimizing Based Intrusion Detection for Intern...

引用

Decision Aid sciences and Application (DASA), International Conference on

作者： Haider K. Hoomod Mohammad Alaa Al-Hamami Aqeel Kamil Kadhim Qutaiba Humadi Mohammed Jolan Rokan Niaf College of Education Mustansiriyah University Baghdad Iraq Department of Management Information Systems Applied Science University Manama Kingdom of Bahrain Computer Techniques Engineering Department Imam Al-Kadhim College Baghdad Iraq College of Nursing University of Baghdad Baghdad Iraq Informatics Institute for Postgraduate Studies University of Information Technology and Communications Baghdad Iraq

ISBN: (数字)9798350369106

ISBN: (纸本)9798350369113

With the advent of the Internet of Things, a world was born in which everything could be uniquely identified and monitored, tracked, and managed by computer programs. Items can self-configure using a predefined communication protocol. Other software programs can be linked to operate together using Message Queue Telemetry Transport Protocol (MQTT) or MQSeries components. Business integration software and middleware are common terms for this category of applications. With its suggested lightweight, easy-to-implement, and lowbandwidth system for billions of smart items, the MQTT protocol offers a wide range of potential applications, including home automation. In order to enhance the power savings in MQservice routing, we presented an intelligent assistant for optimizing routing model. For Internet of Things (IoT) purposes, it introduces an optimal routing model based on optimized hybrid machine learning-based anomaly detection (OHMLA). In order to extend the reach of a network, the offered approach allows Internet of Things devices to make efficient use of energy. To further enhance Intrusion Detection identification and get optimum network selection routes, the moth Salp Swarm technique (SSA) technique is used for the optimized hyperparameters. The model is capable of accurately detecting attacks that result in network congestion, causing delays in connection response and data transfer in IoT network.

关键词： Transport protocols Network intrusion detection Machine learning Routing Data transfer Data models Delays Classification algorithms Internet of Things Intelligent sensors

来源：评论

学校读者我要写书评

暂无评论

A novel binary modified beluga whale optimization algorithm using ring crossover and probabilistic state mutation for enhanced bladder cancer diagnosis

引用

Informatics in Medicine Unlocked 2024年 50卷

作者： Gharaibeh, Hasan Alawad, Noor Aldeen Nasayreh, Ahmad Al Mamlook, Rabia Emhamed Makhadmeh, Sharif Naser Bashkami, Ayah Abualigah, Laith Ezugwu, Absalom E. Computer Science Department Faculty of Information Technology and Computer Sciences Yarmouk University Irbid 21163 Jordan Department of Business Administration Trine University IN United States Department of Mechanical and Industrial Engineering University of Zawia Tripoli Libya Department of Information Technology King Abdullah II School of Information Technology The University of Jordan Amman 11942 Jordan Department Medical Laboratory Sciences – Faculty of Science Al Balqa Applied University Salt 19117 Jordan Department of Cyber Security and Cloud Computing Faculty of Information Technology Applied Science Private University Amman 11937 Jordan Artificial Intelligence and Sensing Technologies (AIST) Research Center University of Tabuk Tabuk 71491 Saudi Arabia Computer Science Department Al al-Bayt University Mafraq 25113 Jordan MEU Research Unit Middle East University Amman 11831 Jordan Applied science research center Applied science private university Amman 11931 Jordan Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India Unit for Data Science and Computing North-West University 11 Hofman Street Potchefstroom 2520 South Africa Artificial Intelligence Research Center (AIRC) College of Engineering and Information Technology Ajman University Ajman P.O. Box 346 United Arab Emirates

Bladder cancer (BC) remains a significant global health challenge, requiring the development of accurate predictive models for diagnosis. In this study, a new Binary Modified White Whale Optimization (B-MBWO) algorithm is proposed to address the BC problem. The proposed method utilizes circular transitivity optimization and the Probabilistic State Mutation Algorithm (PSMA) to enhance its optimization performance. The new method is called the BBWORCPS algorithm. High-dimensional and complex medical datasets pose challenges to the original optimization algorithms in addressing the BC problem, motivating the proposed modifications to the original Beluga Whale Optimization algorithm. These enhancements, including quantum-inspired mutation and circular crossing, aim to improve solution space exploration and enhance the algorithm's effectiveness in handling intricate feature spaces. Through comprehensive experiments on BC datasets, the superiority of the BBWORCPS algorithm in terms of feature selection accuracy and computational efficiency is demonstrated compared to existing optimization methods. The obtained findings suggest that BBWORCPS offers a promising approach for developing more precise and reliable predictive models for bladder cancer analysis. © 2024 The Author(s)

关键词： Binary modified beluga whale optimization Bladder cancer Feature selection Machine learning Predictive modeling

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：