检索结果-内蒙古大学图书馆

Electronics and Renewable Systems (ICEARS), International Conference on

作者： Patrick D. Cerna Charisma S. Ututalum Ryan S. Evangelista Aldaruhz T. Darkis Masnona Sabdani Asiri Jehana A. Muallam-Darkis Northern Negros State College of Science and Technology Sagay City Philippines CESE SUC President II Sulu State College Sulu Philippines Graduate School / Institute of Technology PolyTechnic University of the Philippines School of Computer Studies and Engineering Sulu State College Sulu Philippines School of Graduate Studies Sulu State College Sulu Philippines

Early communication among infants is very helpful especially on the growth and mental ability of the child. Infants' early communication, as they have limited verbal skills and may struggle to communicate their needs and feelings effectively to their caregivers. While sign language has been shown to be an effective way to bridge this communication gap, caregivers may not have the necessary skills or knowledge to understand or teach signs to their infants. To address this problem, this research aims to develop and evaluate an automated sign language recognition system that can enhance early communication between infants and caregivers, thus improving infants' overall language development and quality of life. Using the internet of things and the models of machine learning algorithms for early recognition of sign language gesture results better understanding of mental acquisition of infants. This research explores the feasibility of using an Internet of Things (IoT) device, specifically a Raspberry Pi, combined with deep learning techniques to recognize baby sign language. The study uses a deep learning model to recognize sign language gestures and evaluates the impact of various variables, such as lighting conditions and background, on the accuracy of the model. The results demonstrate that the system is capable of accurately recognizing baby sign language gestures with an overall accuracy of 94.6%. This research has important implications for early intervention for hearing-impaired infants, as it allows for real-time monitoring and tracking of a baby’s development of sign language skills. The study recommends further exploration of using IoT devices and deep learning techniques for recognizing and monitoring baby sign language, as well as potential applications for assistive technologies and other areas of human communication.

关键词： Deep learning Pediatrics Renewable energy sources Machine learning algorithms Lighting Gesture recognition Assistive technologies

来源：评论

学校读者我要写书评

暂无评论

AI-driven Gene Expression Analysis on HPC Platforms: Challenges and Solutions

AI-driven Gene Expression Analysis on HPC Platforms: Challen...

引用

International Conference on Contemporary Computing and Informatics (IC3I)

作者： V.S Anusuya Devi N. Sreevani Amandeep Nagpal Susmita Kalyani K.Pushpa Rani Ali Albawi Departmento of Applied Sciences New Horizon College of Engineering Bangalore India Department of CSE(Cyber Security) Institute of Aeronautical Engineering Dundigal Hyderabad India Lovely Professional University Phagwara India Lloyd Law College Plot No. 11 Knowledge Park II Greater Noida Uttar Pradesh Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

HPC technology’s rapid rise has simplified gene expression research. A study proposes AI-GEM, which stands for “AI-Driven Gene Expression on High-Performance Computing Platforms.” We devised an approach to circumvent the issues associated with gene expression studies. We provide a full gene expression research strategy to improve accuracy, scalability, and comprehension. AI-GEM examined six methods: GEA-HPC, Expression AI, Genomic Solver, HPC-GENE, Bio AI-Express, and Gene Xcel. All approaches were tested. The findings suggest that AI-GEM outperforms other approaches. Our new approach averages 10.8 seconds, whereas the previous one took 45.7 seconds. The previous way is faster. AI-GEM is 95.2% accurate. This approach is far more accurate than the standard $\mathbf{7 1. 2 \%}$. This differs greatly from proper procedures. AI-GEM has far more potential than prior approaches, which could only handle 20,850 genes. AI-GEM outperforms other gene expression approaches in interpretability ($\mathbf{9. 2} \mathbf{v s}$. 4.4). One other reason: AI-GEM works better than conventional approaches. The AI-GEM system achieves $\mathbf{9 3 \%}$ client privacy, whereas traditional approaches obtain 58%. AI-GEM uses computer resources well, scoring $\mathbf{8 5 \%}$ vs. $\mathbf{6 6 \%}$ for other approaches. The final preprocessing time for AI-GEM is under 3.2 seconds. The previous best was 13.4 seconds, a significant improvement. AI-GEM is a novel gene expression data analysis tool for powerful computers. AI-GEM is a novel gene expression data analysis tool that is faster, more accurate, more scalable, simpler to comprehend, better at preserving privacy, more efficient in using resources, and reduces difficulties in pre-processing chores. This technology might aid biology and genetics in many ways.

关键词： Privacy Accuracy Data analysis Scalability Genomics Transforms Gene expression Reliability Bioinformatics Standards

来源：评论

学校读者我要写书评

暂无评论

Innovative Strategies for Ensuring Data Protection and Maintaining Integrity in Digital Systems

Innovative Strategies for Ensuring Data Protection and Maint...

引用

International Conference on Contemporary Computing and Informatics (IC3I)

作者： Shiva Prakash Yagateela Pandu Rangaiah Amandeep Nagpal Garima Bhardwaj T Mounika Saurabh Sharma Department of Mechanical Engineeering New Horizon College of Engineering Bangalore India Department of Electronics and Communication Enfineering Institute of Aeronautical Engineering Dundigal Hyderabad India Lovely Professional University Phagwara India Amity Business School Amity University Greater Noida India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Lloyd Law College Plot No. 11 Knowledge Park II Greater Noida Uttar Pradesh India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Data security is difficult in the ever-changing digital world. Existing techniques may not provide comprehensive security, real-time hazard monitoring, and usercentred access management. Our response must be forceful and adaptable. The study led to the development of a five-part data safety technique. AEA, DTD, SIM, UCAC, and AAP are all part of this organisation. AAP makes identification fast and secure; AEA protects data; DTD detects hazards in real time; SIM tests security on a broad scale; and UCAC regulates access. Ablation can reveal systemic roles. New methods outperformed previous ones in some key aspects. Visual tools emphasise privacy, freedom, user experience, and connection to aid decisionmaking. In ever-changing digital situations, one may employ a powerful and adaptable data security solution.

关键词： Visualization Privacy Law Scalability User experience Real-time systems Hazards Threat assessment Informatics Monitoring

来源：评论

学校读者我要写书评

暂无评论

A review of Communication and Data Networks Algorithms Shaping Modem Connectivity

A review of Communication and Data Networks Algorithms Shapi...

引用

International Conference on Contemporary Computing and Informatics (IC3I)

作者： Mk Srinath Anitha Gatla Sorabh Lakhanpal Saurabh Sharma B.Ravali Reddy Taqi Mohammed Khattab Al-Rubaye Department of Mechanical Engineering New Horizon College of Engineering Bangalore India Department of Information Technology Institute of Aeronautical Engineering Dundigal Hyderabad India Lovely Professional University Phagwara India Lloyd Law College Plot No. 11 Knowledge Park II Greater Noida Uttar Pradesh Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Department of Medical Laboratory Technology College of Medical Technologies The Islamic University Najaf Iraq

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

The world of today is highly interconnected and undergoes rapid changes. Algorithms are essential for data networks and communication systems. This study looks at how the complexity of algorithms affects network design. It focusses on the GROA (Global Routing Optimisation Algorithm), LBEA (Load Balancing and Efficient Allocation), and QKD-NS systems in particular. We aim to educate individuals on the impact of various methods on security, route completion time, and resource constraints. Based on the results, GROA creates variable paths, QKD-NS boosts safety with quantum-based innovations, and LBEA efficiently divides up resources based on what the network requires. According to the study, putting these many technologies together could lead to strong partnerships that can handle security breaches, traffic jams, and changes in the network. This study focusses on how advances in technology have led to better computer design, which in turn has made the internet safer and easier to use. The paper elucidates the application of these novel mathematical discoveries to enhance the performance and durability of data networks. These new details help communication networks improve by ensuring that they are safe and can meet today’s link standards.

关键词： Technological innovation Reviews Heuristic algorithms Telecommunication traffic Routing Load management Safety Communication networks Time factors Standards

来源：评论

学校读者我要写书评

暂无评论

Effective Khovanskii, Ehrhart Polytopes, and the Erdős Multiplication Table Problem

arXiv

引用

arXiv 2025年

作者： Limbach, Anna M. Scheidweiler, Robert Triesch, Eberhard Institute of Computer Science Czech Academy of Sciences Pod Vodárenskou věží 271/2 Praha 8182 00 Czech Republic Faculty of Electrical Engineering & Information Technology Hochschule Düsseldorf - University of Applied Sciences Münsterstraße 156 Düsseldorf40476 Germany Lehrstuhl II für Mathematik RWTH Aachen University Pontdriesch 10-12 Aachen52062 Germany

Let P (k, n) be the set of products of k factors from the set {1, . . ., n}. In 1955, Erdős posed the problem of determining the order of magnitude of |P (2, n)| and proved that |P (2, n)| = o(n2) for n → ∞. In 2015, Darda and Hujdurović asked whether, for each fixed n, |P (k, n)| is a polynomial in k of degree π(n) - the number of primes not larger than n. Recently, Granville, Smith and Walker published an effective version of Khovanskii’s Theorem. We apply this new result to show, that for each integer n, there is a polynomial qn of degree π(n) such that |P (k, n)| = qn(k) for each k ≥ n2 ·[Equation presented]− n + 1. Moreover, we give an upper estimate of the leading coefficient of qn © 2025, CC BY-NC-SA.

关键词： Choquet integral

来源：评论

学校读者我要写书评

暂无评论

Blockchain and Machine Learning for Optimized Resource Allocation in Cloud Computing Services

Blockchain and Machine Learning for Optimized Resource Alloc...

引用

International Conference on Contemporary Computing and Informatics (IC3I)

作者： Yagateela Pandu Rangaiah Hanamant Yaragudri K.Pushpa Rani Navdeep Singh Ali Albawi Susmita Kalyani Department of Electronics and Communication Enfineering Institute of Aeronautical Engineering Dundigal Hyderabad India Department of Mechanical Engineering New Horizon College of Engineering Bangalore India Department of Computer Science and Engineering MLR Institute of Technology Hyderabad Telangana India Lovely Professional University Phagwara India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Lloyd Law College Plot No. 11 Knowledge Park II Greater Noida Uttar Pradesh

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Resource efficiency becomes increasingly critical as cloud computing services alter. This article uses bitcoin and machine learning to optimize resource utilization. We study PRDA, BSCA, and DRAA algorithms and propose “Blockchain and Machine Learning for Optimized Resource Allocation in Cloud Computing Services.” We employ blockchain, machine learning, and smart contracts to make resource sharing safer, clearer, and adaptable to cloud contexts. A comparative test demonstrates our resource allocation strategy works. PRDA reliably predicts resource usage using real-time data and prior patterns. This greatly reduces expenses and waste. The BSCA ensures safe and transparent delivery via guidelines. In multi-tenant cloud systems, DRAA optimizes resource consumption via reinforcement learning. This fixes underuse, exorbitant pricing, and speed loss. With this strategy, cloud service providers can remain open, keep rates low, and serve customers promptly.

关键词： Cloud computing Smart contracts Reinforcement learning Transforms Blockchains Resource management Security Reliability Standards Testing

来源：评论

学校读者我要写书评

暂无评论

Optimizing Low-Energy Carbon iioT Systems with Quantum Algorithms: Performance Evaluation and Noise Robustness

arXiv

引用

arXiv 2025年

作者： Dave, Kshitij Innan, Nouhaila Behera, Bikash K. Mumtaz, Shahid Al-Kuwari, Saif Farouk, Ahmed Institute of Advanced Research Gandhinagar India Quantum Physics and Magnetism Team LPMC Faculty of Sciences Ben M’sick Hassan II University of Casablanca Morocco NYUAD Research Institute NYUAD Abu Dhabi United Arab Emirates Pvt. Ltd. WB Mohanpur741246 India Nottingham Trent University Engineering Department United Kingdom Qatar Center for Quantum Computing College of Science and Engineering Hamad Bin Khalifa University Doha Qatar Department of Computer Science Faculty of Computers and Artificial Intelligence Hurghada University Hurghada Egypt

Low-energy carbon Internet of Things (IoT) systems are essential for sustainable development, as they reduce carbon emissions while ensuring efficient device performance. Although classical algorithms manage energy efficiency and data processing within these systems, they often face scalability and real-time processing limitations. Quantum algorithms offer a solution to these challenges by delivering faster computations and improved optimization, thereby enhancing both the performance and sustainability of low-energy carbon IoT systems. Therefore, we introduced three quantum algorithms: quantum neural networks utilizing Pennylane (QNN-P), Qiskit (QNN-Q), and hybrid quantum neural networks (QNN-H). These algorithms are applied to two low-energy carbon IoT datasets—room occupancy detection (RODD) and GPS tracker (GPSD). For the RODD dataset, QNN-P achieved the highest accuracy at 0.95, followed by QNN-H at 0.91 and QNN-Q at 0.80. Similarly, for the GPSD dataset, QNN-P attained an accuracy of 0.94, QNN-H 0.87, and QNN-Q 0.74. Furthermore, the robustness of these models is verified against six noise models. The proposed quantum algorithms demonstrate superior computational efficiency and scalability in noisy environments, making them highly suitable for future low-energy carbon IoT systems. These advancements pave the way for more sustainable and efficient IoT infrastructures, significantly minimizing energy consumption while maintaining optimal device performance. © 2025, CC BY.

关键词： Low emission

来源：评论

学校读者我要写书评

暂无评论

Towards a European HPC/AI ecosystem: A community-driven report 2

Towards a European HPC/AI ecosystem: A community-driven repo...

引用

2nd EuroHPC user day, EuroHPC 2024

作者： Taborsky, Petr Colonnelli, Iacopo Kurowski, Krzysztof Sarma, Rakesh Pontoppidan, Niels Henrik Jansík, Branislav Detlefsen, Nicki Skafte Pedersen, Jens Egholm Larsen, Rasmus Hansen, Lars Kai Technical University of Denmark Anker Engelunds Vej 1 Bygning 101A Kongens Lyngby2800 Denmark University of Torino Computer Science Dept. Corso Svizzera 185 Torino10149 Italy Poznań Supercomputing and Networking Center Jana Pawla II 10 Poznań61-139 Poland Forschungszentrum Jülich GmbH Jülich Supercomputing Centre Wilhelm-Johnen-Straße Jülich52425 Germany Eriksholm Research Centre Rørtangvej 20 Snekkersten3070 Denmark IT4Innovations VSB - Technical University of Ostrava Ostrava Czech Republic KTH Royal Institute of Technology Brinellvägen 8 Stockholm114 28 Sweden Alexandra Instituttet Rued Langgaards Vej 7 Copenaghen2300 Denmark

The rapid advancements in AI and Machine Learning necessitate a robust computational infrastructure to support cutting-edge research and industrial applications. From the academic and industrial AI community perspective, voiced in the recent ELISE project, the European AI platform is recommended to center around the EuroHPC growing ecosystem. It should be user-driven, easily accessible, powerful, and compliant with European regulations. AI-optimized and dedicated supercomputers for the European AI community are also coming, in addition to upgrading partitions of existing EuroHPC systems to 'AI enabled' stage. Related calls have been initiated in September 2024. Further, conventional EuroHPC systems are suggested to be extended with quantum computing, edge AI, and neuromorphic computing to cater to AI models deployed on network edge devices and sustainability in the long run. The challenges are presented in three case studies, ranging from training Transformers on HPC to LLMs trained federally across three different Euro HPC systems to recent results on hybrid classical-quantum application. This paper concludes with case studies results-informed next steps believed to benefit AI practitioners and the broader AI community. © 2025 The Authors. Published by Elsevier B.V.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

A Study on “Blockchain-Enabled Digital Twins: The Next Wave of Industrial Transformation with Future Research Challenges”

A Study on “Blockchain-Enabled Digital Twins: The Next Wave...

引用

International Conference on computer, Information and Telecommunication Systems (CITS)

作者： Sanjeev Kumar Dwivedi Mohammad S. Obaidat Mansi Mittal Nilesh Ranjan Honey Tyagi Ruhul Amin Kuei-Fang Hsiao Madhav Institute of Technology & Science (MITS) Gola ka Mandir Gwalior Madhya Pradesh India King Abdullah II School of Information Technology University of Jordan Amman Jordan University of Science and Technology Beijing Beijing China SRM University SRM Nagar Kattankulathur TN India eAmity University Noida UP India Department of Information Technology KIET Group Of Institutions Delhi-NCR Ghaziabad India Department of Computer Science and Engineering DSPM IIIT Naya Raipur (IIIT-NR) Chattisgarh India KASIT The University of Jordan Amman Jordan

ISBN: (数字)9798350359091

ISBN: (纸本)9798350359107

A new era of creativity, efficiency, and optimisation has emerged across a number of industrial sectors with the introduction of digital twin technologies. To enhance their capabilities, digital twins are frequently combined with cutting-edge technologies like blockchain, artificial intelligence (AI), and the Internet of Things (IoT). This paper summarises and evaluates the present status of research and applications of blockchain enabled digital twins in the context of industrial sectors. This review highlights the benefits of blockchain based digital twins in the different industrial domains such as production manufacturing, product data management, construction project management and, healthcare. Furthermore, the paper addresses the challenges and future directions of digital twin adoption in industries, discussing interoperability, data security, and the need for standardized frameworks.

关键词： Reviews Project management Production Medical services Digital twins Blockchains Telecommunications

来源：评论

学校读者我要写书评

暂无评论

GPNST: An Improved Graphical Password Authentication Scheme Leveraging Neural Style Transfer Technique on Smartphones

引用

International Journal of Information Security 2025年第3期24卷 1-34页

作者： Ray, Palash Giri, Debasis Obaidat, Mohammad S. Jana, Manasi Sasmal, Mahuya Alenazi, Mohammed J. F. Haldia Institute of Technology West Bengal Haldia India Maulana Abul Kalam Azad University of Technology West Bengal Nadia India King Abdullah II School of Information Technology The University of Jordan Amman Jordan School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Department of Computational Intelligence School of Computing SRM University SRM Nagar TN Kattankulathur603203 India School of Engineering The Amity University UP Noida201301 India King Saud University Riyadh Saudi Arabia

The growing prevalence of smartphones and the increasing dependence on digital services have made it crucial to have authentication techniques that are both secure and user-friendly. This study examines the effectiveness and usability of graphical passwords named GPNST as an alternative authentication method on mobile devices. Graphical passwords use users’ capacity to remember visuals or patterns, offering a possible equilibrium between security and user pleasure. GPNST is a two-factor authentication technique that requires users to remember content and style images, or stylized images, as portfolio images. Additionally, a unique key token is assigned to each user device and securely sent to the server using the reversible data hiding approach, therefore mitigating several potential attacks. The research uses a combination of quantitative analysis to evaluate the strength of passwords and qualitative evaluations to measure user satisfaction and memorability. We investigate the influence of several design elements in graphical passwords, such as the intricacy of images and the layout of grids, on both the level of security and ease of use. In addition, the study evaluates the robustness of graphical passwords against popular forms of attacks, such as shoulder surfing and brute-force efforts. The findings provide valuable insights regarding the practicality of incorporating graphical passwords into smartphone authentication systems. This has implications for designers, developers, and users who are looking for secure and user-friendly solutions in the constantly changing field of mobile technology. The GPNST scheme demonstrates outstanding performance in our assessment test, with an accuracy rate of up to 94.80% and a login time of 9.61 seconds. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Static random access storage

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：