检索结果-内蒙古大学图书馆

Exploring Post Quantum Blockchain Technologies: Potential and Challenges in Digital Forensics Applications 1

7th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Rajawat, Anand Singh Goyal, S.B. Joshi, Poonam Solanki, Ram Kumar Singh, Kuldeep Deaprtment of CSE Sandip University Nashik422213 India Faculty of Information Technology City University Petaling Jaya46100 Malaysia Department of Computer Engineering Thakur College of Engineering and Technology Mumbai400101 India GL Bajaj Institute of Technology and Management Greater Noida201306 India

ISBN: (数字)9783031508875

ISBN: (纸本)9783031508868

As the world prepares for the arrival of quantum computing, numerous conventional cryptographic methods confront imminent vulnerabilities. The field of post-quantum cryptography endeavors to construct cryptographic algorithms that are impervious to the potential threats presented by quantum computers. The technology underlying cryptocurrencies, known as blockchains, heavily rely on cryptographic security and consequently assume a pivotal role in the quantum era. This scholarly article investigates the potential of post-quantum blockchain technologies and their implications in the realm of digital forensics applications. We initiate with a comprehensive overview of the fundamental concepts of post-quantum cryptography and delve into its applicability within the blockchain domain. The potential advantages of integrating post-quantum techniques into blockchain technologies encompass heightened security against quantum attacks, lengthened cryptographic life cycles, and the establishment of platforms that ensure forensic soundness. Nevertheless, along with these potential benefits, challenges also emerge. The increased complexity of post-quantum algorithms may result in lengthier transaction du-rations, augmented computational requirements, and issues pertaining to scalability. Moreover, from the perspective of digital forensics, the robustness of post-quantum blockchains may introduce intricacies in data retrieval, evidence authentication, and cross-jurisdictional investigations. The study assesses a variety of post-quantum blockchain projects currently under development, evaluating their strengths and limitations within the context of digital forensics. In conclusion, while post-quantum blockchains offer a new frontier of security and forensic reliability, their effective implementation necessitates a harmonious balance between cryptographic robustness, practicality, and the evolving needs of digital forensic practitioners. © The Author(s), under exclusive license to S

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Leveraging Machine Learning for More Efficient Real-Time Data Analysis 3

Leveraging Machine Learning for More Efficient Real-Time Dat...

引用

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

作者： Rajan, T. Surulivel Chavan, Gurunath T. Kumar, Ritesh Saini, Rajat Rajesh, A. Doda, Devendra Kumar Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Computer Science Engineering Faculty of Engineering and Technology Karnataka Bangalore India Vivekananda Global University Department of Electrical Engineering Jaipur India

ISBN: (纸本)9798350319125

The present-day state of real-time statistics analysis, in the main, relies on guide evaluation techniques that require trained records scientists as a way to extract significant insights from statistics streams. Leveraging machine-gaining knowledge of (ML) methods provides the capacity for increasing the efficiency and accuracy of real-time statistics analysis. This paper presents an automation process for data analysis, utilizing machine learning algorithms to improve the efficiency and accuracy of real-time data analysis. The proposed process involves data preprocessing, feature selection, algorithm selection, model training, and validation, all of which can be automated to reduce human intervention and errors. Additionally, the paper highlights the benefits of incorporating machine learning in the data analysis process, such as fast and accurate predictions, increased scalability, and reduced costs. The results obtained from implementing this automation process demonstrate its effectiveness in achieving more efficient real-time data analysis. Ultimately, this study provides valuable insights for organizations looking to leverage machine learning for better data analysis and decision-making. we present numerous use case studies illustrating current successes in leveraging ML for more efficient actual-time records evaluation. © 2023 IEEE.

关键词： Deploying Evaluation Leveraging Particular Successes

来源：评论

学校读者我要写书评

暂无评论

2D-LLFE-NVC: 2D Laser Line Feature Extraction Using Normal Vector Clustering 30

2D-LLFE-NVC: 2D Laser Line Feature Extraction Using Normal V...

引用

30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Ou, Jinshun Ren, Jiying Li, Wenguang Huang, Panling Zhou, Jun Zhou, Jiehan Zhang, Tao Shandong University School of Mechanical Engineering Jinan China Shandong University of Science and Technology School of Computer Science and Technology Qingdao China University of Oulu Faculty of Information Technology and Electrical Engineering Oulu Finland Qingdao Hanhe Cable Co. Ltd. Qingdao China

ISBN: (纸本)9798350391916

This paper presents a novel 2D laser data line feature extraction algorithm based on normal vector clustering(2D-LLFE-NVC). The algorithm consists of normal vector calculation, normal normalization based on multi-scale operator normal difference and median filter, and line feature extraction based on normal vector clustering. Unlike existing methods, 2D-LLFE-NVC leverages the continuity of laser point clouds and detects breakpoints using multi-scale operators based on normal differences. The extracted line features are more accurate and correct on a global scale. To validate its performance, we conducted SLAM experiments in a 5000-square-meter indoor environment using both the proposed algorithm and existing methods. By comparing the line feature points extracted by these different approaches with manually annotated line feature points, and demonstrating the superior performance of the proposed method in terms of correctness and completeness. © 2024 IEEE.

关键词： Median filters

来源：评论

学校读者我要写书评

暂无评论

Enhancing Video Anomaly Detection Using Spatio-Temporal Autoencoders and Convolutional LSTM Networks

引用

SN computer Science 2024年第1期5卷 1-13页

作者： Almahadin, Ghayth Subburaj, Maheswari Hiari, Mohammad Sathasivam Singaram, Saranya Kolla, Bhanu Prakash Dadheech, Pankaj Vibhute, Amol D. Sengan, Sudhakar Department of Networks and Cybersecurity Faculty of Information Technology Al Ahliyya Amman University Country Amman Jordan School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai 600127 India Department of Networks and Cybersecurity Information Technology Al Ahliyya Amman University Amman Jordan Department Computing Technology School of Computing SRM Institute of Science and Technology Kattankulathur Campus Tamil Nadu Chennai 603203 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur 522302 India Department of Computer Science and Engineering Swami Keshvanand Institute of Technology Management and Gramothan (SKIT) Rajasthan Jaipur 302017 India Symbiosis Institute of Computer Studies and Research (SICSR) Symbiosis International (Deemed University) MH Pune 411016 India Department of Computer Science and Engineering PSN College of Engineering and Technology Tamil Nadu Tirunelveli 627152 India

Identifying suspicious activities or behaviors is essential in the domain of Anomaly Detection (AD). In crowded scenes, the presence of inter-object occlusions often complicates the detection of such behaviors. Therefore, developing a robust method capable of accurately detecting and locating anomalous activities within video sequences becomes crucial, especially in densely populated environments. This research initiative aims to address this challenge by proposing a novel approach focusing on AD behaviors in crowded settings. By leveraging a spatio-temporal method, the proposed approach harnesses the power of both spatial and temporal dimensions. This enables the method to effectively capture and analyze the intricate motion patterns and spatial information embedded within the continuous frames of video data. The objective is to create a comprehensive model that can efficiently detect and precisely locate anomalies within complex video sequences, specifically those featuring human crowds. The efficacy of the proposed model will be rigorously evaluated using a benchmark dataset encompassing diverse scenarios involving crowded environments. The dataset is designed to simulate real-world conditions where millions of video footage need to be continuously monitored in real time. The focus is on identifying anomalies, which might occur within short time frames, sometimes as brief as five minutes or even less. Given the challenges posed by the massive volume of data and the requirement for rapid AD, the research emphasizes the limitations of traditional Supervised Learning (SL) methods in this context. © 2024, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Anomaly detection Autoencoders LSTM Machine learning Spatio-temporal features Suspicious activities

来源：评论

学校读者我要写书评

暂无评论

IoT-based remote control for robotic arm

引用

International Journal of Systems, Control and Communications 2024年第2期15卷 146-158页

作者： Do, Tri Nhut Department of Embedded Systems and Robotics Faculty of Computer Engineering University of Information Technology Viet Nam Vietnam National University Ho Chi Minh City 1 Han Thuyen Street Linh Trung Ward Thu Duc Ho Chi Minh City71308 Viet Nam

Robotic arms can perform various tasks with high accuracy, efficiency, and safety, especially in hazardous environments. This paper presents four degrees of freedom robotic arm that can be controlled remotely by two methods: direct control via Wi-Fi and indirect control via internet. We have designed an embedded system that allows the user to manipulate the robotic arm by moving the robot hand in different directions. We have also developed two software applications for remote control: one using MIT inventor 2 tool for direct control, and another using a web-based interface for indirect control. The software applications enable the user to adjust the angles of the four servo motors that drive the robotic arm in both clockwise and counter – clockwise directions. We have conducted several experiments to demonstrate the feasibility and stability of our system under different scenarios. Our results show that our system can perform wireless control of the robotic arm effectively using various mobile devices such as phone, tablet, or computer such as laptop, personal computer. © 2024 Inderscience Enterprises Ltd.

关键词： Robotic arms

来源：评论

学校读者我要写书评

暂无评论

Automated COVID-19 screening framework via Deep Convolutional Neural Network with Chest X-ray Medical Images 6

Automated COVID-19 screening framework via Deep Convolutiona...

引用

6th International Conference on information technology, InCIT 2022

作者： Damkham, Waris Thaipisutikul, Tipajin Supratak, Akara Kraisangka, Jidapa Mongkolwat, Pattanasak Wang, Jja-Ching Mahidol University Faculty of Information and Communication Technology Thailand National Central University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9781665489126

COVID-19 screening using chest X-rays plays a significant role in the early diagnosis of COVID-19 illness during the ongoing pandemic. Manually identifying this infection from chest X-ray films is a challenging and time-consuming technique due to time restrictions and the competence of radiologists. Also, the manual Covid-19 identification technique is made much more difficult and opaquer by the feature similarity between positive and negative chest X-ray images. Therefore, we propose an automated COVID-19 screening framework that utilizes artificial intelligence techniques with a transfer learning approach for COVID-19 diagnosis using chest X-ray images. Specifically, we employ the transfer learning concept for feature extraction before further processing with modified deep neural networks. Also, Grad-CAM visualization is used for our case study to support the predicted diagnosis. The results of the experiments on the publicly accessible dataset show that the convolutional neural network model, which is simple yet effective, performs significantly better than other deep learning techniques across all metrics, including accuracy, precision, recall, and F-measure. © 2022 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Foreign Embassies Internationalization Support for Small and Medium-Sized Enterprises: Need to Balance Innovation Strategy and Innovation Support Policies

引用

IEEE engineering Management Review 2023年第2期51卷 63-74页

作者： Gupta, Varun Gupta, Chetna Rubalcaba, Luis Nguyen-Duc, Anh Wang, Xiaofeng Butlewski, Marcin University of Alcala Department of Economics and Business Administration Madrid28802 Spain Potsdam14469 Germany University of South-Eastern Norway School of Business Department of Business and It Notodden3679 Norway Free University of Bozen-Bolzano Faculty of Computer Science Bolzano39100 Italy Poznań University of Technology Faculty of Engineering Management Poznań60-965 Poland Jaypee Institute of Information Technology Department of Computer Science and Engineering Noida201305 India

For American businesses trying to expand internationally, the embassies serve as a crucial component of the innovation ecosystem. By utilizing their close professional relationships with stakeholders like governments, market experts, local consumers, and local public institutions, they boost access to information about international markets. Since foreign markets differ from domestic markets, expanding internationally necessitates adaptations and/or innovations to current business models. An accurate international market study should be the foundation for successful adaptations or innovations. The cost of the assistance provided by embassies appears to be minimal to the firms. From the perspective of small and medium-sized enterprises (SMEs), support policy innovations appear to be required. SMEs do not appear to be in a position to decide which embassy resources they need and take the best advantage to internationalize, given their liability of newness and smallness. This makes it clear that support policies should provide these SMEs with more holistic, organized, and thorough help that is customized to their specific needs, business size, product category, and industry of operation. Additionally, SMEs must align their innovation strategies with the innovation support policies of a nation, which are pushed out through by different institutions, for instance, embassies abroad. As they must take part in SMEs' innovation management processes in global marketplaces, embassies play a role more akin to boundary spanners or coinnovators. Strategic alliances with university libraries may also aid embassies in improving their commercial diplomacy because they can cocreate with SMEs to innovate their services and SMEs benefit from improved globalization assistance. © 1973-2011 IEEE.

关键词： International trade

来源：评论

学校读者我要写书评

暂无评论

Application of Adaptive Modulation Strategies for Enhancing Peak Bit Rates in High-Speed Fiber Optic Communication Networks 3

Application of Adaptive Modulation Strategies for Enhancing ...

引用

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

作者： Futane, Pravin R. Yadav, Rakesh Kumar Khurana, Saniya Shankar, Amar Kar, Abhijeet Ashok, V. Vishwakarma Institute of Information Technology Department of Information Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Food Technology Faculty of Engineering and Technology Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Mechanical Engineering Chennai127 India

ISBN: (纸本)9798350319125

Optical communication networks suffer from excessive peak bit quotes today's the physical and environmental constraints present day fiber optic cables. Adaptive modulation techniques offer a potential approach to the trouble with the aid of making an allowance for increased facts throughput with the aid of tailoring the information rate latest the signal to the channel's country. Those techniques have the ability to modify modulation formats and facts fees in real-time to optimize the height bit fee and universal throughput modern the network. This paper examines the software trendy adaptive modulation strategies for enhancing top bit prices in excessive-velocity fiber optic verbal exchange networks and evaluations the to be had strategies for fixing this hassle. The evaluation additionally critiques the present day adaptive modulation algorithms and their overall performance in terms modern-day top bit fee and throughput modern-day the verbal exchange networks. Finally, this paper affords an overview modern day several future research challenges important for further improvements in this discipline. © 2023 IEEE.

关键词： Exchange Modern Modulation Performance Throughput

来源：评论

学校读者我要写书评

暂无评论

Studying the Effects of Prolonged Thermal Stress Aiming to Induce Artificial Aging on DRAM Retention-Based Physical Unclonable Functions

Studying the Effects of Prolonged Thermal Stress Aiming to I...

引用

2024 IEEE International Conference on Consumer Electronics, ICCE 2024

作者： Anagnostopoulos, Nikolaos Athanasios Mexis, Nico Fan, Yufan Bartsch, Stephanie Senjuty Schaier, Tanja Katzenbeisser, Stefan Arul, Tolga Technical University of Darmstadt Department of Electrical Engineering and Information Technology Darmstadt64283 Germany University of Passau Faculty of Computer Science and Mathematics Passau94032 Germany Technical University of Darmstadt Department of Computer Science Darmstadt64289 Germany

ISBN: (纸本)9798350324136

This work studies the effects of thermal stress on Dynamic Random-Access Memory (DRAM) retention-based Physical Unclonable Functions (PUFs) based on Commercial Off-The-Shelf (COTS) Single-Board computer (SBC) modules. Our results show that prolonged thermal stress, in general, leads to a decrease in the entropy of the responses of this PUF (as the number of bit flips is reduced) and a loss of its reliability (as responses taken before and after the stress has been applied to this PUF do not adequately match each other). Nevertheless, we note that as time passes after we stop applying thermal stress to the relevant PUF devices, their responses start to resemble more and more those that they produced before thermal stress was applied to them. As prolonged thermal stress has been utilised in order to induce artificial aging on electronics, our work not only studies the potential effects of aging on such electronics as DRAMs in general and DRAM PUFs in particular, but also sheds some doubt on the ability of this method to induce permanent effects that would truly resemble the effects of aging. © 2024 IEEE.

关键词： DRAM PUF DRAM retention-based PUF Physical Unclonable Function (PUF) Physical Unique Function silicon aging thermal stress transistor aging

来源：评论

学校读者我要写书评

暂无评论

Technical Job Distribution at BSD SHARP Service Center Using Combination of Naïve Bayes and K-Nearest Neighbour

Technical Job Distribution at BSD SHARP Service Center Using...

引用

2022 IEEE Symposium on Wireless technology and Applications, ISWTA 2022

作者： Pebrianti, Dwi Ariawan, Angga Bayuaji, Luhur Mahdiana, Deni Rusdah, Rusdah Universitas Budi Luhur Magister of Computer Science Faculty of Information Technology Jakarta Indonesia International Islamic University Malaysia Faculty of Engineering Dept. of Mechanical Engineering Gombak Malaysia Universitas MNC Faculty of Computer Science Department of Computer and Media Jakarta Indonesia Universitas Budi Luhur Faculty of Information Technology Department of Information System Jakarta Indonesia

ISBN: (数字)9781665484824

ISBN: (纸本)9781665484824

Works distribution is a routine carried out every day by the head of the branch in the SHARP Service Center. The accuracy of the labor division is very important to get customer satisfaction. Inappropriate work distribution can increase complaints from customers. Currently, works distribution in SHARP Service Center is carried out manually, where the works received on the selected system is then shared through the document provided. Time taken for this process is about 1.42 minutes on average for each damage reports. Speed of Service also depends on the Head of Department's expertise and experience. In this study, an automatic system based on Machine Learning will be designed for the technicians work distribution by using a combination of k Nearest Neighbor (k-NN) and Naïve Bayes. Naïve Bayes algorithm is used to improve the feature extraction accuracy by considering the feature below the average (α). Meanwhile, k-NN algorithm is used to classify the experimental data. From the study, it is found that the best of k value for k-NN algorithm is 15. It is known that a high number of accuracy values, the labor distribution can be more accurate. The validation of the proposed method is conducted by using a confusion matrix with a composition of 80% training data and 20% test data. The single Classifier test with the Naïve Bayes algorithm produces the highest accuracy value of 72.7%, while using k-NN algorithm is 81.5%. With a combination of Naive Bayes and k-NN algorithms, the accuracy value is increasing to 86%. This result shows that the proposed method improves the accuracy by 13.3% on single Naive Bayes algorithms and 4% on a single k-NN algorithm. The results obtained show that in the manual process, the average time per job is 1.42 minutes, while by using the proposed method, the average processing time is around 0.03 seconds per job. An increase of 2480 times faster is found and confirmed during the implementation of the proposed method. © 2022 IEEE.

关键词： Customer satisfaction

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：