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Research on Innovation Governance Intellectual Property Management System under the Integration of Digital and intelligent technology 3

Research on Innovation Governance Intellectual Property Mana...

引用

3rd ieee international conference on Power, Electronics and Computer Applications, ICPECA 2023

作者： Huang, Lei Zhongnan University of Economics and Law College of Business Administration Wuhan China

ISBN: (纸本)9781665472784

Combining IPFS, SHA256 algorithm and digital certificate technology, this paper proposes a four-level, three-module public-tested intellectual property trusted management system. The system first extracts the information management process on the basis of sorting out the agent-oriented intellectual property business process. Then this paper establishes the intellectual property information integration platform model and designs it from the aspects of platform function architecture and security guarantee. Finally, the PMF software integrated development environment is selected to implement the model system software from three main aspects: data management function, process control function and application management function. The study found that the system can achieve the expected purpose and function, and promote the development of intellectual property management. © 2023 ieee.

关键词： intelligent systems

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Research and Application of Information System Vulnerability control technology Based on Runtime Self-Protection technology 2

Research and Application of Information System Vulnerability...

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2nd international conference on Advanced Sensing, intelligent Manufacturing, ASIM 2023

作者： Du, Huijun Li, Wenjing Zhao, Lina Peng, Jia Yuan, Chuanxin Dong, Yang State Grid Shandong Electric Power Company Taian Power Supply Company Shandong China Information&Telecommuniccations Company State Grid Shandong Electric Power Company Shandong China

ISBN: (纸本)9798350385571

With the rapid development of information technology, information systems are becoming increasingly complex, which also brings more security challenges. Vulnerabilities are weaknesses in information systems that can be maliciously exploited to attack the system. In order to effectively protect the information system from attack, the vulnerability elimination technology based on runtime self-protection technology is developed. Therefore, this paper focuses on the overview of the run-time self-protection technology, the demand analysis of the vulnerability elimination technology, the key mechanism of the run-time self-protection technology, and describes the implementation process of the run-time self-protection vulnerability elimination technology in detail. Finally, the results of two groups of simulation experiments are as follows: After optimization, the vulnerability detection rate of the information system is increased by 12.2% on average, and the comprehensive average vulnerability false positive rate is reduced by 7.35%. The development of this technology improves the overall security of information systems, enabling systems to respond more intelligently and adaptively to emerging threats. © 2023 ieee.

关键词： Information systems

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Machine Learning use Case for cyber Security in Education Industry

Machine Learning use Case for Cyber Security in Education In...

引用

2023 international conference on Sustainable Computing and Smart systems, ICSCSS 2023

作者： Shukla, Sonal Sharma, Anand Mody University of Science and Technology Lakshmangarh India

ISBN: (纸本)9798350333602

Digitized learning is booming all around the world which is shifting the education sector into digitization as well, especially during the period of COVID. A huge impact can be seen on the education system namely with personalizes learning experiences which in turn helps updating contents frequently for learners and reducing costs with improvement in teaching learning techniques. Education sector is rapidly growing as any other major contributing sector present in the society. Institution industries strive for this generation to be ready while facing the competitive world out there. Although similar to these sectors in society, education is also prone to security issues. The security challenges faced by education are: data theft, malwares, spam, phishing and access control. Therefore, to prevent education industry from such threat, machine learning algorithms should be incorporated. Machine learning is one of the most advanced technologies working in information security and might showcase promising results in education sector of modern times. Scanning and analyzing of data at a faster pace with their statistics is the forte of Machine learning. Recently, the amount of data generated by cyber security systems is enormous on everyday basis, where machine learning plays a vital role. In this paper, we have presented the literature review of applications of machine leaning in the information security, its techniques and lastly the complexities. Also, this study presents a different phase to achieve cyber security and act as a foundation for the proposed prevention model to prevent or acknowledge the cyber-attack which might affect the educational industry. © 2023 ieee.

关键词： Machine learning

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Enhanced Machine Learning Approach for Detecting Spammers in Industrial Mobile Cloud Computing Environment 5

Enhanced Machine Learning Approach for Detecting Spammers in...

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5th international conference on IoT Based control Networks and intelligent systems, ICICNIS 2024

作者： Bhavana, K. Sai Abhinandu, B. Sriyesh, P. Sai Rama, K. Satheesh Kumar, S. Institute of Aeronautical Engineering Dept. Computer Science & Information Technology Hyderabad India

ISBN: (纸本)9798331518097

This research study proposes an innovative machine learning algorithm, Spammer Identification Novel K-Means Extension (SINKEX), to fortify IoT mobile networks against commands and potential disruptions in industrial production. Utilizing an industrial mobile cloud dataset, the algorithm employs basic, content, and network features, including follower count, post frequency, message content, and hyperlink usage, for spam detection. After employing Pearson Correlation and Euclidean Distance to eliminate dissimilar records, Principal Component Analysis (PCA) is applied to remove irrelevant features. The SINKEX algorithm then labels unclassified records, designating an account as a SPAMMER or NON-SPAMMER based on features like follower count and post frequency. Comparisons with a hybrid fuzzy c-means clustering algorithm demonstrate SINKEX's superior performance, achieving higher accuracy, precision, and recall. The results are presented through an intuitive graphical user interface, showcasing the algorithm's effectiveness in securing industrial IoT networks against malicious activities. © 2024 ieee.

关键词： Adversarial machine learning

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A Keypoint-based Object Representation for Generating Task-specific Grasps 18

A Keypoint-based Object Representation for Generating Task-s...

引用

ieee 18th international conference on automation Science and Engineering (ieee CASE)

作者： Robson, Mark Sridharan, Mohan Univ Birmingham Sch Comp Sci Intelligent Robot Lab Birmingham W Midlands England

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

This paper describes a method for generating robot grasps by jointly considering stability and other task and object-specific constraints. We introduce a three-level representation that is acquired for each object class from a small number of exemplars of objects, tasks, and relevant grasps. The representation encodes task-specific knowledge for each object class as a relationship between a keypoint skeleton and suitable grasp points that is preserved despite intra-class variations in scale and orientation. The learned models are queried at run time by a simple sampling-based method to guide the generation of grasps that balance task and stability constraints. We ground and evaluate our method in the context of a Franka Emika Panda robot assisting a human in picking tabletop objects for which the robot does not have prior CAD models. Experimental results demonstrate that in comparison with a baseline method that only focuses on stability, our method is able to provide suitable grasps for different tasks.

关键词： Robot grasping visual object representation learning and adaptive systems

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Design of Automatic control technology of Passive Hydrogen Maser 5

Design of Automatic Control Technology of Passive Hydrogen M...

引用

5th international conference on intelligent control, Measurement and Signal Processing, ICMSP 2023

作者： Zheng, Hefei Wang, Feng Li, Jing Li, Yuebao Beijing Institute of Radio Metrology and Measurement Time Frequency Stand Lab Beijing China

ISBN: (纸本)9798350336030

The passive hydrogen maser is one of the widely used atomic frequency standards with outstanding performance, which utilizes a hyper-fine transition between two ground state levels of hydrogen atoms as a frequency discriminator. In the past, the space passive hydrogen maser is developed, which outputs the standard signal for satellite navigation and positioning systems. Its structures are suitable for space-borne but not convenient for user operation. For the passive hydrogen maser for surface use, the automatic control technology is significant. With the FPGA technique to design the servo loop and the temperature control loop, the passive hydrogen maser performance is improved and the debugging becomes easy. The long-duration frequency stability performance is better than 5∗10-13at one second and 4∗10-15 at one day, which reached the international advanced level. To facilitate the operation personnel monitoring, the working status data of the passive hydrogen maser is displayed and critical parameters can be set by the liquid crystal display touchscreen through the display and control system. In addition, real-time control between the computer and the passive hydrogen maser is realized through network interface communication. Thus, the data and parameters can be monitored and controlled through IPC. © 2023 ieee.

关键词： Real time control

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PiAGI: The Concept, Mechanism and Framework

PiAGI: The Concept, Mechanism and Framework

引用

Digital Twins and Parallel Intelligence (DTPI), ieee international conference on

作者： Qiang Li Zhuoya Ju Lili Fan Xin Liu Wenhua Liu Feiyue Wang Scientific and Technological Innovation Center Beijing China The School of Automation Beijing Institute of Technology Beijing China School of Big Data & Cyber Security China University of Petroleum Qingdao China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

As social production and living spaces gradually expand from the physical and information domains to the cognitive and social domains, this article addresses the new changes brought about by these expansions. Starting from the new impact of era of intelligent connectivity on social cognitive management, it analyzes the urgent need to enhance social cognitive management capabilities centered on cognitive decision-making, identifying the core key as Adversarial Generated Intelligence (AGI). It delves into the conceptual characteristics, operating mechanisms, and winning strategies of AGI, identifies the new challenges it faces, and proposes a Parallel Intelligence empowering AGI (PiAGI) system architecture through the empowerment of parallel intelligence. This provides theoretical support for improving social cognitive management capabilities centered on cognitive decision-making.

关键词： Decision making systems architecture Production Digital twins Faces

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An intelligent Recommendation System for Improvisation Playing and Singing Built with Database technology

An Intelligent Recommendation System for Improvisation Playi...

引用

2023 international conference on Computer Science and automation technology, CSAT 2023

作者： Dai, Chenyan Tianhua College Shanghai Normal University Shanghai China

ISBN: (纸本)9798350371437

In order to facilitate the retrieval of relevant information and provide users with an efficient method, the author uses database technology to propose an intelligent recommendation system for improvisation and singing. This algorithm supplements traditional search methods to a certain extent. Based on this study, a thorough analysis of the recommended methods was conducted through collaboration, and their specifications were carefully examined. Finally, a systematic software analysis of the model was conducted using B/S software, achieving personalized music recommendation. The results indicate that in order to provide song recommendations to the target user Xiao Ming, the system first calculates the similarity between Xiao Ming and other users in the database. Subsequently, the system selects the K users with the highest similarity score and retrieves their improvised playback time. Based on the investigation, the system hypothesized Xiaoming's preference for classical improvisation. Then calculate the similarity score for the last three users, namely Zhang San, Li Si, and Wang Wu. Finally, through frequent mining and evaluation of project set association rules, the system recommended the following songs to Xiao Ming: Nocturne, Scottish Dance, and Narrative Music. Conclusion: The system aims to provide a comprehensive set of services that effectively meet the recommendation needs of users. With this system, users can receive recommendations for various improvisation and singing styles, which can be customized according to each user's personal preferences. © 2023 ieee.

关键词： Recommender systems

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controlling BLDC Motor with Bidirectional Converters with cyber-Physical systems 9

Controlling BLDC Motor with Bidirectional Converters with Cy...

引用

9th ieee international conference on Electronics, Computing and Communication Technologies, CONECCT 2023

作者： Thrishana, B.B. Nalinakshan, Shankar Venkatesh, Appalabathula Nishana, B.B. Workload Analyst Alstom Bangalore India The National Institute of Engineering Electrical and Electronics Engineering Mysuru India Anil Neerukonda Institute of Technology and Sciences Electrical and Electronics Engineering Andhra Pradesh India

ISBN: (纸本)9798350334395

Brushed DC motor has simple speed control techniques. In brushed DC motor, commutation is done by the rotating part which is placed on the rotor and brushes known as commutator. The amount of losses in brushed DC motors is high because of the presence of mechanical parts. But the commutation in brushless DC motors (BLDC) is achieved with the aid of solidstate switches (Electronic commutation). As there is reduction in the losses, the motor's performance is improved. Hence, brushed motors are being replaced by BLDC motors as they are used in many applications due to its high mechanical and electrical properties. The advantages of BLDC motors are low maintenance, electronic control and high speed therefore finds application in computer peripherals, portable power tools and vehicles such as model planes to automotive. The regulation of a BLDC motor using a bidirectional DC-DC converter is demonstrated in this research work. The output of the DC-DC converter is supplied into the three-phase voltage source inverter (VSI), that powers the motor. PI and Fuzzy controllers are used to regulate the speed of a BLDC motor. The simulation is performed with help of MATLAB R2019b version software and the results are verified. cyber Physical systems (CPS) for controlling BLDC motors with bidirectional converters offers several benefits, including improved accuracy, speed, and reliability of motor control, as well as reduced energy consumption and maintenance costs © 2023 ieee.

关键词： Brushless DC motors

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Energy Consumption in Smart Buildings using Machine Learning 7

Energy Consumption in Smart Buildings using Machine Learning

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7th international conference on intelligent Computing and control systems, ICICCS 2023

作者： Kumar, Katti Bharath Abhay Gopireddy, Gangireddy Ranjana, P. Hindustan Institute of Technology and Science Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350397253

Energy is the indispensable factor of modern societies. From last few decades, there is rapid increase in world's energy consumption due to raise of population and their comfort demands. Buildings are accountable for 40% of global energy hence Building Energy Management has become crucial topic nowadays for reducing energy wastage The ability to forecast the amount of energy used in SB and plan for that use is essential for the implementation of energy-efficient management systems. The proposed method for estimating the amount of energy that is used in buildings, as well as offering suggestions for cutting down on energy use and lowering expenses. The systems use the information like temperature humidity air quality etc. This information is analyzed by machine learning forecast the amount of energy that is used by smart buildings. © 2023 ieee.

关键词： Internet of things

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