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A System for Controlling the GUI by Gestures using a Webcam, Based on MV Algorithms 7

A System for Controlling the GUI by Gestures using a Webcam,...

引用

7th international Youth conference on Radio Electronics, Electrical and Power Engineering, REEPE 2025

作者： Borisov, Nikita S. Belov, Yuri S. Bauman Moscow State Technical University Information Technology Department Moscow Russia

ISBN: (纸本)9798331531836

this article presents a gesture-controlled computer system using a webcam and machine vision (MV) algorithms, which allows for more intuitive and accessible human-computer interaction. the research is of great importance because it improves the usability of a computer for people with disabilities and offers a faster alternative to traditional input methods in limited conditions, such as the workplace. the goal is to develop a system that allows users to control graphical user interfaces (GUIs) using gestures using computer vision techniques. the technique includes image processing, hand segmentation, gesture recognition, and command execution. the experiments were conducted on Windows 10 and macOS. the results show successful gesture recognition and command execution in Windows 10, while macOS testing revealed the potential for simplification with built-in features. the study concludes that gesture control technology has significant potential to improve human-computer interaction, especially in environments where traditional input devices are impractical or unavailable. © 2025 IEEE.

关键词： Graphical user interfaces

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Research on Malware Detection System Using Artificial Intelligence 7

Research on Malware Detection System Using Artificial Intell...

引用

7th IEEE/ACIS international conference on Big Data, Cloud Computing, and Data Science, BCD 2022

作者： Kim, MinSu Joongbu Univ Department of Information Security Engineering Seoul Korea Republic of

ISBN: (数字)9781665465823

ISBN: (纸本)9781665465823

Malicious code is a program that accesses and destroys a system or performs malicious actions such as leaking information. Typically, viruses, Trojan horses, and worms attack the system by hiding malicious code through the same path as e-mail. As modern technology develops, the technology of malicious code is also becoming more sophisticated and diversified. Many malware creators distribute malware for the purpose of gaining financial gain. In order to achieve its purpose, it is necessary to produce the maximum effect with minimum cost and effort, so rather than elaborately produced, malicious programs with similar functions are printed quickly. In addition, there are cases where the malicious code of the creators for political purposes and the creators for the display of technology is elaborately created for the purpose of system vulnerabilities and zero-day attacks, so that it is impossible to detect them. As the core technology of the 4th industrial revolution and the technology that incorporates artificial intelligence, which lies at the center, has emerged as a core industry, major countries and many companies around the world are making intensive investments and RAD in artificial intelligence, there is. As artificial intelligence technology is being researched and invested in various fields, research and development of artificial intelligence technology is in progress in the information security industry. In line with this trend, we plan to effectively respond to malware by applying artificial intelligence to the detection of various and sophisticated malicious codes. © 2022 IEEE.

关键词： Decision trees

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A Fast Deep Learning Based Approach for Unsupervised Anomaly Detection in 3D Data 7

A Fast Deep Learning Based Approach for Unsupervised Anomaly...

引用

7th international conference on Frontiers of Signal processing, ICFSP 2022

作者： Presa, Sergio Saiz, Fatima A. Barandiaran, Inigo Industry and Advanced Manufacturing Fundación Vicomtech Donostia - San Sebastián Spain University of the Basque Country UPV/EHU Computational Intelligence Group Computer Science Faculty Donostia - San Sebastián Spain

ISBN: (数字)9781665481588

ISBN: (纸本)9781665481588

Anomaly detection is an important method in industrial manufacturing environments for defect detection, and consequently, for the quality requirements attainment. there is a strong trend to automate inspection systems using Artificial Intelligence techniques, especially through the use of 2D information. However, for dimensional inspection, it is necessary to have 3D data that provide detailed geometric information of the object. In this paper, we present a novel Deep Learning based approach for fast anomaly detection applicable to industrial domains by using point cloud voxelization. We evaluate our approach on a custom dataset in which our model achieves high accuracy, comparable to the state-of-the-art 3D Deep Learning models, while being faster than traditional anomaly detection methods. © 2022 IEEE.

关键词： Neural networks

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Implementation of Blockchain technology Using Hash Method in Java for Medical Record Application Development 7

Implementation of Blockchain Technology Using Hash Method in...

引用

7th IEEE international conference on information technology and Digital Applications, ICITDA 2022

作者： Jaya, Tryan Nugraha, Salvator Elto Davinsi, Gabriel Rolly Moniaga, Jurike V. Jabar, Bakti Amirul Bina Nusantara University School of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665461368

ISBN: (纸本)9781665461368

Health problems are not only related to the availability of medical facilities and medical personnel but also include the security of health data. In this regard, the development of blockchain technology provides a bright spot for data protection. this group's research is intended to discuss the application of blockchain technology in the health sector, to protect patient medical record data. therefore, in this study, an analysis of several kinds of literature has been collected to find out how the blockchain works. the analysis results found that one of the blockchain elements is the hash. the hash function takes input using a variable length and then produces a fixed-length output. Using a hash algorithm, transactions that are taken as input, are output with a fixed size. the hash function as a blockchain element is then implemented using the Java language to protect medical record data when it is stored and shared among hospitals using medical record applications. © 2022 IEEE.

关键词： Blockchain

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Fixed Point Clip: A New Data Augmentation Method for Object Detection 7

Fixed Point Clip: A New Data Augmentation Method for Object ...

引用

7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Pan, Bei Li, Shanmin Cheng, Yuanshun Yan, Xiaojun Wang, Chao Yang, Chuansheng Zhejiang Ocean University School of Information Engineering Zhoushan China Tianfu College of Swufe Sichuan China Zhejiang Ocean University National Engineering Research Center for Marine Aquaculture Zhoushan China Zhejiang Ocean University Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhoushan China

ISBN: (纸本)9781665478571

Data augmentation is one of the most important ways to improve object detection performance. In this paper, we propose a new offline data augmentation method, this method obtains multiple new anchors and new labels by fixed-point clipping in the original anchor box, by retaining important semantic information, the detection performance of the occlusion object is improved. At the same time, we produced a marine fish dataset with 11 kinds of marine creatures, and we verify the effectiveness of the proposed method in this dataset. Experiments confirmed the effectiveness of this method on the marine fish dataset, in the total dataset, the mAP@0.5 of this method is 10% higher than the Baseline. In the Tuna class that is seriously occluded in the obstruction problem, the mAP@0.5 of this method is 0.25 higher than baseline, which is increased by 46%. It indicates that this method can not only perform well in normal object detection but also maintain the advantage in complex scenes. © 2022 IEEE.

关键词： Object recognition

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To Investigate the Ability of CNN in Learning Specific Frequency Band of Motor Imagery EEG 7

To Investigate the Ability of CNN in Learning Specific Frequ...

引用

7th international conference on Signal and Image processing, ICSIP 2022

作者： Shi, Chenyun Liu, Lei Zhang, Chao Wu, Xiaopei Anhui University School of Computer Science and Technology Hefei China

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

Convolutional neural network (CNN) has achieved great success in the fields of image and speech recognition. However, CNN-based models still have limitations in the field of electroencephalogram (EEG)-based brain-computer interfaces. In this paper, we research the problem of classifying small sample MI-EEG data based on CNN in the context of motor imagery (MI) brain-computer interface (BCI) applications. We designed a one-dimensional CNN (1D-CNN) for identifying individualized frequency features of MI-EEG. Meanwhile, the paper studies the anti-interference performance of CNN. the results show that if the original EEG signal is preprocessed with appropriate temporal and spatial filtering, ID-CNN can search the effective characteristic frequency band of different subjects more accurately and obtain the ideal MI classification results. then, it is difficult to obtain the expected experimental results if the EEG data without pre-processing or with only simple bandpass filtering as pre-processing is used as input. © 2022 IEEE.

关键词： Independent component analysis

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Secured Encrypted Morse Code Communication using Fernet in Defense Applications 7

Secured Encrypted Morse Code Communication using Fernet in D...

引用

7th IEEE Pune Section international conference, PuneCon 2024

作者： Meena, R. Durga Pandiyarajan, Pandiselvam Narasimha, D Lakshmi Yadav, G. Vara Krishna Poornesh, J. Reddy, C Sanjeev Kishore Kalasalingam Academy of Research and Education Department of Computer Science and Engineering Tamilnadu Virudhunagar India

ISBN: (纸本)9798331527822

In today's digital age, ensuring the security and confidentiality of voice communication is crucial. this research work presents an innovative approach that leverages a combination of speech recognition, Morse code conversion, and encryption techniques to achieve secure transmission of spoken messages. By integrating these methods, this research provides a system for encoding, encrypting, and securely transmitting voice data, ensuring that sensitive information remains protected throughout the communication process. this article explains a multi-step process that combines speech recognition, Morse code conversion, and encryption to securely send spoken information. the workflow begins with Speech-to-Text Conversion, where spoken words are converted into text using advanced speech recognition technology. the text is then transformed into Morse Code for further processing. To ensure the confidentiality of the message, the Morse code is encrypted using Fernet symmetric encryption. this encrypted Morse code can be securely transmitted or stored. Upon receiving the encrypted message, the process is reversed: Morse Code Decryption returns the encrypted Morse code to its original form, which is then converted back into text through Morse Code to Text Conversion. Finally, the text is transformed back into Spoken Words using text-to-speech technology, completing the secure transmission of the original spoken message. this research combines classic communication techniques with modern encryption methods to create a system for secure and encrypted voice communication. © 2024 IEEE.

关键词： Cryptography

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Leveraging Machine Learning to Identify Synergistic Drug Combinations for Effective Cancer Treatment 7

Leveraging Machine Learning to Identify Synergistic Drug Com...

引用

7th international conference on Image information processing, ICIIP 2023

作者： Sujatha, P. Saravanan, K. Sohail, Mohammed Ali Basi Reddy, A. Dixit, Rohit R. Krishnaiah, Nallam Amrita Vishwa Vidyapeetham Department of AI/ML Guntur Amaravati India R.M.K Engineering College Department of Information Technology Tamil Nadu Tiruvallur District India Jazan University College of Computer Science & Information Technology Department of Computer & Network Engineering Jazan Saudi Arabia Mohan Babu University School of Computing Department of Computer Science And Engineering Andhra Pradesh Tirupati India Siemens Healthineers NH03755 United States St.Martin's Engineering College Department of Ai&ml Secunderabad Telangana Dhulapally500100 India

ISBN: (纸本)9798350371406

the potential of drug combinations to treat and overcome medication resistance complex genetic diseases is evident. Synergistic drug combinations offer a promising way to enhance drug therapy efficacy and reduce the required medication dosage. However, developing effective combination medication therapies with synergistic effects has been challenging, despite numerous ongoing clinical investigations. Current models and approaches to detect medication synergy outlined in the literature lack the expected consistency in outcomes. to better comprehend the impact of particular medication combinations, it is essential to be familiar with the vocabulary used to describe synergy. In this study, a combinational drug screen is utilized to identify useful features for locating synergistic or efficient drug combinations. the feature selection algorithm (Boruta) helps select the most relevant features, and machine learning models are then trained using the selected feature dataset. Performance assessment metrics like sensitivity, accuracy, and specificity are used to compare the trained models, and the Random Forest model stands out for its significantly better performance compared to other models. © 2023 IEEE.

关键词： Drug dosage

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StatekeepSpec: Securing Speculative Execution via forbidding Change-Of-State 23

StatekeepSpec: Securing Speculative Execution via forbidding...

引用

23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Lv, Zhiyuan Zhao, Youjian Huawei Technologies Beijing China Tsinghua University Department of Computer Science and Technology Beijing China

ISBN: (纸本)9781665494571

Speculation-based attacks, e.g., Spectre and Meltdown, affect hundreds of millions of computers. these attacks utilize speculative execution to access privileged data and leak it through a side-channel, e.g., typical a cache channel. Existing hardware-based defense solutions require major changes to the microprocessor architecture and incur large overheads, while software-based solutions address only specific exploit techniques. In this paper, we propose StatekeepSpec, a novel defense against Spectre attacks by forbidding speculative instructions' side effects to the cache hierarchy. Specifically, given a speculative load, if it triggers a cache hit then StatekeepSpec enforces it reading data from the cache without updating its replacement information;otherwise a cache miss occurs then StatekeepSpec enforces it reading data directly from the next level cache or memory, without updating the current level cache. As a result, StatekeepSpec blocks micro-architectural covert and side channels through the cache hierarchy caused by speculative loads. We have implemented a prototype of StatekeepSpec by modifying the design of an x86-64 processor using the Gem5 full system simulator. the evaluation results show that StatekeepSpec provides a strong security guarantee against cache based Spectre attacks. Furthermore, our simulations with 23 SPEC CPU workloads show that the performance overhead introduced by StatekeepSpec is less than 29%. © 2021 IEEE.

关键词： computers Smart cities Microprocessors Prototypes computer architecture Hardware Central processing Unit

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Energy data anomaly detection based on association rule data mining 7

Energy data anomaly detection based on association rule data...

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7th international conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Wang, Dandan Zhang, Jiexing Wang, Yi Chang, Di Wang, Wei Cui, Xiaomeng Tianjin Sanyuan Electric Information Technology Co. Ltd Tianjin China

ISBN: (纸本)9781665478571

In recent years, the world has seen rapid advances in science and technology, and the level of automation in power plants has increased. Modern power plants generate huge amounts of data every hour, which are stored in real-time databases. Due to the complexity of modern power plants and the diversity of their operating characteristics, these data include very rich but difficult to be discovered knowledge, which makes the operation and management of power plants and fault diagnosis cannot be carried out in a timely and effective manner, seriously affecting the status monitoring and diagnosis of important auxiliary equipment such as power plant fans and pumps, and cannot meet the requirements of ensuring the safe and reliable operation of auxiliary equipment. In order to effectively monitor the auxiliary equipment of power plants and predict the occurrence of faults in a timely manner, this paper uses association rule data mining to establish a model for training based on obtaining a large amount of actual historical operation data in the database of a power plant, and uses the existing operation data for model testing, so as to determine whether the equipment is in the process of fault formation. the results show that using the historical operation data of the equipment and adopting association rules for analysis can effectively reflect the relationship between the measured values and thus achieve the purpose of fault early warning. © 2022 IEEE.

关键词： Auxiliary equipment

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