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Analysis and improvement of the management system on the example of the organization of the aerospace industry

AIP Conference Proceedings 2023年第1期2700卷

作者： V. V. Kuleshov A. L. Zolkin T. G. Aygumov A. S. Bityutskiy V. N. Malikov 1Department of Industrial Ecology and Safety FSBEI HE Omsk State Technical University Omsk 644050 Russia 2Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics Samara 443010 Russia 3Department of computer engineering software and automated systems Dagestan State Technical University Makhachkala 367000 Russia 4"Invent Technology" LLP Almaty A10E5P4 Kazakhstan 5Department of General and Experimental Physics Altai State University Barnaul 656057 Russia

This study has been carried out in the organization of the aerospace industry. The scientific literature has been analysed in the article. Article shows the relevance of ongoing research on the selected topic. It was noted that there is an insufficient attention of the heads of the organization to the workers occupational health and safety. Due to the analysis of the existing occupational safety and health management system, its significant shortcomings have been identified: the use of an ineffective method of analysis of occupational risks, as well as the development of measures only on the basis of accidents and occupational diseases (lagging indicators). To improve the efficiency of the occupational safety and health management system, it was proposed to switch to proactive indicators of safety culture. For the assessment of professional risks, the “Fine Kinney” professional risk assessment method was recommended and implemented. At the same time, in order to increase the efficiency of monitoring the labour conditions management system, an audit system has been introduced, and the levels of management in the organization have been revised. The study made it possible to increase the efficiency of the occupational safety and health management system of the organization significantly. It will reduce the level of industrial injuries.

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Sum-Rate Maximization for NOMA-Assisted Pinching-Antenna Systems

arXiv

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arXiv 2025年

作者： Zhou, Ziwu Yang, Zheng Chen, Gaojie Ding, Zhiguo Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application Fujian Normal Univer sity Fuzhou350117 China Sun Yat-sen University Shenzhen518107 China Department of Computer and Information Engineering Khalifa University Abu Dhabi United Arab Emirates De partment of Electronic and Electrical Engineering The University of Manch ester ManchesterM1 9BB United Kingdom

In this letter, we investigate a non-orthogonal multiple access (NOMA) assisted downlink pinching-antenna system. Leveraging the ability of pinching antennas to flexibly adjust users’ wireless channel conditions, we formulate an optimization problem to maximize the sum rate by optimizing both the users’ power allocation coefficients and the positions of pinching antennas. The optimal power allocation coefficients are obtained in closed-form by using the Karush-Kuhn-Tucker (KKT) conditions. The optimization problem of pinching antenna placements is more challenging than the power allocation problem, and is solved by a bisection-based search algorithm. In particular, the algorithm first optimizes the antenna placements to create favorable channel disparities between users, followed by fine-tuning the antenna positions to ensure the phase alignment for users, thus maximizing the sum rate. Simulation results demonstrate that, compared to conventional-antenna systems, pinching antennas can significantly enhance the sum rate in NOMA scenarios, and the proposed bisection-based search algorithm can achieve a sum rate nearly equivalent to that of an exhaustive search. Copyright © 2025, The Authors. All rights reserved.

关键词： Learning algorithms

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Designing and testing of renewable energy based electric vehicle with GSM technology

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AIP Conference Proceedings 2023年第1期2690卷

作者： B. Senthil Kumaran J. P. Sridhar J. Kamalakannan K. V. Malini S. Monesh A. Venkata Narayana 1Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthaka R&D Institute of Science and Technology Avadi Chennai–600 062Tamil Nadu India 2Department of Electrical and Electronics Engineering SJB Institute of Technology Bangalore - 560060 Karnataka India 3Department of Mechanical Engineering GKM College of Engineering and Technology G.K.M. Nagar Perungalathur Chennai Tamil Nadu 600063 India 4Department Electrical and Electronics Engineering Sri Sairam College of Engineering Anekal Bangalore 562106 Karnataka India 5Department of Computer Science and Engineering Jerusalem College of Engineering Chennai 600100 India 6Department of Biotechnology Vignan’s Foundation for Science Technology & Research (Deemed to be University) Vadlamudi Guntur-522213 Andhra Pradesh India

The ability to drive a car is a significant step toward independence for individuals with impairments, however, the standard driving system placed in a car does not provide the functionality for the challenged driver to operate the vehicle. Hence, in this project, we focused on designing a prototype of a car that works with the help of renewable energy like solar for people who have disabilities related to their legs or arms. It will be very helpful for those people who have physical disabilities to drive from one place to another without counting on anybody. The research shows that the issues about sustainable mobility are gaining increasing attention both in public opinion and specialists because of the major impact of automotive systems on carbon Dioxide production, climate change (global warming), and fuel exhaustion. So, by using renewable energy such as solar energy as source power it helps pollution-free, sustainable, and causes no greenhouse gases which will save the environment in the future. Probably the best development in the clinical field that helped both the old and the impeded is the portability vehicle. The expense of the vehicle may not be reasonable for an average person. In this case, an endeavor is made to manufacture a Solar Electric vehicle for disabled people at an ideal cost that can be used easily. It ensures the physically challenged people to be comfortable in travel and life. As solar energy is the main source on which we are focusing nowadays, because of many reasons like pollution, cost of fuel and also due to unavailability of the fuels. In the future solar energy will be the major source. The features have made in this solar electric vehicle are intelligent ones and are very useful for physically disabled people who want to be independent. In addition to that, the GSM is attached to the vehicle for monitoring disabled people. If the vehicle got any damage or the people is in out of control or any other irregular activities are found

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Fatigue detection using artificial intelligence

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AIP Conference Proceedings 2022年第1期2393卷

作者： Pravin R. Kshirsagar Pankaj Dadheech T. Yuvaraj C. A. Sathiya Moorthy Makarand Upadhyaya 1Department of Electronics and Communication Engineering AVNIET Hyderabad India 2Computer science & Engineering Swami Keshvanand institute of technology Jaipur Rajasthan India 3Department of Electrical and Electronics Engineering Saveetha School of Engineering Chennai India 4Department of Electronics and Communication Engineering CMS College of engineering India 5Department of management & marketing University of Bahrain Bahrain

Over the years the development of computer technology has benefited drivers, often in the form of smart systems. In a significant number of car collisions, tiredness is a major factor. Road collisions are the world's most frequent types of injuries and fatalities, and the main causes are typically drunken, sleepy, and rudely behavioral. The main purpose of this article is to define common sources of knowledge for the detection of drowsiness to evaluate when a specified degree of drowsiness is achieved. Fatigue was one of the key techniques for detecting or tracking augmented reality. In particular, driver drowsiness identification can protect riders from drowsy riding collisions. This technology relies on face detection to warn the driver of somnolence or to avoid accidents in traffic.

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Structural block driven - Enhanced convolutional neural representation for relation extraction

arXiv

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arXiv 2021年

作者： Wang, Dongsheng Tiwari, Prayag Garg, Sahil Zhu, Hongyin Bruza, Peter Department of Computer Science University of Copenhagen Copenhagen Denmark Department of Information Engineering University of Padova Padova Italy École de Technologie Supérieure MontréalQCH3C 1K3 Canada Institute of Automation Chinese Academy of Sciences Beijing China School of Information Systems Queensland University of Technology 2 George St Brisbane CityQLD4000 Australia

In this paper, we propose a novel lightweight relation extraction approach of structural block driven - convolutional neural learning. Specifically, we detect the essential sequential tokens associated with entities through dependency analysis, named as a structural block, and only encode the block on a block-wise and an inter-block-wise representation, utilizing multi-scale Convolutional Neural Networks (CNNs). This is to 1) eliminate the noisy from irrelevant part of a sentence;meanwhile 2) enhance the relevant block representation with both block-wise and inter-block-wise semantically enriched representation. Our method has the advantage of being independent of long sentence context since we only encode the sequential tokens within a block boundary. Experiments on two datasets i.e., SemEval2010 and KBP37, demonstrate the significant advantages of our method. In particular, we achieve the new state-of-the-art performance on the KBP37 dataset;and comparable performance with the state-of-the-art on the SemEval2010 dataset. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolution

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Covid heuristic analysis using machine learning

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AIP Conference Proceedings 2022年第1期2393卷

作者： Pravin R. Kshirsagar Makarand Upadhyaya Pankaj Dadheech T. Yuvaraj C. A. Sathiya Moorthy 1Department of Electronics and Communication Engineering AVNIET Hyderabad India 2Department of management & marketing University of Bahrain Bahrain 3Computer science & Engineering Swami Keshvanand institute of technology Jaipur Rajasthan India 4Department of Electrical and Electronics Engineering Saveetha School of Engineering Chennai India 5Department of Electronics and Communication Engineering CMS College of engineering Namakkal India

The newer avid-19 corona virus created havoc for patients with a variety of complications that prompted health practitioners around the world to develop new technologies and treatment plans. Technologies based on Machine Learning (ML) have been a major factor in addressing complex issues and many businesses have been able to develop and adapt to the COVID-19 challenges. The diagnosis of illness can be used with different AI methods to monitor the present havoc. Since Machine Learning (ML) approaches have been commonly used in other domain fields, a great deal of demand is now being made for ML-supported diagnostic systems to screen, monitor, and forecast void-19 spread and find a cure. The article presents an overview of the role of ML to combat the virus so far, especially from the perspective of screening, prognosis, and vaccine.

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High performance polarization management devices based on thin-film lithium niobate

arXiv

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arXiv 2021年

作者： Lin, Zhongjin Lin, Yanmei Li, Hao Xu, Mengyue He, Mingbo Ke, Wei Li, Zhaohui Wang, Dawei Yao, X. Steve Yu, Siyuan Cai, Xinlun State Key Laboratory of Optoelectronic Materials and Technologies School of Electronics and Information Technology Sun Yat-sen University Guangzhou510275 China Department of Electrical and Computer Engineering The University of British Columbia VancouverBCV6T 1Z4 Canada Photonics Information Innovation Center Hebei Provincial Center for Optical Sensing Innovations College of Physics Science and Technology Hebei University Baoding071002 China

High-speed polarization management is highly desirable for many applications, such as remote sensing, telecommunication, and medical diagnosis. However, most of the approaches for polarization management rely on bulky optical components that are slow to respond, cumbersome to use, and sometimes with high drive voltages. Here, we overcome these limitations by harnessing photonic integrated circuits based on thin-film lithium niobate platform. We successfully realize a portfolio of thin-film lithium niobate devices for essential polarization management functionalities, including arbitrary polarization generation, fast polarization measurement, polarization scrambling, and automatic polarization control. The present devices feature ultra-fast control speed, low drive voltages, low optical losses and compact footprints. Using these devices, we achieve high fidelity polarization generation with a polarization extinction ratio up to 41.9 dB, fast polarization scrambling with a scrambling rate up to 65 Mrad/s, and endless polarization control with a tracking speed up to 10 Krad/s, all of which are best results in integrated optics. The demonstrated devices unlock a drastically new level of performance and scales in polarization management devices, leading to a paradigm shift in polarization management. © 2021, CC BY.

关键词： Thin films

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A mathematical model for multi-item inventory- and price-dependent demands with all-units discount

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AIP Conference Proceedings 2022年第1期2641卷

作者： J. Dharma Lesmono Taufik Limansyah Febrizio Willem Ong Ign. Sandy 1Department of Mathematics Faculty of Information Technology and Sciences Universitas Katolik Parahyangan Jl. Ciumbuleuit No. 94 Bandung 40141 Indonesia 2Department of Industrial Technology Faculty of Industrial Engineering Universitas Katolik Parahyangan Jl. Ciumbuleuit No. 94 Bandung 40141 Indonesia

Inventory control problem becomes one of the most crucial parts in a company. Basically, the problem is to determine the optimal time and quantity of replenishment. But, there are many factors affected the decision such as demand uncertainty, lifetime of the product, deterioration, unit sales price and discount offered by the supplier. In this paper, we consider a mathematical model for inventory control problem. We consider a multi-item problem with inventory and price-dependent demand and all-units discount offered by the supplier. In dealing with multi-item problem, there are two replenishment policies to consider, individual order and joint order policy. Numerical examples are given with different inventory and price-dependent demand functions for each item and compare the individual and joint order policy. We found that in our numerical example, joint replenishment policy gives lower total inventory cost compared to the individual order policy.

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Low Earth Orbit Satellite Security and Reliability: Issues, Solutions, and the Road Ahead

arXiv

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arXiv 2022年

作者： Yue, Pingyue An, Jianping Zhang, Jiankang Ye, Jia Pan, Gaofeng Wang, Shuai Xiao, Pei Hanzo, Lajos The School of Information and Electronics Beijing Institute of Technology Beijing100081 China The School of Cyberspace Science and Technology Beijing Institute of Technology Beijing100081 China The Department of Computing and Informatics Bournemouth University BournemouthBH12 5BB United Kingdom The school of Electrical Engineering Chongqing University Chongqing400044 China The 5GIC & 6GIC Institute for Communication Systems University of Surrey GU2 7XH United Kingdom The School of Electronics and Computer Science University of Southampton SouthamptonSO17 1BJ United Kingdom

Low Earth Orbit (LEO) satellites undergo a period of rapid development driven by ever-increasing user demands, reduced costs, and technological progress. Since there is a lack of literature on the security and reliability issues of LEO Satellite Communication Systems (SCSs), we aim to fill this knowledge gap. Specifically, we critically appraise the inherent characteristics of LEO SCSs and elaborate on their security and reliability requirements. In light of this, we further discuss their vulnerabilities, including potential security attacks launched against them and reliability risks, followed by outlining the associated lessons learned. Subsequently, we discuss the corresponding security and reliability enhancement solutions, unveil a range of trade-offs, and summarize the lessons gleaned. Furthermore, we shed light on several promising future research directions for enhancing the security and reliability of LEO SCSs, such as integrated sensing and communication, computer vision aided communications, as well as challenges brought about by mega-constellation and commercialization. Finally, we summarize the lessons inferred and crystallize the take-away messages in our design guidelines. Copyright © 2022, The Authors. All rights reserved.

关键词： Satellite communication systems

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Meta-analysis of computational methods for breast cancer classification

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International Journal of Intelligent information and Database Systems 2020年第1期13卷 89-111页

作者： Pham, Tri-Cong Luong, Chi-Mai Doucet, Antoine Hoang, Van-Dung Tran, Diem-Phuc Le, Duc-Hau School of Computer Science and Engineering Thu-yloi University 175 Tay Son Dong Da Hanoi Viet Nam Department of Informatics and Communication Technology University of Science and Technology of Hanoi Hanoi Viet Nam Vietnam Academy of Science and Technology 18 Hoang Quoc Viet Cau Giay Hanoi Viet Nam Institute of Information Technology Vietnam Academy of Science and Technology 18 Hoang Quoc Viet Cau Giay Hanoi Viet Nam Laboratory L3i University of La Rochelle France QuangBinh University Dong Hoi Quang Binh Viet Nam DuyTan University Da Nang Viet Nam Department of Computational Biomedicine Vingroup Big Data Institute No 7 Bang Lang 1 Street Viet Hung Ward Hanoi Viet Nam

Millions of women are suffering from breast cancer pressing burden on their shoulders and the global economy. Meanwhile, general treatment methods are applied without considering personalised health and genetic features. Artificial intelligence appears to be a robust method for breast cancer sub-typing. Most of researches have been implemented on binary classification with limited number of data samples. Multi-classification is much more difficult especially on large number of samples. The study aims to use machine learning to find better ways to subtype breast cancer as well as find new disease causative genes which help facilitate more personalised treatment with limited side effect in the future. This study compares the accuracy of three classification methods in combination with eight feature selection methods on a dataset of 2,682 samples. The study shows that the highest accuracy was 83.96% with the SVM-C005 classifier and percentile feature selection (800 genes). Additionally, our method can predict causative disease genes of breast cancer with four of them known to be associated with breast cancer and 29 promising ones with supporting evidence from the literature. This shows the effectiveness of our research. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Gene expression

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