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Equipment for Increasing the Phototrophic Microalgae Production at Lab Scale

Equipment for Increasing the Phototrophic Microalgae Product...

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2023 IEEE international conference on Electrical, computer and Energy Technologies, ICECET 2023

作者： Voina, Andreea Tókos, Atrila Jipa, Monica Circiumaru, Gabriela Bartha, Csaba Chihaia, Rareş-Andrei Tǎnase, Nicolae Lingvay, Iosif Nat. Inst. for R&d in Electrical Engineering ICPE-CA Bucharest Quality Management. Environment Dept. Bucharest Romania R&d Institute-ICPE Bistrita S.A. Electrical & Automation Dept. Bistrita Romania R&d Institute-ICPE Bistrita S.A. Wastewater Treatment Dept. Bistrita Romania Nat. Inst. for R&d in Electrical Engineering ICPE-CA Bucharest Renewable Sources and Energy Efficiency Dept. Bucharest Romania

ISBN: (纸本)9798350327816

The human activities, especially the energy production from fossil fuels and the transport sector, produce huge amounts of CO2, which is a greenhouse gas [1]. In this context, developing and expanding phototrophic microalgae production is a suitable way to reduce the greenhouse effect by converting the anthropogenic CO2 into organic mass and oxygen. It should be also mentioned that the organic mass, including algae, is a high added value product. © 2023 IEEE.

关键词： Chlorella sp ELF electric field greenhouse effect microalgae photobioreactor

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Multi-population particle swarm optimization concerning the worst information 3

Multi-population particle swarm optimization concerning the ...

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3rd international conference on computer Vision and Pattern Analysis, ICCPA 2023

作者： Li, Haiyan Chen, Yanbo Sun, Jiulin Li, Mi Department of Automation Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing International Collaboration Base on Brain Informatics and Wisdom Services Beijing100124 China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing100124 China Engineering Research Center of Digital Community Ministry of Education Beijing100124 China

ISBN: (纸本)9781510667563

Currently, the majority of multi-population algorithms ignore the worst particles and instead learn from the gbest or lbest. Hence, it is simple for these strategies to result in inadequate population variety, which causes early convergence. A multi-population particle swarm optimization considering the worst particles into account (CWMPSO) is suggested to demonstrate the importance of the worst particle information. In addition to considering the best particle, the CWMPSO algorithm concentrates on the worst particle globally. The algorithm divides the population into three subgroups, which learns from the gbest, gworst, and gbest + gworst, respectively. The development of the global worst particle information can be achieved by group learning, allowing for a more thorough exploration of potential optimum solutions and an avoidance of local functional ones. 30 complex CEC2017 benchmark functions were used in this work to test a range of algorithms including CWMPSO with various dimensions. The outcomes demonstrate that, in every dimension, the CWMPSO algorithm is better than other advanced PSOs. © 2023 SPIE.

关键词： Particle swarm optimization (PSO)

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Reliable node localization algorithm for WSN based on weighted AHP-GRA 5

Reliable node localization algorithm for WSN based on weight...

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5th international conference on Artificial Intelligence and computer Science, AICS 2023

作者： Li, Yi Jiangsu Automation Research Institute Jiangsu Lianyungang222000 China

ISBN: (纸本)9781510668621

Target localization is one of the most widespread applications of WSN (Wireless Sensor Network). However, in a number of specific harsh scenarios, physical location of anchor node may drift because of influence of external environment or human factors, which in turn leads to the estimated location of unknown node is not accurate. Therefore, a reliable node localization algorithm for WSN based on weighted AHP-GRA is proposed in this paper. Firstly, distance change among nodes in localization scenarios is counted and reference sequence is constructed, then comprehensive influence matrix is obtained by environmental factors. Next, the weighted comprehensive influence matrix is further obtained by combining the two. After that, the node confidence level is obtained based on AHP-GRA, and three reliable nodes with the highest confidence level are taken as anchor nodes to complete localization by using trilateral localization method. Simulation results show that the algorithm in this paper effectively improves localization effect of WSN in complex scenes. Compared with other algorithms, the algorithm in this paper has great advantages in selection of reliable nodes, localization accuracy, and localization coverage. © 2023 SPIE.

关键词： Analytic hierarchy process

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Capsule Network based 3D Object Orientation Estimation

Capsule Network based 3D Object Orientation Estimation

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2023 international conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Hollósi, János Ballagi, Áron Pozna, Claudiu Radu Széchenyi István University Department of Information Technology Gyor Hungary Széchenyi István University Department of Automation Gyor Hungary

ISBN: (纸本)9798350322972

Convolutional neural networks have proven to be one of the most efficient methods for processing visual data. Due to the popularity of the field, there is a growing interest in the reliability of intelligent systems. It has been shown that convolutional neural networks can be fooled by extreme inputs or noisy inputs. To overcome the current problems of convolutional neural networks, the theory of capsule networks was introduced by Geoffrey Hinton and his research team. In this work we want to investigate the theory of capsule networks for orientation recognition of 3-dimensional objects. We consider the case when the data are noise loaded by various adversarial attacking methods. We compare our results with the efficiency of convolutional neural network based solutions, highlighting the difference between the two theories. We investigate the efficiency reduction that can be observed using different adversarial attacking methods. Our results will show how much more efficient the capsule network is compared to the neural networks. © 2023 IEEE.

关键词： Routing algorithms

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Sharper Specs for Smarter Drones: Formalising Requirements with FRET 31st

Sharper Specs for Smarter Drones: Formalising Requirements ...

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31st international Working conference on Requirements engineering: Foundation for Software Quality, REFSQ 2025

作者： Sheridan, Oisín Becker, Leandro Buss Farrell, Marie Luckcuck, Matt Monahan, Rosemary Department of Computer Science Maynooth University Maynooth Ireland Automation and Systems Department Federal University of Santa Catarina Florianópolis Brazil Department of Computer Science The University of Manchester Manchester United Kingdom School of Computer Science University of Nottingham Nottingham United Kingdom

ISBN: (纸本)9783031885303

[Context and motivation] Software requirements are commonly expressed in natural-language, which must be formalised if they are to be used by formal methods such as Runtime Verification (RV), where we verify that an implementation obeys its requirements during execution. [Question/problem] This paper reports on our experience of using the Formal Requirements Elicitation Tool (FRET) to formalise requirements for an autonomous tilt-rotor drone in the ProVANT Emergentia research project. Structured, formalised requirements help to refine the meaning of, and discover ambiguities in, a requirements set, which is beneficial for safety-critical systems. FRET generates a temporal logic semantics for each requirement, providing formulas that can be used for RV. [Principal ideas/results] We describe the process of formalising the natural-language requirements using FRET. We present the progress made in each of the four versions of the requirements set as new information was elicited and incorporated. Our two concrete outputs are the formalised requirement set, which we will use in our ongoing development and verification of ProVANT;and metrics about the requirements. [Contribution] From our experience, we present guidance for requirements elicitation and formalisation with FRET. We highlight situations where it was difficult to formalise these requirements and describe potential improvements to FRET to address these difficulties. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Drones

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Acupoint classification method based on improved support vector machine 5

Acupoint classification method based on improved support vec...

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5th international conference on Artificial Intelligence and computer Science, AICS 2023

作者： Tu, Juan Dai, Zunxiang Chen, Jianguo College of Electrical Engineering and Automation Fuzhou University Fuzhou350108 China Fujian Provincial Key Laboratory of Medical Instrument and Pharmaceutical Technology Fuzhou350108 China

ISBN: (纸本)9781510668621

Acupoint potential signal is a kind of bioelectric signal collected on the skin surface, which has the characteristics of weak signal, strong noise and strong randomness. These characteristics make it difficult to extract acupoint features, which further affects the accuracy of acupoint classification. This paper proposes an acupoint classification method combining signal processing with intelligent algorithm. Firstly, the signal is decomposed by CEEMDAN (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise), and the decomposed IMFs (Intrinsic Mode Functions are obtained). Secondly, the filtered modal set is taken as input, and the features are extracted by using Convolutional Neural Networks (CNN) to get its deeper features. Finally, the obtained feature parameters are input into the support vector machine (SVM) optimized DBO:(Dung Beetle Optimizer) for classification. The experimental results show that CEEEMDAN-CNN-DBO-SVM model can effectively identify the types of acupoints, with an average accuracy rate of 93.01% at rest and 90.6% at click stimulation. The effect is better than CNN, SVM, CEEMDAN-CNN, CEEMDAN-SVM, CNN-SVM and other five classification methods. © 2023 SPIE.

关键词： Empirical mode decomposition

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Design of Multi-Channel Data Transmission System Based on PCIe-SRIO 3

Design of Multi-Channel Data Transmission System Based on PC...

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3rd international conference on Electronic Information engineering and computer Communication, EIECC 2023

作者： Wang, Fuge Liu, Jianxin Ling, Yunzhi Zhuo, Qingkun Jiangsu Automation Research Institute Lianyungang China

ISBN: (纸本)9798350359961

In order to meet the long-distance and high-reliable transmission needs of multi- channel data, a multi-channel data transmission system based on PCIE-SRIO is designed. The Xilinx K7 series FPGA chip is designed, and the internal integrated PCIe and SRIO IP cores are used, and then the optical cable is connected to the optical cable to achieve long -range data sending and receiving. The system is based on the PCIe bus to realize the interconnection between the CPU chip and the FPGA chip, and the FPGA actively initiates and terminates the DMA transmission method to realize the high-speed interaction of multiple channels of data between the CPU chip and the FPGA chip. The internal logic of FPGA realizes SRIO interface based on HELLO packet format, and the sender uses Round-Robin arbitration mechanism to design multi-interface, which realizes the com-petition processing when multi-channel interfaces share a SRIO interface to send data at the same time. The results show that the designed system can realize data sending and receiving under 8 channels at most, which has certain reference significance for the application of long-distance transmission of interconnected data between boards. © 2023 IEEE.

关键词： component data transmission system multi-channel PCIe SRIO

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A Review of Fault Diagnosis Based on Siamese Neural Networks 3

A Review of Fault Diagnosis Based on Siamese Neural Networks

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3rd international conference on Machine Learning and computer Application, ICMLCA 2022

作者： Yang, Qing Wang, Defang Wu, Dongsheng Dong, Yansong School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China

ISBN: (纸本)9781510664814

In the last few years, mechanical fault diagnosis (FD) based on deep learning has been systematically applied to various industrial fields. However, most methods rely on enough labeled data, but collecting enough sample of failure is time-consuming and labor-intensive. It remains challenging to train a model for FD with numbered training data and to function correctly under intricate operating scenario. In response to this problem, the FD method based on Siamese neural network (SNN) has shown promising results in recent years, especially in the case of insufficient training samples;the fault diagnosis work has achieved good results and has been widely concerned by researchers at domestic and foreign. To better combine the SNN for fault diagnosis and give full play to the advantages of the SNN in fault diagnosis, this paper summarizes and analyzes the fault diagnosis methods based on SNN. Firstly, the basic framework of the SNN method is introduced, and the advantages and application scenarios of the framework are pointed out. Secondly, the existing fault diagnosis methods based on SNN are classified, including the principle of the technique, improved methods, and shortcomings. Finally, the FD methods based on SNN are summarized, and the development of the SNN in FD is in prospect. © 2023 SPIE.

关键词： Failure analysis

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AI-Enabled automation Solution for Utilization Management in Healthcare Insurance 1st

AI-Enabled Automation Solution for Utilization Management in...

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1st EAI international conference on Intelligent Systems and Machine Learning, ICISML 2022

作者： Karki, Gaurav Simha, Jay Bharateesh Agarwal, Rashmi REVA University Bengaluru India

ISBN: (纸本)9783031350801

As businesses advance toward digitalization by automating an increasing number of procedures, unstructured forms of text in documents present new challenges. Most organizational data is unstructured, and this phenomenon is on the rise. Businesses like healthcare and insurance are embracing business process automation and making considerable progress along the entire value chain. Artificial intelligence (AI) algorithms that help in decision-making, connect information, interpret data, and apply the insights gained to rethink how to make better judgments are necessary for business process automation. A healthcare procedure called Prior Authorization (PA) could be made better with the help of AI. PA is an essential administrative process that is a component of their utilization management systems, and as a condition of coverage, insurers require providers to obtain preapproval for the provision of a service or prescription. The processing of insurance claim documents can be facilitated using Natural Language Processing (NLP). This paper describes the migration of manual procedures to AI-based solutions in order to accelerate the process. The use of text similarity in systems for information retrieval, question-answering, and other purposes has attracted significant research. This paper suggests using a universal sentence encoder, a more focused strategy, to handle health insurance claims. By extracting text features, including semantic analysis with sentence embedding, the context of the document may be determined. The outcome would have a variety of possible advantages for members, providers, and insurers. AI models for the PA process are seen as promising due to their accuracy and speed of execution. © 2023, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： automation

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Efficient Application Deployment: GitOps for Faster and Secure CI/CD Cycles

Efficient Application Deployment: GitOps for Faster and Secu...

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2024 international conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Saikiran Reddy, J. Durga Prashanth Padal, S. Albert Mayan, J. Catharine, A. Shanthamalar, J. Jeslin Sathyabama Institute Of Science And Technology Department Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350371567

In the rapidly evolving landscape of technology, the need for swift and efficient deployment of software and applications has never been more critical. Due to the rapid and constant evolution of innovation, there is a consistent demand for quicker, seamless deployment of software and apps. Currently, most of the programming and applications are designed in such a manner that they may encounter diverse operational scenarios. The current study explores the crucial significance of agile approaches, with a particular emphasis on GitOps integration as a paradigm-shifting strategy in the modern software development environment. Leveraging DevOps best practices to underpin automation, GitOps is a useful solution that provides a way to accomplish safer and more efficient system cycles. Teams may improve security and viability while accelerating arrangement times by using Git as the one source of truth for foundation and application code through the use of GitOps. In order to improve the CI/CD pipeline and enable a more automated, straightforward, and simple exporting technique, this paper explores the potential real-world applications of GitOps concepts in AI application design. It looks at how agile approaches and GitOps practices work together to address the various and multifaceted problems that modern programming development encounters. The main emphasis is on how these approaches may guarantee a high level of adaptability and readiness in a technological environment that is always changing, in addition to being able to react quickly to changes. The aim is to explore innovative strategies and methods to enhance the speed and efficiency of software and application delivery, while examining the complexities of a constantly evolving technological landscape. © 2024 IEEE.

关键词： Machine learning

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