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BioAR: Bio-Laboratory Automation Meets Augmented Reality 14th

BioAR: Bio-Laboratory Automation Meets Augmented Reality

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14th international conference on Genetic and Evolutionary computing, ICGEC 2021

作者： Zou, Zheng Liu, Shi-Jian College of Computer and Cyber Security Fujian Normal University No. 8 Xuefu South Road Fujian Shangjie Minhou Fuzhou China Fujian Provincial Engineering Technology Research Center for Public Service Big Data Mining and Application Fujian Normal University No. 8 Xuefu South Road Fujian Shangjie Minhou Fuzhou China Digital Fujian Institute of Big Data Security Technology Fujian Normal University No. 8 Xuefu South Road Fujian Shangjie Minhou Fuzhou China College of Computer Science and Mathematics Fujian University of Technology No. 3 Xueyuan Road University Town Fujian Minhou Fuzhou China

ISBN: (纸本)9789811684296

Modern laboratory is benefiting from science and engineering by adopting automated systems into labor-intensive lab routines. In this paper, a computer-aided system that involves augmented reality (AR) to promote the automatic levels of the bio-laboratory is introduced. The motivation of this work lies in the idea of offering visual guidance for users to pick a tube manually from the rack after the retrieval. Because it is difficult for people to tell the target tube from the others since they look almost the same. Design issues and implementation details are given after a careful analysis of the system requirements. The BioAR system is tested out and successfully applied to a bio-laboratory with tube related operations, whose performance is approved by the technicians. A video demo of the proposed system can be found at https://***/video/BV1FX4y157WB/. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Augmented reality

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Environment control using Forecasting Algorithm by Real Time Data Analysis for automatic Cultivation System 7

Environment Control using Forecasting Algorithm by Real Time...

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7th international conference on engineering, Applied sciences and Technology, ICEAST 2021

作者： Juleang, Pakorn Mitatha, Somsak Ramkhamhaeng University Faculty of Science Electronics Technology Department Bangkok10240 Thailand King Mongkut's Institute of Technology Ladkrabang Hybrid Computing Research Laboratory Faculty of Engineering Bangkok10520 Thailand

ISBN: (纸本)9781665441223

A new automatic cultivation system was proposed using a forecasting algorithm for environmental control. Information used for the forecast was taken from real time data obtained by a wireless sensor system. The objective was the automation of suitable environmental cultivation methods. The proposed forecasting algorithm used historical data to predict future environmental control according to its goals. A real system was implemented and constructed to test the hypothesis. Results showed that the system had the required features. Environmental controls of the original system were compared with the proposed algorithm according to the created thresholds. The proposed forecasting algorithm controlled humidity in the soil at 98.26%, while the original system recorded do 69.33%, with humidity in the air controlled at 93.87% compared to the original system at 48.96%. This algorithm will be very useful to promote sustainable agriculture. © 2021 IEEE.

关键词： Cultivation

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QoS-Aware TAS Scheduling Algorithm with Latest-Data-Only Transmission 11

QoS-Aware TAS Scheduling Algorithm with Latest-Data-Only Tra...

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11th international conference on Mechatronics and Robotics engineering, ICMRE 2025

作者： Choi, Hyeok Jun Lim, Seong Hyeon Do, Young Soo Oh, Sung Bhin Lim, Se Jeong Jeon, Jae Wook Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798331509293

Recent advances in autonomous driving and Advanced Driver Assistance System (ADAS) technologies are expanding in-vehicle entertainment capabilities, and vehicles are evolving beyond simple transport to become multi-functional entertainment systems. These changes have pushed the limits of existing vehicle networks, making the introduction of automotive Ethernet essential for high-bandwidth data transmission. Time-Sensitive Networking (TSN) technology was introduced to address Ethernet real-time issues. Time-Aware Shaper (TAS) supports deterministic data transmission by using a time-triggered scheduler to control queue gates to ensure that traffic types are transmitted in designated time slots. However, when TAS is applied, short cycles of scheduled traffic or time synchronization errors cause scheduled traffic, such as control data, to arrive and stack up in non-scheduled traffic time slots. This may cause the accumulated scheduled traffic to be transmitted at once at the beginning of the next scheduled traffic time slot, resulting in malfunction. To solve these problems, this paper proposes a QoS-aware TAS scheduling algorithm with Latest-Data-Only transmission. This prevents malfunctions caused by temporary transmission of scheduled traffic and improves network QoS. The proposed algorithm is expected to be applicable not only to vehicles, but also to various fields such as industrial automation and robots where real-time control is important. © 2025 IEEE.

关键词： Advanced driver assistance systems

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Securing Complex IoT Platforms with Token Based Access control and Authenticated Key Establishment

Securing Complex IoT Platforms with Token Based Access Contr...

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Sustainable computing and Integrated Communication in Changing Landscape of AI (ICSCAI), international conference on

作者： P. William Arnav Kotiyal Hassan M. Al-Jawahry Anurag Shrivastava Kanchan Yadav Kilaru Aswini Department of Information Technology Sanjivani College of Engineering Pune Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun Department of computers Techniques engineering College of technical engineering The Islamic university Najaf Iraq Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu Department of Electrical Engineering GLA University Mathura Institute of Aeronautical Engineering Hyderabad

ISBN: (数字)9798350355338

ISBN: (纸本)9798350355345

The functionality of a security architecture for advanced Internet of Things (IoT) devices is discussed in this article. Validated key configuration and access control that is based on tokens are absolutely necessary in order to guarantee the safety of this idea. In order to keep up with the rapid proliferation of the IoT ecosystem, it is imperative that the availability, integrity, and security of data be maintained at all times. Token-based access control is an opportunity to provide a workable solution to one of the most common concerns raised about the safety of the internet of things (IoT). This article's objective is to improve the safety of the Internet of Things (IoT) by analyzing the guiding principles, implementation tactics, and benefits offered by a variety of security measures that may be included into complex IoT systems. In this article, we explain how token-based access control and verified key generation may be merged into a single, all-encompassing method to strengthen the safety of platforms used for the internet of things (IoT). Token-based access control provides flexibility and adaptability when it comes to regulating rights in dynamic settings that are linked to the Internet of Things. In order to shield oneself from potential dangers such as man-in-the-middle attacks, one must take the necessary precautions, such as generating authorized keys to keep the privacy of one's communication routes secret. This research uses performance measurements, comparisons of code sizes, and statistical analysis to evaluate and examine the efficacy and efficiency of a variety of different security methods. The findings demonstrate how readily the recommended methodology may be adapted to meet the requirements of a wide variety of Internet of Things (IoT) systems. This paper is a helpful resource for enterprises and developers who work in dynamic situations and are interested in strengthening the security of Internet of Things deployments.

关键词： Access control Codes Statistical analysis Smart cities Process control Safety Internet of Things Security Cryptography Protection

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Laser Engraving for 3D Surfaces: A Robotized Application Case Study 16th

Laser Engraving for 3D Surfaces: A Robotized Application Ca...

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16th APCA international conference on automatic control and Soft computing, controlO 2024

作者： Alvarez, Mariano Brancalião, Laiany Carneiro, Jorge Costa, Paulo Coelho, João Paulo Gonçalves, José Instituto Politécnico de Bragança Campus de Santa Apolónia Bragança5300-253 Portugal Instituto Politécnico de Bragança Campus de Santa Apolónia Bragança5300-253 Portugal Faculty of Engineering of the University of Porto Porto4200-465 Portugal University of Léon Campus de Vegazana s/n León24071 Spain GRESTEL – Produtos Cerâmicos S.A. Vagos Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal

ISBN: (纸本)9783031817236

One of the industry’s most common applications of lasers is engraving, which is generally performed on flat surfaces. However, there are many situations where the object to be engraved has an unevenly curved geometry. In those cases, the light power density will be different along the surface for a fixed head, leading to a poor engraving result. This work deals with this problem by designing a robotic application capable of detecting variations on the object surface and automatically creating a trajectory to engrave on it correctly. This was made possible through a robotic manipulator, a time-of-flight distance sensor, and a data processing algorithm over the measured data. Obtained results were acquired using a custom-made test rig and validated by delivering consistent engraving results on irregular surface shapes. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Robotic assembly

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Smart Monitoring and Diagnostics for Fault Detection in Power Plant Equipment

Smart Monitoring and Diagnostics for Fault Detection in Powe...

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Distributed computing and electrical Circuits and Electronics (ICDCECE), IEEE international conference on

作者： S. Padma Kala Pradeep Kumar S G. Meerimatha Muntather Almusawi Sasikumar Gurumoorthy Dept of CSE Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai Tamilnadu India Department of ECE Nitte Meenakshi Institute of Technology Bengaluru India Department of EEE Srinivas Ramanujan Institute of Technology (Autonomous) Ananthapuramu India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Computer Science and Engineering School of Engineering and Technology Dhanalakshmi Srinivasan University Tiruchirappalli Tamil Nadu India

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

In recent years, Fault Diagnosis and Identification (FDI) has grown significantly. Generally used methodology in these types of frameworks include model-based approaches, fault approaches, and pattern recognition techniques. However, it was essential to society's energy supply, therefore maintaining its safe and effective functioning is of utmost importance. This research used sophisticated Fault Detection and Diagnosis (FDD) methods to diagnose the problems in contemporary power plants in order to decrease maintenance shutdowns and expenses. Therefore, this research applied deep learning to image processing using efficient Long Short-Term Memory (LSTM)-based methods for object recognition and categorization. Using the observed frequency as input, the trained LSTM is utilized to detect power variations in real time. control devices, such as synchronous generators and Energy Storage Systems (ESSs), was maintain a steady frequency by using the detected power variations. According to the results, the suggested approach demonstrated superior performance in terms of LG faults, with 0.427%, LLG faults of 0.800%, LGG faults of 0.186 %, and LL faults of 0.741%. Compared with existing methods namely Sparrow Search Algorithm (SSA) and Deep Long Short-Term Memory (LSTM) it shows that suggested methods are achieved better performances with less faults respectively.

关键词： Deep learning Time-frequency analysis Fault detection Computational modeling Synchronous generators Maintenance Circuit faults

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Human sentiments monitoring during COVID-19 using AI-based modeling 17

Human sentiments monitoring during COVID-19 using AI-based m...

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17th international conference on Future Networks and Communications / 19th international conference on Mobile Systems and Pervasive computing / 12th international conference on Sustainable Energy Information Technology, FNC/MobiSPC/SEIT 2022

作者： Umair, Areeba Masciari, Elio Department of Electrical Engineering and Information Technologies University of Naples Federico II Naples80125 Italy National Research Council Naples Italy

The whole world is facing health challenges due to wide spread of COVID-19 pandemic. To control the spread of COVID-19, the development of its vaccine is the need of hour. Considering the importance of the vaccines, many industries have put their efforts in vaccine development. The higher immunity against the COVID can be achieved by high intake of the vaccines. Therefore, it is important to analysis the people's behaviour and sentiments towards vaccines. Today is the era of social media, where people mostly share their emotions, experience, or opinions about any trending topic in the form of tweets, comments or posts. In this study, we have used the freely available COVID-19 vaccines dataset and analysed the people reactions on the vaccine campaign using artificial intelligence methods. We used TextBlob() function of python and found out the polarity of the tweets. We applied the BERT model and classify the tweets into negative and positive classes based on their polarity values. The classification results show that BERT has achieved maximum values of precision, recall and F score for both positive and negative sentiment classification. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the conference Program Chairs.

关键词： COVID-19

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Determining on-shelf availability based on RGB and ToF depth cameras 23

Determining on-shelf availability based on RGB and ToF depth...

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23rd international conference on control Systems and Computer science Technologies, CSCS 2021

作者： Craciunescu, Mihai Baicu, Diana Mocanu, Stefan Dobre, Cristian Faculty of Automatic Control and Computer Science Department of Automatic Control and Applied Informatics Bucharest Romania Rinftech Bucharest Romania

ISBN: (纸本)9781665439398

In this paper, a method of calculating the occupancy of a shelf will be presented. A vision pillar composed of two RGB cameras and two ToF depth cameras will be used to scan a shelf and determine the percentage of emptiness for the products. Since the cameras will scan a small section of the shelf at the time, a stitching method will be applied on both depth and RGB stream. In order to identify categories of products, along with their spatial delimitation within a shelf, a segmentation neural network is used. By combining the segmentation output with the depth information, the distance from the pillar to the product can be determined. Since this type of information does not help a human operator or a supervisor in understanding the state of the shelf or in making an appropriate decision, such as restocking, a method for computing the shelf occupancy is proposed. Optimization must be done to the processing algorithms to enable them to run on an embedded platform, which will allow for the implementation of the proposed architecture on a platform deployed in a production environment. All the computation is done on board of the mobile robot without transmitting the data to an external server. © 2021 IEEE.

关键词： Cameras

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Implementation of GM Method in AI3DCE

Implementation of GM Method in AI3DCE

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2025 international conference on Intelligent control, computing and Communications, IC3 2025

作者： Mahalakshmi, R. Kishore, G. Uday Jansirani, A. Srinivas, Varanasi Husain, Saef Obad Supreeth, B.R. Saveetha Medical College and Hospital Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India Cmr College of Engineering & Technology Department of Cse Telangana Hyderabad India Sethu Institute of Technology Department of Electrical Communication Engineering Pulloor Tamil Nadu Kariapatti626115 India Gokaraju Rangaraju Institute of Engineering and Technology Department of Cse Telangana Hyderabad India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq Oxford Degree and Pg College Department of Computer Science Sir. AM. Visveshwaraiah Layout Ullal Bangalore India

ISBN: (纸本)9798331527495

This methodology applies an optimal stochastic solution to a virtual combat in a computational search and aims to have a machine that can be able to change its judgment call characteristics quickly to evolve its performances to a better level against even a good opponent. To turn around and see the result, an Endogenous switching proxy models use Connectionist temporal Probabilistic is learn on the fly to generalizing a data;predicting an unexplored area of the vector space, the globe. [potentially] Gaining a really similar effect as [1] allowing super valuable advice for future forecast improvements, and allowing the teacher engine to explore some representative metrics across hyperparameters, probably improving its efficiency. For Probabilistic implementations but courve - compatible workflow you are not be able to find globe optimum from scratch beacause you do not have a substitute model due to very different conditions and complicated criteria. New continuous measures of speech in different variation patterns (types of MSP) are provided to overcome these problems in the construction of speech in the new statistical key that is namely a new statistical test of repetition of a repeated (based on MSP) test of repetitions in the statistical speech. Further, Lrr polling polling will combine with Conduit temporal proxy designs that learn through mathematical modeling and the AI judgement call lever will then be able to better predict clear goal states and optimize parameters accordingly. © 2025 IEEE.

关键词： Genetic algorithms

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Implementation of GM Method in AI3DCE

Implementation of GM Method in AI3DCE

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Intelligent control, computing and Communications (IC3), international conference on

作者： Mahalakshmi R G. Uday Kishore A. Jansirani Varanasi Srinivas Saef Obad Husain B. R. Supreeth Anaesthesiology Saveetha Medical College and Hospital Saveetha Institute of Medical and Technical Sciences Saveetha University Chennai Tamil Nadu India Department of CSE CMR College of Engineering & Technology Hyderabad Telangana Department of Electrical Communication Engineering Sethu Institute of Technology Kariapatti Tamil Nadu India Department of CSE Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad Telangana India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Science Oxford Degree and PG College Sir. AM. Visveshwaraiah Layout Ullal Bangalore

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

This methodology applies an optimal stochastic solution to a virtual combat in a computational search and aims to have a machine that can be able to change its judgment call characteristics quickly to evolve its performances to a better level against even a good opponent. To turn around and see the result, an Endogenous switching proxy models use Connectionist temporal Probabilistic is learn on the fly to generalizing a data; predicting an unexplored area of the vector space, the globe. [potentially] Gaining a really similar effect as [1] allowing super valuable advice for future forecast improvements, and allowing the teacher engine to explore some representative metrics across hyperparameters, probably improving its efficiency. For Probabilistic implementations but courve - compatible workflow you are not be able to find globe optimum from scratch beacause you do not have a substitute model due to very different conditions and complicated criteria. New continuous measures of speech in different variation patterns (types of MSP) are provided to overcome these problems in the construction of speech in the new statistical key that is namely a new statistical test of repetition of a repeated (based on MSP) test of repetitions in the statistical speech. Further, Lrr polling polling will combine with Conduit temporal proxy designs that learn through mathematical modeling and the AI judgement call lever will then be able to better predict clear goal states and optimize parameters accordingly.

关键词： Computational modeling Stochastic processes Switches Predictive models Probabilistic logic Mathematical models Data models Vectors Artificial intelligence Optimization

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