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4th International Conference on engineering Technology 2019, ICET 2019

作者： Mamat, Nor Hana Mohd Noor, Samsul Bahari Che Soh, Azura Saleena Taip, Farah Rashid, Ahmad Hazri Ab. Jufika Ahmad, Nur Liyana Yusof, Ishak Mohd Mohamad, Adida Zuraida Control System and Signal Processing Research Centre Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Putra Malaysia UPM Serdang Selangor43400 Malaysia Food and Process Department Faculty of Engineering Universiti Putra Malaysia UPM Serdang Selangor43400 Malaysia Industrial Biotechnology Research Centre SIRIM Berhad Persiaran Dato' Menteri Seksyen 2 Selangor Shah Alam40700 Malaysia Faculty of Electrical and Automation Engineering Technology TATI University College Teluk Kalong Kemaman Terengganu24000 Malaysia

Biomass concentration is an important indicator of production rate in polyhydroxyalkanoates (PHA) fermentation process. In current practice, measurement of biomass concentration is done off-line by laboratory analysis that is unsuitable for online process monitoring and control. Soft-sensor is often used as an alternative that provides an estimate of hard to measure parameters from easy to measure process data. However, most of these studies use simulated data or data generated from mathematical model that was developed without full consideration of process and measurement uncertainty. In this study, a soft-sensor is developed from real production data for PHA fermentation in pilot-scale bioreactor with the appropriate data pre-processing techniques applied to process data that was obtained from this system. Multilayer perceptron (MLP) neural network is used to estimate biomass concentration using secondary process parameters such as dissolved oxygen (DO), temperature, pH and agitation speed as inputs. Different models are developed based on different batches of production data and various network architecture in order to study the appropriate integration of process data and network topology that gives the best model accuracy. Results indicate that the biomass soft-sensor developed using MLP-ANN provides a better estimate of biomass in comparison to radial basis function (RBF) neural network and support vector regression (SVR) methods. The developed soft-sensor can be further used in monitoring and control of production output. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Multilayer neural networks

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INSTANCE SEGMENTATION AND TEETH CLASSIFICATION IN PANORAMIC X-RAYS

arXiv

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arXiv 2024年

作者： Budagam, Devichand Ghosh, Sayan Imanbayev, Azamat Zhanatuly Kaplun, Dmitrii Rychenkov, Artem Sinitca, Aleksandr Kumar, Ayush Shrivastav, Anuj Akhmetov, Iskander Rafailovich Antonov, Sergey Cyganov, Gleb Department of Computer Science and Engineering Indian Institute of Technology Kharagpur Kharagpur India Department of Chemical Engineering Indian Institute of Technology Kharagpur Kharagpur India School of IT and Engineering Kazakh-British Technical University Almaty Kazakhstan Artificial Intelligence Research Institute China University of Mining and Technology Xuzhou China Department of Automation and Control Processes St. Petersburg Electrotechnical University"LETI" St. Petersburg Russia Centre for Digital Telecommunication Technologies St. Petersburg Electrotechnical University"LETI" St. Petersburg Russia Department of Humanities and Social Sciences Indian Institute of Technology Kharagpur Kharagpur India Department of Architecture and Regional Planning Indian Institute of Technology Kharagpur Kharagpur India Faculty of Digital Transformation ITMO University St. Petersburg Russia

Teeth segmentation and recognition are critical in various dental applications and dental diagnosis. Automatic and accurate segmentation approaches have been made possible by integrating deep learning models. Although teeth segmentation has been studied in the past, only some techniques were able to effectively classify and segment teeth simultaneously. This article offers a pipeline of two deep learning models, U-Net and YOLOv8, which results in BB-UNet, a new architecture for the classification and segmentation of teeth on panoramic X-rays that is efficient and reliable. We have improved the quality and reliability of teeth segmentation by utilising the YOLOv8 and U-Net capabilities. The proposed networks have been evaluated using the mean average precision (mAP) and dice coefficient for YOLOv8 and BB-UNet, respectively. We have achieved a 3% increase in mAP score for teeth classification compared to existing methods, and a 10-15% increase in dice coefficient for teeth segmentation compared to U-Net across different categories of teeth. A new Dental dataset was created based on UFBA-UESC dataset with Bounding-Box and Polygon annotations of 425 dental panoramic X-rays. The findings of this research pave the way for a wider adoption of object detection models in the field of dental diagnosis. © 2024, CC BY.

关键词： Object detection

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Iterative surface mapping using local geometry approximation with sparse measurements during robotic tooling tasks

arXiv

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arXiv 2020年

作者： Amersdorfer, Manuel Meurer, Thomas The Chair of Automatic Control Faculty of Engineering Kiel University Kaiserstraße 2 Kiel24143 Germany

We present a cost-efficient and versatile method to map an unknown 3D freeform surface using only sparse measurements while the end-effector of a robotic manipulator moves along the surface. The geometry is locally approximated by a plane, which is defined by measured points on the surface. The method relies on linear Kalman filters, estimating the height of each point on a 2D grid. Therefore, the approximation covariance for each grid point is determined using a radial basis function to consider the measured point positions. We propose different update strategies for the grid points exploiting the locality of the planar approximation in combination with a projection method. The approach is experimentally validated by tracking the surface with a robotic manipulator. Three laser distance sensors mounted on the end-effector continuously measure points on the surface during the motion to determine the approximation plane. It is shown that the surface geometry can be mapped reasonably accurate with a mean absolute error below 1 mm. The mapping error mainly depends on the size of the approximation area and the curvature of the surface. Copyright © 2020, The Authors. All rights reserved.

关键词： End effectors

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Yolov7-Tp: A Deep Convolutional Neural Network for Identifying Tea Buds and Their Plucking Points

SSRN

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SSRN 2023年

作者： Gui, Zhiyong Chen, Zhiwei Wang, Mengjie Chen, Jianneng Wu, Chuanyu Dong, Chunwang Li, Yang Key Laboratory of Tea Quality and Safety Control Ministry of Agriculture and Rural Affairs Tea Research Institute Chinese Academy of Agricultural Sciences Hangzhou310018 China Faculty of Mechanical Engineering & Automation Zhejiang Sci-Tech University Hangzhou310018 China Key Laboratory of Transplanting Equipment and Technology of Zhejiang Province Hangzhou310018 China Tea Research Institute Shandong Academy of Agricultural Sciences Jinan250100 China

To achieve intelligent tea plucking, it is essential to let the machine know the location of tea bud picking. A Yolov7-TP (Yolov7-Tea-bud and plucking point) model is proposed herein for identifying tea buds and their plucking points. Here, images of tea buds in actual tea plantations were collected and labeled to establish a dataset. Thereafter, the Yolov7-TP was trained, tested, optimized, and improved according to the test results. The specific improvements were as follows: a localization loss function of tea-bud plucking points, AW tea plucking-point (AWTP) loss, is proposed to replace the original object key point similarity loss function, which significantly improved the positioning accuracy of plucking points. The shuffle attention mechanism was introduced into the model to advance the detection performance of the model. To evaluate the accuracy of the model to predict tea plucking points, this study proposes a means tea plucking point similarity (MTPS). A new indicator for tea plucking-point evaluation is proposed, the mean tea plucking-point similarity (MTPS), which better reflects the accuracy of the model. Here, the precision, recall, mean Average Precision (Intersection over Union=0.5) (MAP@0.5), and MTPS of the proposed model reached 0.975, 0.884, 0.946, and 0.9835, respectively. The proposed model was observed to be more stable and accurate in a complex environment. This study provides technical solutions and optimization methods for intelligent precision plucking, application values for the acquisition of tea-bud plucking points, and reference values for the identification of key points for other objects. © 2023, The Authors. All rights reserved.

关键词： Object detection

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Selection of Suitable Automatic CPR Device Chassis Material Using Intuitionistic Fuzzy TOPSIS, VIKOR, and CODAS Methods

SSRN

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SSRN 2022年

作者： Kağızman, Ahmet Deveci, Kaan Sezer, Volkan Istanbul Technical University Institute of Science Ayazaga Campus Maslak Istanbul34469 Turkey Kirklareli University Faculty of Technology Department of Mechatronic Engineering Kayali Campus Kirklareli39000 Turkey Istanbul Technical University Energy Institute. İTÜ Energy Institute Ayazaga Campus Sariyer İstanbul34469 Turkey Istanbul Technical University Department of Control and Automation Engineering Ayazaga Campus Maslak Istanbul34469 Turkey

The alternative intervention method that should be applied in cases of cardiac arrest is Cardiopulmonary Resuscitation (CPR), which consists of effective chest compressions. Nowadays, chest compressions are performed in two different ways: Manually or using an automatic CPR device. Since manual chest compressions require an excessive amount of strength, cause fatigue in the provider even during the first minutes of CPR. Automatic CPR devices developed to provide more effective chest compressions also have not yet become widespread except in developed countries. In this study, it has been investigated whether CPR device chassis can be produced also with the presented thermoplastic materials instead of expensive materials such as carbon fiber or fiberglass used in existing devices. This study examined the problem of which thermoplastic material the chassis of the CPR device should be made of by the American Heart Association (AHA) standards and at a low cost under four main criteria (economic, manufacturability, sustainability, and structural features). The Intuitionistic Fuzzy (IF) TOPSIS, IF VIKOR, and IF CODAS methods, which are distance-based MCDM methods, have been used to solve this problem. According to the results obtained from the mentioned methods, it is seen that the most suitable material for the chassis of the CPR device should be Polycarbonate / Acrylonitrile Butadiene Styrene Flame Retardant (PC/ABS FR). © 2022, The Authors. All rights reserved.

关键词： Costs

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Swarm intelligent algorithm for re-entrant hybrid flow shop scheduling problems

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International Journal of Simulation and Process Modelling 2019年第1期14卷 17-27页

作者： Han, Zhonghua Tian, Xutian Dong, Xiaoting Xie, Fanyi Faculty of Information and Control Engineering Shenyang Jianzhu University Shenyang Liaoning China Department of Digital Factory Shenyang Institute of Automation Chinese Academy of Sciences Shenyang Liaoning China Faculty of Electrical Engineering Sichuan College of Architectural Technology Deyang Sichuan China

In order to solve re-entrant hybrid flowshop (RHFS) scheduling problems and establish simulations and processing models, this paper uses wolf pack algorithm (WPA) as global optimisation. For local assignment, it takes minimum remaining time rule. Scouting behaviours of wolf are changed in former optimisation by means of Levy flight, extending searching ranges and increasing rapidity of convergence. When it comes to local extremum of WPA, dynamic regenerating individuals with high similarity adds diversity. Hamming distance is used to judge individual similarity for increased quality of individuals, enhanced search performance of the algorithm in solution space and promoted evolutionary vitality. A painting workshop in a bus manufacture enterprise owns typical features of re-entrant hybrid flowshop. Regarding it as the algorithm applied target, this paper focuses on resolving this problem with dynamic wolf pack algorithm based on levy flight (LDWPA). Results show that LDWPA can solve re-entrant hybrid flowshop scheduling problems effectively. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Hamming distance

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The System to Study Pulse Transit Time Measurement Error

The System to Study Pulse Transit Time Measurement Error

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Mediterranean Conference on Embedded Computing (MECO)

作者： Sergey G. Gurzhin Vladimir I. Zhulev Michail B. Kaplan Evgeniy M. Proshin Andrey V. Shulyakov Faculty of Automation and Information Technologies in Control Ryazan State Radio Engineering University RSREU Ryazan Russia

ISBN: (数字)9781728169491

ISBN: (纸本)9781728169507

The article considers software-hardware implementation of the system to study the errors in pulse transit time measurement methods. Flexible and powerful possibilities of software tools in the form of virtual instruments capable to set and reproduce forms and parameters of test signals as well as probabilistic characteristics of interferences are shown.

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Analysis of Metrological Test Method Accuracy

Analysis of Metrological Test Method Accuracy

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Mediterranean Conference on Embedded Computing (MECO)

作者： Aleksey M. Abramov Sergey G. Gurzhin Vladimir I. Zhulev Evgeniy M. Proshin Andrey V. Shulyakov Faculty of Automation and Information Technologies in Control Ryazan State Radio Engineering University RSREU Ryazan Russia

The article gives the analysis of errors in the method of “sliding histogram” taken place as a result of combined non-linearity of standard test signal together with non-linearity of its movement.

ISBN: (数字)9781728169491

ISBN: (纸本)9781728169507

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Methods for digital signal processing and digital filter synthesis

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AIP Conference Proceedings 2022年第1期2656卷

作者： O. A. Jumaev D. S. Karpovic M. T. Ismoilov 1Navoi State Mining Institute Department of Automation and Control Automation Faculty Navoi Uzbekistan 2Belarusian State Technological University Department of Automation of Production Processes and Electrical Engineering Chemical Technology and Engineering Faculty Minsk Belarus

Methods of digital signal processing in control and monitoring systems are relevant today and largely replace the classic analog methods. This article discusses the main methods of digital signal processing and synthe...

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Modular smart furniture system for independent living of older adults- user experience study

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Gerontechnology 2020年第4期19卷 1-13页

作者： Merilampi, Sari Poberžnik, Anja Saari, Santeri Serrano, J. Artur Güttler, Jörg Langosch, Katharina Bock, Thomas Zou, Ling Magne, Trine A. Faculty of Technology Satakunta University of Applied Sciences Pori Finland Department of Neuromedicine and Movement Science Faculty of Medicine and Health Sciences NTNU/Norwegian University of Science and Technology Trondheim Norway Chair of Building Realization and Robotics Technical University of Munich Munich Germany School of Microelectronics and Control Engineering Changzhou University Changzhou 213164 China

Background: The ageing of the population represents a significant challenge, however, it is also a huge potential driver for innovation. Technology development capabilities are rapidly increasing, which enables new, innovative solutions when considering the ageing population. Objective: To promote the successful development and implementation of new technologies (in this case, smart furniture), positive user feedback and experiences are required. Methods: In this study, several modular smart furniture prototypes were developed, offering a potential solution to several challenges associated with ageing. The aim was to investigate which features positively affect user experience and consequently form the basis for smart, ageing-friendly furniture design guidelines. The smart furniture systems consisted of five prototypes: Fall Detection system with assistive Mobile Robot, ReAblechair, Magic Mirror, Smart Gaming chair, and 3D printed handles. These prototypes were presented to seniors in a home-like environment, after which participants completed a questionnaire and were interviewed. The themes used in the semi-structured interview followed the structure of Jesse Garrett's user experience framework. Results: The most essential feature was found to be modularity, or the ability to customize solutions according to the end user's capabilities and needs. In addition, results highlight that smart furniture should be aesthetically pleasing whilst still serving its primary purpose (i.e. as an item of furniture). Administrative components of the software should be removed from the end user's User Interface (UI) and integrated in a separate UI, to simplify the end user's interaction with the technology. Installation and customization services, as well as value-adding services (i.e. monitoring) were seen to offer potential. Conclusions: In general, the user experiences were positive. Smart features were readily accepted as part of the furniture prototypes, with hidden technologi

关键词： active and assistive living assistive technologies design for older adults fall detection serious games Smart furniture

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