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Detection of Various Dental Conditions on Dental Panoramic Radiography Using Faster R-CNN

IEEE Access 2023年 11卷 127388-127401页

作者： Chen, Shih-Lun Chen, Tsung-Yi Mao, Yi-Cheng Lin, Szu-Yin Huang, Ya-Yun Chen, Chiung-An Lin, Yuan-Jin Chuang, Mian-Heng Abu, Patricia Angela R. Chung Yuan Christian University Department of Electronic Engineering Taoyuan320314 Taiwan Feng Chia University Department of Electronic Engineering Taichung407102 Taiwan Chang Gung Memorial Hospital Department of General Dentistry Taoyuan61363 Taiwan National Ilan University Department of Computer Science and Information Engineering Yilan26047 Taiwan Academy of Innovative Semiconductor and Sustainable Manufacturing Department of Program on Semiconductor Manufacturing Technology National Cheng Kung University Tainan717005 Taiwan Ming Chi University of Technology Department of Electrical Engineering New Taipei243303 Taiwan Ateneo de Manila University Department of Information Systems and Computer Science Quezon1108 Philippines

The dental panoramic radiograph (DPR) is a pivotal diagnostic tool in dentistry. However, despite the growing prevalence of artificial intelligence (AI) across various medical domains, manual methods remain the prevailing means of interpreting DPR images. This study aims to introduce an advanced identification system for detecting seven dental conditions in DPR images by utilizing Faster R-CNN. The primary objectives are to enhance dentists' efficiency and evaluate the performance of various CNN models as foundational training networks. This study contributes significantly to the field in several notable ways. Firstly, including a Butterworth filter in the training process yielded an approximately 7% enhancement in judgment accuracy. Secondly, the proposed enhancement technology tailored to different dental symptoms effectively bolstered the training model's accuracy. Consequently, all dental conditions attained an accuracy rate exceeding 95% in CNN analysis. These accuracy enhancements ranged from 1.34% to 13.24% compared to existing recognition technologies. Thirdly, this study pioneers the application of Faster R-CNN for identifying dental conditions, achieving an impressive accuracy rate of 94.18%. The outcomes of this study mark a substantial advancement compared to prior research and offer dentists a more efficient and convenient means of pre-diagnosing dental conditions. © 2013 IEEE.

关键词： Image segmentation

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Security of Cyber-Physical Systems Against Actuator Attacks through Cryptography*

Security of Cyber-Physical Systems Against Actuator Attacks ...

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International Conference on Information technology (ICIT)

作者： Samuel Oliveira André B. Leal Marcelo Teixeira Yuri K. Lopes Department of Exact and Technological Sciences Federal University of Amapá (UNIFAP) Macapá/AP Brazil Graduate Program in Electrical Engineering Santa Catarina State University (UDESC) Joinville/SC Brazil Graduate Program in Electrical Engineering Federal University of Technology (UTFPR) Pato Branco/PR Brazil

The connectivity demanded by Industry 4.0 poses new challenges for cyber-physical systems (CPS), notably bolstering resilience against cyberattacks. In this paper, the authors use the formalism of Discrete Event Systems (DES) to design an approach that aims to protect CPS against actuator attacks using event-based symmetric cryptography. In this approach, controllable events that are properly selected are encrypted before being transmitted from the controller to the plant, leading intruders to mistakenly infer the supervisor's control actions. Thus, attacks on actuators do not have the expected impact on the plant, preventing unsafe states from being reached. The proposed approach is applied to a case study from the literature, where the identification of the attack is done without causing any damage while maintaining the integrity of the system.

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Preliminary Design for Reference tracking feedback for Medical Cyber-Physical Pharmacokinetic Systems 26

Preliminary Design for Reference tracking feedback for Medic...

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2024 IEEE International Conference on Automation/26th Congress of the Chilean Association of Automatic Control, ICA-ACCA 2024

作者： Oliveira, Pedro M. Bustos, Daniel Lobo, Rodolfo Lacerda, Marcio J. Palma, Jonathan M. Federal University of Minas Gerais Graduate Program in Electrical Engineering Belo Horizonte Brazil Universidad Católica Del Maule Dept. of Translational Medicine Talca Chile Universidad Diego Portales Ingenieria en Telecomunicaciones e Informática Santiago Chile London Metropolitan University Centre for Communications Technology School of Computing and Digital Media London United Kingdom Universidad de Talca Faculty of Engineering Curicó Chile

ISBN: (纸本)9798350378115

This paper addresses the reference tracking control problem for Medical Cyber-Physical Systems (MCPS). The control theory is employed to guarantee the suitable concentration of drugs in the body of patients to guarantee a safe treatment. The MCPS is modeled as a switched system, and the modes consider the different scenarios for the problem. A discrete-time model is utilized for the pharmacokinetic process, and the zero input control strategy is employed to design state-feedback controllers with a guaranteed exponential convergence rate. A numerical experiment is presented to illustrate the validity and effectiveness of our method. © 2024 IEEE.

关键词： State feedback

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Proactive Opinion-Driven Robot Navigation Around Human Movers

Proactive Opinion-Driven Robot Navigation Around Human Mover...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Charlotte Cathcart María Santos Shinkyu Park Naomi Ehrich Leonard Department of Mechanical and Aerospace Engineering Princeton University Princeton NJ USA Park is with the Electrical and Computer Engineering program King Abdullah University of Science and Technology Thuwal Saudi Arabia

We propose, analyze, and experimentally verify a new proactive approach for robot social navigation driven by the robot's “opinion” for which way and by how much to pass human movers crossing its path. The robot forms an opinion over time according to nonlinear dynamics that depend on the robot's observations of human movers and its level of attention to these social cues. For these dynamics, it is guaranteed that when the robot's attention is greater than a critical value, deadlock in decision making is broken, and the robot rapidly forms a strong opinion, passing each human mover even if the robot has no bias nor evidence for which way to pass. We enable proactive rapid and reliable social navigation by having the robot grow its attention across the critical value when a human mover approaches. With human-robot experiments we demonstrate the flexibility of our approach and validate our analytical results on deadlock-breaking. We also show that a single design parameter can tune the trade-off between efficiency and reliability in human-robot passing. The new approach has the additional advantage that it does not rely on a predictive model of human behavior.

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A High-step-down Converter with Negative Output Voltage

A High-step-down Converter with Negative Output Voltage

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International Conference on Power Electronics (ICPE)

作者： Yeu-Torng. Yau Thanh-Phu. Luu Ph.D. Program PTOEECS National Chin-Yi University of Technology Taichung Taiwan Department of Electrical Engineering National Chin-Yuuuuuuui University of Technology Taichung Taiwan

This paper proposes a new high step-down converter with negative voltage output, which has the following advantages: (1) Compared to conventional buck-boost or SEPIC converters, the proposed converter operates with zero voltage turn-on function. (2) The voltage gain of this circuit does not contain non-linear components, and the control is simple and can be driven by existing buck control ICs. (3) Due to the DC blocking capacitor between the output and input terminals, the high voltage at the input will not pass through to the output when the converter fails to be controlled. The load is protected. Finally, a prototype is completed and the proposed method is verified to be feasible.

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Study Case on Implementation Elevator 2 Floor System on PLC OMRON CP1E N30

Study Case on Implementation Elevator 2 Floor System on PLC ...

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International Conference on Education and technology (ICET)

作者： Muhammad Afnan Habibi Arif Wibawa Irham Fadlika Mochamad Farhan Ali Irfani Mohamad Farel Firmansyah Angger Baskoro Study Program of Power Plant Engineering Technology Malang Indonesia Dept. of Electrical Engineering Universitas Negeri Malang Malang Indonesia Dept. of Electrical Engineering and Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

The swift progression of industrial technology underscores the need for adept professionals capable of skillfully implementing and managing intricate systems. Vocational education assumes a pivotal role in cultivating competent intermediaries proficient in translating theoretical knowledge into practical applications. At the core of industrial automation lies the programmable Logic Controller (PLC), a specialized digital computer that interfaces with sensors, switches, and actuators to execute real-time control programs, thus facilitating meticulous industrial processes. This study concentrates on the practical deployment of a two-floor elevator system utilizing the OMRON CP1E N30 PLC. Elevators, integral to contemporary structures, mandate precision for secure vertical conveyance. Leveraging input signals from elevator buttons, sensors, and switches, the PLC orchestrates efficient motor control and dependable door operations. This hands-on application underscores the PLC’s significance within real-time control contexts. Nonetheless, Vocational Higher Education graduates frequently grapple with the challenge of transitioning to industry settings due to limited practical exposure. This partnership harmonizes with the center’s objective of enriching vocational education by integrating sophisticated technologies like PLCs, equipping the workforce with the acumen to bridge the gap between theoretical foundations and the pragmatic demands of industry.

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The Application of Artificial Neural Network Model to Predicting the Acid Mine Drainage from Long-Term Lab Scale Kinetic Test

arXiv

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arXiv 2024年

作者： Abfertiawan, Muhammad Sonny Kautsar, Muchammad Daniyal Hasan, Faiz Palinggi, Yoseph Pranoto, Kris Water and Wastewater Research Group Faculty of Civil and Environmental Engineering Bandung Institute of Technology Indonesia Department of Electrical and Information Engineering Universitas Gadjah Mada Indonesia Environmental Engineering Master Program Faculty of Civil and Environmental Engineering Bandung Institute of Technology Indonesia Environmental Department PT Kaltim Prima Coal Indonesia

Acid mine drainage (AMD) is one of the common environmental problems in the coal mining industry that was formed by the oxidation of sulfide minerals in the overburden or waste rock. The prediction of acid generation through AMD is important to do in overburden management and planning the post-mining land use. One of the methods used to predict AMD is a lab-scale kinetic test to determine the rate of acid formation over time using representative samples in the field. However, this test requires a long-time procedure and large amount of chemical reagents lead to inefficient cost. On the other hand, there is potential for machine learning to learn the pattern behind the lab-scale kinetic test data. This study describes an approach to use artificial neural network (ANN) modeling to predict the result from lab-scale kinetic tests. Various ANN model is used based on 83 weeks experiments of lab-scale kinetic tests with 100% potential acid-forming rock. The model approaches the monitoring of pH, ORP, conductivity, TDS, sulfate, and heavy metals (Fe and Mn). The overall Nash-Sutcliffe Efficiency (NSE) obtained in this study was 0.99 on training and validation data, indicating a strong correlation and accurate prediction compared to the actual lab-scale kinetic tests data. This show the ANN ability to learn patterns, trends, and seasonality from past data for accurate forecasting, thereby highlighting its significant contribution to solving AMD problems. This research is also expected to establish the foundation for a new approach to predict AMD, with time efficient, accurate, and cost-effectiveness in future applications. © 2024, CC BY-NC-SA.

关键词： Coal industry

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A Novel Isolated Intelligent Adjustable Buck-Boost Converter with Hill Climbing MPPT Algorithm for Solar Power Systems

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Processes 2023年第4期11卷

作者： Sabir, Bushra Lu, Shiue-Der Liu, Hwa-Dong Lin, Chang-Hua Sarwar, Adil Huang, Liang-Yin Department of Electrical Engineering National Taiwan University of Science and Technology Taipei 106 Taiwan Department of Electrical Engineering National Chin-Yi University of Technology Taichung411 Taiwan Undergraduate Program of Vehicle and Energy Engineering National Taiwan Normal University Taipei106 Taiwan Department of Electrical Engineering ZHCET Aligarh Muslim University Aligarh202002 India Graduate Institute of Manufacturing Technology National Taipei University of Technology Taipei106 Taiwan

This study proposes a new isolated intelligent adjustable buck-boost (IIABB) converter with an intelligent control strategy that is suitable for regenerative energy systems with unsteady output voltages. It also serves as a reliable voltage source for loads such as battery systems, microgrids, etc. In addition, the hill climbing (HC) maximum power point tracking (MPPT) algorithm can be utilized with this innovative IIABB converter to capture the MPP and then enhance system performance. In this converter, five inductors (LA, LB, LC, LD, and LE) and four power MOSFETs (SA, SB, SC, and SD) are used in the proposed novel isolated intelligent adjustable buck-boost (IIABB) converter to adjust the applied voltage across the load side. It also has a constant, stable output voltage. The new IIABB converter is simulated and verified using MATLAB R2021b, and the performances of the proposed IIABB converter and conventional SEPIC converter are compared. The solar photovoltaic module output voltages of 20 V, 30 V, and 40 V are given as inputs to the proposed IIABB converter, and the total output voltage of the proposed converter is 48 V. In the new IIABB converter, the duty cycle of the power MOSFET has a small variation. The proposed IIABB converter has an efficiency of 92~99%. On the other hand, in the conventional SEPIC converter, the duty cycle of a power MOSFET varies greatly depending on the relationship between the output and input voltage, which deteriorates the efficiency of the converter. As a result, this research contributes to the development of a novel type of IIABB converter that may be employed in renewable energy systems to considerably increase system performance and reduce the cost and size of the system. © 2023 by the authors.

关键词： Buck-Boost converter

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Visual Field Examination technology Based on Semi-transparent Elliptical Mirror

Visual Field Examination Technology Based on Semi-transparen...

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Educational Innovation (ECEI), IEEE Eurasian Conference on

作者： Chao-Kai Chang Chun-Yu Chiang Feng-Ming Yeh Chi-Hung Lee Chuen-Lin Tien Der-Chin Chen Department of Optometry Yuanpei University of Medical Technology Hsinchu Taiwan Ph.D. Program of Electrical and Communications Engineering Feng Chia University Taichung Taiwan Department of Electrical Engineering Feng Chia University Taichung Taiwan

In this study, the human visual field test technology is established by using an optoelectrical system consisting of a translucent ellipsoid, an area light source, and a landscape scene with an indicator. During the test, the subjects stared at the indicator directly in front of them with one eye and kept their eyeballs still, scanning the light strip with peripheral vision and using the mouse button plus the playback program to record the start and end positions of the scanning light strip in the landscape scene. This method is tested subjectively, and the subject needs to respond during the test. Therefore, before the test, the subject needs to understand the test process and be trained in advance to improve the exam accuracy. In the experiment, fifteen subjects with normal vision and no eye disease were selected. Their visual fields were confirmed normal after a preliminary assessment. The test results showed that the subjects' eyes were within the normal visual field, indicating that this method was feasible. In this research, a digital optical platform for the near visual field is proposed to establish an optoelectric visual field measurement technology. The proposed method is characterized by small size, rapid operation, and easy portability. With the digital LCD and visual imaging technology, both dynamic and static visual fields can be tested. The test data on the eyes' upper, lower, nasal, and temporal sides were consistent with the normal visual field. This shows that this method is feasible and worthy of promotion in the optometry industry.

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Prototype Design of Smart Diabetic Shoes with Lora Module Communication

Prototype Design of Smart Diabetic Shoes with Lora Module Co...

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2023 International Conference on Computer Science, Information technology and engineering, ICCoSITE 2023

作者： Purwono, Purwono Burhan, Asmat Nisa, Khoirun Wibisono, Sony Kartika Setiawan Mangkunegara, Iis Dewi, Pramesti Ma'Arif, Alfian Suwarno, Iswanto Universitas Harapan Bangsa Department of Informatics Purwokerto Indonesia Universitas Harapan Bangsa Department of Anesthesiology Nursing Purwokerto Indonesia Universitas Harapan Bangsa Department of Information Technology Purwokerto Indonesia Universitas Harapan Bangsa Nursing Study Program Purwokerto Indonesia Universitas Ahmad Dahlan Department of Electrical Engineering Yogyakarta Indonesia Universitas Muhammadiyah Yogyakarta Department of Engineer Professional Program Yogyakarta Indonesia

ISBN: (纸本)9798350320954

Diabetes is a disease that affects many people in the world. Diabetes mellitus is a type of metabolic disease in a person who suffers from blood glucose levels with extreme conditions, namely insufficient insulin production in the human body. Monitoring diabetes is an important concern for researchers because it can be useful for improving the quality of the nursing service system. One of the common conditions in diabetic patients is ulceration which is difficult to detect on time. technology can minimize the total cost of monitoring chronic diseases such as Diabetes continuously and on time. This research focuses on solutions to produce IoT-based smart diabetic shoes that utilize pressure sensors and the temperature of the feet of people with diabetic feet. Smart diabetic shoes are made using the Lora E32 module to be applied to areas with poor internet connections. The results of the testing carried out for 60 seconds in this study succeeded in detecting the area of the foot that experienced the greatest pressure, which was located on the rear footrest with a portion of pressure of around 25 - 28% of the total body weight. The patient's foot temperature increases when the pedestal load is greater. The Lora E32 module also functions as a media transmitter and receiver at a distance of 2.2 km in sending sensor data. © 2023 IEEE.

关键词： Diseases

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