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2023 International Conference on Sustainable Emerging Innovations in engineering and Technology, ICSEIET 2023

作者： Wiliyanto, Danang Puji Supriyadi, Slamet Mukhtar, Agus Setyoadi, Yuris Novita, Mega Dixit, Ankur Singh, Prabhat Virmani, Rahul Universitas Pgri Semarang Faculty of Engineering and Informatics Department of Mechanical Engineering Jl. Sidodadi Timur No. 24 Central Java Semarang50232 Indonesia Universitas Pgri Semarang Postgraduate Program of Science Education Jl. Sidodadi Timur No. 24 Central Java Semarang50232 Indonesia ABES Engineering College Department of Mechanical Engineering 19th KM Stone NH-09 Uttar Pradesh Ghaziabad201009 India

ISBN: (纸本)9798350329186

The use of automated goods transfer robots, capable of autonomously moving items from one point to another without the need for manual operation, is widely adopted in various industries. The Waypoint GPS navigation method can be employed in developing an automated goods transfer robot. This research focuses on the design and development of a robot using two Global Positioning System (GPS) coordinates for navigation and a smartphone as the user interface, equipped with ultrasonic sensors as input. The main components utilized in this robot include the Arduino Mega 2560 microcontroller, neo-7M GPS module, HC-06 Bluetooth module, SR-04 sensor, and omni-directional wheels. The position data is obtained by converting the two GPS coordinates into distance and direction values. These values are further translated into Pulse Width Modulation (PWM) signals, which are used to drive the robot's motors. To avoid collision, fuzzy logic is employed to regulate the PWM signals. The research results demonstrate that the robot can autonomously navigate from one point to another based on the provided coordinates while effectively avoiding obstacles. The findings of this study address a research gap in the application of the Waypoint GPS navigation method for goods transfer robots. The purpose of this research is to design and develop a robot that can autonomously transfer goods using the proposed method. The methodology involves the integration of GPS coordinates, smartphone interface, ultrasonic sensors, and motor control mechanisms. The results indicate successful navigation from the origin to the desired destination, following the specified coordinates, and obstacle avoidance capability. In conclusion, the developed robot utilizing the Waypoint GPS navigation method showcases promising potential for automated goods transfer applications. The ability to operate autonomously, guided by GPS coordinates, and the avoidance of obstacles enhances the efficiency and safety of goods transf

关键词： Navigation

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Improving Control Theory Education Through Face-to-Face Implementation of a Mobile Robotics Methodology

Improving Control Theory Education Through Face-to-Face Impl...

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2024 Brazilian Symposium on Robotics (SBR), and 2024 Workshop on Robotics in Education (WRE)

作者： M. A. Pastrana William Humberto Cuéllar Sánchez Jose Mendoza-Peñaloza M. S. Santana Daniel M. Muñoz Department of Mechanical Engineering Mechatronics Graduate Program University of Federal District UDF Brasilia DF Brazil Faculty of Gama Electronics Engineering Undergraduate Program University of Brasilia Brasilia DF Brazil

ISBN: (数字)9798350391084

ISBN: (纸本)9798350391091

Advances in information and communication technologies have significantly transformed engineering education. Virtual laboratories are increasingly adopted to enhance student interaction with control system simulations. The improved visualization and interaction capabilities of modern computers offer a more organic way to teach theoretical foundations. This paper describes the implementation of a methodology for teaching control theory that until now was entirely online in a face-to-face environment at the University of the Federal District in Brasilia, Brazil. This methodology utilizes virtual laboratories with CoppeliaSim, MATLAB, and the EVA mobile robot to teach control theory focused on single-input, single-output (SISO) systems for mobile robot tracking and obstacle avoidance applications. The results of the face-to-face implementation are compared to those of the fully online methodology, revealing that in-person teaching significantly enhances the quality of instruction.

关键词： Visualization Mechatronics Educational robots SISO Education Laboratories Software Control theory Mobile robots MATLAB

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Ensemble Deep Learning NARX for Estimating Time Series of Earthquake Occurrence

Ensemble Deep Learning NARX for Estimating Time Series of Ea...

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Robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： Hapsoro Agung Nugroho Eka Yuni Astuty Aries Subiantoro Benyamin Kusumoputro Department of Electrical Engineering Research Center for Artificial Intelligence and Data Engineering Faculty of Engineering University of Indonesia Depok Indonesia Information Systems Study Program Faculty of Engineering Darma Persada University Jakarta Indonesia

ISBN: (数字)9798350307566

ISBN: (纸本)9798350307573

Predicting earthquake occurrences in time series data remains a challenging task in seismology. NARX (Nonlinear Autoregressive with eXogenous input) neural networks have recently shown promise for accurate predictions. While previous research has demonstrated NARX's effectiveness in estimating earthquake frequencies, the architecture still relies on several pre-determined parameters. These parameters include the number of hidden layers, number of neurons, and delay time. This study aims to investigate the effectiveness of Ensemble Deep Learning NARX neural networks in predicting time series of earthquakes. The proposed ensemble model integrates multiple NARX neural networks, each trained on a distinct subset of earthquake data. This approach aims to enhance prediction accuracy and bolster model robustness. The dataset consists of time series records detailing earthquake occurrence frequencies and magnitudes. The results show performance evaluation metrics in terms of Mean Square Error (MSE) values. For training frequency data, the MSE is 4.10e-26, and for testing, it is 6.05e-22. Regarding training magnitude data, the MSE is 2.86e-21 for training and 3.17e-19 for testing. This study makes a valuable contribution to the advancement of earthquake prediction techniques, underscoring the potential of Ensemble Deep Learning NARX neural networks for precise time series estimation in seismology.

关键词： Deep learning Training Time series analysis Earthquakes Seismology Estimation Predictive models

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Performance Analysis of YOLO-DeepSORT on Thermal Video-Based Online Multi-Object Tracking

Performance Analysis of YOLO-DeepSORT on Thermal Video-Based...

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Robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： Nur Ibrahim Arsyad Ramadhan Darlis Herianto Benyamin Kusumoputro Department of Electrical Engineering Research Center for Artificial Intelligence and Data Engineering Faculty of Engineering University of Indonesia Depok Indonesia Information Systems Study Program Faculty of Engineering Darma Persada University Jakarta Indonesia

ISBN: (数字)9798350307566

ISBN: (纸本)9798350307573

Recently, thermal cameras have been used in various fields, including surveillance systems and advanced driver assistance systems (ADAS), as they perform better in low light than visible-light cameras. Some challenges in the surveillance system or ADAS field related to thermal cameras are occlusion and thermal crossover between objects with similar appearances during object detection or object tracking tasks, which can lead to misdetection, false positives, and lost tracking. In this paper, performance analysis of you-only-look-once (YOLO) combined with deep online real-time tracking (DeepSORT) on thermal video-based online multi-object tracking (MOT) in occlusion and thermal crossover scene is presented. YOLO, as one of state-of-the-art method for detection task, is used for detection system. Then, the detected object from YOLO is tracked using DeepSORT. The results demonstrate that the online MOT of sequential thermal images using YOLO-DeepSORT achieved a MOTA score of 44.2% and IDF1 of 45.3%. Thus, negative example was added in YOLO training process to reduce false detection, and it gives improvement with MOTA score of 63.8% and IDF1 score of 54.6%.

关键词： YOLO Training Surveillance Cameras Real-time systems Thermal analysis Performance analysis

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LoRa Network Design for Monitoring Landslides on 150 KV Delivery Tower

LoRa Network Design for Monitoring Landslides on 150 KV Deli...

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International Conference on Smart Computing & Communications (ICSCC)

作者： I Wayan Dikse Pancane I Putu Gelgel Astika Putra I Wayan Gede Suarjana Agus Supranartha Electrical Engineering Study Program Universitas Pendidikan Nasional Denpasar Indonesia Department of Public Health Faculty of Sport Science and Public Health Universitas Negeri Manado Sulawesi Indonesia Electro Enginering Elektrical Engineering Program Study Politechnic Negeri Bali Badung Indonesia

ISBN: (数字)9798350363104

ISBN: (纸本)9798350363111

The objective of this research is to design and develop an integrated landslide early detection system at Tower Number Eight, 150 kV Gianyar. The research is expected to result in the construction of a communication system based on LoRa technology that will serve to reduce the potential damage from landslides. In order to achieve this, several parameters must be considered as benchmarks. These include RSSI, SNR, BER and PDR. The device operates by monitoring changes in position, soil moisture and rainfall, and then transmitting the data via LoRa technology. At the sink, the data is recorded and monitored for RSSI, SNR, PDR and BER values. In the test, the source 1 node, situated 300 metres away, exhibited an RSSI value of −100 to −109 dBm and an SNR value of 6.75 to −6.7 in both sunny and rainy weather, with a PDR value of 100%. The source 2 node, situated 600 metres away, exhibited an RSSI value of −97 to −109 dBm and an SNR value of 8.5 to −11.75 dB, with a PDR value of 70 to 100%. It should be noted that the number of bits in the sensor data sent is always complete. This is evidenced by the bit error ratio (BER) value, which is always 0 on both source nodes.

关键词： Rain Electricity Poles and towers Soil moisture LoRa Terrain factors Reliability Monitoring Signal to noise ratio Meteorology

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Centralized Training with Decentralized Execution Reinforcement Learning for Cooperative Multi-agent Systems with Communication Delay 61

Centralized Training with Decentralized Execution Reinforcem...

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61st Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2022

作者： Ikeda, Takuma Shibuya, Takeshi University of Tsukuba Master's Program in Intelligent and Mechanical Interaction Systems Ibaraki Japan University of Tsukuba Faculty of Engineering Information and Systems Ibaraki Japan

ISBN: (数字)9784907764784

ISBN: (纸本)9784907764784

In cooperative multi-agent systems, efficient coordination among agents is important when accomplishing tasks. VFFAC is a method that learns the communication system between agents and their interactions with the environment to obtain policies with high performance. However, this method results in decreased performance of policy in environments with a delay in communication. Furthermore, there is no formulation of the control problem of a cooperative multi-agent system with communication delays in unknown environments. In this study, we formulated a decision-making problem in a cooperative multi-agent system with an unknown environment model and a certain length delay in communication. We also propose a method to handle communication delays by using the history of information obtained through communication. We demonstrated that the proposed method successfully learns policy with high rewards through simulated experiments in an environment with a communication delay. © 2022 The Society of Instrument and Control Engineers - SICE.

关键词： Reinforcement learning

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Evaluation Electrical System of Mini Plant Waste Energy on Institut Teknologi PLN

Evaluation Electrical System of Mini Plant Waste Energy on I...

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Converging Technology in Electrical and Information engineering (ICCTEIE), International Conference on

作者： Pawenary Dwi Listiawati Hendri Electrical Engineering Study Program Faculty of Electricity and Renewable Energy Insitut Teknologi PLN Jakarta Indonesia

Waste is a problem in almost every region, especially related to how the processing of waste can be converted into other forms as a form of energy that can be utilized, one of which is waste processing by pyrolysis is one of the technologies to convert waste into useful energy or fuel. At this time waste processing requires waste processing machines ranging from organic and un-organic waste shredding machines, briquette processing machines, pellets, using star-delta 3-phase motors, generally still conventional/manually. Current research, the author began to develop a waste and flue gas particle handling machine, a non-incinerator pyrolysis machine with the wet method, a high efficiency cyclone system which originally used a machine manually/ conventionally, replaced with a Delta series Star - Delta series with interlock and interface) automatically. Garbage processing The machine in addition to aiming to reduce waste waste, the machine must be made automatically and friendly to the operator who runs it.

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Reinforcement Learning to Efficiently Recover Control Performance of Robots Using Imitation Learning After Failure

Reinforcement Learning to Efficiently Recover Control Perfor...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Kobayashi, Shoki Shibuya, Takeshi University of Tsukuba Master's Program in Intelligent and Mechanical Interaction Systems Ibaraki Japan University of Tsukuba Faculty of Engineering Information and Systems Ibaraki Japan

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

Extreme environments, such as space and underwater, are difficult for humans to enter because they involve risks, hence it is necessary to employ autonomous robots instead of humans. When robots fail in extreme environments, it is essential for the robot to automatically recover control following the rules of failure because humans cannot repair the robot directly. Reinforcement learning is expected to automatically acquire the control rule;however, the retrieval of the control rule requires significant trial-and-error. Imitation learning cannot acquire the control rule if no suitable expert data exist. Methods combining imitation learning and reinforcement learning reduce the number of trial-and-errors;however, they are still not effective against robot failure because these methods cannot utilize expert data effectively. This paper proposes a reinforcement learning method that efficiently recovers control performance from failures by utilizing both the control rules prepared by the designer and multiple discriminators to calculate measures similar to expert data. Experimental results show that the proposed method recovers the control performance with fewer episodes than the conventional method. The main contribution of the proposed method is its efficiency against robot failure through utilizing expart data prepared for failure by the designers for imitation learning. © 2022 IEEE.

关键词： Reinforcement learning

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Using a spiral fin to replace a wavy fin in the condenser of an air conditioner

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International Journal of Thermofluids 2024年 21卷

作者： Chimres, Nares Kaew-on, Jatuporn Surapapwong, Thanis Chittiphalungsri, Thunyawat Wongwises, Somchai Mechanical Engineering Program Faculty of Engineering Thaksin University Phatthalung93210 Thailand PTT Exploration and Production Public Company Limited Bangkok Chatuchak10900 Thailand Co. Ltd. Nonthaburi Muang11000 Thailand Department of Mechanical Engineering Faculty of Engineering King Mongkut's University of Technology Thonburi Bangkok Bangmod10140 Thailand Pathum Thani12120 Thailand

An experimental and numerical investigation of an L-footed spiral fin's thermal performance for replacement of wavy fins used in condensers is presented. This condenser is used for air conditioners with a capacity of 2.64 kW–3.52 kW (9000–12,000 BTU/hr). Eight spiral fins with various fin pitches and fin diameters are studied. Each spiral fin is designed to have an area that is equal to that of a baseline wavy fin. The investigation found that the heat transfer coefficient and pressure drop obtained with the wavy fin are greater than those obtained with a spiral fin. Moreover, the spiral fin gives a performance index or "goodness factor" that is about 0.2–11.9 % greater than that of a wavy fin. © 2023 The Author(s)

关键词： Heat transfer coefficients

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Continuous Lithium-Ion Extraction From Seawater and Mine Water With a Fuel Cell System and Ceramic Membranes

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Energy & Environmental Materials 2024年第6期7卷 254-261页

作者： Cansu Kök Lei Wang Jean Gustavo A.Ruthes Antje Quade Matthew E.Suss Volker Presser INM–Leibniz Institute for New Materials Campus D2266123Saarbr¨uckenGermany Department of Materials Science&Engineering Saarland UniversityCampus D2266123Saarbr¨uckenGermany Leibniz Institute for Plasma Science and Technology Felix-Hausdorff-Straße 217489GreifswaldGermany Faculty of Mechanical Engineering Technion–Israel Institute of TechnologyHaifa3200003Israel Wolfson Department of Chemical Engineering Technion–Israel Institute of TechnologyHaifa3200003Israel Grand Technion Energy Program Technion–Israel Institute of TechnologyHaifa3200003Israel Saarene–Saarland Center for Energy Materials and Sustainability Campus C4266123Saarbr¨uckenGermany

The demand for electronic devices that utilize lithium is steadily increasing in this rapidly advancing technological *** high-purity lithium in an environmentally friendly way is challenging by using commercialized ***,we propose the first fuel cell system for continuous lithium-ion extraction using a lithium superionic conductor membrane and advanced *** fuel cell system for extracting lithium-ion has demonstrated a twofold increase in the selectivity of Li^(+)/Na^(+)while producing *** data show that the fuel cell with a titania-coated electrode achieves 95%lithium-ion purity while generating 10.23 Wh of energy per gram of *** investigation revealed that using atomic layer deposition improved the electrode's uniformity,stability,and electrocatalytic *** 2000 cycles determined by cyclic voltammetry,the electrode preserved its stability.

关键词： atomic layer deposition cation selectivity electrochemical lithium-ion extraction fuel cell

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