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2024 International Conference on Information technology Systems and Innovation, ICITSI 2024

作者： Gunawan, Rudy Azwar, Ade Geovania Gunawan, Aditya Zufar Mahendra Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia Bandung Institute of Technology Department of Industrial Engineering Bandung Indonesia FITB Bandung Institute of Technology Bandung Indonesia

ISBN: (纸本)9798331511470

Real-time detection of drowsiness is an important need in efforts to improve safety, especially in the transportation sector. This research focuses on the development of a non-invasive system to detect drowsiness based on eye blink analysis. This system utilizes computer vision technology to measure blink frequency and duration as the main parameters. With an Eye Aspect Ratio (EAR)-based algorithm implemented, the system can detect changes in eye blink patterns accurately. The data obtained is used to identify signs of drowsiness such as increased blink duration or decreased frequency. The study evaluates hardware performance for real-time image processing in detecting drowsiness through blink dynamics. The results reveal that an AMD A9 laptop performs significantly better, achieving a sampling rate of 16 Hz, compared to the Raspberry Pi 3B+, which operates at 1.6 Hz, approximately 10 times slower. Additionally, the experiment establishes two drowsiness detection criteria: the duration of a single blink and the frequency of blinks within a set timeframe. The latter requires additional program functionality to store and analyze blink data over time. These findings underscore the need for robust hardware and software optimization to ensure reliable, real-time drowsiness detection. Experimental results show a high level of accuracy in detecting drowsiness, making it a reliable solution to improve user safety in various sectors. © 2024 IEEE.

关键词： Digital storage

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Implementation of YOLO V5 Integrated on Jetson Nano for Autonomous Underwater Vehicle Prototype to Overcome Pollution in Aquatic Areas

Implementation of YOLO V5 Integrated on Jetson Nano for Auto...

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2024 International Conference on Electrical and Information technology, IEIT 2024

作者： Pardede, Theorilus Putra, Oditya.Andalas Wiji Saputra, J. Widodo Saputra, Mahesa Anam Lestari, Dyah Sendari, Siti Mustika, Soraya Widiyaningtyas, Triyanna Mahandi, Yogi Dwi Elbaith Zaeni, Ilham Ari State University of Malang Departemen of Electrical and Informatics Engineering Malang Indonesia State University of Malang Electronic System Engineering Technology Malang Indonesia

ISBN: (纸本)9798331516888

Indonesia is a country with vast maritime territory. According to the Indonesian Central Statistics Agency (BPS) in 2022, Indonesia consists of 17,001 islands spread from Sabang to Merauke. Based on this report, it is evident that Indonesia possesses extensive maritime areas, including seas, straits, bays, and rivers. However, Indonesia faces water pollution issues. To address this, Autonomous Underwater Vehicle (AUV) technology is utilized, supported by image processing algorithms like Yolo V5 to accurately detect and identify water pollution. Leveraging these advancements, robots are designed using YOLO V5 to gather object class datasheets for accurate classification. Similarly, after successfully detecting objects, robots determine movement positions using Proportional-Integral-Derivative (PID) to ascertain center of bounding box accuracy, orientation stability, and completion time. Research results indicate that handling 1300 to 300 object numbers can achieve high average precision with accurate confidence. This serves as a reference for robots in determining movements towards objects using error and desired value comparisons. PID testing on robots shows that with Kp:Ki:Kd settings of 50:5:0.5, Center of Bounding Box Accuracy of 85.4 and Orientation Stability of 79.4 are achieved in 4.8 seconds. With settings of 100:5:2, these values increase to 91.4 and 89.6 with an allocation time of 3.4 seconds. These conditions demonstrate that increasing PID values contributes to improved robot performance, characterized by faster allocation times and higher stability. With settings of 125:12:8, Center of Bounding Box Accuracy of 96.4 and Orientation Stability of 90.8 are achieved in 2 seconds, enhancing robot stability further. © 2024 IEEE.

关键词： Autonomous underwater vehicles

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Limits to the Deployment of DC Microgrids

Limits to the Deployment of DC Microgrids

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2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

作者： Keoves, Andras Ivancsy, Tamas Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Electric Power Engineering Budapest Hungary

ISBN: (纸本)9798350320169

Nowadays microgrids are becoming more and more popular. These are small-scale networks that operate independently or in cooperation with other small-scale electrical networks. One of their main features is that they use renewable energy sources (mainly solar panels) and energy storage (mainly batteries). Solar panels and batteries are DC devices, as are most of the loads used in the office, so it would be logical to use DC microgrids. However, DC solutions are not very widespread, and in most cases you will find AC and hybrid microgrids, being a mixture of AC and DC solutions. In this article, we have sought to explain why AC microgrids are more popular and what are the difficulties in the uptake of DC microgrids. Overall, the main reasons for the lagging behind of DC microgrids are the high investment costs, the lack of well-defined standards and the complexity of connecting to the grid. © 2023 IEEE.

关键词： Energy storage

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Exploring Network Dynamics: Community Detection and Influencer Analysis in Multidimensional Social Networks

Exploring Network Dynamics: Community Detection and Influenc...

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2024 IEEE International Conference on Big Data, BigData 2024

作者： Kanavos, Andreas Vonitsanos, Gerasimos Karamitsos, Ioannis Al-Hussaeni, Khalil Ionian University Department of Informatics Corfu Greece University of Patras Computer Engineering and Informatics Department Patras Greece Rochester Institution of Technology Dubai United Arab Emirates Rochester Institute of Technology Computing Sciences Department Dubai United Arab Emirates

ISBN: (纸本)9798350362480

In the digital era, multidimensional social networks have become integral to daily communication, catering to diverse relational needs, from interpersonal to professional and commercial. This study utilizes two comprehensive datasets from Twitter to explore and visualize user interactions within these networks. Focusing on advanced community detection algorithms, we apply the Louvain and Label Propagation methods to delineate the structure of these communities and identify influential users effectively. Through systematic analysis, our research reveals significant insights into the dynamics of network clusters and the pivotal role of influencers. We demonstrate that community structures significantly influence in formation dissemination and user engagement, providing key data to optimize digital communication strategies in complex environments. The findings underscore the importance of strategic influencer engagement and tailored community management in enhancing interaction within multidimensional social networks. Additionally, our results suggest that understanding the network's structural nuances can aid in developing targeted interventions that leverage influencer capabilities to maximize communication impact, illustrating potential applications across various sectors, including marketing, politics, and public health. © 2024 IEEE.

关键词： Tweets

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Motion Capture System based on RGB Camera for Human Walking Recognition using Marker-based and Markerless for Kinematics of Gait 13

Motion Capture System based on RGB Camera for Human Walking ...

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13th IEEE Symposium on Computer Applications and Industrial Electronics, ISCAIE 2023

作者： Yunardi, Riky Tri Sardjono, Tri Arief Mardiyanto, Ronny Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Biomedical Engineering Faculty of Intelligent Electrical and Informatics Technology Surabaya Indonesia

ISBN: (纸本)9798350347319

The motion capture system has the potential to perform kinematics of gait analysis. Gait analysis can be applied in human activity recognition (HAR) for human walking recognition technology. The walking recognition makes it challenging for researchers to develop using RGB camera with high accuracy. This paper compares the accuracy of vision-based motion capture based on an RGB Camera using marker-based and markerless methods. The evaluation to determine the accuracy of the proposed of both methods was compared with statistical analysis. The marker-based method uses the Kalman filter, and the markerless method uses MediaPipe to measure gait parameters. Development of motion capture that can detect joint leg positions and measure joint angles based on OpenCV. It is designed for joint trajectories and angles at the hip, knee, and ankle. The motion capture system is implemented by a Logitech C270 webcam, Intel core i5 2.1 GHz processor, 8 GB RAM, and processed by JupyterLab with Python programming. It has been tested on recorded video data containing the subject walking straight with three gait cycles: slow, fast, and zigzag. In the marker-based method, each movement's average joint position detection errors are 22 pixels, 134 pixels, and 50 pixels. The angles of the hip and knee joints have an average angle difference with a reference of ±7°. In comparison, the markerless method has an average position error are 23 pixels, 65 pixels, and 49 pixels. And markerless has an average angle difference with a reference of ±5°. © 2023 IEEE.

关键词： Pixels

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Predictive Analytics Model for Optimizing Carbon Emission from Student Activity and Behavior with A Design Thinking Approach Case Study: Bandung Institute of technology 23

Predictive Analytics Model for Optimizing Carbon Emission fr...

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12th International Conference on Software and Computer Applications, ICSCA 2023

作者： Hans, Michael Hikmawati, Erna Surendro, Kridanto School of Electrical Engineering & Informatics Bandung Institute of Technology Indonesia Universitas Nasional PASIM Indonesia

ISBN: (纸本)9781450398589

Global warming is starting to become a major issue to maintain the sustainability of the environment and the earth. This phenomenon is caused by high greenhouse gas emissions, most of which come from human activities. At the university level, there have been many studies related to carbon footprint in universities, but only a few have studied the behavior and activities of the people in it, especially students. Predictive Analytics can be applied as the model to predict the future trends of emission carbon in the university based on the emission carbon data. Design Thinking can be used as an approach to solve such an abstract and complex problem to use the emission data to optimize carbon emissions at the student level. This research is expected to provide insights for universities regarding their level of carbon footprint and provide awareness of this so that several decision-making steps can be taken regarding optimizing carbon emissions at the student level. Bandung Institute of technology will be the subject of this research. This study is preliminary research which will be implemented in the future work. © 2023 Copyright held by the owner/author(s).

关键词： Carbon footprint

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Energy-Aware Heterogeneous Federated Learning via Approximate DNN Accelerators

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IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 2025年第6期44卷 2054-2066页

作者： Pfeiffer, Kilian Balaskas, Konstantinos Siozios, Kostas Henkel, Jorg Karlsruhe Institute of Technology Chair for Embedded Systems Karlsruhe76131 Germany University of Patras Department of Computer Engineering and Informatics Patras26504 Greece Aristotle University of Thessaloniki Department of Physics Thessaloniki54124 Greece

In Federated Learning (FL), devices that participate in the training usually have heterogeneous resources, i.e., energy availability. In current deployments of FL, devices that do not fulfill certain hardware requirements are often dropped from the collaborative training. However, dropping devices in FL can degrade training accuracy and introduce bias or unfairness. Several works have tackled this problem on an algorithm level, e.g., by letting constrained devices train a subset of the server neural network (NN) model. However, it has been observed that these techniques are not effective w.r.t. accuracy. Importantly, they make simplistic assumptions about devices’ resources via indirect metrics, such as multiply accumulate (MAC) operations or peak memory requirements. We observe that memory access costs (that are currently not considered in simplistic metrics) have a significant impact on the energy consumption. In this work, for the first time, we consider on-device accelerator design for FL with heterogeneous devices. We utilize compressed arithmetic formats and approximate computing, targeting to satisfy limited energy budgets. Using a hardware-aware energy model, we observe that, contrary to the state of the art’s moderate energy reduction, our technique allows for lowering the energy requirements (by 4× ) while maintaining higher accuracy. © 1982-2012 IEEE.

关键词： Budget control

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Establishing Pattern Sequences Using Artificial Neural Networks with an Application to Organizational Patterns 10

Establishing Pattern Sequences Using Artificial Neural Netwo...

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10th Workshop on Software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2023

作者： Matovič, Viktor Vranić, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology in Bratislava Ilkovičova 2 Bratislava84216 4 Slovakia

Explicit relationships included in textual description of patterns are insufficient to establish pattern sequences. This article brings a new method of establishing pattern sequences using artificial neural networks. The method is based on extracting implicit relationships between organizational patterns using the softmax regression model by Zhang et al., which are learned by the artificial neural network and encoded in its weights. The implementation of the method is based on the mini-batch stochastic gradient descent method by Zhang et al. and the Keras application programming interface of the TensorFlow framework. To evaluate the method, we conducted four experiments on selected organizational patterns documented by Coplien and Harrison. Two pattern sequences were established in each experiment. For each pattern sequence, a pattern story was created in order to check its meaningfulness. © 2023 Copyright for this paper by its authors.

关键词： artificial neural networks organizational pattern pattern relationships pattern sequence softmax regression

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Hydrodynamic function and spring constant calibration of FluidFM micropipette cantilevers

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Microsystems & Nanoengineering 2024年第1期10卷 277-286页

作者： Attila Bonyár Ágoston G.Nagy Hans Gunstheimer Gotthold Fläschner Robert Horvath Department of Electronics Technology Faculty of Electrical Engineering and InformaticsBudapest University of Technology and EconomicsBudapestHungary Nanobiosensorics Laboratory Institute of Technical Physics and Materials ScienceCentre for Energy ResearchHUN-RENBudapestHungary Nanosurf AG Gräubernstrasse 12CH-4410 LiestalSwitzerland

Fluidic force microscopy(FluidFM)fuses the force sensitivity of atomic force microscopy with the manipulation capabilities of microfluidics by using microfabricated cantilevers with embedded fluidic *** innovation initiated new research and development directions in biology,biophysics,and material *** acquire reliable and reproducible data,the calibration of the force sensor is ***,the hollow FluidFM cantilevers contain a row of parallel pillars inside a rectangular *** precise spring constant calibration of the internally structured cantilever is far from trivial,and existing methods generally assume simplifications that are not applicable to these special types of *** addition,the Sader method,which is currently implemented by the FluidFM community,relies on the precise measurement of the quality factor,which renders the calibration of the spring constant sensitive to *** this study,the hydrodynamic function of these special types of hollow cantilevers was experimentally determined with different *** on the hydrodynamic function,a novel spring constant calibration method was adapted,which relied only on the two resonance frequencies of the cantilever,measured in air and in a *** on these results,our proposed method can be successfully used for the reliable,noise-free calibration of hollow FluidFM cantilevers.

关键词： spring cantilever function

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Quadratic Regression Model Based Predictive Control of PMSM Drives with Field Weakening Operation Capability Constrained to the Linear Modulation Range 32

Quadratic Regression Model Based Predictive Control of PMSM ...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Bándy, Kristóf Stumpf, Péter Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Automation and Applied Informatics Megyetem rkp. 3. H-1111 Budapest Hungary

ISBN: (纸本)9798350399714

Continuous Control Set Model Predictive Control in power electronics has prospective outlooks, however, due to the computational requirements, these techniques are still underutilized. In the paper, a novel method is discussed that allows the reduction of the complex optimization underlying the predictive control algorithm. However, the optimization is further restricted with a non-linear (circular) constraint, that allows the modulator to remain in the linear modulation region. The paper offers an effective solution to the optimization problem, with simulation results showing the effectiveness of the proposed method. © 2023 IEEE.

关键词： Electric drives

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