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Semantic Segmentation of Brain Tumors: A Performance Evaluation Using DeepLabV3+, UNet, and Intel’s OpenVINO Toolkit

Semantic Segmentation of Brain Tumors: A Performance Evaluat...

引用

International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Medina Kapo Amila Akagic Emir Buza Department of Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Artificial intelligence, Machine Learning, and Deep Learning are increasingly making significant contributions to the field of medicine. Individual patient conditions, disease localization, and various influencing factors underscore the complexity of disease diagnosis and treatment planning. Introducing new technologies can revolutionize medical diagnostics, facilitating swift and accurate assessments. Among the noninvasive diagnostic methods, Magnetic Resonance Imaging (MRI) stands out, particularly in tumor diagnosis. UNet, renowned for its effectiveness in medical image analysis, serves as a robust model for semantic segmentation, as does DeepLabV3+. However, these models are inherently complex, and their inference process can be time-consuming. By leveraging the OpenVINO toolkit, the inference process is significantly reduced. In this study, nearly a 2-fold acceleration is achieved in inference time with the DeepLabV3+ model and a roughly 1.2-fold improvement with the UNet model on CPU. Moreover, when employing GPU with FP16 precision, the acceleration reached almost 2.5fold for UNet and nearly 3-fold for DeepLabV3+, showcasing the substantial performance enhancements attainable through optimized hardware utilization.

关键词： Deep learning Adaptation models Semantic segmentation Magnetic resonance imaging Graphics processing units Brain modeling Hardware Medical diagnosis Medical diagnostic imaging Tumors

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Smart Traffic Light Using Raspberry Pi and Digital Image Processing 9

Smart Traffic Light Using Raspberry Pi and Digital Image Pro...

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9th International Conference on Wireless and Telematics, ICWT 2023

作者： Susilawati, Helfy Pathur Rahman, Shelmy Luthfi Rukmana, Ade Malik Matin, Iik Muhamad Sarbini Ismail, Nanang Universitas Garut Electrical Engineering Departement Garut Indonesia Computer and Informatics Engineering Jakarta State Polytechnic Jakarta Indonesia Uin Sunan Gunung DJati Bandung Psychology Department Bandung Indonesia Uin Sunan Gunung DJati Bandung Departement of Electrical Engineering Bandung Indonesia

ISBN: (纸本)9798350305029

Congestion is one of the problems in traffic, especially at intersections with traffic lights. In this study, a traffic light management system was developed by utilizing image processing that can adjust the duration in the queue depending on road conditions. The system is developed using Raspberry Pi 4 as the controller. The system will capture the image of the traffic conditions via cameras and then perform the image processing using OpenCV and Tensorflow to calculate the number of vehicles. The number of vehicles will be sent to the webserver database to be processed as the input for traffic system settings. The testing shows that the system can set the timing of the traffic lights. When there are 3 vehicles in the queue with traffic light is red then the system set the timing for the green light to 10 seconds. Additional of 1 vehicle in the queue will increase the duration of the green light by 4 seconds. © 2023 IEEE.

关键词： Image processing

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Observing Generator Performance by Finite Element Analysis Considering Coil Numbers 5

Observing Generator Performance by Finite Element Analysis C...

引用

5th International Conference on Technology and Policy in Energy and Electric Power, ICT-PEP 2023

作者： Habibi, Muhammad Afnan Ali Irfani, Mochamad Farhan Gumilar, Langlang Kusumawardana, Arya Aripriharta Baskoro, Angger Universitas Negeri Malang Study Program of Power Plant Engineering Technology Malang Indonesia Universitas Negeri Malang Department of Electrical Engineering and Informatics Malang Indonesia National Yang Ming Chiao Tung University Dept. Electrical Engineering and Computer Sciences Hsinchu Taiwan

ISBN: (纸本)9798350369717

This paper conducts a comprehensive analysis of electrical generator performance using Finite Element Analysis (FEA), with a specific emphasis on the role of coil numbers in influencing generator efficiency and functionality. In the context of modern energy systems, where efficient power generation is paramount, this research aims to elucidate the relationship between the number of coils within a generator and its overall performance, including power output and electromagnetic behavior. Through systematic FEA simulations that vary coil numbers while keeping other parameters constant, this study provides valuable insights into the trade-offs associated with increased coil numbers and enhanced efficiency. These findings have significant implications for optimizing generator designs across various applications, from renewable energy systems to industrial power generation, ultimately advancing our understanding of generator dynamics and contributing to more sustainable and efficient power generation technologies. © 2023 IEEE.

关键词： Finite element method

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Classification of Arrhythmias 12-Lead ECG Signals Based on 1 Dimensional Convolutional Neural Networks

Classification of Arrhythmias 12-Lead ECG Signals Based on 1...

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Smart Computing, IoT and Machine Learning (SIML), International Conference on

作者： Arief Kurniawan Bayu Aditya Triwibowo Dion Hayu Fandiantoro Department of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember

ISBN: (数字)9798350364101

ISBN: (纸本)9798350364118

Heart disease is the highest cause of death in the world. Arrhythmia is an abnormality in the rhythm of the heartbeat. The heart beats too fast, too slow, or irregularly. Arrhythmias are not always dangerous, e.g., someone who does excessive activity has a faster heart rate. Then, a diagnosis is needed to classify arrhythmias. One method used is ECG (Electrocardiogram) signal analysis. The ECG signal consists of P, QRS Complex, and T waves. The morphology of the QRS is used for arrhythmia classification. Currently, cardiologists analyze ECG signals by observing directly. This method is depending on the level of expertise of the cardiologist. Previous research classified arrhythmias based on the QRS morphology from a single ECG lead. As 12-lead ECG devices have now become standard in ECG examinations because abnormalities can be observed from multiple angles. This study proposes the classification of arrhythmias in 12-lead ECG signals based on the morphology of QRS complex waves using a deep learning 1-dimensional Convolutional Neural Network. The output of deep learning is the classification of arrhythmias into four classes, namely: Normal, Right Bundle Branch Block, Premature Ventricular Contraction, and Atrial Premature Beat. The outcome of the proposed system is that each QRS segment is used as input for deep learning, which can improve classification performance compared to the classification carried out by each lead. The experimental results show the method can be done well, with an average Accuracy, Precision, Sensitivity, and F1-Score were 98.8%, 99.2%, 99.2%, and 99.2%, respectively.

关键词： Deep learning Accuracy Sensitivity Heart beat Arrhythmia Morphology Electrocardiography

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Predictive Analysis of Sarajevo’s AQI using Machine Learning Models for Varied Data Granularity and Prediction Windows

Predictive Analysis of Sarajevo’s AQI using Machine Learnin...

引用

Proceedings of the International Convention MIPRO

作者： Emina Zolota Vahidin Hasić Amina Mević Amra Delić Senka Krivić Department for Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (数字)9798350382501

ISBN: (纸本)9798350382518

This study scrutinizes five years of Sarajevo’s Air Quality Index (AQI) data using diverse machine learning models — Fourier autoregressive integrated moving average (Fourier ARIMA), Prophet, and Long short-term memory (LSTM)—to forecast AQI levels. Focusing on various prediction frames, we evaluate model performances and identify optimal strategies for different temporal granularities. Our research unveils subtle insights into each model’s efficacy, shedding light on their strengths and limitations in predicting AQI across varied timeframes. This research presents a robust framework for automatic optimization of AQI predictions, emphasizing the influence of temporal granularity on prediction accuracy, automatically selecting the most efficient models and parameters. These insights hold significant implications for data-driven decision-making in urban air quality control, paving the way for proactive and targeted interventions to improve air quality in Sarajevo and similar urban environments.

关键词： Accuracy Atmospheric modeling Urban areas Machine learning Predictive models Air quality Data models

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Cybersecurity of Sensors on Smart Vehicles: Review of Threats and Solutions 6

Cybersecurity of Sensors on Smart Vehicles: Review of Threat...

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6th International Conference on computer and informatics engineering, IC2IE 2023

作者： Putro, Prasetyo Adi Wibowo Amelia, Fetty Pidanic, Jan Suhartanto, Heru Rahardjo, Imam Arif Imandeka, Ejo Universitas Indonesia Faculty of Computer Science Depok Indonesia Cryptographic Hardware Engineering Politeknik Siber Dan Sandi Negara Bogor Indonesia University of Pardubice Faculty of Electrical Engineering and Informatics Pardubice Czech Republic Universitas Negeri Jakarta Department of Electrical Engineering Jakarta Indonesia

ISBN: (纸本)9798350345162

The use of sensors in smart vehicles brings benefits and vulnerabilities. Different kinds of sensors in smart vehicles are vulnerable to cyber-attack. Until now, the investigation of challenges and solutions for in-vehicle cybersecurity hasn't discussed various sensor objects and their correlation. In this study, we studied the cyber security problems of sensors in smart vehicles and how to overcome them. The research was designed as Systematic Literature Review (SLR) using the Kitchenham methodology with modification in the filtering phase using the artificial intelligence application, Elicit, to identify the problems, conclusions, and methodology description. Seventeen publications from 2016 until 2023 were gained from five databases. As a result, we find that the most discussed object related to cybersecurity sensors on smart vehicles are Electronic Control Units. Spoofing and jamming is still the most addressed threat, and machine learning is the most utilized solution to be implemented in detection systems. Advanced detection systems are incorporating updated attack models. We also suggest using updated attack models and machine learning algorithms to ensure the safety and security of smart vehicle technology. All identified sensor technology correlated using mind maps under the Intelligent Transport System theory. © 2023 IEEE.

关键词： cybersecurity Kitchenham sensor SLR smart vehicles solution threat

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High-Resolution Wideband DOA Estimation Based on Multi-Frequency Cyclic Rank-Minimization

High-Resolution Wideband DOA Estimation Based on Multi-Frequ...

引用

IEEE International Conference on Communications (ICC)

作者： Y. Hedeng Zhenlong Xiao Xinghao Ding Xianbin Wang School of Informatics Xiamen University China Department of Electrical and Computer Engineering Western University Canada

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Wideband DOA estimation has been applied in various signal source location scenarios, e.g., in wireless communication systems to improve the capacity of communication. Existing wideband DOA methods often require prior knowledge such as the number of sources as well as pre-estimations. Moreover, they may suffer from model-mismatch problem. In this paper, we employ the manifold separation technique and Jacobi-Anger expansion to allow multi-frequency joint processing of wideband DOA, which alleviates the challenge of model-mismatch and leads to a much higher DOA resolution. The proposed method is further formulated to be a multi-convex rank-minimization problem to facilitate the analysis of the problem and to improve the convergence performance. The superior performance of the proposed multi-frequency joint processing method has been demonstrated by several numerical studies.

关键词： Jacobian matrices Wireless communication Direction-of-arrival estimation Simulation Estimation Customer relationship management Numerical models

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Modeling Blockage in High Directional Wireless Systems 2

Modeling Blockage in High Directional Wireless Systems

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2nd IEEE Virtual Conference on Communications, VCC 2024

作者： Koutsonas, Evangelos Boulogeorgos, Alexandros-Apostolos A. Trevlakis, Stylianos E. Ali, Tanweer Tsiftis, Theodoros A. University of Western Macedonia Department of Electrical and Computer Engineering Kozani50100 Greece InnoCube P.C. Research and Development Department Thessaloniki55535 Greece Manipal Institute of Technology Manipal Academy of Higher Education Department of Electronics and Communication Engineering Manipal576104 India University of Thessaly Department of Informatics and Telecommunications Lamia35100 Greece University of Nottingham Ningbo China Department of Electrical and Electronic Engineering Ningbo315100 China

ISBN: (纸本)9798331530099

While the wireless word moves towards higher frequency bands, new challenges arises, due to the inherent characteristics of the transmission links, such as high path and penetration losses. Penetration losses causes blockages that in turn can significantly reduce the signal strength at the receiver. Most published contributions consider a binary blockage stage, i.e. either fully blocked or blockage-free links. However, in realistic scenarios, a link can be partially blocked. Motivated by this, in this paper, we present two low-complexity models that are based on tight approximations and accommodates the impact of partial blockage in high-frequency links. To demonstrate the applicability of the derived framework, we present closed-form expressions for the outage probability for the case in which the distance between the center of the receiver plane and the blocker's shadow center follow uniform distribution. Numerical results verify the derived framework and reveal how the transmission parameters affect blockage. © 2024 IEEE.

关键词： Blockage high-frequency communications modeling outage probability

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Embedded Real-Time Analogue NeoPixel Clock

Embedded Real-Time Analogue NeoPixel Clock

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Mehmed Mujić Ehlimana Cogo Ingmar Bešić Department of Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

Embedded real-time clock systems have a large number of applications in practice. The main issue is the accuracy of time they show, which is why performing time synchronization is very important for their usability and reliability. This paper proposes an embedded real-time analogue clock that uses an AdaFruit NeoPixel LED ring for visualizing current time. Three different colors are used for showing hour, minute and second values, whereas different levels of brightness are used for describing accurate values of time to the level of milliseconds. An Ethernet LAN module is used for performing time synchronization via a remote NTP server. Dynamic synchronization interval change is used for removing the effect of the microcontroller clock error on the accuracy of the shown time. After being put to use, the system was able to perform multiple functions successfully, including the conveying of information to the user when the clock is out of sync.

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Multi-Criteria Decision-Making Approach for Laptop Selection: A Case Study 3

Multi-Criteria Decision-Making Approach for Laptop Selection...

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3rd IEEE Asian Conference on Innovation in Technology, ASIANCON 2023

作者： Channi, Harpreet Kaur Sandhu, Ramandeep Faiz, Mohammad Islam, Sardar M. N. Chandigarh University Gharuan Department of Electrical Engineering Punjab Mohali India School of Computer Science and Engineering Lovely Professional University Punjab Jalandhar India Victoria University Applied Informatics Research Melbourne Australia

ISBN: (纸本)9798350302288

This article uses the well-known multi-criteria decision-making (MCDM) theory to determine which laptop is the best among those that are currently on the market. To illustrate the importance of decision-making in a class of 25 students, data on laptop features was gathered for this case study. The following eight factors were considered while choosing an option: price, weight, RAM, camera megapixels, screen size, clock speed, operating system, and laptop appearance. SAW and WPM determine the optimal laptop alternative. To rank laptop qualities, identical weights are applied. The suggested work displays laptop rankings derived by SAW and WPM methods. Future engineers and management may benefit significantly from this straightforward decision-making process. More important attributes/criteria and alternatives may be taken into account, and there are a variety of weighting techniques from which to choose. The study emphasizes the importance of incorporating user preferences and real-time market data to ensure personalized and up-to-date laptop recommendations. Through this approach, users can make well-informed decisions that align with their specific needs and environmental considerations. © 2023 IEEE.

关键词： Decision making

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