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Histopathological Cancer Detection with Topological Signatures

Histopathological Cancer Detection with Topological Signatur...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Ankur Yadav Faisal Ahmed Ovidiu Daescu Reyhan Gedik Baris Coskunuzer Dept. of Computer Science U. Texas at Dallas Dept. of Math. Sciences U. Texas at Dallas Dept. of Pathology Harvard - MGH

We present a transformative approach to histopathological cancer detection and grading by introducing a very powerful feature extraction method based on the latest topological data analysis tools. By analyzing the evolution of topological patterns in different color channels, we discovered that every tumor class leaves its own topological footprint in histopathological images, allowing to extract feature vectors that can be used to reliably identify tumor *** topological signatures, even when combined with traditional machine learning methods, provide very fast and highly accurate results in various settings. While most DL models work well for one type of cancer, our model easily adapts to different scenarios, and consistently gives highly competitive results with the state-of-the-art models on benchmark datasets across multiple cancer types including bone, colon, breast, cervical (cytopathology), and prostate cancer. Unlike most DL models, our proposed Topo-ML model does not need any data augmentation or pre-processing steps and works perfectly on small datasets. The model is computationally very efficient, with end-to-end processing taking only a few hours for datasets consisting of thousands of images.

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Design and Development of Neural Network Based Gesture Recognition for Mini Drone Control

Design and Development of Neural Network Based Gesture Recog...

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IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)

作者： Khushi Bhadiyadra Rishabh Kumar Sagar D Jayahar Sivasubramanian Dept. of Automotive and Aeronautical Engineering M. S. Ramaiah University of Applied Sciences Bengaluru India Dept. of Computer Science and Engineering M. S. Ramaiah University of Applied Sciences Bengaluru India

ISBN: (数字)9798350385922

ISBN: (纸本)9798350385939

In this paper, we propose an automatic video processed hand gesture based drone control strategy. It is based on automatic gesture recognition using a camera mounted on the mini-drone and using the neural network concept to control the motion of the drone in terms of longitude and latitude. The model is implemented in two-folds. First, we developed the hardware control strategies to control the camera signals and the motor controls for direction and load. Secondly, we propose to implement the image processing and object/gesture recognition model for control signal generation. The results acquired show cases the accuracy of the hardware response ranging from 0.3 to 1 Sec and software response for gesture recognition being 17 milliseconds, with true-positive and true-negative accuracy being more than 90%.

关键词： Protocols Computational modeling Neural networks Keyboards Gesture recognition Control systems Cameras

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Exploring Mixed-Grid Environments for Drone-Based Last-Mile Logistics Optimization

Exploring Mixed-Grid Environments for Drone-Based Last-Mile ...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Francesco Betti Sorbelli Federico Corò Cristina M. Pinotti Anil Shende Dept. of Computer Science and Mathematics University of Perugia Italy Dept. of Mathematics University of Padua Italy Dept. of Math. CS & Physics Roanoke College

In recent years, drone-based delivery systems have gained significant attention for last-mile logistics in various domains. This study focuses on optimizing drone deliveries in mixed-grid environments, which combine urban and rural areas. The objective is to minimize the sum of distances between the delivery locations and the drone’s depot. By selecting the optimal depot placement, we aim to improve factors such as expected delivery time, energy consumption, and environmental impacts. To address this optimization problem, we conducted a comprehensive comparison of several state-of-the-art algorithms specifically designed for computing the drone placement in mixed-grid environments. Our evaluation utilized synthetic and quasi-real data and two distinct scenarios were considered: the full-grid scenario, and the partial-grid scenario. Through empirical analyses, we demonstrate the effectiveness of the proposed algorithms and provide valuable insights into their trade-offs in terms of performance and time complexity.

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Forecasting Electricity Consumption of Electrical Machines of a Coal Industry Enterprise Using the Wavelet Transform 23

Forecasting Electricity Consumption of Electrical Machines o...

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23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

作者： Manusov, Vadim Z. Orlov, Dmitry V. Karmanov, Vitaly S. Khusnutdinov, Alexander O. Tretyakova, Elena S. Korolev, Dmitry V. Novosibirsk State Technical University Dept. of Industrial Power Supply Systems Novosibirsk Russia Novosibirsk State Technical University Dept. of Theoretical and Applied Computer Science Novosibirsk Russia Angarsk State Technical University Dept. of Power Supply for Industrial Enterprises Angarsk Russia

ISBN: (纸本)9781665498043

Electricity consumption forecasting is an integral part of the workflow in most industries that does not lose its relevance. Modern international energy-control systems do not function without forecast models of electricity consumption. At the same time, daily load schedules of the mining industry are characterized by deterministic chaotic fluctuations in the electricity consumption curve caused by the technology of the production process. The main criteria are the accuracy of the forecast values and the trainability of this model based on the actual data on electricity consumption. A high-quality forecast of electricity consumption for a given planning horizon can significantly increase the energy efficiency of enterprise operation in real time with the possibility of production management of an industrial enterprise by taking into account the possible conditions of the object. In the paper, a mathematical model of short-term forecasting based on the wavelet transform for each hour for the day ahead is proposed. The selection of the model structure taking into account the features of the described process help to find and work with noise and outlier values in the data. The forecast values obtained using eleven basis wavelet functions were compared, and the average percentage values of relative forecast errors for each hour were obtained. The predicted values of electricity consumption for a given planning horizon were verified on test data in order to assess the relevance of the forecast model. © 2022 IEEE.

关键词： Wavelet transforms

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Thermal Model Validation of a Power Electronics Module for Digital Twin Application

Thermal Model Validation of a Power Electronics Module for D...

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European Conference on Power Electronics and Applications

作者： Svenja Zöller Claudia Cabre-Piqueras Boris Schilder Alber Filba-Martinez Lukas Acker Faculty of Computer Science and Engineering Frankfurt University of Applied Science Frankfurt Germany Power Systems Dept. Catalonia Institute for Energy Research (IREC) Barcelona Spain

ISBN: (数字)9798350364446

ISBN: (纸本)9798350364453

Thermal stress is a critical failure factor for power electronics components. Hence, when developing a precise digital twin for a power system, it is imperative that thermal models provide a reliable portrayal of the component physics. In that regard, manufacturers offer simplified thermal models that enable designers and users to estimate its behaviour. Nevertheless, the accuracy of these models remains unknown, thus compromising the overall certainty of the digital twin. Therefore, it is of interest to discern whether these simplified models are sufficient for the precision required by the digital twin, and to assess the need of developing a more accurate model. Hence, this paper focuses on validating the theoretical thermal model of a power electronics switch module setup by using the deviation of the module mean time to failure (MTTF) as the acceptance parameter. To achieve this, a novel experimental validation methodology is proposed to retrieve an experimental thermal model and compare it to the theoretical one. This validation is performed considering the discrete thermal impedances and introducing the study of the coupling effects within the module.

关键词： Couplings Accuracy Europe Switches Power electronics Digital twins Power system reliability Reliability Thermal stresses Stress

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Text-independent Speaker Recognition: A Deep Learning Approach

Text-independent Speaker Recognition: A Deep Learning Approa...

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

作者： Arman Shirzad Ali Nasiri Razieh Darshi Zohreh Safarpour Razieh Abdollahipour Dept. of Computer Engineering University of Science and Culture Tehran Iran Dept. of Electrical and Computer Engineering University of Tabriz Tabriz Iran Dept. of Electrical Engineering Iran University of Science and Technology Tehran Iran Dept. of Electrical Engineering Berlin University of Applied Sciences Berlin Germany Dept. of Sensors and Modeling Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) Potsdam Germany

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

In this study, we introduce an artificial neural network (ANN) model specifically designed for speaker recognition and compare its performance and accuracy with that of the established Keras speaker recognition model. Our investigation utilizes two distinct datasets: the first comprises voice recordings in three different languages from both male and female speakers; the second is the widely recognized LibriSpeech dataset, a comprehensive corpus of English speech derived from 50 individuals reading audiobooks. The proposed model leverages the Fast Fourier Transform (FFT) to analyze the input data, which consists of labeled .wav files. These files undergo a preprocessing stage before being input into the ANN for training. Our results indicate that while the proposed model outperforms the Keras model on the first dataset, it exhibits marginally lower performance on the LibriSpeech dataset. This finding suggests that even well-established models like those provided by Keras may not universally deliver optimal results across different datasets.

关键词： Training Analytical models Accuracy Fast Fourier transforms Computational modeling Speech recognition Artificial neural networks Data models Speaker recognition Recording

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Using a Design Pattern to Build Microservices for Instant Messaging Software to Access IoT Devices

Using a Design Pattern to Build Microservices for Instant Me...

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IEEE Global Conference on Consumer Electronics (GCCE)

作者： Hsin-Yu Huang Yong-Yi Fanjiang Hsing-Yu Tsai Yung-Shiang Huang Yi-Shiang Yu Dept. of Digital Multimedia Lee-Ming Institute of Technology New Taipei City Taiwan Dept. of Computer Science and Information Engineering Graduate Institute of Applied Science and Engineering Fu Jen Catholic University New Taipei City Taiwan Dept. of Computer Science and Information Engineering Fu Jen Catholic University New Taipei City Taiwan

ISBN: (数字)9798350355079

ISBN: (纸本)9798350355086

This study introduces a design pattern to build microservices, which provides an opportunity for instant messaging software developers, Internet of Things(IoT) device manufacturers and third parties to deploy themselves belonging to the APIs in microservices. Users can use instant messaging software to access IoT devices through the APIs deployed by the system. Instant messaging software developers, IoT device manufacturers and third parties can develop and deploy APIs in Instant Messaging (IM) microservice and IoT microservice of this system based on the OpenAPI specification document using a design pattern. The goal of this system is for users to use the installed and usually used instant messaging software without having to install and learn new app to access various IoT devices.

关键词： Microservice architectures Instant messaging Software Internet of Things Smart phones Consumer electronics

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Adaptive Filtering Methods for ECG Waveform Restoration during Cardiopulmonary Resuscitation

Adaptive Filtering Methods for ECG Waveform Restoration duri...

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2022 Computing in Cardiology, CinC 2022

作者： Iza, Alvaro Elola, Andoni Isasi, Iraia Aramendi, Elisabete Eftestol, Trygve Kramer-Johansen, Jo Wik, Lars Communications Engineering Dept. University of the Basque Country Bilbao Spain Electronic Technology Dept. University of the Basque Country Bilbao Spain Applied Mathematics Dept. University of the Basque Country Bilbao Spain Electrical Engineering and Computer Science Dept. University of Stavanger Stavanger Norway Oslo University Hospital Oslo Norway

ISBN: (纸本)9798350300970

An artifact-free ECG is essential during cardiopulmonary resuscitation (CPR) to decide adequate therapy. Chest compressions (CCs) cause artifacts that alter the ECG waveform. This study analyzes the effectiveness of CPR artifact suppression filters to restore the ECG. For that purpose, artificial mixtures of artifact-free ECGs and CPR artifacts mixed at different signal-to-noise ratios (SNRin) were used. Several configurations of three state-of-the-art filters were compared: Least Mean Squares (LMS), Recursive Least Squares (RLS) and Kalman. Performance was evaluated by comparing the artifact-free ECGs and the filtered ECGs in terms of the restored SNR (SNRres) and the Pearson's Correlation coefficient (PCC). RLS was the best option with a mean SNRres of 3.3 dB at the optimal working point, slightly above the LMS algorithm in terms of SNRres. The similarity of the restored and the clean ECG increased with SNRin, obtaining PCC values above 0.6 for SNRin > -5 dB. In conclusion, suitable filtering methods to restore ECG waveforms during CPR were proposed, that would enhance the reliability of the ECG analysis during CCs. © 2022 Creative Commons.

关键词： Electrocardiograms

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Object-aware Multi-criteria Decision-Making Approach using the Heuristic data-driven Theory for Intelligent Transportation Systems 10

Object-aware Multi-criteria Decision-Making Approach using t...

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10th IEEE International Conference on Data science and Advanced Analytics, DSAA 2023

作者： Mekala, M.S. Eyad, Elyan Srivastava, Gautam Robert Gordon University School of Computing AberdeenAB10 7AQ United Kingdom Brandon University Dept. of Math and Computer Science BrandonMB R7A 6A9 Canada

ISBN: (纸本)9798350345032

Sharing up-to-date information about the surrounding measured by On-Board Units (OBUs) and Roadside Units (RSUs) is crucial in accomplishing traffic efficiency and pedestrians safety towards Intelligent Transportation Systems (ITS). Transferring measured data demands geq10Gbit/s transfer rate and geq1GHz bandwidth though the data is lost due to unusual data transfer size and impaired line of sight (LOS) propagation. Most existing models concentrated on resource optimization instead of measured data optimization. Subsequently, RSU-LiDARs have become increasingly popular in addressing object detection, mapping and resource optimization issues of Edge-based Software-Defined Vehicular Orchestration (ESDVO). In this regard, we design a two-step data-driven optimization approach called Object-aware Multi-criteria Decision-Making (OMDM) approach. First, the surroundings-measured data by RSUs and OBUs is processed by cropping object-enabled frames using YoLo and FRCNN at RSU. The cropped data likely share over the environment based on the RSU Computation-Communication method. Second, selecting the potential vehicle/device is treated as an NP-hard problem that shares information over the network for effective path trajectory and stores the cosine data at the fog server for end-user accessibility. In addition, we use a nonlinear programming multi-tenancy heuristic method to improve resource utilization rates based on device preference predictions (Like detection accuracy and bounding box tracking) which elaborately concentrate in future work. The simulation results agree with the targeted effectiveness of our approach, i.e., mAP(geq71%) with processing delay (leq3.5times 10{6}bits/slot), and transfer delay (leq3Sms). Our simulation results indicate that our approach is highly effective. © 2023 IEEE.

关键词： Object detection

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On the Way to Realize the 5thIndustrial Revolution: Achievements, Challenges and Research Areas 36

On the Way to Realize the 5thIndustrial Revolution: Achievem...

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36th IEEE/IFIP Network Operations and Management Symposium, NOMS 2023

作者： Dimirakopoulos, George Gutt, Thomas Ehm, Hans Hoess, Alfred Karathanasopoulou, Konstantina Lackner, Anna Schneider, Germar Harokopio Univesity of Athens Dept. of Informatics and Telematics Athens Greece Infineon Technologies A.G. Munich Germany University of Applied Sciences Amberg-Weiden Dept. of Electrical Engineering Media and Computer Science Amberg Germany Eesy-innovation GmbH Unterhaching Germany Infineon Technologies Dresden GmbH&Co.KG Dresden Germany

ISBN: (纸本)9781665477161

The industrial world is rapidly moving towards its 5th industrial revolution (a.k.a. 'Industry5.0'). Industry5.0 is reflected on the digital sovereignty in comprehensively sustainable production, through adopting, extending and implementing A I-enabled hardware, as well as A I tools & methods and semiconductors technology across the whole industrial value chain. It is expected that in doing so, manufacturing costs will be decreased, while at the same time, product quality will be increased through AI-enabled innovation, time-to-market will be shortened and user acceptance of versatile technology offerings will be achieved and global supply chains stabilized. The above will, in turn, foster a sustainable development, in an economical, ecological and societal sense and act as enablers for the Green Deal. This paper accordingly discusses on the fundamental research areas relevant to further advancing the digitalized industry, its research and development achievements so far, as well as the challenges confronted, in order to boost industrial competitiveness through interdisciplinary innovations, establishing sustainable value chains and therefore contribute to the Digital Sovereignty. © 2023 IEEE.

关键词： Sustainable development

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