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2023 European Data Handling and Data Processing Conference for Space, EDHPC 2023

作者： Sridharan, Saish Qedar, Ran Space Products and Innovation GmbH System Engineer and Technical Lead Darmstadt Germany Space Products and Innovation SRL Software and System Engineer Frascati Italy

This paper describes an ESA project that maps and tests interface and protocol compatibility of European cubesat/smallsat avionics-components. The project is called the Modular-Avionics-Test-Bench (MATB). The outcome ... 详细信息

ISBN: (纸本)9789090379241

关键词： Avionics

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Utilization of Automotive SPICE Assessments with Cybersecurity Extension 1

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29th European systems, software and Services Process Improvement, EuroSPI 2022

作者： Zinhom, Engy Provisional ASPICE Assessor and Senior System and Software Quality Assurance Engineer Valeo Egypt

ISBN: (数字)9783031155598

ISBN: (纸本)9783031155581

ASPICE has been introduced to the development of embedded systems at automotive suppliers to assess the capability of processes. ASPICE covers processes for software, system, quality assurance, configuration management, problem resolution, change management, project management, and supplier monitoring. It defines a scheme for determining the capability of the process based on the underlying PAM. Regarding the new appendix of A-SPICE, HW SPICE is considered because it is also necessary for Cybersecurity, but not mechanical SPICE so far. Based on A-SPICE PRM, VDA has defined new processes for Cybersecurity engineering, Cybersecurity Risk Management, and Supplier Request and Selection. This means additional effort for the assessors and the engineering team when the ASPICE assessment is extended by processes of Cybersecurity to satisfy the requirements of standard ISO/SAE 21434. This paper investigates the method of mapping the base practices (BP) of the cyber-security process defined by VDA to BP of some A-SPICE processes to reduce the time of an assessment by merging the Base Practices of Processes from Cybersecurity with the Base Practices of Processes from ASPICE. © 2022, Springer Nature Switzerland AG.

关键词： Risk management

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Hand-Drawn Electronic Component Recognition Using ORB

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Procedia Computer Science 2023年 218卷 504-513页

作者： S Pavithra N K Shreyashwini H S Bhavana G Nikhitha T Kavitha Assistant System Engineer TCS VLSI design & Verification Engineer HCL Project Engineer WIPRO Software Developer Craft Silicone Professor New Horizon College of Engineering

There is growth in interest to build a system that can recognize freely drawn symbols. In past two years, the situation in the world has become more difficult, almost all the work in their organizations has been digitalized. However, many challenges remain in terms of the recognition accuracy of different drawing styles. To address these challenges, a new approach is proposed to classify and predict the hand-drawn component. In this work Computer Vision approach using the ORB algorithm is used to recognize and predict the component. The drawing tools that are being used need to be upgraded in order to have a better learning experience in order to recognize the symbol that is drawn and directly convert it into digitized form. As it is very difficult to write it on an online platform every time this method would be very useful. Here 15 different electronic components are considered with three different orientations. In this approach, GUI is used to draw the symbol which is easy instead of picking and placing. This input-drawn image is given to the model developed using the CV algorithm, where the input image gets compared with the database image, according to ORB using the FAST method key points are generated for both images. Using a Brute force matcher both images get matched depending on the number of matched features, and the output image gets predicted. The results of the ORB and SIFT CV algorithms are analyzed and compared.

关键词： Computer vision electronic component symbol sift orb key point matching

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Modular Avionics Test Bench

Modular Avionics Test Bench

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Data Handling & Data Processing Conference (EDHPC), European

作者： Saish Sridharan Ran Qedar System Engineer and Technical Lead Space Products and Innovation GmbH Darmstadt Germany Software and System Engineer Space Products and Innovation SRL Frascatti Italy

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Research on Adaptive Evolution Architecture for Spacecraft Control system 2

Research on Adaptive Evolution Architecture for Spacecraft C...

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2nd Asia Conference on Advanced Robotics, Automation, and Control engineering, ARACE 2023

作者： Wang, Ruozhang Chen, Zhaohui Du, Janwei Beijing Institute of Control Engineering Software Center Beijing China Beijing Institute of Control Engineering Chief Engineer's Office Beijing China Beijing Institute of Control Engineering System Innovation Center Beijing China

ISBN: (纸本)9798350328363

With the continuous expansion of space missions and the growth on complexity of on-board software, improving the adaptive evolution ability of spacecraft control system becomes an important research issue. This paper focus on the adaptive evolution architecture of spacecraft software, which aims to solve the problems including software and hardware coupling, logic and information coupling, etc. And it introduces adaptive evolution layer to the architecture and enhances software flexibility through hierarchy and modularity. Besides, the dynamic parsing execution mechanism of evolution rule is proposed to provide the basic support for the dynamic adjustment through task scheduling, system parameters, and task logic. The architecture and mechanism have good application value for realizing adaptive evolution of spacecraft control system. © 2023 IEEE.

关键词： Memory architecture

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Social Media Multi-Emotion Detection 2

Social Media Multi-Emotion Detection

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2nd International Conference on Advanced Innovations in Smart Cities, ICAISC 2025

作者： Ibrahiem, Soha S. El-Sayed Mohammed, Bahy Ibrahim El Sayed Ahmed, Mohammed Ahmed Elbahnasy, Khaled Menofia University Computality R&D System Analyst & Nlp Researcher Faculty of Science Menofia Egypt Web Developer Cairo Egypt Software Engineer Ekad Soft Cairo Egypt Jeddah International College Computer Science and Information Technology Department Jeddah Saudi Arabia

ISBN: (纸本)9798331506995

Natural language in social media is often ambiguous, carrying diverse perspectives that are critical for opinion analysis. With vast amounts of unstructured data, particularly on platforms like Twitter, it is impractical to manually analyse relevant insights. This rapid data growth has highlighted the need for intelligent filtering and mining techniques in decision support systems to help organizations build brand reputation, foster online communities, and enhance profitability. Multi-Emotion detection is key for capturing implicit user opinions and specific emotional states;however, challenges such as text bipolarity, limited representative feature vectors, and inadequate annotated lexicons often hinder accuracy. This research aims to improve multi-emotion detection accuracy by extracting emotion implied tokens and converting them into feature vectors that capture semantic relevance. Using annotated lexicons, word embeddings, unigrams, and term frequency, these vectors are trained across five machine learning models, which are Naïve Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), K- nearest neighbor (KNN), and Multi- layer Percepton (MLP). Finally, two ensemble techniques are applied to refine model outputs, achieving an improvement accuracy over previous work worked. The proposed system, evaluated on a real dataset, achieves a hamming score of 0.55 and an average F1 score of 0.68, demonstrating its potential for effective multi-label emotion detection. © 2025 IEEE.

关键词： Tweets

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TexGAN: Textile Pattern Generation Using Deep Convolutional Generative Adversarial Network (DCGAN)

TexGAN: Textile Pattern Generation Using Deep Convolutional ...

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2023 IEEE International Conference on Emerging Trends in engineering, Sciences and Technology, ICES and T 2023

作者： Yar, Ghulam Nabi Ahmad Hassan Taha, Muhammad Afzal, Zeshan Zafar, Farhan Shahid, Inam-Ur-Rehman Noor-Ul-Hassan, Abubakar AI Developer Maanz-AI Pakistan Team Lead RandD Technosense21 Pvt Ltd The Islamia University Department of Software Engineering Islamabad Pakistan ZR-Tech Greater Manchester United Kingdom Design Engineer Embedded System AKSA-SDS Pakistan Software Developer Nakisa Inc. Pakistan

ISBN: (纸本)9781665455602

Generative Adversarial Networks (GANs) are used for image, video, and 3D scene generation along with their ability to enhance images. In image generation, GANs generate new images by learning features from the existing images. Features are extracted by a convolutional network, and images are generated through a de-convolutional network. GANs have been recently applied to the field of fashion where they have been used to generate new kinds of shoes and clothes. In the field of textile design, designs are printed onto clothes. These designs are mostly made of single repetitive patterns. These patterns need to be created by the designers and then these patterns are photoshopped to make the whole design. Generating textile patterns through GANs can help designers to take inspiration for new ideas. To achieve this goal GANs have been proposed to generate new patterns. Different variants of GANs are available in fields and they helped in many other fields along with the field of fashion. At first, we formulated a dataset of 17k+ images collected via google images. The dataset is available at the GitHub repository of the project (https://***/Gnahy/***). We provided an idea of generating textile patterns in general and one can also specify the patterns they want to generate i.e., cheetah, geometric, and abstract. DCGAN has been trained on all the patterns collectively up to a specific point and the weights from the trained model have been saved. After that point model is trained on specific kinds of patterns i.e., cheetah in order to generate that specific kind of new patterns. This technique helps even when the data for the new patterns are small and resources to train the model are fewer. © 2023 IEEE.

关键词： Generative adversarial networks

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Implementation Learning Vector Quantization Using Neural Network for Classification of Ear, Nose and Throat Disease 1

Implementation Learning Vector Quantization Using Neural Net...

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1st Lekantara Annual Conference on engineering and Information Technology, LiTE 2021

作者： Samsir, Samsir Daulay, Nelly Khairani Harahap, Syaiful Zuhri Zalmi, Wahyuni Fithratul Sari, Afni Nia Nasution, Fitri Aini Watrianthos, Ronal Department of Informatics Engineering Universitas Al Washliyah Labuhanbatu Indonesia Department of Computer System Universitas Bina Insan Indonesia Department of Information System Universitas Labuhanbatu Indonesia Department of Information System Universitas Putra Indonesia Padang Indonesia Department of Software Engineer Universitas Dharmawangsa Medan Indonesia

This study aims to use data from 57 patients at Rantauprapat Hospital to train a Neural Network using a quantization learning vector method for the categorization of ear, nose, and throat disorders. The input factors were fever, tiredness, nausea, breathing pain, sore throat, hearing loss, allergies, chills and sweating, and thick and transparent mucus. The factors studied were ear canal infections, pharyngitis of the neck, throat, nose, and sinusitis. The findings revealed that ten neurons with an objective value of 0.01 in the learning rate range of 0.01 - 0.05 resulted in categorizing snoring, nose, and ear disorders, including the input layer. The MATLAB program is utilized in this approach, with an average accuracy of 67 per cent and a mean square error of 0.2. © Published under licence by IOP Publishing Ltd.

关键词： Mean square error

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Tow-Body Control system Modeling and Tuning on a Real-World Vehicle

Tow-Body Control System Modeling and Tuning on a Real-World ...

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OCEANS

作者： Jasmine Cashbaugh Droppers Wesley Fisher Andriy Predmyrskyy Control Systems Engineer Kraken Robotic Systems Dartmouth Canada Software Developer Kraken Robotic Systems Dartmouth Canada Control System Engineer Kraken Robotic Systems Dartmouth Canada

This paper presents a model-based approach for developing a stable, robust control system for a shallow water survey towfish. A model of the towfish system was developed based on experimental data from open-water operations. This model was then implemented in Simulink and a Bode analysis was performed on the open loop transfer functions. Once the desired phase margin crossover frequency was achieved, the system was run in Simulink to ensure the performance of the system met overshoot and stability requirements. Finally, the improved gains were tested in open water sea trials in Bedford Basin and the nearby open water. Both improved gain sets resulted in better performance that the original baseline gain set and have been demonstrated to meet the requirements for high quality Synthetic Aperture Sonar imagery and SeaVision™ 3D laser imaging. These control system improvements have since been implemented on systems worldwide as part of Kraken Robotic systems’ ongoing product support and operational improvements were realized immediately in the field.

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Development of Multi Objective Approach for Validation of PID Controller for Buck Converter 1

Development of Multi Objective Approach for Validation of PI...

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1st International Conference on Advances in Computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Arun Kumar, K. Vegineni, Gopi Chand Suresh, C. Chowdari Marella, Bhagath Chandra Addanki, Sireesha Chimwal, Palak Big Data Architect India Sr.Software Engineer Enrollment and Eligibility Team India Electrical and Electronics Engineering School of Engineering and Technology Dhanalakshmi Srinivasan University Trichy Samayapuram621112 India Insights & Data Capgemini Department of Financial Services India System soft Technologies LLC India Bipin Tripathi Kumaon Institute of Technology Department of Electrical Engineering Almora Dwarahat India

ISBN: (纸本)9798331518578

Buck converters are a common converter of DCDC used for high energy conversion and power sources. These regulators are utilized in electronic gear to alter the result voltage because of changes in the heap current and information voltage. Therefore, in order to react to enquiries in real time, an efficient control system is required. In this work, an upgraded Sine Cosine Algorithm (ISCA) with proportional-integral-derivative (PID) controller is proposed for Mult objective optimization of a DC-DC buck converter. Through two distinct modifications, the limitations of the traditional SCA were therefore addressed, leading to the innovative use of nonlinear equations in conjunction with instrumental mechanisms to update the average location. By contrasting its response for frequency, response for increment, uncertainties of parametric, statistics of time-space indispensable error execution, objective capability, and resistance from aggravation with the previous methods-based PID for buck converters of DC-DC, the suggested ISCA-PID technique's robustness was evaluated. The results obtained later revealed that the suggested approach outperformed its algorithmic predecessors in terms of the DC-DC buck converter's remarkably improved transient responsiveness. © 2025 IEEE.

关键词： Buck converter

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