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检索条件"机构=Department of System and Computer Architecture"

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Implementation of Safety-Related Intrusion Detection for an Industrial Robotic Arm

Implementation of Safety-Related Intrusion Detection for an ...

引用

2025 International Conference on Control, Automation, and Instrumentation, IC2AI 2025

作者： Haydar, Georgio Abou Telawi, Samer Borcsok, Josef Architecture and System Programming University of Kassel Department of Computer Kassel Germany

ISBN: (纸本)9798331529604

Ensuring the safety of human workers collaborating with industrial robots is paramount. This research work presents a novel approach by developing a safety-related intruder detection system for the operational zones of industrial robots, following the IEC 61508 standard and adopting the related redundant architecture. The hardware integrates light curtains and radar sensors in a dual-layer configuration, while the software utilizes a safety system-on-chip to implement real-time diagnostics and fault tolerance. Protecting employees and ensuring a smooth and safe work environment are significant concerns for all companies. As a result, numerous standards and regulations have been established to provide safe collaboration between humans and machines. However, despite these measures, accidents continue to occur, resulting in varying degrees of injuries. The proposed system is depicted through a comprehensive schematic, emphasizing the integration of safety measures within the robotic environment. The detailed prototype demonstrates practical application, show-casing the system's ability to detect intrusions, initiate emergency responses, and transition to fail-safe states during component failures. This research work advances safety protocols in human-robot collaboration within industrial settings, fostering a safe working environment through a well-defined safety framework. © 2025 IEEE.

关键词： Industrial robots

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Model Based Development Methodology in Compliance with ISO 26262 for Safe Automotive ECU

Model Based Development Methodology in Compliance with ISO 2...

引用

2023 IEEE International Conference on Electrical, computer and Energy Technologies, ICECET 2023

作者： Hafiz, Muhammad Ikram University of Kassel Department of Computer Architecture and System Programming Kassel Germany

ISBN: (纸本)9798350327816

This work presents a practical approach of designing a functionally safe ECU for automotive application by implementing the Model Based Development (MBD) methodology. Functional safety (FuSa) in automotive can be achieved by strictly following the processes of electrical and electronic systems development as given in the ISO 26262. The scope of FuSa encompasses the risks emerging from systematic failures and random hardware failures. One approach to mitigate these failures is the Model Based Development (MBD) on which the ISO 26262 provides guidance. This approach enables to model an ECU and accelerates an IP creation by automatic RTL code generation for rapid prototyping on an FPGA level. In this work the MBD is implemented in accordance to the ISO 26262 to design and test a hardware model of an embedded ECU. The embedded Design under Test (DUT) is simulated and its output verified in Matlab/Simulink. Upon successful results, the RTL codes of the DUT are generated for a target FPGA. The RTL codes are simulated and the functionality of the DUT is verified at the FPGA level. © 2023 IEEE.

关键词： FPGA Functional Safety HDL code generation ISO 26262 Model Based Development systematic failures

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Enhancing EMI Suppressor Designs through Multilayered Magnetic Cores in Toroidal Inductors 4

Enhancing EMI Suppressor Designs through Multilayered Magnet...

引用

4th IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2024

作者： Ghaleb Al-Duhni, Ghaleb Saleh Pial, Mohammad Mohtasim Hamid Khasgiwala, Mudit Volakis, John L. Pulugurtha, Markondeyaraj Florida International University Electrical and Computer Department Miami United States RF / Analog System Architecture and AI system Solutions Applied Materials Santa Clara United States Florida International University Biomedical department Miami United States

ISBN: (纸本)9798350395914

EMI suppressors are passive components typically used to filter high-frequency noise due to their high resistance value. That is usually employed using ferrite material with a higher magnetic loss. This paper introduces a novel approach to fabricating such a device without relying on bulky ferrite materials as the magnetic core. The proposed approach relies on using multilayered materials with high electrical conductivity as the magnetic core. We propose three toroid inductor designs using two customized magnetic materials (A and B) with higher electrical conductivity properties. The first toroid design is based on a single-layer magnetic core, the second on a double-layer magnetic core, and the last on an eight-layer magnetic core. The performance of the single-layered toroid inductor is improved by employing a multi-layered core technique in terms of AC resistance across broadband bandwidth. Notably, the multilayered toroid core exhibits higher resistance across the 5-1175 MHz range as compared to the single-layer design. In addition, Depositing conductive layers like copper onto the multilayered toroids leads to inductors that have multiple resonances. Thus, such an approach allows to control and adjust the operational frequency as needed. © 2024 IEEE.

关键词： Magnetic cores

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Development of a Safe Charging Infrastructure system: Requirements, Design, Verification and Validation 10th

Development of a Safe Charging Infrastructure System: Requ...

引用

10th International Conference on Smart Cities and Green ICT systems, SMARTGREENS 2021, and 7th International Conference on Vehicle Technology and Intelligent Transport systems, VEHITS 2021

作者： Kivelä, Tommi Sperling, Marvin Abdelawwad, Mohamed Drabesch, Malte Schwarz, Michael Börcsök, Josef Furmans, Kai Karlsruhe Germany Department of Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (纸本)9783031170973

With the ongoing shift from fossil fuels towards electric mobility, there’s an increasing need for charging infrastructure for electric vehicles, both private and public. With this increasing role of charging infrastructure in day-to-day life, safety and security should be guaranteed for these systems. In this work we report on the development of an integrated electronic charging infrastructure system. The development was based on both current functional safety and charging infrastructure standards. The whole development process is presented, including requirements analysis, overall system design, safety hardware and software design, as well as the verification & validation of the safety system against the requirements set in the beginning. The presented work can be used as a basis and reference for the functional safety aspects when developing next generation charging infrastructure systems. © 2022, Springer Nature Switzerland AG.

关键词： systems analysis

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Implementation of Safety-Related Intrusion Detection for an Industrial Robotic Arm

Implementation of Safety-Related Intrusion Detection for an ...

引用

Control, Automation, and Instrumentation (IC2AI), International Conference on

作者： Georgio Abou Haydar Samer Telawi Josef Börcsök Department of Computer Architecture and System Programming University of Kassel Kassel Germany

ISBN: (数字)9798331529604

ISBN: (纸本)9798331529611

关键词： Service robots Intrusion detection Prototypes Human-robot interaction Industrial robots Manipulators Safety system-on-chip IEC Standards Standards

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Design of a Novel Safe Approach to Monitor Drivers While Operating Their Cars 7

Design of a Novel Safe Approach to Monitor Drivers While Ope...

引用

7th International Conference on Advances in Biomedical Engineering, ICABME 2023

作者： Elhawawsha, Aseel Zeine, Carla Zeid Daou, Roy Abi Kalinowski, Dominik Khattar, Joseph Telawi, Samer Boercsoek, Josef University of Kassel Department of Computer Architecture and System Programming Kassel Germany Université la Sagesse Saculty of Engineering Mechatronics Eng. Department Beirut Lebanon

ISBN: (纸本)9798350325850

Road accidents have been known to be one of the leading death causes around the world for a long time. Thus, cars and all kinds of road vehicles form a huge source of danger, and they relate to multiple high risks. There are many factors that can contribute to road traffic accidents such as the health condition of the driver if a medical emergency event happened while driving, drowsiness, or mind-wandering. The proposed system can monitor the behavior of the driver while driving as well as his/her health status. Moreover, it analyzes the monitored data, alerts the driver in a timely manner, and assists him/her in adjusting the driving behavior. Different dangerous and risky situations which can be faced during driving can be captured and avoided by using such a system which leads at the end to increase road traffic safety and reduce vehicle collisions. Notifications are developed in cases of drowsiness, loss of focus, or other concerns that may emerge while driving. However, when the driver's ability to operate the vehicle safely is hampered by a health concern, the implemented system is only able at this stage to alarm the driver itself and the surrounding cars as a first level of alarms. © 2023 IEEE.

关键词： Roads and streets

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A Comparative Study on Deep Learning Models for Stock Price Prediction 5

A Comparative Study on Deep Learning Models for Stock Price ...

引用

5th Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2024

作者： He, Zhexin Zhang, Huan Por, Lip Yee Chongqing College of Architecture and Technology Chongqing401331 China Chongqing Academy of Science and Technology Chongqing401123 China Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur50603 Malaysia

ISBN: (纸本)9781643685243

With the advancement of deep learning technology, researchers have begun employing deep neural network models such as LSTM, MLP, CNN, and GRU to tackle nonlinear prediction problems in stock markets. This study harnesses these deep learning models, including LSTM, MLP, CNN, and GRU, to investigate the nonlinear forecasting of stock market price indices. The experiment selects globally representative stock indices and, through analyzing short-term, mid-term, and long-term data, discovers that the GRU model demonstrates exceptional performance in both prediction accuracy and generalization capabilities. To further enhance precision, the research constructs a filtering ensemble decision-making system based on multiple GRU models. This strategy reduces the error by at least 0.3% in medium to long-term predictions, significantly outperforming a single standalone GRU model. Consequently, the GRU-filtered ensemble decision model has been empirically proven as an effective tool for predicting stock indices, not only broadening the methods available for stock market prediction but also deepening the understanding and application of the generalization abilities of deep learning models within financial markets. © 2024 The Authors.

关键词： Long short-term memory

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Characterization Model for Irregular MPI Applications Based on PAS2P 43

Characterization Model for Irregular MPI Applications Based ...

引用

43rd International Conference of the Chilean computer Science Society, SCCC 2024

作者： Tirado, Felipe Wong, Alvaro Rexachs, Dolores Luque, Emilio Universidad Católica Del Maule Departamento de Computación e Industrias Talca Chile Universidad Autónoma de Barcelona Computer Architecture and Operating System Department Barcelona Spain

ISBN: (纸本)9798331527891

Performance modeling of parallel applications is essential for optimizing resource usage in high-performance computing (HPC) systems. However, some scientific applications exhibit irregular performance behaviors, which complicates cre-ating accurate characteristic models. This irregularity is mainly due to these applications' nondeterministic computational and communication patterns. Tools such as PAS2P (Parallel Application Signatures for Performance Prediction) are used to extract detailed information about parallel applications. PAS2P is based on the repetitive behavior of the application to analyze and predict the application's performance, using the same resources that the parallel application uses for its execution. This paper presents a characterization model based on the PAS2P methodology for irregular applications that groups the repeatability patterns of all the processes running the application into a single characteristic model. To achieve this, we consolidate the different characterizations performed by each process independently, using metrics such as the number of instructions, the execution time of relevant sections, and the topological characteristics of the application. By grouping these repeatability patterns of all processes, we can obtain a concise and accurate representation of the behavior of irregular applications, thus improving predictability and performance optimization in HPC systems. © 2024 IEEE.

关键词： Application performance analysis irregular parallel applications MPI parallel application parallel application modeling

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Smart Material Selection: Leveraging Machine Learning for Sustainable and Cost-Effective Building Design 2

Smart Material Selection: Leveraging Machine Learning for Su...

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2nd Jordanian International Biomedical Engineering Conference, JIBEC 2024

作者： Hashim, Wassan Adnan Khoshaba, Lina Sami Kareem, Shahab Wahhab Khoshaba, Farah Sami Al-Qalam University College Medical Device Engineering Department Kirkuk Iraq Lebanese French University College of Engineering and Computer Science Architecture Engineering Department Erbil Iraq Polytechnic University Technical Engineering College Information System Engineering Department Erbil Iraq

ISBN: (纸本)9798331539542

In modern-day architecture, the choice of building material plays an important role in sustainability, cost-value engineering, and design integrity. Moreover, the traditional methods for selecting materials tended to make use of manual approaches, which at times led to drawbacks by not focusing on the basics of integration and proper data management. The paper is a very interesting approach of how a complex material selection process can be optimized with simple machine learning algorithms. In that sense, the current research developed a framework from environmental sustainability to economic cost, durability, and aesthetic appeal, with an intention for its use in guiding the design final decision process. The proposed machine learning model suggests ideal prediction for material combination from different material datasets concerning the properties and performance metrics applicable to architecture. The research showed that the approach had a hand in getting thoughtful, analytic-based decisions while assuring, at the same time, that an architect would be able to satisfy the project goals and budget constraints with environmentally safe execution. It elaborates on the cases, or rather case studies, that have applied the model and gives illustrations of great improvements not only in efficiency in design but also in the sustainability of the project coupled with better strategies for saving costs. The current research is opening an entirely new field of innovation in architecture that emphasizes the role of technology for the future form of building practice. © 2024 IEEE.

关键词： Budget control

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Model Based Development Methodology in Compliance with ISO 26262 for Safe Automotive ECU

Model Based Development Methodology in Compliance with ISO 2...

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Electrical, computer and Energy Technologies (ICECET), International Conference on

作者： Muhammad Ikram Hafiz Department of Computer Architecture and System Programming University of Kassel Kassel Germany

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