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Balancing Energy Efficiency and Portability: Assessing Domain-Specific Languages in Edge Platforms

Balancing Energy Efficiency and Portability: Assessing Domai...

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international conference on Distributed computing in Sensor systems (DCOSS)

作者： Youssef Faqir-Rhazoui Luis Costero Carlos García Computer Science Faculty Complutense University of Madrid Spain

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

Edge computing stands as a crucial component of the IoT revolution. IoT benefits significantly from reduced latency, enhancing real-time applications, and time-sensitive processes. However, since edge platforms must be energy-efficient while maintaining high performance in real-time environments, exploiting accelerators becomes pivotal to reduce energy consumption while increasing performance. CUDA or HIP languages are widely used to program GPUs; however, they are limited to specific vendor platforms. In contrast, solutions such as SYCL or Kokkos could benefit from their ability to run across parallel *** paper explores the trade-offs of CUDA, SYCL, and Kokkos in three Edge platforms: Jetson AGX Orin, Jetson Orin Nano, and UP Squared Pro 7000 (Intel). the work conducts an analysis of the power modes of each platform and compares CUDA, SYCL, and Kokkos on those *** experimental results revealed that, on average, there is an increased level of energy consumption compared to native solutions. Specifically, Kokkos demonstrated a 25% higher demand, whereas SYCL exhibited an average increase of 11%. these figures underscore the trade-off that programmers face in pursuit of achieving code portability when most performant solutions are non-crucial.

关键词： Energy consumption Graphics processing units real-time systems Energy efficiency Internet of things Distributed computing Hip

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Bimodal Emotion Recognition Based on Vocal and Facial Features 27

Bimodal Emotion Recognition Based on Vocal and Facial Featur...

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27th international conference on Knowledge Based and Intelligent Information and Engineering Sytems, KES 2023

作者： Wozniak, Mateusz Sakowicz, Michal Ledwosinski, Kacper Rzepkowski, Jakub Czapla, Pawel Zaporowski, Szymon Multimedia Systems Department Gdansk University of Technology Narutowicza 11/12 Gdansk80-233 Poland Audio Acoustic Laboratory Gdansk University of Technology Narutowicza 11/12 Gdansk80-233 Poland

Emotion recognition is a crucial aspect of human communication, with applications in fields such as psychology, education, and healthcare. Identifying emotions accurately is challenging, as people use a variety of signals to express and perceive emotions. In this study, we address the problem of multimodal emotion recognition using both audio and video signals, to develop a robust and reliable system that can recognize emotions even when one modality is absent. To achieve this goal, we propose a novel architecture based on well-designed feature extractors for each modality and use model-level fusion based on a TFusion block to combine the information from both sources. To be more efficient in real-world scenarios, we trained our model on a compound dataset consisting of RAVDESS, RML, and eNTERFACE'05. It is then evaluated and compared to the state-of-the-art models. We find that our approach performs close to the modern solutions and can recognize emotions accurately when one of the modalities is missing. Additionally, we have developed a real-time emotion recognition application as a part of this work. © 2023 the Authors. Published by Elsevier B.V. this is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0)

关键词： Affective computing Deep Learning Emotion recognition TFusion

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Can embedded real-time Linux System Effectively Support Multipath Transmission? An Experimental Study

Can Embedded Real-Time Linux System Effectively Support Mult...

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IEEE international Workshop on Factory Communication systems (WFCS)

作者： Xiaojing Fan Tao Zheng Shangpeng Sun Mikael Gidlund Johan Åkerberg School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Department of Biorcsourcc Engineering Macdonald Campus McGill University QC Canada Department of Information Systems and Technology Mid Sweden University Sundsvall Sweden Division of Networked and Embedded Systems Malardalen University Vasteras Sweden

the rise of technologies such as 6G networks, edge computing, and the Industrial Internet has led to a dramatic increase in the amount of data that needs to be transmitted over heterogeneous integrated networks. the resources of embedded devices limit the ability of the Industrial Internet to transmit data. While the multipath transmission mechanism can mitigate data transmission issues of low reliability and low real-time performance from the network-level perspective. As the complexity of industry applications increases, however, the phenomenon that the high-quality data transmission is subject to the influence of the underlying layer is becoming increasingly apparent. the paper aims to explores the possibility of multipath transmission protocol running on a real-time kernel from the perspective of the operating system, as there is a lack of research and reports in this area. Based on RT-Preempt, a real-time system RT-Linux suitable for the “NXP ***6Q” ARM integrated board has been proposed, which replaces the native Linux kernel to optimize and enhance its real-time performance. As described in the experiment part, the original standard Linux system OR-Linux and the new RT-Linux are tested with single-threaded and multi-threaded load experiments, respectively. the results of the analysis show that this paper provides a way of validating the trial data and ensuring its accuracy using the lognormal distribution model, which is a statistical distribution used to model variables that are positive and skewed to the right. the RT-Linux scheme has better real-time performance and is more stable than the OR-Linux scheme after real-time processing, showing the viability of the scheme.

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Agile systems Engineering in Complex Scenarios 11

Agile Systems Engineering in Complex Scenarios

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11th IEEE international conference on Intelligent Data Acquisition and Advanced computing systems - Technology and applications (IDAACS)

作者： Wolff, Carsten Tendyra, Philipp Wiecher, Carsten Fachhsch Dortmund IDiAL Otto Hahn Str 23 D-44227 Dortmund Germany

ISBN: (纸本)9781665426053

the successful development of complex systems of systems (SoS) is highly dependent on quality of the requirements engineering (RE). the goal is to get "good" requirements in the beginning and to keep them stable until the delivery of the final product. In reality, this is wishful thinking. In complex real-world scenarios the requirements are never fully understood and never stable - they evolve during the development process. this is a severe issue for complex and highly elaborated systems engineering processes. Usually, the projects get out of control due to the change requests or do not deliver a result fitting the current need of the customer. Elaborated innovation management, marketing and customer relation processes are used to understand the need of the customer (market pull) and the new technical possibilities (technology push). the design and implementation of such innovation management processes is complex in itself and well researched. this paper extends the state-of-the-art with a focus on the interfacing between the systems engineering process (for the product development) and the innovation management process (for the ideation and innovation creation). We propose a parallel, interlinked execution of both processes instead of the over-the-fence practice where an innovation idea is handed over to product development at a certain point of time. A continuous interaction of both processes with agile management methods reduces the risk of getting the wrong product. Instead of using wrong or outdated information in the product development due to the missing updates from innovation management, a continuous linking and exchange mechanism with the systems engineering project is proposed. Interlinking these two complex processes is addressed with scenario-based methods and a process similar to BizDevOps. the full paper will evaluate the concepts based on a complex eMobility case study.

关键词： systems of systems Agile Management Innovation Management

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Integrating Retrospective Framework in Multi-Robot Collaboration

Integrating Retrospective Framework in Multi-Robot Collabora...

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international conference on Autonomous Robots and Agents, ICARA

作者： Jiazhao Liang Hao Huang Yu Hao Geeta Chandra Raju Bethala Congcong Wen Yi Fang NYUAD Center for Artificial Intelligence and Robotics (CAIR) Abu Dhabi UAE Embodied AI and Robotics (AIR) Lab NYU Abu Dhabi UAE New York University Abu Dhabi UAE New York University US

ISBN: (数字)9798331509231

ISBN: (纸本)9798331509248

Recent advancements in Large Language Models (LLMs) have demonstrated substantial capabilities in enhancing communication and coordination in multi-robot systems. However, existing methods often struggle to achieve efficient collaboration and decision-making in dynamic and uncertain environments, which are common in real-world multi-robot scenarios. To address these challenges, we propose a novel retrospective actor-critic framework for multi-robot collaboration. this framework integrates two key components: (1) an actor that performs real-time decision-making based on observations and task directives, and (2) a critic that retrospectively evaluates the outcomes to provide feedback for continuous refinement, such that the proposed framework can adapt effectively to dynamic conditions. Extensive experiments conducted in simulated environments validate the effectiveness of our approach, demonstrating significant improvements in task performance and adaptability. this work offers a robust solution to persistent challenges in robotic collaboration.

关键词： Robot kinematics Large language models Decision making Collaboration Robustness real-time systems Planning Multi-robot systems Resource management Tuning

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Evolution of Models and Methods in the Field of Resilient computing 11

Evolution of Models and Methods in the Field of Resilient Co...

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11th IEEE international conference on Intelligent Data Acquisition and Advanced computing systems - Technology and applications (IDAACS)

作者： Drozd, Oleksandr Ustynowicz, Adam Rucinski, Andrzej Sachenko, Anatoliy Drozd, Julia Odessa Polytech State Univ Ave Shevchenko 1 UA-65044 Odessa Ukraine eCollaborat Ventures Inc Mt Vernon NH 03057 USA Univ New Hampshire Durham NH 03824 USA West Ukrainian Natl Univ 11 Lvivska Str UA-46009 Ternopol Ukraine

ISBN: (纸本)9781665426053

this paper examines the development of computer models and methods based on a comparative analysis conducted by S. Lem in relation to two evolutions: biological and technological in his scientific work "Summa Technologiae". the conclusions made by the author were decades ahead of time and received many confirmations in the development of the computer world. the analysis of the integration process of the computer world into the natural one continues the comparison of evolutions and shows examples of resilient, i.e., elastic development of computer models and methods in modern conditions. this development is gaining the greatest importance in containing the risks of accidents in critical infrastructures that solve the problems of energy and food security of mankind. An example of such a development is considered to improve checkability, which is important for the safety of critical systems built on FPGAs.

关键词： computer models and methods biological and technological evolutions resilient development safety-related system checkability

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Shallow vs. Deep Learning: Prioritizing Efficiency in Next Generation Networks

Shallow vs. Deep Learning: Prioritizing Efficiency in Next G...

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international conference on Future Internet of things and Cloud (FiCloud)

作者： Rafael Teixeira Leonardo Almeida Pedro Rodrigues Mário Antunes Diogo Gomes Rui L. Aguiar Instituto de Telecomunicações Universidade de Aveiro DETI Universidade de Aveiro

ISBN: (数字)9798331527198

ISBN: (纸本)9798331527204

With the exponential growth of mobile network traffic and diverse application demands, traditional network management methods struggle to meet the stringent requirements of 5th Generation (5G) and Beyond-5G (B5G) networks. Artificial Intelligence (AI), particularly Deep Learning (DL), has emerged as a promising solution. However, large and complex DL models can be computationally expensive for real-time applications. this paper investigates the potential of shallow Machine Learning (ML) models for 5G/B5G tasks. We compare the performance and training/inference time of shallow ML models with state-of-the-art DL models in two key tasks: network slicing attribution and Intrusion Detection systems (IDS). the results demonstrate that shallow models achieve comparable performance with significantly faster training and prediction, leading to an acceleration of over 90% in most cases.

关键词： Training Deep learning Computational modeling Network slicing Intrusion detection Telecommunication traffic Predictive models real-time systems Internet of things Next generation networking

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Object Recognition based on Deep Learning Algorithms using embedded IoT with Interactive Interface

Object Recognition based on Deep Learning Algorithms using E...

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international conference on ent computing and Control systems (ICICCS)

作者： Swapna Borde Chandan Patil Chinmay Sonawane Mankrit Singh Vidyavardhini’s College of Engineering and Technology Vasai India B.E. Computer Engineering Vidyavardhini’s College of Engineering and Technology Vasai India

Object detection is one of the most popular applications of machine learning in the modern era. With the growth of IOT in recent times, dedicated devices offering real-time object detection have seen overwhelming demand and applications in many sectors e.g. security, healthcare, workplace etc. Different algorithms and approaches have been implemented and studied in terms of object detection. To refer to a few the YOLO family, RCNN family, SSD etc. this research study compares the performance of YOLO and Faster RCNN based on a custom dataset containing different objects and items. the IOU of each data point (image) is calculated and compared. YOLO performs better for a small margin. In this research study, a language learning interactive model is demonstrated based on object detection(YOLO), NLP, python, flask and IoT (Raspberry Pi.) the web application is running on is divided into two parts, learning and practice. the learning part has a raspberry pi device which has a camera module that captures real-time footage, recognizes the object and reads out its name in the language the user is learning. the practice has the same setup, with the application asking the user to show a particular object. Points are awarded for correct guesses, making the learning process more interactive and involving.

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IOT Based Case Study: applications and Challenges 5

IOT Based Case Study: Applications and Challenges

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5th international conference on computing Methodologies and Communication, ICCMC 2021

作者： Das, Sonia Pooja, M.R Anusha, K.S Vidya Vardhaka College of Engineering Department of Computer Science and Engineering Mysore India

ISBN: (纸本)9781665403603

Internet of things (IoT) has been emerging day-to-day because of multiple technologies like embedded systems, machine learning, real-time analytics, and commodity sensors. IoT contributes more to smart home applications, it can control with devices that are associated with it. In IoT, the applications are often divided into infrastructure, consumer, industrial, commercial applications. IoT creates more opportunities for direct integrations, in which it brings the physical world into computer-based systems, which makes people life so easier. Nowadays IoT has hundreds of applications, which in turn help people in many ways and reduce more human interactions. © 2021 IEEE.

关键词： Wireless sensor networks

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Design and Implementation of a Hybrid Recommender System Based on Apache Spark

Design and Implementation of a Hybrid Recommender System Bas...

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Information Communication and applications (ICICA), international conference on

作者： Shi Yongjie Stanislav V. Grigorev School of Information Technology and Data Science Irkutsk National Research Technical University Irkutsk Russia

With the rapid development of Internet technology, people are surrounded by a variety of data information, but among this massive data information, only a very small amount of data information is of interest to users., so how to find the useful information in the massive data information and push it to the targeted user is a problem to be studied by the recommendation system. through the analysis of the recommendation system, it is found that the traditional recommendation algorithm has some shortcomings, and the emergence of the hybrid recommendation algorithm effectively alleviates these problems.

关键词： Cluster computing real-time systems Internet Task analysis Recommender systems

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