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E-Health and Bioengineering Conference (EHB)

作者： Iustina-Bianca Bulai Otilia Zvorişteanu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Worldwide, autism affects 1 in 100 children, with diagnoses steadily rising since the 2000s. Romania lacks official statistics on autism prevalence, but global estimates suggest similarity. Children with autism struggle with social interactions and verbal communication, prompting interest in social robots for therapy and education. Tailored robot-assisted sessions offer potential for cognitive development, vocabulary enhancement, social interaction, and behavioral stimulation like concentration and attention. The NAO robot's user-friendly design, technical capabilities, and integrated features make it well-suited for these purposes. This paper presents activities that exemplify the concept of “learning through play,” allowing children to engage in exploration, experimentation, and effective learning in an enjoyable manner.

关键词： Autism Vocabulary Hospitals Social robots Education Biomedical engineering

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COMPARING WSN PERFORMANCE: TRADITIONAL VS. SDN APPROACH

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2024年第4期86卷 81-94页

作者： Hamad, Diyar Jamal Yalda, Khirota Gorgees Okumus, Ibrahim Taner Tapus, Nicolae Faculty of Automatic Control and Computer Science University of Science and Technology POLITEHNICA Bucharest Soran Technical college Erbil Polytechnic University Erbil Iraq Computer Engineering Kahramanmaras Sutcu Imam University Kahramanmaras Turkey Dept. of Computer Science University of Science and Technology POLITEHNICA Bucharest Romania

The proliferation of Wireless Sensor Networks (WSN) in various applications has necessitated the exploration of network architectures that can ensure efficient, scalable, and reliable communication. This study presents a comparative performance evaluation of traditional networking paradigms and Software-Defined Networking (SDN)-based architectures within WSN. Utilizing the Floodlight SDN controller and Mininet-WiFi emulator, we conducted a series of experiments across three different network topologies, varying the number of hosts and access points. The performance metrics focused on are average latency, packet loss percentage, and throughput. The results demonstrate a considerable improvement in all measured parameters under the SDN-based environment compared to the traditional setup. Specifically, SDN environments consistently showcased lower latency, minimal packet loss, and higher throughput, with the most notable difference observed in smaller network configurations. The findings suggest that SDN, with its centralized control plane, can significantly enhance the performance of WSNs, particularly in scenarios demanding rapid scalability and dynamic traffic management. This study underscores the potential of SDN architectures in optimizing WSN operations and lays the groundwork for future research in this domain. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Floodlighting

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Automated Assessment of Medical Rehabilitation of Gait by Means of Video Processing in Cloud Environment

Automated Assessment of Medical Rehabilitation of Gait by Me...

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E-Health and Bioengineering Conference (EHB)

作者： Elena-Claudia Maftei Otilia Zvorişteanu Hariton-Nicolae Costin Silviu Bejinariu Florin Rotaru Vasile Manta Ramona Luca Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Institute of Computer Science Romanian Academy Iaşi Branch Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Human gait analysis provides qualitative and quantitative information concerning different characteristics of walking of a certain person. Cloud computing proves to be a modern and valuable technology when dealing with data scalability, security and efficiency of processing and storage. Also, this paradigm has some key-benefits like real-time data sharing, fast computation as well as collaborative research. The applications gamut which uses cloud computing is getting bigger and bigger, and healthcare sector is an important domain in this respect. Our approach proposed a cloud-based service designed for the automated assessment of medical rehabilitation of human gait by using video processing. We have chosen this processing technology because it is marker-less, allows fast computation and offers a very good precision of the gait analysis. Cloud computing approach proved to be encouraging and underscores remarkable advantages in comparison with traditional on-site video processing. In this way the patient, after a short training session, can himself/herself make tests and assessments of his/her mobility status, avoiding many consultations of medical or kineto-therapeutic staff.

关键词： Legged locomotion Training Cloud computing Scalability Medical services Gain measurement People with disabilities Real-time systems Security Personnel

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Pose-free visual servoing from 3D measurements

Pose-free visual servoing from 3D measurements

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European control Conference (ECC)

作者： Adrian Burlacu Radu L. Rosca Andrei I. Iancu Enric Cervera Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Romania Dept. of Computer Science and Engineering Jaume I University Spain

In this paper, a novel approach to visual servo control robotic systems is proposed. It is focused on developing a solution using 3D point features without recovering the rigid object’s pose. Pose-free motion is achieved using motion parameterization techniques based on dual numbers and dual vectors. Considering an imposed velocity field over the motion of the 3D point features ensemble, this work proposes a close-form solution to a visual servoing problem. The solution provides stable motion control while preserving the image features in the field of view. However, when some point features leave the field of view, their contribution to the control law is dropped without losing stability. The proposed solution is easy to tune and implement. Various scenarios are used in simulations and real experiments to show how the proposed solution overcomes classic servoing problems.

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Towards a Holistic controller: Reinforcement Learning for Data Center control 21

Towards a Holistic Controller: Reinforcement Learning for Da...

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12th ACM International Conference on Future Energy Systems, e-Energy 2021

作者： Heimerson, Albin Brännvall, Rickard Sjölund, Johannes Eker, Johan Gustafsson, Jonas Lund University Dept. of Automatic Control Sweden Rise Research Institutes of Sweden Dept. of Computer Science Sweden Ericsson Research Lund University Sweden

ISBN: (纸本)9781450383332

The increased use of cloud and other large scale datacenter IT services and the associated power usage has put the spotlight on more energy-efficient datacenter management. In this paper, a simple model was developed to represent the heat rejection system and energy usage in a small DC setup. The model was then controlled by a reinforcement learning agent that handles both the load balancing of the IT workload, as well as cooling system setpoints. The main contribution is the holistic approach to datacenter control where both facility metrics, IT hardware metric and cloud service logs are used as inputs. The application of reinforcement learning in the proposed holistic setup is feasible and achieves results that outperform standard algorithms. The paper presents both the simplified DC model and the reinforcement learning agent in detail and discusses how this work can be extended towards a richer datacenter model. © 2021 ACM.

关键词： Reinforcement learning

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Trust region policy optimization with optimal transport discrepancies: duality and algorithm for continuous actions 22

Trust region policy optimization with optimal transport disc...

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Proceedings of the 36th International Conference on Neural Information Processing Systems

作者： Antonio Terpin Nicolas Lanzetti Batuhan Yardim Florian Dörfler Giorgia Ramponi Automatic Control Laboratory ETH Zürich Dept. of Computer Science ETH Zürich Dept. of Computer Science ETH AI Center

ISBN: (纸本)9781713871088

Policy Optimization (PO) algorithms have been proven particularly suited to handle the high-dimensionality of real-world continuous control tasks. In this context, Trust Region Policy Optimization methods represent a popular approach to stabilize the policy updates. These usually rely on the Kullback-Leibler (KL) divergence to limit the change in the policy. The Wasserstein distance represents a natural alternative, in place of the KL divergence, to define trust regions or to regularize the objective function. However, state-of-the-art works either resort to its approximations or do not provide an algorithm for continuous state-action spaces, reducing the applicability of the method. In this paper, we explore optimal transport discrepancies (which include the Wasserstein distance) to define trust regions, and we propose a novel algorithm - Optimal Transport Trust Region Policy Optimization (OT-TRPO) - for continuous state-action spaces. We circumvent the infinite-dimensional optimization problem for PO by providing a one-dimensional dual reformulation for which strong duality holds. We then analytically derive the optimal policy update given the solution of the dual problem. This way, we bypass the computation of optimal transport costs and of optimal transport maps, which we implicitly characterize by solving the dual formulation. Finally, we provide an experimental evaluation of our approach across various control tasks. Our results show that optimal transport discrepancies can offer an advantage over state-of-the-art approaches.

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Analysis and Detection of Melanoma through Collective Intelligence with AI

Analysis and Detection of Melanoma through Collective Intell...

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Enrique Fernández-Morales Carlos L. Sanchez-Bocanegra Rafael Pastor-Vargas José-Juan Pereyra-Rodriguez Juan M. Haut José Alberto Benítez-Andrades Communications and Control Systems Dpt. Computer Science Faculty UNED Madrid Spain Communications and Control Systems Dpt. Computer Science Faculty UNED Malaga Spain Virgen Del Rocio Hospital Universitario Seville Spain School of Tecnology University of Extremadura Cáceres Spain Dept. of Electric Systems and Automatics Engineering Universidad de León León Spain

ISBN: (数字)9798350384727

ISBN: (纸本)9798350384734

Cancer is a widespread global health problem, claiming millions of lives each year, and skin cancer represents a significant threat as it is one of the most common types. Early tumor detection via medical imaging is critical for effective treatment. Leveraging artificial intelligence, particularly novel models like Transformers, presents promising avenues for improved diagnosis. This paper explores the efficacy of a Collective Intelligence approach using AI in classifying cancerous and non-cancerous tumors, aiming to reduce classification errors and support clinical decision-making. We created five different configurations using various datasets to compare the results. The results show solid performance for the CI in the evaluated tasks, reaching up to 75.89% accuracy. The lack of images in certain classes significantly contributes to overfitting. It is suggested to explore data expansion strategies and improve consistency in image capture for future work.

关键词： Accuracy Melanoma Collective intelligence Image capture Transformers Solids Artificial intelligence

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Trust Region Policy Optimization with Optimal Transport Discrepancies: Duality and Algorithm for Continuous Actions

arXiv

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arXiv 2022年

作者： Terpin, Antonio Lanzetti, Nicolas Yardim, Batuhan Dörfler, Florian Ramponi, Giorgia Automatic Control Laboratory ETH Zürich Switzerland Dept. of Computer Science ETH Zürich Switzerland Dept. of Computer Science ETH AI Center Switzerland

Policy Optimization (PO) algorithms have been proven particularly suited to handle the high-dimensionality of real-world continuous control tasks. In this context, Trust Region Policy Optimization methods represent a popular approach to stabilize the policy updates. These usually rely on the Kullback-Leibler (KL) divergence to limit the change in the policy. The Wasserstein distance represents a natural alternative, in place of the KL divergence, to define trust regions or to regularize the objective function. However, state-of-the-art works either resort to its approximations or do not provide an algorithm for continuous state-action spaces, reducing the applicability of the method. In this paper, we explore optimal transport discrepancies (which include the Wasserstein distance) to define trust regions, and we propose a novel algorithm – Optimal Transport Trust Region Policy Optimization (OT-TRPO) – for continuous state-action spaces. We circumvent the infinite-dimensional optimization problem for PO by providing a one-dimensional dual reformulation for which strong duality holds. We then analytically derive the optimal policy update given the solution of the dual problem. This way, we bypass the computation of optimal transport costs and of optimal transport maps, which we implicitly characterize by solving the dual formulation. Finally, we provide an experimental evaluation of our approach across various control tasks. Our results show that optimal transport discrepancies can offer an advantage over state-of-the-art approaches. Copyright © 2022, The Authors. All rights reserved.

关键词： Approximation algorithms

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FaitH: Trusted Chain Network for Non-Cooperative D2D Communication Underlying HetNet 13

FaitH: Trusted Chain Network for Non-Cooperative D2D Communi...

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13th International Conference on Electronics, computers and Artificial Intelligence, ECAI 2021

作者： Gupta, Rajesh Rathod, Tejal Reebadiya, Dakshita Tanwar, Sudeep Bhattacharya, Pronaya Pricop, Emil Nirma University Dept. of Computer Science and Engg. Ahmedabad India Petroleum-Gas University of Ploiesti Automatic Control Comp. and Elect. Dept Ploiesti Romania

ISBN: (纸本)9781665425346

The requirement of Device-to-device (D2D) communication is increasing day-by-day for rapid data transmission by bypassing the base station. Communication can be established either through cooperative devices or non-cooperative devices. Cooperative devices relay the information to the weak user, but the non-cooperative behavior of some intermediate nodes leads to malicious activities like fraud, misguide, and data-threat. In non-cooperative communication, the source node directly transmits data to the destination node (with a direct link) to eliminate the intermediate nodes for higher trust. But, such communications are vulnerable to various security and privacy threats such as spoofing, data modification, etc. due to the long-distance coverage of signal from source to destination. To overcome these security issues, this paper proposes a blockchain-based trusted network for non-cooperative D2D communication in a heterogeneous network, FaitH. Here, the devices are communicating via a secured blockchain network, where all the involved peer devices validate each transmission of data. Blockchain records each activity performed by any D2D node in communication. It helps to detect the malicious behavior of any D2D user. Each device is connected to a smart contract having some predefined rules. FaitH ensures secure, trusted, and reliable communication over traditional systems. © 2021 IEEE.

关键词： Smart contract

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Game-based Resource Allocation for Secure UAV Communication in Wireless Networks

Game-based Resource Allocation for Secure UAV Communication ...

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International Conference on Electronics, computers and Artificial Intelligence (ECAI)

作者： Riya Kakkar Rajesh Gupta Smita Agrawal Sudeep Tanwar Emil Pricop Dept. of Computer Science and Engg. Inst. of Tech. Nirma University Ahmedabad India Automatic Control Comp. & Elect. Dept. Petroleum-Gas University of Ploiesti Ploieşti Romania

Unmanned aerial vehicles (UAVs) are one of the applications of device-to-device (D2D) technology, where two UAVs can communicate with or without the existence of a base station. It facilitates high content delivery, low latency, low cost, and high data rate communication in wireless networks. Despite the aforementioned benefits, an eavesdropping attack is one of the critical challenges that cause interference in UAV communication in the presence of an eavesdropper. To mitigate the aforementioned challenges, we proposed a secure resource allocation for UAV communication in wireless networks. The applied single carrier orthogonal frequency division multiple access (SC-OFDMA) technique utilize the orthogonality feature to provide secure UAV communication in wireless networks. Moreover, a zero-sum game approach is considered to enable the secure and optimal resource allocation for UAV communication. The main aim of the zero-sum game theory is to maximize the communication channel's data rate and secrecy capacity to achieve a secure and optimal UAV communication scenario in wireless networks. Finally, the performance and simulation of the proposed approach are evaluated against the existing random approach in terms of various metrics such as data rate and secrecy capacity of the communication channel.

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