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International Conference on control Systems and computer science (CSCS)

作者： Alexandru-Marius Bonteanu Cătălin Tudose Ana Magdalena Anghel Department of Computer Science “Politehnica” University of Bucharest Bucharest Romania Learning Management Department Luxoft Romania Bucharest Romania Department of Automatic Control “Politehnica” University of Bucharest Bucharest Romania

Data is information or a collection of information about something. Almost every application nowadays needs to persist data so that they can keep track of their state in case of any trouble that might appear. Databases are the main piece of an application for persisting data and they can be of two types: SQL or NoSQL. SQL (Structured Query Language) is a query language used to create, read, update, or delete (CRUD operations) the information in most relational databases. Data is structured in a set of tables in the relational database model, with rows as entries and columns as specific attributes of the entry. Over the years, new relational database management systems appeared. A comparison between some of the most used relational database management systems tied to a Java application using Hibernate is worth analyzing in the given context. The evaluation is done on timing for each CRUD operation by using Java Microbenchmark Harness, because these are the most used operations, for thousands and hundreds of thousands of entries. Depending on the majority type of operation, switching the database management system might help.

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End-to-End Lip Reading in Romanian with Cross-Lingual Domain Adaptation and Lateral Inhibition

arXiv

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arXiv 2023年

作者： Mănescu, Emilian-Claudiu Smădu, Razvan-Alexandru Avram, Andrei-Marius Cercel, Dumitru-Clementin Pop, Florin Faculty of Mathematics and Computer Science University of Bucharest Romania Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania National Institute for Research and Development in Informatics - ICI Bucharest Romania

Lip reading or visual speech recognition has gained significant attention in recent years, particularly because of hardware development and innovations in computer vision. While considerable progress has been obtained, most models have only been tested on a few large-scale datasets. This work addresses this shortcoming by analyzing several architectures and optimizations on the underrepresented, short-scale Romanian language dataset called Wild LRRo. Most notably, we compare different backend modules, demonstrating the effectiveness of adding ample regularization methods. We obtain state-of-the-art results using our proposed method, namely cross-lingual domain adaptation and unlabeled videos from English and German datasets to help the model learn language-invariant features. Lastly, we assess the performance of adding a layer inspired by the neural inhibition mechanism. © 2023, CC BY.

关键词： Speech recognition

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ELSA: Euler-Lagrange Skeletal Animations - Novel and Fast Motion Model Applicable to VR/AR Devices 21st

ELSA: Euler-Lagrange Skeletal Animations - Novel and Fast Mo...

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21st International Conference on Computational science, ICCS 2021

作者： Wereszczyński, Kamil Michalczuk, Agnieszka Foszner, Pawel Golba, Dominik Cogiel, Michal Staniszewski, Michal Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland KP Labs Gliwice Poland

ISBN: (纸本)9783030779764

Euler Lagrange Skeletal Animation (ELSA) is the novel and fast model for skeletal animation, based on the Euler Lagrange equations of motion and configuration and phase space notion. Single joint’s animation is an integral curve in the vector field generated by those PDEs. Considering the point in the phase space belonging to the animation at current time, by adding the vector pinned to this point and multiplied by the elapsed time, one can designate the new point in the phase space. It defines the state, especially the position (or rotation) of the joint after this time elapses. Starting at time 0 and repeating this procedure N times, there is obtained the approximation, and if the N→ ∞ the integral curve itself. Applying above, to all joint in the skeletal model constitutes ELSA. © 2021, Springer Nature Switzerland AG.

关键词： Animation

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Detection of Early Pregnancy in Ultrasound Images Using YOLOv3 *

Detection of Early Pregnancy in Ultrasound Images Using YOLO...

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Mediterranean Conference on control and Automation (MED)

作者： Oana Mihaela Teodor Monica Mihaela Cirstoiu Loretta Ichim Dan Popescu Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania Carol Davila University of Medicine and Pharmacy Bucharest

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

automatic interpretation of morphological metrics recently gained great interest in medical imaging applications. For ultrasound image analysis various artificial intelligence algorithms emerged with the aim to overcome drawbacks related to measurement variability and image quality. Advanced methods of automatic analysis can meet the need to centralize a large amount of information from these images, to accurately interpret the medical data, and to minimize the rate of human error. In the current paper, we propose a solution designed for automating the detection of early pregnancy from endovaginal ultrasound scans. A YOLOv3 convolutional neural network was configured to detect the gestational sac, the yolk sac, and the embryo given the potential to facilitate ultrasound diagnostic in obstetrics by automating the detection of these early pregnancy elements. The database created for this research included 349 images evaluating incipient pregnancies with gestational age ranging from 40 to 70 days. The results obtained support the use of YOLOv3 for the precise detection of ultrasound elements specific to an incipient pregnancy.

关键词： Pregnancy Image quality Ultrasonic imaging Embryo Databases Ultrasonic variables measurement Current measurement

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Multi-Platform Performance Analysis for CRUD Operations in Relational Databases from Java Programs using Spring Data JPA

Multi-Platform Performance Analysis for CRUD Operations in R...

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International Symposium on Advanced Topics in Electrical Engineering (ATEE)

作者： Alexandru-Marius Bonteanu Cătălin Tudose Ana Magdalena Anghel Department of Computer Science "Politehnica" University of Bucharest Bucharest Romania Learning Management Department Luxoft Romania Bucharest Romania Department of Automatic Control "Politehnica" University of Bucharest Bucharest Romania

Databases are the fundamental component of an application for storing data. SQL (Structured Query Language) is a query language that is used to create, read, update, and remove records in most relational databases (CRUD operations). Because new relational database management systems have arisen, it is useful to compare some of them when linked to a Java application using Spring Data JPA. The time for each CRUD activity is analyzed for thousands and hundreds of thousands of entries. The motivation is to find the most performant combination for an application, considering its size (number of entries).

关键词： Productivity Structured Query Language Java Relational databases Switches Software Timing

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LiDAR-based drone navigation with reinforcement learning

arXiv

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arXiv 2023年

作者： Miera, Pawel Szolc, Hubert Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland

Reinforcement learning is of increasing importance in the field of robot control and simulation plays a key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number of published scientific papers involving this approach. In this work, an autonomous drone control system was prepared to fly forward (according to its coordinates system) and pass the trees encountered in the forest based on the data from a rotating LiDAR sensor. The Proximal Policy Optimization (PPO) algorithm, an example of reinforcement learning (RL), was used to prepare it. A custom simulator in the Python language was developed for this purpose. The Gazebo environment, integrated with the Robot Operating System (ROS), was also used to test the resulting control algorithm. Finally, the prepared solution was implemented in the Nvidia Jetson Nano eGPU and verified in the real tests scenarios. During them, the drone successfully completed the set task and was able to repeatably avoid trees and fly through the forest. © 2023, CC BY.

关键词： Robot Operating System

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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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Assessment of quality of health services in fractal-organized connectionist networks 23

Assessment of quality of health services in fractal-organize...

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23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Zinca, Gabriela Mocanu, Stefan Dragulinescu, Ana-Maria Dobrescu, Radu University Politehnica of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania University Politehnica of Buchares Faculty of Electronics Telecommunications and Information Technology Telecommunications Department Bucharest Romania

ISBN: (纸本)9781665439398

As complexity is increasing there is an essential need to adapt modern systems to provide efficiency despite the current challenges. The main goal of the organizations providing health services is to satisfy the beneficiary's needs in an ethical, equitable and timely manner. The health system is characterized by the variation of services that are offered and challenged by the need to adapt fast while also providing safe, accurate and reliable services. In this context, fractal organized connectionist networks bring characteristics that might optimize the outcomes of complex systems. In this paper healthcare services are viewed as fractal-organized connectionist networks (FOCNs). The proposed architecture is designed with the aim to provide assessment of quality for health service in FOCNs. © 2021 IEEE.

关键词： Health

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Real-Time Object Detection and Robotic Manipulation for Agriculture Using a YOLO-Based Learning Approach 25

Real-Time Object Detection and Robotic Manipulation for Agri...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Zhao, Hongyu Tang, Zezhi Li, Zhenhong Dong, Yi Si, Yuancheng Lu, Mingyang Panoutsos, George Imperial College The Department Of Physics London United Kingdom University Of Sheffield The Department Of Automatic Control And Systems Engineering SheffieldS1 3JD United Kingdom University Of Manchester The Department Of Electrical And Electronic Engineering Manchester United Kingdom University Of Southampton The Department Of Electronics And Computer Science Southampton United Kingdom Fudan University The Department Of Economics Shanghai200433 China AmesIA50011 United States

ISBN: (纸本)9798350340266

The optimization of crop harvesting processes for commonly cultivated crops is of great importance in the aim of agricultural industrialization. Nowadays, the utilization of machine vision has enabled the automated identification of crops, leading to the enhancement of harvesting efficiency, but challenges still exist. This study presents a new framework that combines two separate architectures of Convolutional Neural Networks (CNNs) in order to simultaneously accomplish the tasks of crop detection and harvesting (robotic manipulation) inside a simulated environment. Crop images in the simulated environment are subjected to random rotations, cropping, brightness, and contrast adjustments to create augmented images for dataset generation. The You Only Look Once(YOLO) algorithmic framework is employed with traditional Rectangular Bounding Boxes (R-Bbox) for crop localization. The proposed method subsequently utilises the acquired image data via a visual geometry group model in order to reveal the grasping positions for the robotic manipulation. © 2024 IEEE.

关键词： Crops

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Methods and tools for automatic or semi-automatic recognition of selected emotions using machine learning algorithms

Methods and tools for automatic or semi-automatic recognitio...

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Progress in Applied Electrical Engineering (PAEE)

作者： Piotr Schneider Dariusz Mikołajewski Anna Bryniarska Magdalena Igras-Cybulska Artur Cybulski Walery Marcinowicz Maciej Janiszewski Aleksandra Kawala-Sterniuk Department of Neuroinformatics and Biomedical Engineering Institute of Computer Science Maria Curie-Sklodowska University Lublin Poland Hishoo Sp. z o.o Gdynia Poland Faculty of Computer Science Kazimierz Wielki University Bydgoszcz Poland Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland

ISBN: (数字)9798331527563

ISBN: (纸本)9798331527570

automatic or semi-automatic recognition of selected emotions using Machine Learning (ML) algorithms requires practical, fast and accurate implementation of the steps involved in acquiring the actual signals (e.g. speech, facial expression, posture and body movements), recording them in the form of an optimal feature vector/matrix, correctly interpreting the above data and reproducing and generalising this process within the ML system. Depending on the accuracy and speed required and the degree of its ‘invasiveness’ (e.g. by attaching sensors to the user’s body), single or multi-modal interpretations of biometric signals associated with different groups of emotions are possible. This group of studies, despite their relative non-invasiveness, requires the caution prescribed by the Artificial Intelligence (AI) Act and RODO Act and the possibility of being replaced (if necessary) by alternatives. This article aims to analyse the opportunities and risks associated with this group of technologies, with a particular focus on directions for further development.

关键词： Emotion recognition Machine learning algorithms Accuracy Video on demand Speech recognition Machine learning Feature extraction Recording Convolutional neural networks Web sites

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