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Proceedings of the 7th International Conference on Future Networks and Distributed Systems

作者： Aws Zuhair Sameen Mohammed Hasan Alwan Mayssam Saad Kadhum Yousif I Hammadi Mokhalad Abdulameer Kadhim Alsaeedi Ahmed Aziz Mohammed Saleh Ali Muthanna Department of Medical Instrumentation Engineering Techniques Al-Farahidi University Iraq Department of Communications Engineering University of Diyala Iraq Dep. of Medical Instruments Engineering Techniques Bilad Alrafidain University College Iraq Department of computer science Benha university Egypt and International Business Management Department Tashkent State University of Economics Uzbekistan Institute of Computer Technologies and Information Security Southern Federal University Russia

ISBN: (纸本)9798400709036

Vehicular Ad-hoc Network (VANET) becomes a fundamental subcategory of mobile ad-hoc networks that provides vehicles to communicate with each other and with roadside infrastructure smartly. Various VANET performance challenges are considered in terms of Quality of Service (QoS) due to vehicle speed and transmission rates. Different problems cause performance degradation as performance anomaly where high rates of vehicles have to meet the speed of the low rates vehicle while transmitting data. In this paper, a QoS-aware Signal to Noise Ratio (SNR) admission control mechanism (QASAC) is proposed to handle the performance anomaly problem while maintaining the QoS levels for different traffic types. QASAC has been compared against the latest SNR based admission control mechanism. QASAC has enhanced the performance of data delivery up to 23% in terms of data dropping rates for high priority traffic.

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An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents

arXiv

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arXiv 2021年

作者： Monaci, Marta Agasucci, Valerio Grani, Giorgio Sapienza University of Rome Dep. of Computer Science Control and Management Engineering Rome Italy Sapienza University of Rome Dep. of Statistics Rome Italy

In this work, we present a method that applies Deep Reinforcement Learning, an approximate dynamic programming procedure using deep neural networks, to the job shop scheduling problem (JSSP). The aim is to show that a greedy-like heuristic trained on a subset of problems, can effectively generalize to some extent to unseen instances, and be competitive compared to other methods. We model the JSSP as a Markov Decision Process and we exploit the efficacy of reinforcement learning to solve the problem. We adopt an actor-critic scheme based on policy gradients, specifically the Proximal Policy Gradient method, where the action taken by the agent is influenced by policy considerations on the state-value function. The procedures take into account the challenging nature of JSSP, where the state and the action space change for every instance and after each decision. To tackle this variability, we introduced a novel model based on two incident Long-Short Term Memory networks, followed by an encoding model, different in structure for both the actor and the critic. Experiments show the algorithm reaches good solutions in a short time, proving that is possible to generate new greedy heuristics just from learning-based methodologies. We compared our algorithms against several established heuristics, an adaptive method, a commercial solver based on branch and cut, and another approach based on Deep Reinforcement Learning, proving the validity of the proposed method in terms of time and makespan. The model can generalize, to some extent, to larger problems originating from a different *** Codes 90-08 © 2021, CC BY.

关键词： Reinforcement learning

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Improving Obstacle Avoidance Strategies in Autonomous Navigation of a Sailboat

Improving Obstacle Avoidance Strategies in Autonomous Naviga...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Pedro Paiva Luís Gomes Dep. Electrical and Computer Engineering NOVA School of Science and Technology — FCT-NOVA NOVA University Lisbon Caparica Portugal School of Science and Technology Center of Technology and Systems (UNINOVA-CTS) and Associated Lab of Intelligent Systems (LASI) NOVA University Lisbon Caparica Portugal

This work explores the different mechanisms involved in creating a behavioural system for route planning and collision avoidance, taking into account the constraints imposed by the navigational characteristics of the sailboat. The implementation of these mechanisms is accompanied by an introduction to fundamental concepts, including Artificial Potential Fields, Histograms of Vector Fields, Navigation in the No-Go Zone, Differentiation of the Nature of Obstacles resulting in Different Operations, and the Constitution of Different Areas of Actuation. Finally, multiple simulations are conducted in a virtual environment to verify the resilience of the proposed navigation strategy.

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Smart Harvesting based on Image Processing

Smart Harvesting based on Image Processing

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2020 International computer Symposium, ICS 2020

作者： Joseph, S.P Wijerathna, L.L.M.C. Epa, K.G.R.D. Egalla, E.K.W.A.P.K. Abeygunawardhana, P.W.K. De Silva, R Sri Lanka Institute of Information Technology Dep. of Computer Systems Engineering Faculty of Computing Malabe10115 Sri Lanka Sri Lanka Institute of Information Technology Dep. of Software Engineering Faculty of Computing Malabe10115 Sri Lanka

ISBN: (纸本)9781728192550

Vision device is a critical component of fruit harvesting mobile robot which is designed for recognizing and harvesting of tomato fruits. The system of vision device of the moving robot, for a dedicated path identification with the use of colour detection algorithms and contour detection algorithms could be stated as an additional usage of the image-based technology. When the robot operates in real life, varying environmental parameters would not affect its activity, since the robot will be functioning mainly indoors, specifically in a greenhouse. Robust fruit segmentation algorithms for the visual system and the fruit plucking mechanism using a readymade robot arm with a soft gripper where it operates with basic hardware components like motors, controlled by a microcontroller with the intervention of kinematic theories, is being used with the goal of collecting fruit objects efficiently in the natural world. Plucking only the ripe and healthy object fruit without damaging both the fruit and the tree is the intended task of the system. The aim is to reduce human effort by promoting automation concepts in agriculture in developing countries like Sri Lanka with great potential, where agriculture plays a vital role in the development of the economy while indoor plantation and harvesting mechanism are also being developing to cater to the economy of the country as well. The way that this system is implemented will be discussed in this paper. © 2020 IEEE.

关键词： Fruits

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Effect of Temperature and Germania on the Performance of Germania Doped Silica Fiber Raman Scattering Amplifier

Research Square

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Research Square 2022年

作者： El-Den, B.M. Zaghloul, Adel Communication Dep. Fuclty of Engneering Delta University for Science and Technology Gamasa city Egypt Delta University for Science and Technology College of Engineering Dept. of Communications & Computer Zagazig University Egypt

The Raman gain coefficient, the attenuations at signal and pump wavelengths and the refractive indices of both core and cladding of silica doped Germania optical fiber are functions of the Germania ratio, temperature and wavelengths. The Raman amplifier gain increases with Germania ratio but it decreases with temperature. Also, Raman gain either increases or decreases with signal wavelength. As the fiber core radius increases, the Raman gain decreases. The gain distribution through the amplifier length of dual pumps with power divided ratio (S=0.5) is better than that for the forward pump amplifier and the backward pump amplifier. The forward pump has a maximized gain but the backward pump has a minimized gain, while the dual pumps have both the maximum and minimized gains. The final amplifier gain for the three kinds of pumps with the same pump power (Pp) is equally. The pump wavelength (λp=1.4553μm) gives the biggest Raman gain at the center of wideband signal wavelength (λs=1.50 to 1.60μm). With λp =1.48μm, the gain increases with λs until λs=1.57μm and after that the gain decreases with λs and so with the above three kinds of pumps, gain fluctuations over the band wavelength of signal. The threshold pump power and gain saturation are studied. © 2022, CC BY.

关键词： Stimulated Raman scattering

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Decoupled feedforward-feedback periodic event-triggered control for disturbance rejection ⁎

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IFAC-PapersOnLine 2020年第2期53卷 2708-2713页

作者： Ernesto Aranda-Escolástico María Guinaldo José Luis Guzmén Sebastián Dormido Dep. of Software and Systems Engineering UNED Dep. of Computer Sciences and Automatic Control UNED Dep. of Informatics ceiA3 CIESOL University of Almería

In this paper, feedforward and feedback controllers are studied considering decoupled periodic event-triggering mechanisms for output and disturbance sensors. Stability and robustness conditions for linear systems are obtained considering transportation delays and actuator saturation following the Lyapunov-Krasovskii procedure. A numerical example shows that the proposed control strategy reduces the communication between sensors and controller significantly, while the system performance is not deteriorated.

关键词： Event-triggered control feedforward control Lyapunov stability time delay disturbance rejection saturation

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Evidence-Based Quality-Aware Agile software Development Process: Design and Evaluation

SSRN

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SSRN 2023年

作者： Karhapää, Pertti Behutiye, Woubshet Seppänen, Pertti Rodríguez, Pilar Oivo, Markku Franch, Xavier Martinez-Fernandez, Silverio López, Lidia Choraś, Michal Bagnato, Alessandra Aaramaa, Sanja Partanen, Jari University of Oulu Oulu90014 Finland Department of Service and Information System Engineering UPC-BarcelonaTech Barcelona08034 Spain Kaiserslautern67663 Germany ITTI Sp. z o.o Poznan61-612 Poland University of Science and Technology UTP Univerisy of Science and Technology Bydgoszcz5-796 Poland Softeam Paris75016 France Nokia Oy Oulu90620 Finland Bittium Wireless Ltd. Oulu90590 Finland University of Puget Sound United States Dep. Of Languages Computer Systems and Software Engineering Faculty of Computer Science Universidad Politécnica de Madrid Spain Dep. ESSI GESSI Research Group UPC-BarcelonaTech Barcelona08034 Spain Centro Nacional de Supercomputacíon Barcelona08034 Spain

Context Agile software development (ASD) aims to deliver high-quality software. However, software quality often gets less attention due to focus on *** an evidence-based quality-aware ASD process that organizations can use to create a more quality-aware development process and improve software *** methodUsing design science research, we collaborated with four organizations applying ASD in different contexts. Involving a total of 35 practitioners, we designed company-specific evidence-based quality-aware ASD processes, which were validated through simulated scenarios, implemented, and evaluated by the practitioners. ResultsA general ASD process model, derived from the company-specific models, was created, which shows the specific activities, frequencies, roles, and development phases where evidence can be used to improve software quality. The new process model contributed towards improved bottleneck identification, release readiness, and quality issues prioritization. We also learned that companies must be mindful of the rules that determine the use of evidence. Conclusion Integrating the use of quality related evidence into the ASD process can make it quality-aware, supporting software quality management, and enabling timely reaction through fast feedback loops. The evidence-based quality-aware ASD process is applicable in any Scrum-like ASD process. Applicability in other forms of ASD, however, requires further research. © 2023, The Authors. All rights reserved.

关键词： Quality control

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Deep Learning Technology Used High Dynamic Range Image Reconstruction And Detection

Deep Learning Technology Used High Dynamic Range Image Recon...

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Electrical Electronics and Computing Technologies (ICEECT), International Conference on

作者： M. Bheemalingaiah R. Srinivasan V. Vijey Nathan Raju Kolluri Amit Gupta Department of CSE J.B Institute of Engineering and Technology Hyderabad Telangana Department of CSE School of Computer Science and Engineering Galgotia University U.P India Department of CSE SRM TRP Engineering College Tiruchirappalli Tamilnadu India Department of ECE Narasaraopet Engineering College Narasaraopet Andhra Pradesh India Dep. of AI & ML J.B Institute of Engineering and Technology Hyderabad Telangana

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

The suggested remedy for saturated pixels in digital camera photos introduces a brand-new learning-based method for reconstructing images with high dynamic range (HDR). While current techniques concentrate on increasing brightness range, they frequently fall short in producing realistic textures, leading to errors in places that are too saturated. Our method reconstructs an HDR image by using aesthetically beautiful saturated pixels from a low dynamic range (LDR) image. We provide a feature masking strategy to address problems discovered during training, when saturated and well-exposed pixels got comparable convolutional filters, resulting in uncertainty and checkerboard and halo aberrations. This method improves the overall quality of the reconstruction by reducing the contribution of features from saturated regions. Furthermore, in order to guarantee visually pleasing textures in the reconstructed HDR photos, we adjust the perceptual loss function based on *** use a two-step procedure in order to properly train our system. We first train the system for picture in painting on a sizable dataset, and then we modify it for HDR reconstruction. Our method performs exceptionally well even with a small number of HDR photos because it uses an advanced sampling strategy to choose hard training patches from a wide range of settings. Convolutional neural networks, feature masking, perceptual loss, and high dynamic range imagery are important components of our methodology.

关键词： Training Uncertainty Filters Image color analysis Supervised learning Digital cameras High dynamic range Convolutional neural networks Image reconstruction Painting

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Internet of Things Protocols (IoTp) Literature Review 23

Internet of Things Protocols (IoTp) Literature Review

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Proceedings of the 7th International Conference on Future Networks and Distributed Systems

作者： Ali Alamery Mohanad Abd Shehab Omar Abdulkareem Mahmood Yousif I Hammadi Ahmed Aziz Mohammed Saleh Ali Muthanna Balad Al-hadeth group company Balad Al-hadeth group company Iraq Electrical Engineering Department Mustansiriyah University Iraq Department of Communications Engineering University of Diyala Iraq Dep. of Medical Instruments Engineering Techniques Bilad Alrafidain University College Iraq Department of computer science Benha university Egypt and International Business Management Department Tashkent State University of Economics Uzbekistan Institute of Computer Technologies and Information Security Southern Federal University Russia

ISBN: (纸本)9798400709036

Considering today's variety of technologies and devices connected to the network, a huge number of manufacturers, there are many problems of their interaction and the need to create and adopt specialized communication standards and protocols. This article is devoted to the description of various protocols proposed by the IEEE, IETF and ITU for use in the framework of the concept of the Internet of Things. The article includes a description of the protocols of the application, transport, network and data link layers of the TCP / IP model. It also discusses protocols designed specifically to meet IoT requirements. A brief description of the protocols and the principle of operation of each of them are given. This review article contributes to a more correct choice of protocols when building a network, detecting and managing devices, and establishing interaction between objects of the Internet of Things.

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THE DUAL PC ALGORITHM AND THE ROLE OF GAUSSIANITY FOR STRUCTURE LEARNING OF BAYESIAN NETWORKS

arXiv

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arXiv 2021年

作者： Giudice, Enrico Kuipers, Jack Moffa, Giusi Dep. of Mathematics and Computer Science University of Basel Basel Switzerland Dep. of Biosystems Science and Engineering ETH Zurich Basel Switzerland Division of Psychiatry University College London London United Kingdom

Learning the graphical structure of Bayesian networks is key to describing data-generating mechanisms in many complex applications but poses considerable computational challenges. Observational data can only identify the equivalence class of the directed acyclic graph underlying a Bayesian network model, and a variety of methods exist to tackle the problem. Under certain assumptions, the popular PC algorithm can consistently recover the correct equivalence class by reverse-engineering the conditional indep.ndence (CI) relationships holding in the variable distribution. The dual PC algorithm is a novel scheme to carry out the CI tests within the PC algorithm by leveraging the inverse relationship between covariance and precision matrices. By exploiting block matrix inversions we can also perform tests on partial correlations of complementary (or dual) conditioning sets. The multiple CI tests of the dual PC algorithm proceed by first considering marginal and full-order CI relationships and progressively moving to central-order ones. Simulation studies show that the dual PC algorithm outperforms the classic PC algorithm both in terms of run time and in recovering the underlying network structure, even in the presence of deviations from Gaussianity. Additionally, we show that the dual PC algorithm applies for Gaussian copula models, and demonstrate its performance in that setting. Copyright © 2021, The Authors. All rights reserved.

关键词： Bayesian networks

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