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Letteratura scientifica selezionata sul tema "MADDPG"

Autore: Grafiati

Pubblicato: 25 gennaio 2025

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Articoli di riviste sul tema "MADDPG"

Yang, Jianfeng, Xinwei Yang e Tianqi Yu. "Multi-Unmanned Aerial Vehicle Confrontation in Intelligent Air Combat: A Multi-Agent Deep Reinforcement Learning Approach". Drones 8, n. 8 (7 agosto 2024): 382. http://dx.doi.org/10.3390/drones8080382.

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Multiple unmanned aerial vehicle (multi-UAV) confrontation is becoming an increasingly important combat mode in intelligent air combat. The confrontation highly relies on the intelligent collaboration and real-time decision-making of the UAVs. Thus, a decomposed and prioritized experience replay (PER)-based multi-agent deep deterministic policy gradient (DP-MADDPG) algorithm has been proposed in this paper for the moving and attacking decisions of UAVs. Specifically, the confrontation is formulated as a partially observable Markov game. To solve the problem, the DP-MADDPG algorithm is proposed by integrating the decomposed and PER mechanisms into the traditional MADDPG. To overcome the technical challenges of the convergence to a local optimum and a single dominant policy, the decomposed mechanism is applied to modify the MADDPG framework with local and global dual critic networks. Furthermore, to improve the convergence rate of the MADDPG training process, the PER mechanism is utilized to optimize the sampling efficiency from the experience replay buffer. Simulations have been conducted based on the Multi-agent Combat Arena (MaCA) platform, wherein the traditional MADDPG and independent learning DDPG (ILDDPG) algorithms are benchmarks. Simulation results indicate that the proposed DP-MADDPG improves the convergence rate and the convergent reward value. During confrontations against the vanilla distance-prioritized rule-empowered and intelligent ILDDPG-empowered blue parties, the DP-MADDPG-empowered red party can improve the win rate to 96% and 80.5%, respectively.

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Zhang, Xiaoping, Yuanpeng Zheng, Li Wang, Arsen Abdulali e Fumiya Iida. "Multi-Agent Collaborative Target Search Based on the Multi-Agent Deep Deterministic Policy Gradient with Emotional Intrinsic Motivation". Applied Sciences 13, n. 21 (1 novembre 2023): 11951. http://dx.doi.org/10.3390/app132111951.

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Multi-agent collaborative target search is one of the main challenges in the multi-agent field, and deep reinforcement learning (DRL) is a good way to learn such a task. However, DRL always faces the problem of sparse reward, which to some extent reduces its efficiency in task learning. Introducing intrinsic motivation has proved to be a useful way to make the sparse reward in DRL. So, based on the multi-agent deep deterministic policy gradient (MADDPG) structure, a new MADDPG algorithm with the emotional intrinsic motivation name MADDPG-E is proposed in this paper for the multi-agent collaborative target search. In MADDPG-E, a new emotional intrinsic motivation module with three emotions, joy, sadness, and fear, is designed. The three emotions are defined by corresponding psychological knowledge to the multi-agent embodied situations in an environment. An emotional steady-state variable function H is then designed to help judge the goodness of the emotions. Based on H, an emotion-based intrinsic reward function is finally proposed. With the designed emotional intrinsic motivation module, the multi-agent system always tries to make itself joy, which means it always learns to search the target. To show the effectiveness of the proposed MADDPG-E algorithm, two kinds of simulation experiments with a determined initial position and random initial position, respectively, are carried out, and comparisons are performed with MADDPG as well as MADDPG-ICM (MADDPG with an intrinsic curiosity module). The results show that with the designed emotional intrinsic motivation module, MADDPG-E has a higher learning speed and better learning stability, and the advantage is more obvious when facing complex situations.

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Wilk, Patrick, Ning Wang e Jie Li. "Multi-Agent Reinforcement Learning for Smart Community Energy Management". Energies 17, n. 20 (20 ottobre 2024): 5211. http://dx.doi.org/10.3390/en17205211.

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This paper investigates a Local Strategy-Driven Multi-Agent Deep Deterministic Policy Gradient (LSD-MADDPG) method for demand-side energy management systems (EMS) in smart communities. LSD-MADDPG modifies the conventional MADDPG framework by limiting data sharing during centralized training to only discretized strategic information. During execution, it relies solely on local information, eliminating post-training data exchange. This approach addresses critical challenges commonly faced by EMS solutions serving dynamic, increasing-scale communities, such as communication delays, single-point failures, scalability, and nonstationary environments. By leveraging and sharing only strategic information among agents, LSD-MADDPG optimizes decision-making while enhancing training efficiency and safeguarding data privacy—a critical concern in the community EMS. The proposed LSD-MADDPG has proven to be capable of reducing energy costs and flattening the community demand curve by coordinating indoor temperature control and electric vehicle charging schedules across multiple buildings. Comparative case studies reveal that LSD-MADDPG excels in both cooperative and competitive settings by ensuring fair alignment between individual buildings’ energy management actions and community-wide goals, highlighting its potential for advancing future smart community energy management.

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Wang, Lixing, e Huirong Jiao. "Multi-Agent Reinforcement Learning-Based Computation Offloading for Unmanned Aerial Vehicle Post-Disaster Rescue". Sensors 24, n. 24 (15 dicembre 2024): 8014. https://doi.org/10.3390/s24248014.

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Natural disasters cause significant losses. Unmanned aerial vehicles (UAVs) are valuable in rescue missions but need to offload tasks to edge servers due to their limited computing power and battery life. This study proposes a task offloading decision algorithm called the multi-agent deep deterministic policy gradient with cooperation and experience replay (CER-MADDPG), which is based on multi-agent reinforcement learning for UAV computation offloading. CER-MADDPG emphasizes collaboration between UAVs and uses historical UAV experiences to classify and obtain optimal strategies. It enables collaboration among edge devices through the design of the ’critic’ network. Additionally, by defining good and bad experiences for UAVs, experiences are classified into two separate buffers, allowing UAVs to learn from them, seek benefits, avoid harm, and reduce system overhead. The performance of CER-MADDPG was verified through simulations in two aspects. First, the influence of key hyperparameters on performance was examined, and the optimal values were determined. Second, CER-MADDPG was compared with other baseline algorithms. The results show that compared with MADDPG and stochastic game-based resource allocation with prioritized experience replay, CER-MADDPG achieves the lowest system overhead and superior stability and scalability.

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Petrenko, V. I., F. B. Tebueva, M. M. Gurchinsky e A. S. Pavlov. "Method of Multi-Agent Reinforcement Learning in Systems with a Variable Number of Agents". Mekhatronika, Avtomatizatsiya, Upravlenie 23, n. 10 (9 ottobre 2022): 507–14. http://dx.doi.org/10.17587/mau.23.507-514.

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Multi-agent reinforcement learning methods are one of the newest and actively developing areas of machine learning. Among the methods of multi-agent reinforcement learning, one of the most promising is the MADDPG method, the advantage of which is the high convergence of the learning process. The disadvantage of the MADDPG method is the need to ensure the equality of the number of agents N at the training stage and the number of agents K at the functioning stage. At the same time, target multi-agent systems (MAS), such as groups of UAVs or mobile ground robots, are systems with a variable number of agents, which does not allow the use of the MADDPG method in them. To solve this problem, the article proposes an improved MADDPG method for multi-agent reinforcement learning in systems with a variable number of agents. The improved MADDPG method is based on the hypothesis that to perform its functions, an agent needs information about the state of not all other MAS agents, but only a few nearest neighbors. Based on this hypothesis, a method of hybrid joint / independent learning of MAS with a variable number of agents is proposed, which involves training a small number of agents N to ensure the functioning of an arbitrary number of agents K, K> N. The experiments have shown that the improved MADDPG method provides an efficiency of MAS functioning com-parable to the original method with varying the number of K agents at the stage of functioning within wide limits.

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Chen, Zhisheng. "DQN–MADDPG Coordinating the Multi-agent Cooperation". Highlights in Science, Engineering and Technology 39 (1 aprile 2023): 1141–45. http://dx.doi.org/10.54097/hset.v39i.6720.

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Multi-agent coordinating aims for many agents to finish the same or more mutual goals. To achieve this function, there are two main ideas; the first is making multi-agents communicate with each other and acquire the information for other agents. Another is sharing the same environment, dividing the work, and cooperating to achieve the goal. ‘’Gym-cooking’’ is an excellent model to test the algorithms’ performance in network coordination and game theory; this is a sharing environment. Based on sharing information, the agent have two networks(policy and target) and tries to do something more efficiently. This article will increase the complexity of the environment and use different algorithms to process the experiment. Specially, this paper will use the MADDPG model as the primary model to show its performance in a complex environment and contrast other models like DQN. The MADDPG model in this experiment is unlike the traditional MADDPG; the work trains the MADDPG network to deal with emergencies and accidents.

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Liu, Bo, Shulei Wang, Qinghua Li, Xinyang Zhao, Yunqing Pan e Changhong Wang. "Task Assignment of UAV Swarms Based on Deep Reinforcement Learning". Drones 7, n. 5 (29 aprile 2023): 297. http://dx.doi.org/10.3390/drones7050297.

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UAV swarm applications are critical for the future, and their mission-planning and decision-making capabilities have a direct impact on their performance. However, creating a dynamic and scalable assignment algorithm that can be applied to various groups and tasks is a significant challenge. To address this issue, we propose the Extensible Multi-Agent Deep Deterministic Policy Gradient (Ex-MADDPG) algorithm, which builds on the MADDPG framework. The Ex-MADDPG algorithm improves the robustness and scalability of the assignment algorithm by incorporating local communication, mean simulation observation, a synchronous parameter-training mechanism, and a scalable multiple-decision mechanism. Our approach has been validated for effectiveness and scalability through both simulation experiments in the Multi-Agent Particle Environment (MPE) and a real-world experiment. Overall, our results demonstrate that the Ex-MADDPG algorithm is effective in handling various groups and tasks and can scale well as the swarm size increases. Therefore, our algorithm holds great promise for mission planning and decision-making in UAV swarm applications.

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Wei, Juyao, Zhenggang Lu, Zheng Yin e Zhipeng Jing. "Multiagent Reinforcement Learning for Active Guidance Control of Railway Vehicles with Independently Rotating Wheels". Applied Sciences 14, n. 4 (19 febbraio 2024): 1677. http://dx.doi.org/10.3390/app14041677.

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This paper presents a novel data-driven multiagent reinforcement learning (MARL) controller for enhancing the running stability of independently rotating wheels (IRW) and reducing wheel–rail wear. We base our active guidance controller on the multiagent deep deterministic policy gradient (MADDPG) algorithm. In this framework, each IRW controller is treated as an independent agent, facilitating localized control of individual wheelsets and reducing the complexity of the required observations. Furthermore, we enhance the MADDPG algorithm with prioritized experience replay (PER), resulting in the PER-MADDPG algorithm, which optimizes training convergence and stability by prioritizing informative experience samples. In this paper, we compare the PER-MADDPG algorithm against existing controllers, demonstrating the superior simulation performance of the proposed algorithm, particularly in terms of self-centering capability and curve-negotiation behavior, effectively reducing the wear number. We also develop a scaled IRW vehicle for active guidance experiments. The experimental results validate the enhanced running performance of IRW vehicles using our proposed controller.

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Li, Xilun, Zhan Li, Xiaolong Zheng , Xuebo Yang e Xinghu Yu . "The Study of Crash-Tolerant, Multi-Agent Offensive and Defensive Games Using Deep Reinforcement Learning". Electronics 12, n. 2 (8 gennaio 2023): 327. http://dx.doi.org/10.3390/electronics12020327.

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In the multi-agent offensive and defensive game (ODG), each agent achieves its goal by cooperating or competing with other agents. The multi-agent deep reinforcement learning (MADRL) method is applied in similar scenarios to help agents make decisions. In various situations, the agents of both sides may crash due to collisions. However, the existing algorithms cannot deal with the situation where the number of agents reduces. Based on the multi-agent deep deterministic policy gradient (MADDPG) algorithm, we study a method to deal with a reduction in the number of agents in the training process without changing the structure of the neural network (NN), which is called the frozen agent method for the MADDPG (FA-MADDPG) algorithm. In addition, we design a distance–collision reward function to help agents learn strategies better. Through the experiments in four scenarios with different numbers of agents, it is verified that the algorithm we proposed can not only successfully deal with the problem of agent number reduction in the training stage but also show better performance and higher efficiency than the MADDPG algorithm in simulation.

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Hu, Weichao, Hongzhang Mu, Yanyan Chen, Yixin Liu e Xiaosong Li. "Modeling Interactions of Autonomous/Manual Vehicles and Pedestrians with a Multi-Agent Deep Deterministic Policy Gradient". Sustainability 15, n. 7 (3 aprile 2023): 6156. http://dx.doi.org/10.3390/su15076156.

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This article focuses on the development of a stable pedestrian crash avoidance mitigation system for autonomous vehicles (AVs). Previous works have only used simple AV–pedestrian models, which do not reflect the actual interaction and risk status of intelligent intersections with manual vehicles. The paper presents a model that simulates the interaction between automatic driving vehicles and pedestrians on unsignalized crosswalks using the multi-agent deep deterministic policy gradient (MADDPG) algorithm. The MADDPG algorithm optimizes the PCAM strategy through the continuous interaction of multiple independent agents and effectively captures the inherent uncertainty in continuous learning and human behavior. Experimental results show that the MADDPG model can fully mitigate collisions in different scenarios and outperforms the DDPG and DRL algorithms.

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Più fonti

Tesi sul tema "MADDPG"

Abdulazeez, Abdulhakeem. "Development of an autonomous control protocol for a UAV fleet network using machine learning". Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASG107.

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Dans le contexte de la robotique en réseau sans fil, des missions complexes, telles que la recherche et le sauvetage autonomes, peuvent nécessiter l’utilisation de plusieurs véhicules aériens sans pilote (UAV) déployés en formation afin d’augmenter l’efficacité et la qualité de service (QoS) tout en garantissant des impératifs spécifiques à la mission, tels que la maximisation de la couverture d’une zone en un seul passage de la flotte sur des sous-sections de celle-ci. Pour relever ces défis, un protocole efficace de localisation et de contrôle de formation est nécessaire.Les solutions existantes proposées pour la localisation à faible coût des UAV utilisant les valeurs de l’indicateur de puissance du signal reçu (RSSI) ont été conçues pour des environnements intérieurs, en réponse à la limitation du Global Navigation Satellite System (GNSS) en intérieur, ce qui les rend inapplicables aux environnements extérieurs.Celles développées pour fonctionner en extérieur sont soit inadaptées aux nœuds mobiles, soit inapplicables aux dispositifs aériens déployés dans des environnements complexes avec des effets de propagation variables. De plus, les protocoles de contrôle existants spécifiquement conçus pour le contrôle autonome des flottes de drones ne tiennent pas compte de l’orientation de la formation.Afin de couvrir ces aspects, cette thèse propose un protocole de contrôle de formation basé sur l’apprentissage, comprenant trois mécanismes de contrôle pour aborder les questions d’estimation de distance en extérieur, d’adaptation de la vitesse et d’orientation de la formation. Le protocole adapte le principe d’apprentissage par renforcement multi-agents (MARL) pour autopiloter la structure leader-suiveur de la flotte de drones en utilisant uniquement les valeurs RSSI reçues par les UAV lors des communications sans fil avec leursvoisins. Les suiveurs doivent suivre le leader tout en maintenant la structure leader-suiveur préconfigurée de manière autonome. Tout d’abord, un estimateur de distance basé sur un réseau de neurones profonds (DNN) utilisant le RSSI a été développé pour fournir des estimations plus précises de la distance entre n’importe quelle paire d’UAV en formation afin d’améliorer la localisation. L’estimateur a été entraîné à l’aide d’un ensemble de données collectées par simulation pour diverses configurations de formation en termes de vitesse, d’altitude, de tailles de formation et de modèles de perte de propagation. Le deuxième protocole traite du problème de l’adaptation de la vitesse en utilisant le principe basé sur le MARL, intégrant l’estimateur de distance basé sur le RSSI pour le calcul des distances. Les suiveurs sont formés par l’expérience collective de l’environnement pour ajuster leur vitesse de manière autonome par rapport à celle du leader lors d’un mouvement linéaire. Pour résoudre le problème d’alignement de l’orientation, un protocole de détection de direction et d’alignement de formation a été développé en utilisant le principe basé sur le MARL. Comme l’adaptateur de vitesse, ce protocole intègre également l’estimateur de distance. Les drones suiveurs sont entraînés à détecter la direction de vol du leader et à tourner comme un corps rigide autour de l’axe de lacet pour se réaligner sur le leader. Nous avons implémenté le protocole en utilisant NS3-3.35 intégré à la bibliothèque d’apprentissage automatique mlpack et évalué ses performances à travers plusieurs essais expérimentaux. Les résultats démontrent que le protocole atteint de meilleures performances en termes d’erreur estimée de distance tolérable, de stabilité de formation, d’erreur de déviation de formation et de temps de réponse accru
In the context of wireless networked robotics, complex missions, such as autonomous search and rescue may require the use of multiple Unmanned Aerial Vehicles (UAVs) deployed as a formation to achieve higher efficiency and Quality of Service (QoS) while assuring mission-specific imperatives like the maximization of area covered in a single passage of the fleet over area subsections. Addressing these challenges requires an efficient localization and formation control protocol.Existing solutions proposed for low-cost localization of UAVs using Received Signal Strength Indicator (RSSI) values, were designed for indoor environments in response to the limitation of Global Navigation Satellite System (GNSS) indoors, making them not applicable to outdoor environments.Those developed to work outdoors are either unsuitable for mobile nodes or not applicable for aerial devices deployed in complex environments with varying propagation effects. Also, existing control protocols designed specifically for autonomous control of UAV-fleet do not consider the formation orientation. To cover these areas, this thesis presents an efficient learning-based formation control protocol consisting of three control mechanism to address the issue of outdoor distance estimation, speed adaptation, and formation orientation. The protocol adapts the Multi-Agent Reinforcement Learning (MARL) principle to autopilot the UAV fleet leader-follower structure using only RSSI values the UAVs receive during wireless communication with their neighbors. The followersare expected to follow the leader while maintaining the pre-configured formation leader-follower structure autonomously. First, a DNN RSSI-based distance estimator was developed to provide more accurate estimates of the distance between any pair of UAVs in formation for better localization. The estimator was trained using a dataset collected through simulation for varying formation configurations in terms of speed, altitude, formation sizes, and propagation loss models. The second protocol addresses the issue of speed adaptation using the MARL-based principle, incorporating the RSSI-based distance estimator for ranging. The followers are trained through the collective experience of the environment to autonomously adjust their speed relative to that of the leader during a linear movement.To address the orientation alignment problem, a direction detection and formation alignment protocol was developed using the MARL-based principle. Like the speed adapter, this protocol also incorporates the distance estimator. Follower UAVs are trained to detect the direction of flight of the leader and rotate as rigid body along the yaw-axis to realign themselves with the leader. We implemented the protocol using NS3-3.35 incorporated with mlpack machine learning library, and evaluated its performance using several experimental trials. The results demonstrate that the protocol achieves better, tolerable estimated distance error, formation stability, formation deviation error, and increased response time

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Persson, Kristian, e Max Renberg. "Ambulance Safety: MADDE". Thesis, Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42610.

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Safety, a word that can be linked and interpreted in many different ways. Personal safety, that you should feel safe in your everyday life depending on your surroundings. IT security, to protect a persons or organization's valuable assets such as information. Flight safety, the safety of flying in its various kinds. There are safety issues in almost every area you look at, but this project that you will read about in this report is about traffic safety, more specifically, the safety of working in the back of an ambulance. Imagine working as an ambulance paramedic. You and your colleague have just picked up a “Prio 1” (most critical degree), classified patient who needs urgent care. You are sitting in the back of the ambulance and will take care of the patient while your colleague is driving the car. The situation is so critical that your colleague needs to drive as quickly as possible to get to the hospital in time. Thus, you must sit tight with a seat belt in order not to risk your own safety during the ride. Around you, there are a number of components you need to care of for the patient. You cannot reach these components because of the belt that clings to the chair. What are you going to do? Do you unbutton your belt to reach the components, but risk your own safety while driving? Or do you wear the belt incorrectly, so that you use the belt, but only over the hips (for example), so that you can reach the tools? Both of these alternatives are how the majority of ambulance paramedics use the seatbelt today to be able to do their job. Either you unbutton and release yourself completely from the belt or you use it, but incorrectly to reach everything the person in question needs in the ambulance. Both actions have resulted in a big amount of injuries to the caregivers and the numbers continues to increase continuously. This project is about just that. A solution to the problem of the working environment in the back of ambulances. Further in this report you will read about how two students at Halmstad University encountered the problem, but first and foremost how they solved it.
Säkerhet, ett ord som kan kopplas och tolkas på många olika sätt. Personlig säkerhet, att man ska känna sig trygg i sin vardag beroende på omgivning. IT-säkerhet, att skydda en persons eller en organisations värdefulla tillgångar som exempelvis information. Flygsäkerhet, säkerheten vid flygning av dess olika slag. Det finns säkerhetsfrågor inom nästan varje område, men arbetet som du kommer få läsa om i denna rapport handlar om trafiksäkerhet, mer specifikt, säkerheten vid arbete bak i en ambulans. Föreställ dig att du arbetar som ambulanssjukvårdare. Du och din kollega har precis plockat upp en “Prio 1” (mest akuta graden), klassad patient som behöver akut vård. Du sitter bak i ambulansen och ska vårda patienten medan din kollega kör bilen. Läget är så kritiskt att din kollega behöver köra så snabbt som möjligt för att hinna till sjukhuset i tid. Därmed måste du sitta fastspänd med bilbälte för att inte riskera din egen säkerhet under körningen. Runtomkring dig finns det ett antal komponenter du behöver för att vårda patienten. Du når inte dessa produkter på grund av bältet som håller fast dig i sätet. Vad gör du? Knäpper du loss bältet för att kunna nå komponenterna, men riskerar din egen säkerhet under bilfärden? Eller tar du på dig bältet på ett inkorrekt sätt, så du sitter bältad, men bara över höfterna (exempelvis), så att du kan nå verktygen? Båda alternativen är hur majoriteten av ambulanssjukvårdare går till väga idag för att kunna utföra sitt jobb. Antingen knäpper man loss och frigör sig helt från bältet eller så använder man det, fast på ett inkorrekt sätt för att kunna nå allt personen i fråga behöver i ambulansen. Båda handlingarna har lett till flertalet skador på vårdarna och antalet fortsätter öka kontinuerligt. Arbetet handlar just om detta. En lösning på problemet med arbetsmiljön bak i ambulanser. Vidare i denna rapport kommer du få läsa om hur två studenter vid Högskolan i Halmstad kom i kontakt med problemet, men framförallt hur de fann en lösning till det.

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Santos, Joana Isabel Fontes. "O efeito Maddie: análise da relação entre jornalistas e sistema judicial no desaparecimento de Maddie McCann". Master's thesis, [s.n.], 2009. http://hdl.handle.net/10284/1465.

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Dissertação de Mestrado apresentada à Universidade Fernando Pessoa como parte dos requisitos para obtenção do grau de Mestre em Ciências da Comunicação, especialização em Jornalismo.
A notícia considerada como uma construção social da realidade, resulta da permanente troca e negociação de significado dos acontecimentos. As fontes de informação constituem uma dimensão indispensável para a compreensão e exercício do jornalismo. Todos os dias, os jornalistas vêem-se obrigados a ultrapassar inúmeras barreiras no exercício da sua profissão. Nem a liberdade de informar e ser informado podem ser concebidas em termos absolutos, nem as normas ético-legais podem ser ignoradas. O relacionamento existente entre os jornalistas e o sistema judicial é um dos grandes obstáculos que o jornalista tenta ultrapassar quando o seu objectivo é informar a opinião pública sobre algum caso judicial. A partir do Caso Maddie McCann, um dos acontecimentos mais mediáticos de 2007, analisei a influência inglesa nos media portugueses, assim como a relação que os jornalistas têm com conceitos judiciais e o relacionamento que têm com a Polícia Judiciária. The news are considered as a social construction of reality in permanent change and negotiation with public events. The sources of information are an essential dimension to the understanding and the exercise of journalism. Every day, journalists are obliged to overcome many obstacles in the exercise of their profession. Not the freedom to inform and be informed can be conceived in absolute terms, nor the ethical and legal standards can be ignored. The relationship between journalists and the judiciary is one of the major obstacles that the journalist tries to overcome when your aim is to inform the audiences about a court case. From the Maddie McCann case, one of the most mediatic in 2007, is examined the english influence on the portuguese media and the relationship between journalists, legal concepts and the portuguese police. L’article consideré comme une construction sociale de la réalité résulte de la permanente échange et négociation du sens des événements. Les sources d'informations constituent une dimension indispensable pour comprendre et faire du journalisme. Chaque jour, les journalistes se voient obligés de surmonter de nombreux obstacles dans l'exercice de leur profession. Ni la liberté d'informer et d'être informé peuvent être conçues en termes absolus, ni les normes éthiques et juridiques peuvent être ignorés. La relation entre les journalistes et le pouvoir judiciaire est l'un des principaux obstacles que le journaliste tente de surmonter lorsque son objectif est d'informer l’opinion publique sur une affaire judiciaire. De l'affaire Maddie McCann, l'une des plus médiatiques de 2007, j’ai analisée l'influence anglaise sur les médias portugais, ainsi comme la relation que les journalistes ont avec les concepts juridiques et le relationement qu'ils ont avec la police portugaise.

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Maloney, Eric Daniel. "Frictional convergence and the Madden-Julian oscillation /". Thesis, Connect to this title online; UW restricted, 2000. http://hdl.handle.net/1773/10049.

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Ray, Pallav Kumar. "The Initiation of the Madden-Julian Oscillation (MJO)". Scholarly Repository, 2008. http://scholarlyrepository.miami.edu/oa_dissertations/77.

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A mesoscale tropical channel model is constructed to study the long-standing problem of the initiation of the Madden-Julian Oscillation (MJO). Two observed cases of MJO are chosen, one in boreal spring and one in boreal winter, without a priori knowledge of their initiation mechanism. With initial and lateral boundary conditions provided by a global reanalysis, this model is able to reproduce the initiation and gross features of two observed MJO events up to two months after the start of simulations. This leads to a conjecture that these two MJO events are generated by the influences from the lateral boundaries. This conjecture is supported by a series of sensitivity tests. These sensitivity tests demonstrate that the simulated MJO initiation does not critically depend on detailed characteristics of sea surface temperature (varying vs. constant in time, mean distribution from boreal spring vs. winter), initial conditions (within a 10 day period, perturbations in the initial conditions), the latitudinal location of the lateral boundaries (21 - 45˚N and S), and even latent heating and moist processes. The only factor found critical to the reproduction of the MJO initiation is time varying lateral boundary conditions from the reanalysis. When such lateral boundary conditions are replaced by time independent conditions, the model fails to reproduce the MJO initiation. The analysis of moist static energy has revealed that the discharge-recharge mechanism is not sufficient for the MJO initiation in the model. It is found that the latitudinal transport of westerly momentum from the extratropics is crucial in generating the lower tropospheric westerlies in the reanalysis and model. The energy source for the extratropical perturbation is through extraction of kinetic energy from the mean flow. The estimation of wave activity flux has revealed that there is a major region over the southern Indian Ocean, which produces wave activity flux towards the tropical genesis region of the MJO initiation. We have also investigated the time-scale of the boundary conditions that are responsible for the MJO initiation. Additions of small perturbations in the boundary conditions, and use of 10-day interpolated boundary conditions do not affect the MJO initiation. Thus boundary conditions responsible for the MJO initiation in the model must have time scales greater than 10 days, indicating that the shorter time scale stochastic forcing through the lateral boundaries did not play any major role. The estimation of the zonal momentum budget for the MJO initiation region has revealed the importance of the advective terms, particularly by the meridional winds before the onset of the MJO. The importance of the extratropical influences in initiating the MJO in the channel model leads to a speculation that a multi-year simulation using a tropical channel model would also produce reasonable MJO statistics if forced by time varying boundary conditions. Interestingly, the MJO statistics in the multi-year simulation using a tropical channel model is found to be not better than the global models. Increase of horizontal resolution and use of a different cumulus scheme did not improve the MJO simulation. We found that the error in the mean state was the main reason for the lack of MJO statistics in the model. The model took less than five days for the error to reach its climate bias. Thus, a good simulation of the mean state is important for the successful simulation of the MJO. Implications of these results are discussed. In short, this study has shown that the extratropical influences can be an efficient mechanism for the MJO initiation and calls for further research attention to this mechanism that has been somewhat neglected by mainstream MJO research.

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Saunders, M. W. M. "Ford Maddox Ford and the reading of prose". Thesis, University of Cambridge, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.373696.

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Singhruck, Patama. "Oceanic variability associated with the Madden-Julian oscillation". Thesis, University of East Anglia, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.504852.

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This study investigates the basin-wide oceanic variability associated with the Madden-Julian Oscillation (MJO) using new observations from the global array of profiling floats, known as Argo. Analysis of the Argo gridded data in a case study of the December 2003 to February 2004 MJO event in the Pacific Ocean reveals that the oceanic variability along the equator is characterised by an eastward propagating Kelvin wave response to the MJO surface wind stress anomalies. The observed phase speed and latitudinal structure are characteristics of the first baroclinic mode Kelvin wave. The vertical structures of these Kelvin waves are observed for the first time to extend downward to 1500 m. The amplitude of the deep ocean temperature anomalies is up to three times the amplitude ofthe observed annual cycle. With unprecedented coverage of salinity observations in the deep ocean provided by the Argo data, systematic changes in subsurface salinity variability during the MJO event are revealed for the first time. It is found that the salinity changes are associated with the Kelvin wave displacing isopycnals vertically. The composite study for the full period of the data set from January 2003 to December 2006 confirms the dominance of the Kelvin wave response in the subsurface temperature and salinity variability in the Pacific Ocean. Composites of sea surface temperature and sea surface salinity anomalies suggest the role of horizontal advection mediated by the Kelvin waves in addition to the MJO associated surface heat and fresh water fluxes variation. In the Indian Ocean, there is some evidence of a dynamical response to surface wind stress changes in the form of local upwelling and downwelling along 0°_5° Sin the central basin as well as in the equatorial eastern basin. However, the response did not exhibit propagating characteristics similar to the Pacific Ocean counterpart.

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Batstone, Crispian Peter. "Ocean-atmosphere interactions within the Madden-Julian Oscillation". Thesis, University of East Anglia, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398818.

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Sugiyama, Masahiro Ph D. Massachusetts Institute of Technology. "The Madden-Julian oscillation and nonlinear moisture modes". Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/42924.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2008.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 231-245).
The Madden-Julian oscillation (MJO), the dominant tropical intraseasonal variability with widespread meteorological impacts, continues to puzzle the climate research community on both theoretical and modeling fronts. Motivated by a recent interest in the role of humidity in tropical dynamics, this thesis hypothesizes that the MJO is a nonlinear moisture mode whose existence depends on moisture-convection feedback (the feedback between deep convection and environmental free-tropospheric humidity), and that weak moisture convection feedback in general circulation models accounts for their deficiencies with the MJO simulations. Moisture modes are found to exist in a large class of linear primitive equation models on the equatorial beta-plane. For models with standard quasi-equilibrium parameterizations,perturbation expansion analyses demonstrate that the weak temperature gradient (WTG) approximation of Sobel et al. describes the small-scale limit of the moisture mode accurately,with the small expansion parameter being the ratio between temperature tendency and adiabatic cooling. Under the WTG balance, the only leading order variables are humidity and vertical motion. Analyses of three models in the literature show that a moisture mode is unstable if moist static energy (MSE) sources such as cloud radiative forcing or gust-enhanced surface heat flux exceed the MSE export. Numerical calculations of a single-column model under the WTG configuration show that a realistic convective scheme can reproduce moisture mode instability. Sensitivity tests on the strength of moisture-convection feedback in the Emanuel scheme indicate that such a feedback is essential for moisture mode instability, confirming the prediction from simple models. To explore the nonlinear regime of a moisture mode, numerical calculations of a simplified Quasi-equilibrium Tropical Circulation Model on the equatorial beta-plane have been performed.
A classical Gill model augmented with a prognostic humidity variable can capture nonlinear dynamics of the moisture mode. In particular, nonlinear advection of dry air by Rossby gyres is found to move the moisture mode eastward. Notwithstanding progress made in the present thesis, numerous difficulties abound. The most significant issue is that moisture mode instability favors the smallest scale in the linear regime. The author suggests that scale interaction and its effect on the humidity budget might be an important research topic.
by Masahiro Sugiyama.
Ph.D.

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Ferreira, Ana Cristina. "O caso Maddie, na imprensa nacional: a semana seguinte". Master's thesis, Universidade da Beira Interior, 2009. http://hdl.handle.net/10400.6/1578.

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Na opinião de vários estudiosos dos media, o caso Maddie reúne muitos dos ingredientes necessários para que o público tenha mantido o interesse elevado que vem relevando desde o início. Se, à partida, trata-se “apenas” do desaparecimento de uma criança entre tantas outras, a verdade é que “uma menina inglesa, bonita, de olhos azuis, que desaparece num aldeamento turístico inglês, no Algarve, destino de férias tido por seguro pelos seus conterrâneos, é sempre uma janela aberta de oportunidade ao mediatismo”. (Edson Athayde, apud Carvalho et al., 2007: 14). O caso do desaparecimento de Madeleine McCann terá sido, com certeza, um dos acontecimentos mais mediáticos e, sobretudo, marcantes que terão surgido nos meios de comunicação social durante os últimos dois anos. Assim, neste trabalho procura-se encontrar a prioridade dada nas agendas dos meios de comunicação social a este caso, partindo dos conceitos de noticiabilidade e «agenda-setting» e do efeito do agendamento nos vários órgãos de comunicação social.
In the view of many scholars in the media, the case Maddie meets many of the ingredients necessary for the public interest has kept the high that comes from falling within the top. If, at the outset, it is “only” the disappearance of a child among many others, the truth is that “an English girl, beautiful, blue-eyed, which disappears in an English tourist resort in the Algarve, had a holiday destination for insurance for their countrymen, it is always an open window of opportunity to the media”. The case of the disappearance of Madeleine McCann has been, without doubt, one of the most media and, especially, that have arisen marked in the media over the past two years. Thus, this work seeks to find a priority in the agendas of the media in this case, building on the concepts of news and «agenda-setting» and the effect of scheduling in various media.

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Più fonti

Libri sul tema "MADDPG"

Constantine, David J. Madder. Newcastle Upon Tyne: Bloodaxe, 1987.

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Caswell, Brian. Maddie. St. Lucia, Qld., Australia: University of Queensland Press, 1995.

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Rayner, Claire. Maddie. London: Guild Publishing, 1988.

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Constantine, David. Madder. Newcastle upon Tyne: Bloodaxe Books, 1987.

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Korea). Institute for the Study of Theology Sŏnggyun'gwan Taehakkyo (Seoul. Madang. Seoul, Korea: Sungkonghoe University Press, 2004.

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King, Stephen. Rose Madder. New York: Signet, 1996.

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King, Stephen. Rose Madder. Oxford: ISIS, 1996.

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King, Stephen. Rose Madder. London: BCA, 1996.

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King, Stephen. Rose Madder. Boston: Compass Press, 1995.

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Rajentirakumar. Makalir Maddum. Madras: Arunotayam, 1985.

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Capitoli di libri sul tema "MADDPG"

Zhang, Yu, Shijia Zhou, Ning Guo, Tengfei Li, Xuechao Zou e Pin Tao. "SMPG: Adaptive Soft Update for Masked MADDPG". In Data Mining and Big Data, 50–61. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-9297-1_5.

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Xu, Zhong, Junxiang Liu, Le Luan, Weinan Fan e Wenxiong Mo. "Self-adversarial Network Based on MADDPG for Emergency Power Dispatch". In Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control, 1036–44. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3998-3_99.

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Wang, Ruizhe, Yuanqing Xia, Yiran Wei, Zhenhua Pan e Jie Li. "MADDPG-Based Distributed Cooperative Search Strategy for Heterogeneous Agents System". In Lecture Notes in Electrical Engineering, 292–305. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3332-3_26.

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Zhang, Haiwei, Weijun Zheng, Ding Chen, Jinghui Fang e Yifei Wei. "Optimization of Energy Transaction Strategy Between Microgrids Based on MADDPG". In Human Centered Computing, 261–71. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-23741-6_24.

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Yao, Yiming, Tao Ren, Meng Cui, Dong Liu e Jianwei Niu. "Meta-MADDPG: Achieving Transfer-Enhanced MEC Scheduling via Meta Reinforcement Learning". In Wireless Algorithms, Systems, and Applications, 572–85. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-19211-1_47.

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Nguyen, Tri-Hai, Truong Khang Nguyen, Minh-Phung Bui, Tuan-Duc Nguyen, Vo Nguyen Quoc Bao e Demeke Shumeye Lakew. "Age of Information Minimization in Hierarchical Aerial Networks via MADDPG Approach". In Lecture Notes on Data Engineering and Communications Technologies, 375–84. Cham: Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-75593-4_34.

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Zhou, Ping, e Hui Lu. "An Efficient MADDPG with Episode-Parallel Interaction and Dual Priority Experience Replay". In Lecture Notes in Electrical Engineering, 527–38. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-3336-1_45.

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Wang, Weifeng, Baiqiao Huang e YanXia Wu. "Design of a Multi-unmanned Aerial Vehicle Cooperative Hunting System Based on MADDPG". In Lecture Notes in Electrical Engineering, 480–86. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-7139-4_66.

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Xu, Leixin, Weibin Chen, Xiang Liu e Yang-Yang Chen. "MADDPG: Multi-agent Deep Deterministic Policy Gradient Algorithm for Formation Elliptical Encirclement and Collision Avoidance". In Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control, 239–50. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3998-3_24.

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Johnson, Mark. "Maddog Trades". In Full Trading Circle, 281–94. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119204503.app3.

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Atti di convegni sul tema "MADDPG"

Han, Zhenyuan, Lu Sun, Liangtian Wan, Ruoheng Luo e Xianpeng Wang. "MADDPG-Based Power Control Strategy for Unmanned Vehicles". In 2024 IEEE International Conference on Smart Internet of Things (SmartIoT), 45–50. IEEE, 2024. https://doi.org/10.1109/smartiot62235.2024.00016.

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Guo, Jiawen, e Guohui Zhu. "Resource Allocation Strategy for Intra-slice Networks Based on MADDPG". In 2024 6th International Conference on Natural Language Processing (ICNLP), 643–49. IEEE, 2024. http://dx.doi.org/10.1109/icnlp60986.2024.10692486.

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Xiang, Fangyue. "Multi-vessel area target search model based on MADDPG algorithm". In 2024 4th International Symposium on AI (ISAI), 11–15. IEEE, 2024. http://dx.doi.org/10.1109/isai63299.2024.00012.

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Yun, Hanxu. "Multi-Agents on a Muti-Layer Network A MADDPG-Based Method". In 2024 6th International Conference on Communications, Information System and Computer Engineering (CISCE), 1456–59. IEEE, 2024. http://dx.doi.org/10.1109/cisce62493.2024.10653107.

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Zhao, Liang, Zihang Gao, Ammar Hawbani, Wei Zhao, Chaojin Mao e Na Lin. "Fuzzy-MADDPG based Multi-UAV Cooperative Search in Network-limited Environments". In 2024 International Conference on Information and Communication Technologies for Disaster Management (ICT-DM), 1–7. IEEE, 2024. https://doi.org/10.1109/ict-dm62768.2024.10798954.

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Tilahun, Fitsum Debebe, e Chung G. Kang. "Dynamic Resource Allocation in Cell-Free MEC: Leveraging Attention Mechanism with MADDPG". In 2024 IEEE 29th Asia Pacific Conference on Communications (APCC), 315–18. IEEE, 2024. https://doi.org/10.1109/apcc62576.2024.10768069.

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Xu, Junwei, e Chunhui Liu. "Resource Allocation in Multi-UAV Communication Networks Using MADDPG Framework with Double Reward and Task Decomposition". In 2024 5th International Symposium on Computer Engineering and Intelligent Communications (ISCEIC), 371–76. IEEE, 2024. https://doi.org/10.1109/isceic63613.2024.10810184.

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Sailahari, Kakumani, Anjana A. Mahesh, Charul Rajput e B. Sundar Rajan. "Performance of Maddah-Ali-Niesen Scheme for Multi-Access Coded Caching Over Noisy Channels". In 2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 1–7. IEEE, 2023. http://dx.doi.org/10.1109/pimrc56721.2023.10643138.

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Sodiq, Mochamad, Prasojo Satrio, Endang Mannan e Muhammad Nurpratama. "Utilization Mading (Wall Magazine) in the Faculty of Social and Political Sciences, University of Airlangga". In 3rd International Conference on Record and Library, 203–8. SCITEPRESS - Science and Technology Publications, 2018. http://dx.doi.org/10.5220/0008669200002300.

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Qi, Xiaoke, Hao Gu, Jiangyan Yi, Jianhua Tao, Yong Ren, Jiayi He e Siding Zeng. "MADD: A Multi-Lingual Multi-Speaker Audio Deepfake Detection Dataset". In 2024 IEEE 14th International Symposium on Chinese Spoken Language Processing (ISCSLP), 466–70. IEEE, 2024. https://doi.org/10.1109/iscslp63861.2024.10800535.

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Rapporti di organizzazioni sul tema "MADDPG"

Sperber, Kenneth, Duane Waliser, Eric Maloney, Matthew Wheeler, Daehyun Kim e Steve Woolnough. Legacy of the Madden-Julian Oscillation Working Group. Office of Scientific and Technical Information (OSTI), novembre 2018. http://dx.doi.org/10.2172/1490929.

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Long, Chuck. Atmospheric Radiation Measurement Madden-Julian Oscillation Investigation Experiment Field Campaign Report. Office of Scientific and Technical Information (OSTI), luglio 2016. http://dx.doi.org/10.2172/1302195.

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Houze, Robert A. Using AMIE data to study cloud processes within the Madden-Julian Oscillation. Office of Scientific and Technical Information (OSTI), dicembre 2015. http://dx.doi.org/10.2172/1229886.

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Ceylan, Mustafa. Toplumun Faizli Krediye Dair Değişen Algısı Hakkında Bir Mülakat Çalışması. İLKE İlim Kültür Eğitim Vakfı, marzo 2021. http://dx.doi.org/10.26414/ikm004.

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Faiz, en bilinen tabiri ile kiralanan paranın kira bedeli anlamındadır. İslam iktisadı, Bakara Suresi’nin 275 ayeti kerimesinde de bildirildiği üzere ticaretin helal, faizin (ribâ) haram kılınması düsturu ile hareket etmektedir. Bu çalışmanın amacı, yukarıda bahsedilen faizin haramlığı düsturu da temel alınarak, günümüz kapitalist sisteminde kilit rol oynayan faizin, bireylerin bakış açılarında nasıl bir yer edindiğini araştırmak için yapılmıştır. İslam iktisadının ilkelerini yerine getirmeye çalışılarak oluşturulan kurumların, toplum tarafından nasıl değerlendirildiği de öğrenilmiş olunacaktır. Çalışma boyunca nitel araştırma yöntemi kullanılmıştır. Nitel araştırmada veri toplamak için mülakat yöntemi tercih edilmiştir. Mülakata katılan kişi sayısı 23 kişi olarak belirlenmiştir. Temel bulgulara göre, mülakatlara katılan bireylerin çoğu çevreden borç istemeden bankalara gitmektedir. Toplumsal ilişkilerin, maddi konularda yeterince kapsayıcı olmadığı göze çarpmaktadır. Bununla birlikte bireyler kendi yuvalarını kurmak için yuvadan ayrıldıkları zaman kendi ailelerine karşı “el(yabancı)” statüsüne geçmektedirler. Araştırmamız için görüştüğümüz bireylerden, ihtiyacı olan maddi miktarı bulmanın yollarından biri olan alternatif kurumları bilen birey sayısının az olduğu tespit edilmiştir. Tekrar faizli kredi çekmeyi düşünen bireylerin bu kararlarındaki en önemli etken “hayallerini ertelememek üzerine kurulu bir dünya görüşüne” sahip olmalarıdır.

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Long, C., A. Del Genio, W. Gustafson, R. Houze, C. Jakob, M. Jensen, S. Klein et al. AMIE (ARM MJO Investigation Experiment): Observations of the Madden-Julian Oscillation for Modeling Studies Science Plan. Office of Scientific and Technical Information (OSTI), marzo 2010. http://dx.doi.org/10.2172/973805.

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Munter, J. A. A preliminary evaluation of static water level declines in wells in the Maddux Park Subdivision, Anchorage, Alaska. Alaska Division of Geological & Geophysical Surveys, 1989. http://dx.doi.org/10.14509/1424.

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Brewer, William A. Analysis of Low Level Winds Measured by a Ship-Mounted, High Resolution Doppler Lidar during the Dynamics of the Madden Julian Oscillation (DYANMO) Experiment. Fort Belvoir, VA: Defense Technical Information Center, settembre 2012. http://dx.doi.org/10.21236/ada574048.

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Hrynick, Tabitha, e Santiago Ripoll. Evidence Review: Achieving COVID-19 Vaccine Equity in Ealing and North West London. Institute of Development Studies (IDS), novembre 2021. http://dx.doi.org/10.19088/sshap.2021.040.

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This review sets out key considerations for improving vaccine equity – as well as broader health equity – in the North West London (NWL) borough of Ealing. It foregrounds the political, economic and social dynamics which have perpetuated health inequalities during and prior to COVID-19, and how they have manifested to shape COVID-19 vaccine accessibility and uptake among different social groups. It also highlights how local actors have sought to address these inequalities. By bringing together data and insights from existing social science research and consultations with people involved in local COVID-19 vaccination efforts (in local authorities, the NHS and community groups), we point to ways local authorities and healthcare providers, in collaboration with local people and organisations, can support vaccine equity – and health equity more broadly – now, and into the future. Critical to this are further efforts to integrate sensitivity to context, sustain collaborative working, build trust and meaningfully engage citizens (especially vulnerable groups), and support a robust civil society. The review begins with summary key considerations for operational actors. This review was produced by SSHAP in collaboration with Ealing Council. It was authored by Tabitha Hrynick and Santiago Ripoll, and reviewed by Maddy Gupta-Wright, Ellen Schwartz, and Nikita Simpson. It is the responsibility of SSHAP

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Demir, Abdullah. Oku Okut Derneği Faaliyet Raporu-2021. Oku Okut Yayınları, febbraio 2022. http://dx.doi.org/10.55709/okuokutyayinlari.15.

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Öğrencilerin okuma becerilerini geliştirmek ve topluma okuma alışkanlığı kazandırmak amacıyla projeler üretmeyi ve bu alanda ücretsiz hizmet sunmayı görev edinen Oku Okut Derneği, 07 Aralık 2020 tarihinde Ankara’da kuruldu. Kanunlar çerçevesinde faaliyet gösteren bir sivil toplum kuruluşu olan Derneğimiz, toplum yararı için eğitim alanında sahip olduğu programlarla, okuma alışkanlığının artırılması amacıyla faaliyetler yürütmektedir. Oku Okut Derneği’nin misyonu; kendini, tarihini, kültürünü ve dünyayı bilme yolunda olan öğrencilerimize, bilimsel veriler ve uluslararası başarılı uygulama örnekleri perspektifinde okuma alışkanlığı kazandırmak ve bu alışkanlığın tüm toplumda yaygınlaşmasını sağlamaktır. Oku Okut Derneği’nin hedef kitlesi; öncelikle öğrencilerimiz, vatandaşlarımız ve yurt dışında yaşayan soydaşlarımızdır. Oku Okut Derneği’nin kapsama ve hizmet alanı; yapay zekâ ve çevrim içi teknolojik imkânlarla yakın planda Türkiye, gelecekte tüm dünyadır. Oku Okut Derneği’nin vizyonu; okuma alışkanlığı kazandırmada ve kitap okumayı desteklemede Türkiye’nin KIZILAY’ı olmaktır. Oku Okut Derneği’nin amacı, öğrencilere “kitap okuma alışkanlığı” kazandırmak ve bu alışkanlığı toplumda yaygınlaştırmak amacıyla kapsamlı akademik araştırmalar yaparak her durum için özel “okuma projeleri” üretmektir. Yürütülecek projelerle eğitim-öğretimin her kademesindeki öğrenciler için kitaplarla buluşma imkânları oluşturulacaktır. Okuma-anlama becerilerinin geliştirilmesi için her okuyucuya yapay zekâ ve eğitim danışmanları aracılığıyla rehberlik hizmeti verilecektir. Ayrıca alanında uzman öğretim üyelerinin danışmanlığında ilkokul, ortaokul, lise, lisans, yüksek lisans ve doktora öğrencilerine yönelik çevrim içi okuma kulüpleri oluşturularak öğrencilerin yazarlarla buluşması sağlanacaktır. Proje kapsamında gayretli ve başarılı olan öğrencilerin ödüllendirilmesi; maddi imkânı kısıtlı olan ilkokul, ortaokul ve lise öğrencilerine yönelik ücretsiz çevrim içi canlı destek kurslarının düzenlenmesi de hedeflenmektedir. Oku Okut Derneği’nin projelerine ve sunduğu hizmetlere katılım tamamen ücretsizdir ve www.okuokut.org adresinden kayıtla gerçekleşmektedir. Oku Okut Akademi, 27 Mart 2021 tarihinde Oku Okut Derneği tarafından kurulmuş online akademik eğitim platformudur. Oku Okut Akademi, uzaktan eğitimin getirdiği teknolojik imkanlarla Oku Okut Derneği tarafından yürütülen bir uzaktan eğitim projesidir. Oku Okut Akademi: Online Akademik Eğitim Platformu Projesi'nde tüm seviyelerdeki öğreciler ile çeşitli sebeplerden dolayı eğitimini tamamlayamamış vatandaşlarımızın desteklenmesi, katılımcılara uzaktan eğitim teknolojisi ile öğretmen ve materyal desteği sağlanması öngörülmektedir. Projeyle; ihtiyaç duyduğu bilgiyi arayan öğrencilerin ve dezavantajlı grupların desteklenmesi ve kendini geliştirmek isteyen bireylere imkân sağlanması amaçlanmaktadır. Oku Okut Akademi'nin hedefi, bireylerde oluşan deneyim ve uzmanlık bilgilerinin diğer bireylere ücretsiz olarak aktarılabilmesine imkân sağlayacak dijital eğitim platformunun hayata geçirilmesidir. Tüm bireyler; “öğrenen” veya “öğreten” olarak projede yer alabilmektedir. Oku Okut Akademi; içerisinde uzaktan eğitim (LMS) ve canlı yayın sistemleri, video, doküman ve haber portalları gibi bilgi üretim ve aktarım teknolojilerini içeren güçlü bir altyapıyı ile tüm katılımcılara ücretsiz olarak hizmet sunmaktadır.

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Tic Disorders and Tourette Syndrome: Exploring the INTEND Project. ACAMH, aprile 2024. http://dx.doi.org/10.13056/acamh.26823.

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Abstract (sommario):

In this In Conversation podcast, Dr. Seonaid Anderson is joined by Dr. Maddie Groom to discuss a current research project focusing on Tics and Tourette Syndrome called INTEND. INTEND stands for ImproviNg Tic Services in EnglaND.

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