19,829 research outputs found
Phoneys and the dash man: the hypnotic voice of J. D. Salinger
No full textSalinger called himself 'a dash man', quintessentially a short story writer, but I'm not so sure about that. The Catcher in the Rye is an overblown short story, but the Glass family saga is something else. The dash is a breathless narrative momentum that keeps finding sources of
renewal
Miradeltaphus Dash & Viraktamath 1995
No full textMiradeltaphus Dash & Viraktamath Miradeltaphus Dash & Viraktamath, 1995a: 38–39. Type species: M. mirabilis Dash & Viraktamath, by original designation.Published as part of Webb, Michael D. & Viraktamath, Chandra A., 2009, 2163, pp. 1-64 in Zootaxa 2163 on page
D-DASH: a Deep Q-learning Framework for DASH Video Streaming
No full textThe ever-increasing demand for seamless high-definition video streaming, along with the widespread adoption of the Dynamic Adaptive Streaming over HTTP (DASH) standard, has been a major driver of the large amount of research on bitrate adaptation algorithms. The complexity and variability of the video content and of the mobile wireless channel make this an ideal application for learning approaches. Here, we present D-DASH, a framework that combines Deep Learning and Reinforcement Learning techniques to optimize the Quality of Experience (QoE) of DASH. Different learning architectures are proposed and assessed, combining feed-forward and recurrent deep neural networks with advanced strategies. D-DASH designs are thoroughly evaluated against prominent algorithms from the state-of-the-art, both heuristic and learning-based, evaluating performance indicators such as image quality across video segments and freezing/rebuffering events. Our numerical results are obtained on real and simulated channel traces and show the superiority of D-DASH in nearly all the considered quality metrics. Besides yielding a considerably higher QoE, the D-DASH framework exhibits faster convergence to the rate-selection strategy than the other learning algorithms considered in the study. This makes it possible to shorten the training phase, making D-DASH a good candidate for client-side runtime learning
Deltocephalus vulgaris Dash & Viraktamath.
No full textDeltocephalus vulgaris Dash & Viraktamath. Deltocephalus vulgaris Dash & Viraktamath, 1998: 4, figs 1–11, India. Remarks. There are two forms of the aedeagus in this species as currently recognised (see figs by Dash & Viraktamath, 1998). What appears to be the same species was also recorded (from Japan?) by Kamitani (1999, figs 22–29).Published as part of Webb, Michael D. & Viraktamath, Chandra A., 2009, 2163, pp. 1-64 in Zootaxa 2163 on page 1
dash
No full textdash nGirls often held their "copyhouses", "cobyhouses" (i.e., playhouses) in the rocks just above the dash of the sea.W.J. KIRWIN MAR 1973JH MAR 1973not usedNot usedWithdraw
Distributed Mechanisms for Multi-Agent Systems: Analysis and Design
No full textThere is an increasing need for multi-agent systems to operate under decentralised control regimes that support openness (individual components can enter and leave at will) and enable components representing distinct stakeholders with different aims and objectives to interact effectively. To this end, this thesis explores issues associated with using techniques from Game Theory and Mechanism Design to organise and analyse such systems. In particular, emphasis is given to distributed mechanisms in which there is distributed allocation (no single centre determines the allocation of the resources or the tasks) and distributed information (agents require information privately known by other agents in order to determine their own valuation or cost). Such mechanisms are important because, in comparison to their centralised counterparts, they are robust to a single-point failure, the computational burden can be potentially shared amongst many agents, and there is a reduction in bottlenecks since not all communication need pass through a single point. As a result, distributed mechanisms are better suited to many types of multi-agent application. To provide a grounding for the mechanisms we develop, the thesis contains a running example of a multi-sensor network scenario. In these systems, distributed allocation mechanisms are desirable since they are robust and reduce bottlenecks in the communication system. Furthermore, we show that distributed information naturally arises by deriving an information-theoretic valuation function. This scenario also gives rise to two additional requirements that are addressed within this thesis: (i) constrained capacity, whereby suppliers can only provide a limited amount of goods or services at any given time and (ii) uncertainty in task completion, whereby sensors potentially fail after they have been assigned tasks. Specifically, we focus on the \ac{vcg} mechanisms and investigate ways of extending it so as to address the requirements that arise within distributed setting in general and sensor networks. In particular, we choose the VCG as our point of departure since it is a mechanism that is efficient, individually rational and incentive compatible. Unfortunately, it is brittle in the sense that it does not conserve these desirable properties when considering the requirements that we outlined above. Therefore, we develop novel mechanisms that do. In more detail, the first part of this thesis considers two distributed allocation mechanisms --- a simultaneous auction environment and \ac{cda}. In the former, bidders place sealed bids in a number of selling auctions which are concurrently offering items. This results in a distributed allocation whereby the winner at each auction is determined by the seller conducting it. For this case, we derive the optimal strategy of the bidders using a game-theoretic approach. In the \acs{cda}, buyers and sellers, respectively, submit bids and asks continuously and the market clears when a bid is higher than an ask; meaning that the allocation is again determined in a distributed way. Furthermore, CDAs are known to yield close to efficient allocations, under certain conditions, even when utilising very simple strategies. However, in our case, we need to modify their format in order to deal with the requirement of constrained capacity. In both of these mechanisms, we study the system's loss in efficiency that ensues from distributing the allocation and find that it is in the simultaneous auction case and upto in the continuous double auction case. The second part of this thesis is concerned with designing mechanisms when agents have distributed information within the system. Such settings are more general than those more traditionally studied in that they encompass the fact that agents can potentially change their valuation or cost upon knowing a signal about the system (which they have not observed) that was hitherto unknown to them. Specifically, we first show that interdependent valuations arise naturally within a sensor network when we develop an information-theoretic valuation function. To account for this, we significantly extend the VCG mechanism in order to deal with these interdependent valuations. We then go on to develop a mechanism that can deal with uncertainty in task allocation. In both of these cases, our mechanisms are shown to be efficient, individually rational and incentive compatible. Moreover, their computational properties are studied and efficient algorithms are designed (based on linear and dynamic programming) in order to speed up the computation of the allocation problem which is generally -hard
dash of sea
No full textdash of seaOED 4 and 4b pretty close dash of the oceanWithd? [check]not usedNot usedWithdrawnCheck mark through card
DASH
No full text-citat- D-A-S-H kommt von "dash" -- dem Gedankenstrich D-A-S-H wird gefördert im Rahmen des Aktionsprogramms "Jugend für Toleranz und Demokratie - gegen Rechtsextremismus, Fremdenfeindlichkeit und Antisemitismus". D-A-S-H wird durchgeführt mit der Unterstützung des Programms JUGEND der europäischen Gemeinschaft. D-A-S-H wird zusätzlich unterstützt von der Bundeszentrale für politische Bildung (BpB). Recherche - Archive: Zeitschriftenarchive, Datenbanken und Bibliotheken -/citat- Axel Diederic
Deep Reinforcement Learning for Edge-DASH-Based Dynamic Video Streaming
No full textDynamic Adaptive Streaming over HTTP (DASH) is a promising solution to enhance the Quality of Experience (QoE) of mobile video services. In this paper, we consider an Edge-DASH scenario where two problems of Bitrate Allocation (BrA) and user-to-server allocation (USA) have been jointly formulated. Then, we exploit Deep Reinforcement Learning (DRL) algorithm to solve the USA problem and select the streaming point for users, which can be streaming from the Edge, Macro layer or cloud, and deliver the users the most appropriate bitrate respecting the QoE by solving the BrA problem. In the simulation results, we have demonstrated that our Deep Deterministic Policy Gradient (DDPG) outperforms the traditional solution in terms of bitrate allocation
Scenario for DASH-WebM adaptive streaming transmission
No full textTradicionalmente el videostreaming ha sido soportado por los protocolos RTP y RTSP, de modo que el servidor gestiona una sesión diferente para cada cliente y coordina la entrega de paquetes. Actualmente el estándar de streaming adaptativo DASH ofrece otro enfoque a través de HTTP, de tal forma que el cliente extrae los datos del servidor, sin mantener el estado de la sesión. Así, se tiene como ventajas el pleno uso de la infraestructura de Internet y la adaptación del contenido multimedia al ancho de banda de la red. A pesar de lo anterior, el proceso de generación y distribución de contenidos multimedia DASH, requiere la ejecución secuencial de tareas de codificación, segmentación, creación del descriptor MPD y reproducción del contenido DASH. Para el caso de los contenidos multimedia WebM, las anteriores tareas son realizadas separadamente por un conjunto de herramientas libres, por lo que el proceso de generación del contenido DASH no es automático. En este artículo se propone un escenario de transmisión para streaming adaptativo DASH, cuyo principal componente es la herramienta DASHWebMConverter, la cual se encarga de automatizar el proceso de generación de contenidos DASH WebM. Adicionalmente, se presenta la evaluación del escenario de streaming adaptativo, mediante pruebas de seguimiento de ancho de banda y pruebas de consumo de memoria sobre los principales componentes del escenario.Traditionally, video streaming has been supported by the RTP and RTSP protocols, so that the server manages a different session for each client and coordinates packet delivery. Currently the DASH adaptive streaming standard offers another approach over HTTP, in such a way that the client pulls the data from the server, without maintaining session state. Thus, the advantages are full use of the Internet infrastructure and the adaptation of multimedia content to network bandwidth. Despite the above, the process of generating and distributing DASH multimedia content requires the sequential execution of encoding, segmentation, creation of the MPD descriptor and playback of the DASH content. In the case of WebM multimedia content, the above tasks are performed separately by a set of free tools, so the DASH content generation process is not automatic. This article proposes a transmission scenario for DASH adaptive streaming, whose main component is the DASHWebMConverter tool, which is responsible for automating the DASH content generation process WebM. Additionally, the evaluation of the adaptive streaming scenario is presented, through bandwidth monitoring tests and memory consumption tests on the main components of the scenario
- …
