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reliably serviced, the next request made by client vi is sheduled at time Tk Y , where Y has distribution di . Requests from individual clients are directed to servers randomly (independently and uniformly) over the set of servers. In unreliable communication, this causal requirement is waived. A 2-server, 32-client network con guration with a bottleneck link between gateways G1 and G2 is shown in Fig. 14.1. This network con guration is used for most of the experiments reported below. We will refer to the total traf c arriving at G2 from servers as upstream traf c and the traf c from G2 to G1 as downstream traf c. A le is completely determined by its size X and is split into dX =M e packets, where M is the maximum segment size (1 kB for the results shown in this chapter). The segments are routed through a packet-switched internetwork with packets being dropped at bottleneck nodes in case of buffer over ow. The dynamical model is given by all clients independently placing le transfer requests to servers, where each request is completely detemined by the le size.



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Does anyone have a sample of GOCR image processing from AutoIt please.​Basically grabbing a grey scale rectangle screen shot of a word in ...

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Java OCR (Optical Character Recognition) API - Aspose
Aspose. OCR for Java is a stand-alone OCR API for Java applications while allowing the developers to perform optical character recognition on commonly used ...

We have used the LBNL Network Simulator (ns) as our simulation environment [8] Ns is an event-driven simulator derived from S Keshav's REAL network simulator supporting several avors of TCP (in particular, the TCP Reno's congestion control features Slow Start, Congestion Avoidance, Fast Retransmit=Recovery) and router scheduling algorithms We have modi ed the distributed version of ns to model our interactive client=server environment This entailed, among other things, implementing our client=server nodes as separate application layer agents A UDP-based unreliable transport protocol was added to the existing protocol suite, and an aggressive opportunistic UDP agent was built to service le requests when using unreliable communication We also added a TCP Vegas module to complement the existing TCP Reno and Tahoe modules Our simulation results were obtained from several hundred runs of ns Each run executed for 10,000 simulated seconds, logging traf c at 10 millisecond granularity.





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Download net.sourceforge.tess4j JAR files with all dependencies
14 Jul 2019 ... tess4j from group net.sourceforge.tess4j (version 4.4.0). # Tess4J ## Description: A Java JNA wrapper for Tesseract OCR API. Tess4J is ...

The result in each case is a time series of one million data points; using such extremely long series increases the reliability of statistical measurements of selfsimilarity Although most of the runs reported here were done with a 2-server=32client bottleneck con guration (Fig 141), other con gurations were tested including performance runs with the number of clients varying from 1 to 132 The bottleneck link was varied from 15 Mb=s up to OC-3 levels, and buffer sizes were varied in the range of 1 128 kB Non-bottleneck links were set at 10 Mb=s and the latency of each link was set to 15 ms The maximum segment size was xed at 1 kB for the runs reported here.

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Google Cloud Vision With Spring Boot - DZone Integration
3 Jul 2019 ... A good reference for samples is the Spring Cloud GCP Vision API Sample. The Java source code and the Python source code used in this post, ...

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The inclusion of communication contention in task scheduling yields more accurate and more ef cient schedules compared with those produced under the classic model Yet, the experimental results referenced in Section 754 suggest that even the contention model does not represent a parallel system accurately enough An examination of the results (Sinnen and Sousa [172, 176]) reveals a clear relation between the increase of communication (CCR) and the decrease of accuracy of the produced schedules A possible explanation is that the contention model is still unrealistic regarding communication In the prelude of the previous chapter, three very idealizing assumptions of the classic model (De nition 43) were queried Two of them the assumption of contention-free communication (Property 5) and the assumption of a fully connected network (Property 6) have already been addressed in 7 Property 4, which supposes a dedicated communication subsystem to be present in the target system, is examined in this chapter With the assumed subsystem, computation can overlap with communication, because the processor is not involved in communication However, many parallel systems do not possess such a subsystem (Culler and Singh [48]) Therefore, in many systems the processors are involved, in one way or another, in interprocessor communication Furthermore, involvement of the processor also serializes communication, even if the network interfaces are capable of performing multiple message transfers at the same time, since a processor can only handle one communication at a time For example, a processor can usually only perform one memory copy at a time Thus, considering the processors involvement in task scheduling is of importance as it serializes the communication and, more importantly, prevents the overlap of computation and communication In fact, the involvement of the processors in communication is an aspect that has been considered before The LogP model (Section 213) dedicates the parameter o to describe the computational overhead in icted on a processor for each communication Per de nition of the model, the processor cannot execute other operations while occupied with this overhead Furthermore, the system model used by Sarkar [167],.

For any reasonable assignment to bandwidth, buffer size, mean le request size, and other system parameters, it was found that by adjusting either the number of clients or the mean of the idle time distribution di appropriately, any intended level of network contention could be achieved..

14.4 14.4.1

An important characteristic of our proposed mechanism for traf c self-similarity is that the sizes of les being transferred are drawn from a heavy-tailed distribution. A distribution is heavy tailed if P X > x $ x a as x 3 I;

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net.sourceforge.tess4j - Maven Repository
Tess4J ## Description: A Java JNA wrapper for Tesseract OCR API. Tess4J is released and distributed under the Apache License, v2.0. ## Features: The library ...

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