A Dominant Input Stream for LUD Incremental Computing on a Contention Network

2007 ◽  
pp. 403-414
Author(s):  
Cho-Chin Lin
Keyword(s):  
Input Stream

OPTIMIZATION OF MARKOV SYSTEMS OF QUEUEING WITH WAITING TIME IN THE MATLAB SYSTEM

2017 ◽  
pp. 39-47
Author(s):  
Viktor Afonin ◽  
Vladimir Valer'evich Nikulin
Keyword(s):  
Queueing System ◽  
Queueing Systems ◽  
Random Variable ◽  
Model Systems ◽  
Queuing Systems ◽  
Input Flow ◽  
Continuous Random Variable ◽  
Input Stream ◽  
Time Intervals ◽  
Markov Systems

The article focuses on attempt to optimize two well-known Markov systems of queueing: a multichannel queueing system with finite storage, and a multichannel queueing system with limited queue time. In the Markov queuing systems, the intensity of the input stream of requests (requirements, calls, customers, demands) is subject to the Poisson law of the probability distribution of the number of applications in the stream; the intensity of service, as well as the intensity of leaving the application queue is subject to exponential distribution. In a Poisson flow, the time intervals between requirements are subject to the exponential law of a continuous random variable. In the context of Markov queueing systems, there have been obtained significant results, which are expressed in the form of analytical dependencies. These dependencies are used for setting up and numerical solution of the problem stated. The probability of failure in service is taken as a task function; it should be minimized and depends on the intensity of input flow of requests, on the intensity of service, and on the intensity of requests leaving the queue. This, in turn, allows to calculate the maximum relative throughput of a given queuing system. The mentioned algorithm was realized in MATLAB system. The results obtained in the form of descriptive algorithms can be used for testing queueing model systems during peak (unchanged) loads.

scholarly journals Optimal Estimation of Mass Partition in a Centrifugal Separator by Metallurgical Balance

2016 ◽  
Vol 4 (1) ◽  
pp. 7
Author(s):  
Siney Viana
Keyword(s):  
Fine Particles ◽  
Least Squares Method ◽  
Optimal Estimation ◽  
Separation Process ◽  
Centrifugal Separator ◽  
Input Stream ◽  
Processing Plants ◽  
Chemical Content ◽  
Chemical Segregation ◽  
To Receive

Mineral processing plants make use of several types of equipments for size separation (size classification) to segregate ore particles by size. A particular type of such equipments is the centrifugal separator, which is intended to receive an input stream of ore slurry to be partitioned into two output streams: a coarse and a fines one. The coarse stream contains most of the coarse solids particles of the slurry, whereas the fines stream contains most of the fine particles. Although a centrifugal separator intends to perform a physical segregation of the solids particles by their size, a chemical segregation also results, in such a way that the chemical content of the coarse and the fines streams are normally different from the content of the input stream. When evaluating the performance of the separation process, three fundamental aspects should be analyzed: 1) the size distribution of the solids particles in each stream; 2) the amount of solids mass from the input stream that goes to the coarse stream and to the fines stream, that is, the mass partition; and 3) the chemical content of each stream. This work presents the application of the Least Squares method of optimization to calculate the mass partition, based on the measured chemical content of the streams, and on the metallurgical balance equations of the separation process.

RECOGNITION OF PERSIAN ONLINE HANDWRITING USING ELASTIC FUZZY PATTERN RECOGNITION

2007 ◽  
Vol 21 (03) ◽  
pp. 491-513 ◽  
Author(s):  
RAMIN HALAVATI ◽  
SAEED BAGHERI SHOURAKI
Keyword(s):  
Linguistic Terms ◽  
Input Stream ◽  
Cursive Handwriting ◽  
Novel Approach ◽  
Wide Range ◽  
Fuzzy Pattern ◽  
School Books ◽  
Fuzzy Linguistic ◽  
Online Handwriting ◽  
Different Parts

Persian is a fully cursive handwriting in which each character may take different forms in different parts of the word, characters overlap and there is a wide range of possible styles. These complexities make automatic recognition of Persian a very hard task. This paper presents a novel approach on recognition of such writings systems which is based on the description of input stream by a sequence of fuzzy linguistic terms; representation of character patterns with the same descriptive language; and comparison of inputs with character patterns using a novel elastic pattern matching approach. As there is no general benchmark for recognition of Persian handwriting, the approach has been tested on the set of words in first primary Iranian school books including 1250 words resulting in 78% correct recognition without dictionary and 96% with dictionary.

The single-server queue with independent GI/G and M/G input streams

1987 ◽  
Vol 19 (1) ◽  
pp. 266-286 ◽  
Author(s):  
Teunis J. Ott
Keyword(s):  
Distribution Function ◽  
Numerical Analysis ◽  
Real Time ◽  
Queueing System ◽  
Single Server ◽  
Equivalent System ◽  
Single Server Queue ◽  
Input Stream ◽  
Server Queue ◽  
Single Input

This paper studies the single-server queueing system with two independent input streams: a GI/G and an M/G stream. A new proof is given of an old result which shows how this system can be transformed into an equivalent ‘single input stream’ GI/G/1 queue, and methods to study that equivalent system numerically are given. As part of the numerical analysis, algorithms are given to compute the moments and the distribution function of busy periods in the M/G/1 queue, and of other related busy periods. Special attention is given to the single-server queue with independent D/G and M/G input streams.This work is to be used in the modeling of real-time computer systems, which can often be described as a single-server queueing system with independent D/G and M/G input streams, see for example Ott (1984b).

A Nonlinear Hebbian Network that Learns to Detect Disparity in Random-Dot Stereograms

1996 ◽  
Vol 8 (3) ◽  
pp. 545-566 ◽  
Author(s):  
Christopher W. Lee ◽  
Bruno A. Olshausen
Keyword(s):  
Hebbian Learning ◽  
Learning Rule ◽  
Coincidence Detection ◽  
Input Stream ◽  
Hebbian Learning Rule ◽  
Pairwise Correlations ◽  
Input Layer ◽  
Random Dot Stereograms ◽  
Rule Analysis ◽  
Shed Light

An intrinsic limitation of linear, Hebbian networks is that they are capable of learning only from the linear pairwise correlations within an input stream. To explore what higher forms of structure could be learned with a nonlinear Hebbian network, we constructed a model network containing a simple form of nonlinearity and we applied it to the problem of learning to detect the disparities present in random-dot stereograms. The network consists of three layers, with nonlinear sigmoidal activation functions in the second-layer units. The nonlinearities allow the second layer to transform the pixel-based representation in the input layer into a new representation based on coupled pairs of left-right inputs. The third layer of the network then clusters patterns occurring on the second-layer outputs according to their disparity via a standard competitive learning rule. Analysis of the network dynamics shows that the second-layer units' nonlinearities interact with the Hebbian learning rule to expand the region over which pairs of left-right inputs are stable. The learning rule is neurobiologically inspired and plausible, and the model may shed light on how the nervous system learns to use coincidence detection in general.

scholarly journals Prognosis of severe cytomegalovirus infection in newborns

2021 ◽  
Vol 11 (4) ◽  
pp. 745-751
Author(s):  
L. V. Kravchenko
Keyword(s):  
B Lymphocytes ◽  
Cytomegalovirus Infection ◽  
Severe Form ◽  
T And B Lymphocytes ◽  
T Helper ◽  
Input Stream ◽  
Intercellular Interaction ◽  
Activation Markers ◽  
Systems Of Inequalities ◽  
Consistent Application

Objective is to study the features of impaired activation of T and B lymphocytes in order to predicting severe cytomegalovirus infection in newborns. Materials and methods. 133 newborns with cytomegalovirus infection were examined. Immediately after diagnosing cytomegalovirus infection, all patients observed were immunologically ex amined, including assessing count of peripheral blood T and B lymphocytes, as well as their intercellular interaction by using flow cytometry immunostaining for CD3, CD3+CD28–, CD3+CD28+, CD3–CD28+, CD4, CD8, CD20, CD20+CD40+, CD28, CD40. The test was performed by using a Beckman Coulter Epics XL laser flow cytofluorometer. Depending on the condition severity, all children were divided into two groups: 1 — cytomegalovirus infection, severe form — 60 subjects (45.1%); 2 — cytomegalovirus infection, moderate form — 73 subjects (54.9%). Results of the entire set of studied indicators for cellular and humoral arms of immune system revealed statistically significant differences for the prognosis of severe cytomegalovirus infection: CD3+CD28–, CD20, CD20+CD40+, CD4. T lymphocytes with CD3+CD28+ activation markers, through which costimulating signals necessary for the activation of T helper cells are exerted cell-intrinsic features, serving as an important factor ensuring immune response. Using the “classification trees” method, we developed a differentiated approach to forecast severe cytomegalovirus infection in newborns. Systems of inequalities were obtained, four of which classify a subgroup of newborns with severe cytomegalovirus infection. The consistent application of the obtained inequalities makes it possible to isolate from the input stream of sick patients with a prognosis of the development of severe cytomegalovirus infection. The proposed diagnostic rules can be considered as screening markers for predicting a severe cytomegalovirus infection in newborns, which makes possible the timely onset of specific therapy.

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