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Introduces the concept of classification and its various classifications. The article elaborates on the process of classification. The specific uses of library classification are narrated.
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The paper provides a mathematical model of grain classification processes targeted at prognostication of grain size distribution on the basis of grain distribution in the feed. Predicted (theoretical) values of the cut size and se...
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The paper provides a mathematical model of grain classification processes targeted at prognostication of grain size distribution on the basis of grain distribution in the feed. Predicted (theoretical) values of the cut size and separation sharpness indices (imperfection and coefficients k_1 and k_2 are presented. Results of grain size classification in a coal suspension in a single lamella unit are duly compiled. Measurement results are compared with predicted values. The mathematical description of the grain size distribution in the feed and final product uses Weibull's distribution (Rosin-Rammler-Bennett's distribution) as a singular case of the generalised gamma distribution. Grain sizes obtained experimentally are compared with predicted values. The experimental grade efficiency curves are approximated with several functions. The cut sizes are derived form curves approximating the experimental data set. On that basis experimental cut sizes are obtained and then compared with predicted values. Distribution functions of grain size in classification products prognosticated on the basis of size distribution in the feed agree pretty well with the values obtained from mathematical modelling. The comparison of predicted and experimental values lead us to the conclusion that cut size obtained in experimental classification processes was nearly two times bigger than the predicted value. Separation sharpness indices obtained experimentally are similar to predicted va1ues. In conclusion, the results of experimental verification of the developed model are regarded as satisfactory. The mathematical model of classification processes in lamella settling tanks agrees sufficiently well with experimental results. While compared to other classification apparatuses (centrifugal separators, hydrocyclones), the lamella tank seems to provide for better Separation sharpness.
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Intelligent classification system for complex structured images designed to highlight the image of a given segment class. It belongs to the training systems of classification. The development urgency of complex structured image cl...
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Intelligent classification system for complex structured images designed to highlight the image of a given segment class. It belongs to the training systems of classification. The development urgency of complex structured image classification in intelligent systems occurs in the processing of images from cameras UAV used for navigational purposes in the absence of an artificial earth satellite or the analysis of images in real time by the operator. In this case, there are high demands not only for the quality classification of objects in images, but also to speed identification and classification of the investigated image segments. The contradiction between the effectiveness (classification accuracy) and computing resources offered solved by a distributed computing system (network). The method is built on the idea of hybrid trekking to data processing and aggregation of ?weak? classification algorithms in the ?strong? algorithms.
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The fully automated generation of diagnostic codes requires a knowledge-based system which is capable of interpreting noun phrases. The sense content of the words must be analysed and represented for this purpose. The codes are th...
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The fully automated generation of diagnostic codes requires a knowledge-based system which is capable of interpreting noun phrases. The sense content of the words must be analysed and represented for this purpose. The codes are then generated based on this representation. In comparison with other knowledge-based systems, a system of this kind places the emphasis on the data structures and not on the calculus; coding itself is a simple matter compared to the much more difficult task of incorporating the complex information contained in the words used in natural language in a systematic data model. Initial attempts were based on the assumption that each word was linked to one conceptual meaning, whereas such a naive viewpoint certainly no longer applies today. The notation of concepts and their relations is the task at hand. Existing notation methods include predicate logic, conceptual graphs (CGs) as proposed by J. F. Sowa, GRAIL as used by the GALEN Project and methods developed as part of the WWW consortium, e.g. RDF's (Resource Description Frameworks). For the purpose of coding, we developed a notation system using "concept particles" back in 1989. In 1996, the resulting experience led us to represent "concept molecules" (CM), with which both complex data structures and multi-branched rules can be denoted in a simple manner. In this paper we shall explain the principles behind this notation and compare it with another modern concept representation system, conceptual graphs.
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The classification of retraction of the tympanic membrane and the ateleetasis of the middle ear is of considerable importance, but before a major change to the classification system of a common pathology is introduced, the purpose...
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The classification of retraction of the tympanic membrane and the ateleetasis of the middle ear is of considerable importance, but before a major change to the classification system of a common pathology is introduced, the purpose of classification of pathology of the tympanic membrane should be brought into focus.Recording the condition of a tympanic membrane can be accomplished in many ways, including by means of digital photography, diagrams, verbal descriptions, and, of course, classification. Diagrams have been shown to be very unreliable for this purpose, and it would appear that digital photographs are very reliable indeed.1 Commonly used classifications are somewhat less reliable, as a result of both their poor interrater and intrarater reliability.
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Part Of Speech (POS) tagging forms the important preprocessing step in many of the natural language processing applications such as text summarization, question answering and information retrieval system. It is the process of clas...
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Part Of Speech (POS) tagging forms the important preprocessing step in many of the natural language processing applications such as text summarization, question answering and information retrieval system. It is the process of classifying every word in a given context to its appropriate part of speech. Different POS tagging techniques in the literature have been developed and experimented. Currently, it is well known that some POS tagging models are not performing well on the Quranic Arabic due to the complexity of the Quranic Arabic text. This complexity presents several challenges for POS tagging such as high ambiguity, data sparseness and large existence of unknown words. With this in mind, the main problem here is to find out how existing and efficient methods perform in Arabic and how can Quranic corpus be utilized to produce an efficient framework for Arabic POS tagging. We propose a classifiers combination experimental framework for Arabic POS tagger, by selecting two best diverse probabilistic classifiers used in numerous works in non-Arabic language; namely K-Nearest Neighbour (KNN) and Naive Bayes (NB). The Majority voting is used here as the combination strategy to exploit classifiers advantages. In addition, an in-depth study has been conducted on a large list of features for exploiting effective features and investigating their role in enhancing the performance of POS taggers for the Quranic Arabic. Hence, this study aims to efficiently integrate different feature sets and tagging algorithms to synthesize more accurate POS tagging procedure. The data used in this study is the Arabic Quranic Corpus, an annotated linguistic resource consisting of 77,430 words with Arabic grammar, syntax and morphology for each word in the Holy Quran. The highest accuracy in the results achieved is 98.32%, which can be a significant enhancement for the state-of-the-art for Arabic Quranic text. The most effective features that yield this accuracy are a combination of w_0 (the current word), p_0 (POS of the current word), p_(-3) (POS of three words before), p_(-2) (POS of two words before) and p_(-1) (POS of the word before).
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In this paper, we classify by representativeness the elements of a set of complete genomic sequences of Dengue Virus Type 1 (DENV-1), corresponding to the outbreak in Japan during 2014. The set is coming from four regions: Chiba, ...
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In this paper, we classify by representativeness the elements of a set of complete genomic sequences of Dengue Virus Type 1 (DENV-1), corresponding to the outbreak in Japan during 2014. The set is coming from four regions: Chiba, Hyogo, Shizuoka and Tokyo. We consider this set as composed of independent samples coming from Markovian processes of finite order and finite alphabet. Under the assumption of the existence of a law that prevails in at least 50% of the samples of the set, we identify the sequences governed by the predominant law (see [1,?2]). The rule of classification is based on a local metric between samples, which tends to zero when we compare sequences of identical law and tends to infinity when comparing sequences with different laws. We found that the order of representativeness, from highest to lowest and according to the origin of the sequences is: Tokyo, Chiba, Hyogo, and Shizuoka. When comparing the Japanese sequences with their contemporaries from Asia, we find that the less representative sequence (from Shizuoka) is positioned in groups considerably far away from that which includes the sequences from the other regions in Japan, this offers evidence to suppose that the outbreak in Japan could be produced by more than one type of DENV-1.
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An international consultation on the diagnosis of non-invasive urothelial neoplasms was held in Ancona, Italy in May 2001. Besides histology and problems of classification, one group of experts (Committee no. 3) discussed the mole...
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An international consultation on the diagnosis of non-invasive urothelial neoplasms was held in Ancona, Italy in May 2001. Besides histology and problems of classification, one group of experts (Committee no. 3) discussed the molecular pathology and cytometry of non-invasive urothelial carcinomas. In the following first part, special immunohistochemical and molecular markers for stratifications in bladder cancer were discussed including different cytokeratins (clone 34betaE12, CK 20), cell proliferation markers (Ki67/MIB-1, PCNA, AgNOR, DNA-cytometry), tumor suppressor genes and oncogenes (p53, p21, erb-B2, bcl-2), different receptor expressions of epidermal growth factor and vascular endothelial growth factor and others. These molecular markers were analyzed in diagnosis of urothelial carcinomas, recurrences, progression and response to treatment.
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In lamella classification processes statistical grain size distributions is the final products of the classification processes are determined on the basis of grain size distribution in the feed material. Computed grain size distri...
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In lamella classification processes statistical grain size distributions is the final products of the classification processes are determined on the basis of grain size distribution in the feed material. Computed grain size distributions in the fine product in overflow and the coarse-grained product in underflow depend on the employed statistical distribution pattern. Grain size distributions in the feed materials are mostly unimodal distributions covering the interval (0, infinity). Two most widely applied distribution patterns are the log-normal distribution and RRB (Rosin-Rammler-Bennett distribution). The main aim of the present study is to compare the results of approximation of grain size distribution in lamella classification processes. Grain size distribution in the feed is approximated with the log-normal and RRB distribution patterns; on that basis grain size distributions in the products of lamella classification are obtained. The paper provides the comparison between the two distribution patterns employed in approximation: the long-normal and RRB distributions. The log-normal distribution function was computed for the predetermined parameters m and sigma and thus obtained data were approximated with the RRB distribution. Subsequently, the parameters d0 and n were found. The correlation coefficient and F-Fisher statistics were the tools employed to evaluate the goodness of fit. Rosin-Rammler-Bennett distributions were next used to generate distribution functions which, in turn, were approximated with the log-normal distribution. The results of approximation of grain size distributions in the final products of the lamella classification processes are presented and discussed. There was admitted, that when the feed grain size composition displays little scatter (low values of standard deviation sigma in log-normal distribution or high values of shape parameter n in the RRB distribution), the differences in the value of distribution functions might be even as high as 0.2.
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The paper contains several new transparent proofs of criteria appearing in classification of birth and death processes (BDPs). They are almost purely probabilistic and differ from the classical techniques of three-term recurrence ...
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The paper contains several new transparent proofs of criteria appearing in classification of birth and death processes (BDPs). They are almost purely probabilistic and differ from the classical techniques of three-term recurrence relations, continued fractions and orthogonal polynomials. Let ${T^\infty }$ be the passage time from zero to $\infty$. The regularity criterion says that ${T^\infty } < \infty$ if and only if $\mathbb {E}{T^\infty } < \infty$. It is heavily based on a result of Gong, Y., Mao, Y.-H. and Zhang, C. [J. Theoret. Probab. 25 (2012), no. 4, 950–980]. We obtain the latter expectation by using a two-term recurrence relation. We observe that the recurrence criterion is an immediate consequence of the well-known recurrence criterion for discrete-time BDPs and a result of Chung K. L. [Markov Chains with Stationary Transition Probabilities, Springer-Verlag, New York (1967)]. We obtain the classical criterion of positive recurrence using technique of the common probability space. While doing so, we construct a monotone sequence of BDPs with finite state spaces converging to BDPs with an infinite state space.
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