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Modeling and Analysis of Resequencing Delay in Selective Repeat Automatic Repeat Request  [cached]
Jun Li,Yiqiang Q. Zhao
Journal of Networks , 2010, DOI: 10.4304/jnw.5.7.792-799
Abstract: In selective repeat automatic repeat request (SRARQ) used by a transmitter-receiver pair, data packets correctly received by the receiver need to be delivered to its upper-layer protocol in the same order as they arrived at the transmitter from its upper-layer protocol. In this paper, we propose a novel discrete-time priority queueing network to model SR-ARQ, and study the performance of the resequencing buffer in terms of the mean packet resequencing delay when packets arrive to the network according to a Bernoulli process. Based on the stationary probability distribution of an embedded Markov chain, we derive an explicit expression for the mean packet resequencing delay. Numerical and simulation results of the mean resequencing delay are presented and some performance trends are discussed. This paper presents an analytic framework for accurately computing the mean packet resequencing delay caused by packet retransmission in data communication networks. The proposed discretetime priority queueing network model is expected to be used for performance analysis of ARQ protocols with a more general packet arrival process.
A Hierarchical Link Scheme in Multi-Hop VANETs with Delay Analysis for Congestion Scenario  [PDF]
Yuanlin Yu, Demin Li, Guanglin Zhang, Xiaolu Zhang
Journal of Computer and Communications (JCC) , 2016, DOI: 10.4236/jcc.2016.48002
Abstract: Vehicular Ad-Hoc Networks (VANETs) as a part of intelligent transportation systems (ITS) are a new perspective to settle the traffic problem. Because of the high velocity, variational topology and such other characters, the link between VANETs and road side unit (RSU) is unstable. Besides, on account of the high cost of RSU, some places can’t be covered completely which make the Internet accessing difficult and accessing delay long. In this paper, we propose a hierarchical link scheme to help vehicles access the Internet based on delay analysis for congestion scenario. We select some moving accessing help points (AHPs) from vehicles in VANETs. Two different hierarchical schemes under the circumstances of whole road covered or not are proposed. When the RSUs are enough to cover the whole road fully, we propose the inward progressive hierarchical method. When the RSUs are not enough to cover the whole road, we propose the outward extend hierarchical method. According to the delay analysis, we can get the optimal hierarchy number. This hierarchical link scheme can decrease delay and make all vehicles access the Internet with delay guarantee. The simulation results indicate that our proposed hierarchical link scheme in VANETs can decrease the link delay effectively.
Automatic Hierarchical Color Image Classification  [cached]
Ramin Zabih,S. Ravi Kumar,Jing Huang
EURASIP Journal on Advances in Signal Processing , 2003, DOI: 10.1155/s1687617203211161
Abstract: Organizing images into semantic categories can be extremely useful for content-based image retrieval and image annotation. Grouping images into semantic classes is a difficult problem, however. Image classification attempts to solve this hard problem by using low-level image features. In this paper, we propose a method for hierarchical classification of images via supervised learning. This scheme relies on using a good low-level feature and subsequently performing feature-space reconfiguration using singular value decomposition to reduce noise and dimensionality. We use the training data to obtain a hierarchical classification tree that can be used to categorize new images. Our experimental results suggest that this scheme not only performs better than standard nearest-neighbor techniques, but also has both storage and computational advantages.
Michael Toolan, Progressione narrativa nel racconto: primi passi in una stilistica dei corpora Michael Toolan, Narrative progression in the short story: first steps in a corpus stylistic approach  [cached]
Federico Pianzola
Enthymema , 2010, DOI: 10.6092/2037-2426/579
Abstract: Using tools derived from corpus linguistics, Toolan proposes some principles and techniques for a stylistic analysis which aims at the detection of textual elements that are responsible for reader's expectations and narrative prospection. A specific attention is given to one of this elements: the use of free indirect discourse. He wants to develop some criteria that allow a selection based only on lexical and sintactical data, in order to apply automated methods of searching to wide text corpora and test his theoretical. Here is the original article. Servendosi di strumenti ricavati dalla linguistica dei corpora, Toolan propone una serie di principi e tecniche di analisi stilistica per individuare quegli elementi testuali che inducono il lettore a crearsi aspettative sull'avanzamento della narrazione. Particolare attenzione è riservata a uno di questi elementi: l'uso del discorso indiretto libero. L'intento è quello di ricorrere a criteri di selezione esclusivamente lessicali e sintattici, così da permettere una ricerca automatizzata su ampi corpora testuali per verificare le ipotesi teoriche avanzate.
Automatic Semantic Image Annotation with Granular Analysis Method
图像语义自动标注及其粒度分析方法

ZHANG Su-Lan,GUO Ping,ZHANG Ji-Fu,HU Li-Hua,
张素兰
,郭平,张继福,胡立华

自动化学报 , 2012,
Abstract: To bridge the semantic gap between low-level visual feature and high-level semantic concepts has been the subject of intensive investigation for years in order to improve the accuracy of automatic image annotation and satisfy the users' needs of quick image retrieval. Granular analysis is a hierarchical and important data analyzing method, which provides a new idea and method for solving the complicated problem. The accuracy of automatic image annotation and the efficiency of image retrieval are varying with the granularity size of image understanding and analysis. In this paper, the state-of-art models of automatic semantic image annotation are overviewed, then the idea and models of the granular analysis with its application in the process of automatic semantic image annotation are discussed, and the granular analysis based automatic image annotation methods are investigated as well as the promising research directions are given.
Study of Automatic Abstracting Based on Corpus and Hierarchical Dictionary
基于语料库与层次词典的自动文摘研究

SONG Jin,ZHAO Dong-yan,
宋今
,赵东岩

软件学报 , 2000,
Abstract: The study of automatic abstracting is a vital and practical information processing task in natural language processing,and becomes an important problem in domains such as Internet information retrieval.An approach based on corpus proposed by this paper provides an integration of the advantages of linguistic analysis based methods and those based on statistics.In essence,the basic idea of corpus-based method is at the expense of the cost of analysis outside the system to gain the efficiency of the algorithm inside the system.The algorithm given by the paper implements both keywording and abstracting while the former is based on a hierarchical dictionary and the latter on the corpus.
A hierarchical propelled fusion strategy for SAR automatic target recognition
Zongyong Cui, Zongjie Cao, Jianyu Yang and Jilan Feng
EURASIP Journal on Wireless Communications and Networking , 2013, DOI: 10.1186/1687-1499-2013-39
Abstract: Synthetic aperture radar (SAR) automatic target recognition (ATR) is playing a very important role in military and civil field. Much work has been done to improve the performance of SAR ATR systems. It is well-known that ensemble methods can be used for improving prediction performance. Thus recognition using multiple classifiers fusion (MCF) has become a research hotspot in SAR ATR. Most current researchers focus on the fusion methods by parallel structure. However, such parallel structure has some disadvantages, such as large time consumption, features attribution conflict and low capability on confuser recognition. A hierarchical propelled strategy for multi-classifier fusion (HPSMCF) is proposed in this paper. The proposed HPSMCF has the characters both of series and parallel structure. Features can be used more effective and the recognition efficiency can be improved by extracting features and fusing the probabilistic outputs in a hierarchical propelled way. Meanwhile, the confuser recognition can be achieved by setting thresholds for the confidence in each level. Experiments on MSTAR public data demonstrate that the proposed HPSMCF is robust for variant recognition conditions. Compared with the parallel structure, HPSMCF has better performance both on time consumption and recognition rate.
Study of Phonemes Confusions in Hierarchical Automatic Phoneme Recognition System  [PDF]
Rimah Amami,Noureddine Ellouze
Computer Science , 2015,
Abstract: In this paper, we have analyzed the impact of confusions on the robustness of phoneme recognitions system. The confusions are detected at the pronunciation and the confusions matrices of the phoneme recognizer. The confusions show that some similarities between phonemes at the pronunciation affect significantly the recognition rates. This paper proposes to understand those confusions in order to improve the performance of the phoneme recognition system by isolating the problematic phonemes. Confusion analysis leads to build a new hierarchical recognizer using new phoneme distribution and the information from the confusion matrices. This new hierarchical phoneme recognition system shows significant improvements of the recognition rates on TIMIT database.
Hierarchical analysis of acceptable use policies
P. A. Laughton
South African Journal of Information Management , 2010, DOI: 10.4102/sajim.v10i4.330
Abstract: Acceptable use policies (AUPs) are vital tools for organizations to protect themselves and their employees from misuse of computer facilities provided. A well structured, thorough AUP is essential for any organization. It is impossible for an effective AUP to deal with every clause and remain readable. For this reason, some sections of an AUP carry more weight than others, denoting importance. The methodology used to develop the hierarchical analysis is a literature review, where various sources were consulted. This hierarchical approach to AUP analysis attempts to highlight important sections and clauses dealt with in an AUP. The emphasis of the hierarchal analysis is to prioritize the objectives of an AUP.
Sensitivity analysis for Bayesian hierarchical models  [PDF]
Malgorzata Roos,Thiago G. Martins,Leonhard Held,Havard Rue
Statistics , 2013,
Abstract: Prior sensitivity examination plays an important role in applied Bayesian analyses. This is especially true for Bayesian hierarchical models, where interpretability of the parameters within deeper layers in the hierarchy becomes challenging. In addition, lack of information together with identifiability issues may imply that the prior distributions for such models have an undesired influence on the posterior inference. Despite its relevance, informal approaches to prior sensitivity analysis are currently used. They require repetitive re-runs of the model with ad-hoc modified base prior parameter values. Other formal approaches to prior sensitivity analysis suffer from a lack of popularity in practice, mainly due to their high computational cost and absence of software implementation. We propose a novel formal approach to prior sensitivity analysis which is fast and accurate. It quantifies sensitivity without the need for a model re-run. We develop a ready-to-use priorSens package in R for routine prior sensitivity investigation by R-INLA. Throughout a series of examples we show how our approach can be used to detect high prior sensitivities of some parameters as well as identifiability issues in possibly over-parametrized Bayesian hierarchical models.
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