Hierarchical system

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  • Creating institutions to meet the challenge of sustainability is arguably the most important task confronting society; it is also dauntingly complex. Ecological, economic, and social elements all play a role, but despite ongoing efforts, researchers have yet to succeed in integrating the various disciplines in a way that gives adequate representation to the insights of each.Panarchy, a term devised to describe evolving hierarchical systems with multiple interrelated elements, offers an important new framework for understanding and resolving this dilemma.

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  • A computer system consists of a processor, memory, I/O, and the interconnections among these major components. With the exception of the processor, which is suffi- ciently complex to devote Part Three to its study, Part Two examines each of these components in detail.

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  • This chapter examines a range of external memory devices and systems. We begin with the most important device, the magnetic disk. Magnetic disks are the foundation of ex- ternal memory on virtually all computer systems. The next section examines the use of disk arrays to achieve greater performance, looking specifically at the family of systems known as RAID (Redundant Array of Independent Disks).

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  • Domain Name System (DNS)is a hierarchical, distributed database that contains mappings of DNS domain names to various types of data, such as IP addressesDomain Name System (DNS)is a hierarchical, distributed database that contains mappings of DNS.InterNIC is responsible for delegating administrative responsibility for portions of the domain namespace and for registering domain names.

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  • Real-Time Systems are computing systems that must meet their temporal specification. In computer science, real-time or reactive computing is the study of hardware and software systems that are subject to a real-time constraint called deadline, which the system should respect it in its response to events. Real-time systems, in fact, must guarantee response within strict time constraints. Real-time systems often appear as critical systems such as mission critical ones.

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  • Modern complex dynamical systems1 are highly interconnected and mutually interdependent, both physically and through a multitude of information and communication network constraints. The sheer size (i.e., dimensionality) and complexity of these large-scale dynamical systems often necessitates a hierarchical decentralized architecture for analyzing and controlling these systems. Specifically, in the analysis and control-system design of complex large-scale dynamical systems it is often desirable to treat the overall system as a collection of interconnected subsystems.

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  • Communication Systems Lecturer: M.E. P.T.A. Quang .Contents           Chapter 1: Introductory Concepts Chapter 2: QoS Chapter 3: Transmission and switching Chapter 4: Digital networks Chapter 5: Signaling Chapter 6: PSTN Chapter 7: VoIP Chapter 8: Mobile communication Chapter 9: Satellite communication Chapter 10: Fiber-optic communication .

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  • This paper proposes a hierarchical text categorization (TC) approach to encoding free-text clinical notes with ICD-9-CM codes. Preliminary experimental result on the 2007 Computational Medicine Challenge data shows a hierarchical TC system has achieved a microaveraged F1 value of 86.6, which is comparable to the performance of state-of-the-art flat classification systems.

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  • As mentioned, the DNS “phone book” looks like a hierarchical system. This is also reflected in how the actual database which holds the information is implemented. Instead of having a big database containing answers to all queries, DNS works by delegating the responsibility, or “authority”, for each hierarchical component (i.e., a subtree of the DNS hierarchical tree, also called a “zone”) to the servers that should be responsible for that component. These servers can further sub-delegate authority, resulting in a distributed database based on a tree topology....

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  • In this paper, we propose a novel method of reducing the size of translation model for hierarchical phrase-based machine translation systems. Previous approaches try to prune infrequent entries or unreliable entries based on statistics, but cause a problem of reducing the translation coverage.

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  • In hierarchical phrase-based SMT systems, statistical models are integrated to guide the hierarchical rule selection for better translation performance. Previous work mainly focused on the selection of either the source side of a hierarchical rule or the target side of a hierarchical rule rather than considering both of them simultaneously. This paper presents a joint model to predict the selection of hierarchical rules.

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  • We present a statistical phrase-based translation model that uses hierarchical phrases— phrases that contain subphrases. The model is formally a synchronous context-free grammar but is learned from a bitext without any syntactic information. Thus it can be seen as a shift to the formal machinery of syntaxbased translation systems without any linguistic commitment. In our experiments using BLEU as a metric, the hierarchical phrasebased model achieves a relative improvement of 7.5% over Pharaoh, a state-of-the-art phrase-based system. ...

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  • This paper describes a new discourse module within our multilingual NLP system. Because of its unique data-driven architecture, the discourse module is language-independent. Moreover, the use of hierarchically organized multiple knowledge sources makes the module robust and trainable using discourse-tagged corpora. Separating discourse phenomena from knowledge sources makes the discourse module easily extensible to additional phenomena.

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  • We propose a novel method for learning morphological paradigms that are structured within a hierarchy. The hierarchical structuring of paradigms groups morphologically similar words close to each other in a tree structure. This allows detecting morphological similarities easily leading to improved morphological segmentation. Our evaluation using (Kurimo et al., 2011a; Kurimo et al., 2011b) dataset shows that our method performs competitively when compared with current state-ofart systems.

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  • We present a simple yet powerful hierarchical search algorithm for automatic word alignment. Our algorithm induces a forest of alignments from which we can efficiently extract a ranked k-best list. We score a given alignment within the forest with a flexible, linear discriminative model incorporating hundreds of features, and trained on a relatively small amount of annotated data. We report results on Arabic-English word alignment and translation tasks. Our model outperforms a GIZA++ Model-4 baseline by 6.3 points in F-measure, yielding a 1.

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  • We investigate the use of Fisher’s exact significance test for pruning the translation table of a hierarchical phrase-based statistical machine translation system. In addition to the significance values computed by Fisher’s exact test, we introduce compositional properties to classify phrase pairs of same significance values. We also examine the impact of using significance values as a feature in translation models.

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  • The main aim of the MIMA (Mining Information for Management and Acquisition) Search System is to achieve ‘structuring knowledge’ to accelerate knowledge exploitation in the domains of science and technology. This system integrates natural language processing including ontology development, information retrieval, visualization, and database technology. The ‘structuring knowledge’ that we define indicates 1) knowledge storage, 2) (hierarchical) classification of knowledge, 3) analysis of knowledge, 4) visualization of knowledge.

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  • In this paper we compare and contrast two approaches to Machine Translation (MT): the CMU-UKA Syntax Augmented Machine Translation system (SAMT) and UPC-TALP N-gram-based Statistical Machine Translation (SMT). SAMT is a hierarchical syntax-driven translation system underlain by a phrase-based model and a target part parse tree. In N-gram-based SMT, the translation process is based on bilingual units related to word-to-word alignment and statistical modeling of the bilingual context following a maximumentropy framework. ...

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  • Lip until now, no automated system for these insertion tasks existed. INSYST (INserter SYSTem), we describe here, can efficiently insert lexical items under the appropriate nodes in hierarchies. It currently handles hierarchies specified in the DATR formalism (Evans and Gazdar 1989, 1990). The system uses a classification algorithm that maximizes the number of inherited features for each entry.

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  • In this chapter presenting the terminology and basic concepts that will be used throughout the lecture. This chapter discusses data models and defines the concepts of schemas and instances, which are fundamental to the study of database systems, discuss the three-schema DBMS architecture, provides a user’s perspective on what a DBMS is supposed to do, describe the types of interfaces and languages that are typically provided by a DBMS,...

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