• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.160-169
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• 2004

With an emergence of SOC from developed IC technology, the VLSI design has required the core re-use technique and modular test development. To minimize the cost of testing SOC, an efficient method is required to optimize the test time and area overhead in conjunction for the core test wrapper, which is one of the important elements for SOC test architecture. In this paper, we propose an efficient design strategy of core test wrapper to achieve the minimum cost for SOC testing. The proposed strategy adopted advantages of traditional methods and more developed to be successfully used in practice.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2235-2242
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• 2006

It became important to develop a wrapper for web information sources due to prevalence of information services through web information sources. We present a wrapper prototype that is a middleware to integrate web information sources. We present the derivation strategy of XML Schema from HTML documents and the query processing method based on XQJ. The usage example of wrapper API will show the usefulness of our prototype system.

• Journal of KIISE:Databases
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• v.29 no.4
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• pp.311-320
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• 2002

The 'wrapper' is a module that extracts and processes information from the specified data source by the pre-composed extraction rule. 'HTML Wrapper for XML' extracts information from the web source as the form of XML document. Since composing the extraction rule is a repetitious and tedious job, it should be done as easy and fast as possible. This paper presents the method to minimize the composing job, which integrates GUI based training and scripting.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.3
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• pp.65-70
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• 2004

The SOC(System on Chip) testing has required the core re-use methodology and the efficiency of test method because of increase of its cost. The goal of SOC testing is to minimize the testing time, area overhead, and power consumption during testing. Prior research has concentrated on only one aspect of the test core wrapper design problem at a test time. Our research is concentrated on optimization of test time and area overhead for the core test wrapper, which is one of the important elements for SOC test architecture. In this paper, we propose an efficient wrapper design algorithm that improves on earlier approaches by also reducing the TAM(Test Access Mechanism) width required to achieve these lower testing times.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.1
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• pp.127-132
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• 2003

This paper proposes a wrapper generation method for collecting comparative shopping information from various Internet shopping malls. The proposed method is a kind of supervised learning method to learn wrappers from sample web pages along with information locations designated by the administrators. It generates wrappers expressed in the form of generalized tags sequences and frame filling procedures for semi-structured web pages. The paper also presents how to use the learned wrappers and describes a prototype system which implemented the proposed ideas and methods.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.11
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• pp.109-118
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• 2007

As the integration density and the operating speed of System on Chips (SoCs) become increasingly high, it is crucial to test delay defects on the SoCs. This paper introduces an enhanced IEEE 1500 wrapper cell architecture and IEEE 1149.1 TAP controller for the wrapper interface logic, and proposes a transition delay fault test method. The method proposed can detect slow-to-rise and slow-to-fall faults sequentially with low area overhead and short test time. and simultaneously test IEEE 1500 wrapped cores operating at different core clocks.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.2
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• pp.226-235
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• 2016

The yield of 3D stacked IC manufacturing improves with the pre-bond integrity testing of through silicon vias (TSVs). In this paper, an efficient pre-bond test method is presented based on IEEE std. 1500, which can precisely diagnose any happening of TSV defects. The IEEE std. 1500 wrapper cells are augmented for the proposed method. The pre-bond TSV test can be performed by adjusting the driving strength of TSV drivers and the test clock frequency. The experimental results show the advantages of the proposed approach.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.51-63
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• 2001

In supervised machine learning, an induction algorithm, which is able to extract rules from data with learning capability, provides a useful tool for data mining. Practical induction algorithms are known to degrade in prediction accuracy and generate complex rules unnecessarily when trained on data containing superfluous features. Thus it needs feature subset selection for better performance of them. In feature subset selection on the induction algorithm, wrapper method is repeatedly run it on the dataset using various feature subsets. But it is impractical to search the whole space exhaustively unless the features are small. This study proposes a heuristic method that uses sensitivity analysis of neural networks to the wrapper method for generating rules with higher possible accuracy. First it gives priority to all features using sensitivity analysis of neural networks. And it uses the wrapper method that searches the ordered feature space. In experiments to three datasets, we show that the suggested method is capable of selecting a feature subset that improves the performance of the induction algorithm within certain iteration.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.67-77
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• 2006

Wrappers play an important role in extracting specified information from various sources. Wrapper rules by which information is extracted are often created from the domain-specific knowledge. Domain-specific knowledge helps recognizing the meaning the text representing various entities and values and detecting their formats However, such domain knowledge becomes powerless when value-representing data are not labeled with appropriate textual descriptions or there is nothing but a hyper link when certain text labels or values are expected. In order to alleviate these problems, we propose a probabilistic method for recognizing the entity type, i.e. generating wrapper rules, when there is no label associated with value-representing text. In addition, we have devised a method for using the information reachable by following hyperlinks when textual data are not immediately available on the target web page. Our experimental work shows that the proposed methods help increasing precision of the resulting wrapper, particularly extracting the title information, the most important entity on a web page. The proposed methods can be useful in making a more efficient and correct information extraction system for various sources of information without user intervention.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.447-456
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• 2004

Information extraction is a process of recognizing and fetching particular information fragments from a document. In order to extract information uniformly from many heterogeneous information sources, it is necessary to produce information extraction rules called a wrapper for each source. Previous methods of information extraction can be categorized into manual wrapper generation and automatic wrapper generation. In the manual method, since the wrapper is manually generated by a human expert who analyzes documents and writes rules, the precision of the wrapper is very high whereas it reveals problems in scalability and efficiency In the automatic method, the agent program analyzes a set of example documents and produces a wrapper through learning. Although it is very scalable, this method has difficulty in generating correct rules per se, and also the generated rules are sometimes unreliable. This paper tries to combine both manual and automatic methods by proposing a new method of learning information extraction rules. We adopt the scheme of supervised learning in which a user-interface agent is designed to get information from the user regarding what to extract from a document, and eventually XML-based information extraction rules are generated through learning according to these inputs. The interface agent is used not only to generate new extraction rules but also to modify and extend existing ones to enhance the precision and the recall measures of the extraction system. We have done a series of experiments to test the system, and the results are very promising. We hope that our system can be applied to practical systems such as information-mediator agents.