• Journal of Information Processing Systems
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• v.16 no.4
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• pp.820-831
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• 2020

Extractive document summarization aims to select a few sentences while preserving its main information on a given document, but the current extractive methods do not consider the sentence-information repeat problem especially for news document summarization. In view of the importance and redundancy of news text information, in this paper, we propose a neural extractive summarization approach with joint sentence semantic clipping and selection, which can effectively solve the problem of news text summary sentence repetition. Specifically, a hierarchical selective encoding network is constructed for both sentence-level and document-level document representations, and data containing important information is extracted on news text; a sentence extractor strategy is then adopted for joint scoring and redundant information clipping. This way, our model strikes a balance between important information extraction and redundant information filtering. Experimental results on both CNN/Daily Mail dataset and Court Public Opinion News dataset we built are presented to show the effectiveness of our proposed approach in terms of ROUGE metrics, especially for redundant information filtering.

• Ocean Systems Engineering
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• v.6 no.3
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• pp.217-231
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• 2016

This paper presents a new approach for underwater image analysis using the bi-dimensional empirical mode decomposition (BEMD) technique and the phase congruency information. The BEMD algorithm, fully unsupervised, it is mainly applied to texture extraction and image filtering, which are widely recognized as a difficult and challenging machine vision problem. The phase information is the very stability feature of image. Recent developments in analysis methods on the phase congruency information have received large attention by the image researchers. In this paper, the proposed method is called the EP model that inherits the advantages of the first two algorithms, so this model is suitable for processing underwater image. Moreover, the receiver operating characteristic (ROC) curve is presented in this paper to solve the problem that the threshold is greatly affected by personal experience when underwater image edge detection is performed using the EP model. The EP images are computed using combinations of the Canny detector parameters, and the binaryzation image results are generated accordingly. The ideal EP edge feature extractive maps are estimated using correspondence threshold which is optimized by ROC analysis. The experimental results show that the proposed algorithm is able to avoid the operation error caused by manual setting of the detection threshold, and to adaptively set the image feature detection threshold. The proposed method has been proved to be accuracy and effectiveness by the underwater image processing examples.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.7
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• pp.337-352
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• 2017

Clone-and-own reuse is an approach to creating new software variants by copying and modifying existing software products. A family of legacy software products developed by clone-and-own reuse often requires high maintenance cost and tends to be error-prone due to patch-ups without refactoring and structural degradation. To overcome these problems, many organizations that have used clone-and-own reuse now want to migrate their legacy products to software product line (SPL) for more systematic reuse and management of software asset. However, with most of existing methods, variation points are embedded directly into design and code rather than modeled and managed separately; variation points are not created ("engineered") systematically based on a variability model. This approach causes the following problems: it is difficult to understand the relationships between variation points, thus it is hard to maintain such code and the asset tends to become error-prone as it evolves. Also, when SPL evolves, design/code assets tend to be modified directly in an ad-hoc manner rather than engineered systematically with appropriate refactoring. To address these problems, we propose a feature-oriented method for extracting a SPL asset from a family of legacy applications. With the approach, we identify and model variation points and their relationships in a feature model separate from implementation, and then extract and manage a SPL asset from legacy applications based on the feature model. We have applied the method to a family of legacy Notepad++ products and demonstrated the feasibility of the method.

• Advances in environmental research
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• v.9 no.1
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• pp.55-64
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• 2020

The problems with unsorted municipal waste are always associated with disposal issues as it requires a large area for landfilling or high energy used for incineration. In recent years, an autoclaving technique has been considered a promising approach which could minimize the volume of organic waste from being directly disposed or incinerated. In this work, an attempt was done to study the saccharification potential of organic residues under elevated temperature Thermal treatment involving hot water bath was applied to treat the organic residue ranging from 60℃ to 100℃ for 30 and 60 minutes. The result obtained showed an increasing trend for the concentration of glucose and carbohydrate. However, the result for lignocellulose content which contains various component includes extractive, holocellulose, hemicellulose, cellulose and lignin show variation. Based on the thermal treatment carried out, the result indicated that the trend of glucose and carbohydrate content. The highest percentage of glucose that can be obtained 978.602 ㎍/ml which could be obtained at 90℃ at 60 minutes. The carbohydrate also shows an increasing trend with 0.234 mg/ml as the highest peak achieved at 80℃ for 30 minutes treatment. However, it was found that the lignocellulose content varies with temperature and time. The statistical analysis was carried out using two-ways ANOVA shows an interaction effect between the independent variables (temperature and contact time) and the saccharification effects on the food wastes. The result shows a variation in the significant effect of independent variables on the changes in the composition of food waste.

• Journal of KIISE:Software and Applications
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• v.36 no.7
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• pp.539-547
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• 2009

Software product line (SPL) engineering is an emerging paradigm for successful software reuse and has been adopted for various industrial and consumer products to improve their productivity and quality. However, most SPL methods require high initial costs and long development time, which makes many companies hesitate to adopt the SPL paradigm. In this paper we introduce a method to construct an SPL by extracting core assets from legacy components based on the feature model, which requires less initial time and effort. We also present a case study on cable set-top box software to illustrate the applicability of this method, and lessons learned that will provide guidelines for many companies to adopt the SPL paradigm.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.505-515
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• 2004

In a newspaper, 5W1H information is the most fundamental and important element for writing and understanding articles. Focusing on such a relation between a newspaper article and the 5W1H, we propose a summarization method based on the activation degree of 5W1H. To overcome problems of the lead-based and the title-based methods, both of which are known to be the most effective in newspaper summarization, sufficient 5W1H information is extracted from both a title and a lead sentence. Moreover, for each sentence, its weight is computed by considering various factors, such as activation degree of 5W1H, the number of 5W1H categories, and its length and position. These factors make a great contribution to the selection of more important sentences, and thus to the improvement of readability of the summarized texts. In an experimental evaluation, the proposed method achieved a precision of 74.7% outperforming the lead-based method. In sum, our 5W1H approach was shown to be promising for automatic summarization of newspaper articles.

• Smart Media Journal
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• v.11 no.3
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• pp.31-38
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• 2022

In the document extraction summary study, various methods for selecting important sentences based on the relationship between sentences were proposed. In the Korean document summary using the summation similarity of sentences, the summation similarity of the sentences was regarded as the amount of sentence information, and the summary sentences were extracted by selecting important sentences based on this. However, the problem is that it does not take into account the various importance that each sentence contributes to the entire document. Therefore, in this study, we propose a document extraction summary method that provides a summary by selecting important sentences based on the amount of quantitative and semantic information in the sentence. As a result, the extracted sentence agreement was 58.56% and the ROUGE-L score was 34, which was superior to the method using only the combined similarity. Compared to the deep learning-based method, the extraction method is lighter, but the performance is similar. Through this, it was confirmed that the method of compressing information based on semantic similarity between sentences is an important approach in document extraction summary. In addition, based on the quickly extracted summary, the document generation summary step can be effectively performed.

• Resources Recycling
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• v.26 no.1
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• pp.51-58
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• 2017

The present study to develop a process for extracting nitric acid and gold from aqua regia leach solution using TBP(tributyl phosphate) was conducted. The pure aqua regia was used to investigate the extractive behavior of nitric acid depending on the concentration of extractant, concentration ratio of nitric and hydrochloric acid. The extraction rate of nitric acid and gold from the gold bearing aqua regia was also examined. The theoretical extraction number was verified by counter current using the number of operations and the phase ratio obtained from McCabe-Thiele diagram. Stripping experiments were carried out for continuous recovery of nitric acid and gold in loaded organic. Considering the effect of extraction acid and gold, the simulation showed that greater than 99.9% extraction of $103.0mg{\cdot}L^{-1}$ gold and 98.0% of $151.2g{\cdot}L^{-1}$ nitric acid could be attained in a two and three-stage counter-current extraction at an O/A phase ratio of 1:0.85. Distilled water and sodium thiosulfate were used as the nitric acid and gold stripping solution. The stripping rates were 99.5% and 92.0%, respectively. The study revealed that the recovery of nitric acid and gold from gold bearing aqua regia was a plausible approach through simultaneous extraction and continuous stripping of nitric acid and gold.