• Geotechnical Engineering
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• v.14 no.2
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• pp.107-126
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• 1998

Ground settlements induced by tunnel excavation cause the foundations of the neighboring building structures to deform. An expert system called NESASS( Neural network Expert System for Adjacent Structure Safety analysis) was developed to analyze the structural safety of such building structures. NESASS predicts the trend of ground settlements resulting from tunnel excavation and carries out a safety analysis for building structures on the basis of the predicted ground settlements. Using neural network technique. the NESASS learns the database consisting of the measured ground settlements collected from numerous actual fields and infers a settlement trend at the field of interest. The NESASS calculates the magnitudes of angular distortion, deflection ratio, and differential settlement of the structure. and in turn, determines the safety of the structure. In addition, the NESASS predicts the patterns of cracks to be formed in the structure, using Dulacska model for crack evaluation. In this study, the ground settlements measured from Seoul subway construction sites were collected and classified with respect to the major factors influencing ground settlement. Subsequently, a database of ground settlement due to tunnel excavation was built. A parametric study was performed to select the optimal neural network model for the database. A comparison of the ground settlement predicted by the NESASS with the measured ones indicates that the NESASS leads to reasonable predictions. The results of confidence evaluation for safety evaluation system of the NESASS are presented in this paper.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.588-592
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• 1996

In this paper, we have constructed an expert system for semiconductor chip encapsulation which combines a knowledge-based system with CAE software. The knowledge-base module includes heuristic and pre-analysis knowledge for evaluation and redesign. Evaluation of the initial design and generation of redesign recommendations can be developed from the rules as applied to a given chip Package. The CAE programs can be used for simulating the filling and packing stage of encapsulation process. The expert system is a new tool which enables package design or process conditions with high yields and high productivity.

• Journal of the Ergonomics Society of Korea
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• v.26 no.4
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• pp.57-64
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• 2007

In the world, the old population is growing fast and many countries went into an advanced age society. Therefore the development of everyday products, electric appliances, and welfare services considering old people is more important than ever. In particular, the complexity of products can cause many problems for old people. Universal design is an approach to create environments and products that recognizes the diversity of users, regardless of their ability or age. Universality evaluation for a product is very important to verify old people's accessibility and usability for the product. Universality means how good a product was designed in view of universal design principles. In this study, UNIX, a method to evaluate the universality of a product was developed. UNIX was based on seven universal design principles; equitable use, flexibility in use, simple and intuitive, perceptible information, tolerance for error, low physical effort, size and space for approach and use. UNIX is a kind of expert evaluation and very simple method. The method is consisted of two steps. In the first step, relative weights for seven principles and subjective ratings on design suitability for each principle are obtained. In the second step, universality index (UNIX) of each product is obtained by weighted average multiplying relative weights and rating scores. As a case study, this method was applied for mouse designs. In conclusion, this method could be effectively applied to evaluate the universality of a product.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.13 no.5
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• pp.59-80
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• 2010

This research This research aims at developing systemic evaluation model in terms of biotope preservation through reports, literatures, and expert survey analysis by implementing biotope structure analysis in area level with selecting Hyunpoong and Yuga-myeon, Dalseong county, Daegu metropolitan city as a site. First of all, as a result of biotope type classification of research site, biotope type groups are classified into total 13, and its biotope types are divided into total 61. Also, as a result of literature analysis, total 18 items are drawn such as diversity of biotope typical species as a index item to assess the preservation value of biotope, and the first evaluation index are divided into 10 and the second ones are divided into 8 according to characteristic of index items. As a result of expert survey analysis, All 10 index items, first evaluation index, show high importance average (above 4.7). As a result of implementation of main cause for categorizing evaluation index by characteristic, there are 3 factors such as 'obstructive factor.' Based on above survey analysis result, as a result of estimating the weight of each item, 'restoration factor' showed the highest, 3.4541, but 'factor of habitat stability' showed 3.1468, which is the lowest The systemic value evaluation was set by comprehensively analyzing these results. As a result of biotope preservation value evaluation through applying research site, total 19 types which are abundant in vegetation are classified into I class, 12 types in II class, 5 types in III class, 10 types in IV class, and 15 types in V class respectively. Lastly, as a result of second evaluation, it is analyzed that there are 17 special meaningful space to preserve species and biotope(1a, 1b) and 61 meaningful space to preserve species (2a, 2b, 2c).

• Journal of Korean Institute of Industrial Engineers
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• v.20 no.4
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• pp.153-180
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• 1994

The assemblability is determined by the structure of product and the relationship between composing parts and machining parts. In this paper, the bolt was divided into bolt-head, -shaft, -thread and -end. For higher assemblability in bolting process, it was analyzed the geometric and technological characteristics of bolts were analysed regarding pre- and in-assembly process. And this paper presents the knowledge-based expert system to assist for designer in the processor of designing bolt for easier assembly. The developed expert system for supporting bolt design assemblability which is named as BDFA SYSTEM consists of two system such as "BOLT DESIGN SYSTEM" which provide feasible assembly bolt design to designer and "EVALUATION SYSTEM" which provide assembly evaluation to alternative of bolt design.

• Journal of Korean Society for Quality Management
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• v.23 no.2
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• pp.1-9
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• 1995

Two user groups, expert and non-expert, are sampled to measure the image quality of G3 facsimile. A ITU-TS tset chart No. 2 has been transmitted among some selected cities and evaluated by user groups. Their subjective evaluation to the image quality is quantified by Mean Opinion Score method. There is highly significant difference in the image quality between expert and non-expert. From modified logit model, it is concluded that there is no significance in two considered factors, the effects of the number of links and transmission time. The derived percent curves show that 80% of non-experts(90% of expert) is considering the image quality of G3 facsimile "fair, good, or excellent".

• Nuclear Engineering and Technology
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• v.29 no.1
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• pp.25-34
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• 1997

This study presents a new approach for expert opinion elicitation process to assess an uncertainty inherent in accident management. The need to work with rare event and limited data in accident management leads analysis to use expert opinions extensively. Unlike the conventional approach using point-valued probabilities, the study proposes the concept of fuzzy probability to represent expert opinion. The use of fuzzy probability has an advantage over the conventional approach when an expert's judgment is used under limited dat3 and imprecise knowledge. The study demonstrates a method of combining and propagating fuzzy probabilities. finally, the proposed methodology is applied to the evaluation of the probability of a bottom head failure for the flooded case in the Peach Bottom BWR nuclear power plant.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.139-147
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• 2019

A false alarm, which is an incorrect report of an emergency, could trigger an unnecessary action. The predictive maintenance framework developed in our previous work has a feature whereby a machine alarm is triggered based on sensor data evaluation. The sensor data evaluator performs three essential evaluation steps. First, it evaluates each sensor data value based on its threshold (lower and upper bound) and labels the data value as "alarm" when the threshold is exceeded. Second, it calculates the duration of the occurrence of the alarm. Finally, in the third step, a domain expert is required to assess the results from the previous two steps and to determine, thereby, whether the alarm is true or false. There are drawbacks of the current evaluation method. It suffers from a high false-alarm ratio, and moreover, given the vast amount of sensor data to be assessed by the domain expert, the process of evaluation is prolonged and inefficient. In this paper, we propose a method for automatic false-alarm labeling that mimics how the domain expert determines false alarms. The domain expert determines false alarms by evaluating two critical factors, specifically the duration of alarm occurrence and identification of anomalies before or while the alarm occurs. In our proposed method, Hierarchical Temporal Memory (HTM) is utilized to detect anomalies. It is an unsupervised approach that is suitable to our main data characteristic, which is the lack of an example of the normal form of sensor data. The result shows that the technique is effective for automatic labeling of false alarms in sensor data.

• Journal of the Society of Naval Architects of Korea
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• v.32 no.3
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• pp.44-50
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• 1995

We describe here the research work concerning the development of the CAPP(computer aided process planning) system, named BLOCK. designed to support block division of ship. The system consists of the expert system part generating block division lines, and their evaluation and editing one. As a reasoning approach of expert system, the case-based reasoning is used. The division lines can be graphically edited and the satisfaction measure of block division can be checked up in the evaluation stage with separate window. The expert system is developed by using NEXPERT Object development tool in the workstation. Currently the target ship is VLCC.