• Structural Engineering and Mechanics
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• v.64 no.2
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• pp.173-181
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• 2017

This paper analyzes the influence of the construction process on short- and long-term deflections on a reinforced concrete structure poured on-site by a portable industrialized system. A parametric analysis was carried out by the Finite Elements Method (FEM) that considered: a) type of construction process with reshoring or clearing (partial striking); b) the number of successively shored floors and c) the number of shores used on each floor. All three factors were especially important for the values of short- and long-term deflections, which were highest in the reshoring processes with the lowest number of successively shored floors and the lowest number of shores per floor. Deflections obtained were compared with the limits laid down by ACI 318-14 and as calculated by this code's simplified method. The long-term deflections were seen to be almost double than those obtained by applying the ACI 318-14 code's simplified method and in some cases these deflections were above the established limits. It can thus be concluded that the load history of a building under construction should be taken into account in order to satisfy a structure's in-service conditions and durability.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.119-121
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• 2016

최근 사람과 컴퓨터가 대화를 하는 채팅시스템 연구가 활발해지고 있다. 컴퓨터가 사람의 말에 적절한 응답을 하기 위해선 그 의미를 분석할 필요가 있다. 발화에 대한 의미 분석의 기본이 되는 연구로 감정분석과 화행분석이 있다. 그러나 이 둘은 서로 밀접한 연관이 있음에도 불구하고 함께 분석하는 연구가 시도되지 않았다. 본 연구에서는 Long Short-term Memory(LSTM)를 이용하여 대화체 문장의 감정과 화행, 서술자를 동시에 분석하는 통합 대화 분석모델을 제안한다. 사랑 도메인 데이터를 사용한 실험에서 제안 모델은 감정 58.08%, 화행 82.60%, 서술자 62.74%의 정확도(Accuracy)를 보였다.

• The Journal of the Acoustical Society of Korea
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• v.39 no.2
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• pp.137-142
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• 2020

Many studies based on I-vector have been conducted in a variety of environments, from text-dependent short-utterance to text-independent long-utterance. In this paper, we propose a speaker verification system employing a combination of I-vector with Probabilistic Linear Discriminant Analysis (PLDA) and speaker embedding of Long Short Term Memory (LSTM) with attention mechanism in far-field and noisy environments. The LSTM model's Equal Error Rate (EER) is 15.52 % and the Attention-LSTM model is 8.46 %, improving by 7.06 %. We show that the proposed method solves the problem of the existing extraction process which defines embedding as a heuristic. The EER of the I-vector/PLDA without combining is 6.18 % that shows the best performance. And combined with attention-LSTM based embedding is 2.57 % that is 3.61 % less than the baseline system, and which improves performance by 58.41 %.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.149-160
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• 2017

Sentiment analysis is the process of determining whether a piece of document, text or conversation is positive, negative, neural or other emotion. Sentiment analysis has been applied for several real-world applications, such as chatbot. In the last five years, the practical use of the chatbot has been prevailing in many field of industry. In the chatbot applications, to recognize the user emotion, sentiment analysis must be performed in advance in order to understand the intent of speakers. The specific emotion is more than describing positive or negative sentences. In light of this context, we propose deep learning models for conducting multi-class sentiment analysis for identifying speaker's emotion which is categorized to be joy, fear, guilt, sad, shame, disgust, and anger. Thus, we develop convolutional neural network (CNN), long short term memory (LSTM), and multi-layer neural network models, as deep neural networks models, for detecting emotion in a sentence. In addition, word embedding process was also applied in our research. In our experiments, we have found that long short term memory (LSTM) model performs best compared to convolutional neural networks and multi-layer neural networks. Moreover, we also show the practical applicability of the deep learning models to the sentiment analysis for chatbot.

• International Journal of Advanced Culture Technology
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• v.5 no.4
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• pp.57-62
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• 2017

In this paper, we applied long short term memory(LSTM) for classifying political polarity in cyber public sphere. The data collected from the cyber public sphere is transformed into word corpus data through word embedding. Based on this word corpus data, we train recurrent neural network (RNN) which is connected by LSTM's. Softmax function is applied at the output of the RNN. We conducted our proposed system to obtain experimental results, and we will enhance our proposed system by refining LSTM in our system.

• The Korean Journal of Franchise Management
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• v.13 no.2
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• pp.17-31
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• 2022

Purpose: With the development of the Internet, consumers can quickly access the electronic word-of-mouth. Consumers seek to reduce uncertainty by referring to the opinions of other consumers about products and services when making purchase decisions. In the food service industry, evaluating a restaurant before an actual visitation is difficult. Therefore, electronic word-of-mouth is important to interact with the customer in restaurants. as it can be used as an exchange of information in which consumers participate and interact with other customers. This study was conducted to verify how online word-of-mouth characteristics (Consensus, Vividness, Neutrality) on attitudes and visit intention from the perspective of social exchange theory. And it was performed to verify the structural relationship between short-term visit intention, mid-term visit and long-term visit intention. Research design, data, and methodology: A survey was conducted on customers who have visited restaurants. Of a total of 312 responses, 306 responses were used, excluding insincere responses and missing values for factors analysis. SPSS 25.0 and AMOS 25.0 were used for statistical analysis, and hypothesis testing was conducted after verifying the validity and reliability of the questionnaire items. Result: The result of the analysis showed that, consensus and neutrality have a positive effect on attitude but not much on vividness. In addition, consensus, vividness, and neutrality have no effect on the short-term visit intention. Finally, the short-term visit intention has a positive effect on mid-term visit intention, and mid-term visit intention has a positive effect on long-term visit intention. Conclusions: Based on the results, this study suggested that it is necessary to have practical implications for marketing and monitoring restaurant reviews in consideration of the characteristics of electronic word-of-mouth. When managing electronic-word-of-mouth, it is necessary to manage the consensus and neutrality is essential to provide sufficient information about the restaurant. The focus should not only be on vividness, such as photos and videos. In addition, restaurants should also provide a good experience for first-time visitors as the short-term visit intention positively affects mid-term and long-term visit intention.

• Journal of Technology Innovation
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• v.23 no.4
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• pp.89-121
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• 2015

Recently, national energy policy tends to be approached with the long-term perspective because it became harder to cope with various energy issues fundamentally only through the short-term and piecemeal approaches. To deal with energy policy from a long-term perspective, we need new governing approach that differs from established short-term perspective. In this context, research efforts to apply transition management theory to long-term energy policy are receiving attention. In this paper, we suggest extended transition management model based on case study of Dutch energy transition model and review the transition management traits of long-term energy policy of Korea. We conclude that transition thinking and approaches are diffusing widely in the long-term energy policy formation processes, but also can find various issues that are needed to be addressed for effective transition management especially in the energy policy implementation processes.

• Journal of Sensor Science and Technology
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• v.17 no.4
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• pp.295-302
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• 2008

$TiO_2,\;ZrO_2$, and $SiO_2$ were added in the concentration of 1 - 3 wt.% to improve long-term stability for the $SnO2$ thick film gas sensor. Short-term sensor resistances up to 90 h were measured to investigate the stabilization time of initial resistance in air. Long-term resistance drifts in air and in gas to 5000 ppm methane for the sensors annealed at $750^{\circ}C$ for 1 h and continuously heated at an operating temperature of $400^{\circ}C$ were also measured up to 90 days at an interval of 1 day. The long-term drifts in methane sensitivity for the three metal oxide-doped $SnO2$ sensors are closely related to methane sensitivity level, catalytic activity, and long-term drift in sensor resistance in air. Those stabilities are mainly discussed in terms of oxidation state and catalytic activity.

• Journal of Korean society of Dental Hygiene
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• v.19 no.4
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• pp.515-524
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• 2019

Objectives: This study aimed to investigate the effects of the amount and duration of smoking on gingival symptoms in adolescents. Methods: We used the web-based survey data of youth health behaviors from 2016 conducted by the Korean Centers for Disease Control and Prevention. The subjects of the study were 67,983 middle and high school students. Data analysis was performed using the SPSS Ver 20.0 program, and complex sample multivariate logistic regression analysis was performed to analyze gingival symptoms according to short- or long-term smoking habits. Results: In subjects with short-term smoking habits, there was no significant difference in gingival symptoms according to the smoking amount. However, after adjusting for socioeconomic characteristics and oral health behaviors in subjects with long-term smoking habits, a heavy smoking amount (${\geq}0.52PY$) had a 1.25 times higher effect than a light smoking amount (<0.52 PY) on gingival symptoms. Long-term heavy smoking (${\geq}0.52PY$) and low daily tooth-brushing frequency in high school students were factors affecting gingival symptoms. Conclusions: When conducting a project on the oral health of adolescents, it is argued that specific investigations and measures should be set up regarding health behavior factors, such as the amount and duration of smoking among adolescents.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.472-476
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• 2015

The purpose of this study is to fully understand the present state of the domestic construction companies, and to analyze phased business types and construction management techniques in order to initiate overseas expansion. Because of the recession in the domestic construction market, a thorough and strategic perspective to constantly develop inroads into overseas market is required. So we carried out a questionnaire survey targeting the experts of the overseas construction and researcher, and consulted them in depth. The questionnaire survey was divided into three sections. The first section is the necessity of overseas construction and the reason. The second is the overseas business types classified into the way of advance in short-term and long-term phase possibility of expansion. Lastly, the importance of the phased construction management techniques and the current capacity of the domestic and the foreign business trends were scrutinized. On the basis of the consultation and surveys, we analyzed the overseas business types and the construction management types in the short-term and long-term phase.