• International Journal of Advanced Culture Technology
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• 제11권4호
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• pp.464-469
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• 2023

As modern society develops, the number of diseases caused by bad smells is increasing. As it can harm people's health, it is important to predict in advance the extent to which bad smells may occur, inform the public about this, and take preventive measures. In this paper, we propose a hybrid neural network structure of CNN and LSTM that can be used to detect or predict the occurrence of odors, which are most required in manufacturing or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data, including hydrogen sulfide, ammonia, benzene, and toluene, in real time, and applies this data to the inference model to detect and predict the odor state. The proposed model evaluated the prediction accuracy of the training model through performance indicators based on accuracy, and the evaluation results showed an average performance of more than 94%.

• 디지털산업정보학회논문지
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• 제9권4호
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• pp.127-134
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• 2013

While there are many services that can check current traffic condition and application program such as bus arrival alarm are developed, since it only provide simple alarm and check level of information, it is still insufficient in many senses. Therefore, the program that try to develop in this study is the system that predict arrival time to destination and inform the bus passengers by applying real time traffic information. The system developed related to this study is still very inadequate. In the system developed in this thesis, when the user input the current bus number and destination using smart-phone, relevant server acquire the bus route information from bus information DB, and analyze real time traffic information based on the information from traffic information DB, and inform customer of expected arrival time to destination. In this thesis, traffic congestion can be eased off and regular operation of public transportation can be improved with reliable destination arrival alarm. Also, it is considered that pattern of bus users can be analyzed by using these information, and analyzing average transport speed and time of public transportation, travel time depending on various situation can give a boost to study related to transportation information and its development.

• International Journal of Air-Conditioning and Refrigeration
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• 제13권2호
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• pp.89-98
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• 2005

In this study, indoor VOCs concentration emitted from floor and furniture was measured after the installation of floor and furniture in a real residence. With the measured data, prediction method and predication equations for indoor concentration of each VOCs and BTEX were developed. The following conclusions were drawn from this study. First, according to the predicted results of concentration decrease of BTEX (benzene, toluene, ethylbenzene, m,p,o-xylene) after the installation of floor in a real residence, prediction equation can be expressed using exponential function. Second, in case of floor, more reliable prediction equation can be obtained by using cumulative value of indoor concentration than by using just hourly measured value directly. Indoor concentration of benzene can be expressed as $y=408.52(1­e^{-00031{\times}time})$ with $R^2$ of 0.94 which is significantly high value. Third, toluene showed the highest concentration in case of furniture installation indoors, and it needed the longest time for concentration decrease. However, other substances except toluene showed constant concentration throughout the measurement period. Fourth, in case of furniture installation indoors, prediction equation of toluene concentration decrease is estimated to be $y= 3616.3{\times}e^{(-0.1091{\times}time)}+513.96{\times}e^{(-0.0006{\times}time)}\;with\; R^2$ of 0.95 which is significantly high value.

• 대기
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• 제21권2호
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• pp.209-220
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• 2011

A new consensus algorithm for the prediction of tropical cyclone track has been developed. Conventional consensus is a simple average of a few fixed models that showed the good performance in track prediction for the past few years. Meanwhile, the consensus in this study is a weighted average of a few models that may change for every individual forecast time. The models are selected as follows. The first step is to find the analogous past tropical cyclone tracks to the current track. The next step is to evaluate the model performances for those past tracks. Finally, we take the weighted average of the selected models. More weight is given to the higher performance model. This new algorithm has been named as DYTRAP (DYnamic data-base Typhoon tRAck Prediction) in the sense that the data base is used to find the analogous past tracks and the effective models for every individual track prediction case. DYTRAP has been applied to all 2009 tropical cyclone track prediction. The results outperforms those of all models as well as all the official forecasts of the typhoon centers. In order to prove the real usefulness of DYTRAP, it is necessary to apply the DYTRAP system to the real time prediction because the forecast in typhoon centers usually uses 6-hour or 12-hour-old model guidances.

• 한국해양공학회지
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• 제15권3호
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• pp.43-48
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• 2001

In this paper, the real-time prediction of high temperature creep strength and creep for nickel-based superalloy Udimet 720 (high-temperature and high-pressure gas turbine engine materials) was performed on round-bar type specimens under pure load at the temperatures of 538, 649 and 704$^{\circ}C$. The predictive equation of ISM creep has better reliability than that of LMP and LMP-ISM, and its reliability is getting better for long time creep prediction ($10^3~10^5$h).

• 연구논문집
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• 통권27호
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• pp.47-55
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• 1997

Fatigue life prediction of mechanical components is necessary to develop new products, which is very expensive and time-consuming. This paper reviews technologies proposed for computation of dynamic stress in mechanical components. The methods based on multibody dynamics are considering more real operational conditions than other methods. The technology for fatigue life prediction without the prototype for experiment results in cost and time saving. This technology can be applied to design of various mechanical components like carbody.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.332-335
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• 2006

Red tide(harmful algae) in the Korean Coastal Waters has a given a great damage to the fishery every year. However, the aim of our study understands the influence of meteorological factors (air and water temperature, precipitation, sunshine, solar radiation, winds) relating to the mechanism of red tide occurrence and monitors red tide by satellite remote sensing, and analyzes the potential area for red tide occurrence by GIS. The meteorological factors have directly influenced on red tide formation. Thus, We want to predict and apply to red tide formation from statistical analyses on the relationships between red tide formation and meteorological factors. In future, it should be realized the near real time monitoring for red tide by the development of remote sensing technique and the construction of integrated model by the red tide information management system (the data base of red tide - meteorological informations). Finally our purpose is support to the prediction information for the possible red tide occurrence by coastal meteorological information and contribute to reduce the red tide disaster by the prediction technique for red tide.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2018년도 추계 학술논문 발표대회
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• pp.59-60
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• 2018

The purpose of this study is to predict and classify the accident types based on the KOSHA (Korea Occupational Safety & Health Agency) and weather data. We also have an effort to suggest an important management method according to accident types by deriving feature importance. We designed two models based on accident data and weather data (model(a)) and only weather data (model(b)). As a result of random forest method, the model(b) showed a lack of accuracy in prediction. However, the model(a) presented more accurate prediction results than the model(b). Thus we presented safety management plan based on the results. In the future, this study will continue to carry out real time prediction to occurrence types to prevent safety accidents by supplementing the real time accident data and weather data.

• Journal of Computing Science and Engineering
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• 제11권3호
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• pp.100-108
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• 2017

In the field of Internet of Things (IoT), smarter embedded devices offer functions via web services. The Quality-of-Service (QoS) prediction is a key measure that guarantees successful IoT service applications. In this study, a collaborative filtering method is presented for predicting response time of IoT service due to time-awareness characteristics of IoT. First, a calculation method of service response time similarity between different users is proposed. Then, to improve prediction accuracy, initial similarity values are adjusted and similar neighbors are selected by a similarity threshold. Finally, via a densified user-item matrix, service response time is predicted by collaborative filtering for current active users. The presented method is validated by experiments on a real web service QoS dataset. Experimental results indicate that better prediction accuracy can be achieved with the presented method.

• 전자공학회논문지
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• 제50권2호
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• pp.152-160
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• 2013

본 논문에서는 실시간 동작 환경인 VoIP에 적용 가능한 스팸 대응 기법으로서 예측 평판도 시스템을 제안한다. VoIP 스탬을 차단하기 위한 연구가 다양하게 진행되고 있지만, VoIP 스팸 대응을 위한 기존 기법들은 사용자의 직접적인 개입으로 인한 사용자 불편성, 실시간 동작으로 인한 세션 설립 시간 지연 및 시스템 과부하 등과 같은 문제가 있다. 제안 기법은 발신자의 세션 설립 주기와 수신자의 통화시간을 기준으로 통계적 방법을 이용하여 평판도를 계산하는 시스템이다. 제안 기법은 사용자의 직접적인 개입이 없기 때문에 사용자의 불편성 문제를 해결할 수 있으며, 실시간 동작을 요구하지 않고 세션 설립 전에 통계적 방법으로 발신자의 평판도를 계산하기 때문에 실시간 동작 환경인 VoIP에서 효과적으로 SPIT에 대응할 수 있다.