• ETRI Journal
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• 제36권3호
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• pp.418-428
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• 2014

In social network services, such as Facebook, Google+, Twitter, and certain postings attract more people than others. In this paper, we propose a novel method for predicting the lifespan and retweet times of tweets, the latter being a proxy for measuring the popularity of a tweet. We extract information from retweet graphs, such as posting times; and social, local, and content features, so as to construct prediction knowledge bases. Tweets with a similar topic, retweet pattern, and properties are sequentially extracted from the knowledge base and then used to make a prediction. To evaluate the performance of our model, we collected tweets on Twitter from June 2012 to October 2012. We compared our model with conventional models according to the prediction goal. For the lifespan prediction of a tweet, our model can reduce the time tolerance of a tweet lifespan by about four hours, compared with conventional models. In terms of prediction of the retweet times, our model achieved a significantly outstanding precision of about 50%, which is much higher than two of the conventional models showing a precision of around 30% and 20%, respectively.

• The Journal of Advanced Prosthodontics
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• 제16권3호
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• pp.151-162
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• 2024

PURPOSE. This study aimed to analyze factors influencing the success and failure of implant prostheses and to estimate the lifespan of prostheses using standardized evaluation criteria. An online survey platform was utilized to efficiently gather large samples from multiple institutions. MATERIALS AND METHODS. During the one-year period, patients visiting 16 institutions were assessed using standardized evaluation criteria (KAP criteria). Data from these institutions were collected through an online platform, and various statistical analyses were conducted. Risk factors were assessed using both the Cox proportional hazard model and Cox regression analysis. Survival analysis was conducted using Kaplan-Meier analysis and nomogram, and lifespan prediction was performed using principal component analysis. RESULTS. The number of patients involved in this study was 485, with a total of 841 prostheses evaluated. The median survival was estimated to be 16 years with a 95% confidence interval. Factors found to be significantly associated with implant prosthesis failure, characterized by higher hazard ratios, included the 'type of clinic', 'type of antagonist', and 'plaque index'. The lifespan of implant prostheses that did not fail was estimated to exceed the projected lifespan by approximately 1.34 years. CONCLUSION. To ensure the success of implant prostheses, maintaining good oral hygiene is crucial. The estimated lifespan of implant prostheses is often underestimated by approximately 1.34 years. Furthermore, standardized form, online platform, and visualization tool, such as nomogram, can be effectively utilized in future follow-up studies.

• Corrosion Science and Technology
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• 제18권3호
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• pp.86-91
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• 2019

Generally, atmospheric corrosion is the electrochemical degradation of metal that can be caused by various corrosion factors of atmospheric components and weather, as well as air pollutants. Specifically, moisture and particles of sea salt and sulfur dioxide are major factors in atmospheric corrosion. Using galvanized steel is one of the most efficient ways to protect iron from corrosion by zinc plating on the surface of the iron. Galvanized steel is widely used in automobiles, building structures, roofing, and other industrial structures due to their high corrosion resistance relative to iron. The atmospheric corrosion of galvanized steel shows complex corrosion behavior, depending on the plating, coating thickness, atmospheric environment, and air pollutants. In addition, corrosion products are produced in different types of environments. The lifespans of galvanized steels may vary depending on the use environment. Therefore, this study investigated the corrosion behavior of galvannealed steel under atmospheric corrosion in two locations in Korea, and the lifespan prediction of galvannealed steel in rural and coastal environments was conducted by means of the potentiostatic dissolution test and the chemical cyclic corrosion test.

• 한국산학기술학회논문지
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• 제19권10호
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• pp.424-429
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• 2018

본 연구에서는 플랜트 설비 부품류 중 충격에 취약한 신축관 이음을 대상으로 수충격 발생 시 신축관 이음의 신축량을 유압식 액추에이터의 작동데이터로 적용하여 진동내구 시험을 수행하였다. 진동내구 시험 시 내구수명의 가속 요소로 신축관 내부의 온도상태를 가정하고 온도상태를 $30^{\circ}C$부터 $50^{\circ}C$ 및 $65^{\circ}C$로 가속화한 진동내구 시험을 진행하였다. 각 조건별 온도상태별 수명데이터들은 아레니우스 모델식을 따른다고 가정하고 각 수명데이터를 선형화하여 선형식의 상수값과 활성화 에너지 계수를 유도하였다. 또한 유도된 모델식으로부터 $85^{\circ}C$ 경우의 예측 수명과 $85^{\circ}C$ 온도상태에서의 시험 수명결과와 비교를 통해 작은 편차 범위내에서 유도된 모델식의 유효성을 검증하였다. 한편, 시험 중과 시험 후 발견된 신축관의 고장모드에서는 누수 및 벨로우즈 부 내부 슬리부의 이탈과 내부변형 등을 확인할 수 있었다. 향후 본 연구는 진동내구 수명의 가속요인인 온도상태 외 압력상태 등 다양한 수명변수를 적용한 복합수명예측 모델식을 개발하고 검증할 예정이다.

• Elastomers and Composites
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• 제59권2호
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• pp.73-81
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• 2024

In the field of electronic components, the potting material, which is a part of the electronic circuit package, plays a significant role in protecting circuits from the external environment and reducing signal interference among electronic devices during operation. This significantly affects the reliability of the components. Therefore, the accurate prediction and assessment of the lifespan of a material are of paramount importance in the electronics industry. We conducted an accelerated thermal aging evaluation using the Arrhenius technique on elastic potting material developed in-house, focusing on its insulation, waterproofing, and contraction properties. Through a comprehensive analysis of these properties and their interrelations, we confirmed the primary factors influencing molding material failure, as increased hardness is related to aggregation, adhesion, and post-hardening or thermal-aging-induced contraction. Furthermore, when plotting failure times against temperature, we observed that the hardness, adhesive strength, and water absorption rate were the predominant factors up to 120 ℃. Beyond this temperature, the tensile properties were the primary contributing factors. In contrast, the dielectric constant and loss tangent, which are vital for reducing signal interference in electric devices, exhibited positive changes(decreases) with aging and could be excluded as failure factors. Our findings establish valuable correlations between physical properties and techniques for the accurate prediction of failure time, with broad implications for future product lifespans. This study is particularly advantageous for advancing elastic potting materials to satisfy the stringent requirements of reliable environments.

• 한국기계가공학회지
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• 제17권5호
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• pp.58-63
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• 2018

Recently in weapon systems development, the importance of reliability has been emphasized due to the increase in complexity and the rapid development of key components and components. Accordingly, the importance of lifespan testing is increased. However, lifespan testing to verify the reliability of a system is costly and takes a lot of time. Therefore in this paper, it was demonstrated that the most critical item of a bladder type accumulator is the bladder. Fatigue life is sensitive to temperature and pressure, with temperature having more impact. The fatigue life of the bladder was estimated to be 18,140 hr through fatigue analysis, which satisfies the required life expectancy of 10,000 hr.

• International Journal of Internet, Broadcasting and Communication
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• 제16권3호
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• pp.236-241
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• 2024

Due to the recent emphasis on carbon neutrality and environmental regulations, the global electric vehicle (EV) market is experiencing rapid growth. This surge has raised concerns about the recycling and disposal methods for EV batteries. Unlike traditional internal combustion engine vehicles, EVs require unique and safe methods for the recovery and disposal of their batteries. In this process, predicting the lifespan of the battery is essential. Impedance and State of Charge (SOC) analysis are commonly used methods for this purpose. However, predicting the lifespan of batteries with complex chemical characteristics through electrical measurements presents significant challenges. To enhance the accuracy and precision of existing measurement methods, this paper proposes using a Long Short-Term Memory (LSTM) model, a type of deep learning-based recurrent neural network, to diagnose battery performance. The goal is to achieve safe classification through this model. The designed structure was evaluated, yielding results with a Mean Absolute Error (MAE) of 0.8451, a Root Mean Square Error (RMSE) of 1.3448, and an accuracy of 0.984, demonstrating excellent performance.

• 디지털융복합연구
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• 제19권6호
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• pp.113-132
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• 2021

특허수명은 특허가치를 평가하는 척도로 사용되어 왔다. 본 연구에서는 특허수명을 예측하여 개별특허의 가치를 평가함에 있어, 특허의 내적가치요소와 외적가치요소를 하나의 모델로 평가하기 위하여 화학반응속도 추정식으로 널리 알려진 아레니우스식을 사용한 새로운 평가모델을 제시하였다. 한국의 소멸된 특허데이터를 활용하여 평가모델의 성능을 검증하였으며, 선행연구에서 특허평가모델로 사용되었던 SVM, Logistic reg., ANN 모델과 성능을 비교하였다. 결과적으로, 제안한 평가모델이 다른 모델 보다 정확도가 높았으며, 특허권자의 특성을 고려한 상대체감비용지수 반영 시 여러 평가모델에서 정확도가 상승하는 경향을 보였다. 또한, 특허의 예측수명등급과 특허의 실제수명과는 강한 상관관계가 있었다. 이러한 평가모델은 대량의 특허를 객관적으로 신속하게 평가할 수 있으며 특허의 유지여부에 대한 의사결정 혹은 기술거래나 평가에 활용할 수 있다. 특히, 평가목적에 따라 특허만을 평가하거나 사업화주체나 기술적 특성을 고려한 평가가 필요한 경우에 각각 사용될 수 있다.

• 지능정보연구
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• 제28권2호
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• pp.147-170
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• 2022

특허의 사적 가치(private value)를 나타내는 특허수명 추정은 오래전부터 연구되었으나 추정과정에서 선형모델에 의존하는 경우가 대부분이었고, 기계학습 방법을 사용하더라도 변수 간 관계에 대한 해석이나 설명이 부족하였다. 본 연구에서는 특허의 생존 기간이 특허의 가치를 대리한다는 기존 연구결과를 바탕으로 특허 등록 이후의 생존 기간(연장횟수) 예측을 통해 특허의 가치를 추정한다. 이를 위해 1996~2017년까지 미국 특허청(USPTO)에 출원하여 등록된 특허 4,033,414개를 수집하였다. 특허수명을 예측하기 위해 기존 연구에서 특허수명에 영향을 미친다고 밝혀진 특허의 특성, 특허의 소유자 특성, 특허의 발명가 특성을 반영할 수 있는 다양한 변수가 사용되었다. 서로 다른 4개의 모델(Ridge Regression, Random Forest, Feed-forward Neural Network, Gradient Boosting Models)을 생성하고, 모델 학습 과정에서는 5-fold Cross Validation으로 초매개변수 조정이 이루어졌다. 이후 생성된 모델의 성능을 평가하고 특허수명을 추정할 수 있는 예측변수의 상대적 중요도를 제시하였다. 또한, 성능이 우수했던 Gradient Boosting Model을 기반으로 Accumulated Local Effects Plot을 제시하여 예측변수와 특허수명 간 관계를 시각적으로 나타내었다. 마지막으로 모델에 의해서 평가된 개별 특허의 평가 근거를 제시하기 위하여 Kernal SHAP(SHapley Additive exPlanations)을 적용하고 특허평가 시스템에의 적용 가능성을 제시한다. 본 연구는 기존에 특허수명을 추정하는 연구에 누적적으로 기여한다는 점 그리고 선형성을 바탕으로 진행된 기존 특허수명 추정 연구들의 한계를 보완하고 복잡한 비선형 관계를 설명가능한 방식으로 제시하였다는 점에서 학문적 의의가 있다. 또한, 개별 특허의 평가 근거를 도출하는 방법을 소개하고 특허평가 시스템에의 적용 가능성을 제시하였다는 점에서 실무적 의의가 있다.

• Journal of Information Processing Systems
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• 제18권4호
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• pp.457-469
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• 2022

Hydraulic concrete buildings in the northwest of China are often subject to the combined effects of low-temperature frost damage, during drying and wetting cycles, and salt erosion, so the study of concrete deterioration prediction is of major importance. The prediction model of the relative dynamic elastic modulus (RDEM) of four different kinds of modified concrete under the special environment in the northwest of China was established using Grey residual Markov theory. Based on the available test data, modified values of the dynamic elastic modulus were obtained based on the Grey GM(1,1) model and the residual GM(1,1) model, combined with the Markov sign correction, and the dynamic elastic modulus of concrete was predicted. The computational analysis showed that the maximum relative error of the corrected dynamic elastic modulus was significantly reduced, from 1.599% to 0.270% for the BS2 group. The analysis error showed that the model was more adjusted to the concrete mixed with fly ash and mineral powder, and its calculation error was significantly lower than that of the rest of the groups. The analysis of the data for each group proved that the model could predict the loss of dynamic elastic modulus of the deterioration of the concrete effectively, as well as the number of cycles when the concrete reached the damaged state.