• Proceedings of the Korea Information Processing Society Conference
• /
• 2006.11a
• /
• pp.645-648
• /
• 2006

생물학적 데이터 서열에는 크게 DNA 서열과 단백질 서열이 있다. 이들 서열 데이터들은 여러 데이터베이스에 걸쳐 매우 방대한 양을 가지고 있으며, 각각의 서열은 수백 또는 수천 개의 항목들을 가지고 있어 길이가 매우 길다. 일반적으로 유전적인 변형, 또는 변이로부터 보존된 영역이나 특정 패턴들을 서열 안에 포함하고 있는데 생물학적 서열 데이터에서 보존된 영역이나 패턴들은 계통발생학적 근거로 활용 될 수도 있으며 기능과 밀접한 관계를 가지기도 한다. 따라서 서열들로부터 빈번하게 발생하는 패턴을 발견하고자 하는 알고리즘 개발이 요구되고 있다. 초창기 Apriori 알고리즘을 변형하여 빈발 패턴을 발견하고자 하는 노력들로부터 근래에는 PrefixSpan 트리를 이용하여 효과적으로 성능을 개선하고 있지만 아직까지는 여러 번의 데이터베이스 접근이 요구되고 있어 성능저하가 발생한다. 이에 본 논문에서는 접미사 트리를 변형하여 데이터베이스 접근을 획기적으로 줄이고 많은 서열들로부터 빈번하게 발생하는 연속적인 서열을 효과적으로 발견하는 방법을 제안한다.

• Journal of Information Processing Systems
• /
• v.10 no.4
• /
• pp.543-554
• /
• 2014

It is difficult for mobile learners to maintain a high level of concentration when learning content for more than an hour while they are on the move. Despite the attention span issue, many m-learning systems still provide their mobile learners with the same content once used in e-learning systems. This has called for an investigation to identify the suitable characteristics of the m-learning environment. With this in mind, we have conducted a survey in hopes of determining the requirements for developing more suitable m-learning content. Based on the results of the survey, we have developed a content model comprised of two types: a segment type and a supplement type. In addition, we have implemented a prototype system of the content model for Apple iPhones and Android smartphones in order to investigate a feasibility study of the model application.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.583-585
• /
• 2015

도시농촌을 대상으로 스마트팜(Smart-Farm) 솔루션은 현재 많이 출시되어 운용되고 있다. 하지만, 대부분의 스마트팜 제품들은 시설재배의 유형, 재배대상 작물의 특성 및 시설재배관리자(사용자)의 요구를 반영할 수 있는 개방형 시스템과는 거리가 멀다. 본 연구팀에서는 대규모의 시설 농가를 대상으로 통합관제기술과 스마트제어, 센서기술을 적용한 단동형 스마트팜 관리시스템을 개발 및 상용화를 목표로 하고 있으며, 이는 각 작물의 특징과 사용자의 요구에 따라 관리시스템의 유연성 및 확장성을 고려하여 설계하고 있다. 본 논문에서는 해당 연구의 일환으로 단일시설재배작물로는 세계 최대 생산지인 경상북도 성주참외를 대상으로 사용자 편의성이 증진된 단동형 농작물관리시스템을 설계하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.11a
• /
• pp.362-363
• /
• 2012

외국어 능력이 현대 사회에서 요구하는 필수적인 요소 중에 하나이다. 본 논문에서는 기존의 외국어 능력을 평가하는 능력 시험이 아닌 언어심리학적 관점으로 외국어 능력을 평가하는 방법을 제안한다. 외국어를 처리하는데 있어서 외국어를 모국어를 바꾸는 언어인지 과정이 필요하다. 본 논문에서는 이러한 언어 인지 능력을 측정하는 Reading LDT, Listening LDT, Verbal Span, Yes-No task(Semantic), Same-Different task실험을 제안한다. 해당 과제들은 각각 피험자의 읽기, 듣기, 기억, 의미적 결정, 변환 능력을 측정하는 과제이다.

• Journal of Ceramic Processing Research
• /
• v.13 no.spc1
• /
• pp.145-148
• /
• 2012

Spherical silica aerogel powders were fabricated via an emulsion polymerization method from a water glass. A water-in-oil emulsion, in which droplets of a silicic acid solution are emulsified with span 80 (surfactant) in n-hexane, was produced by a high power homogenizer. After gelation, the surface of the spherical silica hydrogels was modified using a TMCS (trimethylchlorosilane)/n-hexane solution followed by solvent exchange from water to n-hexane. Hydrophobic silica wet gel droplets were dried at 80 ℃ under ambient pressure. A perfect spherical silica aerogel powder between1 to 12 ㎛ in diameter was obtained and its size can be controlled by mixing speed. The tapping density, pore volume, and BET surface area of the silica aerogel powder were approximately 0.08 g·cm-3, 3.5 ㎤·g-1 and 742 ㎡·g-1, respectively.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.626-628
• /
• 2021

사건 관계 추출 태스크는 구조화되지 않은 텍스트 데이터에서 사건의 구조화된 표현을 얻는 것이다. 하나의 문장에서도 많은 정보를 얻을 수 있는 중요한 태스크임에도 불구하고, 다양한 사전 학습 모델을 적용한 연구는 아직 활발하게 연구되지 않고 있다. 따라서 본 연구에서 사전 학습된 모델의 임베딩 기법 중 BERT, RoBERTa, SpanBERT에 각각 base, large 아키텍처를 적용하여 실험하였다. 사건을 식별하기 위한 trigger와 해당 trigger의 세부 argument를 식별하기 위한 분류기를 상위레이어로 각각 설계하였고, 다양한 배치 크기를 적용하여 실험하였다. 성능평가는 trigger/argument 각각 F1 score를 적용하였고, 결과는 RoBERTa large 모델에서 좋은 성능을 보인 것을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.05a
• /
• pp.647-649
• /
• 2023

Sentiment analysis as part of natural language processing (NLP) has received much attention following the demand to understand people's opinions. Aspect-based sentiment analysis (ABSA) is a fine-grained subtask from sentiment analysis that aims to classify sentiment at the aspect level. Throughout the years, researchers have formulated ABSA into various tasks for different scenarios. Unlike the early works, the current ABSA utilizes many elements to improve performance and provide more details to produce informative results. These ABSA formulations have provided greater challenges for researchers. However, it is difficult to explore ABSA's works due to the many different formulations, terms, and results. In this paper, we conduct a comparative analysis of recent studies on ABSA. We mention some key elements, problem formulations, and datasets currently utilized by most ABSA communities. Also, we conduct a short review of the latest papers to find the current state-of-the-art model. From our observations, we found that span-level representation is an important feature in solving the ABSA problem, while multi-task learning and generative approach look promising. Finally, we review some open challenges and further directions for ABSA research in the future.

• The KIPS Transactions:PartD
• /
• v.15D no.2
• /
• pp.155-162
• /
• 2008

Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological dataset with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.61-67
• /
• 1997

The electronic speckle pattern interferometer (ESPI) has been applied to many technical problems such as deformation and displacement measurement, strain visualization and surface roughness monitoring. In this study, we used an ESPI system based on the dual beam speckle interferometer method in order to measure in-plane displacement and vibration mode using the ESIP technique. This research was carried out for the purpose of applying the vibration analysis method employing Electro-Optic holographic interference technique to the vibration analysis of uniform rectangular cantilevers plate(SS400,STS304) with cantilevers span to breadth ratio of 150 by 75. And thickness of 1mm and 0.8mm respectively. We improved the ESPI technique in order to obtain the distribution of displacement component resolved in one direction through a CCD camera combined with an image processing system. To certify and to assess the accuracy in measuring by this ESPI, the results obtained with the speckle method and vibration mode analysis are to be compared with those results by Warbuton's Theoretical expression and vibration made in FEM analysis.

• Smart Structures and Systems
• /
• v.11 no.4
• /
• pp.365-386
• /
• 2013

Monitoring systems currently applied to concrete bridges include strain gauges, inclinometers, accelerometers and displacement transducers. In general, vertical displacements are one of the parameters that more often need to be assessed because their information reflects the overall response of the bridge span. However, the implementation of systems to continuously and directly observe vertical displacements is known to be difficult. On the other hand, strain gauges and inclinometers are easier to install, but their measurements provide no more than indirect information regarding the bridge deflection. In this context, taking advantage of the information collected through strain gauges and inclinometers, and the processing capabilities of current computers, a procedure to evaluate bridge girder deflections based on polynomial functions is presented. The procedure has been implemented in an existing software system - MENSUSMONITOR -, improving the flexibility in the data handling and enabling faster data processing by means of real time visualization capabilities. Benefiting from these features, a comprehensive analysis aiming at assessing the suitability of polynomial functions as an approximate solution for deflection curves, is presented. The effect of boundary conditions and the influence of the order of the polynomial functions on the accuracy of results are discussed. Some recommendations for further instrumentation plans are provided based on the results of the present analysis. This work is supported throughout by monitoring data collected from a laboratory beam model and two full-scale bridges.