• Ocean Systems Engineering
• /
• 제4권1호
• /
• pp.53-62
• /
• 2014

The detection of ship wakes image can demonstrate substantial information regarding on a ship, such as its tonnage, type, direction, and speed of movement. Consequently, the wake target recognition is a favorable way for ship identification. This paper proposes a Local Binary Pattern (LBP) approach to extract image features (wakes) for training an Improved Back Propagation Artificial Neural Network (IBPANN) to identify ship speed. This method is applied to sort and recognize the ship wakes of five different speeds images, the result shows that the detection accuracy is satisfied as expected, the average correctness rates of wakes target recognition at the five speeds may be achieved over 80%. Specifically, the lower ship's speed, the better accurate rate, sometimes it's accuracy could be close to 100%. In addition, one significant feature of this method is that it can receive a higher recognition rate than the nearest neighbor classification method.

• Current Optics and Photonics
• /
• 제1권4호
• /
• pp.402-411
• /
• 2017

Combined LIBS-Raman spectroscopy has been widely studied, due to its complementary capabilities as an elemental analyzer that can acquire signals of atoms, ions, and molecules. In this study, the classification of polymorphs was performed by laser-induced breakdown spectroscopy (LIBS) to overcome the limitation in molecular analysis; the results were verified by Raman spectroscopy. LIBS signals of the $CaCO_3$ polymorphs calcite and aragonite, and $CaSO_4{\cdot}2H_2O$ (gypsum) and $CaSO_4$ (anhydrite), were acquired using a Nd:YAG laser (532 nm, 6 ns). While the molecular study was performed using Raman spectroscopy, LIBS could also provide sufficient key data for classifying samples containing different molecular densities and structures, using the peculiar signal ratio of $5s{\rightarrow}4p$ for the orbital transition of two polymorphs that contain Ca. The basic principle was analyzed by electronic motion in plasma and electronic transition in atoms or ions. The key factors for the classification of polymorphs were the different electron quantities in the unit-cell volume of each sample, and the selection rule in electric-dipole transitions. The present work has extended the capabilities of LIBS in molecular analysis, as well as in atomic and ionic analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권5호
• /
• pp.2171-2185
• /
• 2020

In order to judge that whether the vehicles in different images which are captured by surveillance cameras represent the same vehicle or not, we proposed a novel vehicle face recognition algorithm based on improved Nonnegative Matrix Factorization (NMF), different from traditional vehicle recognition algorithms, there are fewer effective features in vehicle face image than in whole vehicle image in general, which brings certain difficulty to recognition. The innovations mainly include the following two aspects: 1) we proposed a novel idea that the vehicle type can be determined by a few key regions of the vehicle face such as logo, grille and so on; 2) Through adding weight, sparseness and classification property constraints to the NMF model, we can acquire the effective feature bases that represent the key regions of vehicle face image. Experimental results show that the proposed algorithm not only achieve a high correct recognition rate, but also has a strong robustness to some non-cooperative factors such as illumination variation.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권8호
• /
• pp.2881-2894
• /
• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

• 한국시뮬레이션학회논문지
• /
• 제19권3호
• /
• pp.99-108
• /
• 2010

본 논문의 주요 내용은 인터넷의 웹서비스 공격에 대한 효과적인 대책을 수립하기 위한 연구로서, 웹서비스 대상으로 하는 공격 정보를 네트워크 계층 및 호스트 구성단위 별 취약점을 분류하며, 서비스 유형에 따른 공격범위 산정 및 분류방법에 대한 모색을 하고자 한다. 이 논문 자료를 이용하여 웹 서비스 공격 정보들의 분석정보를 축척을 통한 다양한 웹 보안 강화 사업 추진의 핵심 정보로 활용될 수 있으며, 웹사이트 공격 탐지 및 대응을 위한 관련 보안 연구의 기초자료 및 정보 보호 산업 활성화에 기여할 수 있다.

• 국제학술발표논문집
• /
• The 1th International Conference on Construction Engineering and Project Management
• /
• pp.662-666
• /
• 2005

Using data gathered from expert opinion of plant and equipment professionals; this paper presents the key variables that may constitute a maintenance proficient plant operator. The Multivariate Discriminant Analysis (MDA) was applied to generate data and was tested for sensitivity analysis. Results showed that the MDA model was able to classify plant operators' proficiency at 94.10 percent accuracy and determined nine (9) key variables of a maintenance proficient plant operator. The key variables included: i) number of years of experience as equipment operator (PQ1); ii) eye-hand coordination (PQ9); iii) eye-hand-foot coordination (PQ10); iv) planning skills (TE16); v) pay/wage (MQ1); vi) work satisfaction (MQ4); vii) operator responsibilities as defined by management (MF1); viii) clear management policies (MF4); and ix) management pay scheme (MF5). The classification procedure of nine variables formed the general model with the equation viz: OMP (general) = 0.516PQ1 + 0.309PQ9 + 0.557PQ10 + 0.831TE16 + 0.8MQ1 + 0.0216MQ4 + 0.136MF1 + 0.28MF4 + 0.332MF5 - 4.387

• 정보관리학회지
• /
• 제35권2호
• /
• pp.37-62
• /
• 2018

문헌정보학 분야의 국내 학술지 논문으로 구성된 문헌집합을 대상으로 기계학습에 기초한 자동분류의 성능에 영향을 미치는 요소들을 검토하였다. 특히, "정보관리학회지"에 수록된 논문에 주제 범주를 자동 할당하는 분류 성능 측면에서 용어 가중치부여 기법, 학습집합 크기, 분류 알고리즘, 범주 할당 방법 등 주요 요소들의 특성을 다각적인 실험을 통해 살펴보았다. 결과적으로 분류 환경 및 문헌집합의 특성에 따라 각 요소를 적절하게 적용하는 것이 효과적이며, 보다 단순한 모델의 사용으로 상당히 좋은 수준의 성능을 도출할 수 있었다. 또한, 국내 학술지 논문의 분류는 특정 논문에 하나 이상의 범주를 할당하는 복수-범주 분류(multi-label classification)가 실제 환경에 부합한다고 할 수 있다. 따라서 이러한 환경을 고려하여 단순하고 빠른 분류 알고리즘과 소규모의 학습집합을 사용하는 최적의 분류 모델을 제안하였다.

• 디지털융복합연구
• /
• 제6권4호
• /
• pp.177-183
• /
• 2008

This paper aims to offer a solution based on intelligent document classification to create a user-centric information retrieval system allowing user-centric linguistic expression. So, structures expressing user intention and fine document classifying process using EBL, similarity, knowledge base, user intention, are proposed. To overcome the problem requiring huge and exact semantic information, a hybrid process is designed integrating keyword, thesaurus, probability and user intention information. User intention tree hierarchy is build and a method of extracting group intention between key words and user intentions is proposed. These structures and processes are implemented in HDCI(Hybrid Document Classification with Intention) system. HDCI consists of analyzing user intention and classifying web documents stages. Classifying stage is composed of knowledge base process, similarity process and hybrid coordinating process. With the help of user intention related structures and hybrid coordinating process, HDCI can efficiently categorize web documents in according to user's complex linguistic expression with small priori information.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 하계종합학술대회 논문집(3)
• /
• pp.169-172
• /
• 2000

IP Switching is a new routing technology proposed to improve the performance of IP routers. Flow classification is one of the key issues in IP Switching. To achieve better performance, flow classification should be matched to the varying IP traffic and an IP switch should make use of its hardware switching resources as fully as possible. This paper proposes an adaptive flow classification algorithm for IP Switching. By dynamically adjusting the values of its control parameters in response to the present usage of the hardware switching resources, this adaptive algorithm can efficiently match the varying IP traffic and thus improve the performance of an IP switch.

• 디지털산업정보학회논문지
• /
• 제10권2호
• /
• pp.203-211
• /
• 2014

In recent highly competitive business environment, collaboration has become one of the important business strategies for companies to survive and/or prosper. There are many different types of collaboration strategies, and it is crucial for companies to select the right ones according to the types of collaboration they require. To select the right type of collaboration options for business, in the past research, there have been two important criteria to classify collaboration types, namely governance (who makes key decisions - one kingpin participant or all players?) and membership (can anyone participate, or just select players?). In this research, we add a new classification criterion, recognition of collaboration purpose, which means whether collaborators know or do not know the purpose of collaboration in advance. Recently, we see many cases in which social media data are used in many unknown purposes a priori. In this research, we add such cases to develop new classification model.