• Title/Summary/Keyword: Co-Classification Analysis

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Identification of Sweet Pepper Greenhouse by Analysis of Environmental Data in Greenhouse (온실 내 환경데이터 분석을 통한 파프리카 온실의 식별)

  • Kim, Na-eun;Lee, Kyoung-geun;Lee, Deog-hyun;Moon, Byeong-eun;Park, Jae-sung;Kim, Hyeon-tae
    • Journal of Bio-Environment Control
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    • v.30 no.1
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    • pp.19-26
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    • 2021
  • In this study, analysis was performed to identify three greenhouses located in the same area using principal component analysis (PCA) and linear discrimination analysis (LDA). The environmental data in the greenhouse were from 3 farms in the same area, and the values collected at 1 hour intervals for a total of 4 weeks from April 1 to April 28 were used. Before analyzing the data, it was pre-processed to normalize the data, and the analysis was performed by dividing it into 80% of the training data and 20% of the test data. As a result of PCA and LDA analysis, it was found that PCA classification accuracy was 57.51% and LDA classification was 67.06%, indicating that it can be classified by greenhouse. Based on the farmhouse data classified in advance, the data of the new environment can be classified into specific groups to determine the tendency of the data. Such data is judged to be a way to increase the utilization of data by facilitating identification.

Improvement in Grade of Sericite Ore by Dry Beneficiation (건식정제에 의한 견운모광의 품위향상연구)

  • Cho, Keon-Joon;Kim, Yun-Jong;Park, Hyun-Hae;Cho, Sung-Baek
    • Korean Journal of Materials Research
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    • v.19 no.4
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    • pp.212-219
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    • 2009
  • A study on the dry beneficiation of sericite occurring in the Daehyun Mine of the Republic of Korea region as performed by applying selective grinding and air classification techniques. Quartz and sericite occurred in the raw ore as major components. The results of liberation using a ball mill and an impact mill showed that the contents of $R_2O$ were increased while $SiO_2$ was decreased in proportion to decreasing particle size. According to the XRD, XRF analysis and the EDS of SEM analysis, the ball mill gave a better grade product in $R_2O$ content than the impact mill when the particle size was the same. When the raw ore was ground by the impact mill with arotor speed 57.6 m/sec and then followed by 15,000rpm classification using an air classifier, the chemical composition of the over flowed product was 49.65wt% $SiO_2$, 32.15wt% $Al_2O_3$, 0.13wt% $Fe_2O_3$, 10.37wt% $K_2O$, and 0.14wt% $Na_2O$. This result indicates that the $R_2O$ contents were increased by 49.5% compared to that of the raw ore. From these results described above, it is suggested that hard mineral such as Quartz little ground by selective grinding using impact mill whereas soft mineral such as sericite easily ground to small size. As a result of that hard minerals can be easily removed from the finely ground sericite by air classification and the $R_2O$ grade of thus obtained concentrate was improved to higher than 10wt% which can be used for ceramics raw materials.

The vegetation analysis of Northern region at Jungnang riverside - Between two bridges of Wallgae 1 and Sangdo - (서울시 중랑천 북부구간 하천변 식생과 식물상 분석 - 월계1교에서 상도교 구간을 대상으로 -)

  • Lee, Sanghwa;Lee, Kyunghee;Jeong, Jongcheol
    • Journal of Environmental Impact Assessment
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    • v.23 no.4
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    • pp.315-322
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    • 2014
  • After the modern industrial revolution, rivers in cities became covered and disappeared due to the pressure to develop them. Likewise, their function which is to serve as the basis of natural ecology system in the cities began to be damaged. This research demonstrated that there are a total of 268 categories when it comes to the list of plants, including 64 families, 179 genera, 230 species, 36 varieties, and 1 subspecies. When the relative abundance of the plants that were found at the target research site was studied, the secondary survey demonstrated Bromus japonicus 22.97, Artemisia princeps var. orientalis 16.76 and Erigeron annuus 15.69 while third survey demonstrated Digitaria ciliaris 26.78, Ambrosia trifida 16.29 and Aster pilosus 14.31. There were 54 species of naturalized plants that appeared. Analysis demonstrated annual plant 23 classification category (43%), perennial 11 classification category (20%), multi-perennation 17 classification category (31%), woody plant 3 classification category (6%) and others. When the naturalized plants that were found at the target research site were analyzed by the place of origin, North America and EU took up 76%, which accounts for 3/4 of the all the naturalized plants. At the target research site, naturalization degree of 5 pertained to 22 classification category (41%), which was the highest, followed by 19 classification category (35%) with naturalization degree of 3, 8 classification category (15%) with naturalization degree of 2 and 5 classification category (9%) with naturalization degree of 4 in the order mentioned. Flora of Jungnangcheon did not manifest any change compared to 10 years ago. Thus, it is necessary to increase of biodiversity efforts to improve SeoulCity's natural environment and cityscape.

Application of Multivariate Statistics and Geostatistical Techniques to Identify the Distribution Modes of the Co, Ni, As and Au-Ag ore in the Bou Azzer-East Deposits (Central Anti-Atlas Morocco)

  • Souiri, Muhammad;Aissa, Mohamed;Gois, Joaquim;Oulgour, Rachid;Mezougane, Hafid;El Azmi, Mohammed;Moussaid, Azizi
    • Economic and Environmental Geology
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    • v.53 no.4
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    • pp.363-381
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    • 2020
  • The polymetallic Co, Ni, Cu, As, Au, and Ag deposits of Bou Azzer East are located in the western part of the Bou Azzer inlier in the Central Anti Atlas, Morocco. Six stages of emplacement of the mineralization have been identified. Precious metals (native gold and electrum) are present in all stages of this deposit except the early nickeliferous stage. From the Statistical analysis of the Co, As, Ni, Au, and Ag contents of a set of 501 samples, shows that the Pearson correlation coefficient between As-Co elements (0.966) is the highest followed by that of the Au-Ag couple (0.506). Principal component analysis (PCA) and hierarchical ascending classification (HAC) of the grades show, that Ni is associated with the pair (As-Co) and Cu is rather related to the pair (Au-Ag). The kriging maps show that the highest values of the Co, As and Ni appear in the contact of the serpentinite with other facies, as for those of Au and Ag, in addition to anomalous zones concordant with those of Co, Ni and As, they show anomalies at the extreme South and North of the study area. The development of the anomalous Au and Ag zones is mainly along the N40-50°E and N145°E directions.

Consideration for IMO Type C Independent Tank Rule Scantling Process and Evaluation Methods (IMO C형 독립탱크의 설계치수 계산과정 및 평가방법에 대한 고찰)

  • Heo, Kwang-hyun;Kang, Won-sik;Park, Bong-qyun
    • Special Issue of the Society of Naval Architects of Korea
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    • 2017.10a
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    • pp.93-104
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    • 2017
  • IMO type C independent tank is one of the cargo containment system specified on IGC code. It is normally adopted for small and medium size liquefied gas carrier's cargo containment system and it can be applied to fuel tank of LNG fueled vessel. This study focuses on rule scantling process and evaluation methods in early design stage of type C independent tank. Actual design results of 22K LPG/Ammonia/VCM carrier's No.2 cargo tank are demonstrated. This paper presents the calculation methods of design acceleration and liquid height for internal design pressure as defined on IGC code. And this paper shows the applied results of classification rules about shell thickness requirement and buckling strength. Additionally this paper deals with evaluation methods of structural strength and cumulative fatigue damage using FE analysis.

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Exploring Potential Application Industry for Fintech Technology by Expanding its Terminology: Network Analysis and Topic Modelling Approach (용어 확장을 통한 핀테크 기술 적용가능 산업의 탐색 :네트워크 분석 및 토픽 모델링 접근)

  • Park, Mingyu;Jeon, Byeongmin;Kim, Jongwoo;Geum, Youngjung
    • The Journal of Society for e-Business Studies
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    • v.26 no.1
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    • pp.1-28
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    • 2021
  • FinTech has been discussed as an important business area towards technology-driven financial innovation. The term fintech is a combination of finance and technology, which means ICT technology currently associated with all finance areas. The popularity of the fintech industry has significantly increased over time, with full investment and support for numerous startups. Therefore, both academia and practice tried to analyze the trend of the fintech area. Despite the fact, however, previous research has limitations in terms of collecting relevant databases for fintech and identifying proper application areas. In response, this study proposed a new method for analyzing the trend of Fintech fields by expanding Fintech's terminology and using network analysis and topic modeling. A new Fintech terminology list was created and a total of 18,341 patents were collected from USPTO for 10 years. The co-classification analysis and network analysis was conducted to identify the technological trends of patent classification. In addition, topic modeling was conducted to identify the trends of fintech in order to analyze the contents of fintech. This study is expected to help both managers and investors who want to be involved in technology-driven financial services seize new FinTech technology opportunities.

Building and Analyzing Panic Disorder Social Media Corpus for Automatic Deep Learning Classification Model (딥러닝 자동 분류 모델을 위한 공황장애 소셜미디어 코퍼스 구축 및 분석)

  • Lee, Soobin;Kim, Seongdeok;Lee, Juhee;Ko, Youngsoo;Song, Min
    • Journal of the Korean Society for information Management
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    • v.38 no.2
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    • pp.153-172
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    • 2021
  • This study is to create a deep learning based classification model to examine the characteristics of panic disorder and to classify the panic disorder tendency literature by the panic disorder corpus constructed for the present study. For this purpose, 5,884 documents of the panic disorder corpus collected from social media were directly annotated based on the mental disease diagnosis manual and were classified into panic disorder-prone and non-panic-disorder documents. Then, TF-IDF scores were calculated and word co-occurrence analysis was performed to analyze the lexical characteristics of the corpus. In addition, the co-occurrence between the symptom frequency measurement and the annotated symptom was calculated to analyze the characteristics of panic disorder symptoms and the relationship between symptoms. We also conducted the performance evaluation for a deep learning based classification model. Three pre-trained models, BERT multi-lingual, KoBERT, and KcBERT, were adopted for classification model, and KcBERT showed the best performance among them. This study demonstrated that it can help early diagnosis and treatment of people suffering from related symptoms by examining the characteristics of panic disorder and expand the field of mental illness research to social media.

An Analysis of Human Error Mode and Type in the Railway Accidents and Incidents (철도 사고 및 장애의 인적오류 유형 분석)

  • Ko, Jong-Hyun;Jung, Won-Dea;Kim, Jae-Whan
    • Journal of the Korean Society of Safety
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    • v.22 no.4
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    • pp.66-71
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    • 2007
  • Human error is one of the major contributors to the railway accidents or incidents. In order to develop an effective countermeasure to remove or reduce human errors, a systematic analysis should be preferentially performed to identify their causes, characteristics, and types of human error induced in accidents or incidents. This paper introduces a case study for human error analysis of the railway accidents and incidents. For the case study, more than 1,000 domestic railway accidents or incidents that happened during the year of 2004 have been investigated and a detailed error analysis was performed on the selected 90 cases, which were obviously caused by human error. This paper presents a classification structure for human error analysis, and summarizes the analysis results such as causes of the events, error modes and types, related worker, and task type.

Convolutional Neural Network with Expert Knowledge for Hyperspectral Remote Sensing Imagery Classification

  • Wu, Chunming;Wang, Meng;Gao, Lang;Song, Weijing;Tian, Tian;Choo, Kim-Kwang Raymond
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.8
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    • pp.3917-3941
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    • 2019
  • The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.

Verification of Effective Support Points of Stern Tube Bearing Using Nonlinear Elastic Multi-Support Bearing Elements (비선형 탄성 다점지지 베어링 요소를 이용한 선미관 베어링의 유효지지점 검증)

  • Choung, Joon-Mo;Choe, Ick-Heung;Kim, Kyu-Chang
    • Journal of the Society of Naval Architects of Korea
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    • v.42 no.5 s.143
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    • pp.479-486
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    • 2005
  • The final goal of shift alignment design is that the bearing reaction forces or mean pressures are within design boundaries for various service conditions of a ship. However, it is found that calculated bearing load can be substantially variable according to the locations of the effective support points of after sterntube bearing which are determined by simple calculation or assumption suggested by classification societies. A new analysis method for shaft alignment calculation is introduced in order to resolve these problems. Key concept of the new method is featured by adopting both nonlinear elastic and multi-support elements to simulate a bearing support Hertz contact theory is basically applied for nonlinear elastic stiffness calculation instead of the projected area method suggested by most of classification societies. Three loading conditions according to the bearing offset and the hydrodynamic moment and twelve models according to the locations of the effective support points of sterntube bearings are prepared to carry out quantitative verifications for an actual shafting system of 8000 TEU class container vessel. It is found that there is relatively large difference between assumed and calculated effective support points.