• Title/Summary/Keyword: Information value approach

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How to Measure the Agglomeration Effects of Industrial Cluster : A Case Study of the FOODPOLIS ( KOREA NATIONAL FOOD CLUSTER ) (산업클러스터 효과 추정 방법에 관한 연구 : 국가식품클러스터조성사업 사례를 중심으로)

  • Kim, Jung-Wook;Kim, Suk-Young;Yang, Seung-Min
    • Journal of the Economic Geographical Society of Korea
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    • v.15 no.1
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    • pp.42-62
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    • 2012
  • This paper suggests a genuine method to estimate the agglomeration effects of Industrial Cluster focusing on the FOODPOLIS (KOREA NATIONAL FOOD CLUSTER). In this study, we will focus on two issues related to the clustering effect. First, Clusters affect productivity, and a cluster allows companies to operate more productively in inputs; accessing technology, human resource, information, services, and needed institutions. Second, we assume that the effects of Industrial Cluster can be estimated from measurement on differency of an added value between large-scale enterprises and smaller ones. To demonstrate effectiveness of this approach, the estimated effect was compared with that from the related study (A Mini-Cluster). Industry Clusters have been considered as critical factors for regional competitiveness and economic revitalization. For this, the government and local government should find a way and strategy to provide useful contents that can attract the participation of firms and to secure strategic positioning and competition strategies.

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Elevation Correction of Multi-Temporal Digital Elevation Model based on Unmanned Aerial Vehicle Images over Agricultural Area (농경지 지역 무인항공기 영상 기반 시계열 수치표고모델 표고 보정)

  • Kim, Taeheon;Park, Jueon;Yun, Yerin;Lee, Won Hee;Han, Youkyung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.3
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    • pp.223-235
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    • 2020
  • In this study, we propose an approach for calibrating the elevation of a DEM (Digital Elevation Model), one of the key data in realizing unmanned aerial vehicle image-based precision agriculture. First of all, radiometric correction is performed on the orthophoto, and then ExG (Excess Green) is generated. The non-vegetation area is extracted based on the threshold value estimated by applying the Otsu method to ExG. Subsequently, the elevation of the DEM corresponding to the location of the non-vegetation area is extracted as EIFs (Elevation Invariant Features), which is data for elevation correction. The normalized Z-score is estimated based on the difference between the extracted EIFs to eliminate the outliers. Then, by constructing a linear regression model and correcting the elevation of the DEM, high-quality DEM is produced without GCPs (Ground Control Points). To verify the proposed method using a total of 10 DEMs, the maximum/minimum value, average/standard deviation before and after elevation correction were compared and analyzed. In addition, as a result of estimating the RMSE (Root Mean Square Error) by selecting the checkpoints, an average RMSE was derivsed as 0.35m. Comprehensively, it was confirmed that a high-quality DEM could be produced without GCPs.

An Improvement in K-NN Graph Construction using re-grouping with Locality Sensitive Hashing on MapReduce (MapReduce 환경에서 재그룹핑을 이용한 Locality Sensitive Hashing 기반의 K-Nearest Neighbor 그래프 생성 알고리즘의 개선)

  • Lee, Inhoe;Oh, Hyesung;Kim, Hyoung-Joo
    • KIISE Transactions on Computing Practices
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    • v.21 no.11
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    • pp.681-688
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    • 2015
  • The k nearest neighbor (k-NN) graph construction is an important operation with many web-related applications, including collaborative filtering, similarity search, and many others in data mining and machine learning. Despite its many elegant properties, the brute force k-NN graph construction method has a computational complexity of $O(n^2)$, which is prohibitive for large scale data sets. Thus, (Key, Value)-based distributed framework, MapReduce, is gaining increasingly widespread use in Locality Sensitive Hashing which is efficient for high-dimension and sparse data. Based on the two-stage strategy, we engage the locality sensitive hashing technique to divide users into small subsets, and then calculate similarity between pairs in the small subsets using a brute force method on MapReduce. Specifically, generating a candidate group stage is important since brute-force calculation is performed in the following step. However, existing methods do not prevent large candidate groups. In this paper, we proposed an efficient algorithm for approximate k-NN graph construction by regrouping candidate groups. Experimental results show that our approach is more effective than existing methods in terms of graph accuracy and scan rate.

A Study on Machine Learning-Based Real-Time Gesture Classification Using EMG Data (EMG 데이터를 이용한 머신러닝 기반 실시간 제스처 분류 연구)

  • Ha-Je Park;Hee-Young Yang;So-Jin Choi;Dae-Yeon Kim;Choon-Sung Nam
    • Journal of Internet Computing and Services
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    • v.25 no.2
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    • pp.57-67
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    • 2024
  • This paper explores the potential of electromyography (EMG) as a means of gesture recognition for user input in gesture-based interaction. EMG utilizes small electrodes within muscles to detect and interpret user movements, presenting a viable input method. To classify user gestures based on EMG data, machine learning techniques are employed, necessitating the preprocessing of raw EMG data to extract relevant features. EMG characteristics can be expressed through formulas such as Integrated EMG (IEMG), Mean Absolute Value (MAV), Simple Square Integral (SSI), Variance (VAR), and Root Mean Square (RMS). Additionally, determining the suitable time for gesture classification is crucial, considering the perceptual, cognitive, and response times required for user input. To address this, segment sizes ranging from a minimum of 100ms to a maximum of 1,000ms are varied, and feature extraction is performed to identify the optimal segment size for gesture classification. Notably, data learning employs overlapped segmentation to reduce the interval between data points, thereby increasing the quantity of training data. Using this approach, the paper employs four machine learning models (KNN, SVC, RF, XGBoost) to train and evaluate the system, achieving accuracy rates exceeding 96% for all models in real-time gesture input scenarios with a maximum segment size of 200ms.

Assessment of wetland ecosystem services for ecological management in the border area of the Han River Estuary (한강하구 접경지역 습지 생태계 서비스 평가를 통한 생태적 관리 방안 분석)

  • Hyun-Ah Choi;Donguk Han;Woo-Kyun Lee;Cholho Song
    • Korean Journal of Environmental Biology
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    • v.41 no.4
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    • pp.683-696
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    • 2023
  • The conservation of wetland ecosystems has a significant role in climate change. Notably, the Han River Protected Area, including the Siam-ri wetland and Janghang wetland, provides high biodiversity value. Thus, it is necessary to comprehensively evaluate the function and value of wetland ecosystems. This study evaluated the ecosystem services of Siam-ri and Janghang Wetlands located in the Han River Protected Area using the Rapid Assessment Wetland Ecosystem Services approach, a function-oriented ecosystem analysis. The results were calculated using the Ecosystem Services Index formula to analyze wetland ecosystem services. We also assessed the key ecosystem services based on a focus group interview. We identified that the supporting and cultural services index scores were relatively high in the study area. The results can provide helpful information for sustainable wetland conservation, conservation planning as primary data, and raising awareness for the Han River Protected Area.

Importance of End User's Feedback Seeking Behavior for Faithful Appropriation of Information Systems in Small and Medium Enterprises (중소기업 환경에서의 합목적적 정보시스템 활용을 위한 최종사용자 피드백 탐색행위의 중요성)

  • Shin, Young-Mee;Lee, Joo-Ryang;Lee, Ho-Geun
    • Asia pacific journal of information systems
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    • v.17 no.4
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    • pp.61-95
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    • 2007
  • Small-and-medium sized enterprises(SMEs) represent quite a large proportion of the industry as a whole in terms of the number of enterprises or employees. However researches on information system so far have focused on large companies, probably because SMEs were not so active in introducing information systems as larger enterprises. SMEs are now increasingly bringing in information systems such as ERP(Enterprise Resource Planning Systems) and some of the companies already entered the stage of ongoing use. Accordingly, researches should deal with the use of information systems by SME s operating under different conditions from large companies. This study examined factors and mechanism inducing faithful appropriation of information systems, in particular integrative systems such as ERP, in view of individuals` active feedback-seeking behavior. There are three factors expected to affect end users` feedback-seeking behavior for faithful appropriation of information systems. They are management support, peer IT champ support, and IT staff support. The main focus of the study is on how these factors affect feedback-seeking behavior and whether the feedback-seeking behavior plays the role of mediator for realizing faithful appropriation of information systems by end users. To examine the research model and the hypotheses, this study employed an empirical method based on a field survey. The survey used measurements mostly employed and verified by previous researches, while some of the measurements had gone through minor modifications for the purpose of the study. The survey respondents are individual employees of SMEs that have been using ERP for one year or longer. To prevent common method bias, Task-Technology Fit items used as the control variable were made to be answered by different respondents. In total, 127 pairs of valid questionnaires were collected and used for the analysis. The PLS(Partial Least Squares) approach to structural equation modeling(PLS-Graph v.3.0) was used as our data analysis strategy because of its ability to model both formative and reflective latent constructs under small-and medium-size samples. The analysis shows Reliability, Construct Validity and Discriminant Validity are appropriate. The path analysis results are as follows; first, the more there is peer IT champ support, the more the end user is likely to show feedback-seeking behavior(path-coefficient=0.230, t=2.28, p<0.05). In other words, if colleagues proficient in information system use recognize the importance of their help, pass on what they have found to be an effective way of using the system or correct others' misuse, ordinary end users will be able to seek feedback on the faithfulness of their appropriation of information system without hesitation, because they know the convenience of getting help. Second, management support encourages ordinary end users to seek more feedback(path-coefficient=0.271, t=3.06, p<0.01) by affecting the end users' perceived value of feedback(path-coefficient=0.401, t=6.01, p<0.01). Management support is far more influential than other factors that when the management of an SME well understands the benefit of ERP, promotes its faithful appropriation and pays attention to employees' satisfaction with the system, employees will make deliberate efforts for faithful appropriation of the system. However, the third factor, IT staff support was found not to be conducive to feedback-seeking behavior from end users(path-coefficient=0.174, t=1.83). This is partly attributable to the fundamental reason that there is little support for end users from IT staff in SMEs. Even when IT staff provides support, end users may find it less important than that from coworkers more familiar with the end users' job. Meanwhile, the more end users seek feedback and attempt to find ways of faithful appropriation of information systems, the more likely the users will be able to deploy the system according to the purpose the system was originally meant for(path-coefficient=0.35, t=2.88, p<0.01). Finally, the mediation effect analysis confirmed the mediation effect of feedback-seeking behavior. By confirming the mediation effect of feedback-seeking behavior, this study draws attention to the importance of feedback-seeking behavior that has long been overlooked in research about information system use. This study also explores the factors that promote feedback-seeking behavior which in result could affect end user`s faithful appropriation of information systems. In addition, this study provides insight about which inducements or resources SMEs should offer to promote individual users' feedback-seeking behavior when formal and sufficient support from IT staff or an outside information system provider is hardly expected. As the study results show, under the business environment of SMEs, help from skilled colleagues and the management plays a critical role. Therefore, SMEs should seriously consider how to utilize skilled peer information system users, while the management should pay keen attention to end users and support them to make the most of information systems.

RBM-based distributed representation of language (RBM을 이용한 언어의 분산 표상화)

  • You, Heejo;Nam, Kichun;Nam, Hosung
    • Korean Journal of Cognitive Science
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    • v.28 no.2
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    • pp.111-131
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    • 2017
  • The connectionist model is one approach to studying language processing from a computational perspective. And building a representation in the connectionist model study is just as important as making the structure of the model in that it determines the level of learning and performance of the model. The connectionist model has been constructed in two different ways: localist representation and distributed representation. However, the localist representation used in the previous studies had limitations in that the unit of the output layer having a rare target activation value is inactivated, and the past distributed representation has the limitation of difficulty in confirming the result by the opacity of the displayed information. This has been a limitation of the overall connection model study. In this paper, we present a new method to induce distributed representation with local representation using abstraction of information, which is a feature of restricted Boltzmann machine, with respect to the limitation of such representation of the past. As a result, our proposed method effectively solves the problem of conventional representation by using the method of information compression and inverse transformation of distributed representation into local representation.

A Study on the Teaching of SW coding by Design-Thinking 5 Step Maker Model (Design-Thinking 5 Step 메이커 모형 적용 SW코딩 교수학습에 대한 연구)

  • Kim, Myung-sook;Chung, Jong-In;Kim, Chang-Suk;Kang, Shin-Cheon;Kim, Eui-jung
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2018.05a
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    • pp.309-313
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    • 2018
  • Maker Activity based Design-Thinking 5 Step is a better experience for providing the public with a better approach to design by sympathizing with human needs and exploring the public's potential desires. This paper studied the teaching method by applying the value of the Maker Training that emphasizes the importance of sharing and opening results with others after creating them based on the ideas of the learners using different tools, the basic mind of Design-Thinking with the observation and empathy about human beings and the derivation of user-centric results to the SW coding curriculum. For this purpose, we studied teaching methods by Design-thinking based on sections that require coding in the information classes of the secondary school curriculum. We demonstrated the class to a group of education experts by applying the syllabus of instruction. Then we collected evaluations and opinions of the experts and we modified the syllabus to reflect the collected assessment. Under the Design-thinking 5 step foundation, classes were demonstrated with a group of education experts, opinions collected, and suggestions collected were reflected on the assessment outcome. I think that It is an effective training opportunity to practice a widespread idea that enables infinite thinking and a convergence of thinking that brings out the best decision from a widespread idea.

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Wild Boar (Sus scrofa corranus Heude ) Habitat Modeling Using GIS and Logistic Regression (GIS와 로지스틱 회귀분석을 이용한 멧돼지 서식지 모형 개발)

  • 서창완;박종화
    • Spatial Information Research
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    • v.8 no.1
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    • pp.85-99
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    • 2000
  • Accurate information on habitat distribution of protected fauna is essential for the habitat management of Korea, a country with very high development pressure. The objectives of this study were to develop a habitat suitability model of wild boar based on GIS and logistic regression, and to create habitat distribution map, and to prepare the basis for habitat management of our country s endangered and protected species. The modeling process of this restudyarch had following three steps. First, GIS database of environmental factors related to use and availability of wild boar habitat were built. Wild boar locations were collected by Radio-Telemetry and GPS. Second, environmental factors affecting the habitat use and availability of wild boars were identified through chi-square test. Third, habitat suitability model based on logistic regression were developed, and the validity of the model was tested. Finally , habitat assessment map was created by utilizing a rule-based approach. The results of the study were as folos. First , distinct difference in wild boar habitat use by season and habitat types were found, however, no difference in wild boar habiat use by season and habitat types were found , however, ho difference by sex and activity types were found. Second, it was found, through habitat availability analysis, that elevation , aspect , forest type, and forest age were significant natural environmental factors affecting wild boar hatibate selection, but the effects of slope, ridge/valley, water, and solar radiation could not be identified, Finally, the habitat at cutoff value of 0.5. The model validation showed that inside validation site had the classification accuracy of 73.07% for total habitat and 80.00% for cover habitat , and outside validation site had the classification accuracy of 75.00% for total habitat.

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Image segmentation using fuzzy worm searching and adaptive MIN-MAX clustering based on genetic algorithm (유전 알고리즘에 기반한 퍼지 벌레 검색과 자율 적응 최소-최대 군집화를 이용한 영상 영역화)

  • Ha, Seong-Wook;Kang, Dae-Seong;Kim, Dai-Jin
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.12
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    • pp.109-120
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    • 1998
  • An image segmentation approach based on the fuzzy worm searching and MIN-MAX clustering algorithm is proposed in this paper. This algorithm deals with fuzzy worm value and min-max node at a gross scene level, which investigates the edge information including fuzzy worm action and spatial relationship of the pixels as the parameters of its objective function. But the conventional segmentation methods for edge extraction generally need the mask information for the algebraic model, and take long run times at mask operation, whereas the proposed algorithm has single operation according to active searching of fuzzy worms. In addition, we also propose both genetic fuzzy worm searching and genetic min-max clustering using genetic algorithm to complete clustering and fuzzy searching on grey-histogram of image for the optimum solution, which can automatically determine the size of ranges and has both strong robust and speedy calculation. The simulation results showed that the proposed algorithm adaptively divided the quantized images in histogram region and performed single searching methods, significantly alleviating the increase of the computational load and the memory requirements.

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