• Title/Summary/Keyword: system architecture

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A Study on the Application of the Price Prediction of Construction Materials through the Improvement of Data Refactor Techniques (Data Refactor 기법의 개선을 통한 건설원자재 가격 예측 적용성 연구)

  • Lee, Woo-Yang;Lee, Dong-Eun;Kim, Byung-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.24 no.6
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    • pp.66-73
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    • 2023
  • The construction industry suffers losses due to failures in demand forecasting due to price fluctuations in construction raw materials, increased user costs due to project cost changes, and lack of forecasting system. Accordingly, it is necessary to improve the accuracy of construction raw material price forecasting. This study aims to predict the price of construction raw materials and verify applicability through the improvement of the Data Refactor technique. In order to improve the accuracy of price prediction of construction raw materials, the existing data refactor classification of low and high frequency and ARIMAX utilization method was improved to frequency-oriented and ARIMA method utilization, so that short-term (3 months in the future) six items such as construction raw materials lumber and cement were improved. ), mid-term (6 months in the future), and long-term (12 months in the future) price forecasts. As a result of the analysis, the predicted value based on the improved Data Refactor technique reduced the error and expanded the variability. Therefore, it is expected that the budget can be managed effectively by predicting the price of construction raw materials more accurately through the Data Refactor technique proposed in this study.

Effect of Alternating Temperature Conditions, and GA3 Treatment on Seed Germination of Trollius macropetalus (Regel) F.Schmidt (변온 조건 및 GA3 처리가 큰금매화의 종자 발아에 미치는 영향)

  • Dong-Hak Kim;Seungju Jo;Jung-Won Sung;Jung-Won Yoon
    • Korean Journal of Plant Resources
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    • v.37 no.1
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    • pp.79-86
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    • 2024
  • This study was conducted to determine the conditions for breaking dormancy in the seeds of the North Korean plant resource, Trollius macropetalus, and to investigate its germination characteristics. The morphological characteristics and viability of T. macropetalus seeds were examined. Germination characteristics were investigated based on temperature conditions (15/6℃ & 25/15℃), cold stratification treatment, and GA3 treatment. The results showed that cold stratification treatment had no effect on breaking the dormancy of T. macropetalus. GA3 treatment significantly increased the germination rate of T. macropetalus and also improved the mean germination days and germination speed. However, compared to the 15/6℃ condition, the effectiveness of GA3 treatment for T. macropetalus decreased under the 25/15℃ condition. It was determined that T. macropetalus have a nondeep-type morpho-physiological dormancy. The most effective conditions for breaking dormancy were found to be the 15/6℃ temperature condition and GA3 treatment at 500 mg·L-1. The findings of this study are expected to provide valuable information for the mass propagation of T. macropetalus, which has potential applications in landscaping and pharmaceutical materials.

A Gap Analysis Using Spatial Data and Social Media Big Data Analysis Results of Island Tourism Resources for Sustainable Resource Management (지속가능한 자원관리를 위한 섬 지역 관광자원의 공간정보와 소셜미디어 빅데이터 분석 결과를 활용한 격차분석)

  • Lee, Sung-Hee;Lee, Ju-Kyung;Son, Yong-Hoon;Kim, Young-Jin
    • Journal of Korean Society of Rural Planning
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    • v.30 no.2
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    • pp.13-24
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    • 2024
  • This study conducts an analysis of social media big data pertaining to island tourism resources, aiming to discern the diverse forms and categories of island tourism favored by consumers, ascertain predominant resources, and facilitate objective decision-making grounded in scientific methodologies. To achieve this objective, an examination of blog posts published on Naver from 2022 to 2023 was undertaken, utilizing keywords such as 'Island tourism', 'Island travel', and 'Island backpacking' as focal points for analysis. Text mining techniques were applied to sift through the data. Among the resources identified, the port emerged as a significant asset, serving as a pivotal conduit linking the island and mainland and holding substantial importance as a focal point and resource for tourist access to the island. Furthermore, an analysis of the disparity between existing island tourism resources and those acknowledged by tourists who actively engage with and appreciate island destinations led to the identification of 186 newly emerging resources. These nascent resources predominantly clustered within five regions: Incheon Metropolitan City, Tongyeong/Geoje City, Jeju Island, Ulleung-gun, and Shinan-gun. A scrutiny of these resources, categorized according to the tourism resource classification system, revealed a notable presence of new resources, chiefly in the domains of 'rural landscape', 'tourist resort/training facility', 'transportation facility', and 'natural resource'. Notably, many of these emerging resources were previously overlooked in official management targets or resource inventories pertaining to existing island tourism resources. Noteworthy examples include ports, beaches, and mountains, which, despite constituting a substantial proportion of the newly identified tourist resources, were not accorded prominence in spatial information datasets. This study holds significance in its ability to unearth novel tourism resources recognized by island tourism consumers through a gap analysis approach that juxtaposes the existing status of island tourism resource data with techniques utilizing social media big data. Furthermore, the methodology delineated in this research offers a valuable framework for domestic local governments to gauge local tourism demand and embark on initiatives for tourism development or regional revitalization.

Risk assessment for development of consecutive shield TBM technology (연속굴착형 쉴드 TBM 기술 개발을 위한 리스크 평가)

  • Kibeom Kwon;Hangseok Choi;Chaemin Hwang;Sangyeong Park;Byeonghyun Hwang
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.26 no.4
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    • pp.303-314
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    • 2024
  • Recently, the consecutive shield tunnel boring machine (TBM) has gained attention for its potential to enhance TBM penetration rates. However, its development requires a thorough risk assessment due to the unconventional nature of its equipment and hydraulic systems, coupled with the absence of design or construction precedents. This study investigated the causal relationships between four accidents and eight relevant sources associated with the consecutive shield TBM. Subsequently, risk levels were determined based on expert surveys and a risk matrix technique. The findings highlighted significant impacts associated with collapses or surface settlements and the likelihood of causal combinations leading to misalignment. Specifically, this study emphasized the importance of proactive mitigation measures to address collapses or surface settlements caused by inadequate continuous tail void backfill or damaged thrust jacks. Furthermore, it is recommended to develop advanced non-destructive testing technology capable of comprehensive range detection across helical segments, to design a sequential thrust jack propulsion system, and to determine an optimal pedestal angle.

Implementation of Reporting Tool Supporting OLAP and Data Mining Analysis Using XMLA (XMLA를 사용한 OLAP과 데이타 마이닝 분석이 가능한 리포팅 툴의 구현)

  • Choe, Jee-Woong;Kim, Myung-Ho
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.3
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    • pp.154-166
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    • 2009
  • Database query and reporting tools, OLAP tools and data mining tools are typical front-end tools in Business Intelligence environment which is able to support gathering, consolidating and analyzing data produced from business operation activities and provide access to the result to enterprise's users. Traditional reporting tools have an advantage of creating sophisticated dynamic reports including SQL query result sets, which look like documents produced by word processors, and publishing the reports to the Web environment, but data source for the tools is limited to RDBMS. On the other hand, OLAP tools and data mining tools have an advantage of providing powerful information analysis functions on each own way, but built-in visualization components for analysis results are limited to tables or some charts. Thus, this paper presents a system that integrates three typical front-end tools to complement one another for BI environment. Traditional reporting tools only have a query editor for generating SQL statements to bring data from RDBMS. However, the reporting tool presented by this paper can extract data also from OLAP and data mining servers, because editors for OLAP and data mining query requests are added into this tool. Traditional systems produce all documents in the server side. This structure enables reporting tools to avoid repetitive process to generate documents, when many clients intend to access the same dynamic document. But, because this system targets that a few users generate documents for data analysis, this tool generates documents at the client side. Therefore, the tool has a processing mechanism to deal with a number of data despite the limited memory capacity of the report viewer in the client side. Also, this reporting tool has data structure for integrating data from three kinds of data sources into one document. Finally, most of traditional front-end tools for BI are dependent on data source architecture from specific vendor. To overcome the problem, this system uses XMLA that is a protocol based on web service to access to data sources for OLAP and data mining services from various vendors.

User's Impacts on Environmental Deteriorations of Trail in Tôkyusan National Park (덕유산(德裕山) 국립공원(國立公園) 등산로(登山路)의 환경훼손(環境毁損)에 대(對)한 이용영향(利用影響))

  • Seo, Byung Soo;Kim, Sei Cheon;Park, Chong Min;Lee, Chang Heon;Lee, Kyu Wan
    • Journal of Korean Society of Forest Science
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    • v.83 no.3
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    • pp.286-298
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    • 1994
  • The object of this study was to examine the user's impacts on the environmental deteriorations of trail at Ticket Office - Paekryunsa (Temple) Hyangch$\hat{o}$kpong - Dongyupryung - Chilyun Fall area in T$\hat{o}$kyusan National Park. Four trails were sampled in the study area according to the amount of users. Then the user's impacts on trail were measured at each trail. The Ticket Office-Paekryunsa trail was the most used district and followed at Paekryunsa-Hyangch$\hat{o}$kpong trail, Hyangch$\hat{o}$kpong-Dongyupryung trail in descending order. Dongyupryung-Chilyun Fall trail is not used by people because of rest rotation system. The entire width of trail was greater at the more heavily used trail. Maximum depth, cross-sectional area loss, and surface texture and roughness of trail were the highest at Paekryunsa-Hyangch$\hat{o}$kpong trail. Soil hardness, soil acidity, soil moisture content, organic matter content, and exchange canon were influenced by trampling. Soil hardness, soil acidity and exchange canon increased in tramples soil, but content of soil moisture and organic matter decreased therein. Environmental deteriorations of trail were significantly influenced by the amount of users and the slope of trail. Bared lands about $2.000m^2$ were appeared by trampling and camping around Hyangch$\hat{o}$kpong. Effects of carrying of rest rotation system for National Park were partly recognized at Dongyupryung-Chilyun Fall trail.

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제주도 지하수자원의 최적 개발가능량 선정에 관한 수리지질학적 연구

  • 한정상;김창길;김남종;한규상
    • Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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    • 1994.07a
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    • pp.184-215
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    • 1994
  • The Hydrogeologic data of 455 water wells comprising geologic and aquifer test were analyzed to determine hydrogeoloic characteristics of Cheju island. The groundwater of Cheju island is occurred in unconsolidated pyroclastic deposits interbedded in highly jointed basaltic and andesic rocks as high level, basal and parabasal types order unconfined condition. The average transmissivity and specific yield of the aquifer are at about 29,300m$^2$/day and 0.12 respectively. The total storage of groundwater is estimated about 44 billion cubic meters(m$^3$). Average annual precipitation is about 3390 million m$^3$ among which average recharge amount is estimated 1494 million m$^3$ equivalent 44.1% of annual precipitation with 638 million m$^3$ of runoff and 1256 million m$^3$ of evapotranspiration. Based on groundwater budget analysis, the sustainable yield is about 620 million m$^3$(41% of annual recharge)and rest of it is discharging into the sea. The geologic logs of recently drilled thermal water wens indicate that very low-permeable marine sediments(Sehwa-ri formation) composed of loosely cemented sandy sat derived from mainly volcanic ashes, at the 1st stage volcanic activity of the area was situated at the 120$\pm$68m below sea level. And also the other low-permeable sedimentary rock called Segipo-formation which is deemed younger than former marine sediment is occured at the area covering north-west and western part of Cheju at the $\pm$70m below sea level. If these impermeable beds are distributed as a basal formation of fresh water zone of Cheju, most of groundwater in Cheju will be para-basal type. These formations will be one of the most important hydrogeologic boundary and groundwater occurences in the area.

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A Study on the Intelligent Service Selection Reasoning for Enhanced User Satisfaction : Appliance to Cloud Computing Service (사용자 만족도 향상을 위한 지능형 서비스 선정 방안에 관한 연구 : 클라우드 컴퓨팅 서비스에의 적용)

  • Shin, Dong Cheon
    • Journal of Intelligence and Information Systems
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    • v.18 no.3
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    • pp.35-51
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    • 2012
  • Cloud computing is internet-based computing where computing resources are offered over the Internet as scalable and on-demand services. In particular, in case a number of various cloud services emerge in accordance with development of internet and mobile technology, to select and provide services with which service users satisfy is one of the important issues. Most of previous works show the limitation in the degree of user satisfaction because they are based on so called concept similarity in relation to user requirements or are lack of versatility of user preferences. This paper presents cloud service selection reasoning which can be applied to the general cloud service environments including a variety of computing resource services, not limited to web services. In relation to the service environments, there are two kinds of services: atomic service and composite service. An atomic service consists of service attributes which represent the characteristics of service such as functionality, performance, or specification. A composite service can be created by composition of atomic services and other composite services. Therefore, a composite service inherits attributes of component services. On the other hand, the main participants in providing with cloud services are service users, service suppliers, and service operators. Service suppliers can register services autonomously or in accordance with the strategic collaboration with service operators. Service users submit request queries including service name and requirements to the service management system. The service management system consists of a query processor for processing user queries, a registration manager for service registration, and a selection engine for service selection reasoning. In order to enhance the degree of user satisfaction, our reasoning stands on basis of the degree of conformance to user requirements of service attributes in terms of functionality, performance, and specification of service attributes, instead of concept similarity as in ontology-based reasoning. For this we introduce so called a service attribute graph (SAG) which is generated by considering the inclusion relationship among instances of a service attribute from several perspectives like functionality, performance, and specification. Hence, SAG is a directed graph which shows the inclusion relationships among attribute instances. Since the degree of conformance is very close to the inclusion relationship, we can say the acceptability of services depends on the closeness of inclusion relationship among corresponding attribute instances. That is, the high closeness implies the high acceptability because the degree of closeness reflects the degree of conformance among attributes instances. The degree of closeness is proportional to the path length between two vertex in SAG. The shorter path length means more close inclusion relationship than longer path length, which implies the higher degree of conformance. In addition to acceptability, in this paper, other user preferences such as priority for attributes and mandatary options are reflected for the variety of user requirements. Furthermore, to consider various types of attribute like character, number, and boolean also helps to support the variety of user requirements. Finally, according to service value to price cloud services are rated and recommended to users. One of the significances of this paper is the first try to present a graph-based selection reasoning unlike other works, while considering various user preferences in relation with service attributes.

Comparative Analysis of ViSCa Platform-based Mobile Payment Service with other Cases (스마트카드 가상화(ViSCa) 플랫폼 기반 모바일 결제 서비스 제안 및 타 사례와의 비교분석)

  • Lee, June-Yeop;Lee, Kyoung-Jun
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.163-178
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    • 2014
  • Following research proposes "Virtualization of Smart Cards (ViSCa)" which is a security system that aims to provide a multi-device platform for the deployment of services that require a strong security protocol, both for the access & authentication and execution of its applications and focuses on analyzing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service by comparing with other similar cases. At the present day, the appearance of new ICT, the diffusion of new user devices (such as smartphones, tablet PC, and so on) and the growth of internet penetration rate are creating many world-shaking services yet in the most of these applications' private information has to be shared, which means that security breaches and illegal access to that information are real threats that have to be solved. Also mobile payment service is, one of the innovative services, has same issues which are real threats for users because mobile payment service sometimes requires user identification, an authentication procedure and confidential data sharing. Thus, an extra layer of security is needed in their communication and execution protocols. The Virtualization of Smart Cards (ViSCa), concept is a holistic approach and centralized management for a security system that pursues to provide a ubiquitous multi-device platform for the arrangement of mobile payment services that demand a powerful security protocol, both for the access & authentication and execution of its applications. In this sense, Virtualization of Smart Cards (ViSCa) offers full interoperability and full access from any user device without any loss of security. The concept prevents possible attacks by third parties, guaranteeing the confidentiality of personal data, bank accounts or private financial information. The Virtualization of Smart Cards (ViSCa) concept is split in two different phases: the execution of the user authentication protocol on the user device and the cloud architecture that executes the secure application. Thus, the secure service access is guaranteed at anytime, anywhere and through any device supporting previously required security mechanisms. The security level is improved by using virtualization technology in the cloud. This virtualization technology is used terminal virtualization to virtualize smart card hardware and thrive to manage virtualized smart cards as a whole, through mobile cloud technology in Virtualization of Smart Cards (ViSCa) platform-based mobile payment service. This entire process is referred to as Smart Card as a Service (SCaaS). Virtualization of Smart Cards (ViSCa) platform-based mobile payment service virtualizes smart card, which is used as payment mean, and loads it in to the mobile cloud. Authentication takes place through application and helps log on to mobile cloud and chooses one of virtualized smart card as a payment method. To decide the scope of the research, which is comparing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service with other similar cases, we categorized the prior researches' mobile payment service groups into distinct feature and service type. Both groups store credit card's data in the mobile device and settle the payment process at the offline market. By the location where the electronic financial transaction information (data) is stored, the groups can be categorized into two main service types. First is "App Method" which loads the data in the server connected to the application. Second "Mobile Card Method" stores its data in the Integrated Circuit (IC) chip, which holds financial transaction data, which is inbuilt in the mobile device secure element (SE). Through prior researches on accept factors of mobile payment service and its market environment, we came up with six key factors of comparative analysis which are economic, generality, security, convenience(ease of use), applicability and efficiency. Within the chosen group, we compared and analyzed the selected cases and Virtualization of Smart Cards (ViSCa) platform-based mobile payment service.

Object Tracking Based on Exactly Reweighted Online Total-Error-Rate Minimization (정확히 재가중되는 온라인 전체 에러율 최소화 기반의 객체 추적)

  • JANG, Se-In;PARK, Choong-Shik
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.53-65
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    • 2019
  • Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.