• Journal of the Korea Society of Computer and Information
• /
• v.14 no.6
• /
• pp.125-134
• /
• 2009

A biological data acquisition based on web has emerged as a powerful tool for allowing scientists to interactively view entries form different databases, and to navigate from one database to another molecular-biology database links. In this paper, the biological conceptual model is constructed hybrid biological data model to represent interesting entities in the data sources to applying navigation rule property for each biological data source based on four biological data integrating layers to control biological data. When some user's requests for application service are occurred, we can get the data from database and data source via web service. In this paper, we propose a query processing model and execution structure based on integrating data layers that can search information on biological data sources.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.5
• /
• pp.359-366
• /
• 2019

Indoor spatial data has great importance as the demand for representing the complex urban environment in the context of providing LBS (Location-based Services) is increasing. IndoorGML (Indoor Geographic Markup Language) has been established as the data standard for spatial data in providing indoor navigation, but its definitions and relationships must be expanded to increase its applications and to successfully delivering information to users. In this study, we propose an approach to integrate IndoorGML with Indoor POI (Points of Interest) data by extending the IndoorGML notion of space and topological relationships. We consider two cases of representing Indoor POI, by 3D geometry and by point primitive representation. Using the concepts of the NRS (node-relation structure) and multi-layered space representation of IndoorGML, we define layers to separate features that represent the spaces and the Indoor POI into separate, but related layers. The proposed methodology was implemented with real datasets to evaluate its effectiveness for performing indoor spatial analysis.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.38 no.5
• /
• pp.403-413
• /
• 2010

Transition location of boundary layers over airfoils is predicted by using PSE(Parabolized Stability Equations) and $e^N$-method. Growth rates of disturbances are obtained from the PSE analysis and the N-factor curves are calculated by integrating the growth rates. The computational code developed in the present study is validated by comparing the computed results with the well known data for the cases of flat plate boundary layers and airfoils. Predictions of transition location are made for the boundary layers over NACA0012, NLF(1)-0414F, and NLF(1)-0416 airfoil. Predicted transition locations are found to be in good agreement with the experimental data.

• Membrane and Water Treatment
• /
• v.10 no.4
• /
• pp.313-320
• /
• 2019

Increasing the concentration of nitrate ions in the soil solution and then leaching it to underground aquifers increases the concentration of nitrate in the water, and can cause many health and ecological problems. This study was conducted to evaluate the vulnerability of Meymeh aquifer to nitrate pollution. In this research, sampling of 10 wells was performed according to standard sampling principles and analyzed in the laboratory by spectrophotometric method, then; the nitrate concentration zonation map was drawn by using intermediate models. In the drastic model, the effective parameters for assessing the vulnerability of groundwater aquifers, including the depth of ground water, pure feeding, aquifer environment, soil type, topography slope, non-saturated area and hydraulic conductivity. Which were prepared in the form of seven layers in the ARC GIS software, and by weighting and ranking and integrating these seven layers, the final map of groundwater vulnerability to contamination was prepared. Drastic index estimated for the region between 75-128. For verification of the model, nitrate concentration data in groundwater of the region were used, which showed a relative correlation between the concentration of nitrate and the prepared version of the model. A combination of two vulnerability map and nitrate concentration zonation was provided a qualitative aquifer classification map. According to this map, most of the study areas are within safe and low risk, and only a small portion of the Meymeh Aquifer, which has a nitrate concentration of more than 50 mg / L in groundwater, is classified in a hazardous area.

• Journal of KIISE:Computing Practices and Letters
• /
• v.8 no.5
• /
• pp.510-519
• /
• 2002

The OpenGIS Consortium has proposed a new web-mapping technology to support interoperability in web GIS environment by developing the specifications of MapServer and GML. In this environment, the MapServer transforms legacy spatial data into GML data, and clients display them on standard web browsers. This web-mapping testbed proposes methods for discovering, accessing, integrating and displaying GIS information except processing of spatial operations which are essential services in GIS environment. This paper proposes the method for executing spatial operations on GML data which are overlays of different map layers in legacy data servers. To support spatial operations on GML data in web GIS environment, this paper designs and implements GDOM based on the W3C's DOM Specifications and OGC's Simple Features Specifications. This paper shows the specifications and implementation of GDOM and the process of spatial operations in web-mapping testbed environment.

• International Journal of Heart Failure
• /
• v.6 no.1
• /
• pp.11-19
• /
• 2024

The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF. Machine learning (ML) is a subfield of AI that allows computers to analyze data, find patterns, and make predictions without explicit instructions. ML can be supervised, unsupervised, or semi-supervised. Deep learning is a branch of ML that uses artificial neural networks with multiple layers to find complex patterns. These AI technologies have shown significant potential in various aspects of HF research, including diagnosis, outcome prediction, classification of HF phenotypes, and optimization of treatment strategies. In addition, integrating multiple data sources, such as electrocardiography, electronic health records, and imaging data, can enhance the diagnostic accuracy of AI algorithms. Currently, wearable devices and remote monitoring aided by AI enable the earlier detection of HF and improved patient care. This review focuses on the rationale behind utilizing AI in HF and explores its various applications.

• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.13-22
• /
• 2020

Reinforcement steel fixing is a skilled and manually intensive construction trade. Current practice for the quality assessment of reinforcement steel fixing is normally performed by fabricators and has high potential in having errors due to the tedious nature of the work. In order to overcome the current inspection limitation, this study presents an approach that provides visual assistance and inspection enhancement for inspectors to assess the dimensional layout of reinforcement steel fixing. To this end, this study aims to establish an end-to-end framework for rebar layout quality inspection using laser scanning and Augmented Reality (AR). The proposed framework is composed of three parts: (1) the laser-scanned rebar data processing; (2) the rebar inspection procedure integrating with AR; and (3) the checking and fixing the rebar layout through AR visualization. In order to investigate the feasibility of the proposed framework, a case study assessing the rebar layout of a lab-scaled formwork containing two rebar layers is conducted. The results of the case studies demonstrate that the proposed approach using laser scanning and AR has the potential to produce an intuitive and accurate quality assessment for the rebar layout.

• Geomechanics and Engineering
• /
• v.37 no.2
• /
• pp.135-147
• /
• 2024

A GIS-based landslide susceptibility mapping (LSM) was carried out using frequency ratio (FR), modified frequency ratio (M-FR), analytic hierarchy process (AHP), and modified analytic hierarchy process (M-AHP) methods to identify and delineate the potential failure zones along the Halong - Vandon expressway. The thematic layers of various landslide causative factors were generated for modeling in GIS, including geology, rainfall, distance to fault, distance to road, slope, aspect, landuse, density of landslide, vertical relief, and horizontal relief. In addition, a landslide inventory along the road network was prepared using data provided by the management department during the course of construction and operation from 2017 to 2019, when many landslides were documented. The validation results showed that the M-FR method had the highest AUC value (AUC = 0.971), which was followed by the FR method with AUC = 0.961. The AUC values were 0.939 and 0.892 for the M-AHP and AHP methods, respectively. The generated LSM obtained from M-FR method classified the study area into five susceptibility classes: very low (0), low (0-1), moderate (1-2), high (2-3), and very high (3-4) classes, which could be useful for various stakeholders like planners, engineers, designers, and local public for future construction and maintenance in the study area.

• Informatization Policy
• /
• v.25 no.4
• /
• pp.108-120
• /
• 2018

With the rise of the Fourth Industrial Revolution and I-Korea 4.0, both of which pursue strategies for industrial innovation and for the solution to social problems, the real estate industry needs to change in order to make effective use of available space in smart environments. The implementation of smart spaces is a promising solution for this. The smart space is defined as a good use of space, whether it be a home, office, or retail store, within a smart environment. To enhance the use of smart spaces, efficient decision-making and well-timed and accurate interaction are required. This paper proposes a smart space based on platform which takes advantage of emerging technologies for the efficient storage, processing, analysis, and utilization of big data. The platform is composed of six layers - collection, transfer, storage, service, application, and management - and offers three service frameworks: activity-based, market-based, and policy-based. Based on these smart space services, decision-makers, consumers, clients, and social network participants can make better decisions, respond more quickly, exhibit greater innovation, and develop stronger competitive advantages.

• Geomechanics and Engineering
• /
• v.36 no.5
• /
• pp.427-440
• /
• 2024

This study concentrates on the 301 comprehensive caving working face, notable for its considerable mining height. The roof model is established by integrating prior geological data and the latest borehole rock stratum's physical and mechanical parameters. This comprehensive approach enables the determination of lithology, thickness, and mechanical properties of the roof within 50 m of the primary mining coal seam. Utilizing the transfer rock beam theory and incorporating mining pressure monitoring data, the study delves into the geometric parameters of the direct roof, basic roof movement, and roof pressure during the initial mining process of the 301 comprehensive caving working face. The direct roof of the mining working face is stratified into upper and lower sections. The lower direct roof consists of 6.0 m thick coarse sandstone, while the upper direct roof comprises 9.2 m coarse sandstone, 2.6 m sandy mudstone, and 2.8 m medium sandstone. The basic roof stratum, totaling 22.1 m in thickness, includes layers such as silty sand, medium sandstone, sandy mudstone, and coal. The first pressure step of the basic roof is 61.6 m, with theoretical research indicating a maximum roof pressure of 1.62 MPa during periodic pressure. Extensive simulations and analyses of roof subsidence and advanced abutment pressure under varying working face lengths. Optimal roof control effect is observed when the mining face length falls within the range of 140 m-155 m. This study holds significance as it optimizes the working face length in thick coal seams, enhancing safety and efficiency in coal mining operations.