• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.5
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• pp.20-28
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• 2016

A Ubiquitous City (U-city, Smart City) is one that ties information communications technologies (ICT) into many facets of city construction, thereby implicitly intending to function as a smart city that aims to be efficiently managed as well as provide an enhanced standard of living for its residents. Laws related to the construction of such ubiquitous cities point to integrated city management centers, intelligent facilities, and U-City infrastructure, among others, as central components of U-Cities, but do not provide a standard for these structures. Consequently, building of U-Cities by local governments are based on arbitrary judgments constrained the myriad of practical limitations that they face. Such ambiguity brings to light the need to find ways to improve the quality of these efforts. The first and second stages of this research examine the status of the components of a U-City -ubiquitous planning, technology, infrastructure, and services - and undertakes a comprehensive review thereof, with evaluation criteria formulated on the characteristics of stability, connectivity, goal-orientation, and development potential. In the research's third stage, a realistic and detailed evaluation index by which U-Cities can be renewed, demonstrated, and applied (???) is introduced in a step-by-step fashion, which will allow for local governments to properly assess the standard of their U-City in relation to the realities of the locality. Through the research result, it is expected that the index will become a part of the continued development and advancement of the "smart" character of an autonomous U-City at the local scale, and contribute to the overall revitalization of the U-City.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.4
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• pp.378-388
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• 2016

International societies are currently working together to achieve the Climate-Smart Agriculture (CSA) initiative which aims the triple wins: (1) sustainably increasing agricultural productivity and incomes; (2) adapting and building resilience to climate change; and (3) mitigating greenhouse gases emissions. In terms of its scope and context, CSA follows the '3Nong (三農)' vision cast about 200 years ago by Dasan Jeong Yak-Yong who emphasized the triad of governance, management and monitoring towards comfortable, profitable and noble agriculture. Yet, the CSA provides the practical aims that facilitate the development of holistic indicators for quantitative evaluation and monitoring, on which decision-making support system is based. In this study, we introduce an agent-based model, i.e. Mathematical Programming Multi-Agent Systems (MP-MAS), as a tool for supporting the decision-making toward CSA. We have established the initial version of MP-MAS adapted for domestic use and present the preliminary results from an application to the rice farming case in Haenam, Korea. MP-MAS can support both farmers and policy-makers to consider diverse management options from multiple perspectives. When the modules for system resilience and carbon footprint are added, MP-MAS will serve as a robust tool that fulfills not only CSA but also Dasan's '3Nong' vision of sustainable agricultural-societal systems.

• Information Systems Review
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• v.21 no.2
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• pp.1-27
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• 2019

It is possible to provide Smart Tourism Service through the development of information technology. It is necessary for the tourism industry to understand and utilize Big Data that has tourists' consumption patterns and service usage patterns in order to continuously create a new business model by converging with other industries. This study suggests to activate Jeju Smart Tourism by analyzing Big Data based on credit card usage records and location of tourists in Jeju. The results of the study show that First, the percentage of Chinese tourists visiting Jeju has decreased because of the effect of THAAD. Second, Consumption pattern of Chinese tourists is mostly occurring in the northern areas where airports and duty-free shops are located, while one in other regions is very low. The regional economy of Jeju City and Seogwipo City shows a overall stagnation, without changes in policy, existing consumption trends and growth rates will continue in line with regional characteristics. Third, we need a policy that young people flow into by building Jeju Multi-complex Mall where they can eat, drink, and go shopping at once because the number of young tourists and the price they spend are increasing. Furthermore, it is necessary to provide services for life-support related to weather, shopping, traffic, and facilities etc. through analyzing Wi-Fi usage location. Based on the results, we suggests the marketing strategies and public policies for understanding Jeju tourists' patterns and stimulating Jeju tourism industry.

• Smart Structures and Systems
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• v.18 no.6
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• pp.1111-1123
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• 2016

The present study aims at proposing an analytical method for semi-active structural control by using block pulse functions. The performance of the resulting controlled system and the requirements of the control devices are highly dependent on the control algorithm employed. In control problems, it is important to devise an accurate analytical method with less computational expenses. Block pulse functions (BPFs) set proved to be the most fundamental and it enjoyed immense popularity in different applications in the area of numerical analysis in systems science and control. This work focused on the application of BPFs in the control algorithm concerning decrease the computational expenses. Variable orifice dampers (VODs) are one of the common semi-active devices that can be used to control the response of civil Structures during seismic loads. To prove the efficiency of the proposed method, numerical simulations for a 10-story shear building frame equipped with VODs are presented. The controlled response of the frame was compared with results obtained by controlling the frame by the classical clipped-optimal control method based on linear quadratic regulator theory. The simulation results of this investigation indicated the proposed method had an acceptable accuracy with minor computational expenses and it can be advantageous in reducing seismic responses.

• The Journal of Information Systems
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• v.26 no.1
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• pp.171-188
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• 2017

Purpose This study investigates the effects of trust and distrust on intention to purchase in open market, based on the idea that trust and distrust can co-exist. Specifically, this study approached the effects of trust and distrust of the open market on the intention to purchase from a two-dimensional perspective, and examined trustworthiness as the antecedents of trust and distrust. Design/Methodology/Approach In this study, we conducted a questionnaire survey on consumers who have actually purchased a product from open markets in Korea for two months. As a result, 141 users are chosen for the sample. We apply PLS (Partial Least Squares) structural equation modeling (SEM) to verify our theoretical model using the software application SmartPLS 3.0. Findings First, trust in open market positively affects intention to purchase, whereas distrust in open market negatively affects intention to purchase. Second, the three antecedents of trust (i.e. three factors constituting trustworthiness such as ability, benevolence and integrity) affect trust in open market. Third, integrity negatively affects distrust in open market. Since integrity plays an important role in building both trust and distrust in open market, the operators of open market should pay attention to managing their integrity.

• Smart Structures and Systems
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• v.13 no.3
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• pp.407-418
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• 2014

The purpose of this paper is to present an Integrated Life Cycle Bridge Information Modeling that can be used throughout different phases of the bridge life cycle including: design, construction, and operation and maintenance phases. Bridge Information Modeling (BrIM) has become an effective tool in bridge engineering and construction. It has been used in obtaining accurate shop drawings, cost estimation, and visualization. In this paper, BrIM is used as an integrated tool for bridges life cycle information modeling. In the design phase, BrIM model can be used in obtaining optimum construction methods and performing structural advanced analysis. During construction phase, the model selects the appropriate locations for mobile cranes, monitors the status of precast components, and controls documents. Whereas, it acts as a tool for bridge management system in operation and maintenance phase. The paper provides a detailed description for each use of BrIM model in design, construction, and operation and maintenance phases of bridges. It is proven that BrIM is an effective tool for bridge management systems throughout their life phases.

• Smart Structures and Systems
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• v.6 no.4
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• pp.405-421
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• 2010

This paper proposes a method for early warning of hazard for pipelines. Many pipelines transport dangerous contents so that any damage incurred might lead to catastrophic consequences. However, most of these damages are usually a result of surrounding third-party activities, mainly the constructions. In order to prevent accidents and disasters, detection of potential hazards from third-party activities is indispensable. This paper focuses on recognizing the running of construction machines because they indicate the activity of the constructions. Acoustic information is applied for the recognition and a novel pipeline monitoring approach is proposed. Principal Component Analysis (PCA) is applied. The obtained Eigenvalues are regarded as the special signature and thus used for building feature vectors. One-class Support Vector Machine (SVM) is used for the classifier. The denoising ability of PCA can make it robust to noise interference, while the powerful classifying ability of SVM can provide good recognition results. Some related issues such as standardization are also studied and discussed. On-site experiments are conducted and results prove the effectiveness of the proposed early warning method. Thus the possible hazards can be prevented and the integrity of pipelines can be ensured.

• Smart Structures and Systems
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• v.22 no.4
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• pp.441-457
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• 2018

Characteristic parameter values of seismic isolators deviate from their nominal design values due to uncertainties and/or errors in their material properties and element dimensions, etc. Deviations may increase over service life due to environmental effects and service conditions. For accurate evaluation of the seismic safety level, all such effects, which would result in deviations in the structural response, need to be taken into account. In this study, the sensitivity of the probability of failure of the structures equipped with nonlinear base isolation systems to the uncertainties in various isolation system characteristic parameters is investigated in terms of various isolation system and superstructure response parameters in the context of a realistic three-dimensional base-isolated building model via Monte Carlo Simulations. The inherent record-to-record variability nature of the earthquake ground motions is also taken into account by carrying out analyses for a large number of ground motion records which are classified as those with and without forward-directivity effects. Two levels of nominal isolation periods each with three different levels of uncertainty are considered. Comparative plots of cumulative distribution functions and related statistical evaluation presented here portray the potential extent of the deviation of the structural response parameters resulting from the uncertainties and the uncertainty levels considered, which is expected to be useful for practicing engineers in evaluating isolator test results for their projects.

• Smart Structures and Systems
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• v.18 no.2
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• pp.293-315
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• 2016

Seismic isolation is often used in protecting mission-critical structures including hospitals, data centers, telecommunication buildings, etc. Such structures typically house vibration-sensitive equipment which has to provide continued service but may fail in case sustained accelerations during earthquakes exceed threshold limit values. Thus, peak floor acceleration is one of the two main parameters that control the design of such structures while the other one is peak base displacement since the overall safety of the structure depends on the safety of the isolation system. And in case peak base displacement exceeds the design base displacement during an earthquake, rupture and/or buckling of isolators as well as bumping against stops around the seismic gap may occur. Therefore, obtaining accurate peak floor accelerations and peak base displacement is vital. However, although nominal design values for isolation system and superstructure parameters are calculated in order to meet target peak design base displacement and peak floor accelerations, their actual values may potentially deviate from these nominal design values. In this study, the sensitivity of the seismic performance of structures equipped with linear and nonlinear seismic isolation systems to the aforementioned potential deviations is assessed in the context of a benchmark shear building under different earthquake records with near-fault and far-fault characteristics. The results put forth the degree of sensitivity of peak top floor acceleration and peak base displacement to superstructure parameters including mass, stiffness, and damping and isolation system parameters including stiffness, damping, yield strength, yield displacement, and post-yield to pre-yield stiffness ratio.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.