• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.249-254
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• 2023

Recently, the distribution of drones is being activated by saving farmers' working time and protecting them from harmful human bodies from pesticides due to the mission of spraying pesticides using drones. It is possible to compensate for various shortcomings derived from the existing pesticide spraying method, wide-area control and helicopter control. Recently, the smart farm expansion policy has actively used it to generate profits for farmers by increasing harvests by monitoring growth information of various crops based on IoT in real time and collecting big data on key variables, and related drone industry technologies are also being developed. In this study, drones were applied to the work of shading greenhouses to secure diversity in agricultural application fields, and basic research on the greenhouse environment was conducted to materialize the technology related to shading. In order to provide high-quality light in consideration of the internal and external environment of the green house, basic research was conducted to enable light-shielding missions using drones through nozzle design for uniform spraying of nozzles of drones, light-transmitting rate analysis of green houses, and light-shielding agent application experiments.

• Industry Promotion Research
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• v.9 no.3
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• pp.193-203
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• 2024

This study analyzes user behavior on YouTube Shorts within snack culture and proposes short-form video production strategies by identifying key value factors. Prior research identified seven characteristics (playfulness, time killing, information provision, social presence, interactivity, escapism, conciseness) and criteria based on the 5W1H principles. Surveys and interviews revealed that key user values are playfulness, time killing, conciseness, and interactivity. Users engage without specific purposes, watch 10-20 consecutive pieces selectively, and use it in comfortable environments. This research provides insights for understanding user behavior and short-form video production strategies.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.1315-1315
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• 2024

In recent years, the building industry has seen a fundamental transition due to Digitalization Transformation (DX), with the aim of improving efficiency, productivity, sustainability, and cost-effectiveness. In particular, literature has significantly emphasized Smart Buildings (SBs), which are expected to grow in the global marketplace in the coming years. The most noticeable benefits include energy efficiency, increased occupant comfort and productivity, and a reduction in the building's impact on the environment. Most importantly, the shift to SBs has resulted in major changes to how traditional business practices are carried out. The Facility Asset Management (FAM) domain is one key area undergoing considerable changes to meet the needs of managing functional SBs. Despite this shifting landscape, the changes and prospective extensions to the business areas of FAM in the context of SBs remain largely unexplored. Thus, to address this limitation, this paper aims to investigate the potential changes (i.e., either the addition of a new function or the expansion of an existing function) of the FAM domain from the context of SBs. To achieve this objective, • First, based on a generic model of FAM proposed by Jin et al. (2024), a three-level hierarchical classification of FAM business functions for a conventional building is proposed. • Second, the concept of SBs is thoroughly discussed, including its drivers, features, enablers, and improvement areas. • Finally, a new FAM business function for SB is proposed, aligning with the distinct characteristics of SBs. As there are no established functional taxonomies of FAM, the comprehensive breakdown of FAM business functions presented in this study can be used as a standardized functional breakdown of the FAM domain. Moreover, it can also be used to facilitate robust and integrated information management practices throughout the whole lifecycle of SB facilities.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.375-382
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• 2024

Large Language Models (LLMs) still encounter challenges in comprehending domain-specific expressions within construction documents. Analogous to humans acquiring unfamiliar expressions from dictionaries, language models could assimilate domain-specific expressions through the use of a thesaurus. Numerous prior studies have developed construction thesauri; however, a practical issue arises in effectively leveraging these resources for instructing language models. Given that the thesaurus primarily outlines relationships between terms without indicating their relative importance, language models may struggle in discerning which terms to retain or replace. This research aims to establish a robust framework for guiding language models using the information from the thesaurus. For instance, a term would be associated with a list of similar terms while also being included in the lists of other related terms. The relative significance among terms could be ascertained by employing similarity scores normalized according to relevance ranks. Consequently, a term exhibiting a positive margin of normalized similarity scores (termed a pivot term) could semantically replace other related terms, thereby enabling LLMs to comprehend domain-specific terms through these pivotal terms. The outcome of this research presents a practical methodology for utilizing domain-specific thesauri to train LLMs and analyze construction documents. Ongoing evaluation involves validating the accuracy of the thesaurus-applied LLM (e.g., S-BERT) in identifying similarities within construction specification provisions. This outcome holds potential for the construction industry by enhancing LLMs' understanding of construction documents and subsequently improving text mining performance and project management efficiency.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.85-92
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• 2024

Reinforced concrete modular integrated construction (MiC) has been widely used in Hong Kong nowadays, but the solutions for temporary tying of the side walls during the construction of the composite wall have still shortcomings. Based on a MiC project in Hong Kong, this paper proposes a new inner tie system for composite wall. The system components are installed on the side walls of precast modules without penetrating through the side walls. After the loop is rotated to contact the hook, the tying effect can be generated when the concrete is poured on site between the middle gap of two modules. This system replaces tie bolts penetrating through precast side walls, so that the modules' interior fitting-out can be fully completed in factory and the on-site construction has no adverse effects on the internal decoration. This paper mainly describes the mechanism of the system, FEA simulation and optimization of the member size, as well as tensile and punching shear tests to verify the reliability, safety and to get more information about failure mode of the system. The system will be further examined by assembling 1:1 mockup modules, and finally applied to a real MiC project soon. The system can also act as permanent tie bars for the composite wall to reduce the total wall thickness, save the structural cost and increase the usable area. Compared with other existing tying methods in the industry, the system is easy to install, reliable to take loads, adaptable to large construction errors, and has the potential to be widely used in future practical projects.

• Smart Media Journal
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• v.13 no.9
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• pp.18-26
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• 2024

The development of information and communication technology and advanced technologies has led to the full-fledged implementation of smart tourism in the tourism industry. Concurrently, both domestic and international research on smart tourism has been actively pursued. This study aimed to compare and analyze the trends and issues in smart tourism research between South Korea and China, to identify differences in issues related to smart tourism in both countries, and to suggest directions for future research in smart tourism. For this purpose, a text mining analysis was conducted on 69 Korean papers and 42 Chinese papers related to smart tourism published from January 2020 to June 2024. The analysis showed that Korean research on smart tourism focused heavily on improving the quality and satisfaction of tourists' experiences and understanding their behavioral intentions, while Chinese research emphasized provision of immersive contents and studies on sustainable tourism. Based on the analysis results, implications for smart tourism research were presented, along with limitations of this study and future research directions.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.47-67
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• 2017

Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Journal of Food Hygiene and Safety
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• v.33 no.5
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• pp.361-368
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• 2018

N-nitrosamines are probable or possible human carcinogens, which are produced by the reaction between secondary amines and nitrogen oxide in the acidic environment or by heating. Common risk assessment procedure involves the comparison between exposures expressed in the unit, mg/kg body weight/day and the Health-Based Reference dose expressed in the same unit. This procedure is suitable for the policy decision-making and is considered as inappropriate for the consumers to get information about their dietary decision-making. Therefore, the distributions of NDMA (N-nitrosodimethylamine), NDBA (N-nitrosodibutylamine), the six N-nitrosamines (NDMA, NDBA, NDEA (N-nitrosodiethylamine), NPYR (N-nitrosopyrrolidine), NPIP (N-nitrosopiperidine), and NMOR (N-nitrosomorpholine) in the menus grouped based on the presence of main ingredients and cooking methods were analyzed to generate consumer-friendly information regarding food contaminants. Recipes and intakes were taken from 2014 to 2016 KNHANES (The Korean National Health and Nutrition Examination Survey) and only the data from ages of 7 years or older were used. The contamination data were collected from the 2014~2016 Total Diet Study and all the analysis were performed using R software. Rockfish, eel, anchovy broth and pollock were mainly exposed to N-nitrosamines. In terms of cooking methods, soups and stews appeared to contain the highest amount of N-nitrosamines. Cereals, fruits, and dairy products in the ingredient categories, and rice dishes and rice combined with others in recipe categories had the lowest level exposure to N-nitrosamines. In case of N-nitrosamines, unlike other cooking related food contaminants, boiled dishes such as soups and stews and dishes mainly consisting of fishes and shellfishes had highest level of exposure, showing a large discrepancy with the previous thought of processed meat is the main source of N-nitrosamines.

• Journal of the Korean Geographical Society
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• v.29 no.2
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• pp.117-136
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• 1994

Contemporary global space economy is so dynamic that any one specific structural force can not explain the whole dynamic processes or trajectories of spatial industrial development. The major purpose of this paper is extending the traditional notion of industrial districts to functioning and development of new industrial districts with relation to the development of high technology industries. Several dynamic forces, which are dominated in new industrial districts in the modern space economy, are incorporated in the formation and dynamic aspects of new industrial districts. Even though key forces governing Marshallian industrial district are localization of small firms, division of labor between firms, constructive cooperation, and industrial atmosphere, Marshall points out a possibility of growing importance of large firms and non-local networks in the districts with changes of external environments. Some of Italian industrial districts can be regarded as Marshallian industrial districts in broader context, but the role of local authorities or institutions and local embeddedness seem to be more important in the Italian industrial districts. More critical implication form the review of Marshallian industrial districts and Italian industrial districts is that the industrial districts are not a static concept but a dynamic one: small firm based industrial districts can be regarded as only a specific feature evolved over time. Dynamic aspects of new industrial districts are resulting from coexistence of contrasting forces governing the functioning and formation of the districts in contemporary global space economy. The contrasting forces governing new industrial districts are coexistence of flexible and mass production systems, local and global networks, local and non-local embeddedness, and small and large firms. Because of these coexistence of contrasting forces, there are various types of new industrial districts. Nine types of industrial districts are identified based on local/non-local networks and intensity of networks in both suppliers and customers linkages. The different types of new industrial districts are described by differences in production systems, embeddedness, governance, cooperation and competition, and institutional factors. Out of nine types of industrial districts, four types - Marshallian; suppliers hub and spoke; customers hub and spoke; and satellite - are regarded as distinctive new industrial districts and four additional types - advanced hub and spoke types (suppliers and customers) and mature satellites (suppliers and customers) - can be evolved from the distinctive types and may be regarded as hybrid types. The last one - pioneering high technology industrial district - can be developed from the advanced hub and spoke types and this type is a most advanced modern industrial district in the era of globalization and high technology. The dynamic aspects of the districts are related with the coexistence of the contrasting forces in the contemporary global space economy. However, the development trajectory is not a natural one and not all the industrial districts can develop to the other hybrid types. Traditionally, localization of industries was developed by historical chances. In the process of high technology industrial development in contemporary global space economy, however, policy and strategies are critical for the formation and evolution of new industrial districts. It needs formation of supportive tissues of institutions for evolution of dyamic pattern of high technology related new industrial districts. Some of the original distinctive types of new industrial districts can not follow the path or trajectory suggested in this paper and may be declined without advancing, if there is no formation of supportive social structure or policy. Provision of information infrastructure and diffusion of an entrepreneurship through the positive supports of local government, public institutions, universities, trade associations and industry associations are important for the evolution of the dynamic new industrial districts. Reduction of sunk costs through the supports for training and retraining of skilled labor, the formation of flexible labor markets, and the establishment of cheap and available telecommunication networks is also regarded as a significant strategies for dynamic progress of new industrial districts in the era of high technology industrial development. In addition, development of intensive international networks in production, technology and information is important policy issue for formation and evolution of the new industrial districts which are related with high technology industrial development.