• International Journal of Industrial Entomology and Biomaterials
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• v.47 no.2
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• pp.79-89
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• 2023

This paper is about the development results of an automatic silkworm breeding system to reduce labor and time by automatically performing the works for silkworm droppings changing and feed its food. It consists of an automatic guided vehicle and a processing unit. The automatic guided vehicle transports a silkworm dropping changing frame mounted on a silkworm tray stand, and the processing unit takes over the dropping changing frame on it, removes excrement contained the droppings changing frame and feeds silkworm food. In the case of the current silkworm farming, because the breeding period for large silkworms (4 to 5 stage) is short to 14 days and the supply of mulberry leaves takes 98% of the total amount of mulberry leaves needed for breeding silkworms at this time, labor concentration is intensive, and all breeding works depends on manpower. Therefore, it was difficult to breed large silkworms on a large scale. Moreover, silkworms are bred by adding Silkworm bed (Seop) and mulberry in the silkworm tray, and their droppings changing is to separate silkworms and excrement by moving silkworm trays one by one, and the production cost increases due to the high-cost manpower for silkworm breeding. To solve this problem, technology for automating silkworm breeding has also been developed. However, there is still a limitation that silkworm feeding and droppings changing works are not suitable for mass breeding because a lot of labor and time are spent depending on manual work. Therefore, a new silkworm breeding system for breeding silkworm automatically is needed and so we developed an Automatic Silkworm Breeding System applying the droppings change frame, the inverting unit, the feeding silkworm food device and automatic guided vehicle.

• Imaging Science in Dentistry
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• v.53 no.4
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• pp.271-281
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• 2023

Purpose: The objective of this scoping review was to investigate the applicability and performance of various convolutional neural network (CNN) models in tooth numbering on panoramic radiographs, achieved through classification, detection, and segmentation tasks. Materials and Methods: An online search was performed of the PubMed, Science Direct, and Scopus databases. Based on the selection process, 12 studies were included in this review. Results: Eleven studies utilized a CNN model for detection tasks, 5 for classification tasks, and 3 for segmentation tasks in the context of tooth numbering on panoramic radiographs. Most of these studies revealed high performance of various CNN models in automating tooth numbering. However, several studies also highlighted limitations of CNNs, such as the presence of false positives and false negatives in identifying decayed teeth, teeth with crown prosthetics, teeth adjacent to edentulous areas, dental implants, root remnants, wisdom teeth, and root canal-treated teeth. These limitations can be overcome by ensuring both the quality and quantity of datasets, as well as optimizing the CNN architecture. Conclusion: CNNs have demonstrated high performance in automated tooth numbering on panoramic radiographs. Future development of CNN-based models for this purpose should also consider different stages of dentition, such as the primary and mixed dentition stages, as well as the presence of various tooth conditions. Ultimately, an optimized CNN architecture can serve as the foundation for an automated tooth numbering system and for further artificial intelligence research on panoramic radiographs for a variety of purposes.

• Journal of KIBIM
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• v.13 no.3
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• pp.1-11
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• 2023

In order to use BIM as a tool for improving the productivity and quality of products in the construction industry, a BIM model must be created from the design stage first. Infrastructure structures such as bridges and tunnels are mainly created based on three-dimensional alignment in the generation of BIM models. Especially, generation of BIM models based on three-dimensional linearity has high task difficulty and algorithms for automating BIM modeling for railway infra structures have been suggested in previous studies. This study improved the BIM modeling automation algorithm of railway infrastructures and developed a system based on the algorithm so that it can be easily used by ordinary users. The system was built as an add-in system of Autodesk's Revit. As an improvement first, it is possible to arrange different libraries for each pattern, enabling various uses. In addition, it can be created models of several members with a single process and the system can automatically places structures that are added periodically, such as Rock Bolt and Fore Polling. Finally, 3D length information and volume for each pattern are automatically calculated for more accurate 3D-based volume calculation. This study contributes to increasing user accessibility by building a BIM modeling automation algorithm into a system. The system is expected to improve the efficiency of BIM modeling creation of linear-based infra structures, including railway infrastructure.

• Computers and Concrete
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• v.33 no.5
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• pp.535-544
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• 2024

In the rapidly advancing landscape of computer vision (CV) technology, there is a burgeoning interest in its integration with the construction industry. Camera calibration is the process of deriving intrinsic and extrinsic parameters that affect when the coordinates of the 3D real world are projected onto the 2D plane, where the intrinsic parameters are internal factors of the camera, and extrinsic parameters are external factors such as the position and rotation of the camera. Camera pose estimation or extrinsic calibration, which estimates extrinsic parameters, is essential information for CV application at construction since it can be used for indoor navigation of construction robots and field monitoring by restoring depth information. Traditionally, camera pose estimation methods for cameras relied on target objects such as markers or patterns. However, these methods, which are marker- or pattern-based, are often time-consuming due to the requirement of installing a target object for estimation. As a solution to this challenge, this study introduces a novel framework that facilitates camera pose estimation using standardized materials found commonly in construction sites, such as concrete forms. The proposed framework obtains 3D real-world coordinates by referring to construction materials with certain specifications, extracts the 2D coordinates of the corresponding image plane through keypoint detection, and derives the camera's coordinate through the perspective-n-point (PnP) method which derives the extrinsic parameters by matching 3D and 2D coordinate pairs. This framework presents a substantial advancement as it streamlines the extrinsic calibration process, thereby potentially enhancing the efficiency of CV technology application and data collection at construction sites. This approach holds promise for expediting and optimizing various construction-related tasks by automating and simplifying the calibration procedure.

• Knowledge Management Research
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• v.24 no.4
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• pp.153-176
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• 2023

Generative AI, especially conversational AI like ChatGPT, has recently gained traction as a technological alternative for automating customer service. However, there is still a lack of research on whether current generative AI technologies can effectively replace traditional human managers in customer service automation, and whether they are advantageous in some situations and disadvantageous in others, depending on the conditions and environment. To answer the question, "Can generative AI replace human managers in customer service activities?", this study conducted experiments and surveys on customer online reviews of a food delivery platform. We applied the perspective of the elaboration likelihood model to generate hypotheses about whether there is a difference between positive and negative online reviews, and analyzed whether the hypotheses were supported. The analysis results indicate that for positive reviews, generative AI can effectively replace human managers. However, for negative reviews, complete replacement is challenging, and human managerial intervention is considered more desirable. The results of this study can provide valuable practical insights for organizations looking to automate customer service using generative AI.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.49-55
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• 2024

This paper proposes PredFeed Net, a neural network model that mimics the food distribution of fish farming experts. Unlike existing food distribution automation systems, PredFeed Net predicts food distribution by learning the food distribution patterns of experts. This has the advantage of being able to learn using only existing environmental data and food distribution records from food distribution experts, without the need to experiment by changing food distribution variables according to the environment in an actual aquarium. After completing training, PredFeed Net predicts the next food ration based on the current environment or fish condition. Prediction of feed ration is a necessary element for automating feed ration, and feed ration automation contributes to the development of modern fish farming such as smart aquaculture and aquaponics systems.

• Information Systems Review
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• v.21 no.4
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• pp.157-173
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• 2019

Robotic Process Automation (RPA) has attracted great attention from diverse home and foreign industries. To provide lessons learned and action principles based on real RPA adoption and application experiences, various case studies have been conducted. However, lacking is an investigation of public sector for RPA adoption, especially in Korea. To reduce the research gap, this study presents a case study of RPA adoption by a representative Korean ICT public organization, NIA (National Information society Agency). By automating a core process, entering a document to a governmental portal service, NIA has achieved various management performances in terms of cost, operation, and business impacts. Especially, by relieving four types of rigidity of public institutions (i.e. structure, human resource, tasks, and rules), Our case study result suggests that RPA enables public institutes to overcome obstacles of pursuing digital transformation. Implications and limitations for future public RPA adopters are offered.

• Journal of the Korea Institute of Building Construction
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• v.24 no.4
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• pp.507-515
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• 2024

Recent advancements in Building Information Modeling(BIM) have significantly impacted the construction industry, driving competitiveness and innovation. However, rebar construction, a critical component influencing project quality and cost, has lagged behind in BIM adoption. Traditional methods relying heavily on 2D drawings for rebar detailing have hindered efficiency and introduced potential errors. This paper presents a novel system designed to automate the detailed modeling of rebar, thereby promoting BIM integration within rebar construction and optimizing construction management processes. The system leverages confirmed structural drawings from the post-structural design phase to automatically generate intricate rebar models for columns and beams. To ensure adherence to domestic structural design standards, the system is developed using C# programming language and the Revit API. By automating rebar modeling, this system aims to minimize human error, reduce labor-intensive tasks, and enhance overall rebar construction efficiency through the effective utilization of generated rebar model data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.377-386
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• 2012

Crack sealing has been widely used in the pavement maintenance due to its advantage of repairing the cracks at the preliminary stages. However, it has been analyzed that the crack sealing work process is dangerous and labor intensive. Moreover, quality and productivity of crack sealing work are highly depended on labor experience and skills. Therefore, various crack sealing machines have been researched but revealed many limitations in practical application. This research analyses conventional crack sealing work process and previously developed crack sealing machines in order to develop an automated pavement crack sealing machine which can be practically and widely applied in the construction fields. This paper develops the previously proposed conceptual design by drawing detailed designs and fabricating the hardware(manipulator and end-effector) of the automated pavement crack sealing machine. The crack sealing machine suggested in this paper overcomes limitations of existing crack sealing machines and designed to meet the domestic road conditions and regulations. It is expected that automating the conventional crack sealing method contributes to the improvement of quality, economy and reduce accidents.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.96-105
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• 2011

Ubiquitos sensor network(USN) is a technology which is widely used in our life. This paper introduces an example of design and implementation for a system which is based on the USN technology and can provide an efficient management tool for a space that should be precisely controlled for a certain range of uniformity in temperature and humidity. This introduced system builds a wireless sensor network using a number of sensor modules that are equipped with temperature and humidity sensors, and collects temperature and humidity information in real-time while simultaneously providing a method for monitoring the status of temperature and humidity by the graphical user interface. Also, the system will give a warning signal if the monitored values are differ from the pre-specified values of temperature and humidity for each sensor module more than a certain amount of tolerance. This temperature and humidity logging and monitoring system can perform better management for the space easily and efficiently by automating the existing manual method for data collection and management. Furthermore, using the stored data, it can make possible to perform post-analysis on the problems caused by temperature and humidity and to obtain information for environmental enhancement for the space.