• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.56-65
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• 2022

This study tried to identify the key success factors of ABC by identifying the influence of ABC's success factors on project performance and analyzing the moderating effect of communication. For this purpose, factors applicable to construction projects were extracted through case studies related to the success factors of ABC, an activity-based financial management technique. The survey method was conducted as an online survey method using the Delphi method. For statistical analysis, frequency analysis and factor analysis were performed with SPSS Statistic 20, and hypothesis testing was performed with SmartPLS 2.0. As a result of the analysis, it was found that linkage with quality initiatives affects not only ABC's success factors on project performance, but also communication moderation effects. It was confirmed that linkage and communication with quality initiatives are the most important key success factors for ABC's success. Based on the results of this study, it is expected that if ABC and quality management are well linked, it will be effective in improving project performance.

• Journal of KIBIM
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• v.13 no.3
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• pp.21-29
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• 2023

ChatGPT, a chatbot based on GPT large language models, has gained immense popularity among the general public as well as domain professionals. To assess its proficiency in specialized fields, ChatGPT was tested on mainstream exams like the bar exam and medical licensing tests. This study evaluated ChatGPT's ability to answer questions related to Building Information Modeling (BIM) by testing it on Korea's BIM expertise exam, focusing primarily on multiple-choice problems. Both GPT-3.5 and GPT-4 were tested by prompting them to provide the correct answers to three years' worth of exams, totaling 150 questions. The results showed that both versions passed the test with average scores of 68 and 85, respectively. GPT-4 performed particularly well in categories related to 'BIM software' and 'Smart Construction technology'. However, it did not fare well in 'BIM applications'. Both versions were more proficient with short-answer choices than with sentence-length answers. Additionally, GPT-4 struggled with questions related to BIM policies and regulations specific to the Korean industry. Such limitations might be addressed by using tools like LangChain, which allow for feeding domain-specific documents to customize ChatGPT's responses. These advancements are anticipated to enhance ChatGPT's utility as a virtual assistant for BIM education and modeling automation.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.169-177
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• 2024

Industrial Wireless Sensor Network (IWSN) is a key feature of Industrial IoT that enables industrial automation through process monitoring and control by connecting industrial equipment such as sensors, robots, and machines wirelessly, and must support the strict requirements of modern industrial environments such as real-time, reliability, and energy efficiency. To achieve these goals, IWSN uses reliable communication methods such as multipath routing, fixed redundant resource allocation, and non-contention-based scheduling. However, the issue of wasting redundant resources that are not utilized for communication degrades not only the efficiency of limited radio resources but also the energy efficiency. In this paper, we propose a scheme that utilizes reinforcement learning in communication scheduling to periodically identify unused wireless resources and reallocate them to save energy consumption of the entire industrial network. The experimental performance evaluation shows that the proposed approach achieves about 30% improvement of resource efficiency in scheduling compared to the existing method while supporting high reliability. In addition, the energy efficiency and latency are improbed by more than 21% and 38%, respectively, by reducing unnecessary communication.

• Journal of Biosystems Engineering
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• v.43 no.1
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• pp.72-80
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• 2018

Purpose: A modern greenhouse consists of various Information and Communications Technology (ICT) components e.g., sensor nodes, actuator nodes, gateways, controllers, and operating softwarethat communicate with each other. The interoperability between these components is an essential characteristic for any greenhouse control system. A greenhouse control system could not work unless the components communicate via common interfaces. The TTAK.KO-06.0288 is an interface standard consisting of four parts. Notably, TTAK.KO-06.0288-Part3, which describes the interface between a greenhouse operating system (GOS) and a greenhouse control gateway (GCG), is the core standard of TTAK.KO-06.0288. The objectives of this study were to analyze the TTAK.KO-06.0288-Part3 standard, to suggest alternative solutions for identified issues, and to develop a library as a proof of the alternative solutions. Methods: The "data field" was analyzed using a comparative analysis method, since it is a data transmission unit of TTAK.KO-06.0288-Part3. It was compared with other parts of TTAK.KO-06.0288 in terms of definition, format, size, and possible values. Although TTAK.KO-06.0288-Part1 and TTAK.KO-06.0288-Part2 do not use a "data field," they have a similar data structure. That structure was compared with the "data field" of TTAK.KO-06.0288-Part3. Results: Twenty-one issues were identified across four categories: inter-standard issues, intra-standard issues, operational issues, and misprint issues. Since some of the issues can raise interoperability problems, 16 alternative solutions were suggested. In order to prove the alternative solutions, an open-source communication library called libtp3 was developed. The library passed 14 unit tests and was adapted to two research. Conclusions: Although TTAK.KO-06.0288-Part3 is an interface standard for communication between a GOS and a GCG, it might not communicate between different implementations because of the identified issues in the standard. These issues could be solved by the alternative solutions, which could be used to revise TTAK.KO-06.0288. In addition, a relevant organization should develop a program for compatibility testing and should pursue test products for smart greenhouses.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.185-195
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• 2018

As machines have been automated in the field of industries in recent years, it is a paramount importance to manage and maintain the automation machines. When a fault occurs in sensors attached to the machine, the machine may malfunction and further, a huge damage will be caused in the process line. To prevent the situation, the fault of sensors should be monitored, diagnosed and classified in a proper way. In the paper, we propose a sensor fault detection scheme based on SVM and CNN to detect and classify typical sensor errors such as erratic, drift, hard-over, spike, and stuck faults. Time-domain statistical features are utilized for the learning and testing in the proposed scheme, and the genetic algorithm is utilized to select the subset of optimal features. To classify multiple sensor faults, a multi-layer SVM is utilized, and ensemble technique is used for CNN. As a result, the SVM that utilizes a subset of features selected by the genetic algorithm provides better performance than the SVM that utilizes all the features. However, the performance of CNN is superior to that of the SVM.

• Journal of Pharmaceutical Investigation
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• v.30 no.3
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• pp.191-199
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• 2000

Genomics is providing targets faster than we can validate them and combinatorial chemistry is providing new chemical entities faster than we can screen them. Historically, the drug discovery cascade has been established as a sequential process initiated with a potency screening against a selected biological target. In this sequential process, pharmacokinetics was often regarded as a low-throughput activity. Typically, limited pharmacokinetics studies would be conducted prior to acceptance of a compound for safety evaluation and, as a result, compounds often failed to reach a clinical testing due to unfavorable pharmacokinetic characteristics. A new paradigm in drug discovery has emerged in which the entire sample collection is rapidly screened using robotized high-throughput assays at the outset of the program. Higher-throughput pharmacokinetics (HTPK) is being achieved through introduction of new techniques, including automation for sample preparation and new experimental approaches. A number of in vitro and in vivo methods are being developed for the HTPK. In vitro studies, in which many cell lines are used to screen absorption and metabolism, are generally faster than in vivo screening, and, in this sense, in vitro screening is often considered as a real HTPK. Despite the elegance of the in vitro models, however, in vivo screenings are always essential for the final confirmation. Among these in vivo methods, cassette dosing technique, is believed the methods that is applicable in the screening of pharmacokinetics of many compounds at a time. The widespread use of liquid chromatography (LC) interfaced to mass spectrometry (MS) or tandem mass spectrometry (MS/MS) allowed the feasibility of the cassette dosing technique. Another approach to increase the throughput of in vivo screening of pharmacokinetics is to reduce the number of sample analysis. Two common approaches are used for this purpose. First, samples from identical study designs but that contain different drug candidate can be pooled to produce single set of samples, thus, reducing sample to be analyzed. Second, for a single test compound, serial plasma samples can be pooled to produce a single composite sample for analysis. In this review, we validated the issue whether the second method can be applied to practical screening of in vivo pharmacokinetics using data from seven of our previous bioequivalence studies. For a given drug, equally spaced serial plasma samples were pooled to achieve a 'Pooled Concentration' for the drug. An area under the plasma drug concentration-time curve (AUC) was then calculated theoretically using the pooled concentration and the predicted AUC value was statistically compared with the traditionally calculated AUC value. The comparison revealed that the sample pooling method generated reasonably accurate AUC values when compared with those obtained by the traditional approach. It is especially noteworthy that the accuracy was obtained by the analysis of only one sample instead of analyses of a number of samples that necessitates a significant man-power and time. Thus, we propose the sample pooling method as an alternative to in vivo pharmacokinetic approach in the selection potential lead(s) from combinatorial libraries.

• Journal of Korea Game Society
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• v.9 no.3
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• pp.139-150
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• 2009

This paper attempts to investigate the establishment of an interactive knowledge base for action planning by virtual agents and an interactive knowledge-based planning system. A fixed knowledge base is unable to properly handle a change in circumstances because fixed planning is only available under a fixed knowledge base. Therefore, this paper proposes the establishment of an interactive knowledge base which is applicable to diverse environments and an artificial intelligence planning system in which an interactive knowledge base is available. The interactive knowledge base proposed in this paper consists of motivation, behavior, object and action. The association relationship between knowledge base and its input is set using an automation tool. With this tool, a user can easily add to or amend the components of the knowledge base. With this knowledge base, a character plans all action items and chooses one of them to take an action. Since a new action can be applicable by updating the knowledge base even when the character environment changes, it is very useful for virtual reality content developers. This paper has established a relationship between scalable interactive knowledge base components and other components and proposes a convenient input tool and a planning system algorithm effective for an interactive knowledge base. The results of this study have been verified through testing in a virtual environment ('virtual library').

• Convergence Security Journal
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• v.24 no.2
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• pp.89-104
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• 2024

This study is an empirical study to examine the factors that influence the intention to use artificial intelligence (AI) technology for SW engineering-related tasks, and the purpose of the study is to understand the key factors that influence the use in terms of AI augmentation characteristics and interactive UI/UX characteristics. For this purpose, a survey was conducted among information and communication workers who have experience in using AI-related technologies and the collected data was analyzed. The results of the empirical analysis showed that perceived usefulness was positively influenced by the factors of expertise, interestingness, realism, aesthetics, efficiency, and flexibility, and perceived ease of use was positively influenced by the factors of expertise, interestingness, realism, aesthetics, and flexibility. Variety had no effect on both perceived ease of use and perceived usefulness. Perceived ease of use had a significant effect on perceived immersion, which positively influenced intention to use. These findings are significant in that they provide an academic understanding of the factors that influence the use of AI-enhanced tools in SW engineering-related tasks such as application design, development, testing, and process automation, as well as practical directions for the creators of tools that provide AI-enhanced development services to develop user acquisition strategies.

• The Korean Journal of Blood Transfusion
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• v.23 no.2
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• pp.127-135
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• 2012

Background: Despite modern advances in laboratory automated medicine, work-process in the blood bank is still handled manually. Several automated immunohematological instruments have been developed and are available in the market. The IH-1000 (Bio-Rad Laboratories, Hercules, CA, USA), a fully automated instrument for immunohematology, was recently introduced. In this study, we evaluated the performance of the IH-1000 for ABO/Rh typing and irregular antibody screening. Methods: In October 2011, a total of 373 blood samples for ABO/Rh typing and 303 cases for unexpected antibody screening were collected. The IH-1000 was compared to the manual tube and slide methods for ABO/Rh typing and to the microcolumn agglutination method (DiaMed-ID system) for antibody screening. Results: For ABO/Rh typing, concordance rate was 100%. For unexpected antibody screening, positive results for both column agglutination and IH-1000 were observed in 10 cases (four cases of anti-E and c, three of anti-E, one of anti-D, one of anti-M, and one of anti-Xg) and negative results for both were observed in 289 cases. The concordance rate between IH-1000 and column agglutination was 98.7%. Sensitivity and specificity were 90.9% and 99.3%, respectively. Conclusion: The automated IH-1000 showed good correlation with the manual tube and slide methods and the microcolumn agglutination method for ABO-RhD typing and irregular antibody screening. The IH-1000 can be used for routine pre-transfusion testing in the blood bank.