• Title/Summary/Keyword: software testing

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Evaluating ChatGPT's Competency in BIM Related Knowledge via the Korean BIM Expertise Exam (BIM 운용 전문가 시험을 통한 ChatGPT의 BIM 분야 전문 지식 수준 평가)

  • Choi, Jiwon;Koo, Bonsang;Yu, Youngsu;Jeong, Yujeong;Ham, Namhyuk
    • 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.

The Influence of Key Opinion Consumers on Purchase Intention in Live Streaming Commerce

  • Cong-Ying Sun;Jin-Yan Tian
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.6
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    • pp.211-221
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    • 2024
  • Live streaming commerce has emerged as an innovative e-commerce model. This study, based on the Elaboration Likelihood Model (ELM), aims to explore the impact of Key Opinion Consumers' (KOCs) attributes in live streaming commerce on purchase intentions on short video platforms. A survey was conducted with 411 consumers, and data analysis and hypothesis testing were performed using SPSS 24.0 and AMOS 23.0 software. Research has found that differences in consumers' information processing abilities lead to different pathway selections. Central route factors such as recommendation consistency, product involvement, and professionalism, as well as peripheral route factors such as recommendation timeliness, all have significant positive effects on consumers' purchase intention. However, visual cues in the peripheral route do not have a significant impact. This study aims to provide theoretical support and practical guidance for the development of the live streaming commerce industry, and to help companies adjust their promotion strategies based on differences in consumer information processing, thereby improving purchase conversion rates.

Changes and Perspects in the Regulation on Medical Device Approval Report Review, etc. : Focus on Traditional Korean Medical Devices (의료기기 허가·신고·심사 등에 관한 규정 변화와 전망 : 한의 의료기기 중심으로)

  • DaeJin Kim;Byunghee Choi;Taeyeung Kim;Sunghee Jung;Woosuk Kang
    • Journal of Society of Preventive Korean Medicine
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    • v.28 no.1
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    • pp.31-42
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    • 2024
  • Objective : In order to understand the changes in domestic approval regulations applicable to traditional Korean medical device companies, this article will explain the major amendments 「Regulation on Medical Device Approval Report Review, etc.」 from 2005 to the present on a year-by-year basis, and provide a counter plan to the recent changes in approval regulations. Methods : We analysed the changes in approval regulatory amendments related to the traditional Korean medical devices from 2005 to the present. Results : The Ministry of Food and Drug Safety is continuously improving medical device approval regulations to ensure the global competitiveness of domestic medical devices and contribute to the improvement of public health. Recent major approval regulatory amendments include the establishment of a review system for software medical devices and digital therapeutics, the recognition of real world evidence materials, the introduction of a biological evaluation of medical devices within a risk management process and a medical device approval licence renewal system. Conclusions : It is expected that the range of medical devices available to Korean medicine doctors will continue to expand in the future through the provision of non-face-to-face medical services and the development of advanced and new medical devices, as well as wearable medical devices and digital therapeutics. In order to increase the market entry potential of traditional Korean medical devices that incorporate advanced technologies such as digital technology and AI-based diagnosis and prediction technology, it is urgent that the government provide significant support to traditional Korean medical device companies to improve approval regulatory compliance.

A Review on Detection of COVID-19 Cases from Medical Images Using Machine Learning-Based Approach

  • Noof Al-dieef;Shabana Habib
    • International Journal of Computer Science & Network Security
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    • v.24 no.3
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    • pp.59-70
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    • 2024
  • Background: The COVID-19 pandemic (the form of coronaviruses) developed at the end of 2019 and spread rapidly to almost every corner of the world. It has infected around 25,334,339 of the world population by the end of September 1, 2020 [1] . It has been spreading ever since, and the peak specific to every country has been rising and falling and does not seem to be over yet. Currently, the conventional RT-PCR testing is required to detect COVID-19, but the alternative method for data archiving purposes is certainly another choice for public departments to make. Researchers are trying to use medical images such as X-ray and Computed Tomography (CT) to easily diagnose the virus with the aid of Artificial Intelligence (AI)-based software. Method: This review paper provides an investigation of a newly emerging machine-learning method used to detect COVID-19 from X-ray images instead of using other methods of tests performed by medical experts. The facilities of computer vision enable us to develop an automated model that has clinical abilities of early detection of the disease. We have explored the researchers' focus on the modalities, images of datasets for use by the machine learning methods, and output metrics used to test the research in this field. Finally, the paper concludes by referring to the key problems posed by identifying COVID-19 using machine learning and future work studies. Result: This review's findings can be useful for public and private sectors to utilize the X-ray images and deployment of resources before the pandemic can reach its peaks, enabling the healthcare system with cushion time to bear the impact of the unfavorable circumstances of the pandemic is sure to cause

Lessons from constructing and operating the national ecological observatory network

  • Christopher McKay
    • Journal of Ecology and Environment
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    • v.47 no.4
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    • pp.187-192
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    • 2023
  • The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.

Disease Testing in Pelvic Pain Patients: Comparison between Ultrasound and Computed Tomography Imaging (골반통 환자의 질환 검사: 초음파와 컴퓨터단층촬영 간의 비교)

  • EunHoe Goo
    • Journal of Radiation Industry
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    • v.17 no.4
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    • pp.385-390
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    • 2023
  • The uterus, one of women's reproductive organs, is also closely related to women's health. Among them, hemorrhagic luteal cysts, one of the causes of pelvic pain that women often experience, were observed through CT and ultrasound, and the quality of images was evaluated through quantitative and qualitative evaluations. This study sought to find out whether the test method is more helpful to patients during CT and ultrasound. This study was conducted on 15 adolescent women and 15 adult women(21.31±3.45 average age). The equipment used for filming used EC3-10X (3~10 MHZ) and Philips Mx8000 iCT 256 among Endocavity Probes among Ecube Platinum. After setting a constant ROI on the cyst and the interface as a quantitative analysis method, SNR and CNR values were measured on a 5-point scale based on image quality, lesion clarity, image distortion, clarity of the interface, and motion artifacts (p<0.05). Independent t-test and Mann Whiteny U were performed, and the statistical program used was noted when SPSS (Version 22.0 for windows software package, Chicago, IL, USA) was statistically less than 0.05. Comparing the SNR and CNR values for this experiment, it can be seen that the SNR value was higher in the case of CT images(p<0.05). As a result of the qualitative evaluation, the quality of the image, the clarity of the lesion, the distortion of the image, the clarity of the interface, and the clarity of the boundary were measured on a 5-point scale based on the movement artifact. Comparing each score, CT images scored higher with a finer difference than ultrasound images(p<0.05). In conclusion, both test methods showed excellent results in finding the patient's lesions. However, in quantitative and qualitative evaluations, CT produced higher results in detecting lesions than ultrasound. However, for cyst tests that require continuous observation, ultrasonography, a non-invasive method that is advantageous for patients, will be clinically useful. Therefore, observing the patient's lesions by appropriately distributing these two test methods will provide optimal diagnostic information. These results will be useful for providing clinical basic data and educational materials to CT and US users in the future.

Evaluation of the Applicability of Azon and Azo-Core for Enhancing Airtightness and Thermal Insulation Performance of Insulated Shutters (단열 셔터의 기밀성능 및 단열성능 확보를 위한 Azon 및 Azo-Core의 적용성 평가)

  • Kil, Min-Woo;Kim, Gyu-Yong;Choi, Byung-Cheol;Ji, Sung-Jun;Youn, Hye-Young;Nam, Jeong-Soo
    • Journal of the Korea Institute of Building Construction
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    • v.24 no.4
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    • pp.437-445
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    • 2024
  • This study investigated the thermal insulation performance of Azon and Azo-Core, two materials commonly used in window frames, for potential application in window shutters. A three-pronged evaluation approach was employed, utilizing the Therm 7.4 software, confidential test results, and dedicated thermal insulation testing. The simulation data indicated that both Azon and Azo-Core offered superior insulating properties compared to conventional shutter insulation materials. When incorporated into shutters, these materials achieved a first-grade sealing performance and a measured average thermal conductivity of 2.018W/m2·K. While this thermal conductivity value surpasses the standard requirements of 1.5W/m2·K for central regions and 1.8W/m2·K for southern regions in Korea, it falls within the acceptable limit of 2.2W/m2·K established for the Jeju region. Based on these findings, Azo-Core, warranting further dedicated research, presents itself as a promising candidate for shutter insulation material, particularly in applications targeting the Jeju region.

Comparison analysis of YOLOv10 and existing object detection model performance

  • Joon-Yong Kim
    • Journal of the Korea Society of Computer and Information
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    • v.29 no.8
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    • pp.85-92
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    • 2024
  • In this paper presents a comparative analysis of the performance between the latest object detection model, YOLOv10, and its previous versions. YOLOv10 introduces NMS-Free training, an enhanced model architecture, and an efficiency-centric design, resulting in outstanding performance. Experimental results using the COCO dataset demonstrate that YOLOv10-N maintains high accuracy of 39.5% and low latency of 1.84ms, despite having only 2.3M parameters and 6.7G floating-point operations (FLOPs). The key performance metrics used include the number of model parameters, FLOPs, average precision (AP), and latency. The analysis confirms the effectiveness of YOLOv10 as a real-time object detection model across various applications. Future research directions include testing on diverse datasets, further model optimization, and expanding application scenarios. These efforts aim to further enhance YOLOv10's versatility and efficiency.

Design Study of Digital Map Architecture for AAV (미래형 항공기체(AAV)용 전자지도 아키텍처 설계 연구)

  • Kyung-Chul Choi;Ji-Hun Kim;Nak-Min Choi;Gyong-Hoon Baek
    • Journal of Advanced Navigation Technology
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    • v.28 no.4
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    • pp.393-399
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    • 2024
  • The digital map computer for advanced air vehicles (AAV) must be high-performance, lightweight, portable, and modular. It should receive data on terrain, weather, and obstacles from external modules to display digital maps accurately. This necessitates robust communication capabilities with external devices via an Ethernet interface and the ability to output digital map visuals clearly through an high-defintion multimedia Interface (HDMI) or digital visual interface (DVI) interface. This paper presents the design of both hardware and software architecture that fulfills these critical requirements for an AAV digital map system. Additionally, it establishes the minimum specifications needed and verifies the suitability of the designed digital map computer through rigorous performance measurements and testing. By ensuring these standards, the digital map computer can reliably support the complex navigational needs of AAV, enhancing operational efficiency and safety.

Development of the Information Delivery System for the Home Nursing Service (가정간호사업 운용을 위한 정보전달체계 개발 I (가정간호 데이터베이스 구축과 뇌졸중 환자의 가정간호 전산개발))

  • Park, J.H;Kim, M.J;Hong, K.J;Han, K.J;Park, S.A;Yung, S.N;Lee, I.S;Joh, H.;Bang, K.S
    • Journal of Home Health Care Nursing
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    • v.4
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    • pp.5-22
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    • 1997
  • The purpose of the study was to development an information delivery system for the home nursing service, to demonstrate and to evaluate the efficiency of it. The period of research conduct was from September 1996 to August 31, 1997. At the 1st stage to achieve the purpose, Firstly Assessment tool for the patients with cerebral vascular disease who have the first priority of HNS among the patients with various health problems at home was developed through literature review. Secondly, after identification of patient nursing problem by the home care nurse with the assessment tool, the patient's classification system developed by Park (1988) that was 128 nursing activities under 6 categories was used to identify the home care nurse's activities of the patient with CAV at home. The research team had several workshops with 5 clinical nurse experts to refine it. At last 110 nursing activities under 11 categories for the patients with CVA were derived. At the second stage, algorithms were developed to connect 110 nursing activities with the patient nursing problems identified by assessment tool. The computerizing process of the algorithms is as follows: These algorithms are realized with the computer program by use of the software engineering technique. The development is made by the prototyping method, which is the requirement analysis of the software specifications. The basic features of the usability, compatibility, adaptability and maintainability are taken into consideration. Particular emphasis is given to the efficient construction of the database. To enhance the database efficiency and to establish the structural cohesion, the data field is categorized with the weight of relevance to the particular disease. This approach permits the easy adaptability when numerous diseases are applied in the future. In paralleled with this, the expandability and maintainability is stressed through out the program development, which leads to the modular concept. However since the disease to be applied is increased in number as the project progress and since they are interrelated and coupled each other, the expand ability as well as maintainability should be considered with a big priority. Furthermore, since the system is to be synthesized with other medical systems in the future, these properties are very important. The prototype developed in this project is to be evaluated through the stage of system testing. There are various evaluation metrics such as cohesion, coupling and adaptability so on. But unfortunately, direct measurement of these metrics are very difficult, and accordingly, analytical and quantitative evaluations are almost impossible. Therefore, instead of the analytical evaluation, the experimental evaluation is to be applied through the test run by various users. This system testing will provide the viewpoint analysis of the user's level, and the detail and additional requirement specifications arising from user's real situation will be feedback into the system modeling. Also. the degree of freedom of the input and output will be improved, and the hardware limitation will be investigated. Upon the refining, the prototype system will be used as a design template. and will be used to develop the more extensive system. In detail. the relevant modules will be developed for the various diseases, and the module will be integrated by the macroscopic design process focusing on the inter modularity, generality of the database. and compatibility with other systems. The Home care Evaluation System is comprised of three main modules of : (1) General information on a patient, (2) General health status of a patient, and (3) Cerebrovascular disease patient. The general health status module has five sub modules of physical measurement, vitality, nursing, pharmaceutical description and emotional/cognition ability. The CVA patient module is divided into ten sub modules such as subjective sense, consciousness, memory and language pattern so on. The typical sub modules are described in appendix 3.

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