• 정보보호학회논문지
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• 제34권2호
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• pp.229-244
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• 2024

최근 APR1400 노형과 같이 원자력발전소의 디지털 기술 적용에 따라 "이블 PLC"같은 원자력시설 대상의 공급망 공격이 증가하는 추세이다. 원자력 공급망 보안에 있어 산업 특성상 수많은 공급업체가 존재하기에 이를 체계적으로 관리할 수 있는 자원 관리 시스템이 필요하다. 하지만, 제어시스템 특성상 소프트웨어 자산의 긴 생명 주기로 인해 속성 정보가 일관되지 않게 관리된다는 문제점이 존재한다. 또한, 운영 환경의 가용성 문제로 인해 형상 관리 자동화 도입이 미흡한 상태에서 입력 오류와 같은 한계점이 존재한다. 본 연구에서는 SBOM(Software Bill Of Materials)을 적용한 체계적인 자산 관리 방안 및 자연어처리 기법을 적용한 입력 오류에 관한 개선 방안을 제안한다.

• 한국컴퓨터정보학회논문지
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• 제29권6호
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• pp.13-22
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• 2024

기사성광고의 필요성과 긍정적인면도 존재하나, 일부 무분별한 '기사성 광고'로 인하여 과장되고 위장된 정보를 전달함에 따라 독자들은 일반기사와 기사성 광고의 구별이 어려움에 따라 많은 정보의 오인과 혼란을 하고 있다. 독자들은 앞으로도 계속 새로운 정보를 획득하고 이러한 정보를 적재적소에 적용하여 많은 가치를 가져와야 하기에, 정확한 일반기사와 기사성 광고를 식별하는 것이 더욱이 중요하다고 판단된다. 따라서 일반기사와 기사성 광고의 구별된 정보를 필요로 하기에, 이러한 일환으로, 인터넷신문에서 이러한 무분별한 기사성 광고로 인한 정확한 정보식별의 어려움이 많은 독자들을 위해, 본 논문에서는 IT기술과 AI기술을 접목한 시스템측면에서 해결할 수 있는 방법을 제시하고자 하였으며, 이러한 방법은 광고성 키워드를 찾아내어 정제해주는 지식기반 자연어처리 방법과 딥러닝기술을 이용한 기사성 광고를 추출하고자 설계 하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.263-283
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• 2024

Users' comments after online shopping are critical to product reputation and business improvement. These comments, sometimes known as e-commerce reviews, influence other customers' purchasing decisions. To confront large amounts of e-commerce reviews, automatic analysis based on machine learning and deep learning draws more and more attention. A core task therein is sentiment analysis. However, the e-commerce reviews exhibit the following characteristics: (1) inconsistency between comment content and the star rating; (2) a large number of unlabeled data, i.e., comments without a star rating, and (3) the data imbalance caused by the sparse negative comments. This paper employs Bidirectional Encoder Representation from Transformers (BERT), one of the best natural language processing models, as the base model. According to the above data characteristics, we propose the F_MixBERT framework, to more effectively use inconsistently low-quality and unlabeled data and resolve the problem of data imbalance. In the framework, the proposed MixBERT incorporates the MixMatch approach into BERT's high-dimensional vectors to train the unlabeled and low-quality data with generated pseudo labels. Meanwhile, data imbalance is resolved by Focal loss, which penalizes the contribution of large-scale data and easily-identifiable data to total loss. Comparative experiments demonstrate that the proposed framework outperforms BERT and MixBERT for sentiment analysis of e-commerce comments.

• 한국음향학회지
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• 제28권1호
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• pp.61-69
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• 2009

본 연구는 예제 기반 대화 시스템에서 응답을 결정하기 위한 핵심 요소 기술 중 하나인 발차간 유사도 측정 방법의 개선에 대해 논한다. 일반적인 문장간 유사도 측정과는 달리, 대화에서 발차간 유사도 측정은 단어 분포간 유사도 뿐만 아니라, 문형, 시제, 긍/부정, 양태등 대화 자연스러움을 결정하는 문장의 다양한 언어적 요소 역시 중요하게 고려되어야 한다. 그러나 기존 연구에서는 이에 대한 고려가 부족 했던 것이 사실이며, 따라서 본 연구에서는 개선 방안으로서 발화의 형태적 유사성 뿐 아니라 다양한 언어적 자질들을 분석하고 이를 유사도 측정에 반영하여 정확도를 향상시키는 새로운 유사도 측정 방법을 제안한다. 또한, 발차의 자질별 유사도를 고려함으로써, 한정된 수의 예제들의 활용도를 높일 수 있는 방법을 제안하였다. 실험 결과 제안하는 방법이 기존 방식에 비해 10%p 이상 정확도 성능 향상이 있었다.

• 대한두개안면성형외과학회지
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• 제25권3호
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• pp.116-122
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• 2024

Background: Due to the importance of evidence-based research in plastic surgery, the authors of this study aimed to assess the accuracy of ChatGPT in generating novel systematic review ideas within the field of craniofacial surgery. Methods: ChatGPT was prompted to generate 20 novel systematic review ideas for 10 different subcategories within the field of craniofacial surgery. For each topic, the chatbot was told to give 10 "general" and 10 "specific" ideas that were related to the concept. In order to determine the accuracy of ChatGPT, a literature review was conducted using PubMed, CINAHL, Embase, and Cochrane. Results: In total, 200 total systematic review research ideas were generated by ChatGPT. We found that the algorithm had an overall 57.5% accuracy at identifying novel systematic review ideas. ChatGPT was found to be 39% accurate for general topics and 76% accurate for specific topics. Conclusion: Craniofacial surgeons should use ChatGPT as a tool. We found that ChatGPT provided more precise answers with specific research questions than with general questions and helped narrow down the search scope, leading to a more relevant and accurate response. Beyond research purposes, ChatGPT can augment patient consultations, improve healthcare equity, and assist in clinical decision-making. With rapid advancements in artificial intelligence (AI), it is important for plastic surgeons to consider using AI in their clinical practice to improve patient-centered outcomes.

• International Journal of Computer Science & Network Security
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• 제23권12호
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• pp.225-234
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• 2023

In this era of information and communication technology (ICT), tremendous improvements have been witnessed in our daily lives. The impact of these technologies is subjective and negative or positive. For instance, ICT has brought a lot of ease and versatility in our lifestyles, on the other hand, its excessive use brings around issues related to physical and mental health etc. In this study, we are bridging these both aspects by proposing the idea of AI based mental healthcare (AIMS). In this regard, we aim to provide a platform where the patient can register to the system and take consultancy by providing their assessment by means of a chatbot. The chatbot will send the gathered information to the machine learning block. The machine learning model is already trained and predicts whether the patient needs a treatment by classifying him/her based on the assessment. This information is provided to the mental health practitioner (doctor, psychologist, psychiatrist, or therapist) as clinical decision support. Eventually, the practitioner will provide his/her suggestions to the patient via the proposed system. Additionally, the proposed system prioritizes care, support, privacy, and patient autonomy, all while using a friendly chatbot interface. By using technology like natural language processing and machine learning, the system can predict a patient's condition and recommend the right professional for further help, including in-person appointments if necessary. This not only raises awareness about mental health but also makes it easier for patients to start therapy.

• Korean Journal of Radiology
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• 제1권1호
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• pp.19-24
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• 2000

Objective: In order to investigate the functional brain anatomy associated with verbal and visual working memory, functional magnetic resonance imaging was performed. Materials and Methods: In ten normal right handed subjects, functional MR images were obtained using a 1.5-T MR scanner and the EPI BOLD technique. An item recognition task was used for stimulation, and during the activation period of the verbal working memory task, consonant letters were used. During the activation period of the visual working memory task, symbols or diagrams were employed instead of letters. For the post-processing of images, the SPM program was used, with the threshold of significance set at p < .001. We assessed activated brain areas during the two stimulation tasks and compared the activated regions between the two tasks. Results: The prefrontal cortex and secondary visual cortex were activated bilaterally by both verbal and visual working memory tasks, and the patterns of activated signals were similar in both tasks. The superior parietal cortex was also activated by both tasks, with lateralization to the left in the verbal task, and bilaterally without lateralization in the visual task. The inferior frontal cortex, inferior parietal cortex and temporal gyrus were activated exclusively by the verbal working memory task, predominantly in the left hemisphere. Conclusion: The prefrontal cortex is activated by two stimulation tasks, and this is related to the function of the central executive. The language areas activated by the verbal working memory task may be a function of the phonological loop. Bilateral prefrontal and superior parietal cortices activated by the visual working memory task may be related to the visual maintenance of objects, representing visual working memory.

• 복식문화연구
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• 제32권2호
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• pp.247-259
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• 2024

This study assessed the effectiveness of brand image communication on consumer perceptions of cruelty-free fashion brands. Brand messaging data were gathered from postings on the official Instagram accounts of three cruelty-free fashion brands and consumer perception data were gathered from Tweets containing keywords related to each brand. Web crawling and natural language processing were performed using Python and sentiment analysis was conducted using the BERT model. By analyzing Instagram content from Stella McCartney, Patagonia, and Freitag from their inception until 2021, this study found these brands all emphasize environmental aspects but with differing focuses: Stella McCartney on ecological conservation, Patagonia on an active outdoor image, and Freitag on upcycled products. Keyword analysis further indicated consumers perceive these brands in line with their brand messaging: Stella McCartney as high-end and eco-friendly, Patagonia as active and environmentally conscious, and Freitag as centered on recycling. Results based on the assessment of the alignment between brand-driven images and consumer-perceived images and the sentiment evaluation of the brand confirmed the outcomes of brand communication performance. The study revealed a correlation between brand image and positive consumer evaluations, indicating that higher alignment of ethical values leads to more positive consumer assessments. Given that consumers tend to prioritize search keywords over brand concepts, it's important for brands to focus on using visual imagery and promotions to effectively convey brand communication information. These findings highlight the importance of brand communication by emphasizing the connection between ethical brand images and consumer perceptions.

• 유통과학연구
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• 제22권4호
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• pp.11-22
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• 2024

Purpose: This research delves into the various factors that influence the performance of restaurant businesses on social commerce platforms in Bangkok, Thailand. The study considers both internal and external factors, including but not limited to business characteristics and location. Moreover, this research also analyzes the effects of employing multiple social commerce platforms on business efficiency and explores the underlying reasons for such effects. Research design, data, and methodology: Restaurants can be classified into different price ranges: low, medium, and high. To further investigate, we employed natural language processing AI to analyze online reviews and evaluate algorithm performance using machine learning techniques. We aimed to develop a model to gauge customer satisfaction with restaurants across different price categories effectively. Results: According to the research findings, several factors significantly impact restaurant groups in the low and mid-price ranges. Among these factors are population density and the number of seats at the restaurant. On the other hand, in the mid-and high-price ranges, the price levels of the food and drinks offered by the restaurant play a crucial role in determining customer satisfaction. Furthermore, the correlation between different social commerce platforms can significantly affect the business performance of high-price range restaurant groups. Finally, the level of online review sentiment has been found to influence customer decision-making across all restaurant types significantly. Conclusions: The study emphasizes that restaurants' characteristics based on their price level differ significantly, and social commerce platforms have the potential to affect one another. It is worth noting that the sentiment expressed in online reviews has a more significant impact on customer decision-making than any other factor, regardless of the type of restaurant in question.

• 한국인터넷방송통신학회논문지
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• 제24권4호
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• pp.9-14
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• 2024

본 연구는 고령화 사회의 노년층 우울증과 고독감 문제를 해결하기 위해 음성 인식 챗봇 시스템을 개발하였다. 이 시스템은 Whisper 모델, GPT 2.5, XTTS2를 활용하여 고성능 음성 인식과 자연어 처리, 텍스트-음성 변환 기능을 제공한다. 사용자는 이를 통해 감정과 상태를 표현하고 적절한 반응을 얻을 수 있으며, 지인의 목소리를 이용한 음성인식 기능으로 친숙함과 안정감을 느낄 수 있다. UX/UI는 스마트 시니어 세대의 인지 반응과 시력 저하, 운동 능력 제약 등을 고려하여 설계되었다. 명도와 선명도가 높은 색상, 가독성이 좋은 서체등을 활용하여 고령자의 사용 편의성을 높였다.이 연구는 음성 기반 인터페이스를 통해 노년층의 삶의 질 향상에 기여할 것으로 기대된다.