• Journal of the Semiconductor & Display Technology
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• v.22 no.4
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• pp.53-58
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• 2023

The storage capacity of 3D-NAND flash memory has been enhanced by the multi-layer dielectrics. The deposition process has become more challenging due to the tight process margin and the demand for accurate process control. To reduce product costs and ensure successful processes, process diagnosis techniques incorporating artificial intelligence (AI) have been adopted in semiconductor manufacturing. Recently there is a growing interest in process diagnosis, and numerous studies have been conducted in this field. For higher model accuracy, various process and sensor data are required, such as optical emission spectroscopy (OES), quadrupole mass spectrometer (QMS), and equipment control state. Among them, OES is usually used for plasma diagnostic. However, OES data can be distorted by viewport contamination, leading to misunderstandings in plasma diagnosis. This issue is particularly emphasized in multi-dielectric deposition processes, such as oxide and nitride (ON) stack. Thus, it is crucial to understand the potential misunderstandings related to OES data distortion due to viewport contamination. This paper explores the potential for misunderstanding OES data due to data distortion in the ON stack process. It suggests the possibility of excessively evaluating process drift through comparisons with a QMS. This understanding can be utilized to develop diagnostic models and identify the effects of viewport contamination in ON stack processes.

• Journal of Internet of Things and Convergence
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• v.9 no.6
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• pp.75-81
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• 2023

This study propose the traffic shaping scheme on IoT Network. The proposed scheme can be operated on the gateway which called sink node and control the IoT traffic with considering the traffic type(real-time based or non real-time based). It is proved that the proposed scheme shows a efficient and compatible result by the numerical analysis and the simulation on the proposed model. And the efficient of the proposed scheme by the numerical analysis has a approximate result of the simulation.

• Korea Trade Review
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• v.46 no.2
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• pp.263-280
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• 2021

With the advent of the era of the 4th Industrial Revolution, various support policies and programs are being introduced as the promotion of startups related to the 4th industry is promoted as a core policy of the government. Based on major technologies such as Artificial Intelligence(AI), Big Data, Internet of Things(IoT), Blockchain, and Automation leading the 4th industrial revolution, logistics and distribution companies are expanding the range of markets and services provided. The purpose of this study is to examine the current status of startups in the logistics field based on major technologies of the 4th Industrial Revolution, which are rapidly growing at home and abroad, and suggest implications for revitalizing logistics startups through a policy demand survey. As a result of the study, in order to foster domestic logistics startups, we propose policy support for integration of logistics startups, integrated management of information, provision of physical space, network platform, and practical education and mentoring.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1117-1124
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• 2023

The security of information, including image content, is an essential part of today's communications technology and is critical to secure transmission. In this paper, a new ROI-based image encryption algorithm is proposed that can quickly encrypt images with a security level suitable for environments that require real-time data transmission for images containing sensitive information such as ID cards. The proposed algorithm is based on one dimensional 5-neighbor cellular automata, which can be implemented in hardware and performed hardware-friendly operations. Various experiments and analyses are performed to verify whether the proposed encryption algorithm is safe from various brute-force attacks.

• Journal of Information Science Theory and Practice
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• v.12 no.2
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• pp.79-95
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• 2024

The new AI based conversational chatbot, ChatGPT, launched in November 2022, is causing a stir. There are many opinions about this being a 'threat or a promise,' and thus it is important to understand what has been said about this tool and, based on the growing literature that has emerged on the subject, demystify its effective impact on society. To analyse this impact, a systematic literature review with the support of the preferred reporting items for systematic reviews and meta-analysis protocol was used. The data, scientific documents, were collected using the main scientific databases - SCOPUS and Web of Science - and the results were presented based on a bibliometric and thematic exploration of content. The main findings indicate that people are increasingly using this chatbot in more diverse areas. Therefore, this study contributes at the practical level, aiming to enlighten people in general - both in professional and personal life - about this tool and its impacts. Also, it contributes at the theoretical level, which involves expanding understanding and elucidation of the impacts of ChatGPT in different areas of study.

• Journal of information and communication convergence engineering
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• v.22 no.2
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• pp.109-120
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• 2024

Trash or garbage is one of the most dangerous health and environmental problems that affect pollution. Pollution affects nature, human life, and wildlife. In this paper, we propose modern solutions for cleaning the environment of trash pollution by enforcing strict action against people who dump trash inappropriately on streets, outside the home, and in unnecessary places. Artificial Intelligence (AI), especially Deep Learning (DL), has been used to automate and solve issues in the world. We availed this as an excellent opportunity to develop a system that identifies trash using a deep convolutional neural network (CNN). This paper proposes a real-time garbage identification system based on a deep CNN architecture with eight distinct classes for the training dataset. After identifying the garbage, the CCTV camera captures a video of the individual placing the trash in the incorrect location and sends an alert notice to the relevant authority.

• Corrosion Science and Technology
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• v.23 no.3
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• pp.228-234
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• 2024

Zinc wiping is a phenomenon used to control zinc-coating thickness on steel substrate during hot dip galvanizing by equipment called air knife. Uniformity of zinc coating weight in length and width profile along with surface quality are most critical quality parameters of galvanized steel. Deviation from tolerance level of coating thickness causes issues like overcoating (excess consumption of costly zinc) or undercoating leading to rejections due to non-compliance of customer requirement. Main contributor of deviation from target coating weight is dynamic change in air knives equipment setup when thickness, width, and type of substrate changes. Additionally, cold coating measurement gauge measure coating weight after solidification but are installed down the line from air knife resulting in delayed feedback. This study presents a coating weight control model (Galvantage) predicting critical air knife parameters air pressure, knife distance from strip and line speed for coating control. A reverse engineering approach is adopted to design a predictive, prescriptive, and descriptive model recommending air knife setups that estimate air knife distance and expected coating weight in real time. Implementation of this model eliminates feedback lag experienced due to location of coating gauge and achieving setup without trial-error by operator.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.143-148
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• 2024

Traffic congestion has caused issues in various forms such as the environment and economy. Recently, an intelligent transport system (ITS) using artificial intelligence (AI) has been focused so as to alleviate the traffic congestion problem. In this paper, we propose a reinforcement learning-based traffic signal control algorithm that can smooth the flow of traffic while reducing discomfort levels of drivers and pedestrians. By applying the proposed algorithm, it was confirmed that the discomfort levels of drivers and pedestrians can be significantly reduced compared to the existing fixed signal control system, and that the performance gap increases as the number of roads at the intersection increases.

• International journal of advanced smart convergence
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• v.13 no.2
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• pp.205-213
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• 2024

This study uses a large language model (LLM) to identify Aristotle's rhetorical principles (ethos, pathos, and logos) in COVID-19 information on Naver Knowledge-iN, South Korea's leading question-and-answer community. The research analyzed the differences of these rhetorical elements in the most upvoted answers with random answers. A total of 193 answer pairs were randomly selected, with 135 pairs for training and 58 for testing. These answers were then coded in line with the rhetorical principles to refine GPT 3.5-based models. The models achieved F1 scores of .88 (ethos), .81 (pathos), and .69 (logos). Subsequent analysis of 128 new answer pairs revealed that logos, particularly factual information and logical reasoning, was more frequently used in the most upvoted answers than the random answers, whereas there were no differences in ethos and pathos between the answer groups. The results suggest that health information consumers value information including logos while ethos and pathos were not associated with consumers' preference for health information. By utilizing an LLM for the analysis of persuasive content, which has been typically conducted manually with much labor and time, this study not only demonstrates the feasibility of using an LLM for latent content but also contributes to expanding the horizon in the field of AI text extraction.

• East Asian Journal of Business Economics (EAJBE)
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• v.12 no.2
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• pp.35-42
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• 2024

Purpose: With the growth of the hospitality industry, it is imperative to identify how smart tourism characteristics may be used in hotel management. Current and emerging technologies such as analytic tools, automation, and Artificial Intelligence (AI) help to create value for the guests while also contributing to waste reduction, resource optimization, and increased profitability in the industry. Research design, data and methodology: The literature review was conducted to examine a broad scope of research in analyzing smart tourism characteristics for the improved management of hotels and establish the necessary background for this issue. The analysis was employed to specify the systematic approach of selecting, scrutinizing, and integrating the source of information. Results: According to the systematic literature analysis, four smart tourism characteristics have been established, which can improve various aspects of hotel management. They are as follows: (1) Smart Guest Experience Management, (2) Smart Operations and Resource Management, (3) Smart Customer Relationship Management, and (4) Smart Destination Management. Conclusions: The findings expose the radical approach that smart tourism characteristics take towards the management of hotels. The developments in IT and science-oriented solutions have opened greater opportunities as the hotel industry can enhance clients' satisfaction, productivity, and participation in environmental conservation initiatives for tourism.