• International journal of advanced smart convergence
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• v.11 no.2
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• pp.108-117
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• 2022

The recent development of information and communication technology has a great impact on the audio/video industry. In particular, IP-based AoIP transmission technology and AVB technology are making changes in the audio/video market. Video signal transmission technology has been introduced to the market through a network, but it has not replaced the video switcher function. Video signals in the conference room or classroom are still controlled by the switching device. In order to switch input/output video devices, a cable that is not limited by distance must be connected to the switcher. In addition, the control of the switching device must be performed by a person who has received professional training. In this paper, it is a technology that can be operated even by non-experts by replacing complex video cables (RGB, DVI, HDMI, DP) with LAN cables and enabling IP-based video switching and transmission (Video Mirroring over IP: VMoIP) to replace video switcher equipment. We are going to do this study, I/O videos were controlled in the form of matrix and high-definition videos were transmitted without distortion, and VMoIP is expected to become the standard for video switching systems in the future.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.194-204
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• 2022

This study is a one-group pretest-posttest design to evaluate the effect of problem-based learning (PBL) for patient safety on self-leadership, patient safety competencies, and reflective thinking of nursing students. The research was conducted from March 2 to April 15, 2022, in which 57 nursing students participated. PBL for patient safety was examined in a total of 8 sessions in the order of motivation, problem identification, task performance planning, problem-solving methods, summary and solution, presentation, and evaluation. The following topics of patient safety were selected for each team: nursing records, high-alert medication, medication error and intravenous fluid regulation, blood transfusion care, fall, bedsore, infection control, and pain management. We provided feedback on the learning process and outcomes of nursing students. According to the results, self-leadership showed a statistically significant improvement in self-expectations (t=2.60, p=0.01), goal setting (t=2.84, p<0.01), self-reward (t=3.32, p<0.01), and self-criticism (t=2.32, p=0.02). Patient safety competencies showed a statistically significant improvement in patient safety knowledge (t=13.05, p<0.001) and patient safety skills (t=4.87, p<0.001) but not in reflective thinking. The results prove that PBL for patient safety is an effective teaching-learning strategy to improve self-leadership and patient safety competencies. Future studies must develop and validate specific and long-term teaching-learning methods to improve reflective thinking.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.128-134
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• 2022

Nowadays, people consume a lot of content such as web dramas or K-pop videos through mobile devices such as smartphones, and the market for indirect advertisements through these web dramas or K-pop videos is also increasing every year. In order to lead to the immediate purchase of indirect products in web dramas, a system that allows consumers to purchase immediately at the time the products appear in the drama is needed. In this paper, we propose a system to allow viewers to purchase products worn by celebrities immediately when viewers see and click on them. When a user clicks on a video, it recognizes the product worn by the celebrity, and displays information on the screen on the most similar product corresponding to the recognized product, allowing them to go to the seller's site where they can purchase it. In order for such a system to operate stably, a pose estimation and siamese network-based system is proposed. The proposed system will primarily be released as a streaming service in the form of an app or web page that connects the products in web dramas or other K-pop video contents screened on the mobile with e-commerce. Furthermore, in the future, the technology is expected to be used globally in various industries such as smart mobility and display kiosks.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.054-074
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• 2023

With the advent of the '4th Industrial Revolution', digitalization using AI (Artificial Intelligence), big data, IoT (Internet of Things), cloud computing and mobile is accelerating across all industries and global companies have fundamentally reorganized customer experiences, business models, and operations centering on digital transformation. Business innovation drives productivity improvement, process simplification, price, competitiveness and sustainable expansion. Whether digital transformation will be necessary for the current industrial environment is no longer important, and how quickly companies achieve digitalization has emerged as the utmost crucial element in industrial continuity. As non-face-to-face and remote technologies have begun in earnest, and accelerated in the pharmaceutical industry. They are looking for ways to provide value, generate profits, improve efficiency, and sustain the future. Compared to other industries, the pharmaceutical-related sectors have shown high interest in digital transformation especially to reduce costs and meet the challenge of delivering products during the pandemic environment.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.175-185
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• 2023

As the era of ChatGPT and generative AI technologies unfolds, the marketing industry stands on the precipice of a paradigm shift. Innovations such as GPT-4, DALL-E 2, and Mid-journey Stable Diffusion possess the capacity to dramatically transform the methods by which advertisers reach and engage with customers. The potential applications of these advanced tools herald a new age for the marketing and advertising sectors, offering unprecedented opportunities for growth and optimization. Nevertheless, the rapid adoption of generative AI within these industries presents a unique set of challenges, particularly for organizations that lack the necessary technological infrastructure and human capital to effectively leverage these innovations. As a result, a competitive crisis may emerge, exacerbating existing disparities between well-equipped enterprises and their less technologically adept counterparts. In this article, we undertake a comprehensive exploration of the implications of generative AI for the future of marketing, examining both its potential benefits and drawbacks. We consider the possible impact of these developments on the advertising and marketing industries at large, as well as the ways in which professionals operating within these fields may need to adapt to remain competitive in an increasingly AI-driven landscape. By providing a holistic overview of the challenges and opportunities associated with generative AI, this study aims to elucidate the complex dynamics at play in the ongoing evolution of the marketing and advertising sectors.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.68-74
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• 2023

The food industry has been hit hard since the first outbreak of COVID-19 in 2019. However, as of April 2022, social distancing has been resolved and the restaurant industry has gradually recovered, interest in restaurant start-ups is increasing. Therefore, in this paper, 'restaurant start-up' was cited as a key keyword through social media big data analysis using TexTom, and word frequency and cone analysis were conducted for big data analysis. The keyword collection period was selected from May 1, 2022, when social distancing due to COVID-19 was lifted, to May 23, 2023, and based on this, a plan to develop chatbot services for restaurant start-ups was proposed. This paper was prepared in consideration of what to consider when starting a restaurant and a chatbot service that allows prospective restaurant founders to receive information more conveniently. Based on these analysis results, we expected to contribute to the process of developing chatbots for prospective restaurant founders in the future

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.149-156
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• 2023

Joint research on software, electronic engineering, computer engineering, and financial engineering and the use of ICT knowledge through network formation play an important role in strengthening science and technology-based innovation capabilities and facilitating the development and production process of products using new technologies. For the purpose of this study, I would like to strategically propose ICT specialized education in the 4th industrial revolution. To this end, the ICT specialization model, ICT specialization strategy analysis, and ICT specialization operation and effect were explored to establish ICT specialization strategies centered on software, electronic engineering, computer engineering, and financial engineering in the era of super-intelligence, hyper-connected, and hyper-convergence. Secondly, a roadmap for detailed promotion tasks related to efficient ICT characterization based on core strategies, detailed promotion tasks, and programs was proposed, focusing on talent related to ICT characterization. Thirdly, we would like to propose a reorganization of the academic structure and organization related to ICT characterization. Finally, we would like to propose the establishment of a future-oriented education system related to ICT specialization based on the advanced education and research environment.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.221-232
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational reliability of the ICT/Cold-Chain Unmanned Storage, a predictive maintenance system was implemented based on the LSTM model. In this paper, a server for data management, such as collection and monitoring, and an analysis server that notifies the monitoring server through data-based failure and defect analysis are separately distinguished. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on RabbitMQ, loading data in an InMemory method using Redis, and managing snapshot data DB in real time. The predictive maintenance platform can contribute to securing reliability by identifying potential failures and defects that may occur in the operation of the ICT/Cold-Chain Unmanned Storage in the future.

• Electronics and Telecommunications Trends
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• v.38 no.5
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• pp.71-80
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• 2023

With the rapid advancement of the Internet, the use of encrypted traffic has surged in order to protect data during transmission. Simultaneously, network attacks have also begun to leverage encrypted traffic, leading to active research in the field of encrypted traffic analysis to overcome the limitations of traditional detection methods. In this paper, we provide an overview of the encrypted traffic analysis field, covering the analysis process, domains, models, evaluation methods, and research trends. Specifically, it focuses on the research trends in the field of anomaly detection in encrypted network traffic analysis. Furthermore, considerations for model development in encrypted traffic analysis are discussed, including traffic dataset composition, selection of traffic representation methods, creation of analysis models, and mitigation of AI model attacks. In the future, the volume of encrypted network traffic will continue to increase, particularly with a higher proportion of attack traffic utilizing encryption. Research on attack detection in such an environment must be consistently conducted to address these challenges.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.