• International journal of advanced smart convergence
• /
• v.12 no.1
• /
• pp.18-30
• /
• 2023

We compared empirically the forecast accuracies of the LSTM model, and the ARIMA model. ARIMA model used auto.arima function. Data used in the model is 100 days. We compared with the forecast results for 50 days. We collected the stock closing prices of the top 4 companies by market capitalization in Korea such as "Samsung Electronics", and "LG Energy", "SK Hynix", "Samsung Bio". The collection period is from June 17, 2022, to January 20, 2023. The paired t-test is used to compare the accuracy of forecasts by the two methods because conditions are same. The null hypothesis that the accuracy of the two methods for the four stock closing prices were the same were rejected at the significance level of 5%. Graphs and boxplots confirmed the results of the hypothesis tests. The accuracies of ARIMA are higher than those of LSTM for four cases. For closing stock price of Samsung Electronics, the mean difference of error between ARIMA and LSTM is -370.11, which is 0.618% of the average of the closing stock price. For closing stock price of LG Energy, the mean difference is -4143.298 which is 0.809% of the average of the closing stock price. For closing stock price of SK Hynix, the mean difference is -830.7269 which is 1.00% of the average of the closing stock price. For closing stock price of Samsung Bio, the mean difference is -4143.298 which is 0.809% of the average of the closing stock price. The auto.arima function was used to find the ARIMA model, but other methods are worth considering in future studies. And more efforts are needed to find parameters that provide an optimal model in LSTM.

• International journal of advanced smart convergence
• /
• v.12 no.1
• /
• pp.140-148
• /
• 2023

With the OTT media market growing rapidly, the significance of trustworthy data verification and certification cannot be emphasized enough. This study delves into the crucial need for such measures in South Korea, exploring the steps involved, the technological and policy-related considerations, and the challenges that may arise once these measures are put into place. Drawing on in-depth interviews and the analytical hierarchy process (AHP), this study surveyed various stakeholder groups, both directly and indirectly related to OTT data authentication and certification. By assessing the severity of OTT data-related issues and identifying the requirements for reliability-improvement policies, participants shared their valuable insights and opinions on this pressing matter. The survey results clearly indicate a divided opinion among stakeholders and industry experts on the reliability of OTT data, with some expressing trust while others remain skeptical. However, there was a consensus that advertising-based AVOD is more reliable than SVOD. By analyzing the priorities of authentication and verification, this study paves the way for the establishment and operation of a Korean MRC (KMRC), centered on the OTT media industry. The KMRC will serve as a vital platform for ensuring the authenticity and accuracy of OTT data in South Korea, providing businesses and industry players with a reliable source of information for informed decision-making. This study highlights the pressing need for reliable data authentication and certification in the rapidly growing OTT media market, and provides a persuasive case for the establishment of a KMRC in South Korea to meet this critical need.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.25 no.1
• /
• pp.1-11
• /
• 2023

In this study, the stability of the room-and-pillar underground method was investigated using numerical analysis method. In-situ geotechnical investigation was conducted, and a supporting pattern was selected based on the geotechnical investigation data. For the supporting pattern, Type-1, 2, 3 were selected for each ground condition. A 3D numerical analysis model was developed for effective simulation as the room-and-pillar underground method consist of a pillar and room. As a review of numerical analysis, it was confirmed that the crown settlement, convergence, shotcrete and rock bolt were all stable in all supporting patterns. As a result of the analysis by the construction stage, it was confirmed that excessive stress was generated in the room when the construction stage of forming pillar. So, precise construction is required during the actual construction stage of the pillar formation.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.1
• /
• pp.655-661
• /
• 2023

Big data, an important element of the 4th industrial revolution, is actively opening public data in public institutions and local governments. In the public data portal, everyone can conveniently search for data and check related data, but only those in ICT-related fields are using public data. Although data held by public institutions is open to citizens, it is difficult for anyone to easily utilize public data to develop applications. In this paper, data provided in open API format from public data portals has XML and JSON formats. In this study, we are a method of modularizing public data in XML format into a part that can be easily developed by linking it to a GUI interface. Based on the necessary public data, we propose a way to easily develop mobile programs and promote the use of public data.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.1
• /
• pp.199-204
• /
• 2023

The COVID-19 pandemic, which began in early 2020, became an opportunity for unprecedented global reflection and change. And it served as an opportunity to promote a new paradigm in all areas of society, including politics, economy, culture, and industry. In the midst of this upheaval, the 2022 IAA exhibition, which was held in four years, was held as an exhibition that even proposed new concepts of smart logistics and mobility services. Among them, various concepts were also proposed in exhibitions related to last mile mobility, the focus of this study.As a result of this study, the main trend of last mile mobility shown in the IAA 2022 exhibition is that the property of physical products with functions as social interfaces is expanding into the PSS (Product-Service System) ecosystem in which products and services are systematically linked. As a result, the need for a methodological approach that can organically link the design planning of social services and the development of products corresponding to it was derived.

• Journal of Korean Society of Rural Planning
• /
• v.28 no.4
• /
• pp.41-53
• /
• 2022

This study aims to identify perceptions on ESG management evaluation priorities based on public value in the agricultural and rural sector with the focus on the Korea Rural Community Corporation. We conduct Analytic Hierarchy Process (AHP) to analyze how ESG management evaluation priorities are perceived by distinctive groups across industrial fields. To this end, experts working in the agricultural and rural sector and the general public in non-agricultural sector were questioned to derive and compare the weights for each class of ESG management. Results show the followings: First, the weight for the environment (E) was derived as 0.51774 in the first layer, which was found to be the most important evaluation item among the environment (E), society (S), and governance (G). Second, "ecosystem restoration," "urban-rural exchange expansion and regional development," and "increasing transparency" were the most important items in the second layer. Third, priorities between the agricultural and non-agricultural respondents groups were different in environmental (E) and social (S) categories, which explained that perceptions on ESG management by workers and policy makers in the agricultural and rural sector are different from those by general public in the non-agricultural sector.

• Journal of Internet Computing and Services
• /
• v.24 no.2
• /
• pp.11-18
• /
• 2023

Recently, in the field of Speech Emotion Recognition (SER), many studies have been conducted to improve accuracy using voice features and modeling. In addition to modeling studies to improve the accuracy of existing voice emotion recognition, various studies using voice features are being conducted. This paper, voice files are separated by time interval in a time series method, focusing on the fact that voice emotions are related to time flow. After voice file separation, we propose a model for classifying emotions of speech data by extracting speech features Mel, Chroma, zero-crossing rate (ZCR), root mean square (RMS), and mel-frequency cepstrum coefficients (MFCC) and applying them to a recurrent neural network model used for sequential data processing. As proposed method, voice features were extracted from all files using 'librosa' library and applied to neural network models. The experimental method compared and analyzed the performance of models of recurrent neural network (RNN), long short-term memory (LSTM) and gated recurrent unit (GRU) using the Interactive emotional dyadic motion capture Interactive Emotional Dyadic Motion Capture (IEMOCAP) english dataset.

• International journal of advanced smart convergence
• /
• v.11 no.1
• /
• pp.11-18
• /
• 2022

Securities and investment services have and use large data. Investors started to invest through their own analysis methods. There are 22 major securities and investment companies in Korea and only 6 companies support open API. Python is effective for requesting and receiving, analyzing text data from open API. Daishin Securities Co. is the only open API that officially supports Python, and eBest Investment & Securities Co. unofficially supports Python. There are two important differences between CYBOS plus of Daishin Securities Co. and xingAPI of eBest Investment & Securities Co. First, we must log in to CYBOS plus to access the server of Daishin Securities Co. And the python program does not require a logon. However, to receive data using xingAPI, users log on in an individual Python program. Second, CYBOS plus receives data in a Request/Reply method, and zingAPI receives data through events. It can be thought that these points will show a difference in response time. Response time is important to users who use open APIs. Data were measured from August 5, 2021, to February 3, 2022. For each measurement, 15 repeated measurements were taken to obtain 420 measurements. To increase the accuracy of the study, both APIs were measured alternately under same conditions. A paired t-test was performed to test the hypothesis that the null hypothesis is there was no difference in means. The p-value is 0.2961, we do not reject null hypothesis. Therefore, we can see that there is no significant difference between means. From the boxplot, we can see that the distribution of the response time of eBest is more spread out than that of Cybos, and the position of the center is slightly lower. CYBOS plus has no restrictions on Python programming, but xingAPI has some limits because it indirectly supports Python programming. For example, there is a limit to receiving more than one current price.

• International journal of advanced smart convergence
• /
• v.11 no.1
• /
• pp.111-116
• /
• 2022

After COVID-19, the number of people with sleep disorders around the world is increasing. In particular, in the flow of the 4th industrial revolution, the differentiation of types and characteristics of the sleep industry is accelerating. Therefore, in this study, the characteristics of each type of sleep-related industry were reclassified from an industrial point of view, and based on this, an attempt was made to review the classification system that can help companies develop sleep products and improve related national systems. Based on the 10th standard industry classification, we compared input cost, value, and usability and analyzed common characteristics, treatments, and preventive effects based on this. A comprehensive taxonomy using matrix analysis was reviewed. As a result, in terms of cost (A), the most common sleeping products are general mattresses and general bedding. It is an IOT device (auxiliary device), and the value aspect (B, B/D) included sleep cafe, bedding rental and management service, and sleep consulting. In terms of utility (A/B), a total of 6 product groups including sleep aids (health functional foods) belong to this category, and in terms of treatment (A/C), a total of 3 product groups including sleep clinics (medical services) belong to this category. As for the product group (A/D) with both properties, it was found that non-insurance sleep treatment medical devices, sleep-related over-the-counter drugs, and some sleep monitoring applications belong to this category. Ultimately, it was found that the sleep industry classification enables the most active product development and composition according to the relative relationship between cost and utility, and treatment and utility. appeared to be necessary.

• Journal of Internet of Things and Convergence
• /
• v.9 no.3
• /
• pp.13-19
• /
• 2023

In this paper, we investigated the implementation of a hairstyle recommendation system based on big data and deepfake technology. The proposed hairstyle recommendation system recognizes the facial shapes based on the user's photo (image). Facial shapes are classified into oval, round, and square shapes, and hairstyles that suit each facial shape are synthesized using deepfake technology and provided as videos. Hairstyles are recommended based on big data by applying the latest trends and styles that suit the facial shape. With the image segmentation map and the Motion Supervised Co-Part Segmentation algorithm, it is possible to synthesize elements between images belonging to the same category (such as hair, face, etc.). Next, the synthesized image with the hairstyle and a pre-defined video are applied to the Motion Representations for Articulated Animation algorithm to generate a video animation. The proposed system is expected to be used in various aspects of the beauty industry, including virtual fitting and other related areas. In future research, we plan to study the development of a smart mirror that recommends hairstyles and incorporates features such as Internet of Things (IoT) functionality.