• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.493-498
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• 2024

With the rapid advancement of generative artificial intelligence technology, there is growing interest in how to utilize it in practical applications. Additionally, the importance of prompt engineering to generate results that meet user demands is being newly highlighted. Exploring the new possibilities of generative AI can hold significant value. This study aims to utilize ChatGPT 4.0, a leading generative AI, to propose an effective method for evaluating user experience through the analysis of online customer review data. The user experience evaluation method was based on the six-layer elements of user experience: 'functionality', 'reliability', 'usability', 'convenience', 'emotion', and 'significance'. For this study, a literature review was conducted to enhance the understanding of prompt engineering and to grasp the clear concept of the user experience hierarchy. Based on this, prompts were crafted, and experiments for the user experience evaluation method were carried out using the analysis of collected online customer review data. In this study, we reveal that when provided with accurate definitions and descriptions of the classification processes for user experience factors, ChatGPT demonstrated excellent performance in evaluating user experience. However, it was also found that due to time constraints, there were limitations in analyzing large volumes of data. By introducing and proposing a method to utilize ChatGPT 4.0 for user experience evaluation, we expect to contribute to the advancement of the UX field.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.187-199
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• 2024

Due to the educational ecosystem in South Korea, there is a significant need to explore a new balance for students who pursue sports rehabilitation education based on their academic performance, in order to help them adapt to their majors, find career paths, and foster motivation for employment. There is a lack of related research in this crucial phase. The purpose of this study is to ascertain the impact of sports rehabilitation education on career aspirations and employment motivation through psychological reactions. The research methodology involved conducting an online survey from December 11th to December 28th, 2023, targeting university students undergoing sports rehabilitation education, with a final collection of 212 survey responses used for analysis. The research findings indicate: firstly, that the knowledge of sports rehabilitation educators has a positive influence on voluntary psychology. Secondly, the competence of sports rehabilitation educators has a positive impact on voluntary psychology. Thirdly, the attitude of sports rehabilitation educators negatively affects involuntary psychology. Fourthly, voluntary psychology positively influences career aspirations. Finally, voluntary psychology positively influences employment motivation, while conversely, involuntary psychology negatively affects employment motivation. These research results are expected to contribute to the development of sports rehabilitation education that influences career paths and employment motivation through psychological reactions.

• The Journal of the Convergence on Culture Technology
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• v.10 no.2
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• pp.201-208
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• 2024

In this study, we investigated whether the evacuation time according to the exit installation standards specified in the building code during a food factory fire is compatible with the evacuation time based on the performance-based design specified by the fire department, in order to determine if evacuation safety is ensured. We used the Pathfinder program to confirm the evacuation time, and experimented with three scenarios for exit installation standards towards the outside of the building: 60m, 80m, and 100m. The target building in the experiment corresponded to the building code's exit installation standard of 100m from each dwelling. The experimental results showed tt in the cases of 80m and 100m, ASET exceeded RSET, indicating tt evacuation safety was not ensured, while in the case of 60m, evacuation safety was maintained. Through this study, it was confirmed tt even when the exit installation standards towards the outside of the building are met, evacuation safety may not be guaranteed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.139-145
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• 2024

This paper presents the design of a voltage controlled oscillator (VCO) which is one of the key building blocks in modern wireless communication systems with small VCO gain (K_vco) variation. To compensate conventional large K_vco variation, a series varactor bank has been added to the conventional LC-tank with parallel capacitor bank array. And also, in order to achieve excellent phase noise performance while maintaining wide tuning range, a mixed coarse/fine tuning scheme(series varactor array and parallel capacitor array) is chosen. The switched varactor array bank is controlled by the same digital code for switched capacitor array without additional digital circuits. For use at a low voltage of 1.2V, the proposed current reference circuit in this paper used a current reference circuit for safety with the common gate removed more safely. Implemented in a TSMC 0.13㎛ CMOS RF technology, the proposed VCO can be tuned from 4.4GH to 5.3GHz with the K_vco (VCO gain ) variation of less than 9.6%. While consuming 3.1mA from a 1.2V supply, the VCO has -120dBc/Hz phase noise at 1MHz offset from the carrier of the 5.3 GHz.

• Phonetics and Speech Sciences
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• v.16 no.1
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• pp.57-65
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• 2024

Normal pressure hydrocephalus (NPH) is a condition wherein the cerebrospinal pressure in the brain is within the normal range, but the cerebrospinal fluid increases above the normal level, causing ventriculomegaly. In patients with NPH, the articulatory system exhibits reduced mobility and range, which may affect diadochokinesis (DDK) and speech intelligibility. In this study, we investigated the characteristics of DDK, including accurate-token DDK and all-token DDK including inaccurate tokens, in patients with NPH and healthy elderly adults (HE). We also examined the classification accuracy of DDK between the two groups. Finally, we investigated whether there was a correlation between speech intelligibility and DDKs in the NPH group. The results showed that NPH and HE groups differed significantly in both accurate-token DDK and all-token DDK, and their classification accuracy was relatively high. However, there was no correlation between speech intelligibility and DDK. The findings suggest that the DDK is a useful method for sensitively assessing speech motor performance in patients with NPH.

• Phonetics and Speech Sciences
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• v.16 no.1
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• pp.67-76
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• 2024

Recent advances in text-to-speech (TTS) technology have significantly improved the quality of synthesized speech, reaching a level where it can closely imitate natural human speech. Especially, TTS models offering various voice characteristics and personalized speech, are widely utilized in fields such as artificial intelligence (AI) tutors, advertising, and video dubbing. Accordingly, in this paper, we propose a one-shot multi-speaker TTS system that can ensure acoustic diversity and synthesize personalized voice by generating speech using unseen target speakers' utterances. The proposed model integrates a speaker encoder into a TTS model consisting of the FastSpeech2 acoustic model and the HiFi-GAN vocoder. The speaker encoder, based on the pre-trained RawNet3, extracts speaker-specific voice features. Furthermore, the proposed approach not only includes an English one-shot multi-speaker TTS but also introduces a Korean one-shot multi-speaker TTS. We evaluate naturalness and speaker similarity of the generated speech using objective and subjective metrics. In the subjective evaluation, the proposed Korean one-shot multi-speaker TTS obtained naturalness mean opinion score (NMOS) of 3.36 and similarity MOS (SMOS) of 3.16. The objective evaluation of the proposed English and Korean one-shot multi-speaker TTS showed a prediction MOS (P-MOS) of 2.54 and 3.74, respectively. These results indicate that the performance of our proposed model is improved over the baseline models in terms of both naturalness and speaker similarity.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.105-111
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• 2024

This paper deals with the minimum linear arrangement(MinLA) of a lattice graph, to which an approximate algorithm of linear complexity O(n) remains as a viable solution, deriving the optimal MinLA of 31,680 for 33×33 lattice. This paper proposes a partitioning arrangement algorithm of complexity O(1) that delivers exact solution to the minimum linear arrangement. The proposed partitioning arrangement algorithm could be seen as loading boxes into a container. It firstly partitions m rows into r₁,r₂,r₃ and n columns into c₁,c₂,c₃, only to obtain 7 containers. Containers are partitioning with a rule. It finally assigns numbers to vertices in each of the partitioned boxes location-wise so as to obtain the MinLA. Given m,n≥11, the size of boxes C₂,C₄,C₆ is increased by 2 until an increase in the MinLA is detected. This process repeats itself 4 times at maximum given m,n≤100. When tested to lattice in the range of 2≤n≤100, the proposed algorithm has proved its universal applicability to lattices of both m=n and m≠n. It has also obtained optimal results for 33×33 and 100×100 lattices superior to those obtained by existing algorithms. The minimum linear arrangement algorithm proposed in this paper, with its simplicity and outstanding performance, could therefore be also applied to the field of Very Large Scale Integration circuit where m,n are infinitely large.

• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.1-17
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• 2024

Forest management is known to beneficially influence stand structure and wood production, yet quantitative understanding as well as an illustrative depiction of the effects of different management approaches on tree growth and stand dynamics are still scarce. Long-term management of beech forests must balance public interests with ecological aspects. Efficient forest management requires the reliable prediction of tree growth change. We aimed to develop a novel hybrid simulation approach, which realistically simulates short- as well as long-term effects of different forest management regimes commonly applied, but not limited, to German low mountain ranges, including near-natural forest management based on single-tree selection harvesting. The model basically consists of three modules for (a) natural seedling regeneration, (b) mortality adjustment, and (c) tree growth simulation. In our approach, an existing validated growth model was used to calculate single year tree growth, and expanded on by including in a newly developed simulation process using calibrated modules based on practical experience in forest management and advice from the local forest. We included the following different beech forest-management scenarios that are representative for German low mountain ranges to our simulation tool: (1) plantation, (2) continuous cover forestry, and (3) reserved forest. The simulation results show a robust consistency with expert knowledge as well as a great comparability with mid-term monitoring data, indicating a strong model performance. We successfully developed a hybrid simulation that realistically reflects different management strategies and tree growth in low mountain range. This study represents a basis for a new model calibration method, which has translational potential for further studies to develop reliable tailor-made models adjusted to local situations in beech forest management.

• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1498-1505
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• 2023

This study attempted to investigate the difference in service orientation according to the individual characteristics of hair salon workers, and to identify the internal marketing factors of hair salon that influence service orientation. Questionnaires for empirical research were collected from hair salon workers in Gyeongnam, and the results of analyzing the collected questionnaires through IBM SPSS Statistics 26 are as follows. First, as a result of analyzing the difference in service orientation according to the individual characteristics of hair salon workers, the '40s or older' group and the 'working period of 10 years or longer' group showed statistically higher service orientation than other groups. Second, as a result of analyzing the causal relationship between internal marketing and service orientation, it was found that welfare, compensation system, education and training of internal marketings had the statistical effect on service orientation, and in particular, the compensation system had the strongest effect on service orientation. Therefore, service orientation for customers should be improved through internal marketing activities that take into account the individual characteristics of hair salon workers. The improvement of service orientation means the customer's intention to reuse, suggesting that ultimately the management performance of hair salon companies can be further improved.

• Korean Journal of Radiology
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• v.21 no.7
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• pp.869-879
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• 2020

Objective: To evaluate the performance of a convolutional neural network (CNN) model that can automatically detect and classify rib fractures, and output structured reports from computed tomography (CT) images. Materials and Methods: This study included 1079 patients (median age, 55 years; men, 718) from three hospitals, between January 2011 and January 2019, who were divided into a monocentric training set (n = 876; median age, 55 years; men, 582), five multicenter/multiparameter validation sets (n = 173; median age, 59 years; men, 118) with different slice thicknesses and image pixels, and a normal control set (n = 30; median age, 53 years; men, 18). Three classifications (fresh, healing, and old fracture) combined with fracture location (corresponding CT layers) were detected automatically and delivered in a structured report. Precision, recall, and F1-score were selected as metrics to measure the optimum CNN model. Detection/diagnosis time, precision, and sensitivity were employed to compare the diagnostic efficiency of the structured report and that of experienced radiologists. Results: A total of 25054 annotations (fresh fracture, 10089; healing fracture, 10922; old fracture, 4043) were labelled for training (18584) and validation (6470). The detection efficiency was higher for fresh fractures and healing fractures than for old fractures (F1-scores, 0.849, 0.856, 0.770, respectively, p = 0.023 for each), and the robustness of the model was good in the five multicenter/multiparameter validation sets (all mean F1-scores > 0.8 except validation set 5 [512 x 512 pixels; F1-score = 0.757]). The precision of the five radiologists improved from 80.3% to 91.1%, and the sensitivity increased from 62.4% to 86.3% with artificial intelligence-assisted diagnosis. On average, the diagnosis time of the radiologists was reduced by 73.9 seconds. Conclusion: Our CNN model for automatic rib fracture detection could assist radiologists in improving diagnostic efficiency, reducing diagnosis time and radiologists' workload.