• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.235-244
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• 2022

In this study, a class operation case of an engineering design project targeting a golf ball dispenser, a commercial product, was presented. The project was carried out according to the systematic engineering design approach suggested by Kim Jong-won and W. Beitz. This method broadly divides engineering design into four stages: 'product planning → conceptual design → basic design → detailed design'. In particular, the conceptual design stage is divided into 'functional structure diagram → detailed working principle exploration → various design alternatives creation → optimal design selection'. In the conceptual design, the input/output of the golf ball dispenser was defined and a functional structure diagram was prepared for it. Through this process, it was possible to subdivide the functions of the product and to easily explore the working principle for each. The searched working principles are devised as various design alternatives by various combinations, and for each proposal, the advantages and disadvantages were compared with each other to derive the optimal design alternative. In the basic design, the prototype layout was completed through failure mode analysis and the actual prototype was manufactured using it. Through the entire process, students participating in the class will be able to design commercial products in a systematic way and experience manufacturing prototypes within the department of mechanical engineering curriculum.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• Korea Trade Review
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• v.43 no.5
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• pp.25-45
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• 2018

This paper estimates the export losses of the Korean domestic automobile industry due to US trade pressure and its economic ripple effects. Using the HS 6 digit tariff and export data from 2010 to 2017, this paper estimates the tariff elasticity of Korea's US automobile exports against a US tariff increase by applying the Poisson Pseudo maximum likelihood estimation method. After estimating Korea's export losses to the US in three trade pressure scenarios, we estimate its impact on Korean domestic production, value-added and job creation by applying the tariff impact accumulation model based on the industry input-output analysis. Empirical results show that the impact of 25% global tariff by the US on the Korean domestic economy is estimated to result in $30.8 billion in export losses for the five years from 2019 to 2023, about 300 thousand job losses, 88.0 trillion in production inducement losses, and 24.0 trillion in value-added inducement losses. The impacts of withdrawal of the automobile tariff concession are estimated at $4.27 billion export losses and 41.7 thousand job losses. A 15% tariff rate on automobile parts for 3 years is estimated to result in $1.93 billion export losses and 18.7 thousand job losses.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.597-603
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• 2006

The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.

• Journal of Public Diplomacy
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• v.2 no.2
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• pp.1-26
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• 2022

Since the seminal publication of Joseph Nye's Soft Power, soft power became the central concept to public diplomacy. However, over-emphasis on soft power, which is still controversial, deterred academics from producing valuable knowledge that can be applied to practices in the field. Soft power is a cause and effect at the same time and thus it makes systematic analysis almost implausible because it is not only a tool for successful public diplomacy, but it is a result of successful diplomacy. This study aims at offering a theoretical framework linking soft power and public diplomacy by including various factors that may affect the outcomes of effective public diplomacy. This theoretical framework assessing the effectiveness of public diplomacy will make it possible to explore how and when new public diplomacy was adopted in a certain country and examine hard and soft power resources. The model also includes political system variables such as ideas and values, institutions, governance, leadership, and communication system, which are expected to influence public diplomacy effectiveness rather than soft power itself. The model yields the effectiveness of public diplomacy by assessing outcome and impact relative to input and output that are applicable to practices. The model is expected to enable both quantitative and qualitative studies generating possible propositions from the model with some preliminary outcomes of comparative case studies.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.91-110
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• 2011

This paper analyzes the cases where the hotels have increased their services and enhanced their work process through IT solutions to cope with computerization globalization. Also the cases have been studies where national hotels use the CRM solution internally to respond effectively to customers requests, increase customer analysis, and build marketing strategies. In particular, this study discusses the introduction of the CRM solutions and CRM sales business and marketing services using a process for utilizing the presumed, CRM by introducing effective DEA(Data Envelopment Analysis). First, the comparison has done regarding the relative efficiency of L Company with the CCR model, then compared L Company's restaurants and facilities' effectiveness through BCC model. L Company reached a conclusion that it is important to precisely create and manage sales data which are the preliminary data for CRM, and for that reason it made it possible to save sales data generated by POS system on each sales performance database. In order to do that, it newly established Oracle POS system and LORIS POS system concerned with restaurants for food and beverage as well as rooms, and made it possible to stably generate and manage sales data and manage. Moreover, it set up a composite database to control comprehensively the results of work processes during a specific period by collecting customer registration information and made it possible to systematically control the information on sales performances. By establishing a system which unifies database and managing it comprehensively, impeccability of data has been greatly enhanced and a problem which generated asymmetric data could be thoroughly solved. Using data accumulated on the comprehensive database, sales data can be analyzed, categorized, classified through data mining engine imbedded in Polaris CRM and the results can be organized on data mart to provide them in the form of CRM application data. By transforming original sales data into forms which are easy to handle and saving them on data mart separately, it enabled acquiring well-organized data with ease when engaging in various marketing operations, holding a morning meeting and working on decision-making. By using summarized data at data mart, it was possible to process marketing operations such as telemarketing, direct mailing, internet marketing service and service product developments for perceived customers; moreover, information on customer perceptions which is one of CRM's end-products could feed back into the comprehensive database. This research was undertaken to find out how effectively CRM has been employed by comparing and analyzing the management performance of each enterprise site and store after introducing CRM to Hotel enterprises using DEA technique. According to the research results, efficiency evaluation for each site was calculated through input and output factors to find out comparative CRM system usage efficiency of L's Company four sites; moreover, with regard to stores, the sizes of workforce and budget application show a huge difference and so does the each store efficiency. Furthermore, by using the DEA technique, it could assess which sites have comparatively high efficiency and which don't by comparing and evaluating hotel enterprises IT project outcomes such as CRM introduction using the CCR model for each site of the related enterprises. By using the BCC model, it could comparatively evaluate the outcome of CRM usage at each store of A site, which is representative of L Company, and as a result, it could figure out which stores maintain high efficiency in using CRM and which don't. It analyzed the cases of CRM introduction at L Company, which is a hotel enterprise, and precisely evaluated them through DEA. L Company analyzed the customer analysis system by introducing CRM and achieved to provide customers identified through client analysis data with one to one tailored services. Moreover, it could come up with a plan to differentiate the service for customers who revisit by assessing customer discernment rate. As tasks to be solved in the future, it is required to do research on the process analysis which can lead to a specific outcome such as increased sales volumes by carrying on test marketing, target marketing using CRM. Furthermore, it is also necessary to do research on efficiency evaluation in accordance with linkages between other IT solutions such as ERP and CRM system.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.57-73
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• 2021

Maintenance and prevention of failure through anomaly detection of ICT infrastructure is becoming important. System monitoring data is multidimensional time series data. When we deal with multidimensional time series data, we have difficulty in considering both characteristics of multidimensional data and characteristics of time series data. When dealing with multidimensional data, correlation between variables should be considered. Existing methods such as probability and linear base, distance base, etc. are degraded due to limitations called the curse of dimensions. In addition, time series data is preprocessed by applying sliding window technique and time series decomposition for self-correlation analysis. These techniques are the cause of increasing the dimension of data, so it is necessary to supplement them. The anomaly detection field is an old research field, and statistical methods and regression analysis were used in the early days. Currently, there are active studies to apply machine learning and artificial neural network technology to this field. Statistically based methods are difficult to apply when data is non-homogeneous, and do not detect local outliers well. The regression analysis method compares the predictive value and the actual value after learning the regression formula based on the parametric statistics and it detects abnormality. Anomaly detection using regression analysis has the disadvantage that the performance is lowered when the model is not solid and the noise or outliers of the data are included. There is a restriction that learning data with noise or outliers should be used. The autoencoder using artificial neural networks is learned to output as similar as possible to input data. It has many advantages compared to existing probability and linear model, cluster analysis, and map learning. It can be applied to data that does not satisfy probability distribution or linear assumption. In addition, it is possible to learn non-mapping without label data for teaching. However, there is a limitation of local outlier identification of multidimensional data in anomaly detection, and there is a problem that the dimension of data is greatly increased due to the characteristics of time series data. In this study, we propose a CMAE (Conditional Multimodal Autoencoder) that enhances the performance of anomaly detection by considering local outliers and time series characteristics. First, we applied Multimodal Autoencoder (MAE) to improve the limitations of local outlier identification of multidimensional data. Multimodals are commonly used to learn different types of inputs, such as voice and image. The different modal shares the bottleneck effect of Autoencoder and it learns correlation. In addition, CAE (Conditional Autoencoder) was used to learn the characteristics of time series data effectively without increasing the dimension of data. In general, conditional input mainly uses category variables, but in this study, time was used as a condition to learn periodicity. The CMAE model proposed in this paper was verified by comparing with the Unimodal Autoencoder (UAE) and Multi-modal Autoencoder (MAE). The restoration performance of Autoencoder for 41 variables was confirmed in the proposed model and the comparison model. The restoration performance is different by variables, and the restoration is normally well operated because the loss value is small for Memory, Disk, and Network modals in all three Autoencoder models. The process modal did not show a significant difference in all three models, and the CPU modal showed excellent performance in CMAE. ROC curve was prepared for the evaluation of anomaly detection performance in the proposed model and the comparison model, and AUC, accuracy, precision, recall, and F1-score were compared. In all indicators, the performance was shown in the order of CMAE, MAE, and AE. Especially, the reproduction rate was 0.9828 for CMAE, which can be confirmed to detect almost most of the abnormalities. The accuracy of the model was also improved and 87.12%, and the F1-score was 0.8883, which is considered to be suitable for anomaly detection. In practical aspect, the proposed model has an additional advantage in addition to performance improvement. The use of techniques such as time series decomposition and sliding windows has the disadvantage of managing unnecessary procedures; and their dimensional increase can cause a decrease in the computational speed in inference.The proposed model has characteristics that are easy to apply to practical tasks such as inference speed and model management.

• Journal of Technology Innovation
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• v.19 no.1
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• pp.111-144
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• 2011

This study is to confirm the core factors of innovative capabilities and technological entrepreneurship affecting the performance of technology management and business management of small and medium-sized enterprises (SMEs). Through the consideration about the complex natures of technological innovation affecting by multidimensional factors, this study designs the research model that innovative capabilities, the performances of technology and business management are arranged in accordance with the innovation process; input-output-outcome. To meet this research purpose, the hypothesis are set up based on the previous research studies and the research samples are selected from members of the Innovative Business (INNO-BIZ) Association, located in Seoul and Geyonggi province. As a result of regression analysis to the responses gathered from 360 firms, the performance of business management is influenced positively by the technology superiority, market growth and business profitability which are the dominant factors of performance of technology management. In addition, three sub-variables of innovative capabilities such as R&D, strategic planning and learning capability, have positive effects on both the managerial performances. Innovativeness and progressiveness of technological entrepreneurship affect both the performances positively. Moreover, the co-relation between technological entrepreneurship of an innovation leader and innovative capabilities of organizational members are identified. Lastly, technological entrepreneurship has the mediating effect on the path of leading innovative capabilities to the managerial performances. In conclusion, the research results imply that technological innovation-type firms should periodically evaluate the performance of technology management which are the output of technological innovations and the reinvestment for ultimate business success. And improving and developing innovative capabilities and technological entrepreneurship is required to continuously and consistently investing and supporting resources on technological innovations at the firm-and government-level. It is considered that these are the crucial methods for securing the technologically competitive advantage of SMEs with less resources and narrow innovation range.

• Journal of Korean Society of Forest Science
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• v.32 no.1
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• pp.29-35
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• 1976

In order to estimate sawmill productivities, rates of technical change and optimum combination of production factors, Cobb-Douglas production functions have been derived using data obtained from 96 sample mills in Busan-Incheon, southwestern and northeastern areas. The results may be summarized as follows: 1. There is a tendency of expanding average sawmill size in the areas. The horse-power holdings per mill have been increased at the rates of 91 percent in Busan-Incheon, 7.7 percent in southwestern and 16.9 percent in northeastern areas. This implies that the mills around log-importing ports have made rapid development, compared with those in forest regions. 2. The regression coefficients (production elasticities) of the functions for the year of 1967 in the above three areas are much similar each other, but significant differencies are found in the production functions of 1975. In other words, sawmill productivity was mainly restricted by capital deficiencies in all areas in 1967, but this situation was succeeded only by N-E area in 1975. The range of sum of regression coefficients is 1.0437-1.4214, this indicates increasing rates of return to scale. 3. The annual rates of technical changes in B-I, S-W and N-E areas for the observed period are 17.6, 7.6 and 2.2 percents respectively. Busan-Incheon is the only area where labor productivity is higher than that of capital. 4. The best combination of production factors for maximizing firm's profit is subject to the changes of input and output prices. With some assumptions of prices and costs, the optimum levels of power and labor input in B-I, S-W and N-E areas are 57:17, 427:94 and 192:27.

• Membrane Journal
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• v.32 no.4
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• pp.235-252
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• 2022

Forward osmotic pressure-free reverse osmosis (Δ𝜋=0 RO) was invented in 2013. The first patent (US 9,950,297 B2) was registered on April 18, 2018. The "Osmotic Pressure of Concentrated Solutions" in JACS (1908) by G.N. Lewis of MIT was used for the estimation. The Chang's RO system differs from conventional RO (C-RO) in that two-chamber system of osmotic pressure equalizer and a low-pressure RO system while C-RO is based on a single chamber. Chang claimed that all aqueous solutions, including salt water, regardless of its osmotic pressure can be separated into water and salt. The second patent (US 10.953.367B2, March 23, 2021) showed that a low-pressure reverse osmosis is possible for 3.0% input at Δ𝜋 of 10 to 12 bar. Singularity ZERO reverse osmosis from his third patent (Korea patent 10-22322755, US-PCT/KR202003595) for a 3.0% NaCl input, 50% more water recovery, use of 1/3 RO membrane area, and 1/5th of theoretical energy. These numbers come from Chang's laboratory experiments and theoretical analysis. Relative residence time (RRT) of feed and OE chambers makes Δ𝜋 to zero or negative by recycling enriched feed flow. The construction cost by S-ZERO was estimated to be around 50~60% of the current RO system.