• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.101-124
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• 2018

Recently, most of the technologies have been developed in various forms through the advancement of single technology or interaction with other technologies. Particularly, these technologies have the characteristic of the convergence caused by the interaction between two or more techniques. In addition, efforts in responding to technological changes by advance are continuously increasing through forecasting promising convergence technologies that will emerge in the near future. According to this phenomenon, many researchers are attempting to perform various analyses about forecasting promising convergence technologies. A convergence technology has characteristics of various technologies according to the principle of generation. Therefore, forecasting promising convergence technologies is much more difficult than forecasting general technologies with high growth potential. Nevertheless, some achievements have been confirmed in an attempt to forecasting promising technologies using big data analysis and social network analysis. Studies of convergence technology through data analysis are actively conducted with the theme of discovering new convergence technologies and analyzing their trends. According that, information about new convergence technologies is being provided more abundantly than in the past. However, existing methods in analyzing convergence technology have some limitations. Firstly, most studies deal with convergence technology analyze data through predefined technology classifications. The technologies appearing recently tend to have characteristics of convergence and thus consist of technologies from various fields. In other words, the new convergence technologies may not belong to the defined classification. Therefore, the existing method does not properly reflect the dynamic change of the convergence phenomenon. Secondly, in order to forecast the promising convergence technologies, most of the existing analysis method use the general purpose indicators in process. This method does not fully utilize the specificity of convergence phenomenon. The new convergence technology is highly dependent on the existing technology, which is the origin of that technology. Based on that, it can grow into the independent field or disappear rapidly, according to the change of the dependent technology. In the existing analysis, the potential growth of convergence technology is judged through the traditional indicators designed from the general purpose. However, these indicators do not reflect the principle of convergence. In other words, these indicators do not reflect the characteristics of convergence technology, which brings the meaning of new technologies emerge through two or more mature technologies and grown technologies affect the creation of another technology. Thirdly, previous studies do not provide objective methods for evaluating the accuracy of models in forecasting promising convergence technologies. In the studies of convergence technology, the subject of forecasting promising technologies was relatively insufficient due to the complexity of the field. Therefore, it is difficult to find a method to evaluate the accuracy of the model that forecasting promising convergence technologies. In order to activate the field of forecasting promising convergence technology, it is important to establish a method for objectively verifying and evaluating the accuracy of the model proposed by each study. To overcome these limitations, we propose a new method for analysis of convergence technologies. First of all, through topic modeling, we derive a new technology classification in terms of text content. It reflects the dynamic change of the actual technology market, not the existing fixed classification standard. In addition, we identify the influence relationships between technologies through the topic correspondence weights of each document, and structuralize them into a network. In addition, we devise a centrality indicator (PGC, potential growth centrality) to forecast the future growth of technology by utilizing the centrality information of each technology. It reflects the convergence characteristics of each technology, according to technology maturity and interdependence between technologies. Along with this, we propose a method to evaluate the accuracy of forecasting model by measuring the growth rate of promising technology. It is based on the variation of potential growth centrality by period. In this paper, we conduct experiments with 13,477 patent documents dealing with technical contents to evaluate the performance and practical applicability of the proposed method. As a result, it is confirmed that the forecast model based on a centrality indicator of the proposed method has a maximum forecast accuracy of about 2.88 times higher than the accuracy of the forecast model based on the currently used network indicators.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.723-724
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• 2011

• Journal of Engineering Education Research
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• v.23 no.4
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• pp.3-13
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• 2020

The purpose of this study is to analyze the differences in the perception and education requirements between industry and engineering students on engineering convergence competency, and to suggest implications for fostering engineers suitable to industry demand and direction of focus improvement in the current engineering education field. To this end, 73 industrial representatives and 104 engineering students are surveyed the engineering convergence competency and educational needs. The results of this analysis are as follows: first, the difference in engineering convergence competency by background variable was significantly different in gender of engineering students. Second, it is found that there is a significant difference between the current level and the required level of engineering convergence competency from an industry perspective. In the IPA results, it shows that new knowledge generation and future-oriented vision skills are urgently needed to be improved. And it is showed that the creative thinking, knowledge utilization, communication, and cooperation capabilities skills need to be maintained continuously. Third, as a result of the analysis of the differences in recognition of the current competency levels between industry and engineering students, there is statistically significant differences in systemic thinking, communication and cooperation, understanding of other academic fields, humanities, and future-oriented perspectives. Therefore, it is necessary to specific plans and efforts to reduce this perception gap should be prepared at the university.

• ETRI Journal
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• v.37 no.2
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• pp.233-240
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• 2015

The novelty of this study resides in a 6"-wafer-level microfabrication protocol for a microdevice with a fluidic control system for the separation of circulating tumor cells (CTCs) from human whole blood cells. The microdevice utilizes a lateral magnetophoresis method based on immunomagnetic nanobeads with anti-epithelial cell adhesive molecule antibodies that selectively bind to epithelial cancer cells. The device consists of a top polydimethylsiloxane substrate for microfluidic control and a bottom substrate for lateral magnetophoretic force generation with embedded v-shaped soft magnetic microwires. The microdevice can isolate about 93% of the spiked cancer cells (MCF-7, a breast cancer cell line) at a flow rate of 40/100 mL/min with respect to a whole human blood/buffer solution. For all isolation, it takes only 10 min to process 400 mL of whole human blood. The fabrication method is sufficiently simple and easy, allowing the microdevice to be a mass-producible clinical tool for cancer diagnosis, prognosis, and personalized medicine.

• ETRI Journal
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• v.37 no.2
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• pp.387-394
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• 2015

A novel interconnection technology based on a 52InSn solder was developed for flexible display applications. The display industry is currently trying to develop a flexible display, and one of the crucial technologies for the implementation of a flexible display is to reduce the bonding process temperature to less than $150^{\circ}C$. InSn solder interconnection technology is proposed herein to reduce the electrical contact resistance and concurrently achieve a process temperature of less than $150^{\circ}C$. A solder bump maker (SBM) and fluxing underfill were developed for these purposes. SBM is a novel bumping material, and it is a mixture of a resin system and InSn solder powder. A maskless screen printing process was also developed using an SBM to reduce the cost of the bumping process. Fluxing underfill plays the role of a flux and an underfill concurrently to simplify the bonding process compared to a conventional flip-chip bonding using a capillary underfill material. Using an SBM and fluxing underfill, a $20{\mu}m$ pitch InSn solder SoP array on a glass substrate was successfully formed using a maskless screen printing process, and two glass substrates were bonded at $130^{\circ}C$.

• Current Photovoltaic Research
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• v.5 no.1
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• pp.9-14
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• 2017

The screen printing technique is one of process to form electrode for crystalline silicon solar cell and has been studied a lot, because it has many advantages such as low price, high efficiency and mass production due to simple and fast process. The reason why electrode formation is important is for influence of series resistance and amount of incident light in crystalline silicon solar cell. In this study, electrode was formed by screen printing method with various conditions like squeegee angle, printing speed, snap off, printing pressure. After optimizing various conditions, double printing method was applied to obtain low series resistance and high aspect ratio. As a result, we obtained electrode resistance 45.31 ohm, aspect ratio 4.38, shading loss 7.549% mono-crystalline silicon solar cell with optimal double screen printing condition.

• Convergence Security Journal
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• v.16 no.1
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• pp.59-68
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• 2016

Recently, many domestic and foreign industries is increasing gradually in the importance of security such as the emergence of a Convergence Information Technology(internet of things, cloud computing service, big data etc). Among these techniques, the industrial security market is expected to grow gradually and the evolution of security technologies, as well as vulnerabilities are also expected to increase. Therefore, an increase in physical vulnerability factors it is no exaggeration to standards that are determining the security of industrial security. In this paper will be analyzed to the physical security technology and case study, physical vulnerability factor. Thereby this is expected to be utilized as a basis for the countermeasure of physical corresponding infringement and attack in a future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.816-819
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• 2011

The image recognition system using CCTV camera has been introduced to minimize not only loss of life and property but also traffic jam in the tunnel. In this paper, multi-object detection algorithm is proposed to track multi vehicles. The proposed algorithm is to detect multi cars based on Adaboost and to track multi vehicles to use template matching. As results of simulations, it is shown that proposed algorithm is useful for tracking multi vehicles.

• Journal of Korea Multimedia Society
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• v.20 no.11
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• pp.1811-1819
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• 2017

As the induction motor is the core production equipment of the industry, it is necessary to construct a fault prediction and diagnosis system through continuous monitoring. Many researches have been conducted on motor fault diagnosis algorithm based on signal processing techniques using Fourier transform, neural networks, and fuzzy inference techniques. In this paper, we propose a fault diagnosis method of induction motor using LPC and DNN. To evaluate the performance of the proposed method, the fault diagnosis was carried out using the vibration data of the induction motor in steady state and simulated various fault conditions. Experimental results show that the learning time of our proposed method and the conventional spectrum+DNN method is 139 seconds and 974 seconds each executed on the experimental PC, and our method reduces execution time by 1/8 compared with conventional method. And the success rate of the proposed method is 98.08%, which is similar to 99.54% of the conventional method.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.2
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• pp.101-107
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• 2018

As indoor pollutants such as carbon dioxide and dust mainly affect the respiratory and circulatory systems, there is an increasing need for real-time indoor / outdoor environmental monitoring. In this paper, we have developed a real - time environmental monitoring system using the cloud-based 3G integrated environmental sensor module for environmental monitoring. A highly reliable environmental information monitoring system requires various IT technologies such as infrastructure (server, commercial software, etc.), service application software, security, and authentication. A real-time environment monitoring system based on cloud service that can provide reliable service satisfying these configuration requirements is proposed and implemented. It is expected that this system can be applied to various technologies such as indoor automatic window opening/closing system based on the Internet.