• Proceedings of the Technology Innovation Conference
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• 2002.02a
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• pp.133-149
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• 2002

This study aims to investigate the impact of wide use of digital technology, in particular, the Internet, on innovation process and corporate strategy in electronics industry. The introduction of digital technology has changed innovation process, business model and organizational structure of the electronics companies. With the introduction of digital technology, the entire value chain of electronics industry from procurement, sales, and marketing to R&D and manufacturing has been restructured. E-commerce has been a major agenda for e-business. Recently, collaboration among electronics companies through e-marketplace has emerged as an important issue. A web-based e-commerce standard, so called RosettaNet, has been developed for facilitating e-transactions of electronics firms. The development of digital technology has dramatically increased the processing speed and sophisticated the virtual reality technology. As simulation becomes easier and more effective, the uncertainty and risk involved in R&D has decreased significantly. Another positive impact is closer cooperation between R&D and manufacturing functions. Taking advantage of automated and flexible production technology, has a new type of firm, so called, EMS (Electronics Manufacturing Services) emerged, whose strategic focus is on manufacturing only. The EMS can be seen as a kind of innovative organization, that is, a modular organization for production function. Digital technology has made convergence of computer and communication possible at early years but right now the convergence has been accelerated in extensive areas of communication, broadcasting, information appliances, software, contents, and services. Firms' effort for an innovative product and service has been intensified and the competition for a new standard product and service has become severe in electronics industry. Business activities are always realized in a specific organizational context. Accordingly building up innovation-friendly organization has emerged as a critical concern. Due to the striking decrease of transaction cost, a network type of organization has proliferated, and a business function turns into a modular organization. As a whole, digital technology has pushed electronics firms into developing their own business model, which takes consideration of standardization of business platform and their core competency.

• The Journal of Society for e-Business Studies
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• v.25 no.3
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• pp.131-145
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• 2020

The numbers of SNS (Social Network Service) users and usage amounts are increasing every year. The influence of SNS is increasing also. SNS has a wide range of influences from daily decision-making to corporate management activities. Therefore, proper analysis of SNS can be a very meaningful work, and many studies are making a lot of effort to look into various activities and relationships in SNS. In this study, we analyze the SNS following relationships using Twitter, one of the representative SNS services. In other words, unlike the existing SNS analysis, our intention is to analyze the interests of the accounts by extracting and visualizing the accounts that two accounts follow in common. For this, a common following account was extracted using Microsoft Excel macros, and the relationship between the extracted accounts was defined using an adjacency matrix. In addition, to facilitate the analysis of the following relationships, a direction graph was used for visualization, and R programming was used for such visualization.

• Journal of the Korea Society of Computer and Information
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• v.14 no.9
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• pp.179-187
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• 2009

The national boundary's meanings turn to weak according to advent of Global enterprises. The place for design a product and marketing are separated to actual market. R&D is to the area where the knowledge activity is well, and low skilful product assembling is to the place the low wage is acceptable. It shows that the importance of net work structure. From early 90's, production system is diversified to markets where with the consumer as the central as multifarious items and creation new demands through consumer's participation into manufacturing process. This phenomenon show that logistics structures adapt to demand of technical variation, and the development of e-business with VAN(:value added network) and EDI(:Electronic data interchange) prove it. This study tried to analyze utilitarian assay about systems those land, sea, air logistics through documents research, and this study also present the direction of logistics system of airline company and goal of development on the based to the model of domestic airline company accordingly.

• Journal of Ecology and Environment
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• v.34 no.2
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• pp.149-156
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• 2011

Phenological variables derived from remote sensing are useful in determining the seasonal cycles of ecosystems in a changing climate. Satellite remote sensing imagery is useful for the spatial continuous monitoring of vegetation phenology across broad regions; however, its applications are substantially constrained by atmospheric disturbances such as clouds, dusts, and aerosols. By way of contrast, a tower-based ground remote sensing approach at the canopy level can provide continuous information on canopy phenology at finer spatial and temporal scales, regardless of atmospheric conditions. In this study, a tower-based ground remote sensing system, called the "Phenological Eyes Network (PEN)", which was installed at the Gwangneung Deciduous KoFlux (GDK) flux tower site in Korea was introduced, and daily phenological progressions at the canopy level were assessed using ratios of red, green, and blue (RGB) spectral reflectances obtained by the PEN system. The PEN system at the GDK site consists of an automatic-capturing digital fisheye camera and a hemi-spherical spectroradiometer, and monitors stand canopy phenology on an hourly basis. RGB data analyses conducted between late March and early December in 2009 revealed that the 2G_RB (i.e., 2G - R - B) index was lower than the G/R (i.e., G divided by R) index during the off-growing season, owing to the effects of surface reflectance, including soil and snow effects. The results of comparisons between the daily PEN-obtained RGB ratios and daily moderate-resolution imaging spectroradiometer (MODIS)-driven vegetation indices demonstrate that ground remote sensing data, including the PEN data, can help to improve cloud-contaminated satellite remote sensing imagery.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.254-262
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• 2013

This paper proposes FMT(Filtered Multi-Tone)-based digital radio implementation algorithms and the results obtained by various field tests especially in terms of transmitter characteristics. In this study, we predefined frame structure and protocols used for the CSTDMA(Carrier Sensing Time Division Multiple Access) scheme, designed digital filters and RF front end to fulfill the system characteristics such as the spectral mask and processing delays given by the Recommendation ITU-R M.1842-1. The proposed system supports exchange of data for e-Navigation with the usage of wider channel of 50-100kHz bandwidth, Turbo coding and FMT modulation. Furthermore, the common Ethernet protocol makes connection to local WLAN(Wireless Local Area Network) on board the ship for other data services.

• Proceedings of the KIPE Conference
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• 2005.07a
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• pp.587-590
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• 2005

In this paper, the PWM inverter-motor drive system including sensor is controlled through the network. The algorithm to compensate for the time delay of ac current and ac voltage sensors due to the network is proposed. The delay time of sensors is kept nearly constant, using the synchronous signal and timers. The error between the real and estimated ac signals can be reduced by using two slopes for estimating the value of at signals. The proposed algorithms are verified with the simulation studies and experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.410-412
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• 1998

Subsymbolic Knowledge processing is said to be changed states of networks constructed from small elements. subsymbolic systems also make it possible to use connectionist models for knowledge processing. Connectionist realization such modulus are modulus linked together for solving a given problem. We study using neural networks as distinct actions. The output vectors produced by the neural networks are consider as a new facts. These new facts are then processed to activate another networks or used in the current production rule, The production rule is applying knowledge stored in the knowledge base to make inference. After neural networks knowledge base is constructed and trained. We present a running sample of incorporating neural network knowledge base. We implement using rochester connectionist simulator. We suggest that incorporating neural network knowledge base. Therefore incorporated neural network knowledge base ensures a cleaner solution which results in better perfor s.

• Journal of Photoscience
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• v.9 no.2
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• pp.305-307
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• 2002

Spectroscopic titration of D 193N and D 193E mutants of pharaonis phoborhodopsin (ppR) were performed to evaluate the pK$_{a}$ of the Schiff base Asp 193 corresponds to Glu204 of bacteriorhodopsin (bR). The pK$_{a}$ of the Schiff base (SBH$^{+}$) of D193N was 10.1~10.0 (at XH$^{+}$) and 11.4~11.6 (at X) depending on the protonation state of a certain residue (designated by X) and independent on CI$^{[-10]}$ , while those of the wild-type and D193E were> 12. pK$_{a}$ of XH$^{+}$ were; 11.8~11.2 at the state of SB, 10.5 at SBH$^{+}$ state in the presence of CI$^{[-10]}$ , and 9.6 at SBH$^{+}$ without CI$^{[-10]}$ These imply the presence of a long-range interaction in the extracellular channel.r channel.

• Journal of the Korean Chemical Society
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• v.60 no.4
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• pp.225-234
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• 2016

The activity of 34 sulfonamide derivatives has been estimated by means of multiple linear regression (MLR), artificial neural network (ANN), simulated annealing (SA) and genetic algorithm (GA) techniques. These models were also utilized to select the most efficient subsets of descriptors in a cross-validation procedure for non-linear -log (IC50) prediction. The results obtained using GA-ANN were compared with MLR-MLR, MLR-ANN, SA-ANN and GA-ANN approaches. A high predictive ability was observed for the MLR-MLR, MLR-ANN, SA-ANN and MLR-GA models, with root mean sum square errors (RMSE) of 0.3958, 0.1006, 0.0359, 0.0326 and 0.0282 in gas phase and 0.2871, 0.0475, 0.0268, 0.0376 and 0.0097 in solvent, respectively (N=34). The results obtained using the GA-ANN method indicated that the activity of derivatives of sulfonamides depends on different parameters including DP03, BID, AAC, RDF035v, JGI9, TIE, R7e+, BELM6 descriptors in gas phase and Mor 32u, ESpm03d, RDF070v, ATS8m, MATS2e and R4p, L1u and R3m in solvent. In conclusion, the comparison of the quality of the ANN with different MLR models showed that ANN has a better predictive ability.

• Nuclear Engineering and Technology
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• v.48 no.1
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• pp.64-71
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• 2016

Void fraction is an important parameter in the oil industry. This quantity is necessary for volume rate measurement in multiphase flows. In this study, the void fraction percentage was estimated precisely, independent of the flow regime in gas-liquid two-phase flows by using ${\gamma}-ray$ attenuation and a multilayer perceptron neural network. In all previous studies that implemented a multibeam ${\gamma}-ray$ attenuation technique to determine void fraction independent of the flow regime in two-phase flows, three or more detectors were used while in this study just two NaI detectors were used. Using fewer detectors is of advantage in industrial nuclear gauges because of reduced expense and improved simplicity. In this work, an artificial neural network is also implemented to predict the void fraction percentage independent of the flow regime. To do this, a multilayer perceptron neural network is used for developing the artificial neural network model in MATLAB. The required data for training and testing the network in three different regimes (annular, stratified, and bubbly) were obtained using an experimental setup. Using the technique developed in this work, void fraction percentages were predicted with mean relative error of <1.4%.