• STI Policy Review
• /
• v.2 no.3
• /
• pp.35-44
• /
• 2011

Korea has rapidly increased R&D investment over the last few decades and the intensity of R&D investment is among the highest in the world; however, there are serious concerns about R&D performance and R&D efficiency. This study is to improve the economic assessment methodology regarding a feasibility study for national R&D programs that are thought to be one of the most prominent ways to enhance R&D efficiency. In order to improve the methodology of economic assessment, a few of important factors such as technical or market uncertainty, spillover effect, and R&D contribution ratio should be covered in the model. The focus of this article is technological and market uncertainty that has a close relation with strategic flexibility and utilization potential to increase the value of R&D programs. To improve the current linear and definitive R&D process, a new framework with strategic flexibility is suggested, in which the result of economic assessment that considers technological and market uncertainty is reflected in planning. That kind of feedback process is expected to enhance the value of the program/project as well as R&D efficiency.

• Journal of the Korean Society for Precision Engineering
• /
• v.13 no.3
• /
• pp.42-48
• /
• 1996

In this paper, a position correction system of industrial robot for door-chassis assembly tast is developed in connection with the position correction algorithm shown in Part I. Tow notches and a hole of auto chassis are selected as the reference measure points and a vision based error detection algorithm is devised to measure in accuracy of less than 0.07mm. And also, the transformation between base and tool coordinates of the robot is shown to send the suitable correction quantities caaording to robot's option. The obtained algorithms were satisfactorily implemented for a real door-chassis model such that the system could accomplish visually acceptable door-chassis assembly task.

• The Journal of the Acoustical Society of Korea
• /
• v.21 no.3
• /
• pp.237-244
• /
• 2002

In this paper we mention the optimization of MPEG-4 VM (Moving Picture Expert Group-4 Verification Model) GA (General Audio) AAC (Advanced Audio Coding) encoder and the design of the decoder for PDA (Personal Digital Assistant) using MPEG-4 VM source. We profiled the VMC source and several optimization methods have applied to those selected functions from the profiling. Intel Pentium III 600 MHz PC, which uses windows 98 as OS, takes about 20 times of encoding time compared to input sample running time, with additional options, and about 10 times without any option. Decoding time on PDA was over 35 seconds for the 17 seconds input sample. After optimization, the encoding time has reduced to 50% and the real time decoding has achieved on PDA.

• Asia Marketing Journal
• /
• v.15 no.3
• /
• pp.159-172
• /
• 2013

In the present study, we apply the multiple cue probability learning (MCPL) paradigm to examine consumer learning from feedback in repeated trials. This paradigm is useful in investigating consumer learning, especially learning the relationships between the overall quality and attributes. With this paradigm, we can analyze what people learn from repeated trials by using the lens model, i.e., whether it is knowledge or consistency. In addition to introducing this paradigm, we aim to demonstrate that knowledge people gain from repeated trials with feedback is robust enough to weaken one of the most often examined contextual effects, the asymmetric dominance effect. The experiment consists of learning session and a choice task and stimuli are sport rafting boats with motor engines. During the learning session, the participants are shown an option with three attributes and are asked to evaluate its overall quality and type in a number between 0 and 100. Then an expert's evaluation, a number between 0 and 100, is provided as feedback. This trial is repeated fifteen times with different sets of attributes, which comprises one learning session. Depending on the conditions, the participants do one (low) or three (high) learning sessions or do not go through any learning session (no learning). After learning session, the participants then are provided with either a core or an extended choice set to make a choice to examine if learning from feedback would weaken the asymmetric dominance effect. The experiment uses a between-subjects experimental design (2 × 3; core set vs. extended set; no vs. low vs. high learning). The results show that the participants evaluate the overall qualities more accurately with learning. They learn the true trade-off rule between attributes (increase in knowledge) and become more consistent in their evaluations. Regarding the choice task, there is a significant decrease in the percentage of choosing the target option in the extended sets with learning, which clearly demonstrates that learning decreases the magnitude of the asymmetric dominance effect. However, these results are significant only when no learning condition is compared either to low or high learning condition. There is no significant result between low and high learning conditions, which may be due to fatigue or reflect the characteristics of learning curve. The present study introduces the MCPL paradigm in examining consumer learning and demonstrates that learning from feedback increases both knowledge and consistency and weakens the asymmetric dominance effect. The latter result may suggest that the previous demonstrations of the asymmetric dominance effect are somewhat exaggerated. In a single choice setting, people do not have enough information or experience about the stimuli, which may lead them to depend mostly on the contextual structure among options. In the future, more realistic stimuli and real experts' judgments can be used to increase the external validity of study results. In addition, consumers often learn through repeated choices in real consumer settings. Therefore, what consumers learn from feedback in repeated choices would be an interesting topic to investigate.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.12 no.4
• /
• pp.157-165
• /
• 1992

IMS, a precision coordinate measuring system using theodolites, is being used to survey and align precision mechanical structures. Compared to conventional mechanical devices for precision measurement, such as CMM (Coordinate Measuring Machine), the target objects of IMS have little limitations in their sizes and shapes, and can be measured in place. Also since IMS displays the coordinate values in real-time, it is possible to perform measurement and alignment of the objects simultaneously. In this paper, the elements and functions of IMS are introduced and a mathematical model of the new software, which utilizes an altered version of the 'Bundle' adjustment algorithm of analytical photogrammetry for the specific use of IMS, is demonstrated. Differences of the mathematical model of IMS from that of analytical photogrammetry are discussed by following the steps of the 'Measurement' option in the 'Main Menu' of the software. A new IMS calibration method is proposed to calculate better first approximations for the 4 unknown theodolite parameters and the coordinates of target objects. The software provides the 'Bundle' procedure for the first approximations of the unknowns before the real-time measurement. It also provides an opportunity of 'bundling' to re-adjust the collected positional data at the end of the measurement.

• International Journal of Computer Science & Network Security
• /
• v.24 no.8
• /
• pp.14-20
• /
• 2024

Traffic sign recognition is an essential feature of intelligent transportation systems and Advanced Driver Assistance Systems (ADAS), which are necessary for improving road safety and advancing the development of autonomous cars. This research investigates the incorporation of the YOLOv9 model into traffic sign recognition systems, utilizing its sophisticated functionalities such as Programmable Gradient Information (PGI) and Generalized Efficient Layer Aggregation Network (GELAN) to tackle enduring difficulties in object detection. We employed a publically accessible dataset obtained from Roboflow, which consisted of 3130 images classified into five distinct categories: speed_40, speed_60, stop, green, and red. The dataset was separated into training (68%), validation (21%), and testing (12%) subsets in a methodical manner to ensure a thorough examination. Our comprehensive trials have shown that YOLOv9 obtains a mean Average Precision (mAP@0.5) of 0.959, suggesting exceptional precision and recall for the majority of traffic sign classes. However, there is still potential for improvement specifically in the red traffic sign class. An analysis was conducted on the distribution of instances among different traffic sign categories and the differences in size within the dataset. This analysis aimed to guarantee that the model would perform well in real-world circumstances. The findings validate that YOLOv9 substantially improves the precision and dependability of traffic sign identification, establishing it as a dependable option for implementation in intelligent transportation systems and ADAS. The incorporation of YOLOv9 in real-world traffic sign recognition and classification tasks demonstrates its promise in making roadways safer and more efficient.

• Management & Information Systems Review
• /
• v.28 no.4
• /
• pp.27-44
• /
• 2009

Economic value of a certain technology is of great interest and importance in a wide variety of investment circumstances. These vary from companies considering investing in R&D projects, to venture capitalists funding start-up companies. However, such valuation is extremely difficult in any case, and the cost of failure can be very high. Many techniques have been proposed to assist managers facing this issue, from traditional discounted cash flow analysis to more recent methods based on real options. In the meantime, the discounted cash flow method has limitations in applying the valuation of technology. At the same time, there have been various solutions to overcome theoretical problems of the method. Real options have been thought as a solution. However, there are another problems in using them in real world. This paper reviews the previous studies on the valuation of technology in several aspects, discusses the practicability of the various methods available, and explore the application of a hybrid model, which aims to make these rather aore the ideas more accessible to practicing managers.

• Korean Journal of Construction Engineering and Management
• /
• v.13 no.2
• /
• pp.102-109
• /
• 2012

One of key success factors in PPI(Public Private Investment) is the structure of risk sharing between the public and the private, and the determination mechanism of fair return to private participants relative to the risk that private participants undertake. In Korea, two basic types of PPI exist. One is BTO and the other is BTL. In BTO, most risks are taken by the private whereas the opposite is the case in BTL. No intermediate form exists. As a result, BTO type projects had difficulty in attracting private participants because of the excessive risks. In this study, one intermediate form is studied where demand risk is shared between the public and the private. In the setting where the public authority takes all the project revenues and then pays ladder type payments to private participants depending upon the level of project revenues, appropriate level of fixed payments is endogenously derived using the real option pricing model. From the fixed payments, expected investment returns are calculated based upon a certain distributional assumption. The results of this study is expected to help introducing diverse forms of PPI in Korea.

• Journal of Information Management
• /
• v.32 no.3_4
• /
• pp.123-145
• /
• 2001

The purpose of this study is to develop technology valuation system for technology transfer, which is using and supporting knowledge information. The valuation system comprises estimation of latent business profit by supporting formatted patent and technology-products market information, analysis of contribution profit by using industrial standard and innovation step and value of technology by using a real option equation. This study suggests a successful system in order to valuate the technologies quantitatively, and to use and support knowledge information from KISTI databases or other selected internet Information.

• International conference on construction engineering and project management
• /
• 2013.01a
• /
• pp.602-607
• /
• 2013

Financial risks associated with capital investments are often measured with different feasibility indicators such as the net present value (NPV), the internal rate of return (IRR), the payback period (PBP), and the benefit-cost ratio (BCR). This paper aims at demonstrating practical applications of probabilistic feasibility analysis techniques for an integrated feasibility evaluation of the IRR and PBP. The IRR and PBP are concurrently analyzed in order to measure the profitability and liquidity, respectively, of a cash flow. The cash flow data of a real wind turbine project is used in the study. The presented approach consists of two phases. First, two newly reported analysis techniques are used to carry out a series of what-if analyses for the IRR and PBP. Second, the relationship between the IRR and PBP is identified using Monte Carlo simulation. The results demonstrate that the integrated feasibility evaluation of stochastic cash flows becomes a more viable option with the aide of newly developed probabilistic analysis techniques. It is also shown that the relationship between the IRR and PBP for the wind turbine project can be used as a predictive model for the actual IRR at the end of the service life based on the actual PBP of the project early in the service life.