In the civil market, companies launch new products when the acquired innovations are ready, but in defense, customer requests the innovation applied weapon systems. The technology adoption cycle model takes unusual form of market like inverse chasm takes technology inversely. This thesis describes an inverse chasm from the perspective of technology adoption cycle, equipped product model, and technical progress S-curve. As a way to overcome the inverse chasm, considering factors like a self-investment demo model, customer needs, and the temporary chasm expanding phenomenon are derived. And order-effective relationship analysis and chasm marketing strategy are suggested. Especially securing the core technologies and possibility for equipped product by developing self-investment demo model are identified as a good marketing strategy of chasm. This analysis and strategy suggest the policy implications for preemptive advantage of market positioning in the procurement process of defense, discontinuous innovation technology applied on.
The rheological properties of hard red winter, western white and Australian standard white wheat flours and of HRW-WW and HRW-ASW wheat flour blends having the same protein content were studied. Cooking properties of dry noodles prepared from HRW-WW and HRW-ASW wheat flour blends were also investigated. The noodles were prepared with salt and alkaline reagent. The salt and alkaline concentrations used were 1.7% and 0.17%. respectively, based on the weight of wheat flour. The alkaline reagent was an equal mixture of sodium carbonate and potassium carbonate. The HRW-ASW wheat flour blend had higher farinograph absorption and slightly stronger curve than HRW-WW wheat flour blend. Salt decreased the absorption of wheat flours by 2 and of wheat flour blends by 1%. However, alkaline reagent essentially had no effort on farinograph absorption. Salt and alkaline reagent strengthened the dough of wheat floors and wheat flour blends, with the former being more effective. No significant differences in pasting properties between HRW-WW and HRW-ASW wheat flour blends by amylograph were observed. There were no significant differences in rate of increase of weight or volume between noodles prepared from HRW-WW and HRW-ASW wheat flour blends. Alkaline reagent did not affect the weight gain of noodles hut lowered the volume gain. Breaking force of dry noodles and cutting force of cooked noodles were similar between the two noodles. Alkaline reagent increased both the breaking and cutting forces of noodles. Sensory evaluation revealed that the noodles prepared from HRW-WW and HRW-ASW wheat flour blends were slightly different. but not different from each other by preference test.
The Journal of Korean Institute of Communications and Information Sciences
/
v.39C
no.3
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pp.255-263
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2014
Today, a number of CCTV on the highway is to observe the flow of traffics. There have been a number of studies where traffic data (e.g., the speed of vehicles and the amount of traffic on the road) are transferred back to the centralized server so that an appropriate action can be taken. This paper introduces a system that detects the changes of traffic flows caused by an accident or unexpected stopping (i.e., vehicle remains idle) by monitoring each lane separately. The traffic flows of each lane are level spacing curve that shows Wigner distribution for location vector. Applying calogero-moser system and Hamiltonian system, probability equation for each level-spacing curve is derived. The high level of modification of the signal means that the lane is in accident situation. This is different from previous studies in that it does more than looking for the signal from only one lane, now it is able to detect an accident in entire flow of traffic. In process of monitoring traffic flow of each lane, when camera recognizes a shadow of vehicle as a vehicle, it will affect the accident detecting capability. To prevent this from happening, the study introduces how to get rid of such shadow. The system using Basian network method is being compared for capability evaluation of the system of the study. As a result, the system of the study appeared to be better in performance in detecting the modification of traffic flow caused by idle vehicle.
Journal of the Institute of Electronics Engineers of Korea SC
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v.48
no.4
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pp.1-9
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2011
Hemorrhagic shock is a clinically widespread syndrome characterized by inadequate oxygenation and supply. It is important to diagnose hemorrhagic shock in its early stage for improving treatment effects and survival rate. However, an accurate diagnosis and treatment could be delayed in the early stage of hemorrhagic shock by evaluating only vital signs such as heart rate and blood pressure. There have been many studies for the early diagnosis of hemorrhagic shock, reporting that lactate concentration and perfusion were useful variables for tissue hypoxia and metabolic acidosis. In this study, we measured both perfusion using a laser Doppler flowmeter and lactate concentration from the volume controlled hemorrhagic shock using rats. We also proposed a new shock index which was calculated by dividing lactate concentration by perfusion for early diagnosis. As a result of the survival prediction by the proposed index with the receiver operating characteristic curve method, the sensitivity, specificity, and accuracy of survival were 90.0, 96.7 and 94.0%, respectively. The proposed index showed the fastest significant difference among the other parameters such as blood pressure and heart rate. It could offer early diagnosis and effective treatment for human hemorrhagic shock if it is applicable to humans.
Twitter has been continuously growing since October, 2006. Especially, not only the users and the number of messages have been increasing but also a new concept in social networking called 'micro blogging' has diffused. Within Korea, service such as 'me2day' has already been introduced and the improvement of internet accessibility within mobile devices is expected to expand the 'micro blogs'. In this point, this research is executed to study the new medium, 'micro blog'. To do so, we collected and analyzed Twitter logs of Korean users. Especially, we were curious about the extreme heavy users using Twitter, despite of the linguistic and cultural barrier of the foreign service. Who they are, why and how they use the 'micro blog'. First, we reviewed the general aspect of followers and messages by collecting a certain number of random samples. Using the Lorenz curve we found out that there was the imbalance within the users and based on this phenomenon we deducted an extreme heavy user group. In order to perform further analysis, log analysis was performed on the extreme heavy users. As the result, the users used multiple mobile and desktop 'Twitter' clients. The usage pattern was similar to that of internet usage time but was used during their "micro" time. The users using 'Twitter' not only to spread messages about important information, special events and emotions, but also as a habitual 'chatting tool' to express ordinary personal chats similar to SMS and IM services. In this research, it is proved that 68% of the total messages were ordinary personal chats. Also, with 24% of the total messages were retweets, we were able to find out that virtually connected 'people' and 'relationships' acted as the dominant trigger of their articulation.
A capacitive water sensor was developed to measure the capacitance over a wide part of a substrate using an insulated electrode plate (30 cm × 10 cm) with copper and Teflon attached on either side of the substrate. This study aimed to convert the capacitance output obtained from the condenser-type capacitance sensor into the substrate water content. The quantification experiment was performed by measuring the changes in substrate water weight and capacitance while providing a nutrient solution and by subsequently comparing these values. The substrate water weight and capacitance were measured every 20 to 30 seconds using the sensor and load cell with a software developed specifically for this study. Using a curve-fitting program, the substrate water content was estimated from the output of the capacitance using the water weight and capacitance of the substrate as variables. When the amount of water supplied was increased, the capacitance tended to increase. Coefficient of variation (CV) in capacitance according to the water weight in substrate was greater with the 1.0 kg of water weight, compared with other weights. Thus, the fitting was performed with higher than 1.0 kg, from 1.7 to 6.0 kg of water weight. The correlation coefficient between the capacitance and water weight in substrate was 0.9696. The calibration equation estimated water content from the capacitance, and it was compared with the substrate water weight measured by the load cell.
The ground roll is the most common coherent noise in land seismic data and has an amplitude much larger than the reflection event we usually want to obtain. Therefore, ground roll suppression is a crucial step in seismic data processing. Several techniques, such as f-k filtering and curvelet transform, have been developed to suppress the ground roll. However, the existing methods still require improvements in suppression performance and efficiency. Various studies on the suppression of ground roll in seismic data have recently been conducted using deep learning methods developed for image processing. In this paper, we introduce three models (DnCNN (De-noiseCNN), pix2pix, and CycleGAN), based on convolutional neural network (CNN) or conditional generative adversarial network (cGAN), for ground roll suppression and explain them in detail through numerical examples. Common shot gathers from the same field were divided into training and test datasets to compare the algorithms. We trained the models using the training data and evaluated their performances using the test data. When training these models with field data, ground roll removed data are required; therefore, the ground roll is suppressed by f-k filtering and used as the ground-truth data. To evaluate the performance of the deep learning models and compare the training results, we utilized quantitative indicators such as the correlation coefficient and structural similarity index measure (SSIM) based on the similarity to the ground-truth data. The DnCNN model exhibited the best performance, and we confirmed that other models could also be applied to suppress the ground roll.
Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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v.8
no.11
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pp.215-222
/
2018
In this paper, the research on the energy storage system adapting super-capacitor has been performed. The most advanced features compared to the conventional lead-acid battery systems is that it can obtain high power capability due to the super capacitor power characteristics. The suggested system can attain high power in short times and achieve high power quality improvements. The application areas are power quality improvement system, motor start power which requires high power during transient times. The energy conversion system consists of bi-directional converter and inverter and advantages of high speed, high power charging and discharging performances. The design steps for the two loop controller of the bi-directional inverter are suggested and verified by the experiment and manufacturing. The two loop controller design starts from linearized transfer function which is calculated from the state averaging model including state decoupling method. The current controller requirements are 20% overshoot and settling time and voltage controller are no overshoot and settling time which is 10 times longer than current controller. The design is verified from the step input response. The designed controllers have unity power factor characteristics and thus can improve the power quality of the grid. It also has fast response time and zero steady state error.
The Journal of the Convergence on Culture Technology
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v.8
no.3
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pp.91-97
/
2022
The purpose of this study was to analyze the measurements of blood pressure and time using manual and automatic blood pressure monitors in various road conditions to verify reliable blood pressure monitor in a moving ambulance. First, the manual blood pressure monitor palpation on unpaved roads showed a systolic pressure deviation of 5 mmHg. However, the automatic blood pressure monitor showed two measurement failures, one reading failure, and the measured systolic pressure deviation was 35 mmHg. The measurement time was 102 seconds faster on average than the automatic blood pressure monitor. Second, the palpation of the manual blood pressure monitor while going over speed bumps remained constant at 130 mmHg. However, the automatic blood pressure monitor had a systolic pressure deviation of 52 mmHg. The measurement time was 61 seconds faster on average than the automatic blood pressure monitor. Finally, the manual blood pressure monitor palpation on the sharp curve road showed a systolic pressure deviation of 5 mmHg. The automatic blood pressure monitor had one reading failure and the measured systolic pressure deviation was 21 mmHg. The measurement time showed that the manual blood pressure monitor was 101 seconds faster than the automatic blood pressure monitor. As a result, in a moving ambulance during an emergency, the manual blood pressure monitor showed high reliability because the blood pressure measurement was constant and the measurement time was short.
KSCE Journal of Civil and Environmental Engineering Research
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v.30
no.6D
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pp.577-585
/
2010
Traffic accidents are caused by several factors such as drivers, vehicles, and road environment. It is necessary to investigate and analyze them in advance to prevent similar and repetitive traffic accidents. Especially, the human factor is most significant element and traffic accidents by drinking-driving caused from human factor have become social problem to be paid attention to. The study analyzes traffic accidents resulting from drinking-driving and the effects of driver's attributes and environmental factors on them. The study is composed as two parts. First, the log-linear model is applied to analyze that accidents by drinking or non-drinking driving associate with road geometry, weather condition and personal characteristics. Probability is tested for drinking-driving accidents relative to non-drinking drive accidents. The study analyzes probability differences between genders, between ages, and between kinds of vehicles through odds multipliers. Second, traffic accidents related to drinking are classified into property damage, minor injury, heavy injury, and death according to their severity. Heavy injury is more serious than minor one and death is more serious than heavy injury. The ordinal regression models are established to find effecting factors on traffic accident severity.
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