• International Journal of Automotive Technology
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• v.3 no.1
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• pp.41-46
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• 2002

Effect of secondary air injection (SAI) on hydrocarbon reduction has been investigated in a single cylinder Sl engine operating at cold-steady/cold-start conditions. The hydrocarbon emission and exhaust gas temperature with and without catalytic converter were compared with continuous and synchronized SAIs, which injected secondary air intermittently into exhaust port. Effects of SAI location, SAI pressure, SAI timing, and location of catalytic converter have been investigated and the results are compared for both SAls with base condition. At cold-steady condition, the rate of HC reduction increased as the location of SAI was closer to the exhaust valve for both synchronized and continuous SAls. The emission of HC decreased with increasing exhaust-A/F when it was rich, and was relatively insensitive when it was lean. The timing of SAI in synchronized SAI had significant effect on HC reduction and exhaust gas temperature and the synchronized SAI was found to be more effective in HC reduction and exhaust gas temperature compared to the continuous SAI . At cold-start condition, when the catalytic converter was located 20 cm downstream from the exhaust port exit, the catalytic converter warm-up period for both SAls decreased by about 50%, and the accumulated hydrocarbon emission during the first 120 s decreased about by 56% and 22% with the synchronized and continuous SAIs, respectively, compared to that of the base condition.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.330-335
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• 2000

This paper deals with sensing ability of smart sensor that has a sensing ability of distinguish materials. We have developed new signal processing method that have distinguish different materials. We made the two type of smart sensors for experiment. The first type of smart sensor is H2 type. The second type of smart sensor is HH type. The smart sensor was developed for recognition of material. And then we developed estimation method of sensing ability of smart sensors. The first method(Sensing Ability Index) is developed for H2 smart sensor. The second method($R_{SAI}$ Index) is developed for HH smart sensor. We estimated sensing ability of smart sensor with new SAI and $R_{SAI}$ method. This paper describes our primary study for a new method of estimate sensing ability of smart sensor, which is need for precision work system. This is a study of dynamic characteristics of smart sensor according to frequency and displacement changing with new SAI and $R_{SAI}$ method. Experiment and analysis are executed for proper dynamic sensing condition. First, we developed advanced smart sensors. Second, we develop new SAI and $R_{SAI}$ methods that have a sensing ability of distinguish materials. Dynamic characteristics of smart sensor are evaluated through new SAI and $R_{SAI}$ method relatively. We can use the new SAI and $R_{SAI}$ method for finding materials. Applications of this method are finding abnormal condition of object(auto-manufacturing), feeling of object(medical product), robotics, safety diagnosis of structure, etc.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.179-184
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• 2021

In our study we performed a sentiments analysis from the images. For this purpose, we used 153 images that contain: people, animals, buildings, landscapes, cakes and objects that we divided into two categories: images that suggesting a positive or a negative emotion. In order to classify the images using the two categories, we created two models. The SAI-G model was created with Google's AutoML Vision service. The SAI-C model was created on the Clarifai platform. The data were labeled in a preprocessing stage, and for the SAI-C model we created the concepts POSITIVE (POZITIV) AND NEGATIVE (NEGATIV). In order to evaluate the performances of the two models, we used a series of evaluation metrics such as: Precision, Recall, ROC (Receiver Operating Characteristic) curve, Precision-Recall curve, Confusion Matrix, Accuracy Score and Average precision. Precision and Recall for the SAI-G model is 0.875, at a confidence threshold of 0.5, while for the SAI-C model we obtained much lower scores, respectively Precision = 0.727 and Recall = 0.571 for the same confidence threshold. The results indicate a lower classification performance of the SAI-C model compared to the SAI-G model. The exception is the value of Precision for the POSITIVE concept, which is 1,000.

• Korean Journal of Forensic Psychology
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• v.11 no.1
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• pp.1-20
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• 2020

Witnesses will be exposed to a variety of misinformation after the witnessing of the event and state at the scene of the investigation after the delay period. This study was conducted to promote correct recall reporting without being affected by factors that against correct recall. Self-Administered Interview(SAI) is known to obtain eyewitness accounts quickly and accurately. Therefore, we performed a SAI to see if it reported more information than the control group that did not perform the SAI. Also, it also performed that correct information was maintained without being affected by misinformation and delay. Eighty-eight participants were asked to perform SAI or game after showing a video of mock crime. Misinformation was presented in the first or second session to see if it affected recall. An analysis of responses from the final test conducted in the second session by participants showed that groups that conducted SAI after a four-week delay reported more correct information than control groups, while there was no difference between incorrect- and confabulation information. In particular, the timing of presenting misinformation did not affect the amount of recall. This suggests that conducting the SAI immediately after witnessing the event protects correct information even after four weeks. Finally, the significance and limitations of this study, and subsequent studies were discussed.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.2
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• pp.67-74
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• 2001

A synchronized secondaty air injection method has been developed to hydrocarbon emission by injecting secondary air intermittently into exhaust port. The method has been tested in a single cylinder spark-ignition engine operating at cold-steady / cold-start conditions. Effects of air injection timing, intake pressure and engine air-fuel ratio have been investigated at cold-steady condition. Also, hydrocarbon emission and exhaust gas temperature with catalytic conberter are compared with a continuous SAI method and base condition at cold-start condition. Resules show that hydrocarbon reduction rate and exhaust gas temperature are sensitive to the timing of synchronized SAI. At cold-steady condition, HC emission is minimum at engine air-fuel ratio of 10. At cold-start condition, the accumulated hydrocarbon emission during the first 120 s decreases about 56% and 22% with the synchronized and continuous SAI, respectively, compared to that of base condition.

• Proceedings of the Technology Innovation Conference
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• 2000.06a
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• pp.211-241
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• 2000

This study explores building process of innovative capability through overseas direct investment (ODI) by taking the camera business of Samsung Aerospace Industry (SAI) as a case. SAI with less than 20 years history has pursued an aggressive ODI and developed its own camera models. It acquired Rollei in Germany and Union in Japan in 1995, for acquiring advanced technology. Several factors leading to the success of SAI's innovative cability building were taken into consideration. First, SAI effectively absorbed technological knowledge by exchanging technical personnel with foreign partners. Second, it chose right partners with the complementary knowledge required for advancing its technological capability. Third, it strengthened its competrnce to satisfy the technical standards of the partner dompanies in OEM trade relations. Fourth, it successfully formed a global marketing network in which subsidiary companies plays a central role in each region. Finally, SAI successfully addressed the factors of mutual respect between partners in order to let its partners to be confident in their ventures.

• Journal of Technology Innovation
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• v.8 no.2
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• pp.145-170
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• 2000

This study explores the building process of innovative capability through overseas direct investment (ODI) by taking the camera business of Samsung Aerospace Industry (SAI) as a case. SAI with less than 20 years history has pursued an aggressive ODI and developed its own camera models. It acquired Rollei in Germany and Union in Japan in 1995, for acquiring advanced technology. Several factors leading to the success of SAI's innovative capability building were taken into consideration. Fists, SAI effectively absorbed technological knowledge by exchanging technical personnel with foreign partners. Second, it chose right partners with the complementary knowledge required for advancing its technological capability. Third, it strengthened its competence to satisfy the technical standards of the partner companies in OEM trade relations. Fourth, ti successfully formed a global marketing network in which subsidiary companies plays a central role in each region. Finally, SAI successfully addressed the factors of mutual respect between partners in order to let its partners to be confident in their ventures.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.5
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• pp.31-36
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• 2010

SAI(Secondary Air Injection) system has been studied widely as one of the promising countermeasure for reducing HC emission at cold start. In this paper, in order to find out the optimal position of SAI, computational thermal fluid analysis on exhaust system adapted SAI system is performed using commercial 3-D CFD code, CFX. The present results showed that SAI position strongly affected the uniformity of air distribution in front of catalyst. And also through the decision process of optimal position of SAI, new index, uniformity of air distribution($U_{\phi}$) is proposed to define it quantitively. Because $U_{\phi}$ is very simple equation and similar with flow uniformity, it is very easy to figure out the physical meaning and to apply it to practices. Finally, we applied the index $U_{\phi}$ to the decision process of the optimal position of SAI, so that we could get the clear comparison results.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.1
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• pp.299-301
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• 2015

Objectives: To assess safety and efficacy of JiSaiXin (Recombinant Human Granulocyte Colony Stimulating Factor Injection manufactured in China, G-CSF) 150ug per day for three days and whether this regimen could reduce the incidence of febrile neutropenia caused by chemotherapy. Method: From July 2014 to December 2014 patients treated by chemotherapy in our hospital were randomly divided into two groups: Group A with prophylactic use of G-CSF (JiSaiXin) 24 hours after chemotherapy for consecutive 3 days; and Group B with G-CSF (JiSaiXin) after neutropenia. Routine blood tests were performed 7 days and 14 days after chemotherapy. Results: A total of 100 patients fulfilled study criteria, and the incidence of severe neutropenia (grade III/IV) and the incidence of febrile neutropenia in Group A were lower than those in Group B. Nine patients were found severe neutropenia (grade III/IV) in Group B, but one in Group A, three febrile neutropenia in Group B, but 0 in Group A. Conclusions: This study suggested that prophylactic use of G-CSF (JiSaiXin) 150ug per day 24 hours after chemotherapy for consecutive 3 days is safe and could be effective for preventing febrile neutropenia in patients with chemotherapy.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.2
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• pp.99-106
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• 2006

In this paper, the new method that estimates a sensing ability of smart sensor will be proposed. A study is estimation method that evaluates sensing ability about smart sensor respectively. According to acceleration(g) and displacement changing, we estimated sensing ability of smart sensor using SAI(Sensing Ability Index) method respectively. Smart sensors was made fer experiment. The types of smart sensor are two types(hard and soft smart sensor). Smart sensors developed for recognition of material. Experiment and analysis are executed for estimate the SAI method. In develop a smart sensor, the SAI method will be useful for finding optical design condition of smart sensor that can sense a material. And then dynamic characteristics of smart sensors(frequency changing, acceleration changing, critical point, etc.) are evaluated respectively through new method(SAI) that use the power spectrum density. Dynamic characteristic of sensor is evaluated with SAI method relatively. We can use the SAI for finding critical point of smart sensor, too.