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The Preparation of Fermented Milk from Milk and Fruit Juices (우유와 과즙을 이용한 발효유의 제조)

  • Ko, Young-Tae;Kang, Jung-Hwa
    • Korean Journal of Food Science and Technology
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    • v.29 no.6
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    • pp.1241-1247
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    • 1997
  • Gel-type fermented milk was prepared from milk or mixture of milk and apple juice/grape juice. Acid production (pH change) and growth of Lactobacillus acidophilus (KCTC 2182) were studied. The effects of juice addition on sensory property of fermented milk were also studied. The pH value of samples containing mixture of milk and apple juice/grape juice (25 mL : 25 mL to 5 mL : 45 mL) was lower than that of milk sample. However, number of viable cells of L. acidophilus at 21 hr in milk and samples containing juices was similar. During lactic fermentation for 24 hr, pH of all samples dropped significantly between 6 hr and 21 hr. pH values of mixture of milk and juices were lower than that of milk sample. Growth curve showed that lag phase continued to approximately 3 hr and log phase continued to approximately 15 hr in all samples. Number of viable cells in all samples was similar Sensory evaluation showed that overall acceptability of fermented milk prepared from apple juice/grape juice and milk (15 mL : 35 mL or 5 mL : 45 mL) was better than that of reference sample. The optimum ratio of mixture of juice and milk was 15 mL : 35 mL. The score values of sensory test of fermented milk prepared from mixture of grape juice and milk were slightly higher than those of mixture of apple juice and milk.

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Risk factors affecting the difficulty of fiberoptic nasotracheal intubation

  • Rhee, Seung-Hyun;Yun, Hye Joo;Kim, Jieun;Karm, Myong-Hwan;Ryoo, Seung-Hwa;Kim, Hyun Jeong;Seo, Kwang-Suk
    • Journal of Dental Anesthesia and Pain Medicine
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    • v.20 no.5
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    • pp.293-301
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    • 2020
  • Background: The success rate of intubation under direct laryngoscopy is greatly influenced by laryngoscopic grade using the Cormack-Lehane classification. However, it is not known whether grade under direct laryngoscopy can also affects the success rate of nasotracheal intubation using a fiberoptic bronchoscpe, so this study investigated the same. In addition, we investigated other factors that influence the success rate of fiberoptic nasotracheal intubation (FNI). Methods: FNI was performed by 18 anesthesiology residents under general anesthesia in patients over 15 years of age who underwent elective oral and maxillofacial operations. In all patients, the Mallampati grade was measured. Laryngeal view grade under direct laryngoscopy, and the degree of secretion and bleeding in the oral cavity was measured and divided into 3 grades. The time required for successful FNI was measured. If the intubation time was > 5 minutes, it was evaluated as a failure and the airway was managed by another method. The failure rate was evaluated using appropriate statistical method. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were also measured. Results: A total of 650 patients were included in the study, and the failure rate of FNI was 4.5%. The patient's sex, age, height, weight, Mallampati, and laryngoscopic view grade did not affect the success rate of FNI (P > 0.05). BMI, the number of FNI performed by residents (P = 0.03), secretion (P < 0.001), and bleeding (P < 0.001) grades influenced the success rate. The AUCs of bleeding and secretion were 0.864 and 0.798, respectively, but the AUC of BMI, the number of FNI performed by residents, Mallampati, and laryngoscopic view grade were 0.527, 0.616, 0.614, and 0.544, respectively. Conclusion: Unlike in intubation under direct laryngoscopy, in the case of FNI, oral secretion and nasal bleeding had a significant effect on FNI difficulty than Mallampati grade or Laryngeal view grade.

Analysis of Hematological Factor to Predict Plaque of the Carotid Artery in Ultrasound Images (경동맥초음파에서 죽상경화반을 예측하는 혈액학적 수치의 분석)

  • Yang, Sung Hee;Kang, Se Sik;Lee, Jinsoo
    • Journal of the Korean Society of Radiology
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    • v.10 no.3
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    • pp.187-193
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    • 2016
  • In this study, we performed the carotid artery ultrasound targeting 140 subjects who have conducted to evaluate the changes in intima-media thickness(IMT) and plaque correlated with the presence or absence of a hematological test of the carotid artery. Considering that the IMT thickness more than 1mm is abnormal based on the carotid artery ultrasound to assess the presence or absence of plaque, and examined the correlation by classifying the blood lipid value and the fasting blood glucose level through the serum test. Consequently, the fasting blood glucose level is being analyzed as independent predictors of causing dental plaque(p=0.033), cut off value was determined as 126 mg/dL(sensitivity 56.25%, specificity 68.38%) in ROC curve analysis. Furthermore, the odds ratio appeared 1.01 times the value in the Logistic regression. Therefore, it seemed that the necessity to prospective studies in a number of subjects are considered, and also taking into account a number of blood test values along with the sonography of the carotid artery as a valuable part for effective primary prevention and follow-up observation of the cardiac and brain vascular disease is highly recommended.

Electrical Characteristics of PV Modules with Odd Strings by Arrangement on Bypass Diode (홀수스트링 PV모듈의 바이패스 다이오드 배치에 의한 전기적 특성)

  • Shin, Woo-Gyun;Go, Seok-Hwan;Ju, Young-Chul;Song, Hyung-Jun;Kang, Gi-Hwan
    • Journal of the Korean Solar Energy Society
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    • v.37 no.4
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    • pp.1-11
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    • 2017
  • Most PV modules are fabricated by 6 cell-strings with solar cells connected in series. Moreover, bypass diodes are generally installed every 2 cell-strings to prevent PV modules from a damage induced by current mismatch or partial shading. But, in the case of special purpose PV module, like as BIPV (Building Integrated Photovoltaic), the number of cell-strings per module varies according to its size. Differ from a module employing even cell-strings, the configuration of bypass diode should be optimized in the PV module with odd strings because of oppositely facing electrodes. Hence, in this study, electrical characteristics of special purposed PV module with odd string was empirically and theoretically studied depending on arrangement of bypass diode. Here, we assumed that PV module has 3 strings and the number of bypass diodes in the system varies from 2 to 6. In case of 2 bypass diodes, shading on a center string increases short circuit current of the module, because of a parallel circuit induced by 2 bypass diodes connected to center string. Also, the loss is larger, as the shading area in the center string is enlarged. Thus, maximum power of the PV module with 2 bypass diode decreases by up to 59 (%) when shading area varies from 50 to 90 (%). On the other hand, In case of 3 and 6 bypass diodes, the maximum power reduction was within about 3 (W), even the shading area changes from 50 to 90 (%). As a result, It is an alternative to arrange the bypass diode by each string or one bypass diode in the PV module in order to completely bypass current in case of shading, when PV module with odd string are fabricated.

Improvement of LMS Algorithm Convergence Speed with Updating Adaptive Weight in Data-Recycling Scheme (데이터-재순환 구조에서 적응 가중치 갱신을 통한 LMS 알고리즘 수렴 속 도 개선)

  • Kim, Gwang-Jun;Jang, Hyok;Suk, Kyung-Hyu;Na, Sang-Dong
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.9 no.4
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    • pp.11-22
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    • 1999
  • Least-mean-square(LMS) adaptive filters have proven to be extremely useful in a number of signal processing tasks. However LMS adaptive filter suffer from a slow rate of convergence for a given steady-state mean square error as compared to the behavior of recursive least squares adaptive filter. In this paper an efficient signal interference control technique is introduced to improve the convergence speed of LMS algorithm with tap weighted vectors updating which were controled by reusing data which was abandoned data in the Adaptive transversal filter in the scheme with data recycling buffers. The computer simulation show that the character of convergence and the value of MSE of proposed algorithm are faster and lower than the existing LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of LMS algorithm.

A Scalable Montgomery Modular Multiplier (확장 가능형 몽고메리 모듈러 곱셈기)

  • Choi, Jun-Baek;Shin, Kyung-Wook
    • Journal of IKEEE
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    • v.25 no.4
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    • pp.625-633
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    • 2021
  • This paper describes a scalable architecture for flexible hardware implementation of Montgomery modular multiplication. Our scalable modular multiplier architecture, which is based on a one-dimensional array of processing elements (PEs), performs word parallel operation and allows us to adjust computational performance and hardware complexity depending on the number of PEs used, NPE. Based on the proposed architecture, we designed a scalable Montgomery modular multiplier (sMM) core supporting eight field sizes defined in SEC2. Synthesized with 180-nm CMOS cell library, our sMM core was implemented with 38,317 gate equivalents (GEs) and 139,390 GEs for NPE=1 and NPE=8, respectively. When operating with a 100 MHz clock, it was evaluated that 256-bit modular multiplications of 0.57 million times/sec for NPE=1 and 3.5 million times/sec for NPE=8 can be computed. Our sMM core has the advantage of enabling an optimized implementation by determining the number of PEs to be used in consideration of computational performance and hardware resources required in application fields, and it can be used as an IP (intellectual property) in scalable hardware design of elliptic curve cryptography (ECC).

Analysis Study on the Detection and Classification of COVID-19 in Chest X-ray Images using Artificial Intelligence (인공지능을 활용한 흉부 엑스선 영상의 코로나19 검출 및 분류에 대한 분석 연구)

  • Yoon, Myeong-Seong;Kwon, Chae-Rim;Kim, Sung-Min;Kim, Su-In;Jo, Sung-Jun;Choi, Yu-Chan;Kim, Sang-Hyun
    • Journal of the Korean Society of Radiology
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    • v.16 no.5
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    • pp.661-672
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    • 2022
  • After the outbreak of the SARS-CoV2 virus that causes COVID-19, it spreads around the world with the number of infections and deaths rising rapidly caused a shortage of medical resources. As a way to solve this problem, chest X-ray diagnosis using Artificial Intelligence(AI) received attention as a primary diagnostic method. The purpose of this study is to comprehensively analyze the detection of COVID-19 via AI. To achieve this purpose, 292 studies were collected through a series of Classification methods. Based on these data, performance measurement information including Accuracy, Precision, Area Under Cover(AUC), Sensitivity, Specificity, F1-score, Recall, K-fold, Architecture and Class were analyzed. As a result, the average Accuracy, Precision, AUC, Sensitivity and Specificity were achieved as 95.2%, 94.81%, 94.01%, 93.5%, and 93.92%, respectively. Although the performance measurement information on a year-on-year basis gradually increased, furthermore, we conducted a study on the rate of change according to the number of Class and image data, the ratio of use of Architecture and about the K-fold. Currently, diagnosis of COVID-19 using AI has several problems to be used independently, however, it is expected that it will be sufficient to be used as a doctor's assistant.

Evaluation of Flood Regulation Service of Urban Ecosystem Using InVEST mode (InVEST 모형을 이용한 도시 생태계의 홍수 조절서비스 평가)

  • Lee, Tae-ho;Cheon, Gum-sung;Kwon, Hyuk-soo
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.25 no.6
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    • pp.51-64
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    • 2022
  • Along with the urbanization, the risk of urban flooding due to climate change is increasing. Flood regulation, one of the ecosystem services, is implemented in the different level of function of flood risk mitigation by the type of ecosystem such as forests, arable land, wetlands etc. Land use changes due to development pressures have become an important factor in increasing the vulnerability by flash flood. This study has conducted evaluating the urban flood regulation service using InVEST UFRM(Urban Flood Risk Model). As a result of the simulation, the potential water retention by ecosystem type in the event of a flash flood according to RCP 4.5(10 year frequency) scenario was 1,569,611 tons in urbanized/dried areas, 907,706 tons in agricultural areas, 1,496,105 tons in forested areas, 831,705 tons in grasslands, 1,021,742 tons in wetlands, and 206,709 tons in bare areas, the water bodies was estimated to be 38,087 tons. In the case of more severe 100-year rainfall, 1,808,376 tons in urbanized/dried areas, 1,172,505 tons in agricultural areas, 2,076,019 tons in forests, 1,021,742 tons in grasslands, 47,603 tons in wetlands, 238,363 tons in bare lands, and 52,985 tons in water bodies. The potential economic damage from flood runoff(100 years frequency) is 122,512,524 thousand won in residential areas, 512,382,410 thousand won in commercial areas, 50,414,646 thousand won in industrial areas, 2,927,508 thousand won in Infrastructure(road), 8,907 thousand won in agriculture, Total of assuming a runoff of 50 mm(100 year frequency) was estimated at 688,245,997 thousand won. In a conclusion. these results provided an overview of ecosystem functions and services in terms of flood control, and indirectly demonstrated the possibility of using the model as a tool for policy decision-making. Nevertheless, in future research, related issues such as application of models according to various spatial scales, verification of difference in result values due to differences in spatial resolution, improvement of CN(Curved Number) suitable for the research site conditions based on actual data, and development of flood damage factors suitable for domestic condition for the calculation of economic loss.

Applying the Multiple Cue Probability Learning to Consumer Learning

  • Ahn, Sowon;Kim, Juyoung;Ha, Young-Won
    • Asia Marketing Journal
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    • v.15 no.3
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    • pp.159-172
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    • 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.

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Structural features and Diffusion Patterns of Gartner Hype Cycle for Artificial Intelligence using Social Network analysis (인공지능 기술에 관한 가트너 하이프사이클의 네트워크 집단구조 특성 및 확산패턴에 관한 연구)

  • Shin, Sunah;Kang, Juyoung
    • Journal of Intelligence and Information Systems
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    • v.28 no.1
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    • pp.107-129
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    • 2022
  • It is important to preempt new technology because the technology competition is getting much tougher. Stakeholders conduct exploration activities continuously for new technology preoccupancy at the right time. Gartner's Hype Cycle has significant implications for stakeholders. The Hype Cycle is a expectation graph for new technologies which is combining the technology life cycle (S-curve) with the Hype Level. Stakeholders such as R&D investor, CTO(Chef of Technology Officer) and technical personnel are very interested in Gartner's Hype Cycle for new technologies. Because high expectation for new technologies can bring opportunities to maintain investment by securing the legitimacy of R&D investment. However, contrary to the high interest of the industry, the preceding researches faced with limitations aspect of empirical method and source data(news, academic papers, search traffic, patent etc.). In this study, we focused on two research questions. The first research question was 'Is there a difference in the characteristics of the network structure at each stage of the hype cycle?'. To confirm the first research question, the structural characteristics of each stage were confirmed through the component cohesion size. The second research question is 'Is there a pattern of diffusion at each stage of the hype cycle?'. This research question was to be solved through centralization index and network density. The centralization index is a concept of variance, and a higher centralization index means that a small number of nodes are centered in the network. Concentration of a small number of nodes means a star network structure. In the network structure, the star network structure is a centralized structure and shows better diffusion performance than a decentralized network (circle structure). Because the nodes which are the center of information transfer can judge useful information and deliver it to other nodes the fastest. So we confirmed the out-degree centralization index and in-degree centralization index for each stage. For this purpose, we confirmed the structural features of the community and the expectation diffusion patterns using Social Network Serice(SNS) data in 'Gartner Hype Cycle for Artificial Intelligence, 2021'. Twitter data for 30 technologies (excluding four technologies) listed in 'Gartner Hype Cycle for Artificial Intelligence, 2021' were analyzed. Analysis was performed using R program (4.1.1 ver) and Cyram Netminer. From October 31, 2021 to November 9, 2021, 6,766 tweets were searched through the Twitter API, and converting the relationship user's tweet(Source) and user's retweets (Target). As a result, 4,124 edgelists were analyzed. As a reult of the study, we confirmed the structural features and diffusion patterns through analyze the component cohesion size and degree centralization and density. Through this study, we confirmed that the groups of each stage increased number of components as time passed and the density decreased. Also 'Innovation Trigger' which is a group interested in new technologies as a early adopter in the innovation diffusion theory had high out-degree centralization index and the others had higher in-degree centralization index than out-degree. It can be inferred that 'Innovation Trigger' group has the biggest influence, and the diffusion will gradually slow down from the subsequent groups. In this study, network analysis was conducted using social network service data unlike methods of the precedent researches. This is significant in that it provided an idea to expand the method of analysis when analyzing Gartner's hype cycle in the future. In addition, the fact that the innovation diffusion theory was applied to the Gartner's hype cycle's stage in artificial intelligence can be evaluated positively because the Gartner hype cycle has been repeatedly discussed as a theoretical weakness. Also it is expected that this study will provide a new perspective on decision-making on technology investment to stakeholdes.