• Steel and Composite Structures
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• v.48 no.2
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• pp.163-177
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• 2023

Complex and intricate preparation techniques, the imperative for utmost precision and sensitivity in instrumentation, premature sample failure, and fragile specimens collectively contribute to the arduous task of measuring the fracture toughness of concrete in the laboratory. The objective of this research is to introduce and refine an equation based on the gene expression programming (GEP) method to calculate the fracture toughness of reinforced concrete, thereby minimizing the need for costly and time-consuming laboratory experiments. To accomplish this, various types of reinforced concrete, each incorporating distinct ratios of fibers and additives, were subjected to diverse loading angles relative to the initial crack (α) in order to ascertain the effective fracture toughness (Keff) of 660 samples utilizing the central straight notched Brazilian disc (CSNBD) test. Within the datasets, six pivotal input factors influencing the Keff of concrete, namely sample type (ST), diameter (D), thickness (t), length (L), force (F), and α, were taken into account. The ST and α parameters represent crucial inputs in the model presented in this study, marking the first instance that their influence has been examined via the CSNBD test. Of the 660 datasets, 460 were utilized for training purposes, while 100 each were allotted for testing and validation of the model. The GEP model was fine-tuned based on the training datasets, and its efficacy was evaluated using the separate test and validation datasets. In subsequent stages, the GEP model was optimized, yielding the most robust models. Ultimately, an equation was derived by averaging the most exemplary models, providing a means to predict the Keff parameter. This averaged equation exhibited exceptional proficiency in predicting the Keff of concrete. The significance of this work lies in the possibility of obtaining the Keff parameter without investing copious amounts of time and resources into the CSNBD test, simply by inputting the relevant parameters into the equation derived for diverse samples of reinforced concrete subject to varied loading angles.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.3
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• pp.20-34
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• 2023

Single or multi-layered two-dimensional (2D) materials, with thicknesses in the order of a few nanometers, have garnered substantial attention across diverse research domains owing to their distinct properties, including electrical conductivity, flexibility, and optical transparency. These materials are frequently subjected to repetitive mechanical actions in applications like electronic skin (E-Skin) and smart textiles. Moreover, they are often exposed to external factors like temperature, humidity, and pressure, which can lead to a deterioration in component durability and lifespan. Consequently, significant research efforts are directed towards developing self-healing properties in these components. Notably, recent investigations have revealed promising outcomes in the field of self-healing composite materials, with Ti₃Ci₂Ti_x MXene being a prominent component among the myriad of available 2D materials. In this paper, we aim to introduce various synthesis methods and characteristics of Ti₃Ci₂Ti_x MXene, followed by an exploration of self-healing application technologies based on Ti₃Ci₂Ti_x MXene.

• Korean Journal of Radiology
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• v.21 no.8
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• pp.1007-1017
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• 2020

Objective: The purpose of our study was to investigate the predictive abilities of clinical and computed tomography (CT) features for outcome prediction in patients with coronavirus disease (COVID-19). Materials and Methods: The clinical and CT data of 238 patients with laboratory-confirmed COVID-19 in our two hospitals were retrospectively analyzed. One hundred sixty-six patients (103 males; age 43.8 ± 12.3 years) were allocated in the training cohort and 72 patients (38 males; age 45.1 ± 15.8 years) from another independent hospital were assigned in the validation cohort. The primary composite endpoint was admission to an intensive care unit, use of mechanical ventilation, or death. Univariate and multivariate Cox proportional hazard analyses were performed to identify independent predictors. A nomogram was constructed based on the combination of clinical and CT features, and its prognostic performance was externally tested in the validation group. The predictive value of the combined model was compared with models built on the clinical and radiological attributes alone. Results: Overall, 35 infected patients (21.1%) in the training cohort and 10 patients (13.9%) in the validation cohort experienced adverse outcomes. Underlying comorbidity (hazard ratio [HR], 3.35; 95% confidence interval [CI], 1.67-6.71; p < 0.001), lymphocyte count (HR, 0.12; 95% CI, 0.04-0.38; p < 0.001) and crazy-paving sign (HR, 2.15; 95% CI, 1.03-4.48; p = 0.042) were the independent factors. The nomogram displayed a concordance index (C-index) of 0.82 (95% CI, 0.76-0.88), and its prognostic value was confirmed in the validation cohort with a C-index of 0.89 (95% CI, 0.82-0.96). The combined model provided the best performance over the clinical or radiological model (p < 0.050). Conclusion: Underlying comorbidity, lymphocyte count and crazy-paving sign were independent predictors of adverse outcomes. The prognostic nomogram based on the combination of clinical and CT features could be a useful tool for predicting adverse outcomes of patients with COVID-19.

• Steel and Composite Structures
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• v.50 no.6
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• pp.705-720
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• 2024

Analyzing the collapse behavior of thin-walled steel structures holds significant importance in ensuring their safety and longevity. Geometric imperfections present on the surface of metal materials can diminish both the durability and mechanical integrity of steel shells. These imperfections, encompassing local geometric irregularities and deformations such as holes, cavities, notches, and cracks localized in specific regions of the shell surface, play a pivotal role in the assessment. They can induce stress concentration within the structure, thereby influencing its susceptibility to buckling. The intricate relationship between the buckling behavior of these structures and such imperfections is multifaceted, contingent upon a variety of factors. The buckling analysis of thin-walled steel shell structures, similar to other steel structures, commonly involves the determination of crucial material properties, including elastic modulus, shear modulus, tensile strength, and fracture toughness. An established method involves the emulation of distributed geometric imperfections, utilizing real test specimen data as a basis. This approach allows for the accurate representation and assessment of the diversity and distribution of imperfections encountered in real-world scenarios. Utilizing defect data obtained from actual test samples enhances the model's realism and applicability. The sizes and configurations of these defects are employed as inputs in the modeling process, aiding in the prediction of structural behavior. It's worth noting that there is a dearth of experimental studies addressing the influence of geometric defects on the buckling behavior of cylindrical steel shells. In this particular study, samples featuring geometric imperfections were subjected to experimental buckling tests. These same samples were also modeled using Finite Element Analysis (FEM), with results corroborating the experimental findings. Furthermore, the initial geometrical imperfections were measured using digital image correlation (DIC) techniques. In this way, the response of the test specimens can be estimated accurately by applying the initial imperfections to FE models. After validation of the test results with FEA, a numerical parametric study was conducted to develop more generalized design recommendations for the stainless-steel shell structures with the initial geometric imperfection. While the load-carrying capacity of samples with perfect surfaces was up to 140 kN, the load-carrying capacity of samples with 4 mm defects was around 130 kN. Likewise, while the load carrying capacity of samples with 10 mm defects was around 125 kN, the load carrying capacity of samples with 14 mm defects was measured around 120 kN.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1031-1031
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• 2001

The mammary gland is made up of remarkably sensitive tissue, which has the capability of producing a large volume of secretion, milk, under normal or healthy conditions. When bacteria enter the gland and establish an infection (mastitis), inflammation is initiated accompanied by an influx of white cells from the blood stream, by altered secretory function, and changes in the volume and composition of secretion. Cell numbers in milk are closely associated with inflammation and udder health. These somatic cell counts (SCC) are accepted as the international standard measurement of milk quality in dairy and for mastitis diagnosis. NIR Spectra of unhomogenized composite milk samples from 14 cows (healthy and mastitic), 7days after parturition and during the next 30 days of lactation were measured. Different multivariate analysis techniques were used to diagnose the disease at very early stage and determine how the spectral properties of milk vary with its composition and animal health. PLS model for prediction of somatic cell count (SCC) based on NIR milk spectra was made. The best accuracy of determination for the 1100-2500nm range was found using smoothed absorbance data and 10 PLS factors. The standard error of prediction for independent validation set of samples was 0.382, correlation coefficient 0.854 and the variation coefficient 7.63%. It has been found that SCC determination by NIR milk spectra was indirect and based on the related changes in milk composition. From the spectral changes, we learned that when mastitis occurred, the most significant factors that simultaneously influenced milk spectra were alteration of milk proteins and changes in ionic concentration of milk. It was consistent with the results we obtained further when applied 2DCOS. Two-dimensional correlation analysis of NIR milk spectra was done to assess the changes in milk composition, which occur when somatic cell count (SCC) levels vary. The synchronous correlation map revealed that when SCC increases, protein levels increase while water and lactose levels decrease. Results from the analysis of the asynchronous plot indicated that changes in water and fat absorptions occur before other milk components. In addition, the technique was used to assess the changes in milk during a period when SCC levels do not vary appreciably. Results indicated that milk components are in equilibrium and no appreciable change in a given component was seen with respect to another. This was found in both healthy and mastitic animals. However, milk components were found to vary with SCC content regardless of the range considered. This important finding demonstrates that 2-D correlation analysis may be used to track even subtle changes in milk composition in individual cows. To find out the right threshold for SCC when used for mastitis diagnosis at cow level, classification of milk samples was performed using soft independent modeling of class analogy (SIMCA) and different spectral data pretreatment. Two levels of SCC - 200 000 cells/$m\ell$ and 300 000 cells/$m\ell$, respectively, were set up and compared as thresholds to discriminate between healthy and mastitic cows. The best detection accuracy was found with 200 000 cells/$m\ell$ as threshold for mastitis and smoothed absorbance data: - 98% of the milk samples in the calibration set and 87% of the samples in the independent test set were correctly classified. When the spectral information was studied it was found that the successful mastitis diagnosis was based on reviling the spectral changes related to the corresponding changes in milk composition. NIRS combined with different ways of spectral data ruining can provide faster and nondestructive alternative to current methods for mastitis diagnosis and a new inside into disease understanding at molecular level.

• Journal of Korea Technology Innovation Society
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• v.10 no.2
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• pp.284-309
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• 2007

Technology transfer (TT) consortium is an affiliation of two or more public research institutions (PRIs) that participate in a common technology transfer activity or pool their resources together, with the objective of facilitating technology transfer. Based on empirical analysis of five regional TT consortia (2002-2006) operating in Korea, this paper suggests their effectiveness by employing a TT performance index (TTPI) and identifies possible characteristics involved, such as motivations, facilitators, barriers, and challenges. TTPI devised in the paper is a new composite TT performance index to measure how much the TT performance of a PH changed in a designated year compared to a base year. All the performance indicators of TTPI are well-structured based on the unique TT process that is prevalent in Korea. Further, TTPI can bring different size and focus of PRIs to the same scale for comparison by double-normalizing. The paper tests the effectiveness of TT consortium for the escalation of TT performances in member PRIs by highlighting the differences of TTPI's between 2005 and 2001. As a result, the paper found that the escalation of TTPI for member PRIs was greater than that for non-member PRIs. As for the characteristics of TT consortia, their respective factors obtained by TT expert survey were computed with proportion tests of differences (Z tests) to compare two perspectives between intramural and extramural groups. One of key findings is that there is general homogeneity in stakeholder perspectives regarding motivations, facilitators, barriers, and challenges. Some notable responses are as follow; the most probable motivation to join TT consortium is to share or exchange TT competences for enhanced performance. Second, the most probable facilitator is professional capability of consortium-hired personnel. Third, the foremost probable barriers to effective TT consortium are frequent change of consortium director and passive participation of member PRIs. Lastly, both publicizing TT consortia and developing performance metrics are the most important for the improvement of TT consortia. The understanding of the characteristics of TT consortia increases the likelihood of accelerated success, because TT consortia path from formation to termination encompasses many concepts, processes, principles, and factors. Finally, an analysis of the survey data combined with expert interview and observation data led the authors to derive five conditions as being critical to viable TT consortia in Korea at early stage of technology transfer systems. These conditions include policy infrastructure, proactive participation, excellent professionals, personal motivation, and teaming mechanisms. It is expected that the Korean evidence is a starting point to develop and refine the theory of TT consortia and for additional studies in other countries.

• KSBB Journal
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• v.24 no.1
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• pp.30-40
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• 2009

Statistical optimization of the production medium was carried out in order to find an optimal medium composition in itaconic acid fermentation process. Itaconic acid utilized in the manufacture of various synthetic resins is a dicarboxylic acid biosynthesized by fungal cells of Aspergillus terreus in a branch of the TCA cycle via decarboxylation of cis-aconitate. Through OFAT (one factor at a time) experiments, six components (glucose, fructose, sucrose, soluble starch, soybean meal and cottonseed flour) were found to have significant effects on itaconic production among various carbon- and nitrogen-sources. Hence, using these six factors, interactive effects were investigated via fractional factorial design, showing that the initial concentrations of sucrose and cottonseed flour should be high for enhanced production of itaconic acid. Furthermore, through full factorial design (FFD) experiments, negative effects of $KH_2PO_4$ and $MgSO_4$ on itaconic acid biosynthesis were demonstrated, when excess amounts of the each component were initially added. Based on the FFD analysis, further statistical experiments were conducted along the steepest ascent path, followed by response surface method (RSM) in order to obtain optimal concentrations of the constituent nutrients. As a result, optimized concentrations of sucrose and cottonseed flour were found to be 90.4g/L and 53.8g/L respectively, with the corresponding production level of itaconic acid to be 4.36 g/L (about 7 fold higher productivity as compared to the previous production medium). From these experimental results, it was assumed that optimum ratio of the constituent carbon (sucrose) and nitrogen (cottonseed flour) sources was one of the most important factors for the enhanced production of itaconic acid.

• Journal of agricultural medicine and community health
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• v.36 no.2
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• pp.101-112
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• 2011

Objectives: The aim of this study is to determine arterial stiffness levels as measured by brachial-ankle pulse wave velocity (baPWV) and to identify the association between arterial stiffness and inflammatory markers, in healthy adults over 50 years old. Methods: The study population consisted of 4617 persons over the age of 50 years who participated in the baseline survey of the Dong-gu Study, which was conducted in 2007 and 2008. Arterial stiffness was measured using baPWV. A multiple regression analysis was performed to assess the relationship between conventional cardiovascular risk factors and inflammatory markers, including white blood cell (WBC) counts, high-sensitive C-reactive protein (hs-CRP), and gamma glutamyltransferase (GGT). Results: After adjustment for conventional cardiovascular risk factors including sex, age, smoking status, body mass index, systolic blood pressure, fasting glucose, hypertension or diabetic medication, total cholesterol, triglycerides, uric acid, and alanine aminotransferase, baPWV was significantly associated with WBC counts (${\beta}$=0.158, p<0.0001), hs-CRP (${\beta}$=0.244, p=0.026), and GGT (${\beta}$=0.003, p<0.0001). Conclusion: This study shows that arterial stiffness correlates with inflammatory markers. Arterial stiffness may be used as a composite risk factor to identify persons with higher risk for cardiovascular disease. Additionally, arterial stiffness may be a marker for future cardiovascular disease and a target for prevention.

• Asia Marketing Journal
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• v.14 no.1
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• pp.25-51
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• 2012

Researches about the relationship between SST(Self Service Technology) and TRI(Technology Readiness Index) have been carried out after TRI was developed by Parasuraman and his colleagues(2000). We hypothesize Consumer Readiness can also influence consumer's motivation, attitude, and intent to use SST. Currently, there has been no research on this subject. In this study, we investigated the relationship between TR, Consumer Readiness and SST Core Attitudinal Model which Dabholkar & Bagozzi(1994) proposed. The researchers also investigated moderating effects of consumer traits and situational factors to verify the acceptance of such forms of service delivery by all kinds of consumers and under different situational contexts. Self consciousness, the need for interaction with an employee, and the technology anxiety were used as consumer trait variables. Perceived waiting time and perceived crowding were used as situational variables. 380 questionnaires were distributed to a sample group of people in their 20's and 30's, and the data were analyzed with structural equation model using AMOS 18.0 program. All of Cronbach's alpha values representing reliabilities were satisfactory. The values of Composite Reliability(CR) and Average Variance Extracted(AVE) also showed the above criteria, thus providing evidence of convergent validity. To confirm discriminant validity among the constructs, confirmatory factor analysis and correlations among all the variables were examined. The results were satisfactory. The results of this study are summarized as follows. 1. Optimism and innovativeness of TR partially influenced the motivation to use SST. People who tend to be optimistic use SST because of ease of use and fun. The innovative however, usually use SST due to its performance. However, consumer readiness of role clarity, ability and self-efficacy influence all the components of motivation to use SST, ease of use, performance and fun. The relative effect of consumer readiness on the motivation to use SST was much stronger and more significant than that of TR. No other previous studies have examined the effects of Consumer Readiness on SST usage motivation, attitude and intention. It is academically meaningful that the researchers verified that Consumer Readiness is the important precedent construct influencing the self service technology core Attitudinal Model. Our findings suggest that marketers should consider fun and ease of use attributes to promote the use of self service technology. In addition, the SST usage frequency will rise rapidly when role clarity, ability, and self-efficacy which anybody can easily handle SST is assured. If the SST usage rate is increased, waiting times for customers could be decreased. Shorter waiting time could lead to higher customer satisfaction. It may also result in making a long-term profit owing to the reduced number of employees. Thus, presentation of using SST by employees or videos showing how to use it will promote the usage attitude and intent. 2. In SST core attitudinal model, performance and fun factors among SST usage motivation affected attitudes of using SST. The attitude of using SST highly influenced intent to use SST. This result is consistent with previous researches that dealt with the relationship between motivation, attitude and intention. Expectation of using SST could result in good performance just like the effect of ordering menu to service employees and to have fun since fun during its use could promote more SST usage rate. 3. In the relationship among motivation, attitude and intent in SST core attitudinal model, the moderating effect of consumer traits(self-consciousness, need for interaction with service employees and technology anxiety) and situational factors(perceived crowding and perceived waiting time) were tested. The results also supported the hypothesized moderating effects except perceived crowding. The highly self-conscious tended to form attitudes to use SST because of its fun compared to those who were less self-conscious because of its performance. People who had a high need for interaction with service employees tended to use SST for its performance. This result indicates that if ordering results are assured, SST is easily accessible to even consumers who have a high need for interaction with a service employee. When SST is easy to use, attitudes strengthen intent among people who had a high level of anxiety of technology. People who had low technology anxiety formed attitudes to use SST because of its performance. Service firms must ensure their self service technology is designed to be easy to use for those who have a high level of technology anxiety. Shorter perceived waiting times strengthened the attitude to use self service technology because of its fun. If the fun aspect is assured, people willing to use self service technology even perceive waiting time to be shorter than it actually is. Greater perceived waiting times form higher level of intent to use self service technology than those of shorter perceived waiting times. This implies that people view self service technology as a faster alternative to ordering service employees. The fun aspect of self service technology will attract a higher rate of usage for self service technology. 4. It has been proven that ease of use, performance and fun aspects are very important factors in motivation to form attitudes and intent to use self service technology regardless of the amount of perceived waiting time, self-consciousness, need for interaction with service employees, and technology anxiety. Service firms must consider these motivation aspects(ease of use, performance and fun)strongly in their promotion to use self service technology. Ease of use, assuring absolute performance compared to interaction with service employees', and adding a fun aspect will positively strengthen consumers' attitudes and intent to use self service technology. Summarizing the moderating effects, fun is the most valuable factor triggering SST usage attitude and intention. Therefore, designing self service technology to be fun will be the key to its success. This study focused on the touch screen self service technology in fast food restaurant. Although it has its limits due to the fact that it is hard to generalize the results to any other self service technology, the conceptual framework of this study can be applied to future research of any other service site.

• Journal of Distribution Research
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• v.17 no.3
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• pp.25-57
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• 2012

This study identified motives for writing apparel product reviews in online stores, and determined what motives increase the behavior of writing reviews. It also classified store customers based on the type of writing motives, and clarified the characteristics of internet purchase behavior and of a demographic profile. Data were collected from 252 females aged 20s' and 30s' who have experience of reading and writing reviews on online shopping. The five types of writing motives were altruistic information sharing, remedying of a grievance and vengeance, economic incentives, helping new product development, and the expression of satisfaction feelings. Among five motives, altruistic information sharing, economic incentives, and helping new product development stimulate writing reviews. Store customers who write reviews were classified into three groups based on their writing motive types: Other consumer advocates(29.8%), self-interested shoppers(40.5%) and shoppers with moderate motives(29.8%). There were significant differences among three groups in writing behavior (the frequency of writing reviews, writing intent of reviews, duration of writing reviews, and frequency of online shopping) and age. Based on results, managerial implications were suggested. Long Abstract : The purpose of present study is to identify the types of writing motives on online shopping, and to clarify the motives affecting the behavior of writing reviews. This study also classifies online shoppers based on the motive types, and identifies the characteristics of the classified groups in terms of writing behavior, frequency of online shopping, and demographics. Use and Gratification Theory was adopted in this study. Qualitative research (focus group interview) and quantitative research were used. Korean women(20 to 39 years old) who reported experience with purchasing clothing online, and reading and writing reviews were selected as samples(n=252). Most of the respondents were relatively young (20-34yrs., 86.1%,), single (61.1%), employed(61.1%) and residents living in big cities(50.9%). About 69.8% of respondents read and 40.5% write apparel reviews frequently or very frequently. 24.6% of the respondents indicated an "average" in their writing frequency. Based on the qualitative result of focus group interviews and previous studies on motives for online community activities, measurement items of motives for writing after-purchase reviews were developed. All items were used a five-point Likert scale with endpoints 1 (strongly disagree) and 5 (strongly agree). The degree of writing behavior was measured by items concerning experience of writing reviews, frequency of writing reviews, amount of writing reviews, and intention of writing reviews. A five-point scale(strongly disagree-strongly agree) was employed. SPSS 18.0 was used for exploratory factor analysis, K-means cluster analysis, one-way ANOVA(Scheffe test) and ${\chi}^2$-test. Confirmatory factor analysis and path model analysis were conducted by AMOS 18.0. By conducting principal components factor analysis (varimax rotation, extracting factors with eigenvalues above 1.0) on the measurement items, five factors were identified: Altruistic information sharing, remedying of a grievance and vengeance, economic incentives, helping new product development, and expression of satisfaction feelings(see Table 1). The measurement model including these final items was analyzed by confirmatory factor analysis. The measurement model had good fit indices(GFI=.918, AGFI=.884, RMR=.070, RMSEA=.054, TLI=.941) except for the probability value associated with the ${\chi}^2$ test(${\chi}^2$=189.078, df=109, p=.00). Convergent validities of all variables were confirmed using composite reliability. All SMC values were found to be lower than AVEs confirming discriminant validity. The path model's goodness-of-fit was greater than the recommended limits based on several indices(GFI=.905, AGFI=.872, RMR=.070, RMSEA=.052, TLI=.935; ${\chi}^2$=260.433, df=155, p=.00). Table 2 shows that motives of altruistic information sharing, economic incentives and helping new product development significantly increased the degree of writing product reviews of online shopping. In particular, the effect of altruistic information sharing and pursuit of economic incentives on the behavior of writing reviews were larger than the effect of helping new product development. As shown in table 3, online store shoppers were classified into three groups: Other consumer advocates (29.8%), self-interested shoppers (40.5%), and moderate shoppers (29.8%). There were significant differences among the three groups in the degree of writing reviews (experience of writing reviews, frequency of writing reviews, amount of writing reviews, intention of writing reviews, and duration of writing reviews, frequency of online shopping) and age. For five aspects of writing behavior, the group of other consumer advocates who is mainly comprised of 20s had higher scores than the other two groups. There were not any significant differences between self-interested group and moderate group regarding writing behavior and demographics.