• Title/Summary/Keyword: Manufacturing Analysis

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Enzymatic Method for Measuring ATP Related Compounds in Fish Sauces (효소법에 의한 액젓중의 ATP 관련물질 측정)

  • CHO Young Je;IM Yeong Sun;KIM Sang Moo;CHOI Young Joon
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.32 no.4
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    • pp.385-390
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    • 1999
  • HPLC method usually has been used for the determination of ATP and its related compounds in fish muscle and fish sauce. But, total amount of ATP related compounds in fish sauce is determined less than that of fish muscle. In order to establish the extract analysis method for ATP related compounds in fish sauce, a new enzymatic method was developed and compared with existing HPLC method. Fish sauce was extracted with chilled perchloric acid and neutralized to Ph 7.0 with potassium hydroxide solution, the extract was used as sample analyzed by HPLC as usual. On the other hand, for sample analyzed by enzymatic method, 1 ml extract solution was pipetted into test tube. To the tube, 0.5ml of mixed suspension adenosinedeaminase (4U), nucleosidephosphorylase (0.02U) and xanthineoxidase (0.03U) suspended in 2.0ml of 1/15 M sodium phosphate buffer solution pH 7.6 and 1.5ml deionized water wereadded for the decomposition of IMP, HxR and Hx to uric acid at $37^{\circ}C$ for 40 minutes. Total uric acid was determined by measuring optical density at 290nm. In HPLC method, salt decreased the total amount of ATP related compounds by $13.6\~16.2\%$ at $2.5\%$ concentration, but no effect in enzymatic method. IMP, HxR and Hx were detected at 254nm, while uric acid at only 290nm. The ratio of the total amount of ATP related compounds by HPLC method was about $45\%$ of that by enzymatic method in fish sauce. Form these results, enzymatic method is more accurate and simple than HPLC method for analysis of ATP related compounds in fish sauce.

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Study on the Casting Technology and Restoration of "Sangpyong Tongbo" (상평통보 주조와 복원기술연구)

  • Yun, Yong-hyun;Cho, Nam-chul;Jeong, Yeong-sang;Lim, In-ho
    • Korean Journal of Heritage: History & Science
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    • v.47 no.4
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    • pp.224-243
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    • 2014
  • This study examined the materials and casting technology(cast, alloy, etc.) used in the manufacturing of bronze artifacts based on old literature such as Yongjae Chonghwa, Cheongong Geamul, and The Korea Review. In the casting experiment for restoration of Sangpyong Tongbo, a bronze and brass mother coin mold was made using the sand mold casting method described in The Korea Review. The cast was comprised of the original mold plate frame, wooden frame, and molding sand. Depending on the material of the outer frame, which contains the molding sand, the original mold plate frame can be either a wooden frame or steel frame. For the molding sand, light yellow-colored sand of the Jeonbuk Iri region was used. Next, the composition of the mother alloy used in the restoration of Sangpyong Tongbo was studied. In consideration of the evaporation of tin and lead during actual restoration, the composition of Cu 60%, Zn 30%, and Pb 10% for brass as stated in The Korea Review was modified to Cu 60%, Zn 35%, and Pb 15%. For bronze, based on the composition of Cu 80%, Sn 6%, and Pb 14% used for Haedong Tongbo, the composition was set as Cu 80%, Sn 11%, and Pb 19%. The mother coin mold was restored by first creating a wooden father coin, making a cast from the wooden frame and basic steel frame, alloying, casting, and making a mother coin. Component analysis was conducted on the mother alloy of the restored Sangpyong Tongbo, and its primary and secondary casts. The bronze mother alloy saw a 5% increase in copper and 4% reduction in lead. The brass parent alloy had a 5% increase in copper, but a 4% and 12% decrease in lead and tin respectively. Analysis of the primary and secondary mother coin molds using an energy dispersive spectrometer showed that the bronze mother coin mold had a reduced amount of lead, while the brass mother coin mold had less tin. This can be explained by the evaporation of lead and tin in the melting of the primary mother coin mold. In addition, the ${\alpha}$-phase and lead particles were found in the mother alloy of bronze and brass, as well as the microstructure of the primary and secondary coin molds. Impurities such as Al and Si were observed only in the brass mother coin mold.

The Impact of Innovative Efficiency on Performance of Firms (혁신효율성이 기업의 수익성에 미치는 영향)

  • Han, Ji-yeon;Ha, Seok-tae;Cho, Seong-pyo
    • Journal of Technology Innovation
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    • v.28 no.3
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    • pp.1-28
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    • 2020
  • This study examines whether the firm with high innovation efficiency realizes high operating performance. We measured innovation efficiency by the ratio of patent applications for R&D expenditure or R&D stock and measured operating performance by the ratio of operating income or operating cash flow to total assets for the following year. The sample consists of 1,880 manufacturing firm-years, which listed on the Korean Exchange between 2014 and 2017. We analyze the effect of innovation efficiency on operating performance using a model of Hirshleifer et al. (2013) results show that both innovation efficiency variables have a significantly positive relationship with the total asset operating margin. Besides, the following year's performance, measured by the total asset operating cash flow ratio, also shows a positive relationship with the two innovation efficiency variables at the 5% and 1% significance levels, respectively. The results indicate that high innovation efficiency firms that link the outcomes of R&D to more patent applications realize higher operating performance. Also, we divided the R&D-intensive and non-R&D-intensive industries and performed the same analysis. As a result, the innovation efficiency has a significant positive effect on operating margin in both industries. However, the effect of innovation efficiency on the operating cash flow is only significant in R&D-intensive industries. This study suggests that the effects of innovation efficiency are more consistent in the R&D-intensive industry. Additionally, we divided the high patent application and low patent applications industries and performed the same analysis. As a result, the innovation efficiency has a significant positive effect on operating margin in both industries. This study suggests that the effects of innovation efficiency are more consistent in the high patent application industry. We show that a firm's innovation efficiency is a critical factor for a firm's performance, while prior studies on the R&D performance have not considered the innovation efficiency of each firm. The evidence suggests that firms not only consider R&D expenditures but also improve the performance of companies by increasing innovation efficiency. Investors need to consider their innovation efficiency when evaluating the value of firms.

A Study on the Determinants of Blockchain-oriented Supply Chain Management (SCM) Services (블록체인 기반 공급사슬관리 서비스 활용의 결정요인 연구)

  • Kwon, Youngsig;Ahn, Hyunchul
    • Knowledge Management Research
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    • v.22 no.2
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    • pp.119-144
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    • 2021
  • Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

Microbial Qualities of Parasites and Foodborne Pathogens in Ready to Eat (RTE) Fresh-cut Produces at the On/Offline Markets (즉석섭취 신선편의 절단 과일 및 채소의 원충류 및 병원성 식중독균의 미생물학적 품질 실태 연구)

  • Jeon, Ji Hye;Roh, Jun Hye;Lee, Chae Lim;Kim, Geun Hyang;Lee, Jeong Yeon;Yoon, Ki Sun
    • Journal of Food Hygiene and Safety
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    • v.37 no.2
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    • pp.87-96
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    • 2022
  • Recently, the purchase of fresh-cut produce and meal kits has increased. Ready-to-eat (RTE) fresh-cut products have potentially hazard of cross-contamination of various microorganisms in the processes of peeling, slicing, dicing, and shredding. There are frequent cases of protozoa food poisoning, such as Cyclospora and Cryptosporidium, caused by fresh-cut products. The objective of the study is to investigate the microbiological qualities of various types of RTE fresh-cut products in the domestic on/offline markets. RTE fresh-cut fruits cup (n=100), fresh-cut vegetables (n=50), and vegetables in meal kits (Vietnamese spring rolls and white radish rolls kits, n=50) were seasonally analyzed. The contamination levels of hygienic indicator organisms, yeast and mold (YM), and foodborne pathogens (Bacillus cereus, Staphylococcus aureus, Listeria monocytogenes, Salmonella spp., and Escherichia coli O157:H7) were monitored. Overall, the lowest microbiological qualities of meal kits vegetables were observed, followed by RTE fresh-cut fruits cup and fresh-cut vegetables. Contamination levels of total aerobic bacteria, coliforms, and YM in meal kits vegetables were 5.91, 3.90, and 4.71 logs CFU/g, respectively. From the qualitative analysis, 6 out of 200 RTE fresh-cut products (3%) returned positive result for S. aureus. From the quantitative analysis, the contamination levels of S. aureus in purple cabbage from a meal-kit and fresh-cut pineapple were below the acceptable limit (100 CFU/g). Staphylococcus enterotoxin seg and sei genes were detected in RTE fresh-cut celery and red cabbage from meal-kits, respectively. S. aureus contamination must be carefully controlled during the manufacturing processes of RTE fresh-cut products. Neither Cyclospora cayetanensis nor Cryptosporidium parvum was detected in the samples of RTE fresh-cut products and vegetables from meal-kits from the Korean retail markets.

Manufacturing Techniques of Bronze Medium Mortars(Jungwangu, 中碗口) in Joseon Dynasty (조선시대 중완구의 제작 기술)

  • Huh, Ilkwon;Kim, Haesol
    • Conservation Science in Museum
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    • v.26
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    • pp.161-182
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    • 2021
  • A jungwangu, a type of medium-sized mortar, is a firearm with a barrel and a bowl-shaped projectileloading component. A bigyeokjincheonroe (bombshell) or a danseok (stone ball) could be used as a projectile. According to the Hwaposik eonhae (Korean Translation of the Method of Production and Use of Artillery, 1635) by Yi Seo, mortars were classified into four types according to its size: large, medium, small, or extra-small. A total of three mortars from the Joseon period have survived, including one large mortar (Treasure No. 857) and two medium versions (Treasure Nos. 858 and 859). In this study, the production method for medium mortars was investigated based on scientific analysis of the two extant medium mortars, respectively housed in the Jinju National Museum (Treasure No. 858) and the Korea Naval Academy Museum (Treasure No. 859). Since only two medium mortars remain in Korea, detailed specifications were compared between them based on precise 3D scanning information of the items, and the measurements were compared with the figures in relevant records from the period. According to the investigation, the two mortars showed only a minute difference in overall size but their weight differed by 5,507 grams. In particular, the location of the wick hole and the length of the handle were distinct. The extant medium mortars are highly similar to the specifications listed in the Hwaposik eonhae. The composition of the medium mortars was analyzed and compared with other bronze gunpowder weapons. The surface composition analysis showed that the medium mortars were made of a ternary alloy of Cu-Sn-Pb with average respective proportions of (wt%) 85.24, 10.16, and 2.98. The material composition of the medium mortars was very similar to the average composition of the small gun from the Joseon period analyzed in previous research. It also showed a similarity with that of bronze gun-metal from medieval Europe. The casting technique was investigated based on a casting defect on the surface and the CT image. Judging by the mold line on the side, it appears that they were made in a piece-mold wherein the mold was halved and using a vertical design with molten metal poured through the end of the chamber and the muzzle was at the bottom. Chaplets, an auxiliary device that fixed the mold and the core to the barrel wall, were identified, which may have been applied to maintain the uniformity of the barrel wall. While the two medium mortars (Treasure Nos. 858 and 859) are highly similar to each other in appearance, considering the difference in the arrangement of the chaplets between the two items it is likely that a different mold design was used for each item.

DEVELOPMENT OF STATEWIDE TRUCK TRAFFIC FORECASTING METHOD BY USING LIMITED O-D SURVEY DATA (한정된 O-D조사자료를 이용한 주 전체의 트럭교통예측방법 개발)

  • 박만배
    • Proceedings of the KOR-KST Conference
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    • 1995.02a
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    • pp.101-113
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    • 1995
  • The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.

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The Characteristics and Performances of Manufacturing SMEs that Utilize Public Information Support Infrastructure (공공 정보지원 인프라 활용한 제조 중소기업의 특징과 성과에 관한 연구)

  • Kim, Keun-Hwan;Kwon, Taehoon;Jun, Seung-pyo
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.1-33
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    • 2019
  • The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

Intelligent Brand Positioning Visualization System Based on Web Search Traffic Information : Focusing on Tablet PC (웹검색 트래픽 정보를 활용한 지능형 브랜드 포지셔닝 시스템 : 태블릿 PC 사례를 중심으로)

  • Jun, Seung-Pyo;Park, Do-Hyung
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.93-111
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    • 2013
  • As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.

Packaging Technology for the Optical Fiber Bragg Grating Multiplexed Sensors (광섬유 브래그 격자 다중화 센서 패키징 기술에 관한 연구)

  • Lee, Sang Mae
    • Journal of the Microelectronics and Packaging Society
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    • v.24 no.4
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    • pp.23-29
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    • 2017
  • The packaged optical fiber Bragg grating sensors which were networked by multiplexing the Bragg grating sensors with WDM technology were investigated in application for the structural health monitoring of the marine trestle structure transporting the ship. The optical fiber Bragg grating sensor was packaged in a cylindrical shape made of aluminum tubes. Furthermore, after the packaged optical fiber sensor was inserted in polymeric tube, the epoxy was filled inside the tube so that the sensor has resistance and durability against sea water. The packaged optical fiber sensor component was investigated under 0.2 MPa of hydraulic pressure and was found to be robust. The number and location of Bragg gratings attached at the trestle were determined where the trestle was subject to high displacement obtained by the finite element simulation. Strain of the part in the trestle being subjected to the maximum load was analyzed to be ${\sim}1000{\mu}{\varepsilon}$ and thus shift in Bragg wavelength of the sensor caused by the maximum load of the trestle was found to be ~1,200 pm. According to results of the finite element analysis, the Bragg wavelength spacings of the sensors were determined to have 3~5 nm without overlapping of grating wavelengths between sensors when the trestle was under loads and thus 50 of the grating sensors with each module consisting of 5 sensors could be networked within 150 nm optical window at 1550 nm wavelength of the Bragg wavelength interrogator. Shifts in Bragg wavelength of the 5 packaged optical fiber sensors attached at the mock trestle unit were well interrogated by the grating interrogator which used the optical fiber loop mirror, and the maximum strain rate was measured to be about $235.650{\mu}{\varepsilon}$. The modelling result of the sensor packaging and networking was in good agreements with experimental result each other.