• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.9 no.2
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• pp.64-72
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• 2004

We measured the vertical profiles of $O_2$, H$_2$S, and pH in sediment pore water beneath marine cage fish farms using a microsensor with a 25 ${\mu}{\textrm}{m}$ sensor tip size. The sediments are characterized by high organic material load. The oxygen consumption, hydrogen sulfide oxidation, and sulfate reduction rates in the microzonations (derived from the vertical distribution of chemical species concentration) were estimated by adapting a simple one-dimensional diffusion-reaction model. The oxygen penetration depth was 0.75 mm. The oxic microzonations were divided into upper and lower layers. Due to hydrogen sulfide oxidation within the oxic zone, the oxygen consumption rate was higher in the lower layer. The total oxygen consumption rate integrated with reaction zone depth was estimated to be 0.092 $\mu$mol $O_2$cm$^{-2}$ hr$^{-1}$ . The total hydrogen sulfide oxidation rate occurring within 0.7 mm thickness was estimated to be 0.030 $\mu$mo1 H$_2$S cm$^{-2}$ hr$^{-1}$ , and its turnover time in the oxic sediment layer was estimated to be about 2 minutes. This suggests that hydrogen sulfide was oxidized by both chemical and microbial processes in this zone. The molar consumption ratio, calculated to be 0.84, indicates that either other electron accepters exit on hydrogen sulfide oxidation, or elemental sulfur precipitation occurs near the $O_2$- H$_2$S interface. Total sulfate reduction flux was estimated to be 0.029 $\mu$mol cm$^{-2}$ hr$^{-1}$ , which accounted for more than 60% of total $O_2$ consumption flux. This result implied that the degradation of organic matter in the anoxic layer was larger than in the oxic layer.

• Asia pacific journal of information systems
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• v.19 no.1
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• pp.113-145
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• 2009

Recently, due to the globalization of the IT(Information Technology) market, devices and systems designed in one country are used in other countries as well. This phenomenon is becoming the key factor for increased interest on cross-cultural, or cross-national, research within the IT area. However, as the IT market is becoming bigger and more globalized, a great number of IT practitioners are having difficulty in designing and developing devices or systems which can provide optimal experience. This is because not only tangible factors such as language and a country's economic or industrial power affect the user experience of a certain device or system but also invisible and intangible factors as well. Among such invisible and intangible factors, the cultural characteristics of users from different countries may affect the user experience of certain devices or systems because cultural characteristics affect how they understand and interpret the devices or systems. In other words, when users evaluate the quality of overall user experience, the cultural characteristics of each user act as a perceptual lens that leads the user to focus on a certain elements of experience. Therefore, there is a need within the IT field to consider cultural characteristics when designing or developing certain devices or systems and plan a strategy for localization. In such an environment, existing IS studies identify the culture with the country, emphasize the importance of culture in a national level perspective, and hypothesize that users within the same country have same cultural characteristics. Under such assumptions, these studies focus on the moderating effects of cultural characteristics on a national level within a certain theoretical framework. This has already been suggested by cross-cultural studies conducted by scholars such as Hofstede(1980) in providing numerical research results and measurement items for cultural characteristics and using such results or items as they increase the efficiency of studies. However, such national level culture has its limitations in forecasting and explaining individual-level behaviors such as voluntary device or system usage. This is because individual cultural characteristics are the outcome of not only the national culture but also the culture of a race, company, local area, family, and other groups that are formulated through interaction within the group. Therefore, national or nationally dominant cultural characteristics may have its limitations in forecasting and explaining the cultural characteristics of an individual. Moreover, past studies in psychology suggest a possibility that there exist different cultural characteristics within a single individual depending on the subject being measured or its context. For example, in relation to individual vs. collective characteristics, which is one of the major cultural characteristics, an individual may show collectivistic characteristics when he or she is with family or friends but show individualistic characteristics in his or her workplace. Therefore, this study acknowledged such limitations of past studies and conducted a research within the framework of 'theoretically integrated model of user satisfaction and emotional attachment', which was developed through a former study, on how the effects of different experience elements on emotional attachment or user satisfaction are differentiated depending on the individual cultural characteristics related to a system or device usage. In order to do this, this study hypothesized the moderating effects of four cultural dimensions (uncertainty avoidance, individualism vs, collectivism, masculinity vs. femininity, and power distance) as suggested by Hofstede(1980) within the theoretically integrated model of emotional attachment and user satisfaction. Statistical tests were then implemented on these moderating effects through conducting surveys with users of four digital devices (mobile phone, MP3 player, LCD TV, and refrigerator) in three countries (US, Germany, and Russia). In order to explain and forecast the behavior of personal device or system users, individual cultural characteristics must be measured, and depending on the target device or system, measurements must be measured independently. Through this suggestion, this study hopes to provide new and useful perspectives for future IS research.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.163-178
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• 2014

Following research proposes "Virtualization of Smart Cards (ViSCa)" which is a security system that aims to provide a multi-device platform for the deployment of services that require a strong security protocol, both for the access & authentication and execution of its applications and focuses on analyzing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service by comparing with other similar cases. At the present day, the appearance of new ICT, the diffusion of new user devices (such as smartphones, tablet PC, and so on) and the growth of internet penetration rate are creating many world-shaking services yet in the most of these applications' private information has to be shared, which means that security breaches and illegal access to that information are real threats that have to be solved. Also mobile payment service is, one of the innovative services, has same issues which are real threats for users because mobile payment service sometimes requires user identification, an authentication procedure and confidential data sharing. Thus, an extra layer of security is needed in their communication and execution protocols. The Virtualization of Smart Cards (ViSCa), concept is a holistic approach and centralized management for a security system that pursues to provide a ubiquitous multi-device platform for the arrangement of mobile payment services that demand a powerful security protocol, both for the access & authentication and execution of its applications. In this sense, Virtualization of Smart Cards (ViSCa) offers full interoperability and full access from any user device without any loss of security. The concept prevents possible attacks by third parties, guaranteeing the confidentiality of personal data, bank accounts or private financial information. The Virtualization of Smart Cards (ViSCa) concept is split in two different phases: the execution of the user authentication protocol on the user device and the cloud architecture that executes the secure application. Thus, the secure service access is guaranteed at anytime, anywhere and through any device supporting previously required security mechanisms. The security level is improved by using virtualization technology in the cloud. This virtualization technology is used terminal virtualization to virtualize smart card hardware and thrive to manage virtualized smart cards as a whole, through mobile cloud technology in Virtualization of Smart Cards (ViSCa) platform-based mobile payment service. This entire process is referred to as Smart Card as a Service (SCaaS). Virtualization of Smart Cards (ViSCa) platform-based mobile payment service virtualizes smart card, which is used as payment mean, and loads it in to the mobile cloud. Authentication takes place through application and helps log on to mobile cloud and chooses one of virtualized smart card as a payment method. To decide the scope of the research, which is comparing Virtualization of Smart Cards (ViSCa) platform-based mobile payment service with other similar cases, we categorized the prior researches' mobile payment service groups into distinct feature and service type. Both groups store credit card's data in the mobile device and settle the payment process at the offline market. By the location where the electronic financial transaction information (data) is stored, the groups can be categorized into two main service types. First is "App Method" which loads the data in the server connected to the application. Second "Mobile Card Method" stores its data in the Integrated Circuit (IC) chip, which holds financial transaction data, which is inbuilt in the mobile device secure element (SE). Through prior researches on accept factors of mobile payment service and its market environment, we came up with six key factors of comparative analysis which are economic, generality, security, convenience(ease of use), applicability and efficiency. Within the chosen group, we compared and analyzed the selected cases and Virtualization of Smart Cards (ViSCa) platform-based mobile payment service.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.29-45
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• 2015

Response modeling is a well-known research issue for those who have tried to get more superior performance in the capability of predicting the customers' response for the marketing promotion. The response model for customers would reduce the marketing cost by identifying prospective customers from very large customer database and predicting the purchasing intention of the selected customers while the promotion which is derived from an undifferentiated marketing strategy results in unnecessary cost. In addition, the big data environment has accelerated developing the response model with data mining techniques such as CBR, neural networks and support vector machines. And CBR is one of the most major tools in business because it is known as simple and robust to apply to the response model. However, CBR is an attractive data mining technique for data mining applications in business even though it hasn't shown high performance compared to other machine learning techniques. Thus many studies have tried to improve CBR and utilized in business data mining with the enhanced algorithms or the support of other techniques such as genetic algorithm, decision tree and AHP (Analytic Process Hierarchy). Ahn and Kim(2008) utilized logit, neural networks, CBR to predict that which customers would purchase the items promoted by marketing department and tried to optimized the number of k for k-nearest neighbor with genetic algorithm for the purpose of improving the performance of the integrated model. Hong and Park(2009) noted that the integrated approach with CBR for logit, neural networks, and Support Vector Machine (SVM) showed more improved prediction ability for response of customers to marketing promotion than each data mining models such as logit, neural networks, and SVM. This paper presented an approach to predict customers' response of marketing promotion with Case Based Reasoning. The proposed model was developed by applying different weights to each feature. We deployed logit model with a database including the promotion and the purchasing data of bath soap. After that, the coefficients were used to give different weights of CBR. We analyzed the performance of proposed weighted CBR based model compared to neural networks and pure CBR based model empirically and found that the proposed weighted CBR based model showed more superior performance than pure CBR model. Imbalanced data is a common problem to build data mining model to classify a class with real data such as bankruptcy prediction, intrusion detection, fraud detection, churn management, and response modeling. Imbalanced data means that the number of instance in one class is remarkably small or large compared to the number of instance in other classes. The classification model such as response modeling has a lot of trouble to recognize the pattern from data through learning because the model tends to ignore a small number of classes while classifying a large number of classes correctly. To resolve the problem caused from imbalanced data distribution, sampling method is one of the most representative approach. The sampling method could be categorized to under sampling and over sampling. However, CBR is not sensitive to data distribution because it doesn't learn from data unlike machine learning algorithm. In this study, we investigated the robustness of our proposed model while changing the ratio of response customers and nonresponse customers to the promotion program because the response customers for the suggested promotion is always a small part of nonresponse customers in the real world. We simulated the proposed model 100 times to validate the robustness with different ratio of response customers to response customers under the imbalanced data distribution. Finally, we found that our proposed CBR based model showed superior performance than compared models under the imbalanced data sets. Our study is expected to improve the performance of response model for the promotion program with CBR under imbalanced data distribution in the real world.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.6
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• pp.708-722
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• 2016

Land-Ocean Interactions in the Coastal Zone (LOICZ) models for nutrient budgets were used to estimate the seasonal capacity of the Youngsan Estuary and Youngam-Geumho Estuary to sink and/or supply nutrients such as dissolved inorganic phosphorus (DIP) and nitrogen (DIN) to provide an understanding of the behavior of the coupled biogeochemical cycles of phosphorus and nitrogen in the estuaries (Youngsan Estuary, Youngam-Geumho Estuary) near Mokpo Harbor. During non-stratified periods (May, September, and November, 2008), simple three-box models were applied in each sub-region of the system, while a two-layer box model was applied during on-site observation of stratification development (July, 2008). The resulting mass-balance calculation indicated that even after large discharges from artificial lakes (in May and July), DIP influxes due to a mixing exchange ($V_{X-3}$, or $V_{deep}$) were more than terrigenous loads, indicating the backward transportation of nutrients from a marine source. The model results also indicated that for nutrient loads (DIP and DIN fluxes) in September, an extreme congestion of nutrients occurred around the mouths (sub-region III of the model) of the estuaries, possibly due to an imbalance in physical circulations between the estuaries and offshore locations. In November, the Youngam-Geumho Estuary, into which freshwater was discharged from artificial lakes (Youngam and Geumho Lake), showed nutrient enrichment in the water column, but the Youngsan Estuary showed nutrient depletion. In conclusion, to efficiently control water quality in the estuaries near Mokpo Harbor, integrated environmental management programs should be implemented. I.e., the reduction of nutrient loads from land basins as well as the deposit of nutrient loads into adjacent coastal lines.

• Korean Journal of Ecology and Environment
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• v.46 no.4
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• pp.488-498
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• 2013

A three-dimensional hydrodynamic model was applied to the Lake Euiam. The lake has three inflows, of which Gongji Stream has the smallest flow rate and poorest water. The dam-storage volume, watershed area, lake shape and discharge type of the Chuncheon Dam and the Soyang Dam are different. Therefore, it is difficult to analyze the water plume and mixing pattern due to the difference of the two dams regarding the amount of outflow and water temperature. In this study, we analyzed the effects of different characteristics on temperature and conductivity using the model appropriate for the Lake Euiam. We selected an integrated system supporting 3-D time varying modeling (GEMSS) to represent large temporal and spatial variations in hydrodynamics and transport of the Lake Euiam. The model represents the water temperature and hydrodynamics in the lake reasonably well. We examined residence time and spreading patterns of the incoming flows in the lake based on the results of the validated model. The results of the water temperature and conductivity distribution indicated that characteristics of upstream dams greatly influence Lake Euiam. In this study, the three-dimensional time variable water quality model successfully simulated the temporal and spatial variations of the hydrodynamics in the Lake Euiam. The model may be used for efficient water quality management.

• Korean Journal of Ecology and Environment
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• v.53 no.3
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• pp.229-240
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• 2020

In this study, the results of fish assemblage survey for 16 reservoirs in the Yeongsan·Seomjin-River watershed were presented with fish assemblage characteristics analysis in relation to reservoir size. The survey method including number of sampling sites was followed the "Biomonitoring survey and assessment manual" of the Ministry of Environment/National Institute of Environmental Research (MOE/NIER), and the reservoirs were categorized as three size groups, small, medium or large reservoirs, based on the MOE/NIER as well. Total 13 family classified into 44 species were collected from 2018 (7 reservoirs) to 2019 (9 reservoirs), and the dominant and subdominant species were Hemiculter eigenmanni (Relative abundance, RA, 32.9%) and Lepomis macrochirus (RA, 31.4%), respectively. As a result of the analysis in relation to the reservoir size, the average (±standard deviation) number of species of the small, medium and large reservoirs were 11±2.9, 14.3±2.1, 22.7±0.6, respectively, which showed positive correlation with the reservoir size. Total 6 fish assemblage characteristics(number of species, number of individuals, richness index, herbivorous fish ratio, carnivorous fish ratio, exotic fish ratio) showed significant differences between the each reservoir size groups (P<0.05). As a result of cluster analysis, 16 reservoirs were clustered into 5 groups with 60% similarity, and the each reservoirs seems to be clustered depends on the distance from each other, watershed and their historical geology rather than size. These results are baseline information for the understanding of fish assemblage in Korean reservoirs, important for establishing management policy of reservoirs in the Yeongsan·Seomjin-River watershed.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.17 no.2
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• pp.87-94
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• 2012

To compare monthly variations of phytoplankton biomass and community composition between in seawater and sediment of the Gomso Bay (tidal flat: approximately 75%), the photosynthetic pigments were analyzed by HPLC every month in 1999 and every two months in 2000. Ambient physical and chemical parameters (temperature, salinity, nutrients, dissolved oxygen, and chemical oxygen demand) were also examined to find the environmental factors controlling structure of phytoplankton community. The temporal and spatial variations of chlorophyll a concentration in seawater were correlated well with the magnitude of freshwater discharge from land. The biomass of microphytobenthos at the surface sediments was lower than that in other regions of the world and 2-3 times lower than phytoplankton biomass integrated in the seawater column. Based on the results of HPLC pigment analysis, fucoxanthin, a marker pigment of diatoms, was the most prominent pigment and highly correlated with chlorophyll a in seawater and sediment of the Gomso Bay. These results suggest that diatoms are the predominant phytoplankton in seawater and sediment of the Gomso Bay. However, the monthly variation of chlorophyll a concentration in seawater at the subtidal zone was not a good correlation with that in sediment of the Gomso Bay. Although pelagic plankton was identified in seawater by microscopic examination, benthic algal species were not found in the seawater. These results suggest that contribution from the suspended microphytobenthos in the tidal flat to the subtidal zone of the Gomso Bay may be low as a food source to the primary consumer in the upper water column of the subtidal zone. Further study needs to elucidate the vertical and horizontal transport magnitude of the suspended microphytobenthos in the tidal flat to the subtidal zone.

• Journal of Environmental Science International
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• v.25 no.10
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• pp.1445-1457
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• 2016

In this study, we investigated the growth of striped mullet (Mugil cephalus), Yesso scallop (Patinopecten yessoensis) and kelp (Saccharina japonica) farmed under the IMTA (integrated multi-trophic aquaculture) system developed by national institute of fisheries science (NIFS). The farmed striped mullets grew from an initial length and weight of $152.5{\pm}12.1mm$ and $41.6{\pm}7.8g$ in October 2013 to $154.2{\pm}5.6mm$ and $47.5{\pm}8.6g$ in November, $160.2{\pm}8.7mm$ and $55.9{\pm}9.1g$ in December and $168.4{\pm}9.6mm$ and $58.4{\pm}8.7g$ in January. The fish continued to grow and reached $190.2{\pm}9.4mm$ in length and $87.5{\pm}8.9g$ in weight in April and $256.4{\pm}9.7mm$ and $156.7{\pm}6.7g$ in October 2014. The daily growth rate (DGR) for total fish length was 0.015~0.1 mm/day during the periods of fast growth and attained 0.038~0.1 mm/day during February ~ March. The kelp grew from an initial blade length and wet weight of $1.19{\pm}0.2cm$ and $0.0028{\pm}0.0012g$ in January 2014 to $3.3{\pm}0.8cm$ and $2.5{\pm}0.9g$ in February and $126.5{\pm}11.6cm$ and $107.4{\pm}22.6g$ in March, after which, erosion occurred and slowed the growth. The DGRs for kelp length ranged 0.03~1.9 mm/day in January 2014 and increased to 0.88~1.9 mm/day during March~April. Increasing water temperatures beginning in April lowered the DGR to 0.03 mm/day. Yesso scallops grew from an initial shell length, shell height and wet weight of $11.83{\pm}0.6mm$, $12.68{\pm}0.7mm$ and in September 2013 to $19.9{\pm}2.5mm$, $20.8{\pm}2.6mm$ and $0.9{\pm}0.04g$ in November 2013. They continued to grow to $45.91{\pm}0.71mm$ in shell length, $42.55{\pm}0.8mm$ in shell height and $12.7{\pm}1.3g$ in wet weight by May 2014 and $60.2{\pm}2.51mm$, $554.6{\pm}2.61mm$ and $24{\pm}2.70g$ by October 2014. The DGRs for shell length of Yesso scallop ranged from 0.02 to 0.256 mm/day with higher values of 0.256~0.27 mm/day during November~December 2013 and March~April 2014.