• 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.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.95-116
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• 2009

Increasingly the institutional theory has been an important theoretical view of decision making process and IT adoption in many academic researches. This study used the institutional theory as a lens through which we can understand the factors that enable the effective appropriation of advanced information technology. It posits that mimetic, coercive, and normative pressures existing in an institutionalized environment could influence the participation of top managers or decision makers and the involvement of users toward an effective use of IT in their tasks. Since the introduction of IT, organizational members have been using IT in their daily tasks, creating and recreating rules and resources according to their own methods and needs. That is to say, the adaptation process of the IT and outcomes are different among organizations. The previous studies on a diverse use of IT refer to the appropriation of technology from the social technology view. Users appropriate IT through not only technology itself, but also in terms of how they use it or how they make the social practice in their use of it. In this study, the concepts of institutional pressure, appropriation, participation of decision makers, and involvement of users toward the appropriation are explored in the context of the appropriation of the mobile electronic medical record system (M-EMRS) in particularly a hospital setting. Based on the conceptual definition of institutional pressure, participation and involvement, operational measures are reconstructed. Furthermore, the concept of appropriation is measured in the aspect of three sub-constructs-consensus on appropriation, faithful appropriation, and attitude of use. Grounded in the relevant theories to appropriation of IT, we developed a research framework in which the effects of institutional pressure, participation and involvement on the appropriation of IT are analyzed. Within this theoretical framework, we formulated several hypotheses. We developed a second order institutional pressure and appropriation construct. After establishing its validity and reliability, we tested the hypotheses with empirical data from 101 users in 3 hospitals which had adopted and used the M-EMRS. We examined the mediating effect of the participation of decision makers and the involvement of users on the appropriation and empirically validated their relationships. The results show that the mimetic, coercive, and normative institutional pressure has an effect on the participation of decision makers and the involvement of users in the appropriation of IT while the participation of decision makers and the involvement of users have an effect on the appropriation of IT. The results also suggest that the institutional pressure and the participation of decision makers influence the involvement of users toward an appropriation of IT. Our results emphasize the mediating effect of the institutional pressure on the appropriation of IT. Namely, the higher degree of the participation of decision makers and the involvement of users, the more effective appropriation users will represent. These results provide strong support for institutional-based variables as predictors of appropriation. These findings also indicate that organizations should focus on the role of participation of decision makers and the involvement of users for the purpose of effective appropriation, and these are the practical implications of our study. The theoretical contribution of this study is lies in the integrated model of the effect of institutional pressure on the appropriation of IT. The results are consistent with the institutional theory and support previous studies on adaptive structuration theory.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.21-35
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• 2018

Since the introduction of MP3 players, CD recordings have gradually been vanishing, and the music consuming environment of music users is shifting to mobile devices. The introduction of smart devices has increased the utilization of music through music playback, mass storage, and search functions that are integrated into smartphones and tablets. At the time of initial MP3 player supply, the bitrate of the compressed music contents generally was 128 Kbps. However, as increasing of the demand for high quality music, sound quality of 384 Kbps appeared. Recently, music content of FLAC (Free License Audio Codec) format using lossless compression method is becoming popular. The download service of many music sites in Korea has classified by unlimited download with technical protection and limited download without technical protection. Digital Rights Management (DRM) technology is used as a technical protection measure for unlimited download, but it can only be used with authenticated devices that have DRM installed. Even if music purchased by the user, it cannot be used by other devices. On the contrary, in the case of music that is limited in quantity but not technically protected, there is no way to enforce anyone who distributes it, and in the case of high quality music such as FLAC, the loss is greater. In this paper, the author proposes an audio watermarking technology for copyright protection of high quality stereo music. Two kinds of information, "Copyright" and "Copy_free", are generated by using the turbo code. The two watermarks are composed of 9 bytes (72 bits). If turbo code is applied for error correction, the amount of information to be inserted as 222 bits increases. The 222-bit watermark was expanded to 1024 bits to be robust against additional errors and finally used as a watermark to insert into stereo music. Turbo code is a way to recover raw data if the damaged amount is less than 15% even if part of the code is damaged due to attack of watermarked content. It can be extended to 1024 bits or it can find 222 bits from some damaged contents by increasing the probability, the watermark itself has made it more resistant to attack. The proposed algorithm uses quantization in DCT so that watermark can be detected efficiently and SNR can be improved when stereo music is converted into mono. As a result, on average SNR exceeded 40dB, resulting in sound quality improvements of over 10dB over traditional quantization methods. This is a very significant result because it means relatively 10 times improvement in sound quality. In addition, the sample length required for extracting the watermark can be extracted sufficiently if the length is shorter than 1 second, and the watermark can be completely extracted from music samples of less than one second in all of the MP3 compression having a bit rate of 128 Kbps. The conventional quantization method can extract the watermark with a length of only 1/10 compared to the case where the sampling of the 10-second length largely fails to extract the watermark. In this study, since the length of the watermark embedded into music is 72 bits, it provides sufficient capacity to embed necessary information for music. It is enough bits to identify the music distributed all over the world. 272 can identify $4*10^{21}$, so it can be used as an identifier and it can be used for copyright protection of high quality music service. The proposed algorithm can be used not only for high quality audio but also for development of watermarking algorithm in multimedia such as UHD (Ultra High Definition) TV and high-resolution image. In addition, with the development of digital devices, users are demanding high quality music in the music industry, and artificial intelligence assistant is coming along with high quality music and streaming service. The results of this study can be used to protect the rights of copyright holders in these industries.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.4
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• pp.197-206
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• 2014

The purpose of this study is to evaluate coastal erosion due to a sea-level rise. The shoreline retreat rate was calculated due to future sea-level rise. Shoreline retreat rates were quantified with the cross-sectional data of 23 sandy coasts (12 sites from east coast, 5 sites from south coast, and 6 sites of west coast) and 3 cross-sectional profiles from each side of the coasts in Korea. The theory of equilibrium beach profile was employed in this study to evaluate the applicability of the theory into the coast of Korea and was tested with 15 cross-sectional beach profiles. Four scenarios of future sea level rise such as 38 cm, 59 cm, 75 cm, and 100 cm were adopted to estimate the shoreline retreat rates. Overall shoreline retreat rates for the coasts in Korea were predicted as 43.7% for 38 cm, 60.3% for 59 cm, 69.2% for 75 cm, and 80.1% for 100 cm sea level rises, respectively. Retreat rates in the east coast (29.6% for 38 cm, 45.1% for 59 cm, 56.0% for 75 cm, and 69.9% for 100 cm) showed relatively low compared to the south coast (51.9%, 67.6%, 77.2%, 87.3%) and the west coast (53.8%, 71.0%, 78.5%, 86.4%). However, all sandy coasts in Korea were assessed to be vulnerable with increasing sea-level rise. There are uncertainties in the assessment of this study, which include the limitation of the assessment model and the lack of the spatio-temporal data of the beach profiles. Therefore, this study shows that it is very important to spend integrated efforts to respond coastal erosion including comprehensive observations(monitoring) and the development of scientific understanding on the field.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1041-1052
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• 2022

This study is to estimate the optimal ecological flow and analysis the spatial distribution of fish habitat for Andong dam downstream reach (4,565.7 km²) using PHABSIM (Physical Habiat Simulation System) and River2D. To establish habitat models, the cross-section informations and hydraulic input data were collected uisng the Nakdong river basic plan report. The establishment range of PHABSIM was set up about 410.0 m from Gudam streamflow gauging station (GD) and about 6.0 km including GD for River2D. To select representative fish species and construct HSI (Habitat Suitability Index), the fish survey was performed at Pungji bridge where showed well the physical characteristics of target stream located downstream of GD. As a result of the fish survey, Zacco platypus was showed highly relative abundance resulting in selecting as the representative fish species, and HSI was constructed using physical habitat characteristics of the Zacco platypus. The optimal range of HSI was 0.3~0.5 m/s at the velocity suitability index, 0.4~0.6 m at the depth suitability index, and the substrate was sand to fine gravel. As a result of estimating the optimal ecological flow by applying HSI to PHABSIM, the optimal ecological flow for target stream was 20.0 m³/sec. As a result of analysis two-dimensional spatial analysis of fish habitat using River2D, WUA (Weighted Usable Area) was estimated 107,392.0 m²/1000 m under the ecological flow condition and it showed the fish habitat was secured throughout the target stream compared with Q₃₅₅ condition.