• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.21-41
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• 2019

Thanks to the rapid development of information technologies, the data available on Internet have grown rapidly. In this era of big data, many studies have attempted to offer insights and express the effects of data analysis. In the tourism and hospitality industry, many firms and studies in the era of big data have paid attention to online reviews on social media because of their large influence over customers. As tourism is an information-intensive industry, the effect of these information networks on social media platforms is more remarkable compared to any other types of media. However, there are some limitations to the improvements in service quality that can be made based on opinions on social media platforms. Users on social media platforms represent their opinions as text, images, and so on. Raw data sets from these reviews are unstructured. Moreover, these data sets are too big to extract new information and hidden knowledge by human competences. To use them for business intelligence and analytics applications, proper big data techniques like Natural Language Processing and data mining techniques are needed. This study suggests an analytical approach to directly yield insights from these reviews to improve the service quality of hotels. Our proposed approach consists of topic mining to extract topics contained in the reviews and the decision tree modeling to explain the relationship between topics and ratings. Topic mining refers to a method for finding a group of words from a collection of documents that represents a document. Among several topic mining methods, we adopted the Latent Dirichlet Allocation algorithm, which is considered as the most universal algorithm. However, LDA is not enough to find insights that can improve service quality because it cannot find the relationship between topics and ratings. To overcome this limitation, we also use the Classification and Regression Tree method, which is a kind of decision tree technique. Through the CART method, we can find what topics are related to positive or negative ratings of a hotel and visualize the results. Therefore, this study aims to investigate the representation of an analytical approach for the improvement of hotel service quality from unstructured review data sets. Through experiments for four hotels in Hong Kong, we can find the strengths and weaknesses of services for each hotel and suggest improvements to aid in customer satisfaction. Especially from positive reviews, we find what these hotels should maintain for service quality. For example, compared with the other hotels, a hotel has a good location and room condition which are extracted from positive reviews for it. In contrast, we also find what they should modify in their services from negative reviews. For example, a hotel should improve room condition related to soundproof. These results mean that our approach is useful in finding some insights for the service quality of hotels. That is, from the enormous size of review data, our approach can provide practical suggestions for hotel managers to improve their service quality. In the past, studies for improving service quality relied on surveys or interviews of customers. However, these methods are often costly and time consuming and the results may be biased by biased sampling or untrustworthy answers. The proposed approach directly obtains honest feedback from customers' online reviews and draws some insights through a type of big data analysis. So it will be a more useful tool to overcome the limitations of surveys or interviews. Moreover, our approach easily obtains the service quality information of other hotels or services in the tourism industry because it needs only open online reviews and ratings as input data. Furthermore, the performance of our approach will be better if other structured and unstructured data sources are added.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.191-207
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• 2021

Up to this day, mobile communications have evolved rapidly over the decades, mainly focusing on speed-up to meet the growing data demands of 2G to 5G. And with the start of the 5G era, efforts are being made to provide such various services to customers, as IoT, V2X, robots, artificial intelligence, augmented virtual reality, and smart cities, which are expected to change the environment of our lives and industries as a whole. In a bid to provide those services, on top of high speed data, reduced latency and reliability are critical for real-time services. Thus, 5G has paved the way for service delivery through maximum speed of 20Gbps, a delay of 1ms, and a connecting device of 106/㎢ In particular, in intelligent traffic control systems and services using various vehicle-based Vehicle to X (V2X), such as traffic control, in addition to high-speed data speed, reduction of delay and reliability for real-time services are very important. 5G communication uses high frequencies of 3.5Ghz and 28Ghz. These high-frequency waves can go with high-speed thanks to their straightness while their short wavelength and small diffraction angle limit their reach to distance and prevent them from penetrating walls, causing restrictions on their use indoors. Therefore, under existing networks it's difficult to overcome these constraints. The underlying centralized SDN also has a limited capability in offering delay-sensitive services because communication with many nodes creates overload in its processing. Basically, SDN, which means a structure that separates signals from the control plane from packets in the data plane, requires control of the delay-related tree structure available in the event of an emergency during autonomous driving. In these scenarios, the network architecture that handles in-vehicle information is a major variable of delay. Since SDNs in general centralized structures are difficult to meet the desired delay level, studies on the optimal size of SDNs for information processing should be conducted. Thus, SDNs need to be separated on a certain scale and construct a new type of network, which can efficiently respond to dynamically changing traffic and provide high-quality, flexible services. Moreover, the structure of these networks is closely related to ultra-low latency, high confidence, and hyper-connectivity and should be based on a new form of split SDN rather than an existing centralized SDN structure, even in the case of the worst condition. And in these SDN structural networks, where automobiles pass through small 5G cells very quickly, the information change cycle, round trip delay (RTD), and the data processing time of SDN are highly correlated with the delay. Of these, RDT is not a significant factor because it has sufficient speed and less than 1 ms of delay, but the information change cycle and data processing time of SDN are factors that greatly affect the delay. Especially, in an emergency of self-driving environment linked to an ITS(Intelligent Traffic System) that requires low latency and high reliability, information should be transmitted and processed very quickly. That is a case in point where delay plays a very sensitive role. In this paper, we study the SDN architecture in emergencies during autonomous driving and conduct analysis through simulation of the correlation with the cell layer in which the vehicle should request relevant information according to the information flow. For simulation: As the Data Rate of 5G is high enough, we can assume the information for neighbor vehicle support to the car without errors. Furthermore, we assumed 5G small cells within 50 ~ 250 m in cell radius, and the maximum speed of the vehicle was considered as a 30km ~ 200 km/hour in order to examine the network architecture to minimize the delay.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.2
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• pp.108-121
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• 2016

The purpose of this study is to explore the issues and implications for landscape design education in Korean landscape architecture by analyzing the National Exhibition of Korean Landscape Architecture(NEKLA). This study analyzed the suggested topics and selected site as well as the commentary that appeared in the NEKLA's award-winning book published from 2004 to 2014. Results of the study are as follows: First, topics of NEKLA are not only competition guidelines but related to exploring new area and role of Korean landscape architecture. Second, most dealing with site is 'industrial heritage and regeneration space' and 'green infrastructure'. In more recent years, a larger variety of sites were addressed. Third, site locations are concentrated in metropolitan areas, and awards and participation of the non-metropolitan universities was very low. Fourth, seven criteria can be applied in a general landscape design competition such as 'newness of the concept(idea)', 'logicality of the design process', 'selection of site fidelity of analysis(interpretation)', 'presentation and completion of the master plan', 'consistency with the theme', 'linkage of concepts and results' and 'feasibility'. The evaluation criteria are increasing the sophistication of the design language to provide useful suggestions on how to find design education methods. Its implications are as follows: First, training is essential to derive innovative ideas, but it should avoid excessive concept-oriented education. Second, design education may include instruction on how to define the problems related with the site. Third, more emphasis on design logic is essential to transform the innovative concept to actual results. Fourth, 'slick images' unrelated to design should be suppressed. Fifth, practice is needed to solve the topics addressed in the design process of education. Sixth, 'feasibility' and 'creative thinking' are necessary to recognize a reciprocal relationship that is helpful to one another. This study uses direct quote commentary to minimize the subjectivity of the researcher and to trace issues of the contemporary landscape architecture more directly and vividly. This study is a record waiting for another review as meta-criticism. In this regard this study, the landscape architect of the next times will have a mean that historical records to review the current thinking of the landscape theory and design.

• Journal of Forest and Environmental Science
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• v.14 no.1
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• pp.112-127
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• 1998

A meeting for Japan Society of Erosion Control Engineering took place, from May 20-21 in Sapporo, Japan, with the presentations of 21 special topics and 185 general papers. Special topics consists of 6 copies on volcanic disaster prevention, 6 copies on the activity report of Earthquake Erosion Control Engineering Society, 5 copies on the management and guidelines of riparian zone and 4 copies on debris disaster occurred in 1997. General papers consists of 10 copies on slope stability, 10 copies on slope failure, 9 copies on earthquake, 41 copies on environmental erosion control, 25 copies on debris flow, 11 copies on warning and refuge, 10 copies on erosion control plan, 11 copies on erosion control project, 10 copies on erosion control facility, 12 copies on volcanic erosion control, 4 copies on revegetation technology, 4 copies on forest hydrology, 4 copies on avalanche, 4 copies on landslide, 18 copies on debris flow and 2 other copies presented by international student. Among the special topics, 5 papers with the titles of the function and structure of riparian zone, the interactive relation of flood and riparian zone, the management method of channel and river forest for controlling debris flow, the forest restoration efforts by native population, the law and social issue for building river riparian zone were presented in the subsection of "The Management and Guidelines of Riparian Zone". Thus, this article summarize and introduce the presented contents which are very important and can be referred to keep environmentally sound-river in the erosion control field.

• Pediatric Infection and Vaccine
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• v.6 no.2
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• pp.245-252
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• 1999

Purpose : The aim of this study is to determine the age-specific seropositivity and the level of measles specific IgG in adults and to evaluate herd immunity to measles in Korea, the measles specific IgG were measured from the sera of adults over ages of 20 in Korea. Methods : 156 sera were collected from 156 out-patients over ages 20, who had visited clinical laboratory from June to July in 1997 at Korea University Ansan Hospital. The histories of natural measles or vaccination were not undertaken. Measles specific IgG titers were measured using ELISA method($SIA^{TM}$ Measles IgG Kit Co. St. Louis. Mo). Results : The results obtained from this study were as follows. 1) The seropositivity of measles specific IgG in adults was 94.9%. And there were no significant differences in their age and gender. 2) The mean measles-specific IgG titer was $238{\pm}84AU/mL$. And there were no significant differences in age and gender, except significant lower in 4th decades than other age groups. And there were no significant correlations between age and measles specific IgG level. Conclusion : In conclusion, a seropositivity of in adults was 94.9% which was higher than that of adolescents(91.2% in previous study), and antibody level was similar with adolescents. The herd immunity of the adults were considered to enough for protecting the transmission of measles in the community. For the eradication of measles in Korea, more efforts will be required to increase the vaccine coverage rate in children and adolescents.

• Journal of agricultural medicine and community health
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• v.42 no.1
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• pp.13-23
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• 2017

Objectives: This study was conducted to evaluate a relationship between the blood concentrations of toxic metals and the blood pressure in people living near the copper smelter. Methods: The study included 570 adults living within 4km of the smelter. We compared systolic and diastolic blood pressure between tertiary groups for blood cadmium, mercury and lead levels, respectively. Multiple regression analysis was performed to identify risk factors affecting systolic and diastolic blood pressures. Results: In male subjects, there is a significant difference in the mean of systolic and diastolic blood pressure between tertiary groups of blood cadmium and mercury levels, but in women, there was no significant difference in the mean systolic and diastolic blood pressures in all tertiary groups of heavy metals. The results of multiple regression analysis showed that age, BMI, and cadmium concentration in men were risk factors for blood pressure. In women, age and BMI, drinking and smoking, and blood mercury were significantly influenced to blood pressure. Conclusions: Residents living near the Janghang smelter showed high concentrations of blood lead and cadmium, suggesting that they were exposed to high concentrations of heavy metals released from the smelter in the past. Such exposure may have caused some blood pressure increase. Especially, the concentration of cadmium in the case of men and the concentration of mercury in blood in the case of women were found to be significantly related to the increase of blood pressure. The local population should be advised to make efforts to reduce exposure to environmental contaminants, in order to minimize cardiovascular disease, and to pay close attention to any health problems possibly related to toxic metal exposure.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.