• Journal of Korea Technology Innovation Society
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• v.21 no.1
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• pp.151-200
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• 2018

At the Davos Forum in 2016, the Fourth Industrial Revolution, a reference to cloud Schwab, is dramatically changing our lives, and at its height, self-driving cars are emerging as the talk of the day. But there are still many hurdles to overcome before the nation can successfully introduce and establish self-driving cars. In particular, it is necessary to change the paradigm of the legal system centered on human beings to one that includes artificial intelligence. The stable operation of the self-driving car era requires drastic changes to the people-centric legislation system. That is, it is necessary to collect information on the total number of drivers of self-driving cars (what is available), general vehicles on general roads, civil and criminal liability issues in the event of traffic accidents, and collection of insurance problems concerning autonomous driving vehicles. In this study, a separate bill was proposed to address the various legal issues arising from the operation of self-driving cars from a legislative perspective by considering the domestic laws related to road transport, the current state of legislation on foreign soil and legal issues related to self-driving cars.

• Journal of KIISE
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• v.44 no.9
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• pp.893-907
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• 2017

In safety-critical systems, software defects may have serious consequences. Therefore, defects should be considered during the requirements specification process, which is the first step of a software development lifecycle. Stakeholder requirements that are usually written in natural language are difficult to derived, and there may also be defects due to ambiguity and inaccuracy. To address these issues, we propose a requirement specification method using a standardized Boilerplate and a GSN Model. The Boilerplate is a semi-standard language that follows a predefined format. Due to its ability to provide a consistent representation of the requirements, boilerplate helps stakeholders avoid ambiguities about what they mean and to define the exact meaning of the requirement. Meanwhile, GSN is recognized notation to prepare a Safety Case to prove to authorities that a system is safe. It can be expressed as a functional goal, e.g., Safety Evidence, etc. The proposed study allows an analyst to easily identify a fault from the early stage of the software development lifecycle. The Boilerplate and GSN Model are designed to specify the requirements of safety critical systems and to prove safety conformity through a connection with Safety Evidence. In addition, the proposed approach is also useful to develop secure software by correcting deficiencies in the requirements found during this process.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.8
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• pp.297-306
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• 2018

In this paper, we address how to apply Apache Storm, a distributed stream processing framework, to InfiniBand, a high performance communication device. An easy way to run Storm on InfiniBand is to simply use IPoIP (IP over InfiniBand). However, this method causes a serious CPU load on the node, which is caused by frequent context switches and buffer copies. To solve this problem, we propose a new communication method using InfiniBand's Remote Direct Memory Access (RDMA) function in Storm. First, we design and implement RJ-Netty (RDMA/JXIO Netty), a new framework that replaces Netty, the legacy framework, to exploit RDMA functionality. Second, we reimplement the related classes so that Storm can use both existing Netty and new RJ-Netty. Third, we extend the JXIO server functionality so as to support multi-threading to maximize the performance of RJ-Netty. Experimental results show that the proposed RJ-Netty significantly reduces CPU load while improving message throughput compared to IPoIB as well as Ethernet. This paper is the first attempt to run Apache Storm on InfiniBand, and we believe that it is an excellent research result that improves the performance of Storm by using InfiniBand RDMA.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.34-42
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• 2006

As art analytic method to uncover interesting patterns hidden under a large volume of data, data mining research has been actively done so far in various fields. However, current state-of-the-arts in data mining research have several challenging problems such as being too ad-hoc. The existing techniques are mostly the ones designed for individual problems, so there is no unifying theory applicable for more general data mining problems. In this paper, we address the problem of classification, which is one of significant data mining tasks. Specifically, our objective is to evaluate radial basis function (RBF) model for classification tasks and investigate its usefulness. For evaluation, we analyze the popular Monk's problems which are well-known datasets in data mining research. First, we develop RBF models by using the representational capacity based learning algorithm, and then perform a comparative assessment of the results with other models generated by the existing techniques. Through a variety of experiments, it is empirically shown that the RBF model has not only the superior performance on the Monk's problems but also its modeling process can be controlled in a systematic way, so the RBF model with RC-based algorithm might be a good candidate to handle the current ad-hoc problem.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.577-586
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• 2014

As SNS has increased its influence on the society as a whole, companies also have started to consider how to take advantage of the new service paying specific attention to its characteristics of immediacy, sharability and interactivity. This study aims to circumstantiate the relationship between a task support tool of SNS and task-media fit, user characteristics and performance by focusing on its usage in work field. To address this issue, a Task-Technology Fit model is used to propose a research model considering the characteristics of SNS as a social element, information technology as well as its user characteristics. The outcome shows that job characteristics, virtual competence and media characteristics have a significant influence on task-media fit, whereas virtual competence and SNS characteristics variables have a significant influence on SNS usage. Besides, task-media fit has a significant influence on SNS usage and work performance while SNS usage has a significant influence on work performance. The study suggests that strategic use of SNS helps improve work performance and these individual characteristics should be considered in planning of SNS utilizing strategy.

• Journal of the Korea Institute of Building Construction
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• v.15 no.5
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• pp.515-525
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• 2015

Currently, according to the climate change, serious damage by typhoon has been occurred in the world. In this respect, the research on the prediction model to minimize the damage from various natural disaster has been conducted in several developed countries. In the case of U.S, various models to predict building damage costs have been used widely in many organizations such as insurance companies and governments. In South Korea, although studies regarding damage prediction model according to typhoon have been conducted, the scope has been only limited to consider the property of typhoon. However, it is necessary to consider various factors such as typhoon information, geography, construction environment, and socio-economy factors to predict the damages. Therefore, to address this issue, first, correlation analysis is conducted between various variables based on the data of typhoon from 2003 to 2012. Second, the damage prediction model by using regression analysis is developed based on suggested influence factors. The findings of this study can be utilized to develop the model for predicting the damage costs of buildings by typhoon like HAZUS-MH of US.

• Economic and Environmental Geology
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• v.45 no.2
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• pp.169-180
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• 2012

The ESBs (Environmental Specimen Banks) have monitoring functions for the contemporary environmental qualities and also offer the future generation tangible information on the past environment by preserving the specimens. This entails the sampling of the representative specimen for each distinctive ecosystem, which is performed under a strict and stipulated procedure and a condition that does not allow any change in the component so that a retrospective analysis can be readily done even in the distant future. It has been more than 30 years that some developing countries started collecting a broad spectrum of specimens to vindicate the effectiveness of an environmental policy and to monitor the long-term variations of background concentrations of environmental pollutants. Though being late, the National Institute of Environmental Research (NIER), Korea, has successfully launched the National Environmental Specimen Bank (NESB) in 2009 equipped with its state-of-the-art automated cryogenic tanks. Since then, the researchers at the NESB have been doing their best to excel the existing ESBs around the world by learning and improving the expertise. To do so, they conducted a pilot study for developing and testing their own Standard Operating Procedure (SOP) based on the analysis of the examples of the other ESBs. The problems from the pilot study had been reviewed to improve the SOP to meet the requirements for an ESB, that is to say, preserving representative environmental specimens in cryogenic condition and enhancing the analytical method. Furthermore, they also need to prepare themselves to address the future challenges by providing some additional functions, which makes it distinguishable from the other ESBs. If successful, this will be a step further to be recognized as a full-fledged member of the ESB society of the world.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1141-1141
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• 2001

The aim of the study was to evaluate the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural network (ANN) on the prediction of chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with information relative to moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected with 10 different Foss NIR Systems instruments, which were either standardized or not standardized to one master instrument. The spectra were trimmed to a wavelength range between 1100 and 2498 nm. Two data sets, one standardized (IVAL) and the other not standardized (SVAL) were used as independent validation sets, but 10% of both sets were omitted and kept for later expansion of the calibration database. The remaining samples were combined into one database (n=21,696), which was split into 75% calibration (CALBASE) and 25% validation (VALBASE). The chemical components in the 3 validation data sets were predicted with each model derived from CALBASE using the calibration database before and after it was expanded with 10% of the samples from IVAL and SVAL data sets. Calibration performance was evaluated using standard error of prediction corrected for bias (SEP(C)), bias, slope and R2. None of the models appeared to be consistently better across all validation sets. VALBASE was predicted well by all models, with smaller SEP(C) and bias values than for IVAL and SVAL. This was not surprising as VALBASE was selected from the calibration database and it had a sample population similar to CALBASE, whereas IVAL and SVAL were completely independent validation sets. In most cases, Local and ANN models, but not modified PLS, showed considerable improvement in the prediction of IVAL and SVAL after the calibration database had been expanded with the 10% samples of IVAL and SVAL reserved for calibration expansion. The effects of sample processing, instrument standardization and differences in reference procedure were partially confounded in the validation sets, so it was not possible to determine which factors were most important. Further work on the development of large databases must address the problems of standardization of instruments, harmonization and standardization of laboratory procedures and even more importantly, the definition of the database population.

• Science of Emotion and Sensibility
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• v.9 no.1
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• pp.63-75
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• 2006

This is a basic research aimed at enhancing a brand image by unifying color images of a brand at both online and offline stores. h survey was conducted on color images of online and offline stores to measure the level of consistency between consumers' perception of the color image and the brand's color strategy. A brand preference survey was also performed to shed light on the relationship between the brand preference and the consistency of color images at online and offline stores. This study is committed to building an effective color strategy, based on the brand strategy, through web color planning that is consistent with the offline color image. This paper started with a specific purpose of devising solutions in regard to the prior study, entitled 'Study on Color Strategies in Brand Coffee', which recognizes the need for consistent color images, or integrated color strategies, in online and offline stores. I specifically took the approach of looking at color planning in the stage of designing a website. Two standards were used to analyze emotional and functional aspects of color images: color grading by I.R.I and five communicators of color information by Rouge. Direct visits were made to the offline stores for surveys to address the shortcomings of the prior study, in which offline stimuli were limited to printed materials. The direct visits enabled a study of an overall color image of the offline stores, while providing a set of substantial and specific guidelines for designing colors for a website. I hope this study goes a long way toward enhancing the level of consistency between online and offline color images based on the brand's unique color strategy, and thereby improving the overall level of brand image.

• The KIPS Transactions:PartC
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• v.12C no.5 s.101
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• pp.765-772
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• 2005

In this paper, we propose E-mail sending-server authorization method using a distance estimation algorithm between W addresses to check whether the E-mail sending server is registered in the domain of mail sending server or belongs to the domain for filtering spam mail. This method utilizes the distance between the IP address of sending server and IP addresses registered in the DNS to figure out that the E-mail sending server exists in the domain to filter spam mail. The experimental result of applying the proposed algorithm to sample E-mails gathered in a large size laboratory says that 88 percents of legitimate E-mails and only 10 percents of spam mails are sent by servers in the same domains of senders. The algorithm may be effectively used to block spam mails sent by servers outside of the domains of mail senders. It may be also hired as a temporary E-mail protecting system until the standard E-mail authorization protocol is fully deployed.