• Journal of Information Processing Systems
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• v.15 no.3
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• pp.682-693
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• 2019

The traditional classification methods mostly assume that the data for class distribution is balanced, while imbalanced data is widely found in the real world. So it is important to solve the problem of classification with imbalanced data. In Mahalanobis-Taguchi system (MTS) algorithm, data classification model is constructed with the reference space and measurement reference scale which is come from a single normal group, and thus it is suitable to handle the imbalanced data problem. In this paper, an improved method of MTS-CBPSO is constructed by introducing the chaotic mapping and binary particle swarm optimization algorithm instead of orthogonal array and signal-to-noise ratio (SNR) to select the valid variables, in which G-means, F-measure, dimensionality reduction are regarded as the classification optimization target. This proposed method is also applied to the financial distress prediction of Chinese listed companies. Compared with the traditional MTS and the common classification methods such as SVM, C4.5, k-NN, it is showed that the MTS-CBPSO method has better result of prediction accuracy and dimensionality reduction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.9
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• pp.4518-4540
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• 2019

With the development of IT convergence technology, autonomous driving has gradually developed; however, the vehicle is still operated by the driver, who should always be in good health - but sometimes, this is not the case. It is especially dangerous to drive when drowsy, and unable to fully concentrate on driving, such as when taking certain medicines, or through fatigue. Drowsy driving is at least eight times more dangerous than normal driving, and as dangerous as drunk driving. Previous research has looked at technology to detect drowsiness, in order to wake up drivers when necessary, or to safely stop the vehicle. Furthermore, many studies have been conducted to find out when drowsiness occurs. However, it is more desirable for the driver to take sufficient rest during a break, in order to be able to continue to focus and drive. In other words, it is important to maintain a normal state before drowsiness. In this study, we introduce a sound source to increase driver concentration and prevent drowsiness, another that can improve the quality of sleep, and a system that produces these sound sources. The proposed system has a noise reduction effect of about 15 dB. We have confirmed that the proposed sound induces an EEG of the desired form.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.111-121
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• 2018

Many problems in rotating machinery such as aircraft engines, wind turbines and motors are caused by bearing defects. The abnormalities of the bearing can be detected by analyzing signal data such as vibration or noise, proper pre-processing through a few signal processing techniques is required to analyze their frequencies. In this paper, we introduce the condition monitoring method for diagnosing the failure of the rotating machines by analyzing the vibration signal of the bearing. From the collected signal data, the normal states are trained, and then normal or abnormal state data are classified based on the trained normal state. For preprocessing, a Hamming window is applied to eliminate leakage generated in this process, and the cepstrum analysis is performed to obtain the original signal of the signal data, called the formant. From the vibration data of the IMS bearing dataset, we have extracted 6 statistic indicators using the cepstral coefficients and showed that the application of the Mahalanobis distance classifier can monitor the bearing status and detect the failure in advance.

• Management & Information Systems Review
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• v.37 no.3
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• pp.27-47
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• 2018

In this study, we examine how land use zoning affects the land price controlling other variables such as road-facing condition of the land, land form, land age after its development and land size. We employ geographically weighted regression analysis which reflects spatial dependency as methodology with a data sample of land transaction price data of Jangyu, a new town, in Korea. The results of our empirical analysis show that the respective coefficients of traditional regression and geographically weighted regression are not significantly different. However, after calculating Moran's Index with residuals of both OLS and GWR models, we find that Moran's Index of GWR decreases around 26% compared to that of OLS model, thus improving the problem of spatial autoregression of residuals considerably. Unlike our expectation, though, in both traditional regression and geographically weighted regression where residential exclusive area is used as a reference variable, the dummy variable of the residential land for both housing and shops shows a negative sign. This may be because the residential land for both housing and shops is usually located in the level area while the residential exclusive area is located at the foot of a mountain or on a gentle hill where the residents can have good quality air and scenery. Although the utility of the residential land for both housing and shops is higher than its counterpart's since it has higher floor area ratio, amenity which can be explained as high quality of air and scenery in this study seems to have higher impact in purchase of land for housing. On the other hand, land for neighbourhood living facility seems to be valued higher than any other land zonings used in this research since it has much higher floor area ratio than the two land zonings above and can have a building with up to 5 stories constructed on it. With regard to road-facing condition, land buyers seem to prefer land which faces a medium-width road as expected. Land facing a wide-width road may have some disadvantage in that it can be exposed to noise and exhaust gas from cars and that entrance may not be easy due to the high speed traffic of the road. In contrast, land facing a narrow road can be free of noise or fume from cars and have privacy protected while it has some inconvenience in that entrance may be blocked by cars parked in both sides of the narrow road. Finally, land age variable shows a negative sign, which means that the price of land declines over time. This may be because decline of the land price of Jangyu was bigger than that of other regions in Gimhae where Jangyu, a new town, also belong, during the global financial crisis of 2008.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.46 no.8
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• pp.679-686
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• 2018

In previous paper[1], the authors had compared the current status of European and US rotorcraft development status. In this paper, more detailed procedures have been studied how the European rotorcraft technologies are developed preparing for 21 st century to be more competitive to US. For the systematic procedure to develop next generation aviation technologies including rotorcraft, the pan-European organization, ACARE, was established, and proposed major research agenda for next generation aviation technologies and businesses. Based on the proposed research agenda, all the R&D programs supported by EU are reorganized to be more efficient and competitive. The procedures for the rotorcraft technologies are, first, cabin noise/vibration reduction program (FRIENDCOPTER), second, core technologies to increase of rotor efficiencies and reduce rotor noise (GRC), and then finally to develop fast/long-range next generation rotorcraft (Fast Rotorcraft). As mentioned in previously, all the R&D procedure has to satisfy basic research agenda especially the environmental impact. With theses procedure, the European rotorcraft business had successful achievements not only in current and future market share, but also preparing for next generation rotorcraft platform such as compound and tilt-rotor rotorcraft satisfying market needs.

• Journal of Distribution Science
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• v.12 no.11
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• pp.55-65
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• 2014

Purpose - This study aims to investigate the process of political changes in Japan, which has introduced regulatory policies for large-scale retail stores since the 1930s, as well as the examples, and suggests improvement schemes for our policies in Korea, which imposes restrictions on business hours and forced holidays in accordance with the current Distribution Industry Development Act. Research design, data, and methodology - After examining the political change processes related to large-scale retail stores in japan, this study analyzes individually regulated cases based on the ordinances enacted by each local government. Through case analysis in Japan, this study makes political suggestions that may be helpful for our country substantially. Results - Since there is an obvious possibility that our economic restrictions on business hours and mandatory holidays do not coincide with WTO GATS, it is necessary for large-scale distributors to introduce new social and environmental regulations similar to Japan, rather than imposing controls to restrict free competition and also introduce a policy to induce cooperation with small businesses for the advancement of the distribution industry. Thus, it is desirable to take measures on noise, waste, traffic, and parking for the preservation of the living environment in the surroundings when building new large-scale retail stores. It is also important to establish measures to improve the welfare of neighborhood residents and consumers, create a pleasant urban environment, and make it mandatory to make presentations at public hearings among residents. Furthermore, it should be mandatory to establish regional contribution plans when a retail store is established, and take measures to solve various civil complaints or problems that may occur after entering the market. Moreover, it is desirable for large-scale retail stores that entered the market to induce cooperation in performing various activities in the area with a strong sense that they are all members of the local economy. Conclusions - If introducing social regulations like in Japan, there is probably an advantage that the conflicts seen when large-scale retail stores enter the market are absorbed by adjusting the persons concerned within the established institution in order to establish a field to solve such conflicts systematically. In contrast, there are still concerns regarding chaotic operation without any active attempts to have a conversation with large-scale retail stores and local small merchants due to a sharp conflict among the persons concerned, and if it is a briefing session without any decision of the restrictions on their opening itself, there may be doubts with regard to their effectiveness. Moreover, if the de facto opening is restricted by the introduction of such a briefing session procedure, the choice of whether to protect the existing rights of large-scale retail stores might become problematic. However, such problems could be minimized in a way by forming a separate consultative group for all persons concerned including residents, local governments, professionals, civic organizations, small merchants, and massive retail store-related persons.

• The Journal of Society for e-Business Studies
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• v.8 no.4
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• pp.69-88
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• 2003

In high dimensional data, most of clustering algorithms tend to degrade the performance rapidly because of nature of sparsity and amount of noise. Recently, partial dimensional clustering algorithms have been studied, which have good performance in clustering. These algorithms select the dimensional data closely related to clustering but discard the dimensional data which are not directly related to clustering in entire dimensional data. However, the traditional algorithms have some problems. At first, the algorithms employ grid based techniques but the large amount of grids make worse the performance of algorithm in terms of computational time and memory space. Secondly, the algorithms explore dimensions related to clustering using k-medoid but it is very difficult to determine the best quality of k-medoids in large amount of high dimensional data. In this paper, we propose an efficient partial dimensional clustering algorithm which is called CLIP. CLIP explores dense regions for cluster on a certain dimension. Then, the algorithm probes dense regions on a next dimension. dependent on the dense regions of the explored dimension using incremental projection. CLIP repeats these probing work in all dimensions. Clustering by Incremental projection can prune the search space largely and reduce the computational time considerably. We evaluate the performance(efficiency, effectiveness and accuracy, etc.) of the proposed algorithm compared with other algorithms using common synthetic data.

• Management & Information Systems Review
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• v.36 no.2
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• pp.307-327
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• 2017

Ecological efficiency is an important index measuring and reflecting the sustainable development level of economy, resources and environment in a region. This paper makes an empirical study on the ecological efficiency of 31 provinces in China in 2014 with the three-stage DEA model. The results show that the three indexes, the total investment in environmental governance (Unit: hundred million Yuan), the second industry proportion(%), and per capita automobile ownership (car/ten thousand people) functioning as the external environmental variables have significantly impacted the regional ecological efficiency. Excluding the impact of the external environment and statistical noise, the technical efficiency of regional ecological efficiency has increased from 0.526 to 0.639, and the pure technical efficiency has increased from 0.650 to 0.858, with the scale efficiency decreased from 0.833 to 0.740, accurately reflecting the regional ecological efficiency level. 31 Chinese provinces are classified into four different types according to the pure technical efficiency and scale efficiency. Every region shall, according to the characteristics of its efficiency, emphasize differently on improving the management level or expanding the scale of production so as to improve the ecological efficiency.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.91-107
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• 2012

As the Internet becomes more popular, many people use it to communicate. With the increasing number of personal homepages, blogs, and social network services, people often expose their personal information online. Although the necessity of those services cannot be denied, we should be concerned about the negative aspects such as personal information leakage. Because it is impossible to review all of the past records posted by all of the people, an automatic personal information detection method is strongly required. This study proposes a method to detect or classify online documents that contain personal information by analyzing features that are common to personal information related documents and learning that information based on the Na$\ddot{i}$ve Bayes algorithm. To select the document classification algorithm, the Na$\ddot{i}$ve Bayes classification algorithm was compared with the Vector Space classification algorithm. The result showed that Na$\ddot{i}$ve Bayes reveals more excellent precision, recall, F-measure, and accuracy than Vector Space does. However, the measurement level of the Na$\ddot{i}$ve Bayes classification algorithm is still insufficient to apply to the real world. Lewis, a learning algorithm researcher, states that it is important to improve the quality of category features while applying learning algorithms to some specific domain. He proposes a way to incrementally add features that are dependent on related documents and in a step-wise manner. In another experiment, the algorithm learns the additional dependent features thereby reducing the noise of the features. As a result, the latter experiment shows better performance in terms of measurement than the former experiment does.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.2
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• pp.93-102
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• 2023

Objectives: With the evolution of direct reading sensors, it is possible to monitor several substances through telecommunication. However, there are some limitations on the use of direct reading technologies in the Occupational Safety and Health Act in South Korea, which only applies to detector tubes, noise, heat, and carbon monoxides. The number of chemicals and their amount of use have been continuously increasing in South Korea. The Ministry of Employment and Labor (MoEL) has concerns about worker's health because exposure is only covered for about 1.2% of all distributed chemicals. Using a direct reading monitor with photoionization detectors (PID-DRMs), gases and vapors chemicals can be measured. Based on the data, business owners are able to create corrective strategies, provide better working routines, and select correct respiratory equipment. PID-DRMs are less expensive and easier to handle for an owner voluntarily controlling chemicals emitted in the workplace. However, there are several limitations on using these PID-DRMs to the degree that the MoEL has not been able to select a legal monitor. The aim of this study was to review previous studies related to PID-DRMs and identify the characterization and limitation on PID-DRMs. Methods: To search for related studies on PID-DRMs, key words were used including direct reading monitors/instruments and/or photoionization detectors. Through that, four domestic and 15 international studies were reviewed. Results: Studies on PID-DRMs were conducted by chamber (enclosed, dynamic, walk-in) and in the field (experimental environment, actual environment). The concentration of PID-DRMs and charcoal tubes were compared for a single substance or mixture, or within the PID-DRMs. There was a high correlation between the two concentrations, but it did not meet the accuracy criteria (95% confidence interval, within 25%) of the NIOSH technical report (2012). In addition, differences in measured values occurred according to environmental factors (temperature, humidity) and high concentration, and concentration values tended to be underestimated due to contamination of the sensor. As a way to improve the accuracy of PID concentration, it was proposed to use correction factors, charcoal tube-based correction factors, or to calibrate the PID-DRMs in the same environment as the workplace. Conclusions: PID-DRMs can likely be used by business owners for the purpose of voluntarily managing the workplace environment, and it is expected that it will be possible to use them as legal equipment if a PID sensor can be upgraded and the limitations of the sensor (temperature, humidity, high concentration evaluation, sensor pollution) can be overcome in the near future.