• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.411-418
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• 2020

In the field of information security, IDS(Intrusion Detection System) is normally classified in two different categories: signature-based IDS and anomaly-based IDS. Many studies in anomaly-based IDS have been conducted that analyze network traffic data generated in cyberspace by machine learning algorithms. In this paper, we studied pre-processing methods to overcome performance degradation problems cashed by rare classes. We experimented classification performance of a Machine Learning algorithm by reconstructing data set based on rare classes and semi rare classes. After reconstructing data into three different sets, wrapper and filter feature selection methods are applied continuously. Each data set is regularized by a quantile scaler. Depp neural network model is used for learning and validation. The evaluation results are compared by true positive values and false negative values. We acquired improved classification performances on all of three data sets.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.27-35
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• 2021

In this paper, we propose a new stacking ensemble framework for deep learning models which reflects the distribution of label embeddings. Our ensemble framework consists of two phases: training the baseline deep learning classifier, and training the sub-classifiers based on the clustering results of label embeddings. Our framework aims to divide a multi-class classification problem into small sub-problems based on the clustering results. The clustering is conducted on the label embeddings obtained from the weight of the last layer of the baseline classifier. After clustering, sub-classifiers are constructed to classify the sub-classes in each cluster. From the experimental results, we found that the label embeddings well reflect the relationships between classification labels, and our ensemble framework can improve the classification performance on a CIFAR 100 dataset.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.159-168
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• 2021

As the information age enters, the use of biometrics using the body is gradually increasing because it is very important to accurately recognize and authenticate each individual's identity for information protection. Among them, finger vein authentication technology is receiving a lot of attention because it is difficult to forge and demodulate, so it has high security, high precision, and easy user acceptance. However, the accuracy may be degraded depending on the algorithm for identification or the surrounding light environment. In this paper, we designed and manufactured a side-type finger vein recognizer that is highly versatile among finger vein measuring devices, and authenticated using the deep learning model of DenseNet-201 for high accuracy and recognition rate. The performance of finger vein authentication technology according to the influence of the infrared light source used and the surrounding visible light was analyzed through simulation. The simulations used data from MMCBNU_6000 of Jeonbuk National University and finger vein images taken directly were used, and the performance were compared and analyzed using the EER.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.7-14
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• 2021

The emergence of the automated smart grid has become an essential device for responding to these problems and is bringing progress toward a smart grid-based society. Smart grid is a new paradigm that enables two-way communication between electricity suppliers and consumers. Smart grids have emerged due to engineers' initiatives to make the power grid more stable, reliable, efficient and safe. Smart grids create opportunities for electricity consumers to play a greater role in electricity use and motivate them to use electricity wisely and efficiently. Therefore, this study focuses on power demand management through machine learning. In relation to demand forecasting using machine learning, various machine learning models are currently introduced and applied, and a systematic approach is required. In particular, the GP learning model has advantages over other learning models in terms of general consumption prediction and data visualization, but is strongly influenced by data independence when it comes to prediction of smart meter data.

• 한국사회정책
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• v.20 no.2
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• pp.69-96
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• 2013

This paper is to critically review the economic reasoning of non-sustainability of welfare state due to its intrinsic incentive problems and to see how the nordic welfare state responds to them. The welfare state as a political design of state to pursue equality has social insurance as its main economic function. It survives market failure of private insurance to contribute to human capital investment and industrial restructuring. The universal tax-financed welfare state, however, has the problem of tragedy of commons such as reduced work incentive and work ethics. But, the existing nordic welfare state overcomes it through employment-focused policy arrangements, maintenance of work ethics and benefits moral, incentive mechanism of wage-compression, public educational investment and its complementation with social security. The Nordic model shows that problems of incentive and moral are not about those of theory and reasoning, but about their reality which policies and institutions could respond to.

• Korean Journal of Labor Studies
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• v.23 no.2
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• pp.231-276
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• 2017

Chinese society faces increasing outbreaks of labor disputes, may of which are usually characterized as 'the highest level since the establishment of PRC'. Guangdong Province is the hottest place for increasing labor disputes as well as for flexible responses by the local government and labor agencies. Interest-pursuit bargaining model becomes one of the outstanding characteristics for recent labor disputes in Guangdong Province. Chinese central government promulgated well-managed policy package for labor dispute settlement in 2015. Guangdong Province government went one step further by introducing to institutionalize labor dispute settlement. To channel labor dispute conflicts into manageable direction, reliability and capacity of bottom level trade unions become much more essential for the authorities than before. Guangdong Confederation of Trade Unions leads some important experiments of trade union reforms. Employment of 'social cadres' of trade unions by local trade union organizations is the most outstanding experiment to satisfy increasing needs from bottom level ordinary workers who don't have efficient union organizations. It needs to be seen whether changing labor policies go beyond the limits of 'security priority principle'.

• The Korean Journal of Physiology and Pharmacology
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• v.25 no.2
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• pp.131-137
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• 2021

Aging is the process spontaneously occurred in living organisms. Cardiac fibrosis is a pathophysiological process of cardiac aging. Mangiferin is a well-known C-glucoside xanthone in mango leaves with lots of beneficial properties. In this study, rat model of cardiac fibrosis was induced by injected with 150 mg/kg/d D-galactose for 8 weeks. The age-related cardiac decline was estimated by detecting the relative weight of heart, the serum levels of cardiac injury indicators and the expression of hypertrophic biomakers. Cardiac oxidative stress and local inflammation were measured by detecting the levels of malondialdehyde, enzymatic antioxidant status and proinflammatory cytokines. Cardiac fibrosis was evaluated by observing collagen deposition via masson and sirius red staining, as well as by examining the expression of extracellular matrix proteins via Western blot analysis. The cardiac activity of profibrotic TGF-β1/p38/MK2 signaling pathway was assessed by measuring the expression of TGF-β1 and the phosphorylation levels of p38 and MK2. It was observed that mangiferin ameliorated D-galactose-induced cardiac aging, attenuated cardiac oxidative stress, inflammation and fibrosis, as well as inhibited the activation of TGF-β1/p38/MK2 signaling pathway. These results showed that mangiferin could ameliorate cardiac fibrosis in D-galactose-induced aging rats possibly via inhibiting TGF-β/p38/MK2 signaling pathway.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.50-55
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• 2021

Multi-path system is a system in which utilizes various networks simultaneously. It is expected that multi-path system can enhance communication speed, reliability, security of network. In this paper, we focus on path selection in multi-path system. To select optimal path, we propose deep reinforcement learning algorithm which is rewarded by the round-trip-time (RTT) of each networks. Unlike multi-armed bandit model, deep Q learning is applied to consider rapidly changing situations. Due to the delay of RTT data, we also suggest compensation algorithm of the delayed reward. Moreover, we implement testbed learning server to evaluate the performance of proposed algorithm. The learning server contains distributed database and tensorflow module to efficiently operate deep learning algorithm. By means of simulation, we showed that the proposed algorithm has better performance than lowest RTT about 20%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1187-1192
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• 2020

The dronebot combat system is a representative model of the future battlefield in the 4th industrial revolution. In dronebot, unmanned reconnaissance tankrobot can minimize human damage and reduce cost with higher combat power than humans. However, since the battlefield environment is very complex such as obstacles and enemy situations, it is also necessary for the pilot to control the tankrobot. Tankrobot are robots with new ICT technology, capable of hacking attacks, and if there is an abnormality in control, it can pose a threat to manipulation and control. A Bluetooth sniffing attack was performed on the communication section of the tankrobot and the controller to introduce a vulnerability to Bluetooth, and a countermeasure using MAC address exposure prevention and communication section encryption was proposed as a security measure. This paper first presented the vulnerability of tankrobot to be operated in future military operations, and will be the basic data that can be used for defense dronebot units.

• Smart Media Journal
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• v.11 no.1
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• pp.9-16
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• 2022

With the development of online commercializing technology and the growth of online market, it has become extremely important for companies that aim to commercialize their products and services to control time and resources. Even when a single company has control over the entire process, it is necessary to maintain the efficiency among the process of development. In particular, when there is a lot of cooperation throughout the course of development, requiring many parties to communicate with each other, the issue of declining efficiency becomes much clearer. The timing of when to launch a product or service has become just as important as completing and testing them for companies. Companies have developed new tools to prevent situations that may lead to inefficiency in the development process, including an increase in the amount of resource used or issues with security maintenance. However, there is a lack of proper measurement tool that assesses what kind of additional benefits the entire process of the company is bringing, or whether or not the processes need to be improved in certain areas. Thus, this study aims to suggest a method to measure efficiency, to provide an empirical efficiency measurement method for the development process of online content.