• Journal of Computing Science and Engineering
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• v.7 no.2
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• pp.112-121
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• 2013

The last years have seen a rise of interest in using electroencephalography-based brain computer interfacing methodology for investigating non-medical questions, beyond the purpose of communication and control. One of these novel applications is to examine how signal quality is being processed neurally, which is of particular interest for industry, besides providing neuroscientific insights. As for most behavioral experiments in the neurosciences, the assessment of a given stimulus by a subject is required. Based on an EEG study on speech quality of phonemes, we will first discuss the information contained in the neural correlate of this judgement. Typically, this is done by analyzing the data along behavioral responses/labels. However, participants in such complex experiments often guess at the threshold of perception. This leads to labels that are only partly correct, and oftentimes random, which is a problematic scenario for using supervised learning. Therefore, we propose a novel supervised-unsupervised learning scheme, which aims to differentiate true labels from random ones in a data-driven way. We show that this approach provides a more crisp view of the brain states that experimenters are looking for, besides discovering additional brain states to which the classical analysis is blind.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1254-1260
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• 2019

Recently, 5G cellular systems have been attracted great attention as a key enabler for Industry 4.0. In this paper, we propose a novel random access based on pilot-assisted opportunistic transmission to support internet-of-things (IoT) scenario in cellular networks. A key feature of our proposed scheme is to enable each of IoT devices to attempt opportunistic transmission of its data packet in Step 3 with randomly selected uplink pilot signal. Both the opportunistic transmission and the pilot randomization in Step 3 are effective to significantly mitigate the occurrence of packet collisions. We mathematically analyze our proposed scheme in terms of packet collision probability and uplink resource efficiency. Through simulations, we verify the validity of our analysis and evaluate the performance of our proposed scheme. Numerical results show that our proposed scheme outperforms other competitive schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.524-539
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• 2014

To investigate schemes of secret key generation from Ultra-wideband (UWB) channel, we study a statistical characterization of UWB outdoor channel for a campus playground scenario based on extensive measurements. Moreover, an efficient secret key generation mechanism exploiting multipath relative delay is developed, and verification of this algorithm is conducted in UWB Line-of-sight (LOS) outdoor channels. For the first time, we compare key-mismatch probability of UWB indoor and outdoor environments. Simulation results demonstrate that the number of multipath proportionally affects key generation rate and key-mismatch probability. In comparison to the conventional method using received signal strength (RSS) as a common random source, our mechanism achieves better performance in terms of common secret bit generation. Simultaneously, security analysis indicates that the proposed scheme can still guarantee security even in the sparse outdoor physical environment free of many reflectors.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.67-70
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• 1998

In this paper, an interference analyzer for communication and/or broadcasting services is developed and presented based on Monte Carlo technique, which is now under study in the International Telecommunication Union(ITU). Monte Carlo technology is a statistical approach which functions by considering many trials. For each simulation trial, a scenario is built up using a number of different random variables, such as signal and interference strengths, transmitting and receiving antenna heights, antenna gains, etc.. Furthermore, this paper shows and application example of the analyzer to examine interference influence of the PCS(IS-95) base stations affecting to the IMT-2000 FDD base station, depending on serveral service environments like rural, suburban, and urban areas. The wave propagation model used in this simulation is the modified Hata model, which is known to the suitable to Korean environments.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.2
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• pp.121-128
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• 2004

This paper presents a new approach for determining an accurate incentive levels of Direct Load Control (DLC) program using sequential Monte Carlo Simulation (MCS) techniques. The economic analysis of DLC resources needs to identify the hourly-by-hourly expected energy-not-served resulting from the random outage characteristics of generators as well as to reflect the availability and duration of DLC resources, which results the computational explosion. Therefore, the conventional methods are based on the scenario approaches to reduce the computation time as well as to avoid the complexity of economic studies. In this paper, we have developed a new technique based on the sequential MCS to evaluate the required expected load control amount in each hour and to decide the incentive level satisfying the economic constraints. In addition, the mathematical formulation for DLC programs' economic evaluations are developed. To show the efficiency and effectiveness of the suggested method, the numerical studies have been performed for the modified IEEE reliability test system.

• ETRI Journal
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• v.39 no.3
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• pp.364-372
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• 2017

For the reliability of controllers in a software defined network (SDN), a dynamic and self-learning schedule method (DSL) is proposed. This method is original and easy to deploy, and optimizes the combination of multiple controllers. First, we summarize multiple controllers' combinations and schedule problems in an SDN and analyze its reliability. Then, we introduce the architecture of the schedule method and evaluate multi-controller reliability, the DSL method, and its optimized solution. By continually and statistically learning the information about controller reliability, this method treats it as a metric to schedule controllers. Finally, we compare and test the method using a given testing scenario based on an SDN network simulator. The experiment results show that the DSL method can significantly improve the total reliability of an SDN compared with a random schedule, and the proposed optimization algorithm has higher efficiency than an exhaustive search.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.47-57
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• 2015

Recently, Internet of Things (IoT) have become popular for research and development in many areas. IoT makes a new intelligent network between things, between things and persons, and between persons themselves. Social network service technology is in its infancy, but, it has many benefits. Adjacent users in a social network tend to trust each other more than random pairs of users in the network. In this paper, we propose recommendation technique using social network in Internet of Things environment. We study previous researches about information recommendation, IoT, and social IoT. We proposed SIoT_P(Social IoT Prediction) using social relationships and item-based collaborative filtering. Also, we proposed SR(Social Relationship) using four social relationships (Ownership Object Relationship, Co-Location Object Relationship, Social Object Relationship, Parental Object Relationship). We describe a recommendation scenario using our proposed method.

• Korean System Dynamics Review
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• v.12 no.1
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• pp.115-130
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• 2011

This study shows the operational availability(Ao) analysis of the supply chain with maintenance functions using the system dynamics simulation. The simulation uses 60 equipments which are serial systems composed by 4 major components. And every entities are connected each other by causal loops. So whole simulation executed like one organic system. Specially we consider 2 constraints, one is the number of spare parts and the other is maintenance capacity level. 2 constraints have 11 levels each so the simulation has 121(11*11) scenarios which scenario has 30 different random number seed. The simulation executed total 3,630(11*11*30) times. We analysis average Ao of total equipments by 121 scenarios and additionally the regression of the average Ao and 2 constraints. As the result, we can get the more accurate values by the system dynamics simulation than the regression to analysis complex system like the supply chain with maintenance functions.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3150-3152
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• 1999

The efficient representation and encoding of signals with limited resources, e.g., finite storage capacity and restricted transmission bandwidth, is a fundamental problem in technical information processing systems. Typically under realistic circumstances, the encoding and communication of message has to deal with different sources of noise and disturbances. In this paper, I propose a unifying approach to data compression by robust vector quantization, which explicitly deals with channel noise, and random elimination of prototypes. The resulting algorithm is able to limit the detrimental effect of noise in a very general communication scenario. In this paper, based on the robust vector quantization I have an experiment about speech coding.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.49
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• pp.125-133
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• 1999

Nonrecurring congestions are generally caused by random or less predictable events, such as accidents, spilled loads stalled or broken-down vehicles that, temporarily reduce the capacity of the freeway. The purpose of this paper is to present the effect of incidents on the traffic congestion on the urban freeway by simulation method. The simulation scenario is composed of two level traffic conditions, two level incident severities, and eight level incident durations. After incident, the recovering duration to the normal traffic flow, increased by linear of incident duration. Total vehicles travel time increased and average travel speed decreased by squares curve of incident duration. Considering incident impacts, incident management system is evaluated the major function of the urban freeway traffic management system. Also, necessary the related research to detect, verify, and develop effective response strategies for traffic incidents.