• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2853-2873
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• 2013

Over the last few years, one of the most common purposes of smart homes is to provide human centric services in the domain of u-healthcare by analyzing inhabitants' daily living. Currently, the major challenges in activity recognition include the reliability of prediction of each classifier as they differ according to smart homes characteristics. Smart homes indicate variation in terms of performed activities, deployed sensors, environment settings, and inhabitants' characteristics. It is not possible that one classifier always performs better than all the other classifiers for every possible situation. This observation has motivated towards combining multiple classifiers to take advantage of their complementary performance for high accuracy. Therefore, in this paper, a method for activity recognition is proposed by optimizing the output of multiple classifiers with Genetic Algorithm (GA). Our proposed method combines the measurement level output of different classifiers for each activity class to make up the ensemble. For the evaluation of the proposed method, experiments are performed on three real datasets from CASAS smart home. The results show that our method systematically outperforms single classifier and traditional multiclass models. The significant improvement is achieved from 0.82 to 0.90 in the F-measures of recognized activities as compare to existing methods.

• Journal of Agricultural Extension & Community Development
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• v.9 no.2
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• pp.199-213
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• 2002

The purpose of this study uses agricultural knowledge system theory to explore how the extension system in South Korea was developed and have worked well. By agricultural knowledge system we emphasized the dynamic networks of actors, processes of negotiation, and the diverse ways in which knowledge is constructed and performed. It was possible that individuals may participate in and utilize multiple knowledge systems. The knowledge systems reflected the idea that the boundaries between knowledge groups were not closed and that there could be considerable overlap between knowledge systems. The constructions of agricultural knowledge systems thus included social interactions, communication, and the diverse processes individuals employ to create, use, and evaluate multiple types and sources of information. As such, there were six priorities to development agricultural extension system; the linkage between agricultural colleges, Rural Development Administration(RDA), branch of RDA, establishing the research institution of research and extension linkage. exchange research agent with extension agent, developing information technology system, bottom-up approach, the linkage between national project and regional within extension projects, enforcement of informal learning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2354-2370
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• 2015

The advantages of employing SCTP-based Concurrent Multipath Transfer (CMT) have been demonstrated to be very useful for data delivery over multi-homed wireless networks. However, there is still significant ongoing work addressing some remaining limitations and challenges. The most important concern when applying CMT to data delivery is related to handling packet reordering and buffer blocking. Another concern on this topic is that current sender-based CMT solutions seldom consider balancing the overhead and sharing the load between the sender and receiver. This paper proposes a novel Receiver-driven Cooperation-based Concurrent Multipath Transfer solution (CMT-Rev) with the following aims: (i) to balance overhead and share load between the sender and receiver, by moving some functions including congestion and flow control from the sender onto receiver; (ii) to mitigate the data reordering and buffer blocking problems, by using an adaptive receiver-cooperative path aggregation model, (iii) to adaptively transmit packets over multiple paths according to their receiver-inspired sending rate values, by employing a new receiver-aware data distribution scheduler. Simulation results show that CMT-Rev outperforms the existing CMT solutions in terms of data delivery performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.79-95
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• 2016

In order to improve the Quality-of-Service (QoS) of latency sensitive applications in next-generation cellular networks, multi-path is adopted to transmit packet stream in real-time to achieve high-quality video transmission in heterogeneous wireless networks. However, multi-path also introduces two important challenges: out-of-order issue and reordering delay. In this paper, we propose a new architecture based on Software Defined Network (SDN) for flow aggregation and flow splitting, and then design a Multiple Access Radio Scheduling (MARS) scheme based on relative Round-Trip Time (RTT) measurement. The QoS metrics including end-to-end delay, throughput and the packet out-of-order problem at the receiver have been investigated using the extensive simulation experiments. The performance results show that this SDN architecture coupled with the proposed MARS scheme can reduce the end-to-end delay and the reordering delay time caused by packet out-of-order as well as achieve a better throughput than the existing SMOS and Round-Robin algorithms.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.4
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• pp.447-458
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• 2013

The present operating system for the atmospheric monitoring network in the city of Seoul, Korea, has been established since the late 90s by the Korean Ministry of Environment (KMOE). In this research, it was evaluated by the multi-statistical approaches through combinations of time series analysis, correlation matrix, and multiple cluster analysis. Finally, road traffic including resuspended materials can be one of the main sources of particulate matter in the atmosphere. Based on its importance, it will be significant challenges in quantitative evaluation of its contribution to airborne concentrations. The future directions for their amendments such as a new management plan for the source of road dust (including car emissions) were devised and proposed based on the statistical judgements derived in this research.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1400-1420
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• 2012

Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.670-683
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• 2016

Network coding, as a new technique to improve the throughput, is studied combined with multi-relay model in this paper to address the challenges of long distance and power limit in deep space communication. First, an amplify-and-forward relaying approach based on analog network coding (AFNC) is proposed in multi-relay network to improve the capacity for deep space communication system, where multiple relays are introduced to overcome the long distance link loss. The design of amplification coefficients is mathematically formulated as the optimization problem of maximizing SNR under sum-power constraint over relays. Then for a dual-hop relay network with a single source, the optimal amplification coefficients are derived when the multiple relays introduce non-coherent noise. Through theoretic analysis and simulation, it is shown that our approach can achieve the maximum transmission rate and perform better over single link transmission for deep space communication.

• Journal of Information Processing Systems
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• v.18 no.4
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• pp.575-586
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• 2022

Uneven light in real-world causes visual degradation for underexposed regions. For these regions, insufficient consideration during enhancement procedure will result in over-/under-exposure, loss of details and color distortion. Confronting such challenges, an unsupervised low-light image enhancement network is proposed in this paper based on the guidance of the unpaired low-/normal-light images. The key components in our network include super-resolution module (SRM), a GAN-based low-light image enhancement network (LLIEN), and denoising-scaling module (DSM). The SRM improves the resolution of the low-light input images before illumination enhancement. Such design philosophy improves the effectiveness of texture details preservation by operating in high-resolution space. Subsequently, local lightness attention module in LLIEN effectively distinguishes unevenly illuminated areas and puts emphasis on low-light areas, ensuring the spatial consistency of illumination for locally underexposed images. Then, multiple discriminators, i.e., global discriminator, local region discriminator, and color discriminator performs assessment from different perspectives to avoid over-/under-exposure and color distortion, which guides the network to generate images that in line with human aesthetic perception. Finally, the DSM performs noise removal and obtains high-quality enhanced images. Both qualitative and quantitative experiments demonstrate that our approach achieves favorable results, which indicates its superior capacity on illumination and texture details restoration.

• Journal of Families and Better Life
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• v.29 no.5
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• pp.19-32
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• 2011

This study aimed to examine how emotional experience, counselor activity self-efficacy, and job stress affect counselors' burnout. Participants comprising 321 counselors intotal were surveyed on burnout, emotional experience, counselor activity self-efficacy, and job stress. The collected data were analyzed through Cronbach's ${\alpha}$, Pearson's correlation, and stepwise multiple regression. The findings were as follows: 1) Emotional clarity, session management self-efficacy, the job stress of the working environment, counseling challenges self-efficacy and job stress related to interpersonal relationship were significant predictors of counselors' burnout. 2) Counselor activity self-efficacy partly played a mediating role between emotional experience and burnout.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5098-5115
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• 2017

A number of automotive electronics-safety, driver assistance, and infotainment devices-have been deployed in recent vehicles. This raises new challenges regarding in-vehicular network arbitration. A performance analysis of non-destructive arbitration has revealed a fairness issue. The arbitration prioritizes without collisions, despite multiple simultaneous transmissions; however, the performances of the highest priority node and the lowest priority node are very different. In this paper, an ID-rotation arbitration method to solve the arbitration-fairness problem is proposed. The proposed algorithm was applied to several engine control units (ECUs), including a controller area network (CAN) controller. Experimental results showed that the algorithm improved the fairness as well as the total throughput within a specific performance constraint.