• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4611-4624
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• 2020

Future network scenario will be a heterogeneous wireless network environment composed of multiple networks and multimode terminals (MMT). Seamless switching and optimal connectivity for MMT among different networks and different services become extremely important. Here, a vertical handoff algorithm combined an improved entropy weighting method based on grey relational analysis (GRA) is proposed. In which, the improved entropy weight method is used to obtain the objective weights of the network attributes, and GRA is done to rank the candidate networks in order to choose the best network. Through simulation and comparing the results with other vertical handoff decision algorithms, the number of handoffs and reversal phenomenon are reduced with the proposed algorithm, which shows a better performance.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.233-234
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• 2016

본 프로젝트는 편안하고 안전하게 세상과 소통하고 관심사를 공유할 수 있는 커뮤니티 사이트이다. 게시글에 수명을 설정하여 자동으로 글이 삭제되는 기능을 통해 사용자의 보안성을 향상시키며, 기본적으로 닉네임을 사용하여 안전한 익명성을 보장한다. 즉, 자동으로 게시글이 삭제되는 커뮤니티 웹 사이트로 사용자들의 일상, 관심사, 정보 공유 등을 게시글을 통해 공유하고 소통할 수 있고, 커뮤니티 활동에 따라 마일리지를 누적하여 게시글의 기본 수명을 연장 할 수도 있다.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.236-255
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• 2017

The rapid growth of smart devices demands an enhanced throughput for network connection sustainability during mobility. However, traditional wireless network architecture suffers from mobility management issues. In order to resolve the traditional mobility management issues, we propose a novel architecture for future wireless access network based on software-defined network (SDN) by using the advantage of network function virtualization (NFV). In this paper, network selection approach (NSA) has been introduced for mobility management that comprises of acquiring the information of the underlying networking devices through the OpenFlow controller, percepts the current network behavior and later the selection of an appropriate action or network. Furthermore, mobility-related scenarios and use cases to analyze the implementation aspects of the proposed architecture are provided. The simulation results confirm that the proposed scenarios have obtained a seamless mobility with enhanced throughput at minimum packet loss as compared to the existing IEEE 802.11 wireless network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4203-4223
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• 2021

Accelerated by the Internet of Things (IoT), the need for further technical innovations and developments within wireless communications beyond the fifth generation (B5G) networks is up-and-coming in the past few years. High altitude platform station (HAPS) communication is expected to achieve such high levels that, with high data transfer rates and low latency, millions of devices and applications can work seamlessly. The HAPS has emerged as an indispensable component of next-generations of wireless networks, which will therefore play an important role in promoting massive IoT interconnectivity with 6G. The performance of communication and key technology mainly depend on the characteristic of channel, thus we propose an efficient Markov chain based channel model, then analyze the HAPS communication system's uplink capability and swing effect through experiments. According to the simulation results, the efficacy of the proposed scheme is proven to meet the requirements of ubiquitous connectivity in future IoT enabled by 6G.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.810-831
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• 2019

Recently, continuous dimensional emotion recognition from audiovisual clues has attracted increasing attention in both theory and in practice. The large amount of data involved in the recognition processing decreases the efficiency of most bimodal information fusion algorithms. A novel algorithm, namely the incomplete Cholesky decomposition based kernel cross factor analysis (ICDKCFA), is presented and employed for continuous dimensional audiovisual emotion recognition, in this paper. After the ICDKCFA feature transformation, two basic fusion strategies, namely feature-level fusion and decision-level fusion, are explored to combine the transformed visual and audio features for emotion recognition. Finally, extensive experiments are conducted to evaluate the ICDKCFA approach on the AVEC 2016 Multimodal Affect Recognition Sub-Challenge dataset. The experimental results show that the ICDKCFA method has a higher speed than the original kernel cross factor analysis with the comparable performance. Moreover, the ICDKCFA method achieves a better performance than other common information fusion methods, such as the Canonical correlation analysis, kernel canonical correlation analysis and cross-modal factor analysis based fusion methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5410-5426
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• 2019

With the advent of the fifth-generation (5G) era, Massive multiple-input multiple-output (MIMO) relay systems have experienced the rapid development. Recently, the performance analysis models of Massive MIMO relay systems have been proposed, which are mostly based on Rayleigh fading channels. In order to create a more suitable model for 5G Internet of Things scenarios, our study is based on the Rician fading channels, where line-of-sight (LOS) path exists in the channels. In this paper, we assume the channel state information (CSI) is perfect. In this case, we use statistical information to derive the analytical exact closed-form expression for the achievable sum rate of the uplink for the Massive MIMO two-hop relay system over Rician fading channels. Moreover, considering the different communication scenarios, we derive the analytical exact closed-form expression for the achievable sum rates of the uplink for other three scenarios. Finally, based on these expressions, we make simulations and analyze the performance under different transmit powers and Rician-factors, which provides a theoretical basis and reference for further research.

• Journal of Society of Preventive Korean Medicine
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• v.21 no.1
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• pp.95-106
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• 2017

Objectives : Although interest in preventive medicine has increased recently, "Mibyeong", the preventive concept of Korean medicine, is still unfamiliar to the general public. Therefore, this study aims to investigate the concept of Mibyeong and users used on the Internet. Methods : Naver (www.naver.com), which has the highest ranking in terms of market share, number of visitors, search time share, and community category share, has been selected as a search target and jisik-iN Q&A and posts of cafe about Mibyeong were searched for recently approximately 6 years. Results : 105 cases of Jisik-iN Q&A and 283 cases of cafe posts were searched. Overall, the number of Jisik-iN Q&A and cafe posts's Mibyeong term usage was the highest in 2013. In the Internet user category, Mibyeong Term was used most commonly in the Jisik-iN Q&A by Korean medicine related medical personnel (29 cases, 28%) and in the cafe other health-related workers (87cases, 31%). In Mibyeong related cafe classification, Information Exchange (220 cases, 77%) was the most frequent and besides 39 cases (14%) used in Operation of Medical Institutions. And the concept of Mibyeong was often used as symptom-based rather than diagnostic test or disease (Cafe posts 52%, Jisik-iN Q&A 70%), in particular, topic of Mibyeong related Jisik-iN Q&A was used in the order of pain (31 cases, 16%), cancer (17 cases, 9%), fatigue (11 cases, 6%). Conclusions : This study has significance as basic research data of general Internet user group and can be used as fundamental data for awareness promotion, publicity and necessity of Mibyeong.

• Journal of Chest Surgery
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• v.51 no.2
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• pp.85-91
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• 2018

Background: The huge improvements in the speed of data transmission and the increasing amount of data available as the Internet has expanded have made it easy to obtain information about any disease. Since pneumothorax frequently occurs in young adolescents, patients often search the Internet for information on pneumothorax. Methods: This study analyzed an Internet community for exchanging information on pneumothorax, with an emphasis on the importance of accurate information and doctors' role in providing such information. Results: This study assessed 599,178 visitors to the Internet community from June 2008 to April 2017. There was an average of 190 visitors, 2.2 posts, and 4.5 replies per day. A total of 6,513 posts were made, and 63.3% of them included questions about the disease. The visitors mostly searched for terms such as 'pneumothorax,' 'recurrent pneumothorax,' 'pneumothorax operation,' and 'obtaining a medical certification of having been diagnosed with pneumothorax.' However, 22% of the pneumothorax-related posts by visitors contained inaccurate information. Conclusion: Internet communities can be an important source of information. However, incorrect information about a disease can be harmful for patients. We, as doctors, should try to provide more in-depth information about diseases to patients and to disseminate accurate information about diseases in Internet communities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4549-4566
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• 2017

This work presents a novel facial descriptor, which is named as multiscale adaptive local directional texture pattern (MALDTP) and employed for expression recognition. We apply an adaptive threshold value to encode facial image in different scales, and concatenate a series of histograms based on the MALDTP to generate facial descriptor in term of Gabor filters. In addition, some dedicated experiments were conducted to evaluate the performance of the MALDTP method in a person-independent way. The experimental results demonstrate that our proposed method achieves higher recognition rate than local directional texture pattern (LDTP). Moreover, the MALDTP method has lower computational complexity, fewer storage space and higher classification accuracy than local Gabor binary pattern histogram sequence (LGBPHS) method. In a nutshell, the proposed MALDTP method can not only avoid choosing the threshold by experience but also contain much more structural and contrast information of facial image than LDTP.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6080-6096
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• 2019

Text classification is one of the fundamental techniques in natural language processing. Numerous studies are based on text classification, such as news subject classification, question answering system classification, and movie review classification. Traditional text classification methods are used to extract features and then classify them. However, traditional methods are too complex to operate, and their accuracy is not sufficiently high. Recently, convolutional neural network (CNN) based one-hot method has been proposed in text classification to solve this problem. In this paper, we propose an improved method using CNN based skip-gram method for Chinese text classification and it conducts in Sogou news corpus. Experimental results indicate that CNN with the skip-gram model performs more efficiently than CNN-based one-hot method.