• Journal of Korean Society of Water and Wastewater
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• v.31 no.3
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• pp.249-256
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• 2017

Recently, application areas based on M2M (Machine-to-Machine communications) and IoT (Internet of Things) technologies are expanding rapidly. Accordingly, water flow and water quality management improvements are being pursued by applying this technology to water and sewage facilities. Especially, water management will collect and store accurate data based on various ICT technologies, and then will expand its service range to remote meter-reading service using smart metering system. For this, the error in flow rate data transmitting should be minimized to obtain credibility on related additional service system such as real time water flow rate analysis and billing. In this study, we have identified the structural problems in transmitting process and protocol to minimize errors in flow rate data transmission and its handling process which is essential to water supply pipeline management. The result confirmed that data acquisition via communication system is better than via analogue current values and pulse, and for communication method case, applying the industrial standard protocol is better for minimizing errors during data acquisition versus applying user assigned method.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1471-1478
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• 2016

In this study, the system to manage the power automatically was implemented by using Arduino, Raspberry pi, and Beacon technologies. Before the research, pre-research was carried out with the analysis on the existing power management systems in the market in order to find a solution to reduce burdens from standby power and power waste with the increase of electric charges. The system is designed to be able to deliver and receive data through IEEE 802.15.4 wireless protocol, by using Xbee module. Arduino was tested to verify whether it is able to control SSR(Solid State Relay), and it was found that there is no problem. Meanwhile, it was also tested whether it is possible to organize a star topology network through Arduino and Raspberry Pi, and it was confirmed that normal wireless communication is possible through IEEE 802.15.4 wireless protocol. It is designed that the signal from Android smartphone application is to be delivered to Raspberry Pi and then, to be delivered to Arduino through Xbee so that Arduino could control SSR. In addition to this, wireless protocol required to control Arduino with Raspberry Pi is also designed and applied to this research.

• Annual Conference of KIPS
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• 2015.04a
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• pp.909-911
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• 2015

최근 사회적으로 IoT(Internet of Things, 사물인터넷)가 떠오르며 LBS(위치기반서비스) 시장에 대한 이슈로 인해 근거리 위치 인식 기술을 적용한 Beacon(비콘)이 많은 관심을 받고 있다. 이러한 관심에도 불구하고 아직 현재까지는 실질적으로 제공되는 서비스가 다양하지 않다는 문제가 있다. 우리는 본 논문에서 사용자의 라이프 스타일에 따라 다양하게 이용할 수 있는 비콘 활용 애플리케이션을 기획하였다. 이 방법은 비콘을 통해 모든 사람들에게 일괄적으로 같은 서비스를 제공하는 것이 아니라 사용자마다 자신이 지정한 다른 서비스를 제공하여 기존에 문제가 되었던 상기 문제를 해결할 수 있다. 제안하는 방법은 지정한 곳 근처에 가면 자신이 저장한 메모 알림을 주는 기능, 위치를 찾아 주는 기능, 일정 거리 내로 접근한 사용자의 정보를 기록하는 기능 등이 있어 이를 통해 유기견 방지, 아이의 하교 확인 등의 다양한 서비스를 제공할 수 있다는 점에서 효과적일 것으로 사료된다. 본 연구에서는 제안하는 방법의 기획의도 및 동기, 관련 연구 및 응용, 제안하는 방법, 예상 콘텐츠 시나리오, 기대효과, 결론을 소개하고자 한다.

• Journal of Information Processing Systems
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• v.14 no.6
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• pp.1494-1507
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• 2018

Intelligent human identification using face information has been the research hotspot ranging from Internet of Things (IoT) application, intelligent self-service bank, intelligent surveillance to public safety and intelligent access control. Since 2D face images are usually captured from a long distance in an unconstrained environment, to fully exploit this advantage and make human recognition appropriate for wider intelligent applications with higher security and convenience, the key difficulties here include gray scale change caused by illumination variance, occlusion caused by glasses, hair or scarf, self-occlusion and deformation caused by pose or expression variation. To conquer these, many solutions have been proposed. However, most of them only improve recognition performance under one influence factor, which still cannot meet the real face recognition scenario. In this paper we propose a multi-scale parallel convolutional neural network architecture to extract deep robust facial features with high discriminative ability. Abundant experiments are conducted on CMU-PIE, extended FERET and AR database. And the experiment results show that the proposed algorithm exhibits excellent discriminative ability compared with other existing algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5425-5448
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• 2018

Wireless sensor network has been widely used in Internet of Things (IoT) applications to support large and dense networks. As sensor nodes are usually tiny and provided with limited hardware resources, the existing multiple access methods, which involve high computational complexity to preserve the protocol performance, is not available under such a scenario. In this paper, we propose an intelligent Medium Access Control (MAC) protocol selection scheme based on machine learning in wireless sensor networks. We jointly consider the impact of inherent behavior and external environments to deal with the application limitation problem of the single type MAC protocol. This scheme can benefit from the combination of the competitive protocols and non-competitive protocols, and help the network nodes to select the MAC protocol that best suits the current network condition. Extensive simulation results validate our work, and it also proven that the accuracy of the proposed MAC protocol selection strategy is higher than the existing work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3365-3383
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• 2021

The rapid growth of data has successfully promoted the development of modern information and communication technologies, which are used to process data generated by public urban departments and citizens in modern cities. In specific application areas where the ciphertext of messages generated by different users' needs to be transmitted, the concept of broadcast encryption is important. It can not only improve the transmission efficiency but also reduce the cost. However, the existing schemes cannot entirely ensure the privacy of receivers and dynamically adjust the user authorization. To mitigate these deficiencies, we propose an efficient, secure identity-based broadcast encryption scheme that achieves direct revocation and receiver anonymity, along with the analysis of smart grid solutions. Moreover, we constructed a security model to ensure wireless data transmission under cloud computing and internet of things integrated devices. The achieved results reveal that the proposed scheme is semantically secure in the random oracle model. The performance of the proposed scheme is evaluated through theoretical analysis and numerical experiments.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.145-152
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• 2021

In the Recent times, various technological enhancements in the field of artificial intelligence and big data has been noticed. This advancement coupled with the evolution of the 5G communication and Internet of Things technologies, has helped in the development in the domain of smart mine construction. The development of unmanned vehicles with enhanced and smart scheduling system for open-pit mine transportation is one such much needed application. Traditional open-pit mining systems, which often cause vehicle delays and congestion, are controlled by human authority. The number of sensors has been used to operate unmanned cars in an open-pit mine. The sensors haves been used to prove the real-time data in large quantity. Using this data, we analyses and create an improved transportation scheduling mechanism so as to optimize the paths for the vehicles. Considering the huge amount the data received and aggregated through various sensors or sources like, the GPS data of the unmanned vehicle, the equipment information, an intelligent, and multi-target, open-pit mine unmanned vehicle schedules model was developed. It is also matched with real open-pit mine product to reduce transport costs, overall unmanned vehicle wait times and fluctuation in ore quality. To resolve the issue of scheduling the transportation, we prefer to use algorithms based on artificial intelligence. To improve the convergence, distribution, and diversity of the classic, rapidly non-dominated genetic trial algorithm, to solve limited high-dimensional multi-objective problems, we propose a decomposition-based restricted genetic algorithm for dominance (DBCDP-NSGA-II).

• Journal of Internet Computing and Services
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• v.23 no.5
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• pp.17-23
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• 2022

Network slicing is a promising paradigm and significant evolution for adjusting the heterogeneous services based on different requirements by placing dynamic virtual network functions (VNF) forwarding graph (VNFFG) and orchestrating service function chaining (SFC) based on criticalities of Quality of Service (QoS) classes. In system architecture, software-defined networks (SDN), network functions virtualization (NFV), and edge computing are used to provide resourceful data view, configurable virtual resources, and control interfaces for developing the modified deep reinforcement learning agent (MDRL-A). In this paper, task requests, tolerable delays, and required resources are differentiated for input state observations to identify the non-critical/critical classes, since each user equipment can execute different QoS application services. We design intelligent slicing for handing the cross-domain resource with MDRL-A in solving network problems and eliminating resource usage. The agent interacts with controllers and orchestrators to manage the flow rule installation and physical resource allocation in NFV infrastructure (NFVI) with the proposed formulation of completion time and criticality criteria. Simulation is conducted in SDN/NFV environment and capturing the QoS performances between conventional and MDRL-A approaches.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.314-322
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• 2022

During the shipbuilding process, many blocks are moved between shipyard workshops by block carrying vehicles called a transporter. Because block logistics management is one of the essential factors in enhancing productivity, it is necessary to manage block information with the transporter that moves it. Currently, because a large amount of data per day are collected from sensors attached to blocks and transporters via IoT infrastructure installed in shipyards, automated methods are needed to analyze them. Therefore, in this study, we developed an algorithm that can automatically match the transporter and the working block based on the GPS sensor data. By comparing the distance between the transporter and the blocks calculated from the Haversine formula, the block is found which is moved by the transporter. In this process, since the time of the measured data of moving objects is different, the time standard for calculating the distance must be determined. The developed algorithm was verified using actual data provided by the shipyard, and the correct result was confirmed with the distance based on the moving time of the transporter.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.49-59
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• 2020

As technologies have been developing, our lives are getting easier. Today we are surrounded by the new technologies such as AI and IoT. Moreover, the word, "smart" is a very broad one because we are trying to change our daily environment into smart one by using those technologies. For example, the traditional workplaces have changed into smart offices. Since the 3rd industrial revolution, we have used the touch interface to operate the machines. In the 4th industrial revolution, however, we are trying adding the speech recognition module to the machines to operate them by giving voice commands. Today many of the things are communicated with human by voice commands. Many of them are called AI things and they do tasks which users request and do tasks more than what users request. In the 4th industrial revolution, we use smartphones all the time every day from the morning to the night. For this reason, the privacy using phone is not guaranteed sometimes. For example, the caller's voice can be heard through the phone speaker when accepting a call. So, it is needed to protect privacy on smartphone and it should work automatically according to the user context. In this aspect, this paper proposes a method to adjust the voice volume for call to protect privacy on smartphone according to the user context.