• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.89-92
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• 2018

본 논문에서는 Edge computing 환경에서 다수의 노드들로 구성된 네트워크의 디바이스를 효율적으로 관리하기 위한 방법을 제안한다. 기존의 클라이언트-서버 모델은 모든 데이터와 그에 대한 요청을 중심 서버에서 처리하기 때문에, 다수의 노드로부터 생성된 많은 양의 데이터를 처리하는 데 빠른 응답속도를 보장하지 못한다. Edge computing은 분담을 통해 네트워크의 부담을 줄일 수 있는 IoT 네트워크에 적합한 방법으로, 데이터를 전송하고 받는 과정에서 네트워크의 대역폭을 사용하는 대신 서로 연결된 노드들이 협력해서 데이터를 처리하고, 또한 네트워크 말단에서의 데이터 처리가 허용되어 데이터 센터의 부담을 줄일 수 있다. 여러병렬 기계학습 모델 중 본 연구에서는 Stale Synchronous Parallel(SSP) 모델을 이용하여 Edge 노드에서 분산기계 학습에 적용하였다.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1259-1276
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• 2017

As technologies related to sensor network are currently emerging and the use of GeoSensor is increasing along with the development of Internet of Things (IoT) technology, spatial query processing systems to efficiently process spatial sensor data are being actively studied. However, existing spatial query processing systems do not support a spatial-temporal data type and a spatial-temporal operator for processing spatialtemporal sensor data. Therefore, they are inadequate for processing spatial-temporal sensor data like GeoSensor. Accordingly, this paper developed a spatial-temporal query processing system, for efficient spatial-temporal query processing of spatial-temporal sensor data in a sensor network. Lastly, this paper verified the utility of System through a scenario, and proved that this system's performance is better than existing systems through performance assessment of performance time and memory usage.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.2
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• pp.29-35
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• 2021

Recently, with the widespread use of the Internet of Things (IoT), the service structure has been studied to interact with various service domains. A common way to interact with other service domains is to develop the APIs needed to interact on the platform. However, to use a common method, we consider many costs and resources as APIs can increase while adding connections from other service domains. To address this issue, we propose the design and implementation of a dynamic API platform. The proposed platform can dynamically create APIs when requesting service applications, depending on the target service domain. To demonstrate the feasibility of the proposed platform, we develop a COVID-19 weekly infection status, regional infection status, and vaccination status service using dynamic APIs from the Public Data Portal using the proposed dynamic API platform and Node-RED.

• Current Optics and Photonics
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• v.8 no.5
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• pp.508-514
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• 2024

This paper presents a deep learning-based weight sensor, using optical speckle patterns of multimode fiber, designed for real-time intrusion detection. The weight sensor has been trained to identify 11 distinct speckle patterns, ranging in weight from 0.0 kg to 2.0 kg, with an interval of 200 g between each pattern. The estimation for untrained weights is based on the generalization capability of deep learning. This results in an average weight error of 243.8 g. Although this margin of error precludes accurate weight measurement, the system's ability to detect abrupt weight changes makes it a suitable choice for intrusion detection applications. The weight sensor is integrated with the Google Teachable Machine, and real-time intrusion notifications are facilitated by the ThingSpeak^TM cloud platform, an open-source Internet of Things (IoT) application developed by MathWorks.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.07a
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• pp.89-90
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• 2016

본 논문에서는 라디오와 텔레비전을 대상으로 이루어진 전파납치 사건이 오늘날 사물인터넷 시대에서 가지는 의미를 연구한다. 인터넷에 연결되는 사물이 다양해지고 활용 분야가 넓어질수록 사물에 가해지는 네트워크에 의한 공격에서 기기의 안전성과 신뢰성을 보장하기 어렵다. 인터넷이 연결되는 사물일지라도 해당 사물이 이전부터 인터넷과는 다른 통신 기능을 가지고 있는 경우 기존의 통신 규격을 그대로 계승받는다. 이전의 통신 방식은 일반 라디오 및 텔레비전의 통신과 유사한 방법이 많아 전파교란 및 납치의 영향을 받을 수 있다. 이러한 위협에 대응하기 위해 전파납치 사례를 분석하고 사물의 제어에 영향을 미칠 가능성을 연구하여 대응한다.

• Journal of IKEEE
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• v.22 no.3
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• pp.862-865
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• 2018

The proposed scheme minimizes the Idle time under the residual energy of the sensor node to adjust the Sleep-Wakeup period and minimize unnecessary energy consumption. It is The proposed scheme minimizes the Idle time under the residual energy of the sensor node to adjust the Sleep-Wakeup period and minimize unnecessary energy consumption. It is an important process to control the Application Packet Framework including the PHY and the MAC layer at each node's Idle time with the Idle time mechanism state before the proposed function is executed. The Current Control Level of the Report Attribute is fixed at one sending / receiving node where power consumption can occur, by changing Sleep-Wakeup time, the low power consumption efficiency was improved while satisfying the transmission requirement of the given delay time constraint.

• Journal of IKEEE
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• v.22 no.3
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• pp.878-881
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• 2018

In this paper, experiments through performance evaluation under real operation environment were conducted. Transceiver and microcontroller shows the characteristics for the amount of current consumption and software protocol was optimized by controlling the time of Report Attribute and electric current level. To reduce current consumption when using battery, with designing transmission of the same amount of data as soon as possible, power consumption efficiency was enhanced.

• Annual Conference of KIPS
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• 2019.05a
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• pp.60-61
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• 2019

Drones are opening new horizon as a major Internet-of-Things (IoT) player which is a network of objects. Drone needs to charge itself during providing services from the charging stations. If there are lots of drones and one charging station, then it is a critical situation to decide which drone should get charged first and make order of priorities for drones to get charged sequentially. In this paper, we propose an efficient scheduling algorithm for drone power charging (ESADPC), in which charging station would have a scheduler to decide which drone can get charged earlier among many other drones. Simulation results have showed that our algorithm reduces the deadline miss ration and turnaround time.

• Electronics and Telecommunications Trends
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• v.34 no.4
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• pp.117-128
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• 2019

As companies use increasing amounts of data more and more, people are more concerned about protecting their privacy. Many researches studies have been conducted with a to securely view of manage managing and share sharing private information securely using the Bblockchain technology. These studies have suggested a Bblockchain-based approaches to provide efficiency, scalability, data ownership, and systematic data lifecycles that were are the limitations of lacking in traditional access controls. More Sspecifically, these studies have introduced a new access control models, distributed hash tables, trusted execution environments, and hierarchical ID-based cryptographic mechanisms to provide reliable access control even in complex environments such as IoT Internet of Things. In this paperstudy, we present the criteria to for classifying the functional characteristics of the Bblockchain-based access control methods and derive the differentiateion between of each the several methods.

• Korean Management Science Review
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• v.33 no.1
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• pp.49-58
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• 2016

Focusing on the drastic increase of smart devices, machine generated data expansion is a general phenomenon in network services and IoT (Internet of Things). Especially, built-in multi sensors in a smart device are used for collection of user status and moving data. Combining the internal sensor data and environmental information, we can determine landmarks that decide a pedestrian's locations. We use an ANOVA method to analyze data acquired from multi sensors and propose a landmark classification algorithm. We expect that the proposed algorithm can achieve higher accuracy of indoor-outdoor positioning system for pedestrians.