• Journal of Positioning, Navigation, and Timing
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• v.9 no.4
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• pp.405-409
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• 2020

This paper proposes time management system for unmanned aerial vehicle (UAV) network. The computers of the UAVs need time synchronization that time offset does not exceed the minimum interval of data samples for errorless data blending between the computers. The proposed time management system is composed of time synchronization and general management systems for UAV control. The systems communicate each other for time information and control signals. The synchronization system uses improved version of existing time offset estimation that network time protocol (NTP) uses. The time synchronization is operated when the time offset of any UAV exceeds threshold that preconfigured by the general management system. The demonstration of prototype shows stable time synchronization satisfying preconfigured threshold.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.4
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• pp.221-228
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• 2021

With the advent of the IoT (internet of things) era, there has been discussion on how to efficiently use various information from daily life. In academic and industrial society, various smart devices such as smart watches, smart phones, and smart glasses have been developed and commercialized for narrowing the physical/psychological distance with user information. According to recent developments of smart devices, the contemporary people have desired to check their body information and treat disease by themselves. According to the needs of the time, biological researches by phototherapy/monitoring have been actively conducted. Among various light sources, microLEDs have been spotlighted due to their superior optoelectric properties and stability. In this paper, we would like to review the state-of-the research results on the next-generation biological therapy devices via microLEDs.

• 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.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.75-80
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• 2022

With the rapid growth of Internet of Things (IoT) applications and devices, there are still defects in safety and privacy. Current researches indicate that there are weak security mechanisms to protect these devices. Humans use the Internet of Things to control and connect their devices with the Internet. Using the Internet of things has been increased over time. Therefore, capture of sensitive user data has increased intentionally or not [1]. The IP Camera is a type of (IOT) devices. Therefore, in this paper we aim to create a "Security Eyes" application that protects IP Cameras from security attacks according to certain security mechanisms (increasing the strength of encryption and filling the usual security holes in IP cameras … etc) and alerts the user when the live broadcast is interrupted or an error occurs.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.1
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• pp.1-7
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• 2023

In this paper, we implement a lossless compression technique for time-series data generated by IoT (Internet of Things) devices to reduce the disk spaces. The proposed compression technique reduces the size of the encoded data by selectively applying CNN (Convolutional Neural Networks) or Delta encoding depending on the situation in the Forecasting algorithm that performs prediction on time series data. In addition, the proposed technique sequentially performs zigzag encoding, splitting, and bit packing to increase the compression ratio. We showed that the proposed compression method has a compression ratio of up to 1.60 for the original data.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.216-224
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• 2023

Smart lighting systems have become increasingly popular in several public sectors because of trends toward urbanization and intelligent technologies. In this study, we designed and implemented a web application platform to explore and monitor data acquired from lighting devices at Thammasat University (Rangsit Campus, Thailand). The platform provides a convenient interface for administrative and operative staff to monitor, control, and collect data from sensors installed on campus in real time for creating geographically specific big data. Platform development focuses on both back- and front-end applications to allow a seamless process for recording and displaying data from interconnected devices. Responsible persons can interact with devices and acquire data effortlessly, minimizing workforce and human error. The collected data were analyzed using an exploratory data analysis process. Missing data behavior caused by system outages was also investigated.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.138-138
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• 2022

Understanding a stream's or river's discharge is essential for a variety of hydrological and geomorphological applications at various sizes. However, depending on the stream environment and flow conditions, it is crucial to use the appropriate techniques and instruments. This will ensure that discharge estimations are as reliable as possible. This study presents developed smart system for continuous measurement of open channel discharge and evaluate streamflow measurement over various techniques. This includes developed smart flow meter as flow point measurements, smart water level sensor (installed on Hydraulic Structure ? Weir) and current meters. Advantages and disadvantages of each equipment are presented to ensure that the most appropriate method can be selected. we found that smart water level sensor is more prominent once used during flood event as compared to smart flow meter and current meters, while current meters seems to show better accuracy once applied for open channel.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.1-8
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• 2023

Smart IoT over high speed network and high performance smart devices explodes the ubiquitous services and applications. Nearest Neighbor(NN) query is one of the important type of queries that have to be supported for ubiquitous information services. In order to process efficiently NN queries in the wireless broadcast environment, it is important that the clients determine quickly the search space and filter out NN from the candidates containing the search space. In this paper, we propose a hybrid index of Voronoi and grid partition to provide quick search space decision and rapid filtering out NN from the candidates. Grid partition plays the role of helping quick search space decision and Voronoi partition providing the rapid filtering. We show the effectiveness of the proposed index by comparing the existing indexing schemes in the access time and tuning time. The evaluation shows the proposed index scheme makes the two performance parameters improved than the existing schemes.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.73-80
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• 2023

The recent growth in the use of mobile devices has contributed to increased computing and storage requirements. Cloud computing has been used over the past decade to cater to computational and storage needs over the internet. However, the use of various mobile applications like Augmented Reality (AR), M2M Communications, V2X Communications, and the Internet of Things (IoT) led to the emergence of mobile cloud computing (MCC). All data from mobile devices is offloaded and computed on the cloud, removing all limitations incorporated with mobile devices. However, delays induced by the location of data centers led to the birth of edge computing technologies. In this paper, we discuss one of the edge computing technologies, i.e., cloudlet. Cloudlet brings the cloud close to the end-user leading to reduced delay and response time. An algorithm is proposed for scheduling tasks on cloudlet by considering VM's load. Simulation results indicate that the proposed algorithm provides 12% and 29% improvement over EMACS and QRR while balancing the load.