• Journal of the Korea Society of Computer and Information
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• v.26 no.3
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• pp.35-42
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• 2021

In this paper, we propose a deep learning-based person re-identification method using a three-dimensional RGB-Depth Xtion2 camera considering joint coordinates and dynamic features(velocity, acceleration). The main idea of the proposed identification methodology is to easily extract gait data such as joint coordinates, dynamic features with an RGB-D camera and automatically identify gait patterns through a self-designed one-dimensional convolutional neural network classifier(1D-ConvNet). The accuracy was measured based on the F1 Score, and the influence was measured by comparing the accuracy with the classifier model (JC) that did not consider dynamic characteristics. As a result, our proposed classifier model in the case of considering the dynamic characteristics(JCSpeed) showed about 8% higher F1-Score than JC.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.381-404
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• 2022

Forest fires inflict great losses of human lives and serious damages to ecological systems. Hence, numerous fire detection methods have been proposed, one of which is fire detection based on sensors. However, these methods reveal several limitations when applied in large spaces like forests such as high cost, high level of false alarm, limited battery capacity, and other problems. In this research, we propose a novel forest fire detection method based on image processing and correlation coefficient. Firstly, two fire detection conditions are applied in RGB color space to distinguish between fire pixels and the background. Secondly, the image is converted from RGB to YCbCr color space with two fire detection conditions being applied in this color space. Finally, the correlation coefficient is used to distinguish between fires and objects with fire-like colors. Our proposed algorithm is tested and evaluated on eleven fire and non-fire videos collected from the internet and achieves up to 95.87% and 97.89% of F-score and accuracy respectively in performance evaluation.

• Advances in aircraft and spacecraft science
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• v.9 no.3
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• pp.195-215
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• 2022

The increasing interest in CubeSat platforms ant their capability of enlarging the frontier of possible missions impose technology improvements. Miniaturized electrical propulsion (EP) systems enable new mission for multi-unit CubeSats (6U+). While electric propulsion systems have achieved important level of knowledge at equipment level, the investigation of the mutual impact between EP system and CubeSat technology at system level can provide a decisive improvement for both the technologies. The interaction between CubeSat and EP system should be assessed in terms of electromagnetic emissions (both radiated and conducted), thermal gradients, high electrical power management, surface chemical deposition, and quick and reliable data exchanges. This paper shows how a versatile CubeSat Test Platform (CTP), together with standardized procedures and specialized facilities enable the acquisition fundamental and unprecedented information. Measurements can be taken both by specific ground support equipment placed inside the vacuum facility and by dedicated sensors and subsystems installed on the CTP, providing a completely new set of data never obtained before. CTP is constituted of a 6U primary structure hosting the EP system, representative CubeSat avionics and batteries. For the first test campaign, CTP hosts the ambipolar plasma propulsion system, called Regulus and developed by T4I. After the integration and the functional test in laboratory environment, CTP + Regulus performed a Test campaign in relevant environment in the vacuum chamber at CISAS, University of Padua. This paper is focused on the test campaign description and the main results achieved at different power levels for different duration of the firings.

• Journal of Sensor Science and Technology
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• v.31 no.5
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• pp.318-323
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• 2022

Barium titanate (BaTiO₃) is considered to be a beneficial ceramic material for multilayer ceramic capacitor (MLCC) applications because of its high dielectric constant and low dielectric loss. Numerous attempts have been made to improve the physical properties of BaTiO₃ in response to recent market trends by employing multicomponent alloying strategies. However, owing to its significant number of atomic combinations and unpredictable physical properties, finding a traditional experimental approach to develop multicomponent systems is difficult; the development of such systems is also time-consuming. In this study, 168 new structures were fabricated using special quasi-random structures (SQSs) of Ba_1-xCa_xTi_1-yZryO₃, and 1680 physical properties were extracted from first-principles calculations. In addition, we built an integrated database to manage the computational results, and will provide big data solutions by performing data analysis combined with AI modeling. We believe that our research will enable the global materials market to realize digital transformation through datalization and intelligence of the material development process.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.5
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• pp.423-432
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• 2023

With the increasing demand for mobile devices featuring multi-touch operation, extensive research is being conducted on touch screen panel (TSP) Readout ICs (ROICs) that should possess low power consumption, compact chip size, and immunity to external noise. Therefore, this paper discusses capacitive touch sensors and their readout circuits, and it introduces research trends in various circuit designs that are robust against external noise sources. The recent state-of-the-art TSP ROICs have primarily focused on minimizing the impact of parasitic capacitance (Cp) caused by thin panel thickness. The large Cp can be effectively compensated using an area-efficient current compensator and Current Conveyor (CC), while a display noise reduction scheme utilizing a noise-antenna (NA) electrode significantly improves the signal-to-noise ratio (SNR). Based on these achievements, it is expected that future TSP ROICs will be capable of stable operation with thinner and flexible Touch Screen Panels (TSPs).

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.271-280
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• 2010

While the future warfare is expected to be appeared as network-centric, effect-based, and coordinated cooperative, most current M&S systems reflect only the unit behaviors and interactions of each weapon system. There are limitations to analyze the behaviors of managing weapons cooperatively and sharing the situational awareness over the networks of distributed sensors, C2, and shooters using them. Therefore, we introduce the new design of the networkcentric warfare modeling system using the agent-based modeling and simulation approach. We have developed a system for engagement-level warfare models and tested with multi-platform battleship warfare. In this paper, we propose the method to design battle agents, environments, and networks for network centric warfare modeling.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.1
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• pp.64-72
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• 2009

Previous research on sensor networks mainly focused on efficient transmission of data from sensors to fixed sink nodes. Recently there has been active research on mobile sink nodes, but the re-search of an environment where both fixed sink nodes and mobile sinks are present at the same time is rather scarce. This paper proposes a technique for context gathering by mobile devices with the sink functionality added through fixed sinks under a previously built, cluster based multi hop sensor network environment. To this end, clustering of mobile devices were done based on the fixed sinks of a previously built sensor network, and by using appropriate fixed sinks, context gathering was made possible. By mathematical comparison with TTDD routing protocol, which was proposed for mobile sinks, it was conformed that performance increases in energy with the number of mobile sinks, and with the number of movements by mobile devices.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.234-240
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• 2022

This paper proposes a customized AI exercise recommendation service for balancing the relative amount of exercise according to the working environment by each occupation. WISDM database is collected by using acceleration and gyro sensors, and is a dataset that classifies physical activities into 18 categories. Our system recommends a adaptive exercise using the analyzed activity type after classifying 18 physical activities into 3 physical activities types such as whole body, upper body and lower body. 1 Dimensional convolutional neural network is used for classifying a physical activity in this paper. Proposed model is composed of a convolution blocks in which 1D convolution layers with a various sized kernel are connected in parallel. Convolution blocks can extract a detailed local features of input pattern effectively that can be extracted from deep neural network models, as applying multi 1D convolution layers to input pattern. To evaluate performance of the proposed neural network model, as a result of comparing the previous recurrent neural network, our method showed a remarkable 98.4% accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1706-1727
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• 2023

Under Water Sensor Networks (UWSN) has gained attraction among various communities for its potential applications like acoustic monitoring, 3D mapping, tsunami detection, oil spill monitoring, and target tracking. Unlike terrestrial sensor networks, it performs an acoustic mode of communication to carry out collaborative tasks. Typically, surface sink nodes are deployed for aggregating acoustic phenomena collected from the underwater sensors through the multi-hop path. In this context, UWSN is constrained by factors such as lower bandwidth, high propagation delay, and limited battery power. Also, the vulnerabilities to compromise the aquatic environment are in growing numbers. The paper proposes an Energy-Efficient standalone Intrusion Detection System (EEIDS) to entail the acoustic environment against malicious attacks and improve the network lifetime. In EEIDS, attributes such as node ID, residual energy, and depth value are verified for forwarding the data packets in a secured path and stabilizing the nodes' energy levels. Initially, for each node, three agents are modeled to perform the assigned responsibilities. For instance, ID agent verifies the node's authentication of the node, EN agent checks for the residual energy of the node, and D agent substantiates the depth value of each node. Next, the classification of normal and malevolent nodes is performed by determining the score for each node. Furthermore, the proposed system utilizes the sheep-flock heredity algorithm to validate the input attributes using the optimized probability values stored in the training dataset. This assists in finding out the best-fit motes in the UWSN. Significantly, the proposed system detects and isolates the malicious nodes with tampered credentials and nodes with lower residual energy in minimal time. The parameters such as the time taken for malicious node detection, network lifetime, energy consumption, and delivery ratio are investigated using simulation tools. Comparison results show that the proposed EEIDS outperforms the existing acoustic security systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1540-1560
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• 2022

Latest technological innovation in the development of compact lower power radios has led to the explosion of Internet of Things. With Wi-Fi, Zigbee and other physical layer protocols offering short coverage area there was a need for a RF protocol that had a larger coverage area with low power consumption. LoRa offers Long Range with lower power consumption. LoRa offers point to point and point to multipoint connections. with Single hop communication in place the need for routing protocols are eliminated. LoRa Wide Area Network stack can accommodate thousands of nodes under a single LoRa gateway with a single hop communication between the end nodes and LoRaWAN gateway. This paper takes an experimental approach to analyze the basic physical layer parameters of LoRa and the practical coverage offered by a LoRaWAN under highly dense urban conditions with variable topography. The insights gained from the practical deployment of the LoRaWAN network, and the subsequent performance analysis is used to design a novel public utility monitoring platform. The second half of the papers is designing a robust platform to integrate both existing wired sensor water meters, current and future generation wireless water meters. The Common Automated Metering Platform is designed to integrate both wired sensors and wireless (LoRaWAN and Wi-Fi) supported water meters. This integrated platform reduces the number of nodes under each LoRaWAN gateway and thus improves the scalability of the network. This architecture is currently designed to accommodate one utility application but can be modified to integrate multi-utility applications.