• Journal of Korea Multimedia Society
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• v.22 no.2
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• pp.242-249
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• 2019

Old people and patients with cardiovascular disease could die of a heart attack in the bath with heated water for a long time. Various researches have been studied to prevent these accidents from happening such as measuring the ECG signal when taking bath. However, these devices are hard to use and the higher price is not easily accepted by the public. In this paper, a low-cost and use-friendly, real time high precision water temperature monitoring device to prevent heart attack in the bath was developed. The device with waterproof design that lets the device can float on the surface of the water, and an accurate way to make water temperature measurement method was proposed by this paper that is immerging the sensor into water with 4cm depth to measure the temperature of underwater. The manufactured device was conducted to two experiments; one was to verify the basic functions of the device, and another one was for compare the proposed device with commercial products for monitoring the water temperature in the bathtub. As the experimental results shown, the proposed device has stable performance for the water temperature measurement and communicating with laptop in wireless.

• Journal of Practical Engineering Education
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• v.9 no.2
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• pp.139-148
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• 2017

As the connection between objects and computers becomes easier, learning using physical computing is presented as a good alternative to solve the problems raised in programming education for beginners. In this paper, we propose a training method that can be applied to basic programming courses for beginners. To do this, we will proceed with a basic programming lecture based on the physical computing method. Currently, physical computing courses focus on various input sensor connection methods and output device control. However, the content of programming education using physical computing materials is lacking. In this paper, we proposed and tested a teaching method that is used in programming education by using low cost materials used in physical computing.

• Journal of Sensor Science and Technology
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• v.28 no.5
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• pp.329-333
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• 2019

Solution-processed oxide thin-film transistors (TFTs) have garnered great attention, owing to their many advantages, such as low-cost, large area available for fabrication, mechanical flexibility, and optical transparency. Negative bias stress (NBS)-induced instability of sol-gel IGZO TFTs is one of the biggest concerns arising in practical applications. Thus, understanding the bias stress effect on the electrical properties of sol-gel IGZO TFTs and proposing an effective recovery method for negative bias stressed TFTs is required. In this study, we investigated the variation of transfer characteristics and the corresponding electrical parameters of sol-gel IGZO TFTs caused by NBS and positive bias recovery (PBR). Furthermore, we proposed an effective PBR method for the recovery of negative bias stressed sol-gel IGZO TFTs. The threshold voltage and field-effect mobility were affected by NBS and PBR, while current on/off ratio and sub-threshold swing were not significantly affected. The transfer characteristic of negative bias stressed IGZO TFTs increased in the positive direction after applying PBR with a negative drain voltage, compared to PBR with a positive drain voltage or a drain voltage of 0 V. These results are expected to contribute to the reduction of recovery time of negative bias stressed sol-gel IGZO TFTs.

• Journal of Sensor Science and Technology
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• v.30 no.1
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• pp.20-24
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• 2021

The electrocardiogram (ECG) is one of the most extensively employed signals used to diagnose and predict cardiovascular diseases (CVDs). In recent years, several deep learning (DL) models have been proposed to improve detection accuracy. Among these, deep neural networks (DNNs) are the most popular, wherein the features are extracted automatically. Despite the increment in classification accuracy, DL models require exorbitant computational resources and power. This causes the mapping of DNNs to be slow; in addition, the mapping is challenging for a wearable device. Embedded systems have constrained power and memory resources. Therefore full-precision DNNs are not easily deployable on devices. To make the neural network faster and more power-efficient, spiking neural networks (SNNs) have been introduced for fewer operations and less complex hardware resources. However, the conventional SNN has low accuracy and high computational cost. Therefore, this paper proposes a new binarized SNN which modifies the synaptic weights of SNN constraining it to be binary (+1 and -1). In the simulation results, this paper compares the DL models and SNNs and evaluates which model is optimal for ECG classification. Although there is a slight compromise in accuracy, the latter proves to be energy-efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.814-836
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• 2021

Wildlife ecologists and biologists recapture deer to collect tracking data from deer collars or wait for a drop-off of a deer collar construction that is automatically detached and disconnected. The research teams need to manage a base camp with medical trailers, helicopters, and airplanes to capture deer or wait for several months until the deer collar drops off of the deer's neck. We propose an intelligent robust base-station research with a low-cost and time saving method to obtain recording sensor data from their collars to a listener node, and readings are obtained without opening the weatherproof deer collar. We successfully designed the and implemented a robust base station system for automatically collecting data of the collars and listener motes in harsh wilderness environments. Intelligent solutions were also analyzed for improved data collections and pattern predictions with drone-based detection and tracking algorithms.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.1024-1029
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• 2022

Composite scintillation screens on a base of Gd_1.2Y_1.8Ga_2.5Al_2.5O₁₂:Ce (GYAGG) scintillator have been evaluated for neutron detection. Besides the powdered scintillator, the composite includes ⁶LiF particles; both are merged with a binder and deposited onto the light-reflecting aluminum substrate. Results obtained demonstrates that screens are suitable for use with a silicon photomultiplier readout to create a prospective solution for a compact and low-cost thermal neutron sensor. Composite GYAGG/⁶LiF scintillation screen shows a pretty matched sensitivity and γ-background rejection with a widely used ZnS/⁶LiF screens however, possesses forty times faster response.

• Particle and aerosol research
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• v.18 no.3
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• pp.61-68
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• 2022

In this study, a fluidized bed particle generator was developed to generate an aerosol without supply of compressed air and to increase portability. It was assumed that the mixing ratio of the test particles and beads, the input amount, and the air flow rate supplied to the generator would have effect on the aerosol generation characteristics. The product of these three parameters was set as a characteristic parameter and particle generation characteristics according to the change of the characteristic parameter were observed. As a result, it was confirmed that the input amount of test particles and beads was not suitable as a characteristic parameter and a characteristic parameter expressed as a product of the mass mixing ratio and the air flowrate was newly defined. When the new characteristic parameter is applied, it can be confirmed that the total amount of particles generated from the particle generator is a function of the characteristic parameter. As a result of measuring the amount of particle generation by adjusting the characteristic parameter, it was confirmed that the performance required for the test particle generator for the field inspection equipment of PM-2.5 sensors could be satisfied.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.68-74
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• 2017

This paper presents a joint demosaicking and arbitrary-ratio down sampling algorithm for color filter array (CFA) images. Color demosaiking is a necessary part of image signal processing pipeline for many types of digital image recording system using single sensor. Also, such as smart phone, obtained high resolution image from image sensor has to be down-sampled to be displayed on the screen. The conventional solution is "Demosaicking first and down sampling later". However, this scheme requires a significant amount of memory and computational cost. Also, artifacts can be introduced or details get damaged during demosaicking and down sampling process. In this paper, we propose a method in which demosaicking and down sampling are working simultaneously. We use inverse mapping of Bayer CFA and then joint demosaicking and down sampling with arbitrary-ratio scheme based on signal decomposition of high and low frequency component in input data. Experimental results show that our proposed algorithm has better image quality performance and much less computational cost than those of conventional solution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.262-269
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• 2020

Recently, many attempts have been made to reduce the time required for payment in various shopping environments. In addition, for the Fourth Industrial Revolution era, artificial intelligence is advancing, and Internet of Things (IoT) devices are becoming more compact and cheaper. So, by integrating these two technologies, access to building an unmanned environment to save people time has become easier. In this paper, we propose a smart shopping cart system based on low-cost IoT equipment and deep-learning object-detection technology. The proposed smart cart system consists of a camera for real-time product detection, an ultrasonic sensor that acts as a trigger, a weight sensor to determine whether a product is put into or taken out of the shopping cart, an application for smartphones that provides a user interface for a virtual shopping cart, and a deep learning server where learned product data are stored. Communication between each module is through Transmission Control Protocol/Internet Protocol, a Hypertext Transmission Protocol network, a You Only Look Once darknet library, and an object detection system used by the server to recognize products. The user can check a list of items put into the smart cart via the smartphone app, and can automatically pay for them. The smart cart system proposed in this paper can be applied to unmanned stores with high cost-effectiveness.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.2
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• pp.43-55
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• 2010

${\mu}TESLA$ broadcast authentication protocol have been developed by many researchers for providing authenticated broadcasting message between receiver and sender in sensor networks. Those cause authentication delay Tree-based ${\mu}TESLA$[3] solves the problem of authentication delay. But, it has new problems from Merkel hash tree certificate structure. Such as an increase in quantity of data transmission and computation according to the number of sender or parameter of ${\mu}TESLA$ chain. ${\mu}TPCT$-based ${\mu}TESLA$[4] has an advantages, such as a fixed computation cost by altered Low-level Merkel has tree to hash chain. However, it only use the sequential values of Hash chain to authenticate ${\mu}TESLA$ parameters. So, It can't ensure the success of authentication in lossy sensor network. This paper is to propose the improved method for Tree-based ${\mu}TESLA$ by using XOR-based chain. The proposed scheme provide advantages such as a fixed computation cost with ${\mu}$TPCT-based ${\mu}TESLA$ and a message loss-tolerant with Tree-based ${\mu}TESLA$.