• KIPS Transactions on Computer and Communication Systems
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• v.5 no.6
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• pp.135-142
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• 2016

We proposed the new method to estimate the blood pressure with the differential value of the digital arterial pulse waveform and BP relation equation. To get the digital arterial pulse waveform, we use the arterial pulse waveform measurement system that has digital air-pressure sensor device and smart phone. The acquired digital arterial pulse waveforms are classified as hypertension group, normal group, and hypotension group, and we can derive the average differential value between the highest point and lowest point of a single waveform of individuals along with the group. In this study, we found the functional correlation between the blood pressure and differential value as a form of BP relation equation through the regression process on the average of differential value and blood pressure value from a tonometer. The Experimental results show the BP relation equation can give easy blood pressure estimation method with a high accuracy. Although this estimation method has over 66 % error rate and does not give the high level of the accuracy for the diastolic compares to the commercial tonometer, the estimation results for the systolic show the high accuracy that has less than 10 % error rate.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.421-428
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• 2022

The earthwork is a core process of all constructions, and compaction measurement of earthwork play an important role in improving productivity. The analog tests such as Plate Bearing Test and Sand-cone occupy current compaction measurement techniques. Due to advanced 4th Industrial Revolution, research on analog tests combined smart construction technology are actively conducted. DCPT (Dynamic Cone penetration Test), simpler and faster than conventional tests, has recently on rise. However, it is also an analog that measures data manually and has several disadvantages such as history management and data verification. The IoT-based DCPT system developed in this study combines digital wire sensors, mobile phones, and Bluetooth with conventional DCPT. Compare to conventional test methods, IoT-based DCPT has advantages such as performance time, single-person measurement, low cost, mobile-based management, and real-time data verification. In addition, a test bed was built to verify IoT-based DCPT. The test bed was built under similar conditions to the actual earthworks site through roller equipment. DCPT data obtained from 322 stations. As a result, IoT-based DCPT showed good performance, and the test bed was also showed stable results as the compaction was carried out.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.2
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• pp.309-316
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• 2022

Advances in technology have improved people's lives comfortably and have developed more easily, safely and simply. We usually turn on hot water to set the temperature of the water in the bathroom and gradually adjust the temperature to find the temperature we want with our skin. In this situation, I thought, "What if there is a device that can see the temperature of water with my eyes and help with the interior of the bathroom while including a safe system," and tried to create a system that values stability. For example, if a child accidentally changes the temperature of the water to high temperature while washing, he or she can get burned. And the biggest purpose is to secure better safety by adding LCDs and LEDs so that we can visually know the temperature before feeling it tactilely. As a result of the experiment, there was no error between the temperature detected by the water temperature sensor and the temperature displayed on the LCD, and no error occurred up to 27 cm in the distance measurement experiment using the ultrasonic sensor. There has been an error of about 2% since 28cm or older, but there is no significant inconvenience in using it within the category of faucets.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.144-149
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• 2018

The eggs are incubated for 18 days through the generator and incubated in the developing incubator. During the developmental period, the weight loss of the fetus is correlated with the ventricular formation, and the proper ventricular formation is also associated with the healthy embryonic hatching and the egg hatching rate. However, in the incubator period of the domestic hatchery, it is a reality to acquire the resultant side by the Iranian standard weight measurement with the experience of the hatchery and the person concerned and the development period without the apparatus for measuring the present weight. As a result, prevalence of early mortality, hunger and illness during hatching are frequent. Monitoring the reduction of weaning weight is crucial to obtaining chick quality and hatching performance with weight changes within the development machine. Water loss is different depending on the size of eggs, egg shell, and elder group. We can expect to increase the hatching rate by measuring the weight change in real time and optimizing the ventilation change accordingly. There is a need to develop a real-time measurement system that can control 10 to 13% reduction of the total weight during hatching. The system through this study is a way to check the one - time directly when moving the existing egg, and it is impossible to control the measurement of the fetal water evaporation within the development period. Unlike systems that do not affect the hatching rate, four load cells are connected in parallel on the Arduino sketch board and the AT-command command is used to connect the mobile phone and computer in real time. The communication speed of Bluetooth was set to 15200 to match the communication speed of Arduino and Hyper-terminal program. The real - time monitoring system was designed to visually check the change of the weight of the fetus in the artificial incubator. In this way, we aimed to improve the hatching rate and health condition of the hatching eggs.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.78-87
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• 2011

A variety of intelligent application using the sensor network system is being studied. In general, the sensor network consists of nodes which equipped with a variety of sensing module and is utilized to collect environment information. Recently, the demands of multimedia data are increasing due to the demands of more detailed environmental monitoring or high-quality data. In this paper, we overcome the limitations of low bandwidth in Zigbee-based sensor networks and propose a routing algorithm for real-time multimedia data transmission. In the previously proposed algorithm for multimedia data transmission occurs delay time of routing setup phase and has a low data transmission speed due to bandwidth limitations of Zigbee. In this paper, we propose the hybrid routing algorithm that consist of Zigbee and Bluetooth and solve the bandwidth problem of existing algorithm. We also propose the disjointed multipath setup algorithm based on competition that overcome delay time of routing setup phase in existing algorithm. To evaluate the superiority of the proposed algorithm, we compare it with the existing algorithm. Our experimental results show that the latency was reduced by approximately 78% and the communication speed is increased by approximately 6.9-fold.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.7
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• pp.750-755
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• 2003

This paper proposes a new three-line balun. The equivalent circuit of the proposed three-line balun is presented, and impedance matrix［Z］of the equivalent circuit is derived from the relationship between the current and voltage at each port. The design equation for a given set of balun impedance at input and output ports is presented using［S］parameters, which is transferred fom impedance matrix,［Z］. To demonstrate the feasibility and validity of design equation, multi-layer ceramic(MLC) chip balun operated in the 2.4 GHz ISM band frequency is designed and fabricated by the use of the low temperature co-fired ceramic(LTCC) technology. By employing both the proposed new three-line balun equivalent circuit and multi-layer configuration provided by LTCC technology, the 2012 size MLC balun is realized. Measured results of the multi-layer LTCC three-line balun match well with the full-wave electromagnetic simulation results, and measured in band-phase and amplitude balances over a wide bandwidth are excellent. This proposed balun is very easily applicable to multi-layer structure using LTCC as shown in the paper, and also can be realized with microstrip lines on PCB. This distinctive performance is very favorable for wireless communication systems such as wireless LAN(Local Area Network) and Bluetooth applications.

• Smart Media Journal
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• v.6 no.1
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• pp.61-67
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• 2017

A large number of people living in modern times prefer remaining unmarried or living alone independently for the reason of their own will or another person's will. This is because they dislike being interfered with by other persons or because there is a financial problem. This behavior has become mainstream in persons working for professional jobs, persons having a strong disposition toward individual activity or college students. In particular, career women pursuing their own comfortable life have the tendency to prefer single life. However, sometimes, they become a target of crime that targets and makes bad use of this point. For these reasons. Consequently, sometimes, they additionally install and use a security system such as door security guard at front door and so on. It is not so difficult to lock the door security guard at the front door. However, it is apt to be forgotten. And when they are on the bedspread before falling asleep, in case they should check whether the door security guard is locked or in case they should lock it, they should get up, go to the entrance, and check and lock the door security guard. They often don't lock the door security guard due to their feeling that it is all right because of annoyance and inconvenience. This paper is intended to work for safety from crime such as illegal housebreaking by more conveniently using the door security guard after designing and implementing a system that can remotely control the door security guard, using a smartphone as a method of resolving this annoyance and keeping life more safe.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.163-177
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• 2019

As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.