• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.5
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• pp.81-86
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• 2014

A smart phone subscriber needs wide bandwidth services for more fast data communication on the internet. The conventional MIMO system is now developing to resolve these problems with limited device space for antenna and frequency band environment reserved. One of way to make it practically is to add the number of antennas theoretically. But it is difficult to increase the antenna element as a limited space on the system. Therefore an active beam forming scheme is known as a way of constructing a Compact MIMO system for that. In this paper, the fast switching control block was suggested to adjust a reactance of the antenna element and verified experimentally the effects by switching signal on an orthogonal beam forming through a spatial domain.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.1-18
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• 2017

Recently, identification of the extremely stressed condition of children is an essential skill for real-time recognition of a dangerous situation because incidents of children have been dramatically increased. In this paper, therefore, we present a model based on machine learning techniques for stress status identification of a child by using bio-signals such as voice and heart rate that are major factors for presenting a child's emotion. In addition, a smart band for collecting such bio-signals and a mobile application for monitoring child's stress status are also suggested. Specifically, the proposed method utilizes stress patterns of children that are obtained in advance for the purpose of training stress status identification model. Then, the model is used to predict the current stress status for a child and is designed based on conventional machine learning algorithms. The experiment results conducted by using a real-world dataset showed that the possibility of automated detection of a child's stress status with a satisfactory level of accuracy. Furthermore, the research results are expected to be used for preventing child's dangerous situations.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1233-1242
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• 2017

Various attempts have been made to prevent crime risk. One of the cases where outdoor pedestrians are attacked by criminals is the abnormal health condition. When a mental or mental condition that can not sustain normal walking due to drunkenness is exposed, the case of being a crime is revealed through crime case analysis. In this study, we propose a method for estimating the state of an individual that can be detected in outdoor activities. In order to avoid the inconvenience of installing a separate terminal for event information transmission of sensors and sensors, it is possible to estimate an abnormal state by using a 3-axis acceleration sensor built in a smart phone. The state of the user can be estimated by analyzing the momentum of the user and analyzing it with the passage of time. It is possible to distinguish the flow of time at regular intervals, to recognize the activity patterns in each time band, and to distinguish between normal and abnormal. In this study, we have evaluated the total amount of kinetic energy and kinetic energy in each direction of the acceleration sensor and the Fourier transformed value of the total energy amount to distinguish the abnormal state.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.177-198
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• 2021

Existing change detection researches have been focused on changes of land use and land cover (LULC), damaged areas, or large vegetated and water regions. On the other hands, increased temporal and spatial resolution of satellite images are strongly suggesting the feasibility of change detection of small objects such as vehicles and ships. In order to check the feasibility, this paper analyzes the performance of existing pixel-based change detection methods over small objects. We applied pixel differencing, PCA (principal component analysis) analysis, MAD (Multivariate Alteration Detection), and IR-MAD (Iteratively Reweighted-MAD) to Kompsat-3A and Google Map images taken within 10 days. We extracted ground references for changed and non-changed small objects from the images and used them for performance analysis of change detection results. Our analysis showed that MAD and IR-MAD, that are known to perform best over LULC and large areal changes, offered best performance over small object changes among the methods tested. It also showed that the spectral band with high reflectivity of the object of interest needs to be included for change analysis.

• Science of Emotion and Sensibility
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• v.18 no.4
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• pp.25-34
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• 2015

TThis study explored the requirement of fabric sensor that can measure the motion of the joint effectively by measuring and analyzing the variation in electric resistance of a sensor in accordance with bending and stretching motion of the arm by the implementation of a motion sensor utilizing conductive fabric. For this purpose, on both sides of two kinds of knitted fabric, namely 'L' fabric and 'W' fabric Single Wall Carbon Nano-Tube(SWCNT) was coated, fabric sensor was developed by finishing them in a variety of ways, and the sensor was attached to the arm band. The fabric sensor consisted of total 48 cases, namely background fabric for coating, the method of sensor attachment, the number of layer of sensors, the length of sensor, and the width of sensor. The performance of fabric motion sensors in terms of a dummy arm, that is, a Con-Trex MJ with 48 arm bands around it was evaluated. For each arm band, a total of 48, fastened around the dummy arm, it was adjusted to repeat the bending and stretching at the frequency : 0.5Hz, ROM : $20^{\circ}{\sim}120^{\circ}$, the voltage was recorded for each case after conducting three sets of repeat measurement for a total of 48 cases. As a result of the experiment, and as a consequences of the evaluation and analysis of the voltage based on the uniformity of the base line of the peak-to-peak voltage(Vp-p), the uniformity of Vp-p within the same set, and the uniformity of the Vp-p among three sets, the fabric sensors that have been configured in SWCNT coated 'L' fabric / welding / two layers / $50{\times}5mm$, $50{\times}10mm$, $100{\times}10mm$, and SWCNT coated 'W' fabric / welding / two layers / $50{\times}10mm$ exhibited the most uniform and stable signal value within 5% of the total variation rate. Through all these results of the experiment, it was confirmed that SWCNT coated fabric was suitable for a sensor that can measure the human limb operation when it was implemented as a fabric sensor in a variety of forms, and the optimal sensor types were identified.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.25 no.4
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• pp.15-31
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• 2022

The Green Purification Unit System (GPUS) is a green infrastructure facility applicable to the roadside to reduce particulate matter from road traffic. This study introduces two types of GPUS (type1 and type2) and assesses the performance and maintenance costs of each of them. The GPUS's performance analysis used the data collected in November 2021 after the installation of the GPUS type1 and type2 at the study site in Suwon. The changes in the particulate matter concentration near the GPUS were measured. The maintenance cost of GPUS type1 and type2 was assessed by calculating the initial installation cost and the management and repair cost after installation. The results of the performance analysis showed that the GPUS type1, which was manufactured by combining plants and electric dust collectors, had a superior particulate matter reduction performance. In particular, type1 produced a greater effect of particulate matter reduction in the time with a high concentration (50㎍/m³ or higher) of particulate matter due to the operation of electric dust collectors. GPUS type2, which was designed in the form of a plant wall without applying an electric dust collector, showed lower reduction performance than type1 but showed sufficiently improved performance compared to the existing band green area. Meanwhile, the GPUS type1 had three times higher costs for the initial installation than GPUS type2. In terms of costs for managing and repairing, it was evaluated that type1 would be slightly more costly than type2. Finally, this study discussed the applicability of two types of GPUS based on the result of the analysis of their particulate matter performance and maintenance cost at the same time. Since GPUS type2 has a cheaper cost than type1, it could be more economical. However, in the area suffering a high concentration of particulate matter, GPUS type1 would be more effective than type2. Therefore, the choice of GPUS types should rely on the status of particulate matter concentration in the area where GPUS is being installed.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.241-255
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• 2021

The human auricle is the first part to receive sound from the outside. In this part, the frequency range of human recognizable form is divided and organized. In this study, we propose modeling by applying a single sound source to the surface of the human auricle. This means that when the sound pressure of a low frequency (low frequency) sound enters the pinna, the impedance felt at the tip of a part of the non-linear surface of the pinna is mainly due to the tensile force at the end of the part of the non-linear surface of the pinna. By expressing the situation of moving at a very small speed, the characteristic impedance of the pinna was confirmed to be negative infinity, and it was also confirmed that the speed at the tip of a part of the non-linear surface of the pinna was 0 in the anti-resonance state. It was found that the wave propagation phenomenon that determines the characteristics of the filter is determined by how large the wavelength, kL, is compared to the length of the tip of a part of the non-straight surface of the pinna. Humans first receive sounds from outside through their ears. The auricle is non-linear and has a curved shape, and it is known that it analyzes frequencies while receiving external sounds. The human ear has an audible frequency range of 20Hz - 20,000Hz. Through the study, we applied the characteristics of the notch filter to hypothesize that the human audible frequency range is separated from the auricle, and applied filter theory to analyze it, and as a result, meaningful results were obtained. The curved part and the inner part of the auricle function as a trumpet, collecting sounds, and at the same time amplifying the weak sound of a specific band. The point was found and the shape of the envelope detected in the auricle was found. Selectivity for selecting sounds coming from the outside is the formula of the pinna that implements the function of Q. The function of distinguishing human-recognizable sound from the pinna from low to high through frequency analysis is performed in the pinna, and the 2-3kHz area, where human hearing threshold is the most sensitive, is also the acoustic impedance of the most recessed area of the pinna. It can be seen that starting from.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.867-874
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• 2023

Recently, many problems are occurring in the bee ecosystem due to rapid climate change. The decline in the bee population and changes in the flowering period are having a huge impact on the harvest of bee-keepers. Since it is impossible to continuously observe the beehives in the hive with the naked eye, most people rely on knowledge based on experience about the state of the hive.Therefore, interest is focused on smart beekeeping incorporating IoT technology. In particular, with regard to swarming, which is one of the most important parts of beekeeping, we know empirically that the swarming time can be determined by the sound of the queen bee, but there is no way to systematically analyze this with data.You may think that it can be done by simply recording the sound of the queen bee and analyzing it, but it does not solve various problems such as various noise issues around the hive and the inability to continuously record.In this study, we developed a system that records queen bee sounds in a real-time cloud system and analyzes sound patterns.After receiving real-time analog sound from the hive through multiple channels and converting it to digital, a sound pattern that was continuously output in the queen bee sound frequency band was discovered. By accessing the cloud system, you can monitor sounds around the hive, temperature/humidity inside the hive, weight, and internal movement data.The system developed in this study made it possible to analyze the sound patterns of the queen bee and learn about the situation inside the hive. Through this, it will be possible to predict the swarming period of bees or provide information to control the swarming period.