• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.05a
• /
• pp.733-736
• /
• 2009

Power Line Communication(PLC) is need not additional communication line. So establishment expense is inexpensive and application is simple. Therefore, lower part network of various application field is possible. However, there are high subordinate interference and noise problem on limited transmission data and communication interference element. Wireless Sensor Network(WSN) is need not infrastructure, Self-regulating network architecture of sensor nodes is possible. So at short time, network construction is available. But, power consumption is increased by active sensing for QoS elevation and unnecessary information transmission, low electric power design and necessity of improve protocol are refered to life shortening problem and is studied. In this paper, supplement problem of power line communication and wireless sensor network mutually and because advantage becomes linkage integration control system using synergy effect of two technologies as more restriction be and tries to approach structurally control network that is improved for smooth network environment construction. Honeywell's hybrid sensor network does comparative analysis(benchmarking). Confirm performance elevation proposing teaming of power line communication and wireless sensor network. Through simulation, service delay decreases and confirms that performance elevation.

• Applied Chemistry for Engineering
• /
• v.32 no.6
• /
• pp.684-689
• /
• 2021

In this paper, we develop a cost effective and disposable voltammetric sensing platform involving screen-printed carbon electrode (SPCE) modified with the nanocomposites composed of multi-walled carbon nanotubes, polyelectrolyte, and tyrosinase for bisphenol A. This is known as an endocrine disruptor which is also related to chronic diseases such as obesity, diabetes, cardiovascular and female reproductive diseases, precocious puberty, and infertility. A negatively charged oxidized multi-walled carbon nanotubes (MWCNTs) wrapped with a positively charged polyelectrolyte, e.g., polydiallyldimethylammonium, was first wrapped with a negatively charged tyrosinae layer via electrostatic interaction and assembled onto oxygen plasma treated SPCE. The nanocomposite modified SPCE was then immersed into different concentrations of bisphenol A for a given time where the tyrosinase reacted with OH group in the bisphenol A to produce the product, 4,4'-isopropylidenebis(1,2-benzoquinone). Cyclic and differential pulse voltammetries at the potential of -0.08 V vs. Ag/AgCl was employed and peak current changes responsible to the reduction of 4,4'-isopropylidenebis(1,2-benzoquinone) were measured which linearly increased with respect to the bisphenol A concentration. In addition, the SPCE based sensor showed excellent selectivity toward an interferent agent, bisphenol S, which has a very similar structure. Finally, the sensor was applied to the analysis of bisphenol A present in an environmental sample solution prepared in our laboratory.

• Economic and Environmental Geology
• /
• v.52 no.4
• /
• pp.313-322
• /
• 2019

SAR (Synthetic Aperture Radar) remote sensing data is a very useful tool for near-real-time identification of landslide affected areas that can occur over a large area due to heavy rains or typhoons. This study aims to develop an effective algorithm for automatically delineating landslide areas from the polarimetric SAR data acquired after the landslide event. To detect landslides from SAR observations, reduction of the speckle effects in the estimation of polarimetric SAR parameters and the orthorectification of geometric distortions on sloping terrain are essential processing steps. Based on the experimental analysis, it was found that the IDAN filter can provide a better estimation of the polarimetric parameters. In addition, it was appropriate to apply orthorectification process after estimating polarimetric parameters in the slant range domain. Furthermore, it was found that the polarimetric entropy is the most appropriate parameters among various polarimetric parameters. Based on those analyses, we proposed an automatic landslide detection algorithm using the histogram thresholding of the polarimetric parameters with the aid of terrain slope information. The landslide detection algorithm was applied to the ALOS-2 PALSAR-2 data which observed landslide areas in Japan triggered by Typhoon in September 2011. Experimental results showed that the landslide areas were successfully identified by using the proposed algorithm with a detection rate of about 82% and a false alarm rate of about 3%.

• Applied Chemistry for Engineering
• /
• v.30 no.4
• /
• pp.429-434
• /
• 2019

A lateral flow immunoassay platform utilizing antibody functionalized water soluble CdSe/ZnS semiconductor quantum dots (QDs) was developed for the analysis of human serum amyloid A-1 (hSAA1) in a buffer solution. hSAA1 was chosen as a target protein because it is regarded as a potential biomarker associated with early diagnosis and prognosis in patients of lung cancer. The immunoassay strip on a nitrocellulose membrane was fabricated by spraying two lines composed of a test line with a monoclonal antibody against hSAA1 (10G1) (anti hSAA1) and a control line of anti-chicken IgY. While the CdSe/ZnS QDs synthesized in an organic phase were transferred to a water phase by ligand exchange using carboxylic acid modified alkane thiol. The QDs was then conjugated to monoclonal antibody against hSAA1 (14F8) [anti hSAA1 (14F8)] and used as a fluorescent detection probe. The sequential lateral flow of hSAA1 in different concentration and QDs-anti hSAA1 (14F8) complex allowed to form the surface sandwich complex of anti hSAA1 (10G1)/hSAA1/QD-anti hSAA1 (14F8), which was then analyzed using fluorescence microscope. A 100 nM concentration of hSAA1 protein can be detected by naked eyes under an optimized lateral flow buffer condition with a sensing time of 5 mins.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.1
• /
• pp.323-328
• /
• 2019

In order to construct 3D geospatial information about the terrain, current measurement using a total station, remote sensing, GNSS(Global Navigation Satellite System) have been used. However, ground survey and GNSS survey have time and economic disadvantages because they have to be surveyed directly in the field. In case of using aerial photographs and satellite images, these methods have the disadvantage that it is difficult to obtain the three-dimensional shape of the terrain. The terrestrial LiDAR can acquire 3D information of X, Y, Z coordinate and shape obtained by scanning innumerable laser pulses at densely spaced intervals on the surface of the object to be observed at high density, and the processing can also be automated. In this study, terrestrial LiDAR was used to analyze slope displacement. Study area slopes were selected and data were acquired using LiDAR in 2016 and 2017. Data processing has been used to generate slope cross section and slope data, and the overlay analysis of the generated data identifies slope displacements within 0.1 m and suggests the possibility of using slope LiDAR on land to manage slopes. If periodic data acquisition and analysis is performed in the future, the method using the terrestrial lidar will contribute to effective risk slope management.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.4
• /
• pp.253-265
• /
• 2020

As the risk of landslide is recently increasing due to the typhoons and localized heavy rains, effective techniques for the landslide damage detection are required to support the establishment of the recovery planning. This study describes the analysis of landslide-damaged areas using ISODATA(Iterative Self-Organizing Data Analysis Technique Algorithm) with Sentinel-2 image, regarding the case of Gokseong in August 7, 2020. A total of 4.75 ha of landslide-damaged areas was detected from the Sentinel-2 image using spectral characteristics of red, NIR(Near Infrared), and SWIR(Shortwave Infrared) bands. We made sure that the satellite remote sensing is an effective method to detect the landslide-damaged areas and support the establishment of the recovery planning, followed by the field surveys that require a lot of manpower and time. Also, this study can be used as a reference for the landslide management for the CAS500-1/2(Compact Advanced Satellite) scheduled to launch in 2021 and the Korean Medium Satellite for Agriculture and Forestry scheduled to launch in 2024.

• Journal of Apiculture
• /
• v.34 no.1
• /
• pp.47-55
• /
• 2019

Honey bees are a vital part of the food chain as the most important pollinators for a broad palette of crops and wild plants. The climate change and colony collapse disorder (CCD) phenomenon make it challenging to develop ICT solutions to predict changes in beehive and alert about potential threats. In this paper, we report the test results of the bee-counting system which stands out against the previous analogues due to its comprehensive components including an improved dual infrared sensor to detect honey bees entering and leaving the hive, environmental sensors that measure ambient and interior, a wireless network with the bluetooth low energy (BLE) to transmit the sensing data in real time to the gateway, and a cloud which accumulate and analyze data. To assess the system accuracy, 3 persons manually counted the outgoing and incoming honey bees using the video record of 360-minute length. The difference between automatic and manual measurements for outgoing and incoming scores were 3.98% and 4.43% respectively. These differences are relatively lower than previous analogues, which inspires a vision that the tested system is a good candidate to use in precise apicultural industry, scientific research and education.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.3
• /
• pp.515-520
• /
• 2022

In context awareness using multiple sensors, when using sensor data detected and sent by each sensor, it is necessary to give different weights for each sensor. Even if the same type of sensor is configured for the same situation, sometimes it is necessary to assign different weights due to other secondary factors. It is inevitable to assign weights to events in the real world, and it can be said that a weighting method that can be used in a context awareness system using multiple sensors is necessary. In this study, we propose a weighting method for each sensor that reports to the host while the sensors continue to detect over time. In most IoT environments, the sensor continues the detection activity, and when the detected value shows a change pattern beyond a predetermined range, it is basically reported to the host. This can be called a kind of data stream environment. A weighting method was proposed for sensing data from multiple sensors in a data stream environment, and the new weighting method was to select and assign weights to data that indicates a context change in the stream.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.2
• /
• pp.115-121
• /
• 2022

As city environments have recently become crowded, there are many obstacles that interfere with the walking of the visually impaired on pedestrian roads. Typical examples include ballads, parking breakers and standing signs, which usually do not get in the way, but blind people may be injured by collisions. To solve such a problem, many solutions have been proposed, but they are limited in applied in practical environments due to the several restrictions such as outside use only, inaccurate obstacle sensing and requirement of special devices. In this paper, we propose a new method to automatically detect obstacles while walking on the pedestrian roads and warn the collision risk in advance by using only sensors embedded in typical mobile phones. The proposed method supports the walking of the visually impaired by notifying the type of obstacles appearing in front of them as well as the distance remaining from the obstacles. To accomplish this goal, we utilized an object recognition technology applying the latest deep learning algorithms in order to identify the obstacles appeared in real-time videos. In addition, we also calculate the distance to the obstacles using the number of steps and the pedestrian's stride. Compared to the existing walking support technologies for the visually impaired, our proposed method ensures efficient and safe walking with only simple devices regardless of the places.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.3
• /
• pp.239-247
• /
• 2022

Cities are becoming more complex due to rapid industrialization and population growth in modern times. In particular, urban areas are rapidly changing due to housing site development, reconstruction, and demolition. Thus accurate road information is necessary for various purposes, such as High Definition Map for autonomous car driving. In the case of the Republic of Korea, accurate spatial information can be generated by making a map through the existing map production process. However, targeting a large area is limited due to time and money. Road, one of the map elements, is a hub and essential means of transportation that provides many different resources for human civilization. Therefore, it is essential to update road information accurately and quickly. This study uses Semantic Segmentation algorithms Such as LinkNet, D-LinkNet, and NL-LinkNet to extract roads from drone images and then apply hyperparameter optimization to models with the highest performance. As a result, the LinkNet model using pre-trained ResNet-34 as the encoder achieved 85.125 mIoU. Subsequent studies should focus on comparing the results of this study with those of studies using state-of-the-art object detection algorithms or semi-supervised learning-based Semantic Segmentation techniques. The results of this study can be applied to improve the speed of the existing map update process.