• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.6
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• pp.183-190
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• 2011

In this paper, we propose a prototype system for abnormal sound detection and identification which detects and recognizes the abnormal situations by means of analyzing audio information coming in real time from CCTV cameras under surveillance environment. The proposed system is composed of two layers: The first layer is an one-class support vector machine, i.e., support vector data description (SVDD) that performs rapid detection of abnormal situations and alerts to the manager. The second layer classifies the detected abnormal sound into predefined class such as 'gun', 'scream', 'siren', 'crash', 'bomb' via a sparse representation classifier (SRC) to cope with emergency situations. The proposed system is designed in a hierarchical manner via a mixture of SVDD and SRC, which has desired characteristics as follows: 1) By fast detecting abnormal sound using SVDD trained with only normal sound, it does not perform the unnecessary classification for normal sound. 2) It ensures a reliable system performance via a SRC that has been successfully applied in the field of face recognition. 3) With the intrinsic incremental learning capability of SRC, it can actively adapt itself to the change of a sound database. The experimental results with the qualitative analysis illustrate the efficiency of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.61-69
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• 2012

Smart Grid is the next-generation intelligent power grid that maximizes energy efficiency with the convergence of IT technologies and the existing power grid. Smart Grid is created solution for standardization and interoperability. Smart Grid industry enables consumers to check power rates in real time for active power consumption. It also enables suppliers to measure their expected power generation load, which stabilizes the operation of the power system. Smart industy was ecolved actively cause Wireless communication is being considered for AMI system and wireless communication using ZigBee sensor has been applied in various industly. In this paper, we proposed efficient addressing scheme for improving the performance of the routing algorithm using ZigBee in Smart Grid environment. A distributed address allocation scheme used an existing algorithm has wasted address space. Therefore proposing x, y coordinate axes from divide address space of 16 bit to solve this problem. Each node was reduced not only bitwise but also multi hop using the coordinate axes while routing than Cskip algorithm. I compared the performance between the standard and the proposed mechanism through the numerical analysis. Simulation verify performance about decrease averaging multi hop count that compare proposing algorithm and another. The numerical analysis results show that proposed algorithm reduce multi hop than ZigBee distributed address assignment and another.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.7 no.1
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• pp.51-58
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• 2013

As it is changing into aging society, rehabilitation, welfare and sports industry markets are being expanded fast. Especially, the field of vital signals interface to control welfare instruments like wheelchair, rehabilitation ones like an artificial arm and leg and general electronic ones is a new technology field in the future. Also, this technology can help not only the handicapped, the old and the weak and the rehabilitation patients but also the general public in various application field. The commercial bio-signal measurement instruments and interface systems are complicated, expensive and large-scaled. So, there are a lot of limitations for using in real life with ease. this thesis proposes a wireless transmission interface system that uses EMG(electromyogram) signals and a control module to manipulate hardware systems with portable size. We have designed a hardware module that receives the EMG signals occurring at the time of wrist movement and eliminated noises with filter and amplified the signals effectively. DSP(Digital Signal Processor) chip of TMS320F2808 which was supplied from TI company was used for converting into digital signals from measured EMG signals and digital filtering. We also have used PCA(Principal Component Analysis) technique and classified into four motions which have right, left, up and down direction. This data was transmitted by wireless module in order to display at PC monitor. As a result, the developed system obtains recognition success ratio above 85% for four different motions. If the recognition ratio will be increased with more experiments. this implemented system using EMG wrist direction signals could be used to control various hardware systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.7-15
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• 2022

Since the direct and indirect damage caused by the fire in the underground utility tunnel will cause great damage to society as a whole, it is necessary to make efforts to prevent and control it in advance. The most of the fires that occur in cables are caused by short circuits, earth leakage, ignition due to over-current, overheating of conductor connections, and ignition due to sparks caused by breakdown of insulators. In order to find the cause of fire at an early stage due to the characteristics of the underground utility tunnel and to prevent disasters and safety accidents, we are constantly managing it with a detection system using image analysis and making efforts. Among them, a case of developing a fire detection system using CCTV-based deep learning image analysis technology has been reported. However, CCTV needs to be supplemented because there are blind spots. Therefore, we would like to develop a high-performance acoustic-based deep learning model that can prevent fire by detecting the spark sound before spark occurs. In this study, we propose a method that can collect sound in underground utility tunnel environments using microphone sensor through development and experiment of prototype module. After arranging an acoustic sensor in the underground utility tunnel with a lot of condensation, it verifies whether data can be collected in real time without malfunction.

• Journal of Ginseng Research
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• v.47 no.5
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• pp.627-637
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• 2023

Background: Damage to the healthy intestinal epithelial layer and regulation of the intestinal immune system, closely interrelated, are considered pivotal parts of the curative treatment for inflammatory bowel disease (IBD). Plant-based diets and phytochemicals can support the immune microenvironment in the intestinal epithelial barrier for a balanced immune system by improving the intestinal microecological balance and may have therapeutic potential in colitis. However, there have been only a few reports on the therapeutic potential of plant-derived exosome-like nanoparticles (PENs) and the underlying mechanism in colitis. This study aimed to assess the therapeutic effect of PENs from Panax ginseng, ginseng-derived exosome-like nanoparticles (GENs), in a mouse model of IBD, with a focus on the intestinal immune microenvironment. Method: To evaluate the anti-inflammatory effect of GENs on acute colitis, we treated GENs in Caco2 and lipopolysaccharide (LPS) -induced RAW 264.7 macrophages and analyzed the gene expression of proinflammatory cytokines and anti-inflammatory cytokines such as TNF-α, IL-6, and IL-10 by real-time PCR (RT-PCR). Furthermore, we further examined bacterial DNA from feces and determined the alteration of gut microbiota composition in DSS-induced colitis mice after administration of GENs through 16S rRNA gene sequencing analysis. Result: GENs with low toxicity showed a long-lasting intestinal retention effect for 48 h, which could lead to effective suppression of pro-inflammatory cytokines such as TNF-α and IL-6 production through inhibition of NF-κB in DSS-induced colitis. As a result, it showed longer colon length and suppressed thickening of the colon wall in the mice treated with GENs. Due to the amelioration of the progression of DSS-induced colitis with GENs treatment, the prolonged survival rate was observed for 17 days compared to 9 days in the PBS-treated group. In the gut microbiota analysis, the ratio of Firmicutes/Bacteroidota was decreased, which means GENs have therapeutic effectiveness against IBD. Ingesting GENs would be expected to slow colitis progression, strengthen the gut microbiota, and maintain gut homeostasis by preventing bacterial dysbiosis. Conclusion: GENs have a therapeutic effect on colitis through modulation of the intestinal microbiota and immune microenvironment. GENs not only ameliorate the inflammation in the damaged intestine by downregulating pro-inflammatory cytokines but also help balance the microbiota on the intestinal barrier and thereby improve the digestive system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.374-380
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• 2017

In this study, we analyzed the situation of the 119 emergency medical service zone of H town, countryside of Y city from January 1st, 2015 to December 31st, 2016 and then, on the basis of this analysis, we investigated the present condition of the patient-transportation service of the 119 emergency medical service to provide the basic data in order for patients to use the emergency medical service more efficiently. We analyzed the data with SPSS 21.0 using frequency analysis and, after positioning the virtual 119 emergency medical service, we analyzed the data of the transportation time and transportation distance by using GIS. The results of this study show that the use of the 119 emergency medical service for people over 65 years old represents approximately 57% of the total number of patients transported, The average distance and time of the real moving reaction are 6.41 km and 11.86 min, respectively. The distance and time from the pick-up location to the hospital are 18.24 km and 21.52 min, respectively. Given the present position of the 119 emergency medical service, the results of this analysis using GPS show that the (average) distance and time from the 119 emergency medical service to Jang * Ri town are 9.12 km and 12 min, and the (average) total distance and time to arrive at the hospital after the emergency medical service picks up the patient are 36.83 km and 62 min, respectively. In the case of the virtual emergency medical service, the total distance and time required to arrive at the hospital after the emergency medical service picks up the patient are 27.71km and 50min, respectively. The results of this study showed that the present position of the 119 emergency service does not provide the optimum distance and time from the patient's location to the hospital. Therefore, we consider that the repositioning of the 119 emergency medical center is necessary, in order to reduce the time required for the emergency medical service to move to the patient's location and then bring the patient to the hospital.

• Journal of Korean Society of Environmental Engineers
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• v.27 no.9
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• pp.952-957
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• 2005

A sensitivity analysis study was performed to examine the effects of cell size on a distributed non-point source pollution model. The model, AnnAGNPS, whiff is a modified version of USDA's AGNPS, was applied to Eung stream watershed, a tributary of Cheongmi stream located in the South Branch of Han River System. The model components and results, such as channel length, slope, land use, and delivery ratio, were analyzed according to the various cell sizes from 10 to 200 ha. As cell sire increases, channel length decreases due to short-circuiting of meandering creek. The decreased channel length has more significant effects on the model results than any other geomorphological change. When the effects of land use and soil distribution are excluded, sediment delivery loads increase due to shorter time to reach the outlet of the watershed in larger tell size. When those effects are included, however, sediment delivery loads decrease in larger fell size because the variety of land use types can not be inputted. The predominant land use in the applied watershed is forest with very low soil erosion such that the predicted sediment delivery might be much lower than real system. The cell size of 30 ha was determined to produce the most appropriate resolution. Surface runoff and non-point source loads of TN, TP and BOD were predicted and the results agree well with the field measurements. From this study, it was shown that the model results would be very dependent on variations of topography, land use, and soil distribution, as a function of cell size, and the optimum cell size is very important for successful application of distributed non-point source pollution model.

• Analytical Science and Technology
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• v.27 no.2
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• pp.108-113
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• 2014

The harmful materials as volatile organic compounds (VOCS) that is easy for gas to be changed from liquid on ambient temperature, those should be controlled by Korea Chemicals Management Association. The VOCs samples should be collected directly in place so that those could be analyzed. Generally but it couldn't avoid to have the risk of analyst. Moreover, if there is the place limited to entrance, it is impossible to collect directly and measure. Owing to such problem, it tried to be solved by open path FT-IR spectrometer that could be studied on the combustion gases within long path and VOCs samples were tried to measure to large volume by remote and real time. Firstly, it was to investigate optimized measured length between the system and benzene sample of VOCs. As result, The optimized measured length was confirmed with 15 meter length and the qualitative analysis could be measured on seven VOC samples. The calibration curve as quantitative analysis of benzene samples could be worked. On the basis of the result, the system as remote monitor could show to have potentiality.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.739-744
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• 2017

Elastic deformation and fatigue damage can cause the permanent deformation of a kart's frame during turning, affecting the kart's driving performance. A kart's frame does not contain any suspension or differential devices and, therefore, the dynamic behavior caused by torsional deformation when driving along a curve can strongly affect these two kinds of deformations. To analyze the dynamic behavior of a kart along a curved section, the GPS trajectory of the kart is obtained and the torsional stress acting on the kart-frame is measured in real time. The mechanical properties of leisure and racing karts are investigated by analyzing their material properties and conducting a tensile test. The torsional stress concentration and frame distortion are investigated through a stress analysis of the frame on the basis of the obtained results. Leisure and racing karts are tested in each driving condition using driving analysis equipment. The behavior of a kart when being driven along a curved section is investigated through this test. Because load movement occurs owing to centrifugal force when driving along a curve, torsional stress acts on the kart's steel frame. In the case of a leisure kart, the maximum torsional stress derived from the torsional fatigue limit was found to be 230 MPa, and the torsional fatigue limit coefficient was 0.65 when driving at a speed of 40 km/h. Furthermore, the driving elements during the cornering of a kart were measured based on an actual auto-test after installing a driving measurement system, and the driving behavior of the kart was analyzed by measuring its vertical displacement.

• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.77-86
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• 2022

The Republic of Korea is a country in which coastal surveillance is an imperative national task as it is surrounded by seas on three sides under the confrontation between South and North Korea. However, due to Defense Reform 2.0, the number of R/D (Radar) operating personnel has decreased, and the period of service has also been shortened. Moreover, there is always a possibility that a human error will occur. This paper presents specific guidelines for developing an AI learning model for the intelligent coastal surveillance system. We present a three-step strategy to realize the guidelines. The first stage is a typical stage of building an AI learning model, including data collection, storage, filtering, purification, and data transformation. In the second stage, R/D signal analysis is first performed. Subsequently, AI learning model development for classifying real and false images, coastal area analysis, and vulnerable area/time analysis are performed. In the final stage, validation, visualization, and demonstration of the AI learning model are performed. Through this research, the first achievement of making the existing weapon system intelligent by applying the application of AI technology was achieved.