• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.6
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• pp.171-178
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• 2010

Pipeline structure is one of core underground infrastructure which transports primary sources. Since the almost pipeline structures are placed underground and connected each other complexly, it is difficult to monitor their structural health condition continuously. In order to overcome this limitation of recent monitoring technique, recently, a Ubiquitous Sensor Network (USN) system based on on-line and real-time monitoring system is being developed by the authors' research group. In this study, real-time pipeline health monitoring (PHM) methodology is presented based on electromechanical impedance methods using USN. Two types of damages including loosened bolts and notches are artificially inflicted on the pipeline structures, PZT and MFC sensors that have piezoelectric characteristics are employed to detect these damages. For objective evaluation of pipeline conditions, Damage metric such as Root Mean Square Deviation (RMSD) value was computed from the impedance signals to quantify the level of the damage. Optimal threshold levels for decision making are estimated by generalized extreme value(GEV) based statistical method. Throughout a series of experimental studies, it was reviewed the effectiveness and robustness of proposed PHM system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.1916-1932
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• 1997

The synchronous stream cipher which require absoulte clock synchronization has the problem of synchronization loss by cycle slip. Synchronization loss makes the state which sender and receiver can't communicate with each other and it may break the receiving system. To lessen the risk, we usually use a continuous resynchronization method which achieve resynchronization at fixed timesteps by inserting synchronization pattern and session key. While we can get resynchronization effectively by continuous resynchroniation, there are some problems. In this paper, we proposed an adaptive resynchronization algorithm for cipher system using HDLC protocol. It is able to solve the problem of the continuous resynchronization. The proposed adaptive algorithm make resynchronization only in the case that the resynchronization is occurred by analyzing the address field of HDLC. It measures the receiving rate of theaddress field in the decision duration. Because it make resynchronization only when the receiving rate is greateer than the threshold value, it is able to solve the problems of continuous resynchronization method. When the proposed adaptive algorithm is applied to the synchronous stream cipher system in packet netork, it has addvance the result in R_e and D_e.

• Korean Journal of Agricultural Science
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• v.47 no.3
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• pp.615-624
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• 2020

An effective sampling method is necessary to monitor potato tuber moths (Phthorimaea operculella) because they are the biggest concern in potato-cultivating areas. In this study, a sequential sampling method was developed based on the results of field surveys of potato tuber moths in South Korea. Potato tuber moths were collected in fields cultivating potatoes at six sites, and their spatial distribution was investigated using the Taylor power law. The optimal sampling size and cumulative number of potato tuber moths in traps to stop sampling were determined based on the spatial distribution pattern and mean density of the collected potato tuber moths. Finally, the developed sampling method was applied to propose a control action, and its sampling efficiency was compared with that of the traditional sampling method using a binomial distribution. The potato tuber moths tended to aggregate; the optimal number was approximately 5 - 16 traps for sampling, and the number varied with the mean density of potato tuber moths according to the sampling sites. In addition, one, two, and three sites might require the following actions: Continued sampling, control, and no control, respectively. Sampling with the binomial distribution showed the minimum sample size was 12 when considering the economic threshold level. Here, we propose an effective sampling method that can be applied for future monitoring and field surveys of potato tuber moths in South Korea.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.287-292
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• 2012

In this study, Multi-Channel Magnetic Flux Leakage(MFL) sensor - based inspection system was applied to monitor the condition of cables. This inspection system measures magnetic flux to detect the local faults(LF) of steel cable. To verify the feasibility of the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to determine the locations of the flaws and the level of damage. Measured signals from the damaged specimen were compared with thresholds set for objective decision making. In addition, the magnetic flux density values measured from every channel were summed to focus on the detection of axial location. And, sum of flux density were displayed with threshold. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.

• Clinical and Experimental Reproductive Medicine
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• v.38 no.1
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• pp.47-52
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• 2011

Objective: To determine whether characteristics of sperm motility obtained by computer-assisted sperm analysis (CASA) could predict pregnancy after intrauterine insemination (IUI) in couples with unexplained infertility. Methods: Three hundred eighty-three cycles of intrauterine insemination with superovulation were retrospectively analyzed. Semen analysis was performed with CASA before and after swim-up and the parameters were compared between pregnant and non-pregnant women. Results: The pregnancy rate per cycle was 14.1%. Pregnant and non-pregnant women were comparable in terms of age, infertility duration, the number of dominant follicles. While sperm concentration, motility, and parameters such as average path velocity (VAP) and percentage rapid (RAPID) before semen preparation were significantly different between the pregnancy and non-pregnancy groups, there were no differences in sperm parameters when comparing the two groups after preparation. Using a receiver operating characteristic curve to measure sensitivity and specificity, the optimal threshold value for the predictors of pregnancy was revealed to be a concentration of ${\geq}111{\times}10^6/mL$, a motility of ${\geq}$ 51.4%, and RAPID ${\geq}$ 30.1% before preparation for IUI. Conclusion: Sperm parameters including concentration, motility, and RAPID before sperm preparation could have predictive value for pregnancy outcome after intrauterine insemination with superovulation in couples with unexplained infertility, and would be helpful when counseling patients before they make the decision to proceed with IVF/ICSI-ET.

• Korean Journal of Agricultural and Forest Meteorology
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• v.11 no.4
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• pp.221-232
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• 2009

The geographical distribution of freeze risk determines the latitudinal and altitudinal limits and the maximum acreage suitable for fruit production. Any changes in its pattern can affect the policy for climate change adaptation in fruit industry. High-definition digital maps for such applications are not available yet due to uncertainty in the combined responses of temperature and dormancy depth under the future climate scenarios. We applied an empirical freeze risk index, which was derived from the combination of the dormancy depth and threshold temperature inducing freeze damage to dormant buds of 'Changhowon Hwangdo' peach trees, to the high-definition digital climate maps prepared for the current (1971-2000), the near future (2011-2040) and the far future (2071-2100) climate scenarios. According to the geospatial analysis at a landscape scale, both the safe and risky areas will be expanded in the future and some of the major peach cultivation areas may encounter difficulty in safe overwintering due to weakening cold tolerance resulting from insufficient chilling. Our test of this method for the two counties representing the major peach cultivation areas in South Korea demonstrated that the migration of risky areas could be detected at a sub-grid scale. The method presented in this study can contribute significantly to climate change adaptation planning in agriculture as a decision aids tool.

• Journal of the Korea Computer Industry Society
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• v.3 no.1
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• pp.95-104
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• 2002

This paper presents some studies on the Internet TCP/IP(Transmission Control Protocol-Internet Protocol) traffic over ATM(Asynchronous Transfer Mode) UBR(Unspecified Bit Rate) and ABR(Available Bit Rate) classes of service. Fuzzy logic prediction has been used to improve the efficiency and fairness of traffic throughput. For TCP/IP over UBR, a novel fuzzy logic based cell dropping scheme is presented. This is referred to as fuzzy logic selective cell drop (FSCD). A key feature of the scheme is its ability to accept or drop a new incoming packet dynamically based on the predicted future buffer condition in the switch. This is achieved by using fuzzy logic prediction for the production of a drop factor. Packet dropping decision is then based on this drop factor and a predefined threshold value. Simulation results show that the proposed scheme significantly improves TCP/IP efficiency and fairness. To study TCP/IP over ABR, we applied the fuzzy logic ABR service buffer management scheme from our previous work to both approximate and exact fair rate computation ER(Explicit cell Rate) switch algorithms. We then compared the performance of the fuzzy logic control with conventional schemes. Simulation results show that on zero TCP packet loss, the fuzzy logic control scheme achieves maximum efficiency and perfect fairness with a smaller buffer size. When mixed with VBR traffic, the fuzzy logic control scheme achieves higher efficiency with lower cell loss.

• Journal of The Korean Society of Grassland and Forage Science
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• v.44 no.2
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• pp.71-82
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• 2024

It would be advantageous to grow legume forage crops in order to increase the productivity and sustainability of sloped croplands in Hamkyongbukdo. In particular, the identification of potential cultivation areas for alfalfa in the given region could aid decision-making on policies and management related to forage crop production in the future. This study aimed to analyze the climate suitability of alfalfa in Hamkyongbukdo under current and future climate conditions using the Fuzzy Union model. The climate suitability predicted by the Fuzzy Union model was compared with the actual alfalfa cultivation area in the northern United States. Climate data obtained from 11 global climate models were used as input data for calculation of climate suitability in the study region to examine the uncertainty of projections under future climate conditions. The area where the climate suitability index was greater than a threshold value (22.6) explained about 44% of the variation in actual alfalfa cultivation areas by state in the northern United States. The climatic suitability of alfalfa was projected to decrease in most areas of Hamkyongbukdo under future climate scenarios. The climatic suitability in Onseong and Gyeongwon County was analyzed to be over 88 in the current climate conditions. However, it was projected to decrease by about 66% in the given areas by the 2090s. Our study illustrated that the impact of climate change on suitable cultivation areas was highly variable when different climate data were used as inputs to the Fuzzy Union model. Still, the ensemble of the climate suitability projections for alfalfa was projected to decrease considerably due to summer depression in Hamkyongbukdo. It would be advantageous to predict suitable cultivation areas by adding soil conditions or to predict the climate suitability of other leguminous crops such as hairy vetch, which merits further studies.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.4
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• pp.535-547
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• 2019

In this study, the heavy metal analysis in sediments (surface sediments, sediments cores and settling particles) from Shihwa Lake has been carried out to evaluate the changes of metal pollution levels in sediments after the operation of Tidal Power Plant (TPP). The average concentrations of metals in surface sediments sampled in 2015 were 8% (Cd)~31% (Zn, Hg) lower than in 2009 before TPP operation. Results of calculating the pollution load index (PLI) with 8 metals, the PLI value in 2015 showed a 18% decrease compared to 2009. However, Cu, Zn, Pb concentrations of surface sediments in 2015 at the upper region around industrial complex still exceeded the TEL (threshold effect level) values for sediment quality guideline in Korea. After the operation of TPP, the metal contaminated depths were increasing from 15 cm to 30 cm at S6 site and from 8 cm to 20 cm at S7 site, respectively. Our data showed that the mean concentration of heavy metals in core samples decreased but the contaminated depth increased. The average of the total sedimentation flux for particulate matter increased by 3.2 times from 32.5 g/㎡/d in 2009 to 103.5 g/㎡/d in 2015. This showed that the bottom sediments were resuspended by the operation of TPP, resulting in an increase of particulate matter in the water column. These results suggest that the sediments contaminated with heavy metals seem to be resuspended and relocated due to the water current caused by the operation of TPP. Cr, Cu, Zn, Pb and Cd were highly exceeding the TEL values in the upstream region and accumulated more than 40 cm of sediment depth, indicating that heavy metal contamination through industrial activity were still a serious environmental problem of Shihwa Lake. Although the metal pollution of Shihwa Lake has been slightly reduced, the contaminated sediments with heavy metals inside of Shihwa Lake might be discharged to outer sea after the resuspension by TPP operation. It is necessary for the advanced scientific approach and political decision to drastically reduce the heavy metal pollution of the study region.