• Journal of Environmental Science International
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• v.14 no.6
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• pp.525-532
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• 2005

Polyelectrolyte titration, which was called colloid titration is based on the stoichiometric reaction between oppositely charged polyelectrolytes, This can be used, for instance, to determine the charge density of a cationic polyelectrolyte, using an anionic polyelectrolyte of known charge density, such as potassium polyvinyl sulfate (PPVS). The technique requires a suitable method of end-point detection and there are several possibilities. In this work, two methods have been investigated: visual titrimetry based on the color change of a cationic dye (o-toluidine blue, o-Tb) and spectrophotometry based on the absorbance change corresponding to the color change of the same dye. These have been applied to several cationic polyelectrolytes with different charge density and molecular weight. In all cases, the cationic charge was due to quaternary nitrogen groups. In the case of cationic dye, it was shown that the sharpness depends on the charge density of cationic polyelectrolyte. With the polyelectrolytes of lower charge density, the binding to PPVS is weaker and binding of the dye to PPVS can occur before all of the polyelectrolyte charge has been neutralized. However, by carrying out titrations at several polyelectrolyte concentrations, good linear relationships were found, from which reliable charge density values could be derived. Effects of pH and ionic strength were also briefly investigated. For cationic polyelectrolytes (copolymers of acrylamide and dimethylaminoethy] acrylate), there was some loss of charge at higher pH values, probably as a result of hydrolysis. Increasing ionic strength causes a less distinct color change of o-Tb, as a result of weaker electrostatic interactions.

• Journal of Korea Multimedia Society
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• v.16 no.3
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• pp.302-308
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• 2013

In this research, we have explored personal authentication system through multimodal biometrics for mobile computing environment. We have selected face and speaker recognition for the implementation of multimodal biometrics system. For face recognition part, we detect the face with Modified Census Transform (MCT). Detected face is pre-processed through eye detection module based on k-means algorithm. Then we recognize the face with Principal Component Analysis (PCA) algorithm. For speaker recognition part, we extract features using the end-point of voice and the Mel Frequency Cepstral Coefficient (MFCC). Then we verify the speaker through Dynamic Time Warping (DTW) algorithm. Our proposed multimodal biometrics system shows improved verification rate through combining two different biometrics described above. We implement our proposed system based on Android environment using Galaxy S hoppin. Proposed system presents reduced false acceptance ratio (FAR) of 1.8% which shows improvement from single biometrics system using the face and the voice (presents 4.6% and 6.7% respectively).

• Health Policy and Management
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• v.30 no.4
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• pp.433-437
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• 2020

Cancer is a disease which has the huge burden in worldwide, and cancer is the number one cause of death in Korea. At this point, the new framework for cancer monitoring index is required for regional cancer monitoring. Especially, cancer survivors are the important target which is rapidly increasing recently, also cancer survivor's quality of care should be considered in the cancer monitoring index framework. To develop the Multidimensional Cancer Monitoring Index considering cancer survivor's quality of care, we took into account cancer continuum which including prevention, detection, diagnosis, treatment, survivorship, assessment of quality of care and monitoring cancer patient, and end-of life care for stage. For target, components of health care delivery system such as patient, family, provider, payer, and policy maker are included. Also, Donabedian model which is a framework for examining health services and evaluating quality of health care such as structure, process, and outcome is applied to contents. This new cancer monitoring framework which includes multidimensional components could help to develop regional cancer monitoring index, and to make national cancer management and prevention policy in the future.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.6
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• pp.947-960
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• 2023

In Korea, traditional paper promissory notes are currently undergoing a transformation, being gradually replaced by electronic notes. This transformation is being steered under the Korea Financial Telecommunications Institute, a trusted authority. However, existing electronic systems have security vulnerabilities, including the risk of hacking and internal errors within the institute. To this end, we have defined a novel anonymous electronic promissory note system based on blockchain. We have constructed a concrete protocol and conducted security analysis of our protocol. Note that, in our protocol, every note information is committed so that the note remains undisclosed until the point of payment. Once the note information becomes public on the blockchain, it enables the detection of illicit activities, such as money laundering and tax evasion. Furthermore, our protocol incorporates a feature of split endorsement, which is a crucial functionality permitted by the Korean electronic note system. Consequently, our proposed protocol is suitable for practical applications in financial transactions.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.

• Journal of KIISE:Information Networking
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• v.35 no.2
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• pp.99-111
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• 2008

In recent years, the needs for WLANs(Wireless Local Area Networks) technology which can access to Internet anywhere have been dramatically increased particularly in SOHO(Small Office Home Office) and Hot Spot. However, unlike wired networks, there are some unique characteristics of wireless networks. These characteristics include the burst packet losses due to unreliable wireless channel. Note that burst packet losses, which occur when the distance between the wireless station and the AP(Access Point) increase or when obstacles move temporarily between the station and AP, are very frequent in 802.11 networks. Conversely, due to burst packet losses, the performance of 802.11 networks are not always as sufficient as the current application require, particularly when they use TCP at the transport layer. The high packet loss rate over wireless links can trigger unnecessary execution of TCP congestion control algorithm, resulting in performance degradation. In order to overcome the limitations of WLANs environment, MAC-layer LDA(Loss Differentiation Algorithm)has been proposed. MAC-layer LDA prevents TCP's timeout by increasing CRD(Consecutive Retry Duration) higher than burst packet loss duration. However, in the wireless channel with high packet loss rate, MAC-layer LDA does not work well because of two reason: (a) If the CRD is lower than burst packet loss duration due to the limited increase of retry limit, end-to-end performance is degraded. (b) energy of mobile device and bandwidth utilization in the wireless link are wasted unnecessarily by Reducing the drainage speed of the network buffer due to the increase of CRD. In this paper, we propose a new retransmission module based on Cross-layer approach, called BLD(Burst Loss Detection) module, to solve the limitation of previous link layer retransmission schemes. BLD module's algorithm is retransmission mechanism at IEEE 802.11 networks and performs retransmission based on the interaction between retransmission mechanisms of the MAC layer and TCP. From the simulation by using ns-2(Network Simulator), we could see more improved TCP throughput and energy efficiency with the proposed scheme than previous mechanisms.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.1
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• pp.21-29
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• 2010

Nakdong Estuary Delta plays various roles of worldwide habitat for migratory birds and a sand supplier to Haewoondae Beach and Gwanganri, which are tourist attractions of Busan. In this study, long-term topographical changes of Nakdong Estuary (Jinwoo Islet, Sinja Islet, Doyodeung, Dadae Beach) coast were detected and interpreted. Through the analysis of 34 years' satellite images, it was found out that a part in between front side and back side of Jinwoo Islet increased, Sinja Islet was divided into two belts in 1970, and has formed an islet since the 1980s and extended westward. Due to the rapid development of small islets in front of Baekhabdeung since 1990s, Doyodeung formed in the late 1990s and is still growing. To make coastal map of Nakdong Estuary area, 13 images, of which the tide level was $99{\pm}13cm$, from the 112 Landsat images of the period from 1975 to 2009 were selected to section into water zone and land zone using NDV. And the rates of coastal line change such as MATLAB EPR(End Point Rate) and LRR(Linear Regression Rate) were calculated using DSAS 4.0(Digital Shoreline Analysis System). Through detecting topographical changes, EPR showed that the front(south) and back side(north) of Jinwoo Islet moved southward at -0.93~2.56m/yr, and changes in costal line and area of Jinwoo Islet were low and stable. The front and backside of Sinja Islet moved northward at 1~4m/yr, whereas the west side of Sinja Islet was stable at 2~3m/yr and east side of Sinja Islet moved northward at 10m/yr or faster. The front and back side of Doyodeung moved northward at 18~27m/yr, causing the increase of area, while the coastal line of Dadae Beach moved westward at 7m/yr, causing the expansion of the beach. LRR also demonstrated a similar trend to EPR. Although analysis of satellite images and GIS could enabled detection of topographical changes and quantitative analysis of natural phenomena, we found that continuous observation of natural phenomena and various analytical methods are required.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.18 no.1
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• pp.51-62
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• 2020

This study was conducted to develop a method for depth assessment of embedded sources using gamma-spectrum ratio and for the evaluation of field applicability. To this end, Peak to Compton and Peak to valley ratio changes were evaluated according to ¹³⁷Cs, ⁶⁰Co, ¹⁵²Eu point source depth using HPGe detector and MCNP simulation. The effects of measurement distance of PTV and PTC methods were evaluated. Using the results, the source depth assessment equation using the PTC and PTV methods was derived based on the detection distance of 50 cm. In addition, the sensitivity of detection distance changes was assessed when using PTV and PTC methods, and error increased by 3 to 4 cm when detection distance decreased by 20 cm based on 50 cm. However, it was confirmed that if the detection distance was increased to 100 cm, the effects of detection distance were small. And PTV and PTC methods were compared with the two distance measurement method which evaluates the depth of source by the change of net peak counting rate according to the detection distance. As a result of source depth assessment, the PTV and PTC showed a maximum error of 1.87 cm and the two distance measurement method showed maximum error of 2.69 cm. The results of the experiment confirmed that the accuracy of the PTV and PTC methods was higher than two distance measurement. In addition, Sensitivity evaluation by horizontal position error of source has maximum error of less than 25.59 cm for the two distance measurement method. On the other hand, PTV and PTC method showed high accuracy with maximum error of less than 8.04 cm. In addition, the PTC method has lowest standard deviation for the same time measurement, which is expected to enable rapid measurement.

• Korean Journal of Environmental Biology
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• v.19 no.1
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• pp.59-69
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• 2001

Among the biodegradability tests, TOC-HANDAI and OECD method were utilized to examine the degree of biodegradation of endocrine disruptors, Bisphenol A (BPA) and Nonylphenol. Both methods used natural water microcosms and measured their biodegrada-bilities of BPA and Nonylphenol, in terms of TOC or DOC degradation with time for 28 days. Biodegradabilities for BPA, 73-78% with TOC-HANDAI method and 77-81% with OECD method were obtained respectively at the end of experiment. There was no difference in BPA degradation between two methods. BPA degradation was described by two distinct first order decay rates (k$_1$ and k$_2$) which could be separated by a simple visual fitting. Most of the initial decay reaction accelerated within 1-7 days with k$_1$of 0.24-0.34 $day^{-1}$. And the following another long term first order decay coefficient (k$_2$) showed 0.02-0.05 day$^{-1}$ with much flat slope. About 20-25% of initial BPA remained at the end of experiment. It suggests that the remaining TOC components in BPA biodegradation considered to be refractory metabolites of BPA. Nonylphenol at each sampling point was appeared to be mineralized 20-48% of initial TOC concentration. Consequently Nonylphenol seems more recalcitrant against biodegradation. BPA was not detected in the detection limit of ppb in the watershed of Daechung reservoir and Kum river. However 25 ppb concentration of BPA was detected at the influent of industrial wastewater treatment plant in Taejon.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.1-6
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• 2021

In the field of speech recognition, as the DNN is applied, the use of speech recognition is increasing, but the amount of calculation for parallel training needs to be larger than that of the conventional GMM, and if the amount of data is small, overfitting occurs. To solve this problem, we propose an efficient method for robust voice feature extraction and voice signal noise removal even when the amount of data is small. Speech feature extraction efficiently extracts speech energy by applying the difference in frame energy for speech and the zero-crossing ratio and level-crossing ratio that are affected by the speech signal. In addition, in order to remove noise, the noise of the speech signal is removed by removing the noise of the speech signal with an average predictive improved LMS filter with little loss of speech information while maintaining the intrinsic characteristics of speech in detection of the speech signal. The improved LMS filter uses a method of processing noise on the input speech signal by adjusting the active parameter threshold for the input signal. As a result of comparing the method proposed in this paper with the conventional frame energy method, it was confirmed that the error rate at the start point of speech is 7% and the error rate at the end point is improved by 11%.