• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.81-88
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• 2018

In this paper, we present some problems with the Groupware Messenger functionality based on dot net 2.0 and implement a new design structure to solve them. They include memory leakage, slow processing, and client window memory crash. These problems resulted in the inconvenience of using instant messaging and the inefficient handling of office tasks. Therefore, in this paper, instant messaging functionality is implemented according to a new design architecture. The new system upgrades dot net 4.5 for clients and deploys the new features based on MQTT for the messenger server. We verify that the memory leak problem and client window memory crash issues have been eliminated on the system with the new messenger functionality. We measure the amount of time it takes to bind data to a set of messages and evaluate the performance, compared to a given system. Through this comparative evaluation, we can see that the new system is more reliable and performing.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.100-113
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• 2003

In order to improve business competency by the IS(Information Systems), every enterprise needs to evaluate the current level of IS performance and their utilization. The evaluation that measures the performance of enterprise information systems and diagnoses their effectiveness of business goals and efficiency of resources should represent the useful informations based on sustainable goal-oriented viewpoints to managers. This work develops an integrated evaluation system for continuous maturity of information systems performance, enabling enterprises to achieve their goals of information systems and related business strategies. The integrated evaluation system has been applied to performance measurement of information systems with a huge set of real data from domestic industries for three years, and proven reliable and practical.

• The Journal of Bigdata
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• v.6 no.1
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• pp.145-151
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• 2021

In recent years, digital data has been generated in all areas of human activity, and there are many attempts to safely store and process the data to develop useful services. A data lake refers to a data repository that is independent of the source of the data and the analytical framework that leverages the data. In this paper, we designed a tool to safely store various big data generated by smart cities in a data lake and ETL it so that it can be used in services, and a web-based tool necessary to use it effectively. Implement. A series of processes (ETLs) that quality-check and refine source data, store it safely in a data lake, and manage it according to data life cycle policies are often significant for costly infrastructure and development and maintenance. It is a labor-intensive technology. The mounting technology makes it possible to set and execute ETL work monitoring and data life cycle management visually and efficiently without specialized knowledge in the IT field. Separately, a data quality checklist guide is needed to store and use reliable data in the data lake. In addition, it is necessary to set and reserve data migration and deletion cycles using the data life cycle management tool to reduce data management costs.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.279-290
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• 2013

In digital forensics log files have been stored as a form of large data for the purpose of tracing users' past behaviors. It is difficult for investigators to manually analysis the large log data without clues. In this paper, we propose a text mining technique for extracting intrusion logs from a large log set to recommend reliable evidences to investigators. In the training stage, the proposed method extracts intrusion association words from a training log set by using Apriori algorithm after preprocessing and the probability of intrusion for association words are computed by combining support and confidence. Robinson's method of computing confidences for filtering spam mails is applied to extracting intrusion logs in the proposed method. As the results, the association word knowledge base is constructed by including the weights of the probability of intrusion for association words to improve the accuracy. In the test stage, the probability of intrusion logs and the probability of normal logs in a test log set are computed by Fisher's inverse chi-square classification algorithm based on the association word knowledge base respectively and intrusion logs are extracted from combining the results. Then, the intrusion logs are recommended to investigators. The proposed method uses a training method of clearly analyzing the meaning of data from an unstructured large log data. As the results, it complements the problem of reduction in accuracy caused by data ambiguity. In addition, the proposed method recommends intrusion logs by using Fisher's inverse chi-square classification algorithm. So, it reduces the rate of false positive(FP) and decreases in laborious effort to extract evidences manually.

• Journal of the Korean Society of Radiology
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• v.12 no.3
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• pp.297-304
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• 2018

U.S. nuclear power plant decommissioning guidelines(MARSSIM and MARLAP) are recommends to use DQOs when planning and conducting site surveys. The DQOs which is constructed in the site survey planning stage provide a way to make the best use of data. It helps we can get the important information and data to make decisions as well. From fifth to seventh steps of DQOs are the process of designing a site survey by using the collected data and information in the previous step to make reasonable and reliable decisions. The gray region that is set up during this process is defined as the range of concentrations where the consequences of type II decision errors are relatively small. The gray region can be set using DCGL and the average concentration of radionuclide in the sample collected at the survey unit. By setting up the gray region, site survey plan can be made most resource-efficient and the consequences on decision errors can be minimized. In this study, we set up the gray region by using the DCGL of Kori-1 which was derived from the previous research. In addition, we proposed a method to assess the concentration of radionuclide in samples for making decisions correctly.

• Phonetics and Speech Sciences
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• v.11 no.4
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• pp.97-108
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• 2019

An automated Praat script was implemented to measure optimal formant frequencies for adults. Optimal formant analysis could be interpreted to show that the deviation of formant frequency that resulted from the two variously combined setting parameters (maximum formant and number of formants) was minimal. To increase the reliability of formant analysis, LPC order should be set differently, based on the gender or vowel type. Praat recommends 5,000 Hz and 5,500 Hz as maximum formant settings and, at the same time, recommends 5 as the number of formants for males and females. However, verification is needed to determine whether these recommended settings are valid for Korean vowels. Statistical analysis showed that formant frequencies significantly varied across the adapted scripts, especially with respect to the data on females. Formant plots and statistical results showed that linear_script and qtone_script are much more reliable in formant measurements. Among four kinds of scripts, the linear and qtone_scripts proved to be more stable and reliable. While the linear_script was designed to have a linearly increased formant step in for-loop, the increment of formant step in the qtone_script was arranged by quarter tone scale (base frequency×common ratio ($\sqrt[24]{2}$)). When looking at the tendency of the formant setting drawn by the two referred algorithms in the context of front vowel [i, e], the maximum formant was set higher; and the number of formants set at a lower value than recommended by Praat. The back vowel [o, u], on the contrary, has a lower maximum formant and a higher number of formants than the standard setting.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.65-65
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• 2002

In remote sensing, images are acquired over the same area by sensors of different spectral ranges (from the visible to the microwave) and/or with different number, position, and width of spectral bands. These images are generally partially redundant, as they represent the same scene, and partially complementary. For many applications of image classification, the information provided by a single sensor is often incomplete or imprecise resulting in misclassification. Fusion with redundant data can draw more consistent inferences for the interpretation of the scene, and can then improve classification accuracy. The common approach to the classification of multisensor data as a data fusion scheme at pixel level is to concatenate the data into one vector as if they were measurements from a single sensor. The multiband data acquired by a single multispectral sensor or by two or more different sensors are not completely independent, and a certain degree of informative overlap may exist between the observation spaces of the different bands. This dependence may make the data less informative and should be properly modeled in the analysis so that its effect can be eliminated. For modeling and eliminating the effect of such dependence, this study employs a strategy using self and conditional information variation measures. The self information variation reflects the self certainty of the individual bands, while the conditional information variation reflects the degree of dependence of the different bands. One data set might be very less reliable than others in the analysis and even exacerbate the classification results. The unreliable data set should be excluded in the analysis. To account for this, the self information variation is utilized to measure the degrees of reliability. The team of positively dependent bands can gather more information jointly than the team of independent ones. But, when bands are negatively dependent, the combined analysis of these bands may give worse information. Using the conditional information variation measure, the multiband data are split into two or more subsets according the dependence between the bands. Each subsets are classified separately, and a data fusion scheme at decision level is applied to integrate the individual classification results. In this study. a two-level algorithm using hierarchical clustering procedure is used for unsupervised image classification. Hierarchical clustering algorithm is based on similarity measures between all pairs of candidates being considered for merging. In the first level, the image is partitioned as any number of regions which are sets of spatially contiguous pixels so that no union of adjacent regions is statistically uniform. The regions resulted from the low level are clustered into a parsimonious number of groups according to their statistical characteristics. The algorithm has been applied to satellite multispectral data and airbone SAR data.

• The Journal of the Acoustical Society of Korea
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• v.28 no.5
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• pp.409-415
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• 2009

The head-related transfer function (HRTF), which has an important role in virtual sound localization has different characteristics across the subjects. Measuring HRTF is very time-consuming and requires a set of specific apparatus. Accordingly, HRTF customization is often employed. In this paper, we propose a method to search an adequate HRTF from a set of the HRTFs. To achieve rapid and reliable customization of HRTF, all HRTFs in the database are partitioned, where a binary search tree was employed. The distortion measurement adopted in HRTF partitioning was determined in a heuristic way, which predicts the differences in perceived sound location well. The DC-Davis CIPIC HRTF database set was used to evaluate the effectiveness of the proposed method. In the listening test, where 10 subjects were participated, the stimuli filtered by the HRTF obtained by the proposed method were closer to those by the personalized HRTF in terms of sound localization. Moreover, performance of the proposed method was shown to be superior to the previous customization method, where the HRFT is selected by using anthropometric data.

• International Journal of Computer Science & Network Security
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• v.24 no.8
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• pp.32-42
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• 2024

The Internet of Things (IoT) is set to transform patient care by enhancing data collection, analysis, and management through medical sensors and wearable devices. However, the convergence of IoT device vulnerabilities and the sensitivity of healthcare data raises significant data integrity and privacy concerns. In response, this research introduces the Smart-Coord system, a practical and affordable solution for securing healthcare IoT. Smart-Coord leverages blockchain technology and coordinate-based access management to fortify healthcare IoT. It employs IPFS for immutable data storage and intelligent Solidity Ethereum contracts for data integrity and confidentiality, creating a hierarchical, AES-CBC-secured data transmission protocol from IoT devices to blockchain repositories. Our technique uses a unique coordinate system to embed confidentiality and integrity regulations into a single access control model, dictating data access and transfer based on subject-object pairings in a coordinate plane. This dual enforcement technique governs and secures the flow of healthcare IoT information. With its implementation on the Matic network, the Smart-Coord system's computational efficiency and cost-effectiveness are unparalleled. Smart-Coord boasts significantly lower transaction costs and data operation processing times than other blockchain networks, making it a practical and affordable solution. Smart-Coord holds the promise of enhancing IoT-based healthcare system security by managing sensitive health data in a scalable, efficient, and secure manner. The Smart-Coord framework heralds a new era in healthcare IoT adoption, expertly managing data integrity, confidentiality, and accessibility to ensure a secure, reliable digital environment for patient data management.

• Fashion & Textile Research Journal
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• v.12 no.4
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• pp.467-476
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• 2010

The purpose of this study was to develop a plausible methodology based on experimental data how to set up darts and split lines on 3D parametric body dressed with tight-fit garment. The results were as following: Through the process of making convex hull, the concave parts were straightened to make a convex hull, especially in the center part of bust, under breast part and scapular part. To figure out the optimum positions of darts and split lines, the inflection points of curve ratio were searched along the horizontal polylines of waist and bust. This procedures produced reliable results with low deviation. Using Rapidform, CATIA and Unigraphics, six patches of bodice patterns were drawn and aligned. Paired t-test results showed the outline and area between 3D surface and 2D were not significantly different, meaning this method could be adaptable when flattening 3D surfaces. The amount of waist dart measured on the pattern showed that the highest portion was allocated on 2nd dart(back), followed by 1st dart(back), 1st dart(front), 2nd dart(front)/side dart, and center back dart. A series of findings suggested that curve ration inflection point could be used as a guide to set up darts and split line on 3D parametric model with low deviation.