• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.19 no.2
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• pp.111-116
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• 1983

In order to furnish the fundamental data for the domestic production of magnetic compass and the prescription of standardization about it in Korea, authors made the helmholtz coil and investigated the characteristics of them. Subsequently, the damping curves of T190 and T165 compasses in the helmholtz coil were measured and analyzed the performance of those compass. The results obtained are as follows; 1. The relation between electric current (I sub I) to flow in the helmholtz coils, that the thickness of coil is 1mm, diameter 1m, winding number 117, and intensity of magnetic field is presented as follows. Vertical magnetic force: Z(Gauss)=0.34+1.506 I sub(i) Horizontal magnetic force: H(Gauss)=0.183+1.506 I sub(i) 2. Period of T190 compass is longer than T165 compass in all horizontal magnetic force. In the amplitude, the former is larger than the latter above 0.08 Gauss, but this phenomenon is opposed to that below 0.08 Gauss. 3. As the porizontal magnetic force is intensive, period of magnetic compass is short, amplitude is large, and damping degree and damping factor are small. The time elapsed to the principal points of damping curve is proportional to the -0.65 power of the horizontal magnetic force.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.97-103
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• 2009

In this thesis, we discuss the implementation of parallel processing system which is able to get a high degree of efficiency(size, cost, performance and flexibility) by using $Nios^{(R)}$ II(32bit RISC(Reduced Instruction Set Computer) processor) embedded processor in DE2-$70^{(R)}$ reference board. The designed Parallel processing system is master-slave, shared memory and MIMD(Mu1tiple Instruction-Multiple Data stream) architecture with 4-processor. For performance test of system, N-point FFT is used. The result is represented speed-up as follow; in the case of using 2-processor(core), speed-up is shown as average 1.8 times as 1-processor's. When 4-processor, the speed-up is shown as average 2.4 times as it's.

• Membrane Journal
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• v.32 no.1
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• pp.43-49
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• 2022

Solid-state supercapacitors with high safety and robust mechanical properties are attracting global attention as next-generation energy storage devices. As an electrode of a supercapacitor, an economical carbon-based electrode is widely used. However, when an aqueous electrolyte is introduced, the charge transfer resistance increases because the interfacial contact between the hydrophobic electrode surface and aqueous electrolyte is not good. In this regard, we propose a method to obtain higher electrochemical performance based on improved interfacial properties by treating the electrode surface with oxygen plasma. The surface hydrophilization induced by the enriched oxygen functionalities was confirmed by the contact angle measurement. As a result, the degree of hydrophilization was easily adjusted by controlling the power and duration of the oxygen plasma treatment. As the electrolyte of the supercapacitor, PVA/H₃PO₄, which is a typical solid-state aqueous electrolyte, was used. Free-standing membranes of PVA/H₃PO₄ electrolyte were prepared and then pressed onto the electrode. The optimal condition was to perform oxygen plasma treatment for 5 seconds with a low power of 15 W, and the energy density of the supercapacitor increased by about 8%.

• Korean Journal of Cognitive Science
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• v.34 no.2
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• pp.67-84
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• 2023

In this study, Korean older adults (70-75 yrs) were divided into two groups according to the degree of reading exposure, and real-time data were collected through a reading eye movement tracking experiment. Then, overall reading patterns and word frequency ef ects were compared with two groups of older adults and younger adults (20-28 yrs). Furthermore, through the results of the eye movement tracking experiment of older adults with rich reading exposure and older adults with poor reading exposure, we tried to find out whether reading performance af ects not only changes in age but also reading exposure. As a result of the experiment, the older adults with poor reading exposure group generally had a longer fixation time and a shorter saccade than the younger adults group, and the older adults with rich reading exposure group showed the same reading patterns as the younger adults group. The word frequency ef ect was confirmed in all groups, and the fixation time was short in the order of older adults with rich reading exposure group and older adults with poor reading exposure group. In addition, an interaction ef ect was shown in the two elderly groups according to reading exposure, but no interaction could be confirmed in the dif erence between the younger adults group and the older adults with rich reading exposure group. This suggests the possibility that reading performance is not af ected by age itself, but by the reading experience of the elderly.

• The Journal of the Acoustical Society of Korea
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• v.29 no.7
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• pp.458-467
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• 2010

In this paper, a new audio reproduction system was developed in which the cross-talk signals would be reasonably cancelled at an arbitrary listener position. To adaptively remove the cross-talk signals according to the listener's position, a method of tracking the listener position was employed. This was achieved using the two microphones, where the listener direction was estimated using the time-delay between the two signals from the two microphones, respectively. Moreover, room reverberation effects were taken into consideration where linear prediction analysis was involved. To remove the cross-talk signals at the left-and right-ears, the paths between the sources and the ears were represented using the KEMAR head-related transfer functions (HRTFs) which were measured from the artificial dummy head. To evaluate the usefulness of the proposed listener tracking system, the performance of cross-talk cancellation was evaluated at the estimated listener positions. The performance was evaluated in terms of the channel separation ration (CSR), a -10 dB of CSR was experimentally achieved although the listener positions were more or less deviated. A real-time system was implemented using a floating-point digital signal processor (DSP). It was confirmed that the average errors of the listener direction was 5 degree and the subjects indicated that 80 % of the stimuli was perceived as the correct directions.

• The Journal of the Acoustical Society of Korea
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• v.43 no.4
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• pp.422-435
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• 2024

This study intended to verify the effects of face masks on the Korean language in terms of acoustic, aerodynamic, and formant parameters. We chose all types of face masks available in Korea based on filter performance and folding type. Two professional voice actors (a male and a female) with more than 20 years of experience who are native Koreans and speak standard Korean participated in this study as speakers of voice data. Face masks attenuated the high-frequency range, resulting in decreased Vowel Space Area (VSA) and Vowel Articulation Index (VAI)scores and an increased Low-to-High spectral ratio (L/H ratio) in all voice samples. This can result in lower speech intelligibility. However, the degree of increment and decrement was based on the voice characteristics. For female speakers, the Speech Level (SL) and Cepstral Peak Prominence (CPP) increased with increasing face mask thickness. In this study, the presence or filter performance of a face mask was found to affect speech acoustic parameters according to the speech characteristics. Face masks provoked vocal effort when the vocal intensity was not sufficiently strong, or the environment had less reverberance. Further research needs to be conducted on the vocal efforts induced by face masks to overcome acoustic modifications when wearing masks.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.117-127
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• 2012

Due to the recent expansion of the Web 2.0 -based services, along with the widespread of smartphones, online social network services are being popularized among users. Online social network services are the online community services which enable users to communicate each other, share information and expand human relationships. In the social network services, each relation between users is represented by a graph consisting of nodes and links. As the users of online social network services are increasing rapidly, the SNS are actively utilized in enterprise marketing, analysis of social phenomenon and so on. Social Network Analysis (SNA) is the systematic way to analyze social relationships among the members of the social network using the network theory. In general social network theory consists of nodes and arcs, and it is often depicted in a social network diagram. In a social network diagram, nodes represent individual actors within the network and arcs represent relationships between the nodes. With SNA, we can measure relationships among the people such as degree of intimacy, intensity of connection and classification of the groups. Ever since Social Networking Services (SNS) have drawn increasing attention from millions of users, numerous researches have made to analyze their user relationships and messages. There are typical representative SNA methods: degree centrality, betweenness centrality and closeness centrality. In the degree of centrality analysis, the shortest path between nodes is not considered. However, it is used as a crucial factor in betweenness centrality, closeness centrality and other SNA methods. In previous researches in SNA, the computation time was not too expensive since the size of social network was small. Unfortunately, most SNA methods require significant time to process relevant data, and it makes difficult to apply the ever increasing SNS data in social network studies. For instance, if the number of nodes in online social network is n, the maximum number of link in social network is n(n-1)/2. It means that it is too expensive to analyze the social network, for example, if the number of nodes is 10,000 the number of links is 49,995,000. Therefore, we propose a heuristic-based method for finding the shortest path among users in the SNS user graph. Through the shortest path finding method, we will show how efficient our proposed approach may be by conducting betweenness centrality analysis and closeness centrality analysis, both of which are widely used in social network studies. Moreover, we devised an enhanced method with addition of best-first-search method and preprocessing step for the reduction of computation time and rapid search of the shortest paths in a huge size of online social network. Best-first-search method finds the shortest path heuristically, which generalizes human experiences. As large number of links is shared by only a few nodes in online social networks, most nods have relatively few connections. As a result, a node with multiple connections functions as a hub node. When searching for a particular node, looking for users with numerous links instead of searching all users indiscriminately has a better chance of finding the desired node more quickly. In this paper, we employ the degree of user node vn as heuristic evaluation function in a graph G = (N, E), where N is a set of vertices, and E is a set of links between two different nodes. As the heuristic evaluation function is used, the worst case could happen when the target node is situated in the bottom of skewed tree. In order to remove such a target node, the preprocessing step is conducted. Next, we find the shortest path between two nodes in social network efficiently and then analyze the social network. For the verification of the proposed method, we crawled 160,000 people from online and then constructed social network. Then we compared with previous methods, which are best-first-search and breath-first-search, in time for searching and analyzing. The suggested method takes 240 seconds to search nodes where breath-first-search based method takes 1,781 seconds (7.4 times faster). Moreover, for social network analysis, the suggested method is 6.8 times and 1.8 times faster than betweenness centrality analysis and closeness centrality analysis, respectively. The proposed method in this paper shows the possibility to analyze a large size of social network with the better performance in time. As a result, our method would improve the efficiency of social network analysis, making it particularly useful in studying social trends or phenomena.

• The Journal of Small Business Innovation
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• v.19 no.4
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• pp.1-17
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• 2016

The purpose of this study is to suggest an efficient way for ventures to achieve innovation performance through R&D cooperative arrangements. Achieving innovation is one of the critical factors for the survival of ventures. Unlike established firms, ventures often do not have the specialized assets necessary to take technological developments to the product and market stages. Young and resource-constrained firms can achieve innovation by finding and accessing to the complementary resources from R&D cooperation. In the current business environment, many firms are likely to engage in multiple simultaneous R&D cooperations with different partners. Recent research stream addresses the importance of efficient cooperation management from the holistic portfolio perspective. Since maintaining the multiple cooperative relations require substantial amount of time and effort, managing cooperative relationships play a more important role to resource-constrained firms. In order to find an efficient composition of R&D cooperative partners, we mainly focus on the diversity of partner type and dependence level in partnership. We analyze the data on Korean manufacturing ventures collected in the Korean Innovation Survey (KIS) which was conducted by the Science and Technology Policy Institute (STEPI). The KIS questionnaire assesses the existence of cooperative relationships with different types of partners respectively. The types of cooperating partners are affiliated companies, suppliers, clients & customers, competitors or other firms in the same industry, consulting firms, universities, and research institutes. We confirm that ventures obtain relatively higher benefits from R&D cooperation compared with established firms in terms of innovation performance. The results show that a moderate level of diversity in cooperative partner type composition increases innovation. Moreover, diversity of cooperation dependency among the partners enhances innovation performance. Likewise, concentrating on the quality aspects of cooperative composition, such as diversity of partners and degree of dependencies, this study offers some implications for ventures in managing partners from an integrative perspective.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.