• Journal of Information Processing Systems
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• v.15 no.4
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• pp.833-852
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• 2019

In real time applications, due to their effective cost and small size, wireless networks play an important role in receiving particular data and transmitting it to a base station for analysis, a process that can be easily deployed. Due to various internal and external factors, networks can change dynamically, which impacts the localisation of nodes, delays, routing mechanisms, geographical coverage, cross-layer design, the quality of links, fault detection, and quality of service, among others. Conventional methods were programmed, for static networks which made it difficult for networks to respond dynamically. Here, machine learning strategies can be applied for dynamic networks effecting self-learning and developing tools to react quickly and efficiently, with less human intervention and reprogramming. In this paper, we present a wireless networks survey based on different machine learning algorithms and network lifetime parameters, and include the advantages and drawbacks of such a system. Furthermore, we present learning algorithms and techniques for congestion, synchronisation, energy harvesting, and for scheduling mobile sinks. Finally, we present a statistical evaluation of the survey, the motive for choosing specific techniques to deal with wireless network problems, and a brief discussion on the challenges inherent in this area of research.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1025-1037
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• 2015

Flexible base isolation bearings that separate superstructure from ground have been widely used in the construction field because they make a significant contribution to increasing the fundamental period of the structure, thereby decreasing response acceleration transmitted into the superstructure. However, the established bearing devices installed to uphold the whole building give rise to some problems involved with failure and collapse due to lack of the capacity as modern structures are getting more massive and higher. Therefore, this study suggests new isolation bearings assembled with additional restrainers enabled to reinforcing and recentering, and then evaluates their performance to withstand the seismic load. The superelastic shape memory alloy (SMA) bars are installed into the conventional lead-rubber bearing (LRB) devices in order to provide recentering forces. These new systems are modeled as component spring models for the purpose of conducting nonlinear dynamic analyses with near fault ground motion data. The LRB devices with steel bars are also designed and analyzed to compare their responses with those of new systems. After numerical analyses, ultimate strength, maximum displacement, permanent deformation, and recentering ratio are compared to each model with an aim to investigate which base isolation models are superior. It can be shown that LRB models with superelastic SMA bars are superior to other models compared to each other in terms of seismic resistance and recentering effect.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.75-79
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• 2010

Wireless sensor networks (WSN) are widely used in many applications. WSN acquires the data of surrounding environments with sensors attached to each node. It is important to design sensor networks that can communicate energy-efficiently as well as to get sensor readings with high accuracy. In this paper, we propose a novel routing scheme that assures high accuracy and significantly reduces data transmission costs in WSN with faults. First, we organize a number of network topologies randomly for routing sensor readings to the base station. Because every sensor node is connected each other with a single path, redundant transmissions are not incurred. It can reduce unnecessary transmissions and guarantee final sensor readings with high accuracy. To show the superiority of our scheme, we compare it with an existing multi-path routing scheme. In the result, our scheme has similar accuracy as the existing scheme and reduces unnecessary data transmissions by about 70% over the existing technique.

• Journal of Korean Tunnelling and Underground Space Association
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• v.10 no.4
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• pp.405-420
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• 2008

Resistivity survey is one of the widely used methods for the investigation of stability of the ground or bedrock around tunnel and is also used as an essential base data for stability and reduction of construction cost through first-hand approximation of rock quality at design step. Generally, the analysis of resistivity survey data is performed by single measurement. When distribution variation of groundwater around a tunnel over time is necessary for maintenance of a tunnel, resistivity monitoring is very useful survey method to grasp distribution variation of groundwater. So we performed the grid line resistivity survey to monitoring resistivity variation for six times. And we also tried to evaluate application possibility of the resistivity monitoring for construction safety through providing detailed information on fault zones.

• Convergence Security Journal
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• v.7 no.3
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• pp.51-60
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• 2007

Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, exponential distribution and Rayleigh distribution model was reviewed, proposes the mixture reliability model, which made out efficiency substituted for situation for failure time Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using S27 data set for the sake of proposing shape parameter of the mixture distribution was employed. This analysis of failure data compared with the mixture distribution model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Economic and Environmental Geology
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• v.32 no.2
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• pp.129-139
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• 1999

Hydrothermal gold deposits of the Trabong district in Vietnam occur as single-stage quartz $\pm$ calcite veins (0.3-1.2 m thick) which fill fault fractures in graphite-bearing gneiss and schist of the Chulai Complex and Kham Duc Formation of the Proterozoic age. Ore grades are 1.3 to 92.4 g/ton Au. Ore mineralogy is very simple, consisting mainly of pyrite with minor amounts of base-metal sulfides and electrum. Gold grains occur in two assemblages as follows: (1) early, Fe-rich (7.2-10.4 mole % FeS) sphalerite + electrum (50.4-64.3 atom % Au) assemblage occurring as inclusions in pyrite; (2) late, Fe-poor «4.7 mole % FeS) sphalerite + galena + electrum (47.6-81.7 atom % Au) assemblage occurring along fractures of pyrites. Based on fluid inclusion data and thermochemical considerations of ore mineral assemblages, ore minerals were formed at high temperatures (about $230^{\circ}C$ to $420^{\circ}C$) from $H_{2}O-CO_{2}(-CH_{4})$-NaCI fluids with the sulfur fugacity of about $10^{-6}$ to $10^{-10}$ atm. Fluid inclusion data also indicate that ore mineralization occurred mainly as a result of fluid unmixing accompanying $CO_2$ effervescence. Calculated oxygen and measured hydrogen isotope compositions of mineralizing waters (${\delta}^{18}O_{V-SMOW}$ values = 5.3 to 8.6$\textperthousand$, ${\delta}D_{V-SMOW}$ values = - 60 to - 52$\textperthousand$), along with the sulfur isotope compositions of vein sulfides (${\delta}^{34}S_{CDR}$ values = - 1.2 to 2.8$\textperthousand$) and carbon isotope compositions of inclusion $CO_2$ (${\delta}^{13}C_{PDB}$ values = - 4.7 to - 2.0$\textperthousand$) indicate that the high temperature (mesohypothermal) gold mineralization formed from a magmatic fluid.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8A
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• pp.1096-1103
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• 2000

The default server strategy is commonly used for location and state managements of mobile host in mobile computing. With this strategy, we can find the cell of destination mobile host to send data by querying the default server. In SDN(single Default Notification) strategy which is a kind of default server strategy, the call is established after the location and state of the callee is acquired to the query server by querying the default server. But the communication cost overhead from the default server is increased if there are large number of cells and query requests, and if it is too far from the default server to a base station. Still more it will be unable to establish any calls to a mobile host when there is a fault in the default server of this host. In this paper, we suggest add evaluate a default server replication strategy to reduce the communication cost overhead and to make the service available.

• Journal of the Korean Society of Costume
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• v.50 no.2
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• pp.97-109
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• 2000

The purpose of this study is to apply 3D computer graphics in fashion design as a creative medium and it attempts to fine out what advantages 3D technique can offer to fashion design. For this purpose, this study, first, tries to develop a 3D digital model in which designer can select design, color , pattern and fabric palette whatever necessary . This study uses of the software named 'Poser of Fractal Design' and the and the 3D digital model comprises four stages ; body modeling, item design (item coordination), color design (color coordination), pattern and fabric design (pattern and fabric coordination). Secondly, this study seeks to accumulate a data base which was produced in the course of case studies, which have applied 3D digital model to design. The outcome of the case studies shows that 3D digital model can enhance designing in the following four aspects. ⅰ) It can give more freedom to designer to try various ideas, revise and modify them, It can also produce random generation. Through this process, the designer test various input and output without damage on fabric after revision and alteration. ⅱ) It can help designers to enhance their accuracy. Since fault in the design developed by the 3D digital model can be detected in advance, designers can make correlation before actual work begins. In the end, designers can express their ideas and intention accurately as well as freely. ⅲ) Since design developed by the 3D digital model can be shared on screen by various actors in the course of priduction such designers , merchandisers, and supervisors, it can help communication between and cut the time of feedback.ⅳ) By using the 3D digital model, designers can work from the begining with awareness of actual outcome their design, since the 3D digital model provide animation, which helps designers to envisage visual changes as they apply various items, colors, pattern and fabrics.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.6 s.360
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• pp.31-39
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• 2007

In this paper, a system for real-time or periodic measurement and analysis of RF parameters such as forward transmit power and pilot power in CDMA base station systems is proposed. Such RF characteristic parameter measurement can be prevented from system fault and used to achieve optimal service quality and maximum investment return through cell coverage expansion, subscriber capacity increase and so on. For forward power measurement, the local oscillator frequency for the detector is varied so that the transmit power for all channels can be measured. The channel power measurement can be used to analyze the variation in transmit power for changes in voice traffic. By comparing to forward $E_c/I_o$, the pilot channel power can be deducted, which can be used to determine uy degradation in transmit section modules such as the high dover amplifier. Since an accurate analysis of carefully measured data using the CDMA level detector must be made, the system is designed so that measurement errors due to changes in crest factor with modulation method can be overcome.