• Geophysics and Geophysical Exploration
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• v.7 no.1
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• pp.45-50
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• 2004

This paper describes a method of detecting formation boundaries, and permeable fractures, from frequency-domain Stoneley wave logs. Field data sets were collected between the depths of 330 and 360 m in well EE-4 in the Higashi-Hachimantai geothermal field, using a monopole acoustic logging tool with a source central frequency of 15 kHz. Stoneley wave amplitude spectra were calculated by performing a fast Fourier transform on the waveforms, and the spectra were then collected into a frequency-depth distribution of Stoneley wave amplitudes. The frequency-domain Stoneley wave log shows four main characteristic peaks at frequencies 6.5, 8.8, 12, and 13.3 kHz. The magnitudes of the Stoneley wave at these four frequencies are affected by formation properties. The Stoneley wave at higher frequencies (12 and 13.3 kHz) has higher amplitudes in hard formations than in soft formations, while the wave at lower frequencies (6.5 and 8.8 kHz) has higher amplitudes in soft formations than in hard formations. The correlation of the frequency-domain Stoneley wave log with the logs of lithology, degree of welding, and P-wave velocity is excellent, with all of them showing similar discontinuities at the depths of formation boundaries. It is obvious from these facts that the frequency-domain Stoneley wave log provides useful clues for detecting formation boundaries. The frequency-domain Stoneley wave logs are also applicable to the detection of a single permeable fracture. The procedure uses the Stoneley wave spectral amplitude logs at the four frequencies, and weighting functions. The optimally weighted sum of the four Stoneley wave spectral amplitudes becomes almost constant at all depths, except at the depth of a permeable fracture. The assumptions that underlie this procedure are that the energy of the Stoneley wave is conserved in continuous media, but that attenuation of the Stoneley wave may occur at a permeable fracture. This attenuation may take place at anyone of the four characteristic Stoneley wave frequencies. We think our multispectral approach is the only reliable method for the detection of permeable fractures.

• Geophysics and Geophysical Exploration
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• v.9 no.3
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• pp.231-240
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• 2006

A variety of geophysical well loggings have been conducted to investigate the geological characteristics for basaltic volcanic area in Jeju Island. Specially, there is no precedent case study using geophysical well loggings in Jeju Island. And so, the proper understandings for geological features of Jeju Island are the key to interpret geophysical well logs. Presently, seawater intrusion monitoring systems have been constructed for systematic development and conservation of groundwater resources. As the results of geophysical well loggings in this seawater intrusion monitoring boreholes, the responses of well logs for saturated zone have distinctly identified basalt sequences. In particular, neutron logging, gamma-gamma (density) logging, and resistivity logging have well exhibited the characteristics of lava flows and lithologic boundaries. In hyalocastite, porosity is high, and resistivity is low. Eventually, geophysical well logs are useful for securing sustainable development of groundwater in Jeju Island in that it has identified the characteristics of geological responses.

• Geophysics and Geophysical Exploration
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• v.3 no.3
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• pp.101-111
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• 2000

In order to assess the seawater intrusion, induction, temperature and conductivity of fluid, and natural gamma logs were obtained in nine wells at the three study areas having different hydrogeologic characteristics. Besides surface geophysical exploration, supplementary geophysical well logs were carried out to understand the hydrogeological characteristics related to the seawater intrusion in the study areas. The geophysical well logs have been proved to increase the accuracy of interpretation of the surface geophyscial exploration's data for assessment of seawater intrusion, and to get the optimum depth for a long monitoring of groundwater. They, also, revealed that the identification of hydrogeological units for strata's porosity was able to be achieved and were illustrated the applicability of geophysical well logs monitoring. Finally, geophysical well logs are expected to play to get the more quantitative information of seawater infusion, if it is fully collaborated with a better method that is strata's resistivity determination with not relatively much effected by seawater within the drilled borehole and that is the porosity measurement with built on small diameter PVC casing.

• Journal of Sericultural and Entomological Science
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• v.44 no.2
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• pp.74-81
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• 2002

The optimal conditions for mycelial growth of P. linteus ASI 26011 were 25-30$^{\circ}C$ and pH 6.0, respectively. The mycelial growth of P. linteus was excellent on MCM medium. In case of carbon sources, the mycelial growth of P. linteus was best on the culture media that were contained with sucrose, mannose and glucose. Potassium nitrate and sodium nitrate were good for the mycelial growth of P. linteus as a nitrogen source. For comparison of the mycelial colonization of P. linteus on logs, several techniques of inoculation were tested; the sterilized short log inoculation, drilling inoculation and log-end sandwich inoculation. The mycelial colonization of P. linteus on logs was good in the treatment of sterilized short log inoculation, but poor in the traditional methods such as drilling inoculation and log-end sandwich. The initial mycelial growth and the full mycelial colonization of P. linteus were the best on 20 cm logs under the condition of 42% of moisture content in log. Also the initial mycelial growth of P. linteus was accelerated over 12 hours of sterilization. Burying method of logs after 5-6 months of incubation was the best for formation of basidiocarp of P. linteus. The formation of fruiting body of P. linteus was quite good in the cultivation house at the 31-35$^{\circ}C$ and over 96% of relative humidity.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.77-84
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• 2019

Workflow management system is a system that manages the workflow model which defines the process of work in reality. We can define the workflow process by sequencing jobs which is performed by the performers. Using the workflow management system, we can also analyze the flow of the process and revise it more efficiently. Many researches are focused on how to make the workflow process model more efficiently and manage it more easily. Recently, many researches use the workflow log files which are the execution history of the workflow process model performed by the workflow management system. Ourresearch group has many interests in making useful knowledge from the workflow event logs. In this paper we use XES log files because there are many data using this format. This papersuggests what are the cardinalities of the temporal workcases and how to get them from the workflow event logs. Cardinalities of the temporal workcases are the occurrence pattern of critical elements in the workflow process. We discover instance cardinalities, activity cardinalities and organizational resource cardinalities from several XES-based workflow event logs and visualize them. The instance cardinality defines the occurrence of the workflow process instances, the activity cardinality defines the occurrence of the activities and the organizational cardinality defines the occurrence of the organizational resources. From them, we expect to get many useful knowledge such as a patterns of the control flow of the process, frequently executed events, frequently working performer and etc. In further, we even expect to predict the original process model by only using the workflow event logs.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.665-673
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• 2011

In order to estimate the hydrocarbon reserves, the porosity of the reservoir must be determined. The porosity of the area without a well is generally calculated by extrapolating the porosity logs measured at wells. However, if not only well logs but also seismic data exist on the same site, the more accurate pseudo porosity log can be obtained through artificial neural network technique by extracting the relations between the seismic data and well logs at the site. In this study, we have developed a module which creates pseudo porosity logs by using the polynomial neural network method. In order to obtain more accurate pseudo porosity logs, we selected the seismic attributes which have high correlation values in the correlation analysis between the seismic attributes and the porosity logs. Through the training procedure between selected seismic attributes and well logs, our module produces the correlation weights which can be used to generate the pseudo porosity log in the well free area. To verify the reliability and the applicability of the developed module, we have applied the module to the field data acquired from F3 Block in the North Sea and compared the results to those from the probabilistic neural network method in a commercial program. We could confirm the reliability of our module because both results showed similar trend. Moreover, since the pseudo porosity logs from polynomial neural network method are closer to the true porosity logs at the wells than those from probabilistic method, we concluded that the polynomial neural network method is effective for the data sets with insufficient wells such as F3 Block in the North Sea.

• Mycobiology
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• v.36 no.2
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• pp.81-87
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• 2008

The optimal conditions for mycelial growth of Phellinus linteus ATCC 26710 were determined to be a log length of 20 cm, temperature of $30^{\circ}C$ and pH of 6.0. Mycelial growth was excellent on the mushroom complete medium, and was optimal when sucrose, man nose and glucose were supplied as carbon sources. Potassium nitrate and sodium nitrate as nitrogen sources supported good mycelial growth. To evaluate P. linteus mycelial colonization on logs, sterilized short log inoculation, drilling inoculation and log-end sandwich inoculation techniques were used. Only sterilized short log inoculation produced good mycelial colonization. Initial mycelial growth and full mycelial colonization were best on 20 cm logs having 42% moisture content. The initial mycelial growth of P. linteus was accelerated over 12hr of sterilization. Basidiocarp formation was optimal using a burying method of logs after $5{\sim}6$ months, and fruiting body formation was superior in cultivation house conditions of $31{\sim}35^{\circ}C$ and in excess of 96% relative humidity.

• Economic and Environmental Geology
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• v.27 no.3
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• pp.289-294
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• 1994

This paper describes an effective utilization method of well logging data and boring cores for understanding the geology of Keoje-do area. Six holes were drilled in 1988-1989, and all rock cores were recovered. Nevertheless, seven kinds of logs were carried out in each borehole. The geologic situations of the drilling sites are accurately evaluated from a comparison between core descriptions and well logging data. Porosities and clay contents of sedimentary rocks can be calculated using the data of density and gamma-ray logs. Fractured zones are easily detected from the change in inside diameter of borehole by caliper log. Sonic, density and gamma-ray logging data clearly indicate alternated and dyke zones; the former can be detceted from an acoustic wave attenuation and a decline of compaction by sonic and density logs, the latter can be detected from the amount of potassium contents of bed rock and dyke by gamma-ray log.

• Journal of Korea Multimedia Society
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• v.23 no.1
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• pp.24-30
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• 2020

As the number of internet-connected appliances and the variety of IoT services are rapidly increasing, it is hard to protect IT assets with traditional network security techniques. Most traditional network log analysis systems use rule based mechanisms to reduce the raw logs. But using predefined rules can't detect new attack patterns. So, there is a need for a mechanism to reduce congested raw logs and detect new attack patterns. This paper suggests enterprise security management for IoT services using graph and network measures. We model an event network based on a graph of interconnected logs between network devices and IoT gateways. And we suggest a network clustering algorithm that estimates the attack probability of log clusters and detects new attack patterns.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.460-469
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• 2008

Process mining aims at mining valuable information from process execution results (called "event logs"). Even though process mining techniques have proven to be a valuable tool, the mining results from real process logs are usually too complex to interpret. The main cause that leads to complex models is the diversity of process logs. To address this issue, this paper proposes a trace clustering approach that splits a process log into homogeneous subsets and applies existing process mining techniques to each subset. Based on log profiles from a process log, the approach uses existing clustering techniques to derive clusters. Our approach are implemented in ProM framework. To illustrate this, a real-life case study is also presented.