Application of Very Low Frequency (VLF) Method for Estimating Karst Underground River in Tanjungsari District

Drought is the main problem for clean water needs in Tanjungsari district. This research aims to provide information on the existence of underground river for deep well drilling. The methods used are geologic-structural analysis and application of Very Low Frequency (VLF) methods. Strike and dip measurements of 150 joints were conducted in the research area. Analysis using rosette diagram shows that the main geologic-structure orientation has a direction of Northwest - Southeast and Northeast – Southwest. Very Low Frequency (VLF) acquisition was measured across the possible occurrence of subsurface water flow directions predicted from geologic-structural analysis. The length of the VLF acquisition line is 2500 meters with 30 m spacing and 108 points acquisitions. The direction of VLF line is N 2700 E. The result shows that there are 2 locations that have high conductivity values, appearing at 1800 meters and 2200 meters. The results of this structural and VLF analyses indicate the existence of underground river at the location of 454326 N, 9105870 E.

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Identification of Manganese Distribution Using Very Low Frequency (VLF) Method at Karangsari Village, Pengasih Sub-District, Kulonprogo Regency, DIY

Proceeding International Conference on Science and Engineering ◽

10.14421/icse.v1.286 ◽

2017 ◽

Vol 1 ◽

pp. 147-152

Author(s):

Wulan Listyorini ◽

Thaqibul Fikri Niyartama ◽

Muhammad Faizal Zakaria

Keyword(s):

Low Frequency ◽

Line Length ◽

Research Area ◽

Contour Map ◽

Very Low Frequency ◽

Data Processing Software ◽

Tilt Mode ◽

Relative Conductivity ◽

The Village ◽

Space Distance

Research of manganese distribution was conducted in the village of Karangsari, Pengasih sub-district, Kulonprogo Regency, DIY which is the former area exploration and exploitation of manganese. The purpose of the research is known the value of relative conductivity and the distribution of manganese. The method used very low frequency tilt mode. The tools used 2 set of T-VLF BRGM (sensor and monitor) and the data processing software are Ms. Excel and KHFILT. T-VLF operated with 2 frequencies that are 19800 Hz from Australia and 22.200 Hz from Elbino Japan. The total lines are 6 lines with 75 m space. Distance between measured points is 15 m, whereas line length is 300 m. The parameters measured from VLF method are tilt (%) and ellipticity (%). The raw data VLF is processed by Ms Excel to obtain a tilt, ellipse, fraser graph vs distance and the RAE from Karous Hjelt filter. While the results of processed by KHFILT software is the equivalent current density contour map. Relative conductivity of area research are line 1 (-10 to 10) mho/m, line 2 (-40 to 30) mho/m, line 3 (-20 to 20) mho/m, line 4 (-30 to 10) mho/m, line 5 (-40 to 30) mho/m and line 6 (-30 to 40) mho/m. The spread of manganese were in the high conductivity, toward west and east of research area with depth up to 45 m.

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The Attenuation of Very Low Frequency Brain Oscillations in Transitions from a Rest State to Active Attention

Journal of Psychophysiology ◽

10.1027/0269-8803.23.4.191 ◽

2009 ◽

Vol 23 (4) ◽

pp. 191-198 ◽

Cited By ~ 26

Author(s):

Suzannah K. Helps ◽

Samantha J. Broyd ◽

Christopher J. James ◽

Anke Karl ◽

Edmund J. S. Sonuga-Barke

Keyword(s):

Brain Activity ◽

Sampling Rate ◽

Low Frequency ◽

Future Research ◽

Adhd Symptoms ◽

Default Mode ◽

Very Low Frequency ◽

Wide Range ◽

Interference Hypothesis ◽

Mode Interference

Background: The default mode interference hypothesis ( Sonuga-Barke & Castellanos, 2007 ) predicts (1) the attenuation of very low frequency oscillations (VLFO; e.g., .05 Hz) in brain activity within the default mode network during the transition from rest to task, and (2) that failures to attenuate in this way will lead to an increased likelihood of periodic attention lapses that are synchronized to the VLFO pattern. Here, we tested these predictions using DC-EEG recordings within and outside of a previously identified network of electrode locations hypothesized to reflect DMN activity (i.e., S3 network; Helps et al., 2008 ). Method: 24 young adults (mean age 22.3 years; 8 male), sampled to include a wide range of ADHD symptoms, took part in a study of rest to task transitions. Two conditions were compared: 5 min of rest (eyes open) and a 10-min simple 2-choice RT task with a relatively high sampling rate (ISI 1 s). DC-EEG was recorded during both conditions, and the low-frequency spectrum was decomposed and measures of the power within specific bands extracted. Results: Shift from rest to task led to an attenuation of VLFO activity within the S3 network which was inversely associated with ADHD symptoms. RT during task also showed a VLFO signature. During task there was a small but significant degree of synchronization between EEG and RT in the VLFO band. Attenuators showed a lower degree of synchrony than nonattenuators. Discussion: The results provide some initial EEG-based support for the default mode interference hypothesis and suggest that failure to attenuate VLFO in the S3 network is associated with higher synchrony between low-frequency brain activity and RT fluctuations during a simple RT task. Although significant, the effects were small and future research should employ tasks with a higher sampling rate to increase the possibility of extracting robust and stable signals.

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