Global Navigation Satellite System (GNSS) is a navigation system that uses satellite signals to determine its position, which consists of several satellites arranged in a constellation system. GNSS transmits signals t...
Global Navigation Satellite System (GNSS) is a navigation system that uses satellite signals to determine its position, which consists of several satellites arranged in a constellation system. GNSS transmits signals to receivers on Earth. The GNSS receiver determines the user's position, speed, and time by processing the signals transmitted by the satellites. The initial purpose of launching the GNSS was for navigation purposes, but along with its development, GNSS can be used for the purposes of observing deformation of the earth's crust and in studying the atmosphere. The delayed wave data when passing through the ionosphere can be used to obtain Total Electron Content (TEC) values which then used to study ionospheric disturbances. Ionospheric disturbances are caused by various phenomena, the most common one is the ionospheric disturbances caused by the induction of acoustic and gravitational waves excited by co seismic crustal motions from large earthquakes. Ionospheric disturbances that happened before an earthquake are called Pre-seismic Ionospheric Disturbances and those that occur after an earthquake are called Co-seismic Ionospheric Disturbances (CID). Most studies of ionospheric disturbances still provide information on the timing and value of TEC anomalies in 2D form. Therefore, in this study, a 3D ionosphere profile modelling using computed 3D tomography will be carried out. The 3D information provided is in the form of time, ionosphere altitude and TEC anomaly value by utilizing GNSS data. The TEC anomaly value is obtained from the calculation of linear combination of the ionosphere. This study aims to obtain a spatial and temporal analysis of the CID caused by the West Sumatra Earthquake on March 2, 2016.
This research aims to recognize the pattern of pulmonary disease on x-ray radiography image using artificial neural network (ANN) method. The images, which were used such as images of healthy pulmonary, pulmonary tube...
This research aims to recognize the pattern of pulmonary disease on x-ray radiography image using artificial neural network (ANN) method. The images, which were used such as images of healthy pulmonary, pulmonary tuberculosis, and pulmonary tumour. Pattern recognition was using an extraction feature of GLCM (Gray Level Co-occurrence Matrix) and back propagation method. Before being identified, the images were processed by median filter and adaptive histogram equalization. The GLCM features that used were homogeneity, energy, contrast, variance and correlation. The parameters were learning rate and hidden layer. Learning rate was 0.3 and hidden layer was 25. Back propagation training showed 100% accuracy, which all of 44 images were used had been successfully identified. From the result, the healthy pulmonary showed 60% accuracy, 83.3% for pulmonary tuberculosis and 100% for pulmonary tumor. Hence, the overall result showed 81.25% accuracy, which 13 of 16 images had been successfully identified. From these result, extraction feature of GLCM using back propagation method was capable to recognize the pattern of pulmonary disease. However, due to narrow range of the feature, this application may not be used optimally for comparing features in every category of images. Therefore, the further research is needed to determine the best features and parameters of training back propagation.
Indonesia has a very abundant cassava that can be used instead of wheat. Bread made from cassava is safe for celiac sufferers, in which cannot tolerate a protein called gluten found in wheat flour. However, bread from...
详细信息
The aim of Nickel-Tungsten coatings on the material of carbon steel is to improve the wear resistance of the material. However, with the elevated contact temperature due to friction force in the surface area of slidin...
The aim of Nickel-Tungsten coatings on the material of carbon steel is to improve the wear resistance of the material. However, with the elevated contact temperature due to friction force in the surface area of sliding may alter the wear resistance of Nickel-Tungsten layers. If the elevated temperature is quite high to reduce the hardness performance of Nickel-Tungsten layers, the layers may be degraded more quickly. In this work, Nickel-Tungsten was deposited on the surface of medium carbon steel in the process of flame powder spray coating with layer thickness of about 0.2 mm. The wear test was conducted using linear reciprocating ball-on-plat with varying surface temperature of about 30°C up to about 250°C. The wear rate and wear mechanism of Nickel-Tungsten layer is investigated.
Wastewater treatment using plants is being applied by researchers to its capability in metal removal. Technologies are using plants for treatment as a green technology. Phytotreatment is a technology using plants that...
Wastewater treatment using plants is being applied by researchers to its capability in metal removal. Technologies are using plants for treatment as a green technology. Phytotreatment is a technology using plants that can reduce organic and inorganic pollutants in the environment. Kenaf (Hibiscus cannabinus L.) is terrestrial plants that can be used in the phytotreatment process because they can reduce pollutants. The aim of this study was to remove chromium from batik wastewater. This experiment used bacth system in bed evapotranspiration. Variables used were kenaf plant varieties (KR 11 and KR 15), kenaf plant age (30 days and 45 days), and batik wastewater concentration. This research was conducted for 28 days. The specific response of kenaf plants is indicated by the growth of kenaf, the increase in plant height and the number of leaves in the batik wastewater treatment. The most removal of chromium was found 66,49 %. The results showed that Kenaf can be used for phytotreatment agent to removal of chromium.
A pilot Carbon Capture and Storage (CCS) project in Indonesia is planned to be implemented in Gundih area, Central Java Province in Indonesia. Prior to conducting CO2 injection, reservoir characterisations have to stu...
A pilot Carbon Capture and Storage (CCS) project in Indonesia is planned to be implemented in Gundih area, Central Java Province in Indonesia. Prior to conducting CO2 injection, reservoir characterisations have to study thoroughly to assure that the reservoir is to meet with CCS standard requirements. The Jepon well in the Gundih fied was proposed as a suitable site for CO2 injection. The decision was made to proceed with a comprehensive site assessment and geological modelling of the Jepon area. This site was selected based on the reason the presence of a potentially suitable reservoir (Ngrayong Sandstone) and primary and secondary seals (Bulu Limestone and Wonocolo claystone). Using logging data, petrophysics and rock physics model are used to evaluate potential of the CO2 injection site. Permeability results from petrophysics calculations and recent injection tests show very small; whilst porosity is relatively high. This can be caused by fractures mostly are not connected. Hence, rock physics for the reservoir is evaluated and modelled as anisotropy or Vertical Tranverse Isotropy (VTI) in which fractures with preferred orientation. Stiffness calculations for VTI medium with different aspect ratio shows consistent with low permeability result.
This study examined the effects of powder types on capillary pumping performance and wettability of wick samples. The raw material used are molecular sieve and copper powder with grain size of 80-100 microns and 177-2...
This study examined the effects of powder types on capillary pumping performance and wettability of wick samples. The raw material used are molecular sieve and copper powder with grain size of 80-100 microns and 177-200 microns respectively. Wick samples were produced by sintering with two shapes of powder grain comprised spherical and irregular shapes. Tests were carried out to determine the microstructure of the sample, capillary pumping amount and wettability. The test results showed that the grain type and grain size of powder could affect the roughness of the samples, of which, consequently, could also influence their wettability and capillary pumping amount. Proposed grain size and shape of the molecular sieve and copper powder are potential to be considered as wick alternatives for heat pipe application.
Coconut leaf is one of the most potential biomass to be converted into bio-oil through pyrolysis process and the availability in Indonesia is abundance. The mechanism of decomposition of coconut leaf into bio-oil prod...
Coconut leaf is one of the most potential biomass to be converted into bio-oil through pyrolysis process and the availability in Indonesia is abundance. The mechanism of decomposition of coconut leaf into bio-oil productions requires further research because of the complexity of pyrolysis and differences in biomass composition. Therefore, the design, optimization and modeling of pyrolysis processes is strongly influenced by biomass characteristics. The purpose of this study was to find the characteristic differences in pyrolysis behavior of the three main parts of coconut leaf based on its constituent parts; leaflets, midrib and whole leaf. Moisture is removed by drying the sample in an electric oven at 110°C for 24 hours. Characteristics were tested using Cellulose Analysis, Ultimate Analysis, and Heat Value, whereas pyrolysis behavior used Thermogravimetric Analyzer (TGA). The results show that leaflets, midrib and whole leaf exhibit different pyrolysis behavior. In terms of considering flow process of separation, the whole leaf becomes an option as a fuel for further pyrolysis processes. The maximum temperature that as a reference in the pyrolysis process of coconut leaves is 500°C with temperature rate of 20°C/min and the process lasts as long for 130 minutes.
Sigi Biromaru is an area prone to landslides. This study aims to apply the statistical method of Weight of Evidence (WoE) in landslide susceptibility mapping using Geographic Information Systems (GIS). The 265 landsli...
Sigi Biromaru is an area prone to landslides. This study aims to apply the statistical method of Weight of Evidence (WoE) in landslide susceptibility mapping using Geographic Information Systems (GIS). The 265 landslides that occurred 2009-2019 were randomly divided into two groups, 70% of the data were used as training dataset for susceptibility modelling and 30% of the data were used as test data for validation of the susceptibility model. Twenty-one parameters were tested for their influence on landslides. Based on the Area Under Curve (AUC), parameters that significant controlling the landslides are slope gradient, elevation, aspect, flow direction, peak ground acceleration, clay content (<0,002 mm), land cover, terrain ruggedness index (TRI), river density, soil type, lineament density, lithology, rainfall and stream power index (SPI) respectively. The validation results show that the AUC success rate is 0,811 using the training dataset and AUC prediction rate is 0,756 using the test dataset. These results indicate that the WoE method produces a good landslide susceptibility map in the Sigi Biromaru area.
暂无评论