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.
Upflow zone identification at volcanic fields is crucial for geothermal resource exploration. The common problem to identify the upflow zone using conventional mapping method is time-consuming and the limitation of ac...
Upflow zone identification at volcanic fields is crucial for geothermal resource exploration. The common problem to identify the upflow zone using conventional mapping method is time-consuming and the limitation of access to the area. The application of satellite imaging as ground-truthing is aimed to increase the effectiveness of upflow zone detection at geothermal fields. This study selected the volcanic field around the Bandung Basin for a model case. The data used in this study were thermal images of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Thermal Infrared Radiometer (TIR) by the night observations. The TIR data were corrected and calibrated by Visible Near Infrared Radiometer (VNIR) to measure Land Surface Temperature (LST). We then focused our analysis around a volcanic area that showed high LST at the Papandayan crater and other manifestations. Validations were carried out by measuring surface temperature and gas concentrations including SO2 and CO2. The reading value of the gases was different on each location, but the pattern of the gases was relatively similar especially the SO2 gas pattern. The SO2 gas showed a relatively constant trend of gas concentration over time in the upflow zone, but in the outflow zone showed an increase pattern with the time whose reading values were lower than those on the upflow. On the contrary, the non-geothermal features showed that the SO2 concentration decreased with the time towards almost 0. According to the retrieved LST, the surface manifestations were located not only at the high anomaly but also at medium anomaly depending on the manifestation dimension. The gas and temperature measurements proved that LST could be used to enhance the effectiveness of upflow zone identification.
Background: Carbonate apatite (CO3Ap) and silica-calcium phosphate composite (SCPC) are bone substitutes with good prospect for dental application. SCPC creates a hydroxyapatite surface layer and stimulate bone cell f...
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Cryptography is the science and art of maintaining the security of messages when messages are sent from one place to another. One of the ways securing the form of text message information is by the encryption process ...
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The needs of having strong and light material for many construction is increasing. Aluminum is one of materials that fulfill this requirement with other advantages such as corrosion resistant and easily formed. Genera...
The needs of having strong and light material for many construction is increasing. Aluminum is one of materials that fulfill this requirement with other advantages such as corrosion resistant and easily formed. Generally, hardness of aluminum and its alloys is lower than ferrous metal such as iron and steel. Aluminum hardness improvement can be conducted by heat treatment namely artificial aging. Artificial aging in aluminum alloy type 2024 T3 in this study was conducted in 2 phases that is solution treatment in 500 °C for 1 hour and continued with artificial aging process in 180 °C by holding time 2, 4 and 6 hours. From the conducted research, it was found that there was hardness improvement on aluminum type 2024 T3 in line with the increasing of aging time. The gained microstructure was getting smooth which means the precipitation hardening process was getting perfect.
The use of deep learning in medical image classification has become an important study in the past few years. The proper use of this method, however, is still hindered by many problems, one of it being the imbalance o...
The use of deep learning in medical image classification has become an important study in the past few years. The proper use of this method, however, is still hindered by many problems, one of it being the imbalance of dataset available for training which resulted in small-set database. In this study, the effect of noise-based augmentation on the performance of deep learning based classification will be studied. The noises which were used for the augmentation method were Perlin-noise and Gaussian noise. The modality of medical image used in this study is X-ray. 174 X-ray images (87 cancer, 87 normal) were used in this study and will be classified by using transfer learning from previously trained deep learning architecture. The deep learning architecture used was vgg-19. The images were divided into two groups, 138 (69 cancer, 69 normal) images were used for training phase and 36 (18 cancer, 18 normal) were images used for testing phase. Three deep learning models were used for the classification tasks, the first one was retrained to classify the original images, the second one was retrained by using mix of original images and images with Perlin-noise, and the third one was retrained by using mix of original images and images with Gaussian noise. The results showed that the three models returned similar accuracy of 0.8 which indicate that the use of noise-based augmentation can increase the performance of deep learning in classifying medical images with small set training database.
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