International Journal on Advanced Science, Engineering and Information Technology
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2006 research outputs found
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Potential Use of Cross-flow Microfiltration System in Separation of Functional Compound from Fermented Beetroot (Beta vulgaris L.) as Natural Oxidation Prevention
Get PDFThis study was conducted to determine the potential utilization of microfiltration (MF) membrane in separating functional compounds from beetroot (Beta vulgaris L.) biomass as a functional drink for natural oxidation prevention. Separation was performed through MF membrane (pore size of 0.15 µm) at room temperature, flow rate ~7.5 L/min, and TMP 2 and 6 bar for 0, 5, 15, 25, and 35 minutes. The results showed that process optimization based on gallic acid as total polyphenols and acetic acid were achieved at TMP 2 and 6 bar for 35 minutes, respectively. At TMP 2 and 6 bar produced retentate with acetic acids 1.24 and 0.95%, gallic acid 0.42 and 0.41%, total solids 3.49 and 3.47%, total sugars 36.64 and 44.66 mg/mL, pH 3.11 and 3.10, and inhibiting ability of 62.45 and 58.48%, respectively, meanwhile permeate had acetic acid 0.73 and 0.82%, gallic acid 0.31 and 0.33%, total solids 3.39 and 3.38%, total sugars 40.95 and 61.56 mg/mL, pH 3.12 and 3.13, inhibiting ability of 47.62 and 52.43%, respectively. In these conditions, CF-MF is technically able to retain acetic acid (2.63-folds) and gallic acid (1.21-folds) in the retentate and increase inhibition by 25.12 and 11.25% in comparison with the initial process (0 minutes). The LC-MS analysis of permeate at TMP 2 and 6 bar for 35 minutes were predominated by monomers of acetic acid and gallic acid with MW 61.2450 Da. (M+) and 193.0327 Da. (M+Na+) and relative intensities 100 %
Hypocenter Determination and Estimation 1-D Velocity Models Using Coupled Velocity-Hypocenter Method
Get PDFHypocenter relocation is performed to obtain a high-precision hypocenter location (accurate earthquake location). An accurate earthquake location is the key problem in seismology. Further information from an accurate hypocenter location can be used for seismicity analysis, velocity structure study, and earthquake prone mapping as one of the earthquake mitigation efforts. In this research, the method used to relocate the earthquake hypocenter was the Coupled Velocity-Hypocenter. Relocations were conducted in the Central Sulawesi region; we located 40 local earthquake events with a magnitude of ≥ 3.8 ML and a depth of ≤ 25 km. The selected P-wave traveltimes were inverted from 5 seismic stations. The variance of initial velocity models used the 1-D Primary wave velocity model of North Sulawesi, Jeffrey-Bullen and Central Sulawesi. The relocation results show that most of the hypocenters are concentrated precisely in minor faults present in the research area, and the hypocenter distribution of the events indicated as destructive shallow earthquakes occurs at depths of about 5-15 km. The residual distributions resulting from the relocation using the initial velocity model of the Central Sulawesi region indicates an improved quality if compared to Jeffrey-Bullen velocity model and the North Sulawesi velocity model, with RMS error value of 0.08 seconds. This research concluded that the 1-D velocity model in the regional (Central Sulawesi Region) reference was suitable for determining the high-precision hypocenter location
Experimental Study of Masonry Wall Strengthened by Polypropylene Fiber Mortar
Get PDFBased on previous studies, the average strength of Indonesia's masonry wall shows a weak compressive strength that increases the vulnerability of buildings with masonry walls towards the seismic load. This study presents an experimental investigation of the masonry wall's flexural capacity strengthened with Polypropylene Fiber (PP Fiber). In general, the experiments were divided into two groups: the masonry wall with PP Fiber in a joint mortar and the masonry wall with PP Fiber in a plastering. The investigation was carried out on twelve specimens. The specimens consisted of three standard masonry wall (DBK) samples as the controlled specimens, which are without plastering and PP Fiber, three masonry wall samples with PP Fiber (DBP) in a joint mortar, three masonry wall samples with normal plastering (DBKP), and three masonry wall samples with PP Fiber in a joint mortar and plastering (DBPP). The experimental investigation proved that the addition of PP Fiber to the mortar mixture at joint masonry mortar could increase the masonry wall's flexural capacity. The results showed that the mortar with 8% PP Fiber improves the compressive strength by 58.46%. The flexural testing showed that 8% PP Fiber to the mortar could increase the flexural capacity to 35.8%. The maximum deflection also increases as much as 38.58% for masonry walls with PP Fiber on mortar and plastering, compared to the masonry wall without PP Fiber. In addition, the presence of Polypropylene Fiber contributes to give a higher flexural capacity
Choux Pastry Made from Egg Groups based on the Hen Age and Shelf Life of the Eggs
Get PDFThis study examines that hens' age and egg freshness affect water activity (aw) and moisture content (MC). Both also impress the quality and shelf life of choux pastry. Eggs are purchased freshly hatched and stored at ambient temperature for a few days, as is customary. This study measured egg quality before the dough-making process. Then, this study made choux dough by the same recipe and time and grouped it by the hen's age. This study also measured the choux surface temperature simultaneously after the baking process finished. Egg quality indicated albumen freshness, as described by weight loss and Haugh Unit (HU) graphs. And the grade fell over the storage time, as the falling weight loss and HU charts showed. The surface temperature indicates the MC value because temperature affects the water content in the choux. The MC graphs decreased at ten days for eggs of 5- and 16-week hens, while for 22-week hens, it did not decrease. Meantime, the relative humidity of the baker explains the aw of the choux. The aw charts decreased at 20 days for eggs of 16- and 22-week hens, while for the 5-week hens, it dropped at 30 days. Egg freshness affects MC and aw. The longer the egg storage time, the higher the MC and aw. Low MC and aw charts indicate high choux pastry quality and long choux shelf life. Young hens have a longer egg storage time
Effect of Fertilization and Agricultural Amendments on the quality of a Prairy Established on a Volcanic Soil, Andosol
Get PDFThis research was established at El Prado-IASA1 farm, Agricultural Engineering Career, on a soil of volcanic origin of the Andisol order, in order to evaluate the quality of the forage due to the effect of chemical fertilization and four amendments: lime (E1), gypsum (E2), magnesium silicate (E3) and phosphate rock (E4), mixed amendment (EM) and two level of NPK fertilization. These treatments were applied in an established meadow with: kikuyo (Pennisetum clandestinum), blue grass (Dactylis glomerata), perennial rye grass (Lolium perenne) and white clover (Trifolium repens). The amendments and fertilization were incorporated after the first cut, in an amount equivalent to 1500 of lime, 500 of gypsum, 300 of magnesium silicate and 300 of phosphate rock kg ha-1 year-1, plus fertilization F1: N100-P50-K50 and F2: N300-P100-K100, fractionated for 10 cuts per year. The variables evaluated were: green mass production, dry matter, macro and micronutrient soil content. The forage assessment was based on the physiological growth of rye grass as a dominant prairie species. The results positively affected the quality and production of forage in t ha-1, due to the effect of lime, phosphate rock, and NPK fertilization. There was a high fixation of NH4, K, and P, due to the effect of amorphous minerals, high Fe content, and water deficit. Hence it is recommended to keep close to the soil's field capacity level
Face Recognition Application Based on Convolutional Neural Network for Searching Someone’s Photo on External Storage
Get PDFDigital photos are often defined as personal archives collected long ago and are stored on a large enough storage media such as an external hard disk or flash disk. Problems arise when someone wants to find photos of themselves or others in tons of photo collections. Searching manually, such as opening a photo file or folder one by one, will certainly be very troublesome. Based on these problems, this study designed an application for searching certain photos based on the similarity of the inserted face photo. This application is built for computer or laptop devices, which was developed by using the Python programming language and Dlib module that applied the face recognition method through the combination of Convolutional Neural Network (CNN), FaceNet Embedding, and Triplet Loss for matching faces. The recognition scheme starts from face detection, face alignment, face encoding, and face classification stage. Our application is very handy to run in looking for particular face images on external storage compared to prior studies. We have done experimental research, demonstrating that the application can find almost all image files the user is looking for. In addition to the result in the form of an application, this study contributes to exploring the performance of the Dlib module, in terms of precision and recall rate, which could not recognize non-frontal face images well. We encourage other researchers to address this limitation in further studies
Automate Short Cyclic Well Job Candidacy Using Artificial Neural Networks–Enabled Lean Six Sigma Approach: A Case Study in Oil and Gas Company
Get PDFArtificial Neural Networks (ANNs) are a part of Artificial Intelligence (AI) that is commonly used for pattern recognition, regression and classification. This technology allows us to learn historical data and generate patterns from the precedent data. In oil and gas companies, large amounts of data are produced every day. Many accurate decisions in this type of company are made from the data. Cilon Indonesia (CI) Co. Ltd. is one of the oil and gas companies currently operating the largest oil field in Indonesia. This type of company's operation and financial profit depends on oil price, which is affected by global oil supply and demand. If oil prices fall suddenly, all oil and gas companies need to run their businesses more efficiently and effectively. There are many ways to make this kind of company run their business effectively and efficiently by implementing several strategies such as capital cost efficiency, operational cost efficiency and even laying off some employees. One of the major costs in operation in oil and gas companies is the cost for well workover. This well workover does not always produce oil gain. In fact, even it is resulting in oil gain, but not all well workover programs are economical whenever the oil price is low. This condition makes Petroleum Engineer (PE) need to select the best well workover for certain wells. Well candidates for workover are usually selected manually using data from many resources, reports and information. Well candidates are reviewed one by one, and with several criteria, the well is proposed to a certain type of well workover. This research explains how this company improves their selection of well candidates for the most economic workover called Short Cyclic Steam Stimulation (SCSS). The process improvement is done using the hybrid method: lean six sigma method and big data analytics method, which utilize ANNs to predict the oil after workover executed. The result demonstrates how this hybrid method can improve the process with a sustainable solution. Its successful improvement in PE time selects SCSS well candidates from 2 hours to 10 minutes to generate 20 wells per day. Its also improve the success rate of SCSS workover from 61% to 73%
Evaluation of Parameter Selection in the Bivariate Statistical-based Landslide Susceptibility Modeling (Case Study: the Citarik Sub-watershed, Indonesia)
Get PDFA landslide susceptibility mapping is essential for landslide hazard mitigation to reduce the associated risk. This paper aims to present the results of the landslide susceptibility modeling in the Citarik sub-watershed using three bivariate statistical-based methods, i.e., frequency ratio (FR), information value (IV), and weight of evidence (WoE). The main objective of this study is to evaluate the significance of the threshold of the area under curve (AUC) value in parameter selection. In this study, 118 landslide pixels were compiled from Google Earth images, unmanned aircraft vehicle (UAV) aerial photos taken just after the landslide, official landslide reports, and field observation. Thirteen landslide causative factors were prepared in Geographic Information System (GIS) environment, derived from various satellite images and maps. The landslide data were divided into two groups, 70% of data as training data and the rest as test data. Two scenarios that involve a different number of parameters were compared to explain the threshold of the AUC value in parameter selection and model accuracy. The result of this study shows that the AUC value threshold of 0.6 for parameter selection cannot be applied in all cases, and the performance of both two scenarios was excellent in assessing landslide susceptibility in this study area. Those three landslide susceptibility zonation maps of the best scenario showed that the sub-watershed's northern, northeastern, south-eastern, and southern parts were under high to very high susceptibility to landslides, including the Cimanggung area where a recent deadly double landslide occurred
Ensemble Learning Regression Method for Glucose Concentration Prediction System using Colorimetric Paper-based and Smartphones
Get PDFPrediction of glucose concentration on android smartphones and colorimetric paper-based using the Ensemble learning regression model has been successfully developed. Several successful developments in our research include automatic image segmentation, image correction using the RPCC method, and the development of a regression model for urine glucose predictions. Furthermore, the model was successfully validated for best performance in the respondent's urine susceptible to color change. We used artificial urine at a 0–2000 mg/dl concentration to create a regression model based on Ensemble learning with the boosting optimization method. In addition, we also compared the Ensemble Bagging regression model and the single learner model, Decision Tree. Server-based applications were also developed using RESTful API communication with two servers: an upload server using Node.js and a computing server using the MATLAB Production Server. The testing process results using artificial urine samples showed that the performance of R2 and RRMSE were 0.98 and 0.05 for the Decision Tree and Ensemble Bagging regression models, respectively. While for the Ensemble Boosting regression model, R2 and RRMSE at the testing process are 0.98 and 0.04. The best validation results using respondents' urine samples are shown in the Ensemble Boosting regression model with R2 and RRMSE performance values of 0.97 and 0.06, respectively. The success rate of the application was 100% on both the Samsung Galaxy A51 and Huawei Nova 5T. This research estimated the glucose concentration reasonably well for health monitoring applications
The Potentials of Isolated Hexadecanoic Acid of Hydroid Aglaophenia cupressina Lamoureoux as an Antifungal Compound on the Rotten Strawberries Fragaria x ananassa Dutch. and Mango Mangifera indica L
Get PDFOvercoming microbial contaminants in fresh fruits is not merely by recognizing the level of contamination. Still, it requires another effort, such as applying a compound of natural and effective ingredients proven effective in reducing microbial contaminants and safe for health. The hexadecanoic acid used in this study was isolated from the tropical marine hydroids Aglaophenia cupressina Lamoureux. This study aimed to analyze the ability of bioactive compounds acid from the hydroid Aglaophenia cupressina Lamoureoux to inhibit the growth of fungi that cause rotten strawberry Fragaria x ananassa Dutch and mango Mangifera indica. Hexadecanoic acid was obtained by isolating it from the hydroid Aglaophenia cupressina Lamoureoux through the maceration, fractionation, and purification stages. Isolating fungi was done by using the PDA (Potato Dextrose Agar) medium to characterize macroscopically and microscopically and to test the inhibition using the diffusion method, which was incubated for 48 hours and 72 hours at the hexadecanoic acid concentrations of 15 ppm, 30 ppm, and 45 ppm. The results showed the hexadecanoic acid concentration of 45 ppm in the 72-hour incubation could inhibit the growth of two fungal isolates on strawberries, Fragaria x ananassa Dutch, i.e., Botrytis cinerea and Rhizopus stolonifer, for successive concentration, 24.00 mm and 22.75 mm. Meanwhile, the growth of Aspergillus niger, fungi from mangoes, could be inhibited by the hexadecanoic acid by 14.75 mm, 18.25 mm, and 23.50 mm, respectively, for the concentration of 15 ppm, 30 ppm, and 45 ppm with the 72-hour incubation