International Journal on Advanced Science, Engineering and Information Technology
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An Effectiveness of EEG Signal Based on Body Earthing Application
Get PDFStress is part of the social lifestyle, intellectual level, and emotional strain. Stress psychology contributions include mental, cognitive, or behavioral sensation. In summative assessments of body earthing, the grounded person is less anxious and more comfortable in everyday activity because the Earth's potential becomes an intermediary to reduce a negative electrode compliment from the body to the Earth's surface when the body is grounded condition. The balanced electrode amounts in the human body could reduce anxiety, depression, and sleep disorders. This investigation analyzes the EEG signal in the frequency domain and time-frequency domain analysis based on body earthing application in ten electrode placements with a range of EEG frequency bands; Theta, Beta, and Alpha. The Power Spectrum Density (PSD) and Short Time Fourier Transformation (STFT), and Continuous Wavelet Transformation (CWT) have been used to determine the power and energy value. The theta frequency band result shows an increasing power and energy value of EEG signal after applying the body earthing application. However, the alpha frequency band influences the left area's EEG signal efficiency while the right parts beta frequency band is affected. The best classification performance is gained from Levenberg-Marquat neural network and Scale Conjugate Gradient technique for grading into stress index classes
Bayesian Model Averaging (BMA) Based on Logistic Regression for Gene Selection and Classification of Animal Tumor Disease on Microarray Data
Get PDFTumor is one of the deadly diseases which is frequently to be found in animals. However, identifying whether an animal has a tumor still becomes a big challenge. Classification of tumor disease can be done through gene expression, which consists of hundreds of genes, but only a small number of samples is taken. This data structure is called microarray data having the characteristic of high-dimensional data. The choice of a single model can be a problem for high-dimensional data because it ignores model uncertainty. This research proposed to use Bayesian Model Averaging (BMA) to model the uncertainty model by averaging the posterior distribution of all best models, weighted by their posterior model probabilities. Selecting relevant genes to diagnose animal tumors is very important; hence, variable selection needs to be carried out. The selection of predictor variables is carried out by using the iterative BMA algorithm. The BMA results showed that from 335 gene expressions, 12 genes were selected to be relevant genes for classifying whether the animals have a tumor or normal. Moreover, from 2335 possible models formed, 12 of the best models are selected. The accuracy of BMA results is assessed using the Brier Score, resulting from a value indicating that the BMA model is good enough to classify animals, whether they have a tumor or not. This research has proven that BMA with logistic performance has very good predictability; hence, the method can be applied to classify other diseases
Analysis of Chemical and Phase Composition in Powder of U-Zr-Nb Post Hydriding-Dehydriding Process
Get PDFTo be used as a nuclear fuel, a fuel alloy must meet several requirements such as chemical, mechanical, physical, and neutronic compositions. The U-Zr-Nb powder is made from U-Zr-Nb ingots through a hydriding-dehydriding process and has a U composition that adjusts the weight of Zr, the composition of Zr remains at 6% while Nb varies by 2, 5, and 8 wt% (U- 6Zr-2Nb, U-6Zr-5Nb and U-6Zr-8Nb). The powder obtained is then subjected to elemental and phase composition testing. Chemical composition and impurity contain testing uses Atomic Absorption Spectroscopy (AAS) and Ultraviolet (UV-Vis) spectroscopy, while phase analysis uses X-Ray Diffractometer (XRD). The purpose of the analysis of chemical composition and phase is to determine the constituent and impurity elements as well as the phases formed in the U-Zr-Nb alloy. The results of the analysis of U content in the U-6Zr-2Nb, U-6Zr-5Nb, U-6Zr-8Nb alloy powder samples were 89.307, 85.568, and 83.553 wt.%, while the Zr content analysis obtained successive results amounted to 6.220, 5.829, and 6.192. Meanwhile, in the analysis of Nb in U-6Zr-2Nb alloy powder, U-6Zr-5Nb, U-6Zr-8Nb obtained successive results amounted to 2.023, 5.04, and 8.155 wt%. The phase analysis results were obtained for each sample U-6Zr-2Nb, U-6Zr-5Nb, U-6Zr-8Nb contained U, and UO2 compounds, where the U phase was the dominant phase. The highest γU phase content is found in U-6Zr-5Nb, which is 92.108 %, and after the Nb content exceeds 5 %, the greater addition of Nb does not increase the number of ï§U phases formed
Adaptive Phase Error Suppression Concerning 3D surface Deformation Measurement on Color Digital Fringe Projection Profilometry
Get PDF3D surface measurement based on phase-shifting profilometry (PSP) has been actively developed in recent years. Three color channels of RGB that are modulated to generate a one-shot PSP method is a concept of color digital fringe pattern profilometry (CDFPP). The CDFPP is a promising technique for the 3D imaging profile of dynamic surface deformation if several phase errors in the one-shot PSP method can be suppressed. This work proposes a processing scheme for phase error suppression schemes (PESS) based on retrieving the modulated sinusoidal fringe and color fringe normalization in PSP using RGB color channel. The processing of PESS consists of tunable bandpass filtering (BPF) followed by fringe normalization. The initial BPF function is defined based on a smoothing spline data set of frequency and power spectrum from the baseline color fringe image. The predefine BPF function could be tunable during the imaging process by considering each frame's condition and RGB channel spectrum mapping. The corrected fringe images are then normalized from the color imbalance, and the phase shift is calculated using the conventional three-step PSP. For evaluation, PESS is performed to reconstruct simulator membrane deformation from four different static profiles and tested to observe the 3D surface of continuous membrane deformation. The PESS could suppress the phase errors of less than 30% less absolute errors than the conventional method and successfully reconstruct the 3D surface for low-frequency continuous membrane deformation with minimizing phase errors
Flood Vulnerability Evaluation and Prediction Using Multi-temporal Data: A Case in Tangerang, Indonesia
Get PDFLand-use change has an impact on growing physical flood vulnerability. Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) approaches are increasingly being used for flood vulnerability assessments. However, none has used time-series land cover data for evaluation and rainfall over various return periods for prediction simultaneously, especially in Indonesia. Therefore, this study aims to evaluate and predict physical flood vulnerability using time-series land cover data and rainfall data over various return periods. Eight criteria were considered in the assessment: elevation, topographic wetness index, slope, distance to the river, distance downstream, soil type, rainfall, and land cover. The criteria weights were determined using the AHP method based on expert judgment. The multi-criteria model was built and validated using flood inundation data. Based on the validated model, the effect of land cover changes on flood vulnerability was evaluated. The flood vulnerability changes were also predicted based on rainfall over various return periods. The evaluation and prediction models have shown reliable findings. The criterion elevation and distance to the river significantly influenced the physical flood vulnerability by 41% and 20%. The evaluation model showed a strong correlation between the built-up area and the area with high flood vulnerability (r2 = 0.96). Furthermore, the model predicted an inundation area expansion for rainfall over various return periods. Further research using spatial data with higher resolution and more advanced validation techniques is needed to improve the model accuracy
Changes in Land Requirements Analysis for Green Space Needed in Bogor City
Get PDFBogor City is one of the cities with declining air quality, which increases the risk of air pollution in the city. Improving the air quality requires the addition of vegetation as a green space that can be supported by remote sensing analysis using Google Earth Engine to know the availability of vegetation area in Bogor City. This process takes the median value of Landsat 8 Oli's satellite imagery data for 60 to 91 days of each year and classified by Random Forest Classification and supported by BPS-Statistic of Bogor Municipality data for the number of oxygen users of Bogor City that calculated by the Gerarkis Method to observe the needs of oxygen in Bogor City. The results contain a prediction of the addition of green spaces area needed in Bogor City based on the difference between the Gerarkis Method results and the availability of vegetation area in Bogor City each year. The results show an increased number from 2013 to 2019 because of the increased number of oxygen users each year. The highest number in 2019 shows that Bogor City needs 4,639 Hectares or 40.59% more green spaces area, while the lowest number happened in 2013 with 281.31 Hectares or 2.46% more green spaces area needed. This research could help the growth of development in Bogor City to be balanced between oxygen needs by the public user and urban planning plans
Optimization of Multi-Product Aggregate Production Planning Using Improved Genetic Algorithm
Get PDFMedium-term production planning with aggregate production planning (APP) is a crucial step in the manufacturing industry's supply chain. The essential phase determines the production size of each product over a planning horizon. Poor planning will undoubtedly directly impact the company regarding production costs and profits. The aggregate production planning is classified as NP-Hard combinatorial problem. Thus, a powerful approach is required. Most models in aggregate production planning consider a single product. This study modeled aggregate production planning to address a multi-period and multi-product. Thus, a more complex mathematical model is required. Implementing genetic algorithms (GA) may solve the problem with reasonably good solutions. This study aims to improve the GA by applying real-coded chromosomes and the adaptive change of crossover and mutation rates based on predetermined change criteria. The planning produced by the modified genetic algorithm is compared to the manufacturer's actual planning to prove the proposed approach's effectiveness. A set of computational experiments proves that adaptive evolution enables the genetic algorithm to balance its exploration and exploitation ability and obtain better solutions. The modified GA produces a less fluctuating pattern of the production amount. Even though the modified GA yields more inventory cost, the high cost of recruiting new workers can be eliminated. Using the proposed approach, the company can reduce 9 percent of the production cost
Hybrid Canny Zerocross Method for Edge Detection in Retina Identification Cases
Get PDFEdge detection is fundamental to Figure processing. Edges include much information in a figure, including the object's location, shape, size, and information about its texture. Since edge detection is a critical component of Figure processing for object detection, comprehend algorithms for edge detection. This is because the edges define an item's contours, serve as a demarcation between the object and its backdrop, and serve as a demarcation between overlapping objects. That is, if the edges of an image can be identified accurately, all things can be found. The proposal of this paper is the use of the Canny Zerocross hybrid method to perform better edge detection based on comparative studies and the incorporation of the Canny way, which is considered one of the best edge detection methods, with the Zerocross way (cross zero) which is a derivative of the laplacian. In this paper, the research data used is the retinal image dataset—data obtained from STARE (Structured Analysis of the Retina). The Veterans Administration Medical Center in San Diego and the Shiley Eye Center (ECS) at the University of California provided Figures and clinical data from the retinal images. The experimental results of the comparative study show that the Zerocross edge detection technique is better than the Canny edge detection technique. Meanwhile, edge detection and image identification would be better when combining the two methods (hybrid) based on merging studies
Application of the Nailing Technique to Stabilize a Slope in a Section of the Twinning of Road and Rail Infrastructure
Get PDFNailing is one of the most widely used stabilization techniques because of its technical and economic advantages. It is a practical and effective solution for the reinforcement of in-place slopes. It consists of placing in the soil high resistance nails to increase the cohesion of the soil and its resistance to traction and shear, which allows having a new material of great capacity. In this paper, we present the slope stability study in a section twinning of the road and railroad infrastructures between the kilometer points (KP) 105+938 and 106+263 of the line connecting Casablanca to Marrakech. The railroad track's topographic constraints and geometric requirements made the nailing method appeal to the realization of the new railroad in this area. The objective of this work is, on the one hand, to present the stability analysis of the slope before the earthwork and the implementation of the new railroad and, on the other hand, to evaluate the performance and stability of the nailed walls. The stability analysis of the soils in this section was verified in terms of safety coefficient using the calculation software TALREN. In the end, it can be concluded that the stability calculation results are conclusive and allow for highlighting the effectiveness of the innovative solution of nailing. This technique can be considered a good alternative to improve the safety and performance of excavation walls
Trend Analysis of Rainfall, Land Cover, and Flow Discharge in the Citarum Hulu–Majalaya Basin
Get PDFFloods and drought have been essential aspects of the water issue for over the past 50 years. Several studies have found that they are caused by massive land cover and climate changes. Many climate change studies have been conducted to establish their characteristics using historical data. However, land cover change is a human need that inevitably has to be undertaken to improve the standard of living. Changes in land cover affect the response of land to rainfall, which inevitably affect the amount of run-off generated into rivers. Discharge, land cover, and rainfall are variables that are related to each other. By understanding one variable, we can understand the condition of others, which can describe the situation of the catchment area. This study aims to determine the rain, land cover, and discharge trends in the Citarum Hulu - Majalaya Basin. The historical data obtained by the ground station were used to analyze the rainfall and discharge. A hydrology model was used to establish the change in the land cover parameters, specifically a semi-distributed SWAT model. The non-parametric Mann-Kendall test was employed for the trend analysis and was applied to the annual maximum rainfall and discharge data and the curve number (CN) values. The results show the three are positive trends in maximum rainfall and CN value which affect the discharge value