International Journal on Advanced Science, Engineering and Information Technology
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2006 research outputs found
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Quality Signal Degradation in Single-Channel Fiber Using 10 Gbps Bit Rate
Get PDFReliable data transmission capacity is a crucial factor in supporting high-data-rate communication for smart cities by implementing the Internet of Things. Optical fiber has become the most favorable transmission media by taking advantage of optical signals. However, when optical signals propagate through optical fibers, disturbances occur as the transmission distance increases. These disturbances affect the system performance indicated by the deteriorating transmission data quality in terms of the quality factor (Q-factor) and bit error rate. These parameters are vulnerable to certain factors that can alter signal transmissions such as fiber attenuation, group velocity dispersion (GVD), and self-phase modulation (SPM) as a nonlinear effect. In this study, the effects of these factors on a single-channel, single-mode fiber are investigated using a bit rate of 10 Gbps at various transmission distances and source power levels. The parametric study of attenuation, GVD, and SPM with non-return-to-zero (NRZ) modulation format are considered at various transmission distances, from 10 to 100 km, and input powers of 5 and 10 dBm are simulated using OptiSystem to characterize the parameters of Q-factor and received power. The results indicate that the performance of the system deteriorates as the transmission distance increases, and the dominant effect that impacts the performance is GVD. This result is useful for designing effective and precise fiber optic transmission for high-data-rate transmission
The Monitoring of Dirichlet Compositional Data
Get PDFCompositional data are used in many applications such as Cement, Asphalt, and many other Chemical industries. Such data represent random variables whose values must sum up to a certain constant. Quality engineers and technicians require monitoring compositional data and detecting the source of the irregularity in the process as soon as it happens. Throughout the literature, complicated methods were introduced to monitor compositional data. Such methods are computationally complex and can lead to difficulties in interpreting the results. The Dirichlet distribution is commonly used in the literature to model compositional data. In this study, we propose three simple methods to monitor the mean vector of the Dirichlet distribution. The first method is based on a MEWMA control chart. The second method is based on transforming the Dirichlet random variables into beta random variables and then monitoring them using multiple EWMA control charts, while the third method uses multiple EWMA control charts for transformed independent random variables. Using a simulation technique, the performance of the three methods is investigated, and the three methods performed very well under different sample sizes, many random variables, and values of the distribution parameters. When the process is out-of-control, the source of the out-of-control signal can be detected using Method 2 and Method 3. Method 2 maintained its good performance with a probability 0.99 of correctly detecting the source of the signal. Method 3 performed well except for the case of Dirichlet parameter values less than one. However, it maintained almost a probability of correct detection of at least 90% in most cases. The three proposed methods are simple, do not need complicated calculations, and can easily be applied and used by practitioners
Design a Model-Based on Nonlinear Multiple Regression to Predict the Level of User Satisfaction when Optimizing a Traditional WLAN Using SDWN
Get PDFHigher education institutions' wireless networks have different roles and network requirements, ranging from educational platforms and informative consultations. Currently, the inefficient use of network resources, poor wireless planning, and other factors, affect having a robust and stable network platform. Different authors have investigated the various strategies for the optimization of wireless infrastructures. Still, most of the cases studied aim to improve traditional performance variables without considering maximizing the level of user satisfaction, which represents a flaw that this research paper hopes to solve through SDWN and a predictive model. The authors will determine an appropriate methodology to estimate the user's level of satisfaction through an algorithm or predictive model based on nonlinear multiple regression supported on network performance variables, making a characterization of the project's environment analyzing the wireless conditions. The investigation phases will follow the life cycle guidelines defined by the Cisco PPDIOO methodology (Prepare, Plan, Design, Implement, Operate, Optimize). As a result, it is expected that the project will be the beginning of academic research that will help create strategies to optimize the WiFi network of any educational institution to maximize user satisfaction. In short, the optimization process provides the network with differentiating factors through a modular design with variable modification of parameters according to the users' requirements and needs
The Latowu Ultramafic Rock-Hosted Iron Mineralization in the Southeastern Arm Sulawesi, Indonesia: Characteristics, Origin, and Implication for Beneficiation
Get PDFLatowu ultramafic block in the Southeastern Arm Sulawesi locally hosts elevated concentrations of Fe in addition to Ni. We investigated both host rock and mineralized samples' mineralogy and chemistry to find out mineralogical and chemical characteristics and interpret the iron mineralization process with beneficiation implications. The mineralogical nature of the samples was analyzed using optical microscopy and X-ray diffractometry (XRD) methods. The whole-rock and mineral chemistry analyses were performed using X-ray fluorescence (XRF) spectroscopy and electron probe microanalysis (EPMA) techniques. The analysis showed that the ultramafic rocks had been undergone a strong to complete serpentinization degree where lizardite appears to be the predominant mineral. Magnetite in this research comprised the principal iron-bearing mineral and functioned as discrete fine-grains and subhedral to anhedral crystals. Magnetite occurs as fragments in breccia, alteration rim in spinel, fine-grained disseminations, and micro veins. This research found that the whole-rock chemistry of an ultramafic breccia showed an elevated concentration in Fe2O3 with a grade of 28.44 wt%. Electron probe analysis of magnetite shows a wide variation of Fe ranging from 31.10 wt% to 67.20 wt%. It is interpreted that the formation of magnetite within ultramafic rocks is influenced by the hydration of primary minerals, mainly olivine. Iron is most likely released from olivine or pyroxene crystals during serpentinization, and the higher water content of serpentine promotes its mobility. It is suggested that the magnetic separation method can be potentially used to increase the Fe grade
Performance of Water Wheel Knock Down System (W2KDS) for Rice Milling Drive
Get PDFThe number of water wheels operated by the community in West Sumatra, Indonesia, in 1970 was around 4082 units, and now it is estimated that there are around 420 units. The water wheel system is made permanent, made of wood, the construction is quite heavy so that it becomes a problem when installing it. Water Wheel Knock Down System (W2KDS) is a good alternative and solution because the construction is light, and its components can be broken down so that it is easier to install in remote villages. The formulation of the problem of this research is how the performance of W2KDS driving rice milling? The research objective was to analyze W2KDS performance, transmission efficiency, and rice milling productivity. The research methodology is an experiment with the stages of designing W2KDS systems and components, building W2KDS-rice milling, and analyzing the performance of W2KDS driving rice milling. The type of W2KDS that has been successfully built is a breast shot with an outer wheel diameter of 180 cm, an inner diameter of 120 cm, a blade width of 60 cm, 20 blades, and a belt-pulley power transmission system. The results of the W2KDS performance analysis of rice milling driving are, at a water flow rate of 88 L/s, head of 5 m, and a rotational speed of 60 rpm, the resulting torque is 551 Nm, power 3400 W, W2KDS efficiency 78.1%, transmission system efficiency 88.2% and rice milling productivity of 86.40 kg of rice/hour
Carrier RNA (cRNA) Enhances dsDNA Recovery Extracted from Small Volume Spent Embryo Culture Medium
Get PDFEmbryo spent culture medium has been intensively investigated, considering its promising feature for non-invasive bioanalytical techniques in in-vitro fertilization (IVF). Despite, isolating DNA from such samples is quite challenging due to its small volume. Carrier RNA is reported to exhibit DNA retrieval effects and commonly employed in various limited biological samples, but there are no reports regarding its benefit on embryo media. Therefore, we aim to evaluate the competence of cRNA on isolated DNA from embryo medium and analyzed its optimal volume as there are also no records respecting its ideal volume to obtain decent outcomes. Results showed that cRNA significantly increases DNA amounts in the cRNA treated group (p<0.001), but the D-4/D-5 medium yielded similar (p=0.684). Pearson test demonstrated no correlation between cRNA volume vs. total retrieved DNA (r=0.760, p=0.80), and Whole Genome Amplification (WGA) was shown to increase DNA in the treated group (p=0.022), but not in the untreated group (p=0.128). Additionally, electrophoresis successfully resulting in a thick and thin band of TH01 locus signifies the cRNA competence. In conclusion, our study suggests that cRNA addition is essential in embryo medium extraction as it increases initial DNA that crucial for downstream application. However, the optimal volume could not be determined in the current study since the initial amount of DNA in the medium is unknown. Obtained findings are expected to be a new input for subsequent research on DNA extraction
Laser Actuated Non-Invasive Smart Instrumentation - Enabling Lab-on-Chip
Get PDFNon-invasive optical instrumentation provides non-destructive, reliable, and precise control in industrial process regulation, especially when chemical compounds or organic material surfaces are always a point of care. Nanomaterial dynamics intrinsically exhibit higher order of visual scanning complexities, associate wholly or partially to the poor scanning instrumentations. Additionally, growing trends in analytical instrumentation towards smart Lab-On-a-Chip (IoT sensing nodes) have shifted the emphasis on sensitivity and robustness tailoring Product Specific Environment (PSE). This work presents a hybrid laser actuated scanning mechanism, rastered back and forth 3-D imaging technique enabling Microscopy to its widest application in biological and material sciences and hence rose challenge of predicting large missing or incorrect data obtained during experiments. Our Confocal Self Calibrated Interferometry based fabricated Laser Sensor demonstrates its efficacy in non-invasive scanning microscopy to achieve a high-resolution 3D topographical view, eventually an add-on to the analytical model of microorganisms and nanomaterial. In contrast to linear controllers, PI controllers demonstrate better stability in controlling the laser leakage at tip, which consists of two channel tube adjustments and successively in laser reflector lens, Photo Multiplier Tube (PMT), and Data Acquisition Unit (DAU). We expose our results for error propagation across various grid patterns over a 1mm2 section, plotting the intensity of a key band or bands over the PMT grid. We observe that the instrumentation errors can be nullified by modeling the ergodicity of information flow along with the SLM instrumentation
Studies of Genetic and Morphological Characteristics of Indonesian Melon (Cucumis melo L. ‘Hikapel’) Germplasm
Get PDFThe abundance of biodiversity in Indonesia is due to variations in germplasm and the diversity of plant species. Due to the high potential and demand for melons, it is necessary to innovate the assembly of superior varieties through a plant breeding approach. Here, we report the identification of phenotypic and genotypic traits with their phenetic relationships to determine the premium characteristics of the new melon cultivar - Hikapel. Observation of morphological characters using observational studies, qualitative descriptive, and quantitative identification at two cultivation locations: (1) Prambanan, Sleman Regency, Yogyakarta, and (2) Pangalengan, Bandung Regency, West Java. Meanwhile, molecular character testing uses the ISSR markers UBC-807, UBC-808, UBC-810, UBC-812, and UBC-825. Morphological character data were analyzed using SPSS one-way ANOVA with LSD and Duncan tests. All data were grouped based on similarity values using cluster analysis of the multi-variate statistical package (MVSP 3.1) to determine the tested kinship relationship between the varieties. The results showed that Hikapel has several diagnostic characters as a new variety, namely: globular shape with cream-colored skin, aromatic fruit, small size, high sweetness level, and short harvest time. The stability and uniformity test results those characters of Hikapel can be maintained at various locations. This research can serve as basic data for developing melon varieties based on genomic data and aims as an initial step in the innovation of Indonesian Agriculture
Improving the Flight Endurance of a Separate-Lift-and-Thrust Hybrid through Gaussian Process Optimization
Get PDFA separate-lift-and-thrust hybrid is a modified fixed-wing drone which includes quadcopter rotors. This results in the combined capability of forwarding flight as well as vertical take-off and landing (VTOL), making it a low-cost method that can deliver substantial gains in utility. Though this is a strong point compared to other types of VTOL drones, the hybrid design may incur a significant trade-off because added weight and drag can severely reduce the drone's flight endurance. This study attempts to mitigate the impact by improving the configuration of the selection and positioning parameters. Since drag estimations are costly, a Gaussian process optimization method was performed, as it is economical with respect to the required number of iterations. A set of arbitrarily selected components was prepared for use with the optimization method, recording the relevant performance data and constructing the CAD models of the components for use in simulations. The optimization method was able to increase the estimated flight endurance to 27.99 minutes, a significant improvement compared to a set of random configurations, which only yielded 9.54 minutes at best. The respectable result was obtained even though difficulties were experienced regarding the infeasible regions that arise from the many constraints. Future implementation of this optimization approach can be further improved. It may be worthwhile to utilize a low-fidelity model from the base fixed-wing drone simulations, in contrast with using an initial zero mean for the prior of the Gaussian process
Employment the State Space and Kalman Filter Using ARMA models
Get PDFThe research is interested in studying a modern mathematical topic of great importance in contemporary applications known as the representation of the state space for mathematical models of time series represented by ARMA models and the discussion of a Kalman filter such as the one who has very general characteristics and of the utmost importance and depends on the representation of the state space. Raw data on electrical energy consumption in Mosul city have been used for the period from (15/6/2003 to 25/9/2003), and after examining these data as to whether they are stationary or not, it was found that there is no stationary for the series behavior in the arithmetic mean, variance and after conversion. The state-space model is characterized by being an efficient scale in all states that are not observed or controlled, and for this, the state-space model can be used to estimate states that cannot be observed. It can also express the state-space model simply for complex operations and is characterized by the flexible model. The series into a stationary time series with variance and mean. The autocorrelation function (ACF) and the partial autocorrelation function (PACF) have been calculated, and observation of the propagation behavior of these two functions shows that the best model for representing data is ARMA (2,1) model. And then, the parameters of the model were estimated using the matrix system for the state-space model and then taking advantage of the state-space model in estimating the observation equation for a Kalman filter such as the security and it was found that a Kalman filter such as security is very efficient in purifying the series from noise