Search results for: adaptive genetic regions

Authors: C. Senabre, S. Valero, M. Lopez, E. Velasco, M. Sanchez

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This paper focuses on an application of linear mixed models to short-term load forecasting. The challenge of this research is to improve a currently working model at the Spanish Transport System Operator, programmed by us, and based on linear autoregressive techniques and neural networks. The forecasting system currently forecasts each of the regions within the Spanish grid separately, even though the behavior of the load in each region is affected by the same factors in a similar way. A load forecasting system has been verified in this work by using the real data from a utility. In this research it has been used an integration of several regions into a linear mixed model as starting point to obtain the information from other regions. Firstly, the systems to learn general behaviors present in all regions, and secondly, it is identified individual deviation in each regions. The technique can be especially useful when modeling the effect of special days with scarce information from the past. The three most relevant regions of the system have been used to test the model, focusing on special day and improving the performance of both currently working models used as benchmark. A range of comparisons with different forecasting models has been conducted. The forecasting results demonstrate the superiority of the proposed methodology.

Keywords: short-term load forecasting, mixed effects models, neural networks, mixed effects models

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Authors: H. Mansor, S.B. Mohd-Noor, N. I. Othman, N. Tazali, R. I. Boby

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This paper presents an improved robust Proportional Derivative controller for a 3-Degree-of-Freedom (3-DOF) bench-top helicopter by using adaptive methodology. Bench-top helicopter is a laboratory scale helicopter used for experimental purposes which is widely used in teaching laboratory and research. Proportional Derivative controller has been developed for a 3-DOF bench-top helicopter by Quanser. Experiments showed that the transient response of designed PD controller has very large steady state error i.e., 50%, which is very serious. The objective of this research is to improve the performance of existing pitch angle control of PD controller on the bench-top helicopter by integration of PD controller with adaptive controller. Usually standard adaptive controller will produce zero steady state error; however response time to reach desired set point is large. Therefore, this paper proposed an adaptive with deadbeat algorithm to overcome the limitations. The output response that is fast, robust and updated online is expected. Performance comparisons have been performed between the proposed self-tuning deadbeat PD controller and standard PD controller. The efficiency of the self-tuning dead beat controller has been proven from the tests results in terms of faster settling time, zero steady state error and capability of the controller to be updated online.

Keywords: adaptive control, deadbeat control, bench-top helicopter, self-tuning control

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Authors: Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu

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Satellite imagery classification is a challenging problem with many practical applications. In this paper, we designed a deep convolution neural network (DCNN) to classify the satellite imagery. The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at the same level, as the building block to build our DCNN model. Second, we proposed a genetic algorithm based method to efficiently search the best hyper-parameters of the DCNN in a large search space. The proposed method is evaluated on the benchmark database. The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space. Based on the found hyper-parameters, we built our DCNN models, and evaluated its performance on satellite imagery classification, the results show the classification accuracy of proposed models outperform the state of the art method.

Keywords: satellite imagery classification, deep convolution network, genetic algorithm, hyper-parameter optimization

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Authors: Hung-Jiun Chi, Cheng-En Tsai, Jia-Ying Tu

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Semi-active control of Magnetorheological (MR) dampers for vibration reduction of structural systems has received considerable attention in civil and earthquake engineering, because the effective stiffness and damping properties of MR fluid can change in a very short time in reaction to external loading, requiring only a low level of power. However, the inherent nonlinear dynamics of hysteresis raise challenges in the modeling and control processes. In order to control the MR damper, an innovative Duffing-like equation is proposed to approximate the hysteresis dynamics in a deterministic and systematic manner than previously has been possible. Then, the model-reference adaptive control technique based on the Duffing-like model and the Lyapunov method is discussed. Parameter identification work with experimental data is presented to show the effectiveness of the Duffing-like model. In addition, simulation results show that the resulting adaptive gains enable the MR damper force to track the desired response of the reference model satisfactorily, verifying the effectiveness of the proposed modeling and control techniques.

Keywords: magnetorheological damper, duffing equation, model-reference adaptive control, Lyapunov function, hysteresis

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Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

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This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

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Authors: Marine Segui, Simon Bezin, Ruxandra Mihaela Botez

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As part of a ‘Morphing-Wing’ idea, this study consists of measuring how a winglet, which is able to change its shape during the flight, is efficient. Conventionally, winglets are fixed-vertical platforms at the wingtips, optimized for a cruise condition that the airplane should use most of the time. However, during a cruise, an airplane flies through a lot of cruise conditions corresponding to altitudes variations from 30,000 to 45,000 ft. The fixed winglets are not optimized for these variations, and consequently, they are supposed to generate some drag, and thus to deteriorate aircraft fuel consumption. This research assumes that it exists a winglet position that reduces the fuel consumption for each cruise condition. In this way, the methodology aims to find these optimal winglet positions, and to further simulate, and thus estimate the fuel consumption of an aircraft wearing this type of adaptive winglet during several cruise conditions. The adaptive winglet is assumed to have degrees of freedom given by the various changes of following surfaces: the tip chord, the sweep and the dihedral angles. Finally, results obtained during cruise simulations are presented in this paper. These results show that an adaptive winglet can reduce, thus improve up to 2.12% the fuel consumption of an aircraft during a cruise.

Keywords: aerodynamic, Cessna, Citation X, optimization, winglet

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Authors: Jin-Siang Shaw, Patricia Moya Caceres, Sheng-Xiang Xu

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This paper aims to integrate the particle swarm optimization (PSO) method with the adaptive fuzzy sliding mode controller (AFSMC) to achieve vibration attenuation in a piezoelectric actuator subject to base excitation. The piezoelectric actuator is a complicated system made of ferroelectric materials and its performance can be affected by nonlinear hysteresis loop and unknown system parameters and external disturbances. In this study, an adaptive fuzzy sliding mode controller is proposed for the vibration control of the system, because the fuzzy sliding mode controller is designed to tackle the unknown parameters and external disturbance of the system, and the adaptive algorithm is aimed for fine-tuning this controller for error converging purpose. Particle swarm optimization method is used in order to find the optimal controller parameters for the piezoelectric actuator. PSO starts with a population of random possible solutions, called particles. The particles move through the search space with dynamically adjusted speed and direction that change according to their historical behavior, allowing the values of the particles to quickly converge towards the best solutions for the proposed problem. In this paper, an initial set of controller parameters is applied to the piezoelectric actuator which is subject to resonant base excitation with large amplitude vibration. The resulting vibration suppression is about 50%. Then PSO is applied to search for an optimal controller in the neighborhood of this initial controller. The performance of the optimal fuzzy sliding mode controller found by PSO indeed improves up to 97.8% vibration attenuation. Finally, adaptive version of fuzzy sliding mode controller is adopted for further improving vibration suppression. Simulation result verifies the performance of the adaptive controller with 99.98% vibration reduction. Namely the vibration of the piezoelectric actuator subject to resonant base excitation can be completely annihilated using this PSO based adaptive fuzzy sliding mode controller.

Keywords: adaptive fuzzy sliding mode controller, particle swarm optimization, piezoelectric actuator, vibration suppression

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Authors: Kang-Mo Jung

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The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

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Authors: R. Sumalatha, M. V. Subramanyam

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In medical image processing the quality of the image is degraded in the presence of noise. Especially in ultra sound imaging and Magnetic resonance imaging the data was corrupted by signal dependent noise known as salt and pepper noise. Removal of noise from the medical images is a critical issue for researchers. In this paper, a new type of technique Adaptive Spatial Mask Filter (ASMF) has been proposed. The proposed filter is used to increase the quality of MRI and ultra sound images. Experimental results show that the proposed filter outperforms the implementation of mean, median, adaptive median filters in terms of MSE and PSNR.

Keywords: salt and pepper noise, ASMF, PSNR, MSE

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Authors: Yi Ming Zhang, Zhan Xi Wang, Hang Chen, Gang Wang

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Manual polishing has problems such as high labor intensity, low production efficiency and difficulty in guaranteeing the consistency of polishing quality. It is more and more necessary to replace manual polishing with robot polishing. Polishing force directly affects the quality of polishing, so accurate tracking and control of polishing force is one of the most important conditions for improving the accuracy of robot polishing. The traditional force control strategy is difficult to adapt to the strong coupling of force control and position control during the robot polishing process. Therefore, based on the analysis of force-based impedance control and position-based impedance control, this paper proposed a new type of adaptive controller. Based on force feedback control of active compliance control, the controller can adaptively estimate the stiffness and position of the external environment and eliminate the steady-state force error produced by traditional impedance control. The simulation results of the model shows that the adaptive controller has good adaptability to changing environmental positions and environmental stiffness, and can accurately track and control polishing force.

Keywords: robot polishing, force feedback, impedance control, adaptive control

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Authors: Mosaad Hamouda, Kamal Khalaf, Zaker Mousa

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National projects are considered Egypt's future vision in investing its various resources and the best way to bring about a developmental renaissance that constitutes a quantum leap because of its developmental impact on the planning regions, which it achieves in attracting and localizing investments to achieve urban development, and what this has a noticeable impact on dividing those regions in order to achieve a developmental balance or at least reduce the severity of the disparities between them, by measuring the impact of these projects, which appear in the per capita share of the various developmental variables, and also analyzing global and local experiences so that a balanced division of the country’s regions can be reached, and the research finds a set of planning foundations that are compatible with the settlement of these national projects in the future.

Keywords: national projects, regional development, division of regions, development disparities

Procedia PDF Downloads 91

Authors: Mahima Shrivastava, Soumya Kar, B. Swetha Malika, Lalu Saheb, M. Muthu Kumar, P. V. Ponambala Moorthi

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Natural hazards and manmade destruction causes both economic and societal losses. Generalized pre-mitigation strategies introduced and adopted for prevention of disaster all over the world are capable of augmenting the resiliency and optimizing the life-cycle cost of facilities. In countries like India where varied topographical feature exists requires location specific mitigation measures and strategies to be followed for better enhancement by event-driven and code-driven approaches. Present state of vindication measures followed and adopted, lags dominance in accomplishing the required development. In addition, serious concern and debate over climate change plays a vital role in enhancing the need and requirement for the development of time bound adaptive mitigation measures. For the development of long-term sustainable policies incorporation of future climatic variation is inevitable. This will further assist in assessing the impact brought about by the climate change on life-cycle cost of facilities. This paper develops more definite region specific and time bound pre-mitigation measures, by reviewing the present state of mitigation measures in India and all over the world for improving life-cycle cost of facilities. For the development of region specific adoptive measures, Indian regions were divided based on multiple-calamity prone regions and geo-referencing tools were used to incorporate the effect of climate changes on life-cycle cost assessment. This study puts forward significant effort in establishing sustainable policies and helps decision makers in planning for pre-mitigation measures for different regions. It will further contribute towards evaluating the life cycle cost of facilities by adopting the developed measures.

Keywords: climate change, geo-referencing tools, life-cycle cost, multiple-calamity prone regions, pre-mitigation strategies, sustainable policies

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Authors: Doreen Duri, Danai Zhou, Babil Stray-Pedersen, Collet Dandara

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Given the high prevalence of HIV/AIDS in sub-Saharan Africa, and the elusive search for a cure, understanding the pharmacogenetics of currently used drugs is critical in populations from the most affected regions. Compared to Asian and Caucasian populations, African population groups are more genetically diverse, making it difficult to extrapolate findings from one ethnic group to another. This study aimed to investigate the role of genetic variation in CYP2B6 (c.516G>T and c.983T>C) single nucleotide polymorphisms on plasma nevirapine levels among HIV-infected adult Zimbabwean patients. Using a cross-sectional study, patients on nevirapine-containing HAART, having reached steady state (more than six weeks on treatment) were recruited to participate. Blood samples were collected after patients provided consent and samples were used to extract DNA for genetic analysis or to measure plasma nevirapine levels. Genetic analysis was carried out using PCR and RFLP or Snapshot for the two single nucleotide polymorphisms; CYP2B6 c.516G>T and c.983T>C, while LC-MS/MS was used in analyzing nevirapine concentration. CYP2B6 c.516G>T and c.983T>C significantly predicted plasma nevirapine concentration with the c.516T and c.983T being associated with elevated plasma nevirapine concentrations. Comparisons of the variant allele frequencies observed in this group to those reported in some African, Caucasian and Asian populations showed significant differences. We conclude that pharmacogenetics of nevirapine can be creatively used to determine patients who are likely to develop nevirapine-associated side effects as well as too low plasma concentrations for viral suppression.

Keywords: allele frequencies, genetically diverse, nevirapine, single nucleotide polymorphism

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Authors: Alina Mirza, Sumrin M. Kabir, Shahzad A. Sheikh

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The Orthogonal Frequency Division Multiplexing (OFDM) with high data rate, high spectral efficiency and its ability to mitigate the effects of multipath makes them most suitable in wireless application. Impulsive noise distorts the OFDM transmission and therefore methods must be investigated to suppress this noise. In this paper, a State Space Recursive Least Square (SSRLS) algorithm based adaptive impulsive noise suppressor for OFDM communication system is proposed. And a comparison with another adaptive algorithm is conducted. The state space model-dependent recursive parameters of proposed scheme enables to achieve steady state mean squared error (MSE), low bit error rate (BER), and faster convergence than that of some of existing algorithm.

Keywords: OFDM, impulsive noise, SSRLS, BER

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Authors: Amal Jmaii, Damien Rousseliere, Besma Belhadj

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We explore the relationship between internal migration and poverty in Tunisia. We present a methodology combining potential outcomes approach with multiple imputation to highlight the effect of internal migration on poverty states. We find that probability of being poor decreases when leaving the poorest regions (the west areas) to the richer regions (greater Tunis and the east regions).

Keywords: internal migration, potential outcomes approach, poverty dynamics, Tunisia

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Authors: Shohreh Moshiri, Hossein Alimohammadi

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Building construction has a great impact on climate change. Adaptive design strategies were developed to provide new life and purpose to old buildings and create new environments with economic benefits to meet resident needs. The role of smart material systems is undeniable in providing adaptivity of the architectural environments and their effects on creating better adaptive building environments. In this research, a case study named Neuhoff site located near Cumberland River in the Germantown neighborhood in the city of Nashville, Tennessee, was considered. This building in the early 1920s was constructed as a meat-packing facility and then served as a mixed-use space; however, New City has partnered with world-class architects to reinvent this site to be changed to mixed-use waterfront development. The future office space will be designed with LEED certification as a goal. Environmentally friendly sensitive materials and designs will offer for all adaptive reuse of the building. The smart materials and their applications, especially in the field of building technology and architecture, were emphasized in providing a renovation plan for the site. The advantages and qualities of smart material systems were targeted to explore in this research on the field of architecture. Also, this research helps to understand better the effects of smart material systems on the construction and design processes, exploration of the way to make architecture with better adaptive characteristics, plus provide optimal environmental situations for the users, which reflect on the climatic, structural, and architectural performances.

Keywords: adaptive architecture, building technology, case study, smart material systems

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Authors: Javier Fernandez De Canete, Alvaro Fernandez-Quintero

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Nowadays, adaptive control schemes are being used when model based control schemes are applied in presence of uncertainty and model mismatches. Artificial neural networks have been employed both in modelling and control of non-linear dynamic systems with unknown dynamics. In fact, these are powerful tools to solve this control problem when only input-output operational data are available. A neural network controller under SIMULINK together with the ARDUINO hardware platform has been used to perform real-time speed control of a computer case fan. Comparison of performance with a PID controller has also been presented in order to show the efficacy of neural control under different command signals tracking and also when disturbance signals are present in the speed control loops.

Keywords: neural networks, ARDUINO platform, SIMULINK, adaptive speed control

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Authors: Elsheikh Asser

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Time and cost are the main goals of the construction project management. The first schedule developed may not be a suitable schedule for beginning or completing the project to achieve the target completion time at a minimum total cost. In general, there are trade-offs between time and cost (TCT) to complete the activities of a project. This research presents genetic algorithms (GAs) multi-objective model for project scheduling considering different scenarios such as least cost, least time, and target time.

Keywords: genetic algorithms, time-cost trade-off, multi-objective model, project scheduling

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Authors: Jia Li, Huacong Li, Xiaobao Han

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Due to the more variable geometry parameters of VCE (variable cycle aircraft engine), presents an adaptive controller method based on the full-state linear model of VCE and has simulated to solve the multivariate controller design problem of the whole flight envelops. First, analyzes the static and dynamic performances of bypass ratio and other state parameters caused by variable geometric components, and develops nonlinear component model of VCE. Then based on the component model, through small deviation linearization of main fuel (Wf), the area of tail nozzle throat (A8) and the angle of rear bypass ejector (A163), setting up multiple linear model which variable geometric parameters can be inputs. Second, designs the adaptive controllers for VCE linear models of different nominal points. Among them, considering of modeling uncertainties and external disturbances, derives the adaptive law by lyapunov function. The simulation results showed that, the adaptive controller method based on full-state linear model used the angle of rear bypass ejector as input and effectively solved the multivariate control problems of VCE. The performance of all nominal points could track the desired closed-loop reference instructions. The adjust time was less than 1.2s, and the system overshoot was less than 1%, at the same time, the errors of steady states were less than 0.5% and the dynamic tracking errors were less than 1%. In addition, the designed controller could effectively suppress interference and reached the desired commands with different external random noise signals.

Keywords: variable cycle engine (VCE), full-state linear model, adaptive control, by-pass ratio

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Authors: Ali Anwar, Hu Qinglei, Li Bo, Muhammad Taha Ali

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In this paper a generic model of perturbed nonlinear systems is considered which is affected by hard backlash nonlinearity at the input. The nonlinearity is modelled by a dynamic differential equation which presents a more precise shape as compared to the existing linear models and is compatible with nonlinear design technique such as backstepping. Moreover, a novel backstepping based nonlinear control law is designed which explicitly incorporates a continuous-time adaptive backlash inverse model. It provides a significant flexibility to control engineers, whereby they can use the estimated backlash spacing value specified on actuators such as gears etc. in the adaptive Backlash Inverse model during the control design. It ensures not only global stability but also stringent transient performance with desired precision. It is also robust to external disturbances upon which the bounds are taken as unknown and traverses the backlash spacing efficiently with underestimated information about the actual value. The continuous-time backlash inverse model is distinguished in the sense that other models are either discrete-time or involve complex computations. Furthermore, numerical simulations are presented which not only illustrate the effectiveness of proposed control law but also its comparison with PID and other backstepping controllers.

Keywords: adaptive control, hysteresis, backlash inverse, nonlinear system, robust control, backstepping

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Authors: Zia Amjad, Salem Safar Alghamdi

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This experiment was carried out at student educational farm College of Food and Agriculture, KSU, kingdom of Saudi Arabia; in order to characterize 154 Vicia faba, characterization, PCA, ago-morphological diversity. Icia faba L. accessions were based on ipove and ibpgr descriptors. 24 agro-morphological characters including 11 quantitative and 13 qualitative were observed for genetic variation. All the results were analyzed using multivariate analysis i.e. principle component analysis. First 6 principle components with eigenvalue greater than one; accounted for 72% of available Vicia faba genetic diversity. However, first three components revealed more than 10% of genetic diversity each i.e. 22.36%, 15.86%, and 10.89% respectively. PCA distributed the V. faba accessions into different groups based on their performance for the characters under observation. PC-1 which represented 22.36% of the genetic diversity was positively associated with stipule spot pigmentation, intensity of streaks, pod degree of curvature and to some extent with 100 seed weight. PC-2 covered 15.86 of the genetic diversity and showed positive association for average seed weight per plant, pod length, number of seeds per plant, 100 seed weight, stipule spot pigmentation, intensity of streaks (same as in PC-1), and to some extent for pod degree of curvature and number of pods per plant. PC-3 revealed 10.89% of genetic diversity and expressed positive association for number of pods per plant and number of leaflets per plant.

Keywords: Vicia faba, characterization, PCA, ago-morphological diversity

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Authors: B. Grygalewicz, R. Woroniecka, J. Rygier, K. Borkowska, A. Labak, B. Nowakowska, B. Pienkowska-Grela

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Introduction: Chronic lymphocytic leukemia (CLL) is the most common form of adult leukemia in the Western world. Hemizygous and or homozygous loss at 13q14 occur in more than half of cases and constitute the most frequent chromosomal abnormality in CLL. It is believed that deletions 13q14 play a role in CLL pathogenesis. Two microRNA genes miR-15a and miR- 16-1 are targets of 13q14 deletions and plays a tumor suppressor role by targeting antiapoptotic BCL2 gene. Deletion size, as a single change detected in FISH analysis, has haprognostic significance. Patients with small deletions, without RB1 gene involvement, have the best prognosis and the longest overall survival time (OS 133 months). In patients with bigger deletion region, containing RB1 gene, prognosis drops to intermediate, like in patients with normal karyotype and without changes in FISH with overall survival 111 months. Aim: Precise delineation of 13q14 deletions regions in two groups of CLL patients, with mono- and biallelic deletions and qualifications of their prognostic significance. Methods: Detection of 13q14 deletions was performed by FISH analysis with CLL probe panel (D13S319, LAMP1, TP53, ATM, CEP-12). Accurate deletion size detection was performed by CGH Haematological Cancer and SNP array (8x60K). Results: Our investigated group of CLL patients with the 13q14 deletion, detected by FISH analysis, comprised two groups: 18 patients with monoallelic deletions and 18 patients with biallelic deletions. In FISH analysis, in the monoallelic group the range of cells with deletion, was 43% to 97%, while in biallelic group deletion was detected in 11% to 94% of cells. Microarray analysis revealed precise deletion regions. In the monoallelic group, the range of size was 348,12 Kb to 34,82 Mb, with median deletion size 7,93 Mb. In biallelic group discrepancy of total deletions, size was 135,27 Kb to 33,33 Mb, with median deletion size 2,52 Mb. The median size of smaller deletion regions on one copy chromosome 13 was 1,08 Mb while the average region of bigger deletion on the second chromosome 13 was 4,04 Mb. In the monoallelic group, in 8/18 deletion region covered RB1 gene. In the biallelic group, in 4/18 cases, revealed deletion on one copy of biallelic deletion and in 2/18 showed deletion of RB1 gene on both deleted 13q14 regions. All minimal deleted regions included miR-15a and miR-16-1 genes. Genetic results will be correlated with clinical data. Conclusions: Application of CGH microarrays technique in CLL allows accurately delineate the size of 13q14 deletion regions, what have a prognostic value. All deleted regions included miR15a and miR-16-1, what confirms the essential role of these genes in CLL pathogenesis. In our investigated groups of CLL patients with mono- and biallelic 13q14 deletions, patients with biallelic deletion presented smaller deletion sizes (2,52 Mb vs 7,93 Mb), what is connected with better prognosis.

Keywords: CLL, deletion 13q14, CGH microarrays, SNP array

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Authors: M. G. Gopisankar, A. Surendiran, M. Hemachandren

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The dose requirement of warfarin to achieve target INR range varies in patients with prosthetic heart valve. This variation in is affected by both genetic and non-genetic factors. Earlier studies have identified role of CYP2C9 and VKORC1 genetic polymorphisms on warfarin dose requirement. Warfarin being a substrate for drug transporter, P-glycoprotein coded by ABCB1 gene, may also be influenced by its genetic polymorphisms. This study was aimed to study the effect of single nucleotide polymorphism (SNP), ABCB1 2677G > T on warfarin maintenance dose requirement in patients with steady-state International Normalized Ratio (INR). The median dose requirement was significantly different between the genotype groups GG vs. GT (35 ± 20; 42.5 ± 18, p < 0.05), GG vs. TT (35 ± 20; 41.25 ± 25, p<0.05). There was no significant difference between GT vs. TT. In conclusion, patients with variant allele require a higher weekly maintenance dose of warfarin compared to patients without variant allele.

Keywords: warfarin pharamcogenetics, pharmacogenomics of warfarin, ABCB1 and warfarin, pglycoprotein and warfarin

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Authors: Aprilia, Wei Liang Keith Nguyen, Shu Beng Tor, Gerald Gim Lee Seet, Chee Kai Chua

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Automated remanufacturing process is of great interest in today’s marine and offshore industry. Most of the current remanufacturing processes are carried out manually and hence they are error prone, labour-intensive and costly. In this paper, a conceptual framework for automated remanufacturing is presented. This framework involves the integration of 3D non-contact digitization, adaptive surface reconstruction, additive manufacturing and machining operation. Each operation is operated and interconnected automatically as one system. The feasibility of adaptive surface reconstruction on marine and offshore engineering components is also discussed. Several engineering components were evaluated and the results showed that this proposed system is feasible. Conclusions are drawn and further research work is discussed.

Keywords: adaptive surface reconstruction, automated remanufacturing, automatic repair, reverse engineering

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Authors: M. Y. Abubakar, Ipinjolu J. K., Yuzine B. Esa, Magawata I., Hassan W. A., Turaki A. A.

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Catfish (Heterobranchus spp.) is a major freshwater fish that are widely distributed in Nigeria waters and are gaining rapid aquaculture expansion. However, indiscriminate artificial crossbreeding of the species with others poses a threat to their biodiversity. There is a paucity of information about the genetic variability, hence this insight on the genetic variability is badly needed, not only for the species conservation but for aquaculture expansion. In this study, we tested the level of Genetic diversity, population differentiation and phylogenetic relationship analysis on 35 individuals of two populations of Heterobranchus bidorsalis and 29 individuals of three populations of Heterobranchus longifilis using the mitochondrial cytochrome c oxidase subunit I (mtDNA COI) gene sequence. Nucleotide sequences of 650 bp fragment of the COI gene of the two species were compared. In the whole 4 and 5 haplotypes were distinguished in the populations of H. bidorsalis & H. longifilis with accession numbers (MG334168 - MG334171 & MG334172 to MG334176) respectively. Haplotypes diversity indices revealed a range of 0.59 ± 0.08 to 0.57 ± 0.09 in H. bidorsalis and 0.000 to 0.001051 ± 0.000945 in H. longifilis population, respectively. Analysis of molecular variance (AMOVA) revealed no significant variation among H. bidorsalis population of the Niger & Benue Rivers, detected significant genetic variation was between the Rivers of Niger, Kaduna and Benue population of H. longifilis. Two main clades were recovered, showing a clear separation between H. bidorsalis and H. longifilis in the phylogenetic tree. The mtDNA COI genes studied revealed high gene flow between populations with no distinct genetic differentiation between the populations as measured by the fixation index (FST) statistic. However, a proportion of population-specific haplotypes was observed in the two species studied, suggesting a substantial degree of genetic distinctiveness for each of the population investigated. These findings present the description of the species character and accessions of the fish’s genetic resources, through gene sequence submitted in Genetic database. The data will help to protect their valuable wild resource and contribute to their recovery and selective breeding in Nigeria.

Keywords: AMOVA, genetic diversity, Heterobranchus spp., mtDNA COI, phylogenetic tree

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Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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Authors: Ibrahim Ilker Ozyigit, Ertugrul Filiz, Ilhan Dogan

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An in silico analysis of Brachypodium distachyon, Triticum aestivum, Festuca arundinacea, Lolium perenne, Hordeum vulgare subsp. vulgare of the Pooideaea was performed based on complete chloroplast genomes including rbcL coding and trnH-psbA intergenic spacer regions alone to compare phylogenetic resolving power. Neighbor-joining, Minimum Evolution, and Unweighted Pair Group Method with arithmetic mean methods were used to reconstruct phylogenies with the highest bootstrap supported the obtained data from whole chloroplast genome sequence. The highest and lowest values from nucleotide diversity (π) analysis were found to be 0.315813 and 0.043495 in rbcL coding region in chloroplast genome and complete chloroplast genome, respectively. The highest transition/transversion bias (R) value was recorded as 1.384 in complete chloroplast genomes. F. arudinacea-L. perenne clade was uncovered in all phylogenies. Sequences of rbcL and trnH-psbA regions were not able to resolve the Pooideae phylogenies due to lack of genetic variation.

Keywords: chloroplast DNA, Pooideae, phylogenetic analysis, rbcL, trnH-psbA

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Authors: Somayeh Akrami, Habib Onsori, Elham Tahmassebian

Abstract:

Species of Anemone narcissiflora is belonged to Anemone genus of Ranunculaceae family. This species has two subspecies named narcissiflora and willdenowii which the latest is recorded in Iran in 2010. Some samples of A. narcissiflora is gathered from kuhkamar-zonouz region of East -Azerbaijan province, Iran to study the genetic diversity of the species by using RAPD molecular markers, and estimation of genetic diversity were evaluated with the using 10mer RAPD primers by PCR-RAPD method. 39 polymorphic bands were produced from the six primers used in this technique that the maximum band is related to the RP1 primer, the lowest band is related to the RP7 and the average band for all primers were 6.5 polymorphic bands. Cluster analysis of samples in done by UPGMA method in NTSYSpc 2.02 software. Dendrogram resulting from migrating bands showed that the studied samples can be divided into two groups. The first group includes samples with 1-2 flowers and the second group consists of two sub-groups which the first subgroup consists of samples with 3-5 flowers, and the second subgroup consists of samples with 6-7 flowers. The results of the comparison and analysis of the data obtained from RAPD technique and similarity matrix represents the genetic variation between collected samples. This study shows that RAPD markers can determine the polymorphisms between different genotypes of A. narcissiflora and their hybrids. So RAPD technique can serve as a suitable molecular method to determine the genetic diversity of samples.

Keywords: Anemone narcissiflora, genetic diversity, RAPD-PCR

Procedia PDF Downloads 449

Authors: Yong-Kyu Jung

Abstract:

The fast growth in information technology has led to de-mands to access/process data. CPSs heavily depend on the time of hardware/software operations and communication over the network (i.e., real-time/parallel operations in CPSs (e.g., autonomous vehicles). Since data processing is an im-portant means to overcome the issue confronting data management, reducing the gap between the technological-growth and the data-complexity and channel-bandwidth. An adaptive perpetual data approximation method is intro-duced to manage the actual entropy of the digital spectrum. An ADAC implemented as an accelerator and/or apps for servers/smart-connected devices adaptively rescales digital contents (avg.62.8%), data processing/access time/energy, encryption/decryption overheads in AI/ML applications (facial ID/recognition).

Keywords: adaptive codec, AI, ML, HPC, cyber-physical, cybersecurity

Procedia PDF Downloads 50

Authors: Ibrahim Ozkan

Abstract:

In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.

Keywords: cooperative network, adaptive modulation and coding, hybrid ARQ, correlated fading

Procedia PDF Downloads 110