Search results for: nonlinear experimental data

Authors: Alessandro Marzucchini, Yie Sue Chua, Andrew Lian, Richard Shonn Mills

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A unique, fast and easy installed inter-module connection named Candle-Loc was developed and applied in several high-rise steel and reinforced concrete modular buildings in Singapore and Hong Kong, China. However, its effect on the global behaviour of modular buildings in high seismic zones was not studied. Therefore, the design concept and the structural performance of each component in this connection was investigated through analytical approach. Response spectrum, linear time-history, and nonlinear time-history analyses were conducted to investigate the effects of the different joint models of the Candle-Loc in the global analysis of high-rise buildings under high seismic loads. It is found that it is important to assess the level of plasticity developed in the inter-module connection under high seismic loads. The ductility of the lateral force resisting system influences the amount of load taken by the inter-module connections.

Keywords: high-rise, inter-module connection, nonlinear, seismic, time-history analysis

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Authors: Samad Lotfollahzadeh

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Escherichia coli (E.coli) is the most isolated bacteria from blood circulation of septicemic calves. Given the prevalence of septicemia in animals and its economic importance in veterinary practice, better understanding of changes in clinical signs following disease, may contribute to early detection of the disorder. The present study has been carried out to detect changes of clinical signs in induced sepsis in calves with E.coli. Colisepticemia has been induced in 10 twenty-day old healthy Holstein- Frisian calves with intravenous injection of 1.5 X 109 colony forming units (cfu) of O111: H8 strain of E.coli. Clinical signs including rectal temperature, heart rate, respiratory rate, shock, appetite, sucking reflex, feces consistency, general behavior, dehydration and standing ability were recorded in experimental calves during 24 hours after induction of colisepticemia. Blood culture was also carried out from calves four times during the experiment. ANOVA with repeated measure is used to see changes of calves’ clinical signs to experimental colisepticemia, and values of P≤ 0.05 was considered statistically significant. Mean values of rectal temperature and heart rate as well as median values of respiratory rate, appetite, suckling reflex, standing ability and feces consistency of experimental calves increased significantly during the study (P<0.05). In the present study, median value of shock score was not significantly increased in experimental calves (P> 0.05). The results of present study showed that total score of clinical signs in calves with experimental colisepticemia increased significantly, although the score of some clinical signs such as shock did not change significantly.

Keywords: calves, clinical signs scoring, E. coli O111:H8, experimental colisepticemia

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Authors: Parimalah Velo, Ahmad Zakaria

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Introduction: Monte Carlo simulations of preclinical imaging systems allow opportunity to enable new research that could range from designing hardware up to discovery of new imaging application. The simulation system which could accurately model an imaging modality provides a platform for imaging developments that might be inconvenient in physical experiment systems due to the expense, unnecessary radiation exposures and technological difficulties. The aim of present study is to validate the Monte Carlo simulation of thyroid phantom imaging using Geant4-GATE for Siemen’s e-cam single head gamma camera. Upon the validation of the gamma camera simulation model by comparing physical characteristic such as energy resolution, spatial resolution, sensitivity, and dead time, the GATE simulation of thyroid phantom imaging is carried out. Methods: A thyroid phantom is defined geometrically which comprises of 2 lobes with 80mm in diameter, 1 hot spot, and 3 cold spots. This geometry accurately resembling the actual dimensions of thyroid phantom. A planar image of 500k counts with 128x128 matrix size was acquired using simulation model and in actual experimental setup. Upon image acquisition, quantitative image analysis was performed by investigating the total number of counts in image, the contrast of the image, radioactivity distributions on image and the dimension of hot spot. Algorithm for each quantification is described in detail. The difference in estimated and actual values for both simulation and experimental setup is analyzed for radioactivity distribution and dimension of hot spot. Results: The results show that the difference between contrast level of simulation image and experimental image is within 2%. The difference in the total count between simulation and actual study is 0.4%. The results of activity estimation show that the relative difference between estimated and actual activity for experimental and simulation is 4.62% and 3.03% respectively. The deviation in estimated diameter of hot spot for both simulation and experimental study are similar which is 0.5 pixel. In conclusion, the comparisons show good agreement between the simulation and experimental data.

Keywords: gamma camera, Geant4 application of tomographic emission (GATE), Monte Carlo, thyroid imaging

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Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

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This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

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Authors: Hami Ashraf, Mohammad Heydarnejad

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Introduction: The landscape of cancer treatment has been revolutionized by immunotherapy, offering novel therapeutic avenues for diverse cancer types. Animal models play a pivotal role in the development and elucidation of these therapeutic modalities. Nevertheless, the manifestation of Graft-versus-Host Disease (GVHD) in such models poses significant challenges, muddling the interpretation of experimental data within the ambit of cancer immunotherapy. This study is dedicated to scrutinizing the role of GVHD as a confounding factor in animal models used for cancer immunotherapy, alongside proposing viable strategies to mitigate this complication. Method: Employing a systematic review framework, this study undertakes a comprehensive literature survey including academic journals in PubMed, Embase, and Web of Science databases and conference proceedings to collate pertinent research that delves into the impact of GVHD on animal models in cancer immunotherapy. The acquired studies undergo rigorous analysis and synthesis, aiming to assess the influence of GVHD on experimental results while identifying strategies to alleviate its confounding effects. Results: Findings indicate that GVHD incidence significantly skews the reliability and applicability of experimental outcomes, occasionally leading to erroneous interpretations. The literature surveyed also sheds light on various methodologies under exploration to counteract the GVHD dilemma, thereby bolstering the experimental integrity in this domain. Conclusion: GVHD's presence critically affects both the interpretation and validity of experimental findings, underscoring the imperative for strategies to curtail its confounding impacts. Current research endeavors are oriented towards devising solutions to this issue, aiming to augment the dependability and pertinence of experimental results. It is incumbent upon researchers to diligently consider and adjust for GVHD's effects, thereby enhancing the translational potential of animal model findings to clinical applications and propelling progress in the arena of cancer immunotherapy.

Keywords: graft-versus-host disease, cancer immunotherapy, animal models, preclinical model

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Authors: Mohammad Reza Esmaili

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After the occurrence of blackouts, the most important subject is how fast the electric service is restored. Power system restoration is an immensely complex issue and there should be a plan to be executed within the shortest time period. This plan has three main stages of black start, network reconfiguration and load restoration. In the black start stage, operators and experts may face several problems, for instance, the unsuccessful connection of the long high-voltage transmission line connected to the electrical source. In this situation, the generator may be tripped because of the unsuitable setting of its line charging mode or high absorbed reactive power. In order to solve this problem, the line charging process is defined as a nonlinear programming problem, and it is optimized by using GAMS software in this paper. The optimized process is performed on a grid that includes a 250 MW hydroelectric unit and a 400 KV transmission system. Simulations and field test results show the effectiveness of optimal planning.

Keywords: power system restoration, black start, line charging mode, nonlinear programming

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Authors: Sandeep Sharma, Sarabjit Singh

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As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

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Authors: Shahzad Yousaf, Imran Shafi

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This paper presents a new method for calculation of pressure loss coefficients by use of the artificial neural network (ANN) in tee junctions. Geometry and flow parameters are feed into ANN as the inputs for purpose of training the network. Efficacy of the network is demonstrated by comparison of the experimental and ANN based calculated data of pressure loss coefficients for combining flows in a tee junction. Reynolds numbers ranging from 200 to 14000 and discharge ratios varying from minimum to maximum flow for calculation of pressure loss coefficients have been used. Pressure loss coefficients calculated using ANN are compared to the models from literature used in junction flows. The results achieved after the application of ANN agrees reasonably to the experimental values.

Keywords: artificial neural networks, combining flow, pressure loss coefficients, solar collector tee junctions

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Authors: Yujiang Wu

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As electrical machine (e-machine) power density re-querulents become more stringent in vehicle electrification, mounting a temperature sensor for e-machine stator windings becomes increasingly difficult. This can lead to higher manufacturing costs, complicated harnesses, and reduced reliability. In this paper, we propose a deep-learning method for predicting electric machine winding temperature, which can either replace the sensor entirely or serve as a backup to the existing sensor. We compare the performance of our method, the stateful long short-term memory networks (LSTM) with truncated backpropagation through time (TBTT), with that of linear regression, as well as stateless LSTM with/without residual connection. Our results demonstrate the strength of combining stateful LSTM and TBTT in tackling nonlinear time series prediction problems with long sequence lengths. Additionally, in industrial applications, high-temperature region prediction accuracy is more important because winding temperature sensing is typically used for derating machine power when the temperature is high. To evaluate the performance of our algorithm, we developed a temperature-stratified MSE. We propose a simple but effective data preprocessing trick to improve the high-temperature region prediction accuracy. Our experimental results demonstrate the effectiveness of our proposed method in accurately predicting winding temperature, particularly in high-temperature regions, while also reducing manufacturing costs and improving reliability.

Keywords: deep learning, electrical machine, functional safety, long short-term memory networks (LSTM), thermal management, time series prediction

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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Due to many applications and problems in the fields of plasma physics, geophysics, and other many topics, the interaction between the strain field and the magnetic field has to be considered. Adomian introduced the decomposition method for solving linear and nonlinear functional equations. This method leads to accurate, computable, approximately convergent solutions of linear and nonlinear partial and ordinary differential equations even the equations with variable coefficients. This paper is dealing with a mathematical model of generalized thermoelasticity of a half-space conducting medium. A magnetic field with constant intensity acts normal to the bounding plane has been assumed. Adomian’s decomposition method has been used to solve the model when the bounding plane is taken to be traction free and thermally loaded by harmonic heating. The numerical results for the temperature increment, the stress, the strain, the displacement, the induced magnetic, and the electric fields have been represented in figures. The magnetic field, the relaxation time, and the angular thermal load have significant effects on all the studied fields.

Keywords: Adomian’s decomposition method, magneto-thermoelasticity, finite conductivity, iteration method, thermal load

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Authors: Akintunde O. Osibamowo, Abdulrasaq O. Olusanya

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The present study was designed to examine the effect of problem-solving approach as a medium of instruction in teaching and learning of mathematics to improve the achievement of the student. One Hundred (100) students were randomly chosen from five (5) Junior Secondary School in Ijebu-Ode Local Government Area of Ogun State, Nigeria. The data was collected through Mathematics Achievement Test (MAT) on the two groups (experimental and control group). The study confirmed that there is a significant different in the achievement of students exposed to problem-solving approach than those not exposed. The result also indicated that male students, however, had a greater mean-score than the female with no significant difference in their achievement. The result of the study supports the use of problem-solving approach in the teaching and learning of mathematics in secondary schools.

Keywords: problem, achievement, teaching phases, experimental control

Procedia PDF Downloads 279

Authors: G. M. Contessa, L. Lepore, G. Gandolfo, C. Poggi, N. Cherubini, R. Remetti, S. Sandri

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Practical guidelines are provided in this work for the safe use of a portable d-t Thermo Scientific MP-320 neutron generator producing pulsed 14.1 MeV neutron beams. The neutron generator’s emission was tested experimentally and reproduced by MCNPX Monte Carlo code. Simulations were particularly accurate, even generator’s internal components were reproduced on the basis of ad-hoc collected X-ray radiographic images. Measurement campaigns were conducted under different standard experimental conditions using an LB 6411 neutron detector properly calibrated at three different energies, and comparing simulated and experimental data. In order to estimate the dose to the operator vs. the operating conditions and the energy spectrum, the most appropriate value of the conversion factor between neutron fluence and ambient dose equivalent has been identified, taking into account both direct and scattered components. The results of the simulations show that, in real situations, when there is no information about the neutron spectrum at the point where the dose has to be evaluated, it is possible - and in any case conservative - to convert the measured value of the count rate by means of the conversion factor corresponding to 14 MeV energy. This outcome has a general value when using this type of generator, enabling a more accurate design of experimental activities in different setups. The increasingly widespread use of this type of device for industrial and medical applications makes the results of this work of interest in different situations, especially as a support for the definition of appropriate radiation protection procedures and, in general, for risk analysis.

Keywords: instrumentation and monitoring, management of radiological safety, measurement of individual dose, radiation protection of workers

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Authors: Omid Khandel, Azadeh Parvin

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An increase in accidental explosions in recent years has increased the interest on investigating the response and behavior of structures in more details. The present work focused on finite element analysis of multistory steel frame structures with different plan shapes subjected to blast loadings. In order to study the effect of the geometry of the building, three different shapes for the plan of the building were modeled and studied; Rectangular, Square and L shape plans. The nonlinear dynamic analysis was considered in this study. The relocation technique was also used to improve the behavior of structure. The accuracy of the multistory frame model was confirmed with those of the existing study in the literature and they were in good agreement. The effect of span length of the buildings was also considered. Finite element analysis of various scenarios for relocating the plastic hinges and improving the response of the structure was performed. The base shear versus displacement curves were compared to reveal the best possible scenarios to provide recommendations to designers and practitioners.

Keywords: nonlinear dynamic analysis, plastic hinge relocation, Retrofit, SAP2000

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Authors: P. Bharathiraja

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Computer Aided decision making system is used to enhance diagnosis and prognosis of diseases and also to assist clinicians and junior doctors in clinical decision making. Medical Data used for decision making should be definite and consistent. Data Mining and soft computing techniques are used for cleaning the data and for incorporating human reasoning in decision making systems. Fuzzy rule based inference technique can be used for classification in order to incorporate human reasoning in the decision making process. In this work, missing values are imputed using the mean or mode of the attribute. The data are normalized using min-ma normalization to improve the design and efficiency of the fuzzy inference system. The fuzzy inference system is used to handle the uncertainties that exist in the medical data. Equal-width-partitioning is used to partition the attribute values into appropriate fuzzy intervals. Fuzzy rules are generated using Class Based Associative rule mining algorithm. The system is trained and tested using heart disease data set from the University of California at Irvine (UCI) Machine Learning Repository. The data was split using a hold out approach into training and testing data. From the experimental results it can be inferred that classification using fuzzy inference system performs better than trivial IF-THEN rule based classification approaches. Furthermore it is observed that the use of fuzzy logic and fuzzy inference mechanism handles uncertainty and also resembles human decision making. The system can be used in the absence of a clinical expert to assist junior doctors and clinicians in clinical decision making.

Keywords: decision making, data mining, normalization, fuzzy rule, classification

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Authors: Gholam Reza Mirzaei

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This research aimed to investigate the effectiveness of acceptance and commitment therapy (ACT) in reducing corona disease anxiety in the staff working at Shahid Beheshti Hospital of Shiraz. The current research was a quasi-experimental study having pre-test and post-test with two experimental and control groups. The statistical population of the research included all the staff of Shahid Beheshti Hospital of Shiraz in 2021. From among the statistical population, 30 participants (N =15 in the experimental group and N =15 in the control group) were selected by available sampling. The materials used in the study comprised the Cognitive Emotion Regulation Questionnaire (CERQ) and Corona Disease Anxiety Scale (CDAS). Following data collection, the participants’ scores were analyzed using SPSS 20 at both descriptive (mean and standard deviation) and inferential (analysis of covariance) levels. The results of the analysis of covariance (ANCOVA) showed that acceptance and commitment therapy (ACT) is effective in reducing Corona disease anxiety (mental and physical symptoms) in the staff working at Shahid Beheshti Hospital of Shiraz. The effectiveness of acceptance and commitment therapy (ACT) on reducing mental symptoms was 25.5% and on physical symptoms was 13.8%. The mean scores of the experimental group in the sub-scales of Corona disease anxiety (mental and physical symptoms) in the post-test were lower than the mean scores of the control group.

Keywords: acceptance and commitment therapy, corona disease anxiety, hospital staff, Shiraz

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Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

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Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

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Authors: Canapi Patricia Joy, Canlas Tracy Gabriella, Canseco Teresa, Capistrano Reena Marie, Carandang Vernon, Carbonel Khiara Claudine

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Research problem: The main problem of the study was to determine the effect of Projecting the Reflection of the Individual’s Self-esteem (PRIDE) therapy on the level of self-esteem of physically challenged adolescents. Objectives of the Study: The study determined the effect of PRIDE (Projecting the Reflection of the Individuals Self-esteem) therapy on the level of self-esteem among physically challenged adolescents. Methodology: A quasi-experimental study was used which involved 30 randomly-assigned subjects, 15 in the experimental group and 15 in the control group. The Projecting the reflection of the Individuals’ Self-Esteem (PRDIE) therapy was administered to the experimental group. The researchers utilized the Sorensen Self-Esteem test tool as a pretest and posttest questionnaire and yielded a Cronbach’s alpha of .912. Paired T-test was used to analyze the gathered data. Results: The results showed that after the administration of PRIDE therapy, there was an increase on the level of self-esteem. The experimental group had a value of 3.590, which was significant and meant that the level of self-esteem is significantly increased. On the other hand, the control group, had a value of -2.207 which was also significant, therefore, the level of self esteem significantly decreased. Conclusion: the PRIDE Therapy is effective in increasing the level of self-esteem among physically challenged adolescent. Recommendations: The researchers recommend the use of PRIDE Therapy as an intervention in handling physically challenged patients, especially adolescents, in order to enhance their self-esteem. Also, the researchers recommend that nursing students be informed on the efficacy of PRIDE Therapy in enhancing the self-esteem of physically challenged patients. Furthermore, the inclusion of a psychologist during the implementation of PRIDE Therapy, specifically art therapy, to be able to have a more focused interpretation of the drawings and really be able to see the projection of their self-esteem is also recommended.

Keywords: adolescents, PRIDE therapy, physically challenged, self-esteem

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Authors: Najmeh Mohsenifar, Narjes Mohsenifar, Abbas Kargar

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In this paper, has been presented a stable method for predicting the ECG signals through the RBF neural networks, by the PSO algorithm. In spite of quasi-periodic ECG signal from a healthy person, there are distortions in electro cardiographic data for a patient. Therefore, there is no precise mathematical model for prediction. Here, we have exploited neural networks that are capable of complicated nonlinear mapping. Although the architecture and spread of RBF networks are usually selected through trial and error, the PSO algorithm has been used for choosing the best neural network. In this way, 2 second of a recorded ECG signal is employed to predict duration of 20 second in advance. Our simulations show that PSO algorithm can find the RBF neural network with minimum MSE and the accuracy of the predicted ECG signal is 97 %.

Keywords: electrocardiogram, RBF artificial neural network, PSO algorithm, predict, accuracy

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Authors: Justina I. Reamen

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The study examined the influence of rational emotive therapy on the treatment of substance abuse among Senior Secondary School Students in Makurdi metropolis Benue State Nigeria. This research adopted youth self report scale which was distributed to 1,690 SSS Students drawn from Government day Secondary School Makurdi and Government Model College Makurdi. Afterwards, 200 who were identified to indulge in substance abuse were selected for the study, 100 each from the two schools. 100 were taken as the control group and 100 as the experimental group, (50 of each group from each school). The Rational Emotive Behavior Therapy (REBT) intervention program was presented to the experimental group for seven (7) weeks. The students were taught how to apply REBT’s cognitive, Emotive and Behavioral techniques on their problems. After which post test was conducted to find out the impact of REBT on the treatment of adolescent students with substance abuse problem. GLM repeated measures of ANOVA were used to analyze the data from the study. The study reveals that REBT has positive impact on the treatment of adolescent students that abuse substances in the study area. Between pretest to post-test scores, a significant difference was observed (F=26.939; P=000) in substance abuse where a decrease of 1.12 (pre-10.91, post-9.79) scores was noticed irrespective of the groups. However, when the decrease in substance abuse were analyzed group wise, (experimental control) again significant F value (F=38.782; P=000) was obtained. From the mean scores it is evident that experimental group decreased it means by 2.56 (Pre-10.04 - Post-8.83) scores compared to control group, which changed its scores by only 0.32 scores (pre 11.04 - Post 11.36). Recommendations were made based on the findings of the research.

Keywords: abuse, influence, substance, therapy, treatment

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: dynamic modeling, missing data, mobility, multiple imputation

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Authors: Gokhan Dok, Hakan Ozturk, Aydin Demir

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The behavior of reinforced concrete (RC) members is quite important in RC structures. When evaluating the performance of structures, the nonlinear properties are defined according to the cross sectional behavior of RC members. To be able to determine the behavior of RC members, its cross sectional behavior should be known well. The moment-curvature (MC) relationship is used to represent cross sectional behavior. The MC relationship of RC cross section can be best determined both experimentally and numerically. But, experimental study on RC members is very difficult. The aim of the study is to obtain the MC relationship of RC shear walls. Additionally, it is aimed to determine the parameters which affect MC relationship. While obtaining MC relationship of RC members, XTRACT which can represent robustly the MC relationship is used. Concrete quality, longitudinal and transverse reinforcing ratios, are selected as parameters which affect MC relationship. As a result of the study, curvature ductility and effective flexural stiffness are determined using this parameter. Effective flexural stiffness is compared with the values defined in design codes.

Keywords: moment-curvature, reinforced concrete, shear wall, numerical

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Authors: Sanjay Kumar, Lillie Dewan

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The study of complex dynamic systems has advanced through various scientific approaches with the help of computer modeling. The common design trends in aerospace system design can be applied to quadcopter design. A quadcopter is a nonlinear, under-actuated system with complex aerodynamics parameters and creates challenges that demand new, robust, and effective control approaches. The flight control stability can be improved by planning and tracking the trajectory and reducing the effect of sensors and the operational environment. This paper presents a modern design Simmechanics visual modeling approach for a mechanical model of a quadcopter with three degrees of freedom. The Simmechanics model, considering inertia, mass, and geometric properties of a dynamic system, produces multiple translation and rotation maneuvers. The proportional, integral, and derivative (PID) controller is integrated with the Simmechanics model to follow a predefined quadcopter rotational trajectory for a fixed time interval. The results presented are satisfying. The simulation of the quadcopter control performed operations successfully.

Keywords: nonlinear system, quadcopter model, simscape modelling, proportional-integral-derivative controller

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Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

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Constitutive modelling of material behaviour is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behaviour of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behaviour modelling.

Keywords: genetic algorithm, kinematic hardening, material model, objective function

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: A. D. Susanti, W. B. Sediawan, S. K. Wirawan, Budhijanto, Ritmaleni

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Rice bran oil contains significant amounts of oryzanol, a natural antioxidant that considered has higher antioxidant activity than vitamin E (tocopherol). Oryzanol reviewed has several health properties and interested in pharmacy, nutrition, and cosmetics. For practical usage, isolation and purification would be necessary due to the low concentration of oryzanol in crude rice bran oil (0.9-2.9%). Batch chromatography has proved as a promising process for the oryzanol recovery, but productivity was still low and scale-up processes of industrial interest have not yet been described. In order to improve productivity of batch chromatography, a continuous chromatography design namely Simulated Moving Bed (SMB) concept have been proposed. The SMB concept has interested for continuous commercial scale separation of binary system (oryzanol and rice bran oil), and rice bran oil still obtained as side product. Design of SMB chromatography for oryzanol separation requires quantification of its equilibrium. In this study, equilibrium of oryzanol separation conducted in batch adsorption using silica as the adsorbent and n-hexane/acetone (9:1) as the eluent. Three isotherm models, namely the Henry, Langmuir, and Freundlich equations, have been applied and modified for the experimental data to establish appropriate correlation for each sample. It turned out that the model quantitatively describe the equilibrium experimental data and will directed for design of SMB chromatography.

Keywords: adsorption, equilibrium, oryzanol, rice bran oil, simulated moving bed

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Authors: Hidir S. Nogay

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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: cascaded neural network, internal temperature, inverter, three-phase induction motor

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Authors: Kashif Habib, Zeeshan Ayyub

Abstract:

ZnO voltage dependent resistor was widely used as components of the electrical system for over-voltage protection. It has a wide application prospect in superconducting energy-removal, generator de-excitation, overvoltage protection of electrical & electronics equipment. At present, the research for the application of ZnO voltage dependent resistor stop, it uses just in the field of its nonlinear voltage current characteristic and overvoltage protection areas. There is no further study over the over-voltage breakdown characteristics, such as the combustion phenomena and the measure of the voltage/current when it breakdown, and the affect to its surrounding equipment. It is also a blind spot in its application. So, when we do the feature test of ZnO voltage dependent resistor, we need to design a reasonable test power supply, making the terminal voltage keep for sine wave, simulating the real use of PF voltage in power supply conditions. We put forward the solutions of using inverter to generate a controllable power. The paper mainly focuses on the breakdown characteristic test power supply of nonlinear ZnO voltage dependent resistor. According to the current mature switching power supply technology, we proposed power control system using the inverter as the core. The power mainly realize the sin-voltage output on the condition of three-phase PF-AC input, and 3 control modes (RMS, Peak, Average) of the current output. We choose TMS320F2812M as the control part of the hardware platform. It is used to convert the power from three-phase to a controlled single-phase sin-voltage through a rectifier, filter, and inverter. Design controller produce SPWM, to get the controlled voltage source via appropriate multi-loop control strategy, while execute data acquisition and display, system protection, start logic control, etc. The TMS320F2812M is able to complete the multi-loop control quickly and can be a good completion of the inverter output control.

Keywords: ZnO, multi-loop control, SPWM, non-linear load

Procedia PDF Downloads 315

Authors: Shewangizaw Tesfaye Wolde

Abstract:

The current engineering community has developed a method called performance based seismic design in which we design structures based on predefined performance levels set by the parties. Since we design our structures economically for the maximum actions expected in the life of structures they go beyond their elastic limit, in need of nonlinear analysis. In this paper conventional pushover analysis (nonlinear static analysis) is used for the performance assessment of the case study Reinforced Concrete (RC) Frame building located in Addis Ababa City, Ethiopia where proposed peak ground acceleration value by RADIUS 1999 project and others is more than twice as of EBCS-8:1995 (RADIUS 1999 project) by taking critical planar frame. Fiber beam-column model is used to control material nonlinearity with tension stiffening effect. The reliability of the fiber model and validation of software outputs are checked under verification chapter. Therefore, the aim of this paper is to propose a way for structural performance assessment of existing reinforced concrete frame buildings as well as design check.

Keywords: seismic, performance, fiber model, tension stiffening, reinforced concrete

Procedia PDF Downloads 61

Authors: Mahmoud Nabilu

Abstract:

The present study explored the effect of using Mobile listening applications on developing listening skills by Iranian intermediate EFL learners. Fifty male intermediate English learners whose age range was between 15 and 20, participated in the study. The participants were placed in two groups on the basis of their scores on a placement test. Therefore, the participants of the study were homogenized in terms of general proficiency, and groups were assigned as one experimental group and one control group. The experimental group was instructed by the treatment which was using mobile applications to develop their listening skills while the control group received traditional methods. The research data were obtained from the 40-item multiple-choice tests as a pre-test and a post-test. The results of the t-test clearly revealed that the learners in the experimental group performed better in the post-test than the pre-test. This implies that using a mobile application for developing listening skills as a treatment was effective in helping the language learners perform better on post-test. However, a statistically significant difference was found between the post-tests scores of the two groups. The mean of the experimental group was greater compared to the control group. The participants were Iranian and from an Iranian Language Institute, so care should be taken while generalizing the results to the learners of other nationalities. However, in the researcher's view, the findings of this study have valuable implications for teachers and learners, methodologists and syllabus designers, linguists and MALL/CALL (mobile/computer-assisted language learning) experts. Using the result of the present paper is an aim of raising the consciousness of a better technique of developing listening skills in order to make language learning more efficient for the learners.

Keywords: Mobile listening applications, intermediate EFL learners, MALL, CALL

Procedia PDF Downloads 188

Authors: M. Hakan Arslan, I. Hakkı Erkan

Abstract:

Overstrength factor is an important parameter of load reduction factor. In this research, the overstrength factor (Ω) of reinforced concrete (RC) buildings and the parameters of Ω in TEC-2016 draft version have been explored. For this aim, 48 RC buildings have been modeled according to the current seismic code TEC-2007 and Turkish Building Code-500-2000 criteria. After modelling step, nonlinear static pushover analyses have been applied to these buildings by using TEC-2007 Section 7. After the nonlinear pushover analyses, capacity curves (lateral load-lateral top displacement curves) have been plotted for 48 RC buildings. Using capacity curves, overstrength factors (Ω) have been derived for each building. The obtained overstrength factor (Ω) values have been compared with TEC-2016 values for related building types, and the results have been interpreted. According to the obtained values from the study, overstrength factor (Ω) given in TEC-2016 draft code is found quite suitable.

Keywords: reinforced concrete buildings, overstrength factor, earthquake, static pushover analysis

Procedia PDF Downloads 347