Search results for: predictive velocity rate

Authors: Takashi Shimizu, Tomoaki Hashimoto

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Controlling the flow of fluids is a challenging problem that arises in many fields. Burgers’ equation is a fundamental equation for several flow phenomena such as traffic, shock waves, and turbulence. The optimal feedback control method, so-called model predictive control, has been proposed for Burgers’ equation. However, the model predictive control method is inapplicable to systems whose all state variables are not exactly known. In practical point of view, it is unusual that all the state variables of systems are exactly known, because the state variables of systems are measured through output sensors and limited parts of them can be only available. In fact, it is usual that flow velocities of fluid systems cannot be measured for all spatial domains. Hence, any practical feedback controller for fluid systems must incorporate some type of state estimator. To apply the model predictive control to the fluid systems described by Burgers’ equation, it is needed to establish a state estimation method for Burgers’ equation with limited measurable state variables. To this purpose, we apply unscented Kalman filter for estimating the state variables of fluid systems described by Burgers’ equation. The objective of this study is to establish a state estimation method based on unscented Kalman filter for Burgers’ equation. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: observer systems, unscented Kalman filter, nonlinear systems, Burgers' equation

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Authors: Nima Pirhadi, Yong Bo Shao, Xusheng Wa, Jianguo Lu

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Several models based on the simplified method introduced by Seed and Idriss (1971) have been developed to assess the liquefaction potential of saturated sandy soils. The procedure includes determining the cyclic resistance of the soil as the cyclic resistance ratio (CRR) and comparing it with earthquake loads as cyclic stress ratio (CSR). Of all methods to determine CRR, the methods using shear-wave velocity (Vs) are common because of their low sensitivity to the penetration resistance reduction caused by fine content (FC). To evaluate the capability of the models, based on the Vs., the new data from Bachu-Jianshi earthquake case history collected, then the prediction results of the models are compared to the measured results; consequently, the accuracy of the models are discussed via three criteria and graphs. The evaluation demonstrates reasonable accuracy of the models in the Banchu region.

Keywords: seismic liquefaction, banchu-jiashi earthquake, shear-wave velocity, liquefaction potential evaluation

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Authors: Elena B. Cherepetskaya, Alexander A.Karabutov, Vladimir A. Makarov, Elena A. Mironova, Ivan A. Shibaev

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In our study, the object of laser ultrasonic testing was plane-parallel plate of shungit (length 41 mm, width 31 mm, height 15 mm, medium exchange density 2247 kg/m3). We used laser-ultrasonic defectoscope with wideband opto-acoustic transducer in our investigation of the velocities of longitudinal and shear elastic ultrasound waves. The duration of arising elastic pulses was less than 100 ns. Under known material thickness, the values of the velocities were determined by the time delay of the pulses reflected from the bottom surface of the sample with respect to reference pulses. The accuracy of measurement was 0.3% in the case of longitudinal wave velocity and 0.5% in the case of shear wave velocity (scanning pitch along the surface was 2 mm). On the base of found velocities of elastic waves, local elastic moduli of shungit (Young modulus, shear modulus and Poisson's ratio) were uniquely determined.

Keywords: laser ultrasonic testing , local elastic moduli, shear wave velocity, shungit

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Authors: Ayoub El Bourtali, Abdessamed Najine, Amrou Moussa Benmoussa

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It is becoming more and more necessary to manage flood risk, and it must include all stakeholders and all possible means available. The goal of this work is to map the vulnerability of the Oued Derna-region Tagzirt flood zone in the semi-arid region. This is about implementing predictive models and flood control. This allows for the development of flood risk prevention plans. In this study, A resistivity survey was conducted over the area to locate and evaluate soil characteristics in order to calculate discharges and prevent flooding for the study area. The development of a one-dimensional (1D) hydrodynamic model of the Derna River was carried out in HEC-RAS 5.0.4 using a combination of survey data and spatially extracted cross-sections and recorded river flows. The study area was hit by several extreme floods, causing a lot of property loss and loss of life. This research focuses on the most recent flood events, based on the collected data, the water level, river flow and river cross-section were analyzed. A set of flood levels were obtained as the outputs of the hydraulic model and the accuracy of the simulated flood levels and velocity.

Keywords: derna river, 1D hydrodynamic model, flood modelling, HEC-RAS 5.0.4

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Amir Reza Radmanesh, Sina Farajzadeh Khosroshahi, Hani Sadr

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The transient catalytic converter performance is governed by complex interactions between exhaust gas flow and the monolithic structure of the catalytic converter. Stringent emission regulations around the world necessitate the use of highly-efficient catalytic converters in vehicle exhaust systems. Computational fluid dynamics (CFD) is a powerful tool for calculating the flow field inside the catalytic converter. Radial velocity profiles, obtained by a commercial CFD code, present very good agreement with respective experimental results published in the literature. However the applicability of CFD for transient simulations is limited by the high CPU demands. In the present work, Geometric modeling ceramic monolith substrate is done with square shaped channel type of Catalytic converter and it is coated platinum and palladium. This example illustrates the effect of flow distribution on thermal response of a catalytic converter and different gas flow velocities, during the critical phase of catalytic converter warm up.

Keywords: catalytic converter, computational fluid dynamic, porous media, velocity distribution

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Authors: M. Sadique, S. Ainane, Y. F. Yap, P. Rostron, E. Al Hajri

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The presence of sand in production lines in the oil and gas industries causes material degradation due to erosion-corrosion. The material degradation caused by erosion-corrosion in pipelines can result in a high cost of monitoring and maintenance and in major accidents. The process of erosion-corrosion consists of erosion, corrosion, and their interactions. Investigating and understanding how the erosion-corrosion process affects the degradation process in certain materials will allow for a reduction in economic loss and help prevent accidents. In this study, material loss due to erosion-corrosion of mild steel under impingement of sand-laden water at 90˚ impingement angle is investigated using a submerged impingement jet (SIJ) test. In particular, effects of jet velocity and sand loading on TWL due to erosion-corrosion, weight loss due to pure erosion and erosion-corrosion interactions, at a temperature of 29-33 °C in sea water environment (3.5% NaCl), are analyzed. The results show that the velocity and sand loading have a great influence on the removal of materials, and erosion is more dominant under all conditions studied. Changes in the surface characteristics of the specimen after impingement test are also discussed.

Keywords: erosion-corrosion, flow velocity, jet impingement, sand loading

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Authors: Mahesh Gupta

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The main goal in the design of a die for extrusion of a complex profile is to obtain a uniform velocity at the die exit. If the velocity at the exit of an extrusion die is not uniform, the shape of the extrudate profile can change significantly after the polymer exits the die. To rectify the extrudate distortion caused by non-uniform exit velocity, calibrators and sizers are often installed along the extrudate cooling system. Furthermore, the profile shape in calibrators and sizers is sometimes gradually changed to intentionally deform the extrudate to the required final product shape. This is exploited to simplify extrusion die design, because a relatively simple profile at the die exit can be modified to obtain a more complex profile by deforming it in calibrators or sizers. The gradual change in the shape of calibrator or sizer profiles can also be used to extrude slightly different profiles from the same die. In the present work, a combined flow, thermal and structural analysis is used to accurately predict distortion of extrudate profile after the polymer leaves a die. Simulations of the flow and extrudate deformation in two different bilayer coextrusion dies with gradually changing profile shape in successive calibrators and sizers will be presented. The effect of non-uniform exit velocity, cooling shrinkage and shape of sizer profiles on extrudate deformation is included in the simulation. The predicted extrudate shape and layer structure is found to match accurately with those in a coextruded product.

Keywords: coextrusion, extrusion die design, finite element method, polymers

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Authors: Ke Zhang, Yongli Zhu

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Due to rapid load growths in today’s highly electrified societies and the requirement for green energy sources, large-scale wind farm power transmission system is constantly developing. This system is a typical multi-terminal power supply system, whose structure of the network topology of transmission lines is complex. What’s more, it locates in the complex terrain of mountains and grasslands, thus increasing the possibility of transmission line faults and finding the fault location with difficulty after the faults and resulting in an extremely serious phenomenon of abandoning the wind. In order to solve these problems, a fault location method for multi-terminal transmission line based on wind farm characteristics and improved single-ended traveling wave positioning method is proposed. Through studying the zero sequence current characteristics by using the characteristics of the grounding transformer(GT) in the existing large-scale wind farms, it is obtained that the criterion for judging the fault interval of the multi-terminal transmission line. When a ground short-circuit fault occurs, there is only zero sequence current on the path between GT and the fault point. Therefore, the interval where the fault point exists is obtained by determining the path of the zero sequence current. After determining the fault interval, The location of the short-circuit fault point is calculated by the traveling wave method. However, this article uses an improved traveling wave method. It makes the positioning accuracy more accurate by combining the single-ended traveling wave method with double-ended electrical data. What’s more, a method of calculating the traveling wave velocity is deduced according to the above improvements (it is the actual wave velocity in theory). The improvement of the traveling wave velocity calculation method further improves the positioning accuracy. Compared with the traditional positioning method, the average positioning error of this method is reduced by 30%.This method overcomes the shortcomings of the traditional method in poor fault location of wind farm transmission lines. In addition, it is more accurate than the traditional fixed wave velocity method in the calculation of the traveling wave velocity. It can calculate the wave velocity in real time according to the scene and solve the traveling wave velocity can’t be updated with the environment and real-time update. The method is verified in PSCAD/EMTDC.

Keywords: grounding transformer, multi-terminal transmission line, short circuit fault location, traveling wave velocity, wind farm

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Authors: Sahar El-Achkar, Mizan Ahmad

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Poor adaptation of developmental milestones over the lifespan can significantly impact emotional experiences and Satisfaction with Life (SWL) post-retirement. Thus, it is important to understand how adaptive behaviour over the life course can predict emotional experiences. Broadly emotional experiences are either Positive Affect (PA) or Negative Affect (NA). This study sought to explore the impact of successful adaptation of developmental milestones throughout one’s life on emotional experiences and satisfaction with life following retirement. A cross-sectional self-report survey was completed by 132 Australian retirees between the ages 55 and 70 years. Three hierarchical regression models were fitted, controlling for age and gender, to predict PA, NA, and SWL. The full model predicting PA was statistically significant overall, F (8, 121) = 17.97, p < .001, account for 57% of the variability in PA. Industry/Inferiority were significantly predictive of PA. The full model predicting NA was statistically significant overall, F (8, 121) = 12.00, p < .001, accounting for 51% of the variability in NA. Age and Trust/Mistrust were significantly predictive of NA. The full model predicting NA was statistically significant overall, F (8, 121) = 12.00, p < .001, accounting for 51% of the variability in NA. Age and Trust/Mistrust were significantly predictive of NA. The full model predicting SWL, F (8, 121) = 11.05, p < .001, accounting for 45% of the variability in SWL. Trust/Mistrust and Ego Integrity/Despair were significantly predictive of SWL. A sense of industry post-retirement is important in generating PA. These results highlight that individuals presenting with adaptation and identity issues are likely to present with adjustment challenges and unpleasant emotional experiences post-retirement. This supports the importance of identifying and understanding the benefits of successful adaptation and development throughout the lifespan and its significance for the self-concept. Most importantly, the quality of lives of many may be improved, and the future risk of continued poor emotional experiences and SWL post-retirement may be mitigated. Specifically, the clinical implications of these findings are that they support the promotion of successful adaption over the life course and healthy ageing.

Keywords: adaptation, development, negative affect, positive affect, retirement, satisfaction with life

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Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

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The 1MWth PUSPATI TRIGA Reactor (RTP) in Malaysia Nuclear Agency has been operating more than 35 years. The existing core power control is using conventional controller known as Feedback Control Algorithm (FCA). It is technically challenging to keep the core power output always stable and operating within acceptable error bands for the safety demand of the RTP. Currently, the system could be considered unsatisfactory with power tracking performance, yet there is still significant room for improvement. Hence, a new design core power control is very important to improve the current performance in tracking and regulating reactor power by controlling the movement of control rods that suit the demand of highly sensitive of nuclear reactor power control. In this paper, the proposed Model Predictive Control (MPC) law was applied to control the core power. The model for core power control was based on mathematical models of the reactor core, MPC, and control rods selection algorithm. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The proposed MPC was presented in a transfer function model of the reactor core according to perturbations theory. The transfer function model-based predictive control (TFMPC) was developed to design the core power control with predictions based on a T-filter towards the real-time implementation of MPC on hardware. This paper introduces the sensitivity functions for TFMPC feedback loop to reduce the impact on the input actuation signal and demonstrates the behaviour of TFMPC in term of disturbance and noise rejections. The comparisons of both tracking and regulating performance between the conventional controller and TFMPC were made using MATLAB and analysed. In conclusion, the proposed TFMPC has satisfactory performance in tracking and regulating core power for controlling nuclear reactor with high reliability and safety.

Keywords: core power control, model predictive control, PUSPATI TRIGA reactor, TFMPC

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Authors: Ahmed H. Elkholy

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The concept of applying a prescribed oscillation to viscous fluids to aid or increase flow is used to produce a maintenance free pump. Application of this technique to fluids presents unique problems such as physical separation; control of heat and mass transfer in certain industrial applications; and improvement of some fluid process methods. The problem as stated is to obtain the velocity distribution, wall shear stress and energy expended when a pipe containing a stagnant viscous fluid is externally excited by a sinusoidal pulse, one end of the pipe being pinned. On the other hand, the effect of different parameters on the results are presented. Such parameters include fluid viscosity, frequency of oscillations and pipe geometry. It was found that the flow velocity through the pump is maximum at the pipe wall, and it decreases rapidly towards the pipe centerline. The frequency of oscillation should be above a certain value in order to obtain meaningful flow velocity. The amount of energy absorbed in the system is mainly due to pipe wall strain energy, while the fluid pressure and kinetic energies are comparatively small.

Keywords: sinusoidal excitation, pump, shear stress, flow

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Authors: Kazumasa Kitazono, Hiroshi Fukuoka, Nao Kuniyoshi, Minoru Yaga, Eri Ueno, Naoaki Fukuda, Toshio Takiya

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The unsteady supersonic jet formed by a shock tube with a small high-pressure chamber was used as a simple alternative model for pulsed laser ablation. Understanding the vortex ring formed by the shock wave is crucial in clarifying the behavior of unsteady supersonic jet discharged from an elliptical cell. Therefore, this study investigated the behavior of vortex rings and a jet. The experiment and numerical calculation were conducted using the schlieren method and by solving the axisymmetric two-dimensional compressible Navier–Stokes equations, respectively. In both, the calculation and the experiment, laser ablation is conducted for a certain duration, followed by discharge through the exit. Moreover, a parametric study was performed to demonstrate the effect of pressure ratio on the interaction among vortex rings and the supersonic jet. The interaction between the supersonic jet and the vortex rings increased the velocity of the supersonic jet up to the magnitude of the velocity at the center of the vortex rings. The interaction between the vortex rings increased the velocity at the center of the vortex ring.

Keywords: computational fluid dynamics, shock-wave, unsteady jet, vortex ring

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Authors: Lee P. Leon, Raymond Charles

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This paper presents a method of evaluating the effect of aggregate angularity on hot mix asphalt (HMA) properties and its relationship to the Permanent Deformation resistance. The research concluded that aggregate particle angularity had a significant effect on the Permanent Deformation performance, and also that with an increase in coarse aggregate angularity there was an increase in the resistance of mixes to Permanent Deformation. A comparison between the measured data and predictive data of permanent deformation predictive models showed the limits of existing prediction models. The numerical analysis described the permanent deformation zones and concluded that angularity has an effect of the onset of these zones. Prediction of permanent deformation help road agencies and by extension economists and engineers determine the best approach for maintenance, rehabilitation, and new construction works of the road infrastructure.

Keywords: aggregate angularity, asphalt concrete, permanent deformation, rutting prediction

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Authors: Satpal Yadav, Ashish Phulkar, Krishna K. Sahu

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Aim: The research aims at doing a 3 Dimension biomechanical analysis in the shot put techniques of International throwers to evaluate the performance. Research Method: The researcher adopted the descriptive method and the data was subjected to calculate by using Pearson’s product moment correlation for the correlation of the biomechanical parameters with the performance of shot put throw. In all the analyses, the 5% critical level (p ≤ 0.05) was considered to indicate statistical significance. Research Sample: Eight (N=08) international shot putters using rotational/glide technique in male category was selected as subjects for the study. The researcher used the following methods and tools to obtain reliable measurements the instrument which was used for the purpose of present study namely the tesscorn slow-motion camera, specialized motion analyzer software, 7.260 kg Shot Put (for a male shot-putter) and steel tape. All measurement pertaining to the biomechanical variables was taken by the principal investigator so that data collected for the present study was considered reliable. Results: The finding of the study showed that negative significant relationship between the angular velocity right shoulder, acceleration distance at pre flight (-0.70), (-0.72) respectively were obtained, the angular displacement of knee, angular velocity right shoulder and acceleration distance at flight (0.81), (0.75) and (0.71) respectively were obtained, the angular velocity right shoulder and acceleration distance at transition phase (0.77), (0.79) respectively were obtained and angular displacement of knee, angular velocity right shoulder, release velocity shot, angle of release, height of release, projected distance and measured distance as the values (0.76), (0.77), (-0.83), (-0.79), (-0.77), (0.99) and (1.00) were found higher than the tabulated value at 0.05 level of significance. On the other hand, there exists an insignificant relationship between the performance of shot put and acceleration distance [m], angular displacement shot, C.G at release and horizontal release distance on the technique of shot put.

Keywords: biomechanics, analysis, shot put, international throwers

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Authors: Sumaira Ashraf, Elisabete G.S. Félix, Zélia Serrasqueiro

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Traditional financial distress prediction models performed well to predict bankrupt and insolvent firms of the developed markets. Previous studies particularly focused on the predictability of financial distress, financial failure, and bankruptcy of firms. This paper contributes to the literature by extending the definition of financial distress with the inclusion of early warning signs related to quotation of face value, dividend/bonus declaration, annual general meeting, and listing fee. The study used five well-known distress prediction models to see if they have the ability to predict early warning signs of financial distress. Results showed that the predictive ability of the models varies over time and decreases specifically for the sample with early warning signs of financial distress. Furthermore, the study checked the differences in the predictive ability of the models with respect to the financial crisis. The results conclude that the predictive ability of the traditional financial distress prediction models decreases for the firms with early warning signs of financial distress and during the time of financial crisis. The study developed a new model comprising significant variables from the five models and one new variable earning response. This new model outperforms the old distress prediction models before, during and after the financial crisis. Thus, it can be used by researchers, organizations and all other concerned parties to indicate early warning signs for the emerging markets.

Keywords: financial distress, emerging market, prediction models, Z-Score, logit analysis, probit model

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Authors: Francesco Pantano, Marta Fogolari, Michele Iuliani, Sonia Simonetti, Silvia Cavaliere, Marco Russano, Fabrizio Citarella, Bruno Vincenzi, Silvia Angeletti, Giuseppe Tonini

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Background: Although immune checkpoint inhibitors (ICIs) have changed the treatment paradigm of non–small cell lung cancer (NSCLC), these drugs fail to elicit durable responses in the majority of NSCLC patients. The gut microbiota, able to regulate immune responsiveness, is emerging as a promising, modifiable target to improve ICIs response rates. Since the oral microbiome has been demonstrated to be the primary source of bacterial microbiota in the lungs, we investigated its composition as a potential predictive biomarker to identify and select patients who could benefit from immunotherapy. Methods: Thirty-five patients with stage IV squamous and non-squamous cell NSCLC eligible for an anti-PD-1/PD-L1 as monotherapy were enrolled. Saliva samples were collected from patients prior to the start of treatment, bacterial DNA was extracted using the QIAamp® DNA Microbiome Kit (QIAGEN) and the 16S rRNA gene was sequenced on a MiSeq sequencing instrument (Illumina). Results: NSCLC patients were dichotomized as “Responders” (partial or complete response) and “Non-Responders” (progressive disease), after 12 weeks of treatment, based on RECIST criteria. A prevalence of the phylum Candidatus Saccharibacteria was found in the 10 responders compared to non-responders (abundance 5% vs 1% respectively; p-value = 1.46 x 10-7; False Discovery Rate (FDR) = 1.02 x 10-6). Moreover, a higher prevalence of Saccharibacteria Genera Incertae Sedis genus (belonging to the Candidatus Saccharibacteria phylum) was observed in "responders" (p-value = 6.01 x 10-7 and FDR = 2.46 x 10-5). Finally, the patients who benefit from immunotherapy showed a significant abundance of TM7 Phylum Sp Oral Clone FR058 strain, member of Saccharibacteria Genera Incertae Sedis genus (p-value = 6.13 x 10-7 and FDR=7.66 x 10-5). Conclusions: These preliminary results showed a significant association between oral microbiota and ICIs response in NSCLC patients. In particular, the higher prevalence of Candidatus Saccharibacteria phylum and TM7 Phylum Sp Oral Clone FR058 strain in responders suggests their potential immunomodulatory role. The study is still ongoing and updated data will be presented at the congress.

Keywords: oral microbiota, immune checkpoint inhibitors, non-small cell lung cancer, predictive biomarker

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Authors: James Ladzekpo

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Background: The urgent need to identify new pharmacological targets for diabetes treatment and prevention has been amplified by the disease's extensive impact on individuals and healthcare systems. A deeper insight into the biological underpinnings of diabetes is crucial for the creation of therapeutic strategies aimed at these biological processes. Current predictive models based on genetic variations fall short of accurately forecasting diabetes. Objectives: Our study aims to pinpoint key epigenetic factors that predispose individuals to diabetes. These factors will inform the development of an advanced predictive model that estimates diabetes risk from genetic profiles, utilizing state-of-the-art statistical and data mining methods. Methodology: We have implemented a recursive feature elimination with cross-validation using the support vector machine (SVM) approach for refined feature selection. Building on this, we developed six machine learning models, including logistic regression, k-Nearest Neighbors (k-NN), Naive Bayes, Random Forest, Gradient Boosting, and Multilayer Perceptron Neural Network, to evaluate their performance. Findings: The Gradient Boosting Classifier excelled, achieving a median recall of 92.17% and outstanding metrics such as area under the receiver operating characteristics curve (AUC) with a median of 68%, alongside median accuracy and precision scores of 76%. Through our machine learning analysis, we identified 31 genes significantly associated with diabetes traits, highlighting their potential as biomarkers and targets for diabetes management strategies. Conclusion: Particularly noteworthy were the Gradient Boosting Classifier and Multilayer Perceptron Neural Network, which demonstrated potential in diabetes outcome prediction. We recommend future investigations to incorporate larger cohorts and a wider array of predictive variables to enhance the models' predictive capabilities.

Keywords: diabetes, machine learning, prediction, biomarkers

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Authors: Leticia Cervantes, Edith Garcia, Oscar Castillo

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At today, there are several control problems where the main objective is to obtain the best control in the study to decrease the error in the application. Many techniques can use to control these problems such as Neural Networks, PID control, Fuzzy Logic, Optimization techniques and many more. In this case, fuzzy logic with fuzzy system and an optimization technique are used to control the case of study. In this case, Ant Lion Optimization is used to optimize a fuzzy system to control the velocity of a simple treadmill. The main objective is to achieve the control of the velocity in the control problem using the ALO optimization. First, a simple fuzzy system was used to control the velocity of the treadmill it has two inputs (error and error change) and one output (desired speed), then results were obtained but to decrease the error the ALO optimization was developed to optimize the fuzzy system of the treadmill. Having the optimization, the simulation was performed, and results can prove that using the ALO optimization the control of the velocity was better than a conventional fuzzy system. This paper describes some basic concepts to help to understand the idea in this work, the methodology of the investigation (control problem, fuzzy system design, optimization), the results are presented and the optimization is used for the fuzzy system. A comparison between the simple fuzzy system and the optimized fuzzy systems are presented where it can be proving the optimization improved the control with good results the major findings of the study is that ALO optimization is a good alternative to improve the control because it helped to decrease the error in control applications even using any control technique to optimized, As a final statement is important to mentioned that the selected methodology was good because the control of the treadmill was improve using the optimization technique.

Keywords: ant lion optimization, control problem, fuzzy control, fuzzy system

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Authors: Jayant Kumar, Aarcha Jayachandran Sasikala, Barry Adrian Shepherd

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Public Distribution System is a flagship welfare programme of the Government of India with both historical and political significance. Targeted at lower sections of society,it is one of the largest supply chain networks in the world. There has been several studies by academics and planning commission about the effectiveness of the system. Our study focuses on applying predictive analytics to aid the central body to keep track of the problem of breach of service level agreement between the two echelons of food supply chain. Each shop breach is leading to a potential additional inventory carrying cost. Thus, through this study, we aim to show that aided with such analytics, the network can be made more cost effective. The methods we illustrate in this study are applicable to other commercial supply chains as well.

Keywords: PDS, analytics, cost effectiveness, Karnataka, inventory cost, service level JEL classification: C53

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Authors: Vahdettin Sariyel, Birol Dag

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In this research, it is aimed to determine the effects of several environmental factors on adaptation and some yield parameters of Saanen goats reared under intensive conditions at a private farm in Konya province. Gestation rate, twins rate and litter size were evaluated as reproductive traits. Gestation rate was determined as 93.8% and 90.5% for 2011 and 2012 years respectively. Twins rate was determined as 59.35 % and 70.00 % for 2011 and 2012 years respectively. Litter size was 1.49 and 1.46 for 2011 and 2012 years respectively. Survival rates of kids from birth to weaning at three months of age were found as 87.74 % and 98.54 % for 2011 and 2012 years respectively.

Keywords: gestation rate, reproduction, saanen, twins rate, vitality

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Authors: Siyamak Sarafraz, Reza Esmaeil Pour, Saeed Jamshidi, Asghar Molaei Dehkordi

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Cutting transport is one of the major problems in directional and extended reach oil and gas wells. Lack of sufficient attention to this issue may bring some troubles such as casing running, stuck pipe, excessive torque and drag, hole pack off, bit wear, decreased the rate of penetration (ROP), increased equivalent circulation density (ECD) and logging. Since it is practically impossible to directly observe the behavior of deep wells, a test setup was designed to investigate cutting transport phenomena. This experimental work carried out to scrutiny behavior of the effective variables in cutting transport. The test setup contained a test section with 17 feet long that made of a 3.28 feet long transparent glass pipe with 3 inch diameter, a storage tank with 100 liters capacity, drill pipe rotation which made of stainless steel with 1.25 inches diameter, pump to circulate drilling fluid, valve to adjust flow rate, bit and a camera to record all events which then converted to RGB images via the Image Processing Toolbox. After preparation of test process, each test performed separately, and weights of the output particles were measured and compared with each other. Observation charts were plotted to assess the behavior of viscosity, flow rate and RPM in inclinations of 0°, 30°, 60° and 90°. RPM was explored with other variables such as flow rate and viscosity in different angles. Also, effect of different flow rate was investigated in directional conditions. To access the precise results, captured image were analyzed to find out bed thickening and particles behave in the annulus. The results of this experimental study demonstrate that drill string rotation helps particles to be suspension and reduce the particle deposition cutting movement increased significantly. By raising fluid velocity, laminar flow converted to turbulence flow in the annulus. Increases in flow rate in horizontal section by considering a lower range of viscosity is more effective and improved cuttings transport performance.

Keywords: cutting transport, directional drilling, flow rate, hole cleaning, pipe rotation

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Authors: Zhidong Zhang, Zhi-Chao Zhang, Georgianna Duarte

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The social problems of early adolescents in Northeast China were examined with the instrument of Achenbach System of Empirically Based Assessment (ASEBA). In this study, the data consisted of 2532 early adolescents. The relevant variables such as sports activities, hobbies, chores and the number of close friends, as independent variables have been included in this study. The stratified sampling method was used to collect data from 2532 participants. The analysis results indicated that sports activities, hobbies, chores and the number of close friends, as predictors can be used in a predictive model, which significantly predict the social problem T-score.

Keywords: social problems, ASEBA, early adolescents, predictive Model

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Authors: Irtaza M. Syed, Kaamran Raahemifar

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This paper presents a model predictive control (MPC) of a utility interactive (UI) single phase inverter (SPI) for a photovoltaic (PV) system at residential/distribution level. The proposed model uses single-phase phase locked loop (PLL) to synchronize SPI with the grid and performs MPC control in a dq reference frame. SPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a full bridge (FB) voltage source inverter (VSI). No PI regulators to tune and carrier and modulating waves are required to produce switching sequence. Instead, the operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a three kW PV system at the input of UI-SPI in Matlab/Simulink. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: phase locked loop, voltage source inverter, single phase inverter, model predictive control, Matlab/Simulink

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Authors: Wei-Neng Wang, Jhy-Yuan Shieh, Jhy-Hwa Chen, Juin-Jen Chang

Abstract:

This paper incorporate tax evasion into a one-sector real business cycle (RBC) model to explores the quantitative interrelations between income tax rate and equilibrium (in)determinacy, and income tax rate is endogenously determined in order to balance the government budget. We find that the level of the effective income tax rate is key factor for equilibrium (in)determinacy, instead of the level of income tax rate in a tax evasion economy. Under an economy with tax evasion, the higher income tax rate is not sufficiently to lead to equilibrium indeterminate, it must combine with a necessary condition which is the lower fraction of tax evasion and that can result in agents' optimistic expectations to become self-fulfilling and sunspot fluctuation more likely to occur. On the other hand, an economy with tax evasion can see its macroeconomy become more stabilize, and a higher fraction of income tax evasion may has a stronger stabilizing effect.

Keywords: tax evasion, balanced-budget rule, equlibirium (in)determinacy, effective income tax rate

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Authors: Jairo Alejandro Fernandez Ortega

Abstract:

Objective: Regarding effects of training velocity on strength in the functional condition of older adults controversy exists. The purpose of this study was to examine the effects of a twelve-week strength training program (PE) performed at high speed (GAV) versus a traditionally executed program (GBV), on functional performance, maximum strength and muscle power in a group of older adult women. Methodology: 86 women aged between 60-81 years participated voluntarily in the study and were assigned randomly to the GAV (three series at 40% 1RM at maximum speed, with maximum losses of 10% speed) or to the GBV (three series with three sets at 70% of 1RM). Both groups performed three weekly trainings. The maximum strength of upper and lower limbs (1RM), prehensile strength, walking speed, maximum power, mean propulsive velocity (MPV) and functional performance (senior fitness test) were evaluated before and after the PE. Results: Significant improvements were observed (p < 0.05) in all the tests in the two groups after the twelve weeks of training. However, the results of GAV were significantly (P < 0.05) higher than those of the GBV, in the tests of agility and dynamic equilibrium, stationary walking, sitting and standing, walking speed over 4 and 6 meters, MPV and peak power. In the tests of maximum strength and prehensile force, the differences were not significant. Conclusion: Strength training performed at high speeds seems to have a better effect on functional performance and muscle power than strength training performed at low speed.

Keywords: power training, resistance exercise, aging, strength, physical performance, high-velocity, resistance training

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Authors: Anamika Sahu

Abstract:

The Himalayas, like many mountainous regions, is susceptible to multiple hazards. In recent times, the frequency of such disasters is continuously increasing due to extreme weather phenomena. These natural hazards are responsible for irreparable human and economic loss. The Indian Himalayas has repeatedly been ruptured by great earthquakes in the past and has the potential for a future large seismic event as it falls under the seismic gap. Damages caused by earthquakes are different in different localities. It is well known that, during earthquakes, damage to the structure is associated with the subsurface conditions and the quality of construction materials. So, for sustainable mountain development, prior estimation of site characterization will be valuable for designing and constructing the space area and for efficient mitigation of the seismic risk. Both geotechnical and geophysical investigation of the subsurface is required to describe the subsurface complexity. In mountainous regions, geophysical methods are gaining popularity as areas can be studied without disturbing the ground surface, and also these methods are time and cost-effective. The MASW method is used to calculate the Vs30. Vs30 is the average shear wave velocity for the top 30m of soil. Shear wave velocity is considered the best stiffness indicator, and the average of shear wave velocity up to 30 m is used in National Earthquake Hazards Reduction Program (NEHRP) provisions (BSSC,1994) and Uniform Building Code (UBC), 1997 classification. Parameters obtained through geotechnical investigation have been integrated with findings obtained through the subsurface geophysical survey. Joint interpretation has been used to establish inter-relationships among mineral constituents, various textural parameters, and unconfined compressive strength (UCS) with shear wave velocity. It is found that results obtained through the MASW method fitted well with the laboratory test. In both conditions, mineral constituents and textural parameters (grain size, grain shape, grain orientation, and degree of interlocking) control the petrophysical and mechanical properties of rocks and the behavior of shear wave velocity.

Keywords: MASW, mechanical, petrophysical, site characterization

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Authors: R. Adwaith, J. Gopinath, Vasantha Kohila B., R. Chandru, Arul Prakash R.

Abstract:

The turbofan engine is a type of air breathing engine that is widely used in aircraft propulsion produces thrust mainly from the mass-flow of air bypassing the engine core. The present research has developed an effective method numerically by increasing the thrust generated from the bypass air. This thrust increase is brought about by heating the walls of the bypass valve from the combustion chamber using convective heat transfer method. It is achieved computationally by the use external heat to enhance the velocity of bypass air of turbofan engines. The bypass valves are either heated externally using multicell tube resistor which convert electricity generated by dynamos into heat or heat is transferred from the combustion chamber. This increases the temperature of the flow in the valves and thereby increase the velocity of the flow that enters the nozzle of the engine. As a result, mass-flow of air passing the core engine for producing more thrust can be significantly reduced thereby saving considerable amount of Jet fuel. Numerical analysis has been carried out on a scaled down version of a typical turbofan bypass valve, where the valve wall temperature has been increased to 700 Kelvin. It is observed from the analysis that, the exit velocity contributing to thrust has significantly increased by 10 % due to the heating of by-pass valve. The degree of optimum increase in the temperature, and the corresponding effect in the increase of jet velocity is calculated to determine the operating temperature range for efficient increase in velocity. The technique used in the research increases the thrust by using heated by-pass air without extracting much work from the fuel and thus improve the efficiency of existing turbofan engines. Dimensional analysis has been carried to prove the accuracy of the results obtained numerically.

Keywords: turbofan engine, bypass valve, multi-cell tube, convective heat transfer, thrust

Procedia PDF Downloads 337

Authors: Yifu Ding, Vijay Avinash, Malcolm McCulloch

Abstract:

As the proliferation of decentralized energy systems, the UK power system allows small-scale entities such as microgrids (MGs) to tender multiple energy services including energy arbitrage and frequency responses (FRs). However, its operation requires the balance between the uncertain renewable generations and loads in real-time and has to fulfill their provision requirements of contract services continuously during the time window agreed, otherwise it will be penalized for the under-delivered provision. To hedge against risks due to uncertainties and maximize the economic benefits, we propose a stochastic model predictive control (SMPC) framework to optimize its operation for the multi-service provision. Distinguished from previous works, we include a detailed economic-degradation model of the lithium-ion battery to quantify the costs of different service provisions, as well as accurately describe the changing dynamics of the battery. Considering a branch of load and generation scenarios and the battery aging, we formulate a risk-averse cost function using conditional value at risk (CVaR). It aims to achieve the maximum expected net revenue and avoids severe losses. The framework will be performed on a case study of a PV-battery grid-tied microgrid in the UK with real-life data. To highlight its performance, the framework will be compared with the case without the degradation model and the deterministic formulation.

Keywords: model predictive control (MPC), battery degradation, frequency response, microgrids

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Authors: Yu-Jen Chang, Yun Chen, Hei-Lam Wong

Abstract:

The Economic Lot Scheduling Problem (ELSP) is a valuable mathematical model that can support decision-makers to make scheduling decisions. The basic period approach is effective for solving the ELSP. The assumption for applying the basic period approach is that a product must use its maximum production rate to be produced. However, a product can lower its production rate to reduce the average total cost when a facility has extra idle time. The past researches discussed how a product adjusts its production rate under the common cycle approach. To the best of our knowledge, no studies have addressed how a product lowers its production rate under the basic period approach. This research is the first paper to discuss this topic. The research develops a simple fixed rate approach that adjusts the production rate of a product under the basic period approach to solve the ELSP. Our numerical example shows our approach can find a better solution than the traditional basic period approach. Our mathematical model that applies the fixed rate approach under the basic period approach can serve as a reference for other related researches.

Keywords: economic lot, basic period, genetic algorithm, fixed rate

Procedia PDF Downloads 541