Search results for: predictive factor

Authors: Erdinc Ozturk, Gizem Akcan

Abstract:

The aim of this study was to determine some psychosocial variables that predict childhood trauma and dissociation in university students. These psychosocial variables were perceived social support, relationship status, gender and life satisfaction. 250 (125 males, 125 females) university students (bachelor, master and postgraduate degree) were enrolled in this study. They were chosen from universities in Istanbul at the education year of 2016-2017. Dissociative Experiences Scale (DES), Childhood Trauma Questionnaire (CTQ), Multidimensional Perceived Social Support Scale, Life Satisfaction Scale and Relationship Scales Questionnaire were used to assess related variables. Demographic information form was given to students in order to have their demographic information. Frequency distribution, multiple linear regression, and t-test analysis were used for statistical analysis. As together, perceived social support, relationship status and life satisfaction were found to have predictive value on trauma among university students. However, as together, these psychosocial variables did not have predictive value on dissociation. Only, trauma and relationship status had significant predictive value on dissociation. Moreover, there was significant difference between males and females in terms of trauma; however, dissociation scores of participants were not significantly different in terms of gender.

Keywords: childhood trauma, dissociation, perceived social support, relationship status, life satisfaction

Procedia PDF Downloads 253

Authors: Ahmed AlNouss, Salim Ahmed

Abstract:

Process control refers to the techniques to control the variables in a process in order to maintain them at their desired values. Advanced process control (APC) is a broad term within the domain of control where it refers to different kinds of process control and control related tools, for example, model predictive control (MPC), statistical process control (SPC), fault detection and classification (FDC) and performance assessment. APC is often used for solving multivariable control problems and model predictive control (MPC) is one of only a few advanced control methods used successfully in industrial control applications. Advanced control is expected to bring many benefits to the plant operation; however, the extent of the benefits is plant specific and the application needs a large investment. This requires an analysis of the expected benefits before the implementation of the control. In a real plant simulation studies are carried out along with some experimentation to determine the improvement in the performance of the plant due to advanced control. In this research, such an exercise is undertaken to realize the needs of APC application. The main objectives of the paper are as follows: (1) To apply MPC to a number of simulations set up to realize the need of MPC by comparing its performance with that of proportional integral derivatives (PID) controllers. (2) To study the effect of controller parameters on control performance. (3) To develop appropriate performance index (PI) to compare the performance of different controller and develop novel idea to present tuning map of a controller. These objectives were achieved by applying PID controller and a special type of MPC which is dynamic matrix control (DMC) on the multi-tanks process simulated in loop-pro. Then the controller performance has been evaluated by changing the controller parameters. This performance was based on special indices related to the difference between set point and process variable in order to compare the both controllers. The same principle was applied for continuous stirred tank heater (CSTH) and continuous stirred tank reactor (CSTR) processes simulated in Matlab. However, in these processes some developed programs were written to evaluate the performance of the PID and MPC controllers. Finally these performance indices along with their controller parameters were plotted using special program called Sigmaplot. As a result, the improvement in the performance of the control loops was quantified using relevant indices to justify the need and importance of advanced process control. Also, it has been approved that, by using appropriate indices, predictive controller can improve the performance of the control loop significantly.

Keywords: advanced process control (APC), control loop, model predictive control (MPC), proportional integral derivatives (PID), performance indices (PI)

Procedia PDF Downloads 383

Authors: Joshi Manisha, Shivaram, Anand Vinekar, Tanya Susan Mathews, Yeshaswini Nagaraj

Abstract:

Retinopathy of prematurity (ROP) is abnormal blood vessel development in the retina of the eye in a premature infant. The principal object of the invention is to provide a technique for detecting demarcation line and ridge detection for a given ROP image that facilitates early detection of ROP in stage 1 and stage 2. The demarcation line is an indicator of Stage 1 of the ROP and the ridge is the hallmark of typically Stage 2 ROP. Thirty Retcam images of Asian Indian infants obtained during routine ROP screening have been used for the analysis. A graphical user interface has been developed to detect demarcation line/ridge and to extract ground truth. This novel algorithm uses multilevel vessel enhancement to enhance tubular structures in the digital ROP images. It has been observed that the orientation of the demarcation line/ridge is normal to the direction of the blood vessels, which is used for the identification of the ridge/ demarcation line. Quantitative analysis has been presented based on gold standard images marked by expert ophthalmologist. Image based analysis has been based on the length and the position of the detected ridge. In image based evaluation, average sensitivity and positive predictive value was found to be 92.30% and 85.71% respectively. In pixel based evaluation, average sensitivity, specificity, positive predictive value and negative predictive value achieved were 60.38%, 99.66%, 52.77% and 99.75% respectively.

Keywords: ROP, ridge, multilevel vessel enhancement, biomedical

Procedia PDF Downloads 367

Authors: Federico Pittino, Thomas Arnold

Abstract:

The shredding of waste materials is a key step in the recycling process towards the circular economy. Industrial shredders for waste processing operate in very harsh operating conditions, leading to the need for frequent maintenance of critical components. Maintenance optimization is particularly important also to increase the machine’s efficiency, thereby reducing the operational costs. In this work, a monitoring system has been developed and deployed on an industrial shredder located at a waste recycling plant in Austria. The machine has been monitored for one year, and methods for predictive maintenance have been developed for two key components: the cutting knives and the drive belt. The large amount of collected data is leveraged by statistical machine learning techniques, thereby not requiring very detailed knowledge of the machine or its live operating conditions. The results show that, despite the wide range of operating conditions, a reliable estimate of the optimal time for maintenance can be derived. Moreover, the trade-off between the cost of maintenance and the increase in power consumption due to the wear state of the monitored components of the machine is investigated. This work proves the benefits of real-time monitoring system for the efficient operation of industrial shredders.

Keywords: predictive maintenance, circular economy, industrial shredder, cost optimization, statistical machine learning

Procedia PDF Downloads 101

Authors: Siti Nurhidayah Naqiah Abdull Rani, Herlina Abdul Rahim

Abstract:

Near infrared (NIR) spectroscopy has always been of great interest in the food and agriculture industries. The development of predictive models has facilitated the estimation process in recent years. In this research, 176 crude palm oil (CPO) samples acquired from Felda Johor Bulker Sdn Bhd were studied. A FOSS NIRSystem was used to tak e absorbance measurements from the sample. The wavelength range for the spectral measurement is taken at 1600nm to 1900nm. Partial Least Square Regression (PLSR) prediction model with 50 optimal number of principal components was implemented to study the relationship between the measured Free Fatty Acid (FFA) values and the measured spectral absorption. PLSR showed predictive ability of FFA values with correlative coefficient (R) of 0.9808 for the training set and 0.9684 for the testing set.

Keywords: palm oil, fatty acid, NIRS, PLSR

Procedia PDF Downloads 182

Authors: Rewadee Watakakosol, Arunya Tuicomepee, Panrapee Suttiwan, Sakkaphat T. Ngamake

Abstract:

Health problems caused by alcohol consumption not only have short-term effects at the time of drinking but also leave long-lasting health conditions. Teenagers who start drinking in their middle-high or high school years or before entering college have higher likelihood to increase their alcohol use and abuse, and they were found to be less healthy compared with their non-drinking peers when entering adulthood. This study aimed to examine factors that predict intention and readiness to reduce and quit alcohol consumption among Thai teenagers. Participants were 826 high-school and vocational school students, most of whom were females (64.4%) with the average age of 16.4 (SD = 0.9) and the average age of first drinking at 13.7 (SD = 2.2). Instruments included the scales that developed based on the Theory of Planned Behaviour theoretical framework. They were the Attitude toward Alcohol Reduction and Cessation Scale, Normative Group and Influence Scale, Perceived Behavioral Control toward Alcohol Reduction and Cessation Scale, Behavioral Intent toward Alcohol Reduction and Cessation Scale, and Readiness to Reduce and Quit Alcohol Consumption Scale. Findings revealed that readiness to reduce / quit alcohol was the most powerful predictive factor (β=. 53, p < .01), followed by attitude of easiness in alcohol reduction and cessation (β=.46, p < .01), perceived behavioral control toward alcohol reduction and cessation (β =.41, p < .01), normative group and influence (β=.15, p < .01), and attitude of being accepted from alcohol reduction and cessation (β = -.12, p < .01), respectively. Attitude of improved health after alcohol reduction and cessation did not show statistically significantly predictive power. All factors significantly predict teenagers’ alcohol reduction and cessation behavior and accounted for 59 percent of total variance of alcohol consumption reduction and cessation.

Keywords: alcohol consumption reduction and cessation, intention, readiness to change, Thai teenagers

Procedia PDF Downloads 307

Authors: Mohsen Mousivand, Hesam Aminpour

Abstract:

Soil slopes are usually located above the groundwater level that are largely unsaturated. It is possible that unsaturated soil of slope has expanded or collapsed as a result of wetting by rain or other factor that this type of soil behavior can cause serious problems including human and financial damage. The main factor causing this difference in behavior of saturated and unsaturated state of soil is matric suction that is created by interface of the soil and water in the soil pores. So far theoretical studies show that matric suction has important effect on the mechanical behavior of soil although the impact of this factor on slope stability has not been studied. This paper presents a numerical study of effect of matric suction on slope stability. The results of the study indicate that safety factor and stability of soil slope increase due to an increasing of matric suction and in view of matric suction leads to more accurate results and safety factor.

Keywords: slope, unsaturated soil, matric suction, stability

Procedia PDF Downloads 302

Authors: Edwin Hidayat, Redi Yulianto, Disi Hanafiah

Abstract:

On the one hand, parameters which are used for determining the number of lane on the new road construction are average annual average daily traffic (AADT) and peak hour factor (K-factor). On the other hand, the value of K-factor listed in the guidelines and manual for road planning in Indonesia is a value of adoption or adaptation from foreign guidelines or manuals. Thus, the value is less suitable for Indonesian condition due to differences in road conditions, vehicle type, and driving behavior. The purpose of this study is to provide an example on how to determine k-factor values at a road segment with particular conditions in north coast road, West Java. The methodology is started with collecting traffic volume data for 24 hours over 365 days using PLATO (Automated Traffic Counter) with the approach of video image processing. Then, the traffic volume data is divided into per hour and analyzed by comparing the peak traffic volume in the 30th hour (or other) with the AADT in the same year. The analysis has resulted that for the 30th peak hour the K-factor is 0.97. This value can be used for planning road geometry or evaluating the road capacity performance for the 4/2D interurban road.

Keywords: road geometry, K-factor, annual average daily traffic, north coast road

Procedia PDF Downloads 134

Authors: Rabiul Islam

Abstract:

The study was in order to assess soil erosion at plot scale Universal Soil Loss Equation (USLE) erosion model and Geographic Information System (GIS) technique have been used for the study 8 plots in Guthrie Corridor Expressway, Selangor, Malaysia. The USLE model estimates an average soil loss soil integrating several factors such as rainfall erosivity factor(R ), Soil erodibility factor (K), slope length and steepness factor (LS), vegetation cover factor as well as conservation practice factor (C &P) and Results shows that the four plots have very low rates of soil loss, i.e. NLDNM, NDNM, PLDM, and NDM having an average soil loss of 0.059, 0.106, 0.386 and 0.372 ton/ha/ year, respectively. The NBNM, PLDNM and NLDM plots had a relatively higher rate of soil loss, with an average of 0.678, 0.757 and 0.493ton/ha/year. Whereas, the NBM is one of the highest rate of soil loss from 0.842 ton/ha/year to maximum 16.466 ton/ha/year. The NBM plot was located at bare the land; hence the magnitude of C factor(C=0.15) was the highest one.

Keywords: USLE model, GIS, Guthrie Corridor Expressway (GCE), Malaysia

Procedia PDF Downloads 497

Authors: Ayesha Waqar Khan, Mariam Altaf, Jamil Ahmad, Shaheen Shahzad

Abstract:

Kidney fibrosis is an anticipated outcome of possibly all types of progressive chronic kidney disease (CKD). Epithelial-mesenchymal transition (EMT) signaling pathway is responsible for production of matrix-producing fibroblasts and myofibroblasts in diseased kidney. In this study, a discrete model of TGF-beta (transforming growth factor) and CTGF (connective tissue growth factor) was constructed using Rene Thomas formalism to investigate renal fibrosis turn over. The kinetic logic proposed by Rene Thomas is a renowned approach for modeling of Biological Regulatory Networks (BRNs). This modeling approach uses a set of constraints which represents the dynamics of the BRN thus analyzing the pathway and predicting critical trajectories that lead to a normal or diseased state. The molecular connection between TGF-beta, Smad 2/3 (transcription factor) phosphorylation and CTGF is modeled using GenoTech. The order of BRN is CTGF, TGF-B, and SMAD3 respectively. The predicted cycle depicts activation of TGF-B (TGF-β) via cleavage of its own pro-domain (0,1,0) and presentation to TGFR-II receptor phosphorylating SMAD3 (Smad2/3) in the state (0,1,1). Later TGF-B is turned off (0,0,1) thereby activating SMAD3 that further stimulates the expression of CTGF in the state (1,0,1) and itself turns off in (1,0,0). Elevated CTGF expression reactivates TGF-B (1,1,0) and the cycle continues. The predicted model has generated one cycle and two steady states. Cyclic behavior in this study represents the diseased state in which all three proteins contribute to renal fibrosis. The proposed model is in accordance with the experimental findings of the existing diseased state. Extended cycle results in enhanced CTGF expression through Smad2/3 and Smad4 translocation in the nucleus. The results suggest that the system converges towards organ fibrogenesis if CTGF remains constructively active along with Smad2/3 and Smad 4 that plays an important role in kidney fibrosis. Therefore, modeling regulatory pathways of kidney fibrosis will escort to the progress of therapeutic tools and real-world useful applications such as predictive and preventive medicine.

Keywords: CTGF, renal fibrosis signaling pathway, system biology, qualitative modeling

Procedia PDF Downloads 151

Authors: Gamal Shiha, Seham Seif, Shahera Etreby, Khaled Zalata, Waleed Samir

Abstract:

Background: Transient Elastography (TE; FibroScan®) is a non-invasive technique to assess liver fibrosis. Aim: To compare TE and liver biopsy in hepatitis C virus (HCV) patients, genotype IV and evaluate the effect of steatosis and schistosomiasis on FibroScan. Methods: The fibrosis stage (METAVIR Score) TE, was assessed in 519 patients. The diagnostic performance of FibroScan is assessed by calculating the area under the receiver operating characteristic curves (AUROCs). Results: The cut-off value of ≥ F2 was 8.55 kPa, ≥ F3 was 10.2 kPa and cirrhosis = F4 was 16.3 kPa. The positive predictive value and negative predictive value were 70.1% and 81.7% for the diagnosis of ≥ F2, 62.6% and 96.22% for F ≥ 3, and 27.7% and 100% for F4. No significant difference between schistosomiasis, steatosis degree and FibroScan measurements. Conclusion: Fibroscan could accurately predict liver fibrosis.

Keywords: chronic hepatitis C, FibroScan, liver biopsy, liver fibrosis

Procedia PDF Downloads 376

Authors: Takashi Shimizu, Tomoaki Hashimoto

Abstract:

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

Procedia PDF Downloads 123

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

Abstract:

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

Procedia PDF Downloads 246

Authors: Subzar Ahmad Bhat, Saraswati Setia, V. K.Sehgal

Abstract:

During the past earthquakes, open ground storey buildings have performed poorly due to the soft storey defect. Indian Standard IS 1893:2002 allows analysis of open ground storey buildings without considering infill stiffness but with a multiplication factor 2.5 in compensation for the stiffness discontinuity. Therefore, the aim of this paper is to check the applicability of the multiplication factor of 2.5 and study behaviour of the structure after the application of the multiplication factor. For this purpose, study is performed on models considering infill stiffness using SAP 2000 (Version 14) by linear static analysis and response spectrum analysis. Total seven models are analysed and designed for the range of multiplication factor ranging from 1.25 to 2.5. The value of multiplication factor equal to 2.5 has been found on the higher side, resulting in increased dimension and percentage of reinforcement without significant enhancement beyond a certain multiplication factor. When the building with OGS is designed for values of MF higher than 1.25 considering infill stiffness soft storey effect shifts from ground storey to first storey. For the analysis of the OGS structure best way to analysis the structure is to analyse it as the frame with stiffness and strength of the infill taken into account. The provision of infill walls in the upper storeys enhances the performance of the structure in terms of displacement and storey drift controls.

Keywords: open ground storey, multiplication factor, IS 1893:2002 provisions, static analysis, response spectrum analysis, infill stiffness, equivalent strut

Procedia PDF Downloads 363

Authors: Jodie Stevenson, Lisa-Marie Emerson, Abigail Millings

Abstract:

Mindfulness has been conceptualized as a dispositional trait, which is different across individuals. Previous research has independently identified both adult attachment orientations and emotion regulation abilities as correlates of dispositional mindfulness. Research has also presented a two-factor model of the relationship between these three constructs. The present study aimed to further develop this model and investigated theses relationships in a sample of 186 participants. Participants completed the Five Factor Mindfulness Questionnaire Short Form (FFMQ-SF), the Experiences in Close Relationships Scale for global attachment (ECR), the Emotion Regulation Questionnaire (ERC), and the Adult Disorganized Attachment scale (ADA). Exploratory factor analysis revealed a 3-factor solution accounting for 59% of the variance across scores on these measures. The first factor accounted for 32% of the variance and loaded highly on attachment and mindfulness subscales. The second factor accounted for 15% of the variance with strong loadings on emotion regulation subscales. The third factor accounted for 12% of the variance with strong loadings on disorganized attachment, and the mindfulness observes subscale. The results further confirm the relationship between attachment, mindfulness, and emotion regulation along with the unique addition of disorganized attachment. The extracted factors will then be used to predict well-being outcomes for an undergraduate student population.

Keywords: adult attachment, emotion regulation, mindfulness, well-being

Procedia PDF Downloads 352

Authors: Sahar El-Achkar, Mizan Ahmad

Abstract:

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

Procedia PDF Downloads 48

Authors: Mohd Sabri Minhat, Nurul Adilla Mohd Subha

Abstract:

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

Procedia PDF Downloads 214

Authors: Seyed Abolhassan Naeini, Azam Kouhpeyma

Abstract:

Reduction of water level at which a slope is submerged with it is called drawdown. Draw down can took place rapidly or slowly and in both situations, it can affect slope stability. Using coupled analysis (seepage and stability analysis) causes more accurate results. In this study, the stability of homogeneous embankment is investigated numerically. Slope safety factor changes due to changes in three factors of height, slope and drawdown rate have been investigated and compared. It was found that with increasing height and slope, the safety factor decreases, and with increasing the discharge rate, the safety factor increases.

Keywords: drawdown, slope stability, coupled seepage and stability analysis

Procedia PDF Downloads 91

Authors: Lee P. Leon, Raymond Charles

Abstract:

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

Procedia PDF Downloads 370

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

Abstract:

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

Procedia PDF Downloads 219

Authors: James Ladzekpo

Abstract:

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

Procedia PDF Downloads 24

Authors: Leo Carlo B. Rondina

Abstract:

Self-image is an important factor to improve the self-esteem of the personnel. The purpose of the study is to determine the self-image of the police. The respondents were the 503 policemen assigned in different Police Station in Davao City, and they were chosen with the used of random sampling. With the used of Exploratory Factor Analysis (EFA), latent construct variables of police image were identified as follows; professionalism, obedience, morality and justice and fairness. Further, ordinal regression indicates statistical characteristics on ages 21-40 which means the age of the respondent statistically improves self-image.

Keywords: police image, exploratory factor analysis, ordinal regression, Galatea effect

Procedia PDF Downloads 255

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

Abstract:

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

Procedia PDF Downloads 501

Authors: Sherif Sabri, Suzy Fawzi, Sanaa Abdelshafy, Ayman Nagah

Abstract:

Introduction: Static derangements in lactate homeostasis during ICU stay have become established as a clinically useful marker of increased risk of hospital and ICU mortality. Lactate indices or kinetic alteration of the anaerobic metabolism make it a potential parameter to evaluate disease severity and intervention adequacy. This is an inexpensive and simple clinical parameter that can be obtained by a minimally invasive means. Aim of work: Comparing the predictive value of dynamic indices of hyperlactatemia in the first twenty four hours of intensive care unit (ICU) admission with other static values are more commonly used. Patients and Methods: This study included 40 critically ill patients above 18 years old of both sexes with Hyperlactamia (≥ 2 m mol/L). Patients were divided into septic group (n=20) and low oxygen transport group (n=20), which include all causes of low-O2. Six lactate indices specifically relating to the first 24 hours of ICU admission were considered, three static indices and three dynamic indices. Results: There were no statistically significant differences among the two groups regarding age, most of the laboratory results including ABG and the need for mechanical ventilation. Admission lactate was significantly higher in low-oxygen transport group than the septic group [37.5±11.4 versus 30.6±7.8 P-value 0.034]. Maximum lactate was significantly higher in low-oxygen transport group than the septic group P-value (0.044). On the other hand absolute lactate (mg) was higher in septic group P-value (< 0.001). Percentage change of lactate was higher in the septic group (47.8±11.3) than the low-oxygen transport group (26.1±12.6) with highly significant P-value (< 0.001). Lastly, time weighted lactate was higher in the low-oxygen transport group (1.72±0.81) than the septic group (1.05±0.8) with significant P-value (0.012). There were statistically significant differences regarding lactate indices in survivors and non survivors, whether in septic or low-oxygen transport group. Conclusion: In critically ill patients, time weighted lactate and percent in lactate change in the first 24 hours can be an independent predictive factor in ICU mortality. Also, a rising compared to a falling blood lactate concentration over the first 24 hours can be associated with significant increase in the risk of mortality.

Keywords: critically ill patients, lactate indices, mortality in intensive care, anaerobic metabolism

Procedia PDF Downloads 220

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

Abstract:

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

Procedia PDF Downloads 315

Authors: Irtaza M. Syed, Kaamran Raahemifar

Abstract:

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

Procedia PDF Downloads 501

Authors: Mohamed El-Bady

Abstract:

The Northern Egyptian Lagoons are (from east to west) Bardawil Lagoon, Manzala Lagoon, Burullus Lagoon, Edku Lagoons and Mariute Lagoon. These lagoons have been received the bulk of drainage water from the lands of Delta and from the other coastal areas. Where, the heavy metals can occur in Lagoons environments through a variety of sources, including industries, wastewaters and domestic effluents. The potential ecological risk index (RI) calculation of the bottom sediments of the northern lagoons depends on contamination factor (CF), potential ecological risk factor and proposed toxic response factor (Tr). Each lagoon with special indices according to its conditions.

Keywords: Northern Lagoons, Nile Delta, ecological risk index, contamination factor

Procedia PDF Downloads 313

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

Procedia PDF Downloads 102

Authors: Ayoub Moufid, Najib Bennis, Soumia El Hani

Abstract:

The objective of greenhouse climate control is to improve the culture development and to minimize the production costs. A greenhouse is an open system to external environment and the challenge is to regulate the internal climate despite the strong meteorological disturbances. The internal state of greenhouse considered in this work is defined by too relevant and coupled variables, namely inside temperature and hygrometry. These two variables are chosen to describe the internal state of greenhouses due to their importance in the development of plants and their sensitivity to external climatic conditions, sources of weather disturbances. A multivariable model is proposed and validated by considering a greenhouse as black-box system and the least square method is applied to parameters identification basing on collected experimental measures. To regulate the internal climate, we propose a Model Predictive Control (MPC) scheme. This one considers the measured meteorological disturbances and the physical and operational constraints on the control and state variables. A successful feasibility study of the proposed controller is presented, and simulation results show good performances despite the high interaction between internal and external variables and the strong external meteorological disturbances. The inside temperature and hygrometry are tracking nearly the desired trajectories. A comparison study with an On/Off control applied to the same greenhouse confirms the efficiency of the MPC approach to inside climate control.

Keywords: climate control, constraints, identification, greenhouse, model predictive control, optimization

Procedia PDF Downloads 187

Authors: Dongheon Shin, Kyungnam Ko, Jongchul Huh

Abstract:

The investigation on wind turbine degradation was carried out using the nacelle wind data. The three Vestas V80-2MW wind turbines of Sungsan wind farm in Jeju Island, South Korea were selected for this work. The SCADA data of the wind farm for five years were analyzed to draw power curve of the turbines. It is assumed that the wind distribution is the Rayleigh distribution to calculate the normalized capacity factor based on the drawn power curve of the three wind turbines for each year. The result showed that the reduction of power output from the three wind turbines occurred every year and the normalized capacity factor decreased to 0.12%/year on average.

Keywords: wind energy, power curve, capacity factor, annual energy production

Procedia PDF Downloads 407