Search results for: component prediction

Authors: Hamza A. Ali, Adnan H. M. Al-Helali

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Generally, a watermark is information that identifies the ownership of multimedia (text, image, audio or video files). It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications are done according to a secret key in a descriptive model that would be either in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.

Keywords: watermarking, ownership, copyright protection, steganography, information hiding, authentication

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Fouzi Harrou, Ying Sun, Sofiane Khadraoui

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Anomaly detection based on Principal Component Analysis (PCA) was studied intensively and largely applied to multivariate processes with highly cross-correlated process variables. Monitoring metrics such as the Hotelling's T2 and the Q statistics are usually used in PCA-based monitoring to elucidate the pattern variations in the principal and residual subspaces, respectively. However, these metrics are ill suited to detect small faults. In this paper, the Exponentially Weighted Moving Average (EWMA) based on the Q and T statistics, T2-EWMA and Q-EWMA, were developed for detecting faults in the process mean. The performance of the proposed methods was compared with that of the conventional PCA-based fault detection method using synthetic data. The results clearly show the benefit and the effectiveness of the proposed methods over the conventional PCA method, especially for detecting small faults in highly correlated multivariate data.

Keywords: data-driven method, process control, anomaly detection, dimensionality reduction

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Authors: S. Guruprasad, M. Z. Kurian, H. N. Suma

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Medical imaging modalities are becoming life saving components. These modalities are very much essential to doctors for proper diagnosis, treatment planning and follow up. Some modalities provide anatomical information such as Computed Tomography (CT), Magnetic Resonance Imaging (MRI), X-rays and some provides only functional information such as Positron Emission Tomography (PET). Therefore, single modality image does not give complete information. This paper presents the fusion of structural information in CT and functional information present in PET image. This fused image is very much essential in detecting the stages and location of abnormalities and in particular very much needed in oncology for improved diagnosis and treatment. We have implemented and compared image fusion techniques like pyramid, wavelet, and principal components fusion methods along with hybrid method of DWT and PCA. The performances of the algorithms are evaluated quantitatively and qualitatively. The system is implemented and tested by using MATLAB software. Based on the MSE, PSNR and ENTROPY analysis, PCA and DWT-PCA methods showed best results over all experiments.

Keywords: image fusion, pyramid, wavelets, principal component analysis

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Authors: Anirudh Bhaikhel

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The exclusive objective of this paper is to develop a device which can pass on the interpreted result of the sensed information to the interfaced communicable devices to avoid or minimise accidents. This device may also be used in case of emergencies like kidnapping, robberies, medical emergencies etc. The present era has seen a rapid metamorphosis in the automobile industry with increasing use of technology and speed. The increase in purchasing power of customers and price war of automobile companies has made an easy access to the automobile users. The use of automobiles has increased tremendously in last 4-5 years thus causing traffic congestions and thus making vehicles more prone to accidents. This device can be an effective measure to counteract cases of abduction. Risks of accidents can be decreased tremendously through the notifications received by these alerts. It will help to detect the upcoming emergencies. This paper includes the simulation of the communication and sensing device required in automobiles using VHDL.

Keywords: automobiles, communication, component, cyclic redundancy check (CRC), modulo-2 arithmetic, parity bits, receiver, sensors, transmitter, turns, VHDL (VHSIC hardware descriptive language)

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Authors: Yadong Liu

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The experimental study on reduction carbonization of coke containing iron respectively with the particle size of <0.3mm, 0.3-0.6mm and 0.6-0.9mm and synthetic sea sand ore smelting reduction titanium-bearing slag as material were studied under the conditions of holding 6h at most at 1500℃. The effects of coke containing iron particle size and heat preservation time on the formation of TiC and the size of TiC crystal were studied by XRD, SEM and EDS. The results show that it is not good for the formation, concentration and growth of TiC crystal when the particle size of coke containing iron is too small or too large. The suitable particle size is 0.3~0.6mm. The heat preservation time of 2h basically ensures that all the component TiO2 in the slag are reduced and carbonized and converted to TiC. The size of TiC crystal will increase with the prolongation of heat preservation time. The thickness of the TiC layer can reach 20μm when the heat preservation time is 6h.

Keywords: coke containing iron, formation and concentration and growth of TiC, reduction and carbonization, titanium-bearing slag

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Authors: Malki Nadia Fatima Zahra, Kellal Chaimaa, Brahimi Houria

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Quality is one of the most important modern management patterns that organizations seek to achieve in all areas and sectors in order to meet the needs and desires of customers and to remain continuity, as they constitute a competitive advantage for the organization, and among the most prominent organizations that must be available on the quality factor are health organizations as they relate to the most valuable component of production It is a person and his health, and that any error in it threatens his life and may lead to death, so she must provide health services of high quality to achieve the highest degree of satisfaction for the patient. This research aims to study the quality of health services and the extent of their impact on patient satisfaction, and this is through an applied study that relied on measuring the level of quality of health services in the university hospital center of Algeria and the extent of their impact on patient satisfaction according to the dimensions of the quality of health services, and we reached a conclusion that the determinants of the quality of health services. It affects patient satisfaction, which necessitates developing health services according to patients' requirements and improving their quality to obtain patient satisfaction.

Keywords: health service, health quality, quality determinants, patient satisfaction

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Authors: Rifqi Alfadhillah Sentosa, Hasbi Fikru Syabi, Stephen

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West Java is a province in Indonesia which has a number of volcanoes. One of those volcanoes is Mt. Ciremai, located administratively at Kuningan and Majalengka District, and is known for its significant geothermal potential in Java Island. This research aims to assume geothermal prospects at Mt. Ciremai using Fault and Fracture Density (FFD) Method, which is correlated to the geochemistry of geothermal manifestations around the mountain. This FFD method is using SRTM data to draw lineaments, which are assumed associated with fractures and faults in the research area. These faults and fractures were assumed as the paths for reservoir fluids to reached surface as geothermal manifestations. The goal of this method is to analyze the density of those lineaments found in the research area. Based on this FFD Method, it is known that area with high density of lineaments located on Mt. Kromong at the northern side of Mt. Ciremai. This prospect area is proven by its higher geothermometer values compared to geothermometer values calculated at the south area of Mt. Ciremai.

Keywords: geothermal prospect, fault and fracture density, Mt. Ciremai, surface manifestation

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Authors: N. Pegahfar, P. Ghafarian

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In this research, the synoptic weather conditions during the heavy flood of 10-12 January 2020 in the Sistan-va-Balouchestan Province of Iran will be analyzed. To this aim, reanalysis data from the National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), NCEP Global Forecasting System (GFS) analysis data, measured data from a surface station together with satellite images from the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) have been used from 9 to 12 January 2020. Atmospheric parameters both at the lower troposphere and also at the upper part of that have been used, including absolute vorticity, wind velocity, temperature, geopotential height, relative humidity, and precipitation. Results indicated that both lower-level and upper-level currents were strong. In addition, the transport of a large amount of humidity from the Oman Sea and the Red Sea to the south and southeast of Iran (Sistan-va-Balouchestan Province) led to the vast and unexpected precipitation and then a heavy flood.

Keywords: Sistan-va-Balouchestn Province, heavy flood, synoptic, analysis data

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Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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Authors: Hesham A. Elkaranshawy, Amr Abdelrazek, Hosam Ezzat

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This paper analyzes a single point rough collision in three dimensional rigid-multibody systems. A set of nonlinear different equations describing the progress and outcome of the impact are obtained. Specifically in case of the tangential, referred to as sliding, component of impact velocity is of great importance. Numerical methods are used to solve this problem. In this work, all these possible sliding behaviors during impact are identified, conditions leading to each behavior are specified, and an appropriate numerical procedure is suggested. A case of a four-degrees-of-freedom spatial robot that collides with its environment is investigated. The phase portrait of the tangential velocity, which presents the flow trajectories for different initial conditions, is calculated. Using the coefficient of friction as a control parameter, few phase portraits are drawn, each for a specific value of this coefficient. In addition, the bifurcation associated with the variation of this coefficient will be investigated.

Keywords: friction impact, three-dimensional rigid multibody systems, sliding velocity, nonlinear ordinary differential equations, phase portrait

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Authors: John A. Morales, Guillermo Guidi, B. M. Keune

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Electric Power supply is a crucial topic for economic and social development. Power outages statistics show that discharges atmospherics are imperative phenomena to produce those outages. In this context, it is necessary to correctly detect when overhead line insulators are faulted. In this paper, an algorithm to detect if a lightning stroke generates or not permanent fault on insulator strings is proposed. On top of that, lightning stroke simulations developed by using the Alternative Transients Program, are used. Based on these insights, a novel approach is designed that depends on mother functions analysis corresponding to the given variance-covariance matrix. Signals registered at the insulator string are projected on corresponding axes by the means of Principal Component Analysis. By exploiting these new axes, it is possible to determine a flashover characteristic zone useful to a good insulation design. The proposed methodology for flashover detection extends the existing approaches for the analysis and study of lightning performance on transmission lines.

Keywords: mother function, outages, lightning, sensitivity analysis

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Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: M. Akhlaque Ahmed, Maliha Afshan

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Solar energy potential of Capital city Islamabad and five major cities Peshawar, Lahore, Multan, Quetta and Karachi have been analyzed by using sun shine hour data of the area. Global and diffused solar radiation on horizontal surfaces has been assessed to see the feasibility of solar energy utilization. The result obtained shows 70% direct and 30% diffuse solar radiation for five cities throughout the year except Karachi which shows large variation in direct and diffuse component of solar radiation 57% direct and 43% diffuse in the month of July and August. The cloudiness index were also calculated which lies between 60 to 70% for all the cities except for Karachi which shows 37% clear sky in monsoon month July and August. All the cities show high solar potential throughout the year except Karachi which shows low solar potential during July and August months.

Keywords: global and diffuse solar radiations, Pakistan, power generation, solar potential, sunshine hour

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Authors: A. Boudiaf

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The purpose of this paper is to analyze and apprehend, through four case studies, the interest of the project of the implementation of the quality management system (QMS) at four Moroccan small and medium-sized enterprises (SMEs). This project could generate significant organizational change to improve the functioning of the organization. In fact, quality is becoming a necessity in the current business world. It is considered to be a major component in companies’ competitive strategies. It should be noted that quality management is characterized by a set of methods and techniques that can be used to solve malfunctions and reorganize companies. It is useful to point out that the choice of the adoption of the quality approach could be influenced by the circumstances of the business context, it could also be derived from its strategic vision; this means that this choice can be characterized as either a strategic aspect or a reactive aspect. This would probably have a major impact on the functioning of the QMS and also on the perception of the quality issue by company managers and their employees.

Keywords: business context, organizational change, quality, reorganization

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Authors: Sarra Hasni, Sami Faiz

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In recent years, location prediction on social networks has gained significant attention, with short and unstructured texts like tweets posing additional challenges. Advanced geolocation models have been proposed, increasing the need to explain their predictions. In this paper, we provide explanations for a geolocation black-box model using LIME and SHAP, two state-of-the-art XAI (eXplainable Artificial Intelligence) methods. We extend our evaluations to Large Language Models (LLMs) as post hoc explainers for tweet geolocation. Our preliminary results show that LLMs outperform LIME and SHAP by generating more accurate explanations. Additionally, we demonstrate that prompts with examples and meta-prompts containing phonetic spelling rules improve the interpretability of these models, even with informal input data. This approach highlights the potential of advanced prompt engineering techniques to enhance the effectiveness of black-box models in geolocation tasks on social networks.

Keywords: large language model, post hoc explainer, prompt engineering, local explanation, tweet geolocation

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Authors: Pooree Sakot, Marndarath Suksanga

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Organizations are under increasing pressure to improve performance and maximize the contribution of every employee. Employee engagement has become an attractive business proposition. The triple bottom line consists of three Ps: profit, people and planet. It aims to measure the financial, social and environmental performance of the corporation over a period of time. People are the most important asset of every organization. Most of the studies suggest that employee engagement improves the bottom line in almost every instance and it is well worth all organizational efforts to actively engage employees. Engaged employees have an impact on productivity and financial performance. Efficient leadership and effective management can take place if emerging paradigm like employee engagement is appropriately understood and put into practice. Employee engagement starts at the first step i.e. recruitment of an employee to the last step i.e. retirement .The HR Practices of an organization play the most major role in helping the employees walk the extra mile. Effective employee engagement is the key component for improved organizational performance.

Keywords: employee engagement, higher education, tool, success

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Authors: Tan Yong Sheng Edgar, Yeong Wai Yee

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Age-related macular degeneration (AMD) is one of the leading cause of blindness. It can cause severe visual loss due to damaged retinal pigment epithelium (RPE). RPE is an important component of the retinal tissue. It functions as a transducing boundary for visual perception making it an essential factor for sight. The RPE also functions as a metabolically complex and functional cell layer that is responsible for the local homeostasis and maintenance of the extra photoreceptor environment. Thus one of the suggested method of treating such diseases would be regenerating these RPE cells. As such, we intend to grow these cells using a synthetic scaffold to provide a stable environment that reduces the batch effects found in natural scaffolds. Stiffness of the scaffold will also be investigated to determine the optimal Young’s modulus for cultivating these cells. The cells will be generated into a monolayer cell sheet and their functions such as formation of tight junctions and gene expression patterns will be assessed to evaluate the cell sheet quality compared to a native RPE tissue.

Keywords: RPE, scaffold, characterization, biomaterials, colloids and nanomedicine

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Authors: Jafar Ahmadi, Nafiseh Noormohammadi, Sedegeh Fabriki Ourang

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GRF, Growth regulating factor, genes encode a novel class of plant-specific transcription factors. The GRF proteins play a role in the regulation of cell numbers in young and growing tissues and may act as transcription activations in growth and development of plants. Identification of GRF genes and their expression are important in plants to performance of the growth and development of various organs. In this study, to better understanding the structural and functional differences of GRFs family, 45 GRF proteins sequences in A. thaliana, Z. mays, O. sativa, B. napus, B. rapa, H. vulgare, and S. bicolor, have been collected and analyzed through bioinformatics data mining. As a result, in secondary structure of GRFs, the number of alpha helices was more than beta sheets and in all of them QLQ domains were completely in the biggest alpha helix. In all GRFs, QLQ, and WRC domains were completely protected except in AtGRF9. These proteins have no trans-membrane domain and due to have nuclear localization signals act in nuclear and they are component of unstable proteins in the test tube.

Keywords: domain, gene family, GRF, motif

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Authors: Camille A. Issa, Omar Masri

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In the study, the commercial finite element software Abaqus was used to develop a three-dimensional nonlinear finite element model capable of simulating the pull-out test of reinforcing bars from underwater concrete. The results of thirty-two pull-out tests that have different parameters were implemented in the software to study the effect of the concrete cover, the bar size, the use of stirrups, and the compressive strength of concrete. The interaction properties used in the model provided accurate results in comparison with the experimental bond-slip results, thus the model has successfully simulated the pull-out test. The results of the finite element model are used to better understand and visualize the distribution of stresses in each component of the model, and to study the effect of the various parameters used in this study including the role of the stirrups in preventing the stress from reaching to the sides of the specimens.

Keywords: pull-out test, bond strength, underwater concrete, nonlinear finite element analysis, abaqus

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Authors: Punit Kumar, Niraj Kumar

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The traction behavior of lubricants with the linear pressure-viscosity response in EHL line contacts is investigated numerically for smooth as well as rough surfaces. The analysis involves the simultaneous solution of Reynolds, elasticity and energy equations along with the computation of lubricant properties and surface temperatures. The temperature modified Doolittle-Tait equations are used to calculate viscosity and density as functions of fluid pressure and temperature, while Carreau model is used to describe the lubricant rheology. The surface roughness is assumed to be sinusoidal and it is present on the nearly stationary surface in near-pure sliding EHL conjunction. The linear P-V oil is found to yield much lower traction coefficients and slightly thicker EHL films as compared to the synthetic oil for a given set of dimensionless speed and load parameters. Besides, the increase in traction coefficient attributed to surface roughness is much lower for the former case. The present analysis emphasizes the importance of employing realistic pressure-viscosity response for accurate prediction of EHL traction.

Keywords: EHL, linear pressure-viscosity, surface roughness, traction, water/glycol

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Authors: Suvimon Wajeetongratana, Prateep Wajeetongratana

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The purpose of this research will study the organizational behavior including self-efficacy, hope, optimism, and resiliency that affect to the work motivation in the Dusit workplace and the sample consisted of the production workers in a private company in Dusit area for four hundred workers with approximately 10,000 employees and in this study will provide the multiple regression analysis was used to analyze the questionnaire survey data. The results of the analysis indicate the latent core confidence factor derived from the four components of self-efficacy, hope, optimism, and resiliency provided a significant positive impact on performance. The impact of the integrated latent core confidence factor was, in fact, more effective than derived from any one individual component, as well as any core trait-like self-evaluations such as self-esteem, general efficacy, internal locus of control, and emotional stability.

Keywords: firm performance effectiveness, organizational behavior, work motivation, Dusit workplace

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Authors: Erez Kita, Gil Luria

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This study examines gender as a boundary condition for the relationship between the psychological variable of mindfulness and the social variable of income with regards to the use of smartphones by young drivers. The use of smartphones while driving increases the likelihood of a car accident, endangering young drivers and other road users. The study sample included 186 young drivers who were legally permitted to drive without supervision. The subjects were first asked to complete questionnaires on mindfulness and income. Next, their smartphone use while driving was monitored over a one-month period. This study is unique as it used an objective smartphone monitoring application (rather than self-reporting) to count the number of times the young participants actually touched their smartphones while driving. The findings show that gender moderates the effects of social and personal factors (i.e., income and mindfulness) on the use of smartphones while driving. The pattern of moderation was similar for both social and personal factors. For men, mindfulness and income are negatively associated with the use of smartphones while driving. These factors are not related to the use of smartphones by women drivers. Mindfulness and income can be used to identify male populations that are at risk of using smartphones while driving. Interventions that improve mindfulness can be used to reduce the use of smartphones by male drivers.

Keywords: mindfulness, using smartphones while driving, income, gender, young drivers

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Authors: David Aveiga, Carlos Gonzalez

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Thermoforming of pre-impregnated composites (prepreg) is the most employed process to build high-performance composite structures due to their visible advantage over alternative manufacturing techniques. This method allows easy shape moulding with a simple manufacturing system and a more refined outcome. The achievement of complex geometries can be exposed to undesired defects such as wrinkles. It is known that interply and ply-mould sliding behavior governs this defect generation. This work analyses interply and ply-mould friction coefficients for UD AS4/8552 Carbon/Epoxy prepreg. Friction coefficients are determined by a pull-out test method considering actual velocity, pressure and temperature conditions employed in a thermoforming process of an aeronautical composite component. A Stribeck curve is then constructed to find a mathematical expression that relates all the friction coefficients with the test variables through the Hersey number parameter. Two expressions are proposed to model ply-ply and ply-tool friction behaviors.

Keywords: friction, prepreg composite, stribeck curve, thermoforming.

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Authors: Andrew Laming, John Hattie, Mark Wilson

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Nine Queensland Independent high schools provided deidentified student-matched ATAR and NAPLAN data for all 1217 ATAR graduates since 2020 who also sat NAPLAN at the school. Graduating cohorts from the nine schools contained a mean 100 ATAR graduates with previous NAPLAN data from their school. Excluded were vocational students (mean=27) and any ATAR graduates without NAPLAN data (mean=20). Based on Index of Community Socio-Educational Access (ICSEA) prediction, all schools had larger that predicted proportions of their students graduating with ATARs. There were an additional 173 students not releasing their ATARs to their school (14%), requiring this data to be inferred by schools. Gain was established by first converting each student’s strongest NAPLAN domain to a statewide percentile, then subtracting this result from final ATAR. The resulting ‘percentile shift’ was corrected for plausible ATAR participation at each NAPLAN level. Strongest NAPLAN domain had the highest correlation with ATAR (R2=0.58). RESULTS School mean NAPLAN scores fitted ICSEA closely (R2=0.97). Schools achieved a mean cohort gain of two ATAR rankings, but only 66% of students gained. This ranged from 46% of top-NAPLAN decile students gaining, rising to 75% achieving gains outside the top decile. The 54% of top-decile students whose ATAR fell short of prediction lost a mean 4.0 percentiles (or 6.2 percentiles prior to correction for regression to the mean). 71% of students in smaller schools gained, compared to 63% in larger schools. NAPLAN variability in each of the 13 ICSEA1100 cohorts was 17%, with both intra-school and inter-school variation of these values extremely low (0.3% to 1.8%). Mean ATAR change between years in each school was just 1.1 ATAR ranks. This suggests consecutive school cohorts and ICSEA-similar schools share very similar distributions and outcomes over time. Quantile analysis of the NAPLAN/ATAR revealed heteroscedasticity, but splines offered little additional benefit over simple linear regression. The NAPLAN/ATAR R2 was 0.33. DISCUSSION Standardised data like NAPLAN and ATAR offer educators a simple no-cost progression metric to analyse performance in conjunction with their internal test results. Change is expressed in percentiles, or ATAR shift per student, which is layperson intuitive. Findings may also reduce ATAR/vocational stream mismatch, reveal proportions of cohorts meeting or falling short of expectation and demonstrate by how much. Finally, ‘crashed’ ATARs well below expectation are revealed, which schools can reasonably work to minimise. The percentile shift method is neither value-add nor a growth percentile. In the absence of exit NAPLAN testing, this metric is unable to discriminate academic gain from legitimate ATAR-maximizing strategies. But by controlling for ICSEA, ATAR proportion variation and student mobility, it uncovers progression to ATAR metrics which are not currently publicly available. However achieved, ATAR maximisation is a sought-after private good. So long as standardised nationwide data is available, this analysis offers useful analytics for educators and reasonable predictivity when counselling subsequent cohorts about their ATAR prospects.  

Keywords: NAPLAN, ATAR, analytics, measurement, gain, performance, data, percentile, value-added, high school, numeracy, reading comprehension, variability, regression to the mean

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Authors: Razan Farah, Siham Ballah

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Facebook, Instagram, TikTok and other social media applications have become an integral component of everyone’s social life, particularly among younger generations and adolescences. These social apps have been changing a lot of conceptions and believes in the population by representing public figures and celebrities as role models. The social comparison theory, which says that people self-evaluate based on comparisons with similar others, is commonly used to explore the impact of social media on body image. There is a need to study the influence of those social platforms on the body image as there have been an increase in body dissatisfaction in the recent years. This cross sectional study used a self administered questionnaire on a simple random sample of 133 female medical students of the first year. Finding shows that the response rate was 75%. There was an association between social media usage and noticing how the person look(p value = .022), but no significant association between social media use and body image influence or dissatisfaction was found. This study implies more research under this topic in Sudan as the literature are scarce.

Keywords: body image, body dissatisfaction, social media, adolescences

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Authors: Abbas Shafiee, Mohammad Taghi Ahmadian, Maryam Hoviattalab

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The biomechanical behavior of brain tissue is needed for predicting the traumatic brain injury (TBI). Each year over 1.5 million people sustain a TBI in the USA. The appropriate coefficients for injury prediction can be evaluated using experimental data. In this study, an experimental setup on brain soft tissue was developed to perform unconfined compression tests at quasistatic strain rates ∈0.0004 s-1 and 0.008 s-1 and 0.4 stress relaxation test under unconfined uniaxial compression with ∈ 0.67 s-1 ramp rate. The fitted visco-hyperelastic parameters were utilized by using obtained stress-strain curves. The experimental data was validated using finite element analysis (FEA) and previous findings. Also, influence of friction coefficient on unconfined compression and relaxation test and effect of ramp rate in relaxation test is investigated. Results of the findings are implemented on the analysis of a human brain under high acceleration due to impact.

Keywords: brain soft tissue, visco-hyperelastic, finite element analysis (FEA), friction, quasistatic strain rate

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Authors: Ying Su, Morgan C. Wang

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Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

Procedia PDF Downloads 96

Authors: Yogesh Kumar Singh, T. S. Murugesh Prabhu, Upasana Dutta, Girishchandra Yendargaye, Rahul Yadav, Rohini Gopinath Kale, Binay Kumar, Manoj Khare

Abstract:

The Indian subcontinent is severely affected by floods that cause intense irreversible devastation to crops and livelihoods. With increased incidences of floods and their related catastrophes, an Early Warning System for Flood Prediction and an efficient Flood Management System for the river basins of India is a must. Accurately modeled hydrological conditions and a web-based early warning system may significantly reduce economic losses incurred due to floods and enable end users to issue advisories with better lead time. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. High-Performance Computing (HPC), Remote Sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. Considering the complexity of the hydrological modeling and the size of the basins in India, it is always a tug of war between better forecast lead time and optimal resolution at which the simulations are to be run. High-performance computing technology provides a good computational means to overcome this issue for the construction of national-level or basin-level flash flood warning systems having a high resolution at local-level warning analysis with a better lead time. High-performance computers with capacities at the order of teraflops and petaflops prove useful while running simulations on such big areas at optimum resolutions. In this study, a free and open-source, HPC-based 2-D hydrodynamic model, with the capability to simulate rainfall run-off, river routing, and tidal forcing, is used. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta) with actual and predicted discharge, rainfall, and tide data. The simulation time was reduced from 8 hrs to 3 hrs by increasing CPU nodes from 45 to 135, which shows good scalability and performance enhancement. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time. To disseminate warning to the end user, a network-enabled solution is developed using open-source software. The system has query-based flood damage assessment modules with outputs in the form of spatial maps and statistical databases. System effectively facilitates the management of post-disaster activities caused due to floods, like displaying spatial maps of the area affected, inundated roads, etc., and maintains a steady flow of information at all levels with different access rights depending upon the criticality of the information. It is designed to facilitate users in managing information related to flooding during critical flood seasons and analyzing the extent of the damage.

Keywords: flood, modeling, HPC, FOSS

Procedia PDF Downloads 87

Authors: Ramakrishna Rao Mamidi

Abstract:

It is essential for Surface Mounted Permanent Magnet (SMPM) generators to determine the performance prediction and analyze the magnet’s air gap flux density wave shape. The flux density wave shape is neither a pure sine wave or square wave nor a combination. This is due to the variation of air gap reluctance between the stator and permanent magnets. The stator slot openings and the number of slots make the wave shape highly complicated. To reduce the complexity of analysis, approximations are made to the wave shape using Fourier analysis. In contrast to the traditional integration method, the Fourier coefficients, an and bn, are obtained by direct search method optimization. The wave shape with optimized coefficients gives a wave shape close to the desired wave shape. Harmonics amplitudes are worked out and compared with initial values. It can be concluded that the direct search method can be used for estimating Fourier coefficients for irregular wave shapes.

Keywords: direct search, flux plot, fourier analysis, permanent magnets

Procedia PDF Downloads 210