Search results for: post model selection

Authors: Abedalbasit M. Abedalhafiz, Aman Kasawneh, Zyad Altahynah, Ahmad Okor

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The purpose of this study was to determine the construct validity of the morale sprit scale (MSS). Ninety faculty members from colleges of physical education at Jordanian universities were chosen to participate in this study. The design of this study was an ex-post facto. The MSS consists of (48) items that measure different dimensions of morale spirit among faculty members. Principle axis factoring with oblique rotation was utilized to uncover the underlying structure of the instrument. The findings revealed eight factor solution explaining (72.825%). Seven factors were accepted according to the conditions of accepting factors. The seven factors were named morale as reflection of faculty and department's administration, regulations and instructions, working environment and conditions, promotions and incentives and salaries, relations between the faculty member's, the trend toward the college and university, the trend toward self factors.

Keywords: Factorial validity, morale sprit, faculty members, Jordanian Universities

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Authors: Somayeh Komeylian

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The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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Authors: Eda Orhun

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Purpose: This paper analyzes a target firm’s decision to voluntarily disclose information during a takeover event and the effect of such disclosures on the outcome of the takeover. Such voluntary disclosures especially in the form of earnings forecasts made around takeover events may affect shareholders’ decisions about the target firm’s value and in return takeover result. This study aims to shed light on this question. Design/methodology/approach: The paper tries to understand the role of voluntary disclosures by target firms during a takeover event in the likelihood of takeover success both theoretically and empirically. A game-theoretical model is set up to analyze the voluntary disclosure decision of a target firm to inform the shareholders about its real worth. The empirical implication of model is tested by employing binary outcome models where the disclosure variable is obtained by identifying the target firms in the sample that provide positive news by issuing increasing management earnings forecasts. Findings: The model predicts that a voluntary disclosure of positive information by the target decreases the likelihood that the takeover succeeds. The empirical analysis confirms this prediction by showing that positive earnings forecasts by target firms during takeover events increase the probability of takeover failure. Overall, it is shown that information dissemination through voluntary disclosures by target firms is an important factor affecting takeover outcomes. Originality/Value: This study is the first to the author's knowledge that studies the impact of voluntary disclosures by the target firm during a takeover event on the likelihood of takeover success. The results contribute to information economics, corporate finance and M&As literatures.

Keywords: takeovers, target firm, voluntary disclosures, earnings forecasts, takeover success

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Authors: Emily Magoma-Nthite, Nonhlanhla Maseko, Mabatho Sedibe

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In this study, the focus is on the exploration and description of the teachers’ perceptions regarding retirement in Gauteng school in Tshwane North districts. From the individual and group interviews, the findings are leading to suggestions that a more comprehensive program for preparing teachers for retirement is highly necessary. All the participants were aware of their retirement age of 60 years as stipulated in the department of education internal memorandum No: 05 of 2021, which states that the compulsory retirement age in the public service is 60 years. It further states that the age restriction is in accordance with Chapter 4 of the Public Service Act, 1994 and Chapter 4 of the Employment of Educators Act, 1998, as amended. It was found out that there are some anxieties and fears as the majority seemed not ready and maybe not prepared enough for the retirement. Recommendations for a pre-retirement programme aimed at timeous preparation, which may include psychological, financial, and ability to keep functioning post retirement, will be proposed to the department of education in Gauteng and for the Tshwane North district as the pilot site on approval.

Keywords: teachers, pre-retirement, preparedness, gauteng schools

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Authors: Mary Anne Roa

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Congestion in network occurs due to exceed in aggregate demand as compared to the accessible capacity of the resources. Network congestion will increase as network speed increases and new effective congestion control methods are needed, especially for today’s very high speed networks. To address this undeniably global issue, the study focuses on the development of a fuzzy-based congestion control model concerned with allocating the resources of a computer network such that the system can operate at an adequate performance level when the demand exceeds or is near the capacity of the resources. Fuzzy logic based models have proven capable of accurately representing a wide variety of processes. The model built is based on bandwidth, the aggregate incoming traffic and the waiting time. The theoretical analysis and simulation results show that the proposed algorithm provides not only good utilization but also low packet loss.

Keywords: congestion control, queue management, computer networks, fuzzy logic

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Authors: Narender Banwala

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The study critically evaluates that the politics of foreign aid and its effect on Afghanistan. The study argues that dynamics of foreign aid to Afghanistan are not driven solely by the Afghan political, social, and economic realities but much more by the ephemeral political goals of international donor countries. The objective of this paper is to find out the political reality of foreign aid given to Afghanistan in a post 9/11 era. The study analyses the gap between the donor countries' interests and the Afghan government's priorities in aid coordination and management. The aid given to Afghanistan has been accompanied by the political interests of the major powers and therefore violated the core principles of humanitarianism, i.e., humanity, impartiality, neutrality, and independence. This research attempts to explain the areas which are of high priority, extremely vulnerable, and have been a neglected part since 2001. The study focuses on how as a result of politicization, foreign aid could not yield the expected results even after prolong presence of international donors in Afghanistan. Methodologically, the study includes both qualitative and quantitative data, which are collected by interviews with government officials and other government documents.

Keywords: Afganistan, aid, politics, security

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Authors: Puneet Katyal, Punit Kumar

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A great deal of efforts has been done in the field of thermal effects in electrohydrodynamic lubrication (TEHL) during the last five decades. The focus was primarily on the development of an efficient numerical scheme to deal with the computational challenges involved in the solution of TEHL model; however, some important aspects related to the accurate description of lubricant properties such as viscosity, rheology and thermal conductivity in EHL point contact analysis remain largely neglected. A few studies available in this regard are based upon highly complex mathematical models difficult to formulate and execute. Using a simplified thermal EHL model for point contacts, this work sheds some light on the importance of accurate characterization of the lubricant properties and demonstrates that the computed TEHL characteristics are highly sensitive to lubricant properties. It also emphasizes the use of appropriate mathematical models with experimentally determined parameters to account for correct lubricant behaviour.

Keywords: TEHL, shear thinning, rheology, conductivity

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Authors: Rahimah Abdulrahman, A. Eardle, Wilfred Alan, Abdel Hamid Soliman

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With the rapid development in technology, and advances in learning technologies, m-learning has begun to occupy a great part of our lives. The pace of the life getting together with the need for learning started mobile learning (m-learning) concept. In 2008, Saudi Arabia requested a national plan for the adoption of information technology (IT) across the country. Part of the recommendations of this plan concerns the implementation of mobile learning (m-learning) as well as their prospective applications to higher education within the Kingdom of Saudi Arabia. The overall aim of the research is to explore the main issues that impact the deployment of m-learning in nursing institutes in Saudi Arabia, at the Armed Force Hospitals (AFH), Alhada. This is in order to be able to develop a generic model to enable and assist the educational policy makers and implementers of m-learning, to comprehend and treat those issues effectively. Specifically, the research will explore the concept of m-learning; identify and analyse the main organisational; technological and cultural issue, that relate to the adoption of m-learning; develop a model of m-learning; investigate the perception of the students of the Nursing Institutes to the use of m-learning technologies for their nursing diploma programmes based on their experiences; conduct a validation of the m-learning model with the use of the nursing Institute of the AFH, Alhada in Saudi Arabia, and evaluate the research project as a learning experience and as a contribution to the body of knowledge. Activity Theory (AT) will be adopted for the study due to the fact that it provides a conceptual framework that engenders an understanding of the structure, development and the context of computer-supported activities. The study will be adopt a set of data collection methods which engage nursing students in a quantitative survey, while nurse teachers are engaged through in depth qualitative studies to get first-hand information about the organisational, technological and cultural issues that impact on the deployment of m-learning. The original contribution will be a model for developing m-learning material for classroom-based learning in the nursing institute that can have a general application.

Keywords: activity theory (at), mobile learning (m-learning), nursing institute, Saudi Arabia (sa)

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Authors: Muhammad Luthfi, Sutikno Sutikno, Purhadi Purhadi

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Weather forecast has necessarily been improved to provide the communities an accurate and objective prediction as well. To overcome such issue, the numerical-based weather forecast was extensively developed to reduce the subjectivity of forecast. Yet the Numerical Weather Predictions (NWPs) outputs are unfortunately issued without taking dynamical weather behavior and local terrain features into account. Thus, NWPs outputs are not able to accurately forecast the weather quantities, particularly for medium and long range forecast. The aim of this research is to aid and extend the development of ensemble forecast for Meteorology, Climatology, and Geophysics Agency of Indonesia. Ensemble method is an approach combining various deterministic forecast to produce more reliable one. However, such forecast is biased and uncalibrated due to its underdispersive or overdispersive nature. As one of the parametric methods, Bayesian Model Averaging (BMA) generates the calibrated ensemble forecast and constructs predictive PDF for specified period. Such method is able to utilize ensemble of any size but does not take spatial correlation into account. Whereas space dependencies involve the site of interest and nearby site, influenced by dynamic weather behavior. Meanwhile, Geostatistical Output Perturbation (GOP) reckons the spatial correlation to generate future weather quantities, though merely built by a single deterministic forecast, and is able to generate an ensemble of any size as well. This research conducts both BMA and GOP to generate the calibrated ensemble forecast for the daily temperature at few meteorological sites nearby Indonesia international airport.

Keywords: Bayesian Model Averaging, ensemble forecast, geostatistical output perturbation, numerical weather prediction, temperature

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Authors: Afia Naheed, Manmohan Singh, David Lucy

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This work is based on a mathematical as well as statistical study of an SEIJTR deterministic model for the interpretation of transmission of severe acute respiratory syndrome (SARS). Based on the SARS epidemic in 2003, the parameters are estimated using Runge-Kutta (Dormand-Prince pairs) and least squares methods. Possible graphical and numerical techniques are used to validate the estimates. Then effect of the model parameters on the dynamics of the disease is examined using sensitivity and uncertainty analysis. Sensitivity and uncertainty analytical techniques are used in order to analyze the affect of the uncertainty in the obtained parameter estimates and to determine which parameters have the largest impact on controlling the disease dynamics.

Keywords: infectious disease, severe acute respiratory syndrome (SARS), parameter estimation, sensitivity analysis, uncertainty analysis, Runge-Kutta methods, Levenberg-Marquardt method

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Authors: Luca Vascelli, Silvia Iacomini, Giada Gueli, Francesca Cavallini, Carlo Cavallini, Federica Berardo

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The study was conducted to evaluate the effect of training on Big 6 + 6 motor skills to promote daily living skills. Precision teaching (PT) suggests that improved speed of the component behaviors can lead to better performance of composite skills. This study assessed the effects of the repeated timed practice of component motor skills on speed and accuracy of composite skills related to daily living skills. An 18 years old adolescent with intellectual disability participated. A pre post probe single-subject design was used. The results suggest that the participant was able to perform the component skills at his individual aims (endurance was assessed). The speed and accuracy of composite skills were increased; stability and retention were also measured for the composite skill after the training.

Keywords: big 6+6, daily living skills, intellectual disability, precision teaching

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Authors: James A. Adeyanju, John O. Olajide, Akinbode A. Adedeji

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A predictive mathematical model based on the fundamental principles of mass transfer was developed to simulate the moisture content and oil content during Deep-Fat Frying (DFF) process of dodo. The resulting governing equation, that is, partial differential equation that describes rate of moisture loss and oil uptake was solved numerically using explicit Finite Difference Technique (FDT). Computer codes were written in MATLAB environment for the implementation of FDT at different frying conditions and moisture loss as well as oil uptake simulation during DFF of dodo. Plantain samples were sliced into 5 mm thickness and fried at different frying oil temperatures (150, 160 and 170 ⁰C) for periods varying from 2 to 4 min. The comparison between the predicted results and experimental data for the validation of the model showed reasonable agreement. The correlation coefficients between the predicted and experimental values of moisture and oil transfer models ranging from 0.912 to 0.947 and 0.895 to 0.957, respectively. The predicted results could be further used for the design, control and optimization of deep-fat frying process.

Keywords: frying, moisture loss, modelling, oil uptake

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Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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Authors: Endalamaw Ewnu Kassa, Ade Kurniawan, Ya-Fen Wu, Sajal Biring

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Perovskite-based gas sensors represent a highly promising materials within the realm of gas sensing technology, with a particular focus on detecting ammonia (NH3) due to its potential hazards. Our work conducted thorough comparison of various solvents, including dimethylformamide (DMF), DMF-dimethyl sulfoxide (DMSO), dimethylacetamide (DMAC), and DMAC-DMSO, for the preparation of our perovskite solution (MAPbI3). Significantly, we achieved an exceptional response at 10 ppm of ammonia gas by employing a binary solvent mixture of DMAC-DMSO. In contrast to prior reports that relied on single solvents for MAPbI3 precursor preparation, our approach using mixed solvents demonstrated a marked improvement in gas sensing performance. We attained enhanced surface coverage, a reduction in pinhole occurrences, and precise control over grain size in our perovskite films through the careful selection and mixtures of appropriate solvents. This study shows a promising potential of employing binary and multi-solvent mixture strategies as a means to propel advancements in gas sensor technology, opening up new opportunities for practical applications in environmental monitoring and industrial safety.

Keywords: sensors, binary solvents, ammonia, sensitivity, grain size, pinholes, surface coverage

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Authors: Sirimanee Banjong

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This study aimed to 1) develop pre-service teachers’ leadership skills through camp-based learning, and 2) develop pre-service teachers’ teamwork skills through camp-based learning. An applied research methodology was used. The target group was derived from a purposive selection. It involved 32 fourth-year students in Early Childhood Education Program enrolling in a course entitled Seminar in Early Childhood Education provided during the second semester of the academic year 2013. The treatment was camp-based learning activities which applied a PDCA process including four stages: 1) plan, 2) do, 3) check, and 4) act. Research instruments were a learning camp program, a camp-based learning management plan, a 5-level assessment form for leadership skills and a 5-level assessment form for assessing teamwork skills. Data were analyzed using descriptive statistics. Results were: 1) pre-service teachers’ leadership skills yielded the before treatment average score at ¯("x" )=3.4, S.D.= 0.62 and the after-treatment average score at ¯("x" ) 4.29, S.D.=0.66 pre-service teachers’ teamwork skills yielded the before-treatment average score at ¯("x" )=3.31, S.D.= 0.60 and the after-treatment average score at ¯("x" )=4.42, S.D.= 0.66. Both differences were statistically significant at the .05 level. Thus, the pre-service teachers’ leadership and teamwork skills were significantly improved through the camp-based learning approach.

Keywords: learning camp, leadership skills, teamwork skills, pre-service teachers

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Authors: Paulin Mbecke

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Research Issue: Under economic constraints, socio-economic conditions of households worsen discounting child’s wellbeing to the bottom of many governments and households’ priority lists. In such situation, many governments fail to rebalance priorities in providing services such as education, housing and social security which are the prerequisites for the wellbeing of children. Consequently, many households struggle to respond to basic needs especially those of children. Although economic conditions play a crucial role in creating prosperity or poverty in households and therefore the wellbeing or misery for children; they are not the sole cause. Research Insights: The review of the South African Index of Multiple Deprivation and the South African Child Gauge establish the extent to which economic conditions impact on the wellbeing or misery of children. The analysis of social, cultural, environmental and structural theories demonstrates that non-economic factors contribute equally to the wellbeing or misery of children, yet, they are disregarded. In addition, the assessment of a child abuse database proves a weak correlation between economic factors (prosperity or poverty) and child’s wellbeing or misery. Theoretical Implications: Through critical social research theory and modelling, the paper proposes a Theory-Based Model that combines different factors to facilitate the understanding of child’s wellbeing or misery. Policy Implications: The proposed model assists in broad policy and decision making and reviews processes in promoting child’s wellbeing and in preventing, intervening and managing child’s misery with regard to education, housing, and social security.

Keywords: children, child’s misery, child’s wellbeing, household’s despair, household’s prosperity

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Authors: Saeed Farhadypour, Majid Azadi, Habibolla Sayyari, Mahmood Mosavi, Shahram Irani, Aliakbar Bidokhti, Omid Alizadeh Choobari, Ziba Hamidi

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In the recent decades, frequencies of dust events have increased significantly in west and south west of Iran. First, a survey on the dust events during the period (1990-2013) is investigated using historical dust data collected at 6 weather stations scattered over west and south-west of Iran. After statistical analysis of the observational data, one of the most severe dust storm event that occurred in the region from 3rd to 6th July 2009, is selected and analyzed. WRF-Chem model is used to simulate the amount of PM10 and how to transport it to the areas. The initial and lateral boundary conditions for model obtained from GFS data with 0.5°×0.5° spatial resolution. In the simulation, two aerosol schemas (GOCART and MADE/SORGAM) with 3 options (chem_opt=106,300 and 303) were evaluated. Results of the statistical analysis of the historical data showed that south west of Iran has high frequency of dust events, so that Bushehr station has the highest frequency between stations and Urmia station has the lowest frequency. Also in the period of 1990 to 2013, the years 2009 and 1998 with the amounts of 3221 and 100 respectively had the highest and lowest dust events and according to the monthly variation, June and July had the highest frequency of dust events and December had the lowest frequency. Besides, model results showed that the MADE / SORGAM scheme has predicted values and trends of PM10 better than the other schemes and has showed the better performance in comparison with the observations. Finally, distribution of PM10 and the wind surface maps obtained from numerical modeling showed that the formation of dust plums formed in Iraq and Syria and also transportation of them to the West and Southwest of Iran. In addition, comparing the MODIS satellite image acquired on 4th July 2009 with model output at the same time showed the good ability of WRF-Chem in simulating spatial distribution of dust.

Keywords: dust storm, MADE/SORGAM scheme, PM10, WRF-Chem

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Authors: Arazan Jane V., Badiang, Ronesito Jr. R., Clavesillas Cristine Joy H., Belleza Saramie S.

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This study examined the coaching style among the PE Teachers in terms of Autonomy, Supportive style, and Controlling Style. On the other hand, gives opportunities to an athlete to be independent, task-oriented, and acknowledge their feelings and perspective of each individual. A controlling coaching style is also portrayed by the rises and falls over an athlete's training development; when this variance is identified, it might harm training. The selection of the respondents of the study will use a random sample of High School PE teachers of the Division of Davao del Norte with a total of 78 High School PE teachers, which can be broken down into 70 High School PE Teachers for Quantitative data for the survey questionnaire and 8 PE Teachers for Qualitative data (IDI). In the quantitative phase, a set of survey questionnaires will be used to gather data from the participants—the extent of the Implementation Questionnaire. The tool will be a researcher-made questionnaire based on the Coaching Styles of selected High School PE teachers of Davao Del Norte. In the qualitative phase, an interview guide questionnaire will be used. Focus group discussions will be conducted to determine themes and patterns or participants' experiences and insights. The researchers conclude that the degree of coaching style among PE Teachers from the Division of Davao del Norte is high, as seen by the findings of this study, and that coaching style among these teachers is highly noticeable.

Keywords: supportive autonomy style, controlling style, live experiences, exemplified

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Authors: Azli Bin Ariffin, Noor Amy Afiza Binti Mohd Yusof

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This study aims to identify effect of social network usage on the self-learning method in teaching and learning at Sultan Idris Education University. The study involved 270 respondents consisting of students in the pre-graduate and post-graduate levels from nine fields of study offered. Assessment instrument used is questionnaire which measures respondent’s background includes level of study, years of study and field of study. Also measured the extent to which social pages used for self-learning and effect received when using social network for self-learning in learning process. The results of the study showed that students always visit Facebook more than other social sites. But, it is not for the purpose of self-learning. Analyzed data showed that 45.5% students not sure about using social sites for self-learning. But they realize the positive effect that they will received when use social sites for self-learning to improve teaching and learning process when 72.7% respondent agreed with all the statements provided.

Keywords: facebook, self-learning, social network, teaching, learning

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Authors: M. K. Yusuf, W. O. Hamman, U. E. Umana, S. B. Oladele

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Background: Dilatation of the inferior vena cava (IVC) is used as the ultrasonic diagnostic feature in patients suspected of congestive heart failure. The IVC diameter has been reported to vary among the various body mass indexes (BMI) and body shape indexes (ABSI). Knowledge of these variations is useful in precision diagnoses of CHF by imaging scientists. Aim: The study aimed to establish an equation for predicting the ultrasonic mean diameter of the IVC among the various BMI/ABSI of inhabitants of Azare, Bauchi State-Nigeria. Methodology: Two hundred physically healthy adult subjects of both sexes were classified into under, normal, over, and obese weights using their BMIs after selection using a structured questionnaire following their informed consent for an abdominal ultrasound scan. The probe was placed on the midline of the body, halfway between the xiphoid process and the umbilicus, with the marker on the probe directed towards the patient's head to obtain a longitudinal view of the IVC. The maximum IVC diameter was measured from the subcostal view using the electronic caliper of the scan machine. The mean value of each group was obtained, and the results were analysed. Results: A novel equation {(IVC Diameter = 1.04 +0.01(X) where X= BMI} has been generated for determining the IVC diameter among the populace. Conclusion: An equation for predicting the IVC diameter from individual BMI values in apparently healthy subjects has been established.

Keywords: equation, ultrasonic, IVC diameter, body adiposities

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Authors: Tayo P. Ogundunmade, Adedayo A. Adepoju

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Terrorist attacks in liberal democracies bring about a few pessimistic results, for example, sabotaged public support in the governments they target, disturbing the peace of a protected environment underwritten by the state, and a limitation of individuals from adding to the advancement of the country, among others. Hence, seeking for techniques to understand the different factors involved in terrorism and how to deal with those factors in order to completely stop or reduce terrorist activities is the topmost priority of the government in every country. This research aim is to develop an efficient deep learning-based predictive model for the prediction of future terrorist activities in Nigeria, addressing low-quality prediction accuracy problems associated with the existing solution methods. The proposed predictive AI-based model as a counterterrorism tool will be useful by governments and law enforcement agencies to protect the lives of individuals in society and to improve the quality of life in general. A Heterogeneous Bayesian Neural Network (HETBNN) model was derived with Gaussian error normal distribution. Three primary transfer functions (HOTTFs), as well as two derived transfer functions (HETTFs) arising from the convolution of the HOTTFs, are namely; Symmetric Saturated Linear transfer function (SATLINS ), Hyperbolic Tangent transfer function (TANH), Hyperbolic Tangent sigmoid transfer function (TANSIG), Symmetric Saturated Linear and Hyperbolic Tangent transfer function (SATLINS-TANH) and Symmetric Saturated Linear and Hyperbolic Tangent Sigmoid transfer function (SATLINS-TANSIG). Data on the Terrorist activities in Nigeria gathered through questionnaires for the purpose of this study were used. Mean Square Error (MSE), Mean Absolute Error (MAE) and Test Error are the forecast prediction criteria. The results showed that the HETFs performed better in terms of prediction and factors associated with terrorist activities in Nigeria were determined. The proposed predictive deep learning-based model will be useful to governments and law enforcement agencies as an effective counterterrorism mechanism to understand the parameters of terrorism and to design strategies to deal with terrorism before an incident actually happens and potentially causes the loss of precious lives. The proposed predictive AI-based model will reduce the chances of terrorist activities and is particularly helpful for security agencies to predict future terrorist activities.

Keywords: activation functions, Bayesian neural network, mean square error, test error, terrorism

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Authors: Tamás Mankovits, Dávid Huri, Imre Kállai, Imre Kocsis, Tamás Szabó

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Non-linear FEM calculations are indispensable when important technical information like operating performance of a rubber component is desired. Rubber bumpers built into air-spring structures may undergo large deformations under load, which in itself shows non-linear behavior. The changing contact range between the parts and the incompressibility of the rubber increases this non-linear behavior further. The material characterization of an elastomeric component is also a demanding engineering task. In this paper, a comprehensive investigation is introduced including laboratory measurements, mesh density analysis and complex finite element simulations to obtain the load-displacement curve of the chosen rubber bumper. Contact and friction effects are also taken into consideration. The aim of this research is to elaborate an FEM model which is accurate and competitive for a future shape optimization task.

Keywords: rubber bumper, finite element analysis, compression test, Mooney-Rivlin material model

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Authors: Amena Sibghatullah

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The purpose of this study was to examine the existence of Inter-generational Influence (IGI) between two successive generations in the selection of automobile brands. IGI was examined between mother-daughter dyads and father-son dyads. A total sample of 320 respondents (80 fathers and their 80 sons, 80 mothers, and their 80 daughters) from the upper-middle class was selected. Three important findings from this study are; (a) the difference in proportion of agreements Brand-In-Use versus Brand-In-Mind appeared to be statistically significant in the Automobile product category. Thus agreements Brand-In-Use situation between parent and child has more agreements than Brand-In-Mind situation; (b) the difference in proportions between women and men (women means mother-daughter dyad agreement, and men means father-son dyad agreement) is statistically significant in automobile brand preferences. This means that mother-daughter dyad brand preferences, both brand-in-mind and brand-in-use are more significant than that of a father-son dyad, and (c) dominance of the top three brands has been exhibited in automobiles both Brand-In-Use and Brand-In-Mind. These three brands hold more than 57% of auto brand preferences. This means that the three brands occupy distinct and strong positions in the minds of consumers. These results reflect that there is significant evidence of IGI presence between parent and adult child. Marketers of auto brands need to understand this sort of influence on their target consumers.

Keywords: autombile brands, branding, intergenerational influence, preferences

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Authors: Hyungoo Kang, Minsung Kim, Jinkoo Kim

Abstract:

This study investigates the performance of a 2D and 3D steel moment frame subjected to vehicle collision at a first story column using LS-DYNA. The finite element models of vehicles provided by the National Crash Analysis Center (NCAC) are used for numerical analysis. Nonlinear dynamic time history analysis of the 2D and 3D model structures are carried out based on the arbitrary column removal scenario, and the vertical displacement of the damaged structures are compared with that obtained from collision analysis. The analysis results show that the model structure remains stable when the speed of the vehicle is 40km/h. However, at the speed of 80 and 120km/h both the 2D and 3D structures collapse by progressive collapse. The vertical displacement of the damaged joint obtained from collision analysis is significantly larger than the displacement computed based on the arbitrary column removal scenario.

Keywords: vehicle collision, progressive collapse, FEM, LS-DYNA

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Authors: Adrian Travieso Disotuar, J. Antonio Travieso Rodriguez, Ramon Jerez Mesa, Montserrat Vilaseca

Abstract:

The effect of the non-vibration-assisted and vibration-assisted ball burnishing on both the surface and mechanical properties of C300 obtained by Selective Laser Melting additive manufacturing technology is studied in this paper. Different vibration amplitudes preloads, and burnishing strategies were tested. A topographical analysis was performed to determine the surface roughness of the different conditions. Besides, micro tensile tests were carried out in situ on Scanning Electron Microscopy to elucidate the post-treatment effects on damaging mechanisms. Experiments show that vibration-assisted ball burnishing significantly enhances mechanical properties compared to the non-vibration-assisted method. Moreover, it was found that the surface roughness was significantly improved with respect to the reference surface.

Keywords: additive manufacturing, ball burnishing, mechanical properties, metals, surface roughness

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Authors: M. Cynthya, V. Prabhawathi, D. Mukesh

Abstract:

Food contamination occurs during post process handling. This leads to spoilage and growth of pathogenic microorganisms in the food, thereby reducing its shelf life or spreading of food borne diseases. Several methods are tried and one of which is use of antimicrobial packaging. Here, papain, a protease enzyme, is covalently immobilized with the help of glutarldehyde on polyurethane and used as a food wrap to protect food from microbial contamination. Covalent immobilization of papain was achieved at a pH of 7.4; temperature of 4°C; glutaraldehyde concentration of 0.5%; incubation time of 24 h; and 50 mg of papain. The formation of -C=N- observed in the Fourier transform infrared spectrum confirmed the immobilization of the enzyme on the polymer. Immobilized enzyme retained higher activity than the native free enzyme. The efficacy of this was studied by wrapping it over S. aureus contaminated cottage cheese (paneer) and cheese and stored at a temperature of 4°C for 7 days. The modified film reduced the bacterial contamination by eight folds when compared to the bare film. FTIR also indicates reduction in lipids, sugars and proteins in the biofilm.

Keywords: cheese, papain, polyurethane, Staphylococcus aureus

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Authors: Aurore Cauquis, Philippe Heinrich, Mario Ricchiuto, Audrey Gailler

Abstract:

In this talk, we look for an accurate time scheme to model the propagation of waves. Several numerical schemes have been developed to solve the extended weakly nonlinear weakly dispersive Boussinesq Equations. The temporal schemes used are two Lax-Wendroff schemes, second or third order accurate, two Runge-Kutta schemes of second and third order and a simplified third order accurate Lax-Wendroff scheme. Spatial derivatives are evaluated with fourth order accuracy. The numerical model is applied to two monodimensional benchmarks on a flat bottom. It is also applied to the simulation of the Algerian tsunami generated by a Mw=6 seism on the 18th March 2021. The tsunami propagation was highly dispersive and propagated across the Mediterranean Sea. We study here the effects of the order of temporal discretization on the accuracy of the results and on the time of computation.

Keywords: numerical analysis, tsunami propagation, water wave, boussinesq equations

Procedia PDF Downloads 247

Authors: Lawrence Koech, Hilary Rutto, Olga Mothibedi

Abstract:

Worldwide demand for copper has led to intensive search for methods of extraction and recovery of copper from different sources. The study investigates the leaching properties of a low-grade copper ore by optimizing the leaching variables using response surface methodology. The effects of key parameters, i.e., temperature, solid to liquid ratio, stirring speed and pH, on the leaching rate constant was investigated using a pH stat apparatus. A Central Composite Design (CCD) of experiments was used to develop a quadratic model which specifically correlates the leaching variables and the rate constant. The results indicated that the model is in good agreement with the experimental data with a correlation coefficient (R2) of 0.93. The temperature and solid to liquid ratio were found to have the most substantial influence on the leaching rate constant. The optimum operating conditions for copper leaching from the ore were identified as temperature at 65C, solid to liquid ratio at 1.625 and stirring speed of 325 rpm which yielded an average leaching efficiency of 93.16%.

Keywords: copper, leaching, CCD, rate constant

Procedia PDF Downloads 249

Authors: HoYoung Son, DongHoon Shin, WooYoung Jung

Abstract:

This study presented the seismic fragility framework of concrete weir structure subjected to strong seismic ground motions and in particular, concrete aging condition of the weir structure was taken into account in this study. In order to understand the influence of concrete aging on the weir structure, by using probabilistic risk assessment, the analytical seismic fragility of the weir structure was derived for pre- and post-deterioration of concrete. The performance of concrete weir structure after five years was assumed for the concrete aging or deterioration, and according to after five years’ condition, the elastic modulus was simply reduced about one–tenth compared with initial condition of weir structures. A 2D nonlinear finite element analysis was performed considering the deterioration of concrete in weir structures using ABAQUS platform, a commercial structural analysis program. Simplified concrete degradation was resulted in the increase of almost 45% of the probability of failure at Limit State 3, in comparison to initial construction stage, by analyzing the seismic fragility.

Keywords: weir, FEM, concrete, fragility, aging

Procedia PDF Downloads 487