Search results for: test techniques

Authors: Ashraf Nawaz Khan, R. Alagirusamy, Apurba Das, Puneet Mahajan

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The thermoplastic-based fibre composites are acquiring a market sector of conventional as well as thermoset composites. However, replacing the thermoset with a thermoplastic composite has never been an easy task. The inherent high viscosity of thermoplastic resin reveals poor interface properties. In this work, a homo-polymer towpreg is produced through an electrostatic powder spray coating methodology. The produced flexible towpreg offers a low melt-flow distance during the consolidation of the laminate. The reduced melt-flow distance demonstrates a homogeneous fibre/matrix distribution (and low void content) on consolidation. The composite laminate has been fabricated with two manufacturing techniques such as conventional film stack (FS) and powder-coated (PC) technique. This helps in understanding the distinct response of produced laminates on applying load since the laminates produced through the two techniques are comprised of the same constituent fibre and matrix (constant fibre volume fraction). The changed behaviour is observed mainly due to the different fibre/matrix configurations within the laminate. The interface adhesion influences the load transfer between the fibre and matrix. Therefore, it influences the elastic, plastic, and failure patterns of the laminates. Moreover, the effect of preform geometries (plain weave and satin weave structure) are also studied for corresponding composite laminates in terms of various mechanical properties. The fracture analysis is carried out to study the effect of resin at the interlacement points through micro-CT analysis. The PC laminate reveals a considerably small matrix-rich and deficient zone in comparison to the FS laminate. The different load tensile, shear, fracture toughness, and drop weight impact test) is applied to the laminates, and corresponding damage behaviour is analysed in the successive stage of failure. The PC composite has shown superior mechanical properties in comparison to the FS composite. The damage that occurs in the laminate is captured through the SEM analysis to identify the prominent mode of failure, such as matrix cracking, fibre breakage, delamination, debonding, and other phenomena.

Keywords: composite, damage, fibre, manufacturing

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Authors: Chris Phan, Yong Seok Park

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The Toyota Camry is one of the best-selling cars in America. It is economical, reliable, and most importantly, safe. These attributes allowed the Camry to be the trustworthy choice when choosing dependable vehicle. However, a new finding brought question to the Camry’s safety. Since 1997, the Camry received a “good” rating on its moderate overlap front crash test through the Insurance Institute of Highway Safety. In 2012, the Insurance Institute of Highway Safety introduced a frontal small overlap crash test into the overall evaluation of vehicle occupant safety test. The 2012 Camry received a “poor” rating on this new test, while the 2015 Camry redeemed itself with a “good” rating once again. This study aims to find a possible solution that Toyota implemented to reduce the severity of a frontal small overlap crash in the Camry during a mid-cycle update. The purpose of this study is to analyze and evaluate the performance of various A-pillar shapes as energy absorbing structures in improving passenger safety in a frontal crash. First, A-pillar structures of the 2012 and 2015 Camry were modeled using CAD software, namely SolidWorks. Then, a crash test simulation using ANSYS software, was applied to the A-pillars to analyze the behavior of the structures in similar conditions. Finally, the results were compared to safety values of cabin intrusion to determine the crashworthy behaviors of both A-pillar structures by measuring total deformation. This study highlights that it is possible that Toyota improved the shape of the A-pillar in the 2015 Camry in order to receive a “good” rating from the IIHS safety evaluation once again. These findings can possibly be used to increase safety performance in future vehicles to decrease passenger injury or fatality.

Keywords: A-pillar, Crashworthiness, Design Synthesis, Finite Element Analysis

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Authors: Qaisara Parveen, M. Imran Yousuf

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The purpose of this study was to find the effectiveness of the use of advance organizer model for enhancing meta-cognition of students in the subject of science. It was hypothesized that the students of experimental group taught through advance organizer model would show the better cognition than the students of control group taught through traditional teaching. The population of the study consisted of all secondary school students studying in government high school located in Rawalpindi. The sample of the study consisted of 50 students of 9th class of humanities group. The sample was selected on the basis of their pretest scores through matching, and the groups were randomly assigned for the treatment. The experimental group was taught through advance organizer model while the control group was taught through traditional teaching. The self-developed achievement test was used for the purpose of pretest and posttest. After collecting the pre-test score and post-test score, the data was analyzed and interpreted by use of descriptive statistics as mean and standard deviation and inferential statistics t-test. The findings indicate that students taught using advance organizers had a higher level of meta-cognition as compared to control group. Further, meta cognition level of boys was found higher than that of girls students. This study also revealed the fact that though the students at different meta-cognition level approached learning situations in a different manner, Advance organizer model is far superior to Traditional method of teaching.

Keywords: descriptive, experimental, humanities, meta-cognition, statistics, science

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Authors: Kyoung-Jae Kim

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Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

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Authors: Soon-Mi Park, Ihn Sook Jeong

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This retrospective study was aimed to identify risk factors of intravenous (IV) infiltration for hospitalized children. The participants were 1,174 children for test and 424 children for validation, who admitted to a general hospital, received peripheral intravenous injection therapy at least once and had complete records. Data were analyzed with frequency and percentage or mean and standard deviation were calculated, and decision tree analysis was used to screen for the most important risk factors for IV infiltration for hospitalized children. The decision tree analysis showed that the most important traditional risk factors for IV infiltration were the use of ampicillin/sulbactam, IV insertion site (lower extremities), and medical department (internal medicine) both in the test sample and validation sample. The correct classification was 92.2% in the test sample and 90.1% in the validation sample. More careful attention should be made to patients who are administered ampicillin/sulbactam, have IV site in lower extremities and have internal medical problems to prevent or detect infiltration occurrence.

Keywords: decision tree analysis, intravenous infiltration, child, validation

Procedia PDF Downloads 176

Authors: Shakirat Abimbola Adesola, Shuaib Akintunde Asifat, Jelili Olalekan Amoo

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This paper presented the impact of students’ emotions on learning when receiving lectures and when taking tests. It was observed that students experience different types of emotions during the study, and this was found to have a significant effect on their academic performance. A total of one thousand six hundred and seventy-five (1675) students from the department of Computer Science in two Colleges of Education in South-West Nigeria took part in this study. The students were randomly selected for the research. Sample comprises of 968 males representing 58%, and 707 females representing 42%. A structured questionnaire, of Motivated Strategies for Learning Questionnaire (MSLQ) was distributed to the participants to obtain their opinions. Data gathered were analyzed using the IBM SPSS 20 to obtain ANOVA, descriptive analysis, stepwise regression, and reliability tests. The results revealed that emotion moderately shape students’ motivation and engagement in learning; and that self-regulation and self-determination do have significant impact on academic performance. It was further revealed that test anxiety has a significant correlation with academic performance.

Keywords: motivation, self-determination, test anxiety, academic performance, and academic engagement

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Authors: J. Thiele

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Teachers working at vocational Colleges are often confronted with the problem, that many students graduated from different schools and therefore each had a different education. Especially in mathematics many students lack fundamentals or had different priorities at their previous schools. Furthermore, these vocational Colleges have to provide Graduations for many different working-fields, with different core themes. The Colleges are interested in measuring the different Education levels of their students and providing assistance for those who need to catch up. The Project mathe-meistern was initiated to remedy this problem at vocational Colleges. For this purpose, online-tests were developed. The aim of these tests is to evaluate basic mathematical abilities of the students. The tests are online Multiple-Choice-Tests with a total of 65 Items. They are accessed online with a unique Transaction-Number (TAN) for each participant. The content is divided in several Categories (Arithmetic, Algebra, Fractions, Geometry, etc.). After each test, the student gets a personalized summary depicting their strengths and weaknesses in mathematical Basics. Teachers can visit a special website to examine the results of their classes or single students. In total 5830 students did participate so far. For standardization and optimization purposes the tests are being evaluated, using the classic and probabilistic Test-Theory regarding Objectivity, Reliability and Validity, annually since 2015. This Paper is about the Optimization process considering the Rasch-scaling and Standardization of the tests. Additionally, current results using standardized tests will be discussed. To achieve this Competence levels and Types of errors of students attending vocational Colleges in Nordrheinwestfalen, Germany, were determined, using descriptive Data and Distractorevaluations.

Keywords: diagnostical tests in mathematics, distractor devaluation, test-optimization, test-theory

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Authors: Ping Chou, Xiaoyan Zhou

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Domestically and internationally, the Chinese education has long been criticized for being test-oriented, and in spite of efforts made by the Chinese government, it remains hard to find a solution. This paper intends to look at the situation in a comparatively objective manner and discuss the significance of the Shanghai Model as a newly-scheduled experiment for education reform. As a breakthrough, in addition to comprehensive inner-quality evaluation, a small but important step is to be taken in shifting focus of attention back to students by giving them more freedom in selecting certain courses for aptitude tests for college admission. As the first author of the paper has studied and taught both in Chinese and American colleges and universities, comparisons are made when the situation becomes relevant. The official solution for test-oriented education is to make students well-rounded but the writers of this paper believe that it is even more important to make the system well-rounded so it can accept a spectrum of diverse individuals with different potential.

Keywords: college admission, education reform, Shanghai model, test-oriented education

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Authors: Mona Khabiri, Fahimeh Farahani

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The present study was an attempt to investigate the comparative effect of teaching NLP, critical thinking, and a combination of NLP and critical thinking on EFL learners' reading comprehension. To fulfill the purpose of this study, a group of 82 female and male intermediate EFL learners at a Language School in Iran took a piloted sample PET as a proficiency test and 63 of them were selected as homogenous learners and were randomly assigned to three experimental groups. Within a treatment process of 10 sessions the teacher/researcher provided the participants of each group with handouts, explanations, practices, homework, and questionnaires on techniques of NLP, critical thinking, and a combination of both. During these 10 sessions, 10 same reading comprehension texts extracted from the multi-skill course book suggested by the language school where thought to the participants of each experimental group using skills and strategies of NLP, critical thinking, and a combination of both. On the eleventh session, the participants sat for a reading posttest. The results of one-way ANOVA showed no significant difference among the three groups in terms of reading comprehension. Justifications and implications for the findings of the study and suggestions for further research are presented.

Keywords: neuro-linguistic programming (NLP), critical thinking, reading comprehension

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Authors: Abdelkader Anouzla, Soukaina Bouaouda, Roukaya Bouyakhsass, Salah Souabi, Abdeslam Taleb

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During storage and under the combined action of rainwater and natural fermentation, these wastes produce over 800.000 m3 of landfill leachates. Due to population growth and changing global economic activities, the amount of waste constantly generated increases, making more significant volumes of leachate. Leachate, when leaching into the soil, can negatively impact soil, surface water, groundwater, and the overall environment and human life. The leachate must first be treated because of its high pollutant load before being released into the environment. This article reviews the different leachate treatments in September 2022 techniques. Different techniques can be used for this purpose, such as biological, physical-chemical, and membrane methods. Young leachate is biodegradable; in contrast, these biological processes lose their effectiveness with leachate aging. They are characterized by high ammonia nitrogen concentrations that inhibit their activity. Most physical-chemical treatments serve as pre-treatment or post-treatment to complement conventional treatment processes or remove specific contaminants. After the introduction, the different types of pollutants present in leachates and their impacts have been made, followed by a discussion highlighting the advantages and disadvantages of the various treatments, whether biological, physicochemical, or membrane. From this work, due to their simplicity and reasonable cost compared to other treatment procedures, biological treatments offer the most suitable alternative to limit the effects produced by the pollutants in landfill leachates.

Keywords: landfill leachate, landfill pollution, impact, wastewater

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Authors: Romella C. Lina, Matthew Daniel V. Leysa, Zarah D. F. Libozada, Maria Francesca I. Lirio, Angelo A. Liwag, Gabriel D. Ramos, Margaret M. Natividad

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This study aimed to determine the effectiveness of Buteyko Method in asthma control and quality of life of school-age children wherein a pretest-posttest design was utilized to measure the changes after the administration of Buteyko Method. Fourteen (14) subjects with bronchial asthma, aged 7-11 participated in the study. They were equally divided into two groups: the control group received no intervention while the experimental group was asked to attend sessions of Buteyko Method lecture and demonstration. The experimental group was visited for three (3) consecutive weeks to monitor their progress and compliance. Both groups were asked to answer ACQ pre- and post-intervention and PAQLQ before the start of the intervention phase and every week during the follow-up visits. In comparing the asthma control pre-test and post-test mean scores of the control group, no significant difference was noted (p=0.177) while the experimental group showed a significant difference after the administration of Buteyko Method (p=0.002). Moreover, the quality of life pre-test and post-test mean scores of the control group showed no significant difference in any week within one month of follow-up (p=0.736, 0.604, 0.689) while the experimental group showed a significant difference on the third week (p = 0.035) and fourth week (p=0.002) but no significant difference on the second week (p=0.111). Therefore, the use of Buteyko Method within 3-4 weeks as an adjunct to conventional management of asthma helps in improving asthma control and quality of life of school-age children.

Keywords: Buteyko Method, asthma, school-age children, asthma control, quality of life

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Larbi Belagraa, Miloud Beddar, Abderrazak Bouzid

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The needs of the construction sector still increasing for concrete. However, the shortage of natural resources of aggregate could be a problem for the concrete industry, in addition to the negative impact on the environment due to the demolition wastes. Recycling aggregate from construction and demolition (C&D) waste presents a major interest for users and researchers of concrete since this constituent can occupies more than 70% of concrete volume. The aim of the study here in is to assess the effect of sulfate resistant cement combined with the local mineral addition of marble waste fillers on the mechanical behavior of a recycled aggregate concrete (RAC). Physical and mechanical properties of RAC including the density, the flexural and the compressive strength were studied. The non destructive test methods (pulse-velocity, rebound hammer) were performed . The results obtained were compared to crushed aggregate concrete (CAC) using the normal compressive testing machine test method. The optimal content of 5% marble fillers showed an improvement for both used test methods (compression, flexion and NDT). Non-destructive methods (ultrasonic and rebound hammer test) can be used to assess the strength of RAC, but a correction coefficient is required to obtain a similar value to the compressive strength given by the compression tests. The study emphasizes that these waste materials can be successfully and economically utilized as additional inert filler in RAC formulation within similar performances compared to a conventional concrete.

Keywords: marble waste fillers, mechanical strength, natural aggregate, non-destructive testing (NDT), recycled aggregate concrete

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Authors: Ziad Abdallah, Mohamad Oueidat, Ali El-Zaart

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Image Multi-label Classification (IMC) assigns a label or a set of labels to an image. The big demand for image annotation and archiving in the web attracts the researchers to develop many algorithms for this application domain. The existing techniques for IMC have two drawbacks: The description of the elementary characteristics from the image and the correlation between labels are not taken into account. In this paper, we present an algorithm (MIML-HOGLPP), which simultaneously handles these limitations. The algorithm uses the histogram of gradients as feature descriptor. It applies the Label Priority Power-set as multi-label transformation to solve the problem of label correlation. The experiment shows that the results of MIML-HOGLPP are better in terms of some of the evaluation metrics comparing with the two existing techniques.

Keywords: data mining, information retrieval system, multi-label, problem transformation, histogram of gradients

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Authors: Sonia Zulfiqar, Daniele Mantione, Muhammad Ilyas Sarwar, Alexander Rothenberger, David Mecerreyes

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Climate change due to escalating carbon dioxide concentration in the atmosphere is an issue of paramount importance that needs immediate attention. CO2 capture and sequestration (CCS) is a promising route to mitigate climate change and adsorption is the most widely recognized technology owing to possible energy savings relative to the conventional absorption techniques. In this conference, the potential of a new family of solid sorbents for CO2 capture and separation will be presented. Novel pyridinium containing poly(ionic liquid)s (PILs) were synthesized with varying anions i.e bis(trifluoromethylsulfonyl)imide and hexafluorophosphate. The resulting polymers were characterized using NMR, XRD, TGA, BET surface area and microscopic techniques. Furthermore, CO2 adsorption measurements at two different temperatures were also carried out and revealed great potential of these PILs as CO2 scavengers.

Keywords: climate change, CO2 capture, poly(ionic liquid)s, CO2/N2 selectivity

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Authors: F. Rahimi Dehgolan, M. Behzadi, J. Fathi Sola

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In this article, the Johnson-Cook material model’s constants for structural steel ST.37 have been determined by a method which integrates experimental tests, numerical simulation, and optimization. In the first step, a quasi-static test was carried out on a plain specimen. Next, the constants were calculated for it by minimizing the difference between the results acquired from the experiment and numerical simulation. Then, a quasi-static tension test was performed on three notched specimens with different notch radii. At last, in order to verify the results, they were used in numerical simulation of notched specimens and it was observed that experimental and simulation results are in good agreement. Changing the diameter size of the plain specimen in the necking area was set as the objective function in the optimization step. For final validation of the proposed method, diameter variation was considered as a parameter and its sensitivity to a change in any of the model constants was examined and the results were completely corroborating.

Keywords: constants, Johnson-Cook material model, notched specimens, quasi-static test, sensitivity

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Authors: Kedarnath Awati

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Some parallels between Indian Art Music and Western Art Music, such as the identity of the basic heptatonic scale structure, are quite obvious and need no further discussion. Other parallels are far less obvious, and it is one of them that the author is interested in. Specifically, the author would like to make a serious claim that in both types of music, there is an unspoken dependence on melody. Yes, it is true that the techniques that the two systems use for elaboration are very, very different: Western music uses the techniques of harmony, counterpoint, orchestration and motivic variation, while the Indian systems, both the Hindustani and the Carnatic traditions use the technique of raagdaari. The reason that this point is barely spoken about is that both in the West as well as in India, artists tend to think of melody as something elementary or as something 'given'. The Indian musicians would much rather dwell upon this or that meend or taan or other technical device, while the West thinks that melody is passé and would rather discuss the merits and demerits of spectralism and perhaps serialism. The author would like to explore this theme further in his paper.

Keywords: Indian art music, Western art music, melody, raagdaari, motivic variation.

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Authors: John E. Boberg, Steven J. Bourgeois

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The decline in student engagement and motivation through the middle years is well documented and clearly associated with a decline in mathematics achievement that persists through high school. To combat this trend and, very often, to meet high-stakes accountability standards, a growing number of parents, teachers, and schools have implemented various methods to incentivize learning. However, according to Self-Determination Theory, forms of incentivized learning such as public praise, tangible rewards, or threats of punishment tend to undermine intrinsic motivation and learning. By focusing on external forms of motivation that thwart autonomy in children, adults also potentially threaten relatedness measures such as trust and emotional engagement. Furthermore, these controlling motivational techniques tend to promote shallow forms of cognitive engagement at the expense of more effective deep processing strategies. Therefore, any short-term gains in apparent engagement or test scores are overshadowed by long-term diminished motivation, resulting in inauthentic approaches to learning and lower achievement. The current study focuses on the relationships between student trust, engagement, and motivation during these crucial years as students transition from elementary to middle school. In order to test the effects of controlled motivational techniques on achievement in mathematics, this quantitative study was conducted on a convenience sample of 22 elementary and middle schools from a single public charter school district in the south-central United States. The study employed multi-source data from students (N = 1,054), parents (N = 7,166), and teachers (N = 356), along with student achievement data and contextual campus variables. Cross-sectional questionnaires were used to measure the students’ self-regulated learning, emotional and cognitive engagement, and trust in teachers. Parents responded to a single item on incentivizing the academic performance of their child, and teachers responded to a series of questions about their acceptance of various incentive strategies. Structural equation modeling (SEM) was used to evaluate model fit and analyze the direct and indirect effects of the predictor variables on achievement. Although a student’s trust in teacher positively predicted both emotional and cognitive engagement, none of these three predictors accounted for any variance in achievement in mathematics. The parents’ use of incentives, on the other hand, predicted a student’s perception of his or her controlled motivation, and these two variables had significant negative effects on achievement. While controlled motivation had the greatest effects on achievement, parental incentives demonstrated both direct and indirect effects on achievement through the students’ self-reported controlled motivation. Comparing upper elementary student data with middle-school student data revealed that controlling forms of motivation may be taking their toll on student trust and engagement over time. While parental incentives positively predicted both cognitive and emotional engagement in the younger sub-group, such forms of controlling motivation negatively predicted both trust in teachers and emotional engagement in the middle-school sub-group. These findings support the claims, posited by Self-Determination Theory, about the dangers of incentivizing learning. Short-term gains belie the underlying damage to motivational processes that lead to decreased intrinsic motivation and achievement. Such practices also appear to thwart basic human needs such as relatedness.

Keywords: controlled motivation, student engagement, incentivized learning, mathematics achievement, self-determination theory, student trust

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Authors: Obeida Aiche, Mohamed Khiatine, Medjnoun Amal, Ramdane Bahar

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Soil compaction is one of the most challenging tasks in the construction of road embankments, railway platforms, and earth dams. Stability and durability are mainly related to the nature of the materials used and the type of soil in place. However, nature does not always offer the engineer materials with the right water content, especially in arid and semi-arid regions where obtaining the optimum Proctor water content requires the addition of considerable quantities of water. The current environmental context does not allow for the rational use of water, especially in arid and semi-arid regions, where it is preferable to preserve water resources for the benefit of the local population. Low water compaction can be an interesting approach as it promotes the reuse of earthworks materials in their dry or very dry state. Thanks to techniques in the field of soil compaction, such as vibratory compactors, which have made it possible to increase the compaction energy considerably, it is possible for some materials to obtain a satisfactory quality by compacting at low water contents or at least lower than the optimum determined by the Proctor test. This communication deals with the low water content compaction of soils in the semi-arid zone of the Chlef region in Algeria by increasing the compaction energy.

Keywords: compaction, soil, low water content, compaction energy

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: O. J. Akinsola, Yinan Zheng, Rose Anorlu, F. T. Ogunsola, Lifang Hou, Robert Leo-Murphy

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Cervical Cancer (CC) is the 2nd most common cancer among women living in low and middle-income countries, with no associated symptoms during formative periods. With the advancement and innovative medical research, there are numerous preventive measures being utilized, but the incidence of cervical cancer cannot be truncated with the application of only screening tests. The mortality associated with this invasive cervical cancer can be nipped in the bud through the important role of early-stage detection. This study research selected an array of different top features selection techniques which was aimed at developing a model that could validly diagnose the risk factors of cervical cancer. A retrospective clinic-based cohort study was conducted on 178 HIV-associated cervical cancer patients in Lagos University teaching Hospital, Nigeria (U54 data repository) in April 2022. The outcome measure was the automated prediction of the HIV-associated cervical cancer cases, while the predictor variables include: demographic information, reproductive history, birth control, sexual history, cervical cancer screening history for invasive cervical cancer. The proposed technique was assessed with R and Python programming software to produce the model by utilizing the classification algorithms for the detection and diagnosis of cervical cancer disease. Four machine learning classification algorithms used are: the machine learning model was split into training and testing dataset into ratio 80:20. The numerical features were also standardized while hyperparameter tuning was carried out on the machine learning to train and test the data. Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN). Some fitting features were selected for the detection and diagnosis of cervical cancer diseases from selected characteristics in the dataset using the contribution of various selection methods for the classification cervical cancer into healthy or diseased status. The mean age of patients was 49.7±12.1 years, mean age at pregnancy was 23.3±5.5 years, mean age at first sexual experience was 19.4±3.2 years, while the mean BMI was 27.1±5.6 kg/m2. A larger percentage of the patients are Married (62.9%), while most of them have at least two sexual partners (72.5%). Age of patients (OR=1.065, p<0.001**), marital status (OR=0.375, p=0.011**), number of pregnancy live-births (OR=1.317, p=0.007**), and use of birth control pills (OR=0.291, p=0.015**) were found to be significantly associated with HIV-associated cervical cancer. On top ten 10 features (variables) considered in the analysis, RF claims the overall model performance, which include: accuracy of (72.0%), the precision of (84.6%), a recall of (84.6%) and F1-score of (74.0%) while LR has: an accuracy of (74.0%), precision of (70.0%), recall of (70.0%) and F1-score of (70.0%). The RF model identified 10 features predictive of developing cervical cancer. The age of patients was considered as the most important risk factor, followed by the number of pregnancy livebirths, marital status, and use of birth control pills, The study shows that data mining techniques could be used to identify women living with HIV at high risk of developing cervical cancer in Nigeria and other sub-Saharan African countries.

Keywords: associated cervical cancer, data mining, random forest, logistic regression

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Authors: Mohammed Mamdouh Mohammed, Ali Zain Elabdeen Heikal, Hassan Mahdy, Sherif El-Badawy

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The main purpose of this research is to assess the effectiveness of the Cold In-Place Recycling (CIR) technique in asphalt maintenance by analyzing performance outcomes. To achieve this, fifteen CIR mixtures were prepared using slow-setting emulsified asphalt as the recycling agent, with percentages ranging from 2% to 4% in 0.5% increments. Additionally, pure water was incorporated in percentages ranging from 2% to 4% in 1% increments, and Portland cement was added at a constant content of 1%. The components were mixed at room temperature and subsequently compacted using a gyratory compactor with 150 gyrations. Prior to testing, the samples underwent a two-stage treatment process: initially, they were placed in an oven at 60°C for 48 hours, followed by a 24-hour period of air curing. The Hamburg wheel tracking test was performed to evaluate the samples’ resistance to rutting. Additionally, the Indirect Tensile Strength (ITS) test and the Semi-Circular Beam (SCB) test were conducted to assess their resistance to cracking. Upon analyzing the test results, it was observed that the samples’ resistance to rutting decreased with higher asphalt and moisture content. In contrast, ITS and SCB tests revealed that the samples’ resistance to cracking initially increased with higher asphalt and moisture content, peaking at a certain point, and then decreased, forming a bell-curve pattern.

Keywords: cold in-place, indirect tensile strength, recycling, emulsified asphalt, semi-circular beam

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Authors: Gebreegziabher Hailu

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This paper presents the development of residual power series methods aimed at efficiently solving stiff differential equations, which pose significant challenges in numerical analysis due to their rapid changes in solution behavior. The RPSM is a numerical approach that generates polynomial-based approximate solutions without the need for linearization, discretization, or perturbation techniques, making it straightforward to implement and less prone to computational errors. We introduce an approach that utilizes power series expansions combined with residual minimization techniques to enhance convergence and stability. By analyzing the theoretical foundations of stiffness, we delve into the formulation of the residual power series method, detailing how it effectively captures the dynamics of stiff systems while maintaining computational efficiency. Numerical experiments demonstrate the method's superiority in terms of accuracy and computational cost when compared to traditional methods like implicit Runge-Kutta or multistep techniques. We also explore adaptive strategies within our framework to automatically adjust parameters based on the stiffness characteristics of the problem at hand. Ultimately, our findings contribute to the broader toolkit for tackling stiff differential equations, offering a robust alternative that promises to streamline computational workflows in various applied mathematics and engineering contexts.

Keywords: residual power series methods, stiff differential equoations, numerical approach, Runge Kutta methods

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Authors: Ayman M. M. Abdelhaleem, Mustafa Gamal Sadek, Kamal Reyad, Montasser M. Dewidar

Abstract:

The main objective of this research is to study the effect of adding polycarbonate (PC) to pure Acrylonitrile Butadiene Styrene (ABS) using the injection moulding process. The PC was mixed mechanically with ABS in 10%, 20%, 30%, 40%, and 50% by weight. The mechanical properties of pure ABS reinforced with PC were investigated using tensile, impact, hardness, and wear tests. The results showed that, by adding 10%, 20%, 30%, 40%, and 50% wt. of PC to the pure ABS, the ultimate tensile strength increased from 55 N/mm2 for neat ABS to 57 N/mm2 (i.e. 3.63%), 60 N/mm2 (i.e. 9.09%), 63 N/mm2 (i.e. 14.54%), 66 N/mm2 (i.e. 20%), 69 N/mm2 (i.e. 25.45%) respectively. Test results also revealed nearly 5.72% improvement in young's modulus by adding 10% of PC to ABS, 16.74% improvement by adding 20%, 23.34% improvement by adding 30%, 27.75% improvement by adding 40%, and no other increase in case of 50%. The impact test results showed that with the increase of the PC content, first, the impact strength decreased and then increased gradually. The impact strength decreased rapidly when the content of PC was 0% to 10% range. As well as, in the case of 20%, 30%, 40%, and 50% PC, the impact strength is increased. The hardness test results, using the Shore D tester, showed that, as the PC particles contents increased, the hardness increased from 76 for the ABS to 80 for 10% PC, and decreased to 79 for 20% PC, and then increased to 80 in case of 30%, 40%, and 50% PC. Wear test results showed that PC improves the wear resistance of ABS/PC blends. Positron annihilation lifetime spectroscopy showed that with an increase of PC in ABS/PC blends, a slight decrease in free volume size and an increase in the tensile strength due to good adhesion between PC and ABS matrix, which acted as an advantage in the polymer matrix.

Keywords: ABS, PC, injection molding process, mechanical properties, lifetime spectroscopy

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Authors: Manal Kamel, Sara Maher, Hanan El Baz, Faten Salah, Omar Sayyouh, Zeinab Demerdash

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In the recent COVID 19 pandemic, experts of public health have emphasized testing, tracking infected people, and tracing their contacts as an effective strategy to reduce the spread of the virus. Development of rapid and sensitive diagnostic assays to replace reverse transcription polymerase chain reaction (RT-PCR) is mandatory..Our innovative test strip relying on the application of nanoparticles conjugated to recombinant nanobodies for SARS-COV-2 spike protein (S1) & angiotensin-converting enzyme 2 (that is responsible for the virus entry into host cells) for rapid detection of SARS-COV-2 spike protein (S1) in saliva or sputum specimens. Comparative tests with RT-PCR will be held to estimate the significant effect of using COVID 19 nanobodies for the first time in the development of lateral flow test strip. The SARS-CoV-2 S1 (3 ng of recombinant proteins) was detected by our developed LFIA in saliva specimen of COVID-19 Patients No cross-reaction was detected with Middle East respiratory syndrome coronavirus (MERS-CoV) or SARS- CoV antigens..Our developed system revealed 96 % sensitivity and 100% specificity for saliva samples compared to 89 % and 100% sensitivity and specificity for nasopharyngeal swabs. providing a reliable alternative for the painful and uncomfortable nasopharyngeal swab process and the complexes, time consuming PCR test. An increase in testing compliances to be expected.

Keywords: COVID 19, diagnosis, LFIA, nanobodies, ACE2

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Sabuj Mallik

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The emerging approaches to sustainable manufacturing are considered to be solution-oriented with the aim of addressing the environmental, economic and social issues holistically. However, the analysis of the interdependencies amongst the three sustainability dimensions has not been fully captured in the literature. In a recent review of approaches to sustainable manufacturing, two categories of techniques are identified: 1) Sustainable Product Development (SPD), and 2) Sustainability Performance Assessment (SPA) techniques. The challenges of the approaches are not only related to the arguments and misconceptions of the relationships between the techniques and sustainable development but also to the inability to capture and integrate the three sustainability dimensions. This requires a clear definition of some of the approaches and a road-map to the development of a holistic approach that supports sustainability decision-making. In this context, eco-innovation, social impact assessment, and life cycle sustainability analysis play an important role. This paper deployed an integrative approach that enabled amalgamation of sustainable manufacturing approaches and the theories of reciprocity and motivation into a holistic simulation-based impact analysis framework. The findings in this research have the potential to guide sustainability analysts to capture the aspects of the three sustainability dimensions into an analytical model. Additionally, the research findings presented can aid the construction of a holistic simulation model of a sustainable manufacturing and support effective decision-making.

Keywords: life cycle sustainability analysis, sustainable manufacturing, sustainability performance assessment, sustainable product development

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Authors: Tosin Ige

Abstract:

Ethics must be a condition of the world, like logic. (Ludwig Wittgenstein, 1889-1951). As important as data mining is, it possess a significant threat to ethics, privacy, and legality, since data mining makes it difficult for an individual or consumer (in the case of a company) to control the accessibility and usage of his data. This research focuses on Current issues and the latest research and development on Privacy preserving data mining methods as at year 2022. It also discusses some advances in those techniques while at the same time highlighting and providing a new technique as a solution to an existing technique of privacy preserving data mining methods. This paper also bridges the wide gap between Data mining and the Web Application Programing Interface (web API), where research is urgently needed for an added layer of security in data mining while at the same time introducing a seamless and more efficient way of data mining.

Keywords: data, privacy, data mining, association rule, privacy preserving, mining technique

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Authors: Shajida M., Sakthiyadharshini N. P., Kamalesh S., Aswitha B.

Abstract:

Natural Language Processing (NLP) continues to play a strategic part in complaint discovery and medicine discovery during the current epidemic. This abstract provides an overview of performance analysis with a combination of visualization and classification techniques of NLP for a medical chatbot. Sentiment analysis is an important aspect of NLP that is used to determine the emotional tone behind a piece of text. This technique has been applied to various domains, including medical chatbots. In this, we have compared the combination of the decision tree with heatmap and Naïve Bayes with Word Cloud. The performance of the chatbot was evaluated using accuracy, and the results indicate that the combination of visualization and classification techniques significantly improves the chatbot's performance.

Keywords: sentimental analysis, NLP, medical chatbot, decision tree, heatmap, naïve bayes, word cloud

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Authors: Yuri V. Kim

Abstract:

This article presents a new approach to the Functional Testing of Space Systems (SS). It can be considered as a generic test and used for a wide class of SS that from the point of view of System Dynamics and Control may be described by the ordinary differential equations. Suggested methodology is based on using semi-natural experiment- laboratory stand that doesn’t require complicated, precise and expensive technological control-verification equipment. However, it allows for testing system as a whole totally assembled unit during Assembling, Integration and Testing (AIT) activities, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data is then inserted in laboratory PC where it is post-experiment processed by Matlab/Simulink Identification Toolbox. It allows for estimating system dynamics in form of estimation of system differential equations by the experimental way and comparing them with expected mathematical model prematurely verified by mathematical simulation during the design process.

Keywords: system dynamics, space system ground tests and space qualification, system dynamics identification, satellite attitude control, assembling, integration and testing

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Authors: Ádám Vass, István Bakos, Irina Borbáth, Zoltán Pászti, István Sajó, András Tompos

Abstract:

Important requirements for the anode side electrocatalysts of polymer electrolyte membrane (PEM) fuel cells are CO-tolerance, stability and corrosion resistance. Carbon is still the most common material for electrocatalyst supports due to its low cost, high electrical conductivity and high surface area, which can ensure good dispersion of the Pt. However, carbon becomes degraded at higher potentials and it causes problem during application. Therefore it is important to explore alternative materials with improved stability. Molybdenum-oxide can improve the CO-tolerance of the Pt/C catalysts, but it is prone to leach in acidic electrolyte. The Mo was stabilized by isovalent substitution of molybdenum into the rutile phase titanium-dioxide lattice, achieved by a modified multistep sol-gel synthesis method optimized for preparation of Ti0.7Mo.3O2-C composite. High degree of Mo incorporation into the rutile lattice was developed. The conductivity and corrosion resistance across the anticipated potential/pH window was ensured by mixed oxide – activated carbon composite. Platinum loading was carried out using NaBH4 and ethylene glycol; platinum content was 40 wt%. The electrocatalyst was characterized by both material investigating methods (i.e. XRD, TEM, EDS, XPS techniques) and electrochemical methods (cyclic-voltammetry, COads stripping voltammetry, hydrogen oxidation reaction on rotating disc electrode). The electrochemical activity of the sample was compared to commercial 40 wt% Pt/C (Quintech) and PtRu/C (Quintech, Pt= 20 wt%, Ru= 10 wt%) references. Enhanced CO tolerance of the electrocatalyst prepared using the Ti0.7Mo.3O2-C composite material was evidenced by the appearance of a CO-oxidation related 'pre-peak' and by the pronounced shift of the maximum of the main CO oxidation peak towards less positive potential compared to Pt/C. Fuel cell polarization measurements were also carried out using Bio-Logic and Paxitech FCT-150S test device. All details on the design, preparation, characterization and testing by both electrochemical measurements and fuel cell test device of electrocatalyst supported on Ti0.7Mo.3O2-C composite material will be presented and discussed.

Keywords: anode electrocatalyst, composite material, CO-tolerance, TiMoOx

Procedia PDF Downloads 300