Search results for: academic performance prediction
16107 Barriers to Teachers' Use of Technology in Nigeria and Its Implications in the Academic Performance of Students of Higher Learning: A Case Study of Adeniran Ogunsanya College of Education, Lagos
Authors: Iyabo Aremu
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The role of the teacher in stirring a qualitative and distinctive knowledge-driven and value-laden environment with modern teaching practices cannot be over accentuated. In spite of the myriad advantages the use of Information and Communication Technology (ICT) promises, many teachers are still at the rear of this archetypical transition. These teachers; notable forces needed to elicit positive academic performances of students of higher learning are ill-equipped for the task. In view of this, the research work sought to assess how teachers have been able to effectively apply ICT tools to improve students’ academic performance in the higher institution and to evaluate the challenges faced by teachers in using these tools. Thus, the research adopted descriptive survey research design and involved a sample of 25 lecturers from five schools in the study area: Adeniran Ogunsanya College of Education (AOCOED). The barrier to Teachers’ Use of ICT Questionnaire (BTUICTQ) was used to gather data from these respondents. The data gathered was tested with chi-square at 0.05 level of significance. The results revealed that the perception and attitude of teachers towards the use of ICT is not favourable. It was also discovered that teachers suffer from gaps in ICT knowledge and skills. Finally, the research showed that lack of training and inadequate support is a major challenge teacher contend with. The study recommended that teachers should be given adequate training and support and that teachers’ unrestricted access to ICT gadgets should be ensured by schools.Keywords: ICT, teachers, AOCOED, academic performance
Procedia PDF Downloads 15516106 Design and Burnback Analysis of Three Dimensional Modified Star Grain
Authors: Almostafa Abdelaziz, Liang Guozhu, Anwer Elsayed
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The determination of grain geometry is an important and critical step in the design of solid propellant rocket motor. In this study, the design process involved parametric geometry modeling in CAD, MATLAB coding of performance prediction and 2D star grain ignition experiment. The 2D star grain burnback achieved by creating new surface via each web increment and calculating geometrical properties at each step. The 2D star grain is further modified to burn as a tapered 3D star grain. Zero dimensional method used to calculate the internal ballistic performance. Experimental and theoretical results were compared in order to validate the performance prediction of the solid rocket motor. The results show that the usage of 3D grain geometry will decrease the pressure inside the combustion chamber and enhance the volumetric loading ratio.Keywords: burnback analysis, rocket motor, star grain, three dimensional grains
Procedia PDF Downloads 23416105 Investigating Self-Confidence Influence on English as a Foreign Language Student English Language Proficiency Level
Authors: Ali A. Alshahrani
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This study aims to identify Saudi English as a Foreign Language (EFL) students' perspectives towards using the English language in their studies. The study explores students' self-confident and its association with students' actual performance in English courses in their different academic programs. A multimodal methodology was used to fulfill the research purpose and answer the research questions. A 25-item survey questionnaire and final examination grades were used to collect data. Two hundred forty-one students agreed to participate in the study. They completed the questionnaire and agreed to release their final grades to be a part of the collected data. The data were coded and analyzed by SPSS software. The findings indicated a significant difference in students' performance in English courses between participants' academic programs on the one hand. Students' self-confidence in their English language skills, on the other hand, was not significantly different between participants' academic programs. Data analysis also revealed no correlational relationship between students' self-confidence level and their language skills and their performance. The study raises more questions about other vital factors such as course instructors' views of the materials, faculty members of the target department, family belief in the usefulness of the program, potential employers. These views and beliefs shape the student's preparation process and, therefore, should be explored further.Keywords: English language intensive program, language proficiency, performance, self-confidence
Procedia PDF Downloads 13016104 Preparing Faculty to Deliver Academic Continuity during and after a Disaster
Authors: Melissa Houston
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Political pressures, financial restraints, and recent legislation has led to administrators’ at academic institutions to rely upon online education as a viable means for delivering education to students anytime and anywhere. Administrators at academic institutions have utilized online education as a way to ensure that academic continuity takes place while campuses are physically closed or are recovering from damages during and after disaster. There is a gap in the research as to how to best train faculty for academic continuity during and after disasters occur. The lack of available research regarding how faculty members at academic institutions prepared themselves prior to a disaster served as a major rationale for this study. The problem that was addressed in this phenomenological study was to identify the training needed by faculty to provide academic continuity during and after times of disaster. The purpose of the phenomenological study was to provide further knowledge and understanding of the training needed by faculty to provide academic continuity after a disaster. Data collection from this study will help human resource professionals as well as administrators of academic institutions to better prepare faculty to provide academic continuity in the future. Participants were recruited on LinkedIn and were qualified as having been faculty who taught traditional courses during or after a disaster. Faculty members were asked a series of open-ended questions to gain understanding of their experiences of how they acquired training for themselves for academic continuity during and after a disaster. The findings from this study showed that faculty members identified assistance needed including professional development in the form of training and support, communication, and technological resources in order to provide academic continuity. The first conclusion from this study was that academic institutions need to support their students, staff and faculty with disaster training and the resources needed to provide academic continuity during and after disasters. The second conclusion from this study is that while disasters and other academic institution incidents are occurring more frequently, limited funding and the push for online education has created limited resources for academic institutions. The need to create partnerships and consortiums with other academic institutions and communities is crucial for the success and sustainability of academic institutions. Through these partnerships and consortiums academic institutions can share resources, knowledge, and training.Keywords: training, faculty, disaster, academic continuity
Procedia PDF Downloads 18316103 Effect of Instructional Materials on Academic Performance in Heat Transfer Concept among Secondary School Physics Students in Fagge Educational Zone, Kano State, Nigeria
Authors: Shehu Aliyu
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This study investigated the effects of instructional materials on academic achievement among senior secondary school students on the concept of Heat Transfer in physics in Fagge Educational Zone, Kano State Nigeria. The population consisted of SSII students from 10 public schools. Out of this, 87 students were randomly selected from which 24 males and 22 females formed the experimental group and 41 students as control group. A quasi experiential design with pretest and post-test for both the groups was adopted. Two research questions and null hypotheses guided the conduct of the study. The experimental group was exposed to teaching using instructional materials while the control group was taught using the normal lecture mode. Head Transfer Performance Test (HTPT) was used for data collection. The instrument was validated by experts in the science education field. A Pearson Product Moment Correlation (PPMC) was used to determine the reliability co-efficient and was found to be r=0.83. The research questions were answered using descriptive statistics while the hypotheses were tested at p≤ 0.05 level of significance using t-test. The result obtained from the data analysis showed that students in experimental group performed significantly better than those in the control group and that there was no significant difference in the academic performance between male and female students in the experimental group. Based on the findings of this study, it was recommended among others that the physics teachers should be receiving regular training on the importance of using instructional materials whether ready made or improved in their teaching.Keywords: heat transfer, physics, instructional materials, academic performance
Procedia PDF Downloads 17516102 Integrating Life Skills Education for Mental Health and Academic Benefits of Adolescents in Schools in Schools
Authors: Sarwat Sultan, Muhammad Saleem, Frasat Kanwal
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Adolescence is a transition period of life that brings physical and psychological changes and always results in several challenges for an adolescent. An adolescent must learn life skills for a healthy transition from adolescence period to adulthood. Therefore this study was planned to examine the effects of life skill education on adolescents' mental health and academic benefits. A random sample of 720 school students aged between 13-17 years was categorized into two groups; experimental (n=360) and control (n=360). Life skill education was given to the students of the intervention group with repeated assessments of mental health and academic benefits at pre-intervention (T1) and post-intervention (T2) for both groups. Both groups were compared on scores of mental health and academic benefits across two times T1 and T2 by employing a mixed between-within-subjects analysis of variance. Findings showed the main effect of time suggesting the largest changes in mental health and academic benefits over time. Interaction effects between time and both groups were also found significant indicating the largest changes across time between both groups. Results of between-group comparisons showed significant values for Wilks’ Lambda and partial eta squared for students of the intervention group who scored higher on mental health and academic benefits after receiving life skills training than the students of the control group. Results of the present study determined the efficacy of life skill education and have implications for both teachers and psychotherapists to improve the students’ mental health and academic performance.Keywords: academic benefits, life skills, mental health, adolescents
Procedia PDF Downloads 5216101 An Improved Prediction Model of Ozone Concentration Time Series Based on Chaotic Approach
Authors: Nor Zila Abd Hamid, Mohd Salmi M. Noorani
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This study is focused on the development of prediction models of the Ozone concentration time series. Prediction model is built based on chaotic approach. Firstly, the chaotic nature of the time series is detected by means of phase space plot and the Cao method. Then, the prediction model is built and the local linear approximation method is used for the forecasting purposes. Traditional prediction of autoregressive linear model is also built. Moreover, an improvement in local linear approximation method is also performed. Prediction models are applied to the hourly ozone time series observed at the benchmark station in Malaysia. Comparison of all models through the calculation of mean absolute error, root mean squared error and correlation coefficient shows that the one with improved prediction method is the best. Thus, chaotic approach is a good approach to be used to develop a prediction model for the Ozone concentration time series.Keywords: chaotic approach, phase space, Cao method, local linear approximation method
Procedia PDF Downloads 32216100 Health Hazards of Performance Enhancing Drugs
Authors: Austin Oduor Otieno
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There is an ingrained belief that the use of performance-enhancing drugs by athletes enable them to perform better. While this has been found to be truth, it also raises ethical and health issues. This paper analyzes the health hazards associated with performance enhancing drugs. It seeks to achieve this through the analysis of different academic journals as well as publications on the relationship between doping in sports and health. It concludes that there are inherent health hazards associated with the use of performance-enhancing drugs as they affect the physical and psychological health and wellbeing of a user (athlete).Keywords: doping, health hazards, athletes, drugs
Procedia PDF Downloads 15416099 A Generalized Model for Performance Analysis of Airborne Radar in Clutter Scenario
Authors: Vinod Kumar Jaysaval, Prateek Agarwal
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Performance prediction of airborne radar is a challenging and cumbersome task in clutter scenario for different types of targets. A generalized model requires to predict the performance of Radar for air targets as well as ground moving targets. In this paper, we propose a generalized model to bring out the performance of airborne radar for different Pulsed Repetition Frequency (PRF) as well as different type of targets. The model provides a platform to bring out different subsystem parameters for different applications and performance requirements under different types of clutter terrain.Keywords: airborne radar, blind zone, clutter, probability of detection
Procedia PDF Downloads 46316098 Comparing the Contribution of General Vocabulary Knowledge and Academic Vocabulary Knowledge to Learners' Academic Achievement
Authors: Reem Alsager, James Milton
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Coxhead’s (2000) Academic Word List (AWL) believed to be essential for students pursuing higher education and helps differentiate English for Academic Purposes (EAP) from General English as a course of study, and it is thought to be important for comprehending English academic texts. It has been described that AWL is an infrequent, discrete set of vocabulary items unreachable from general language. On the other hand, it has been known for a period of time that general vocabulary knowledge is a good predictor of academic achievement. This study, however, is an attempt to measure and compare the contribution of academic knowledge and general vocabulary knowledge to learners’ GPA and examine what knowledge is a better predictor of academic achievement and investigate whether AWL as a specialised list of infrequent words relates to the frequency effect. The participants were comprised of 44 international postgraduate students in Swansea University, all from the School of Management, following the taught MSc (Master of Science). The study employed the Academic Vocabulary Size Test (AVST) and the XK_Lex vocabulary size test. The findings indicate that AWL is a list based on word frequency rather than a discrete and unique word list and that the AWL performs the same function as general vocabulary, with tests of each found to measure largely the same quality of knowledge. The findings also suggest that the contribution that AWL knowledge provides for academic success is not sufficient and that general vocabulary knowledge is better in predicting academic achievement. Furthermore, the contribution that academic knowledge added above the contribution of general vocabulary knowledge when combined is really small and noteworthy. This study’s results are in line with the argument and suggest that it is the development of general vocabulary size is an essential quality for academic success and acquiring the words of the AWL will form part of this process. The AWL by itself does not provide sufficient coverage, and is probably not specialised enough, for knowledge of this list to influence this general process. It can be concluded that AWL as an academic word list epitomizes only a fraction of words that are actually needed for academic success in English and that knowledge of academic vocabulary combined with general vocabulary knowledge above the most frequent 3000 words is what matters most to ultimate academic success.Keywords: academic achievement, academic vocabulary, general vocabulary, vocabulary size
Procedia PDF Downloads 21516097 Inferring Human Mobility in India Using Machine Learning
Authors: Asra Yousuf, Ajaykumar Tannirkulum
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Inferring rural-urban migration trends can help design effective policies that promote better urban planning and rural development. In this paper, we describe how machine learning algorithms can be applied to predict internal migration decisions of people. We consider data collected from household surveys in Tamil Nadu to train our model. To measure the performance of the model, we use data on past migration from National Sample Survey Organisation of India. The factors for training the model include socioeconomic characteristic of each individual like age, gender, place of residence, outstanding loans, strength of the household, etc. and his past migration history. We perform a comparative analysis of the performance of a number of machine learning algorithm to determine their prediction accuracy. Our results show that machine learning algorithms provide a stronger prediction accuracy as compared to statistical models. Our goal through this research is to propose the use of data science techniques in understanding human decisions and behaviour in developing countries.Keywords: development, migration, internal migration, machine learning, prediction
Procedia PDF Downloads 26616096 EFL Teachers’ Metacognitive Awareness as a Predictor of Their Professional Success
Authors: Saeedeh Shafiee Nahrkhalaji
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Metacognitive knowledge increases EFL students’ ability to be successful learners. Although this relationship has been investigated by a number of scholars, EFL teachers’ explicit awareness of their cognitive knowledge has not been sufficiently explored. The aim of this study was to examine the role of EFL teachers’ metacognitive knowledge in their pedagogical performance. Furthermore, the role played by years of their academic education and teaching experience was also studied. Fifty female EFL teachers were selected. They completed Metacognitive Awareness Inventory (MAI) that assessed six components of metacognition including procedural knowledge, declarative knowledge, conditional knowledge, planning, evaluating, and management strategies. Near the end of the academic semester, the students of each class filled in ‘the Language Teacher Characteristics Questionnaire’ to evaluate their teachers’ pedagogical performance. Four elements of MAI, declarative knowledge, planning, evaluating, and management strategies were found to be significantly correlated with EFL teachers’ pedagogical success. Significant correlation was also established between metacognitive knowledge and EFL teachers’ years of academic education and teaching experience. The findings obtained from this research have contributing implication for EFL teacher educators. The discussion concludes by setting out directions for future research.Keywords: metacognotive knowledge, pedagogical performance, language teacher characteristics questionnaire, metacognitive awareness inventory
Procedia PDF Downloads 32316095 A Study on the Life Prediction Performance Degradation Analysis of the Hydraulic Breaker
Authors: Jong Won, Park, Sung Hyun, Kim
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The kinetic energy to pass subjected to shock and chisel reciprocating piston hydraulic power supplied by the excavator using for the purpose of crushing the rock, and roads, buildings, etc., hydraulic breakers blow. Impact frequency, efficiency measurement of the impact energy, hydraulic breakers, to demonstrate the ability of hydraulic breaker manufacturers and users to a very important item. And difficult in order to confirm the initial performance degradation in the life of the hydraulic breaker has been thought to be a problem.In this study, we measure the efficiency of hydraulic breaker, Impact energy and Impact frequency, the degradation analysis of research to predict the life.Keywords: impact energy, impact frequency, hydraulic breaker, life prediction
Procedia PDF Downloads 43016094 Stock Movement Prediction Using Price Factor and Deep Learning
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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.Keywords: classification, machine learning, time representation, stock prediction
Procedia PDF Downloads 14016093 Various Factors Affecting Students Performances In A Saudi Medical School
Authors: Raneem O. Salem, Najwa Al-Mously, Nihal Mohamed Nabil, Abdulmohsen H. Al-Zalabani, Abeer F. Al-Dhawi, Nasser Al-Hamdan
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Objective: There are various demographic and educational factors that affect the academic performance of undergraduate medical students. The objective of this study is to identify these factors and correlate them to the GPA of the students. Methods: A cross-sectional study design utilizing grade point averages (GPAs) of two cohorts of students in both levels of the pre-clinical phase. In addition, self-administered questionnaire was used to evaluate the effect of these factors on students with poor and good cumulative GPA. Results: Among the various factors studied, gender, marital status, and the transportation used to reach the faculty significantly affected academic performance of students. Students with a cumulative GPA of 3.0 or greater significantly differed than those with a GPA of less than 3.0 being higher in female students, in married students, and type of transportation used to reach the college. Factors including age, educational factors, and type of transportation used have shown to create a significant difference in GPA between male and females. Conclusion: Factors such as age, gender, marital status, learning resources, study time, and the transportation used have been shown to significantly affect medical student GPA as a whole batch as well as when they are tested for gender.Keywords: academic performance, educational factors, learning resources, study time, gender, socio-demographic factors
Procedia PDF Downloads 26616092 Cellular Traffic Prediction through Multi-Layer Hybrid Network
Authors: Supriya H. S., Chandrakala B. M.
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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.Keywords: MLHN, network traffic prediction
Procedia PDF Downloads 8116091 A Study for Area-level Mosquito Abundance Prediction by Using Supervised Machine Learning Point-level Predictor
Authors: Theoktisti Makridou, Konstantinos Tsaprailis, George Arvanitakis, Charalampos Kontoes
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In the literature, the data-driven approaches for mosquito abundance prediction relaying on supervised machine learning models that get trained with historical in-situ measurements. The counterpart of this approach is once the model gets trained on pointlevel (specific x,y coordinates) measurements, the predictions of the model refer again to point-level. These point-level predictions reduce the applicability of those solutions once a lot of early warning and mitigation actions applications need predictions for an area level, such as a municipality, village, etc... In this study, we apply a data-driven predictive model, which relies on public-open satellite Earth Observation and geospatial data and gets trained with historical point-level in-Situ measurements of mosquito abundance. Then we propose a methodology to extract information from a point-level predictive model to a broader area-level prediction. Our methodology relies on the randomly spatial sampling of the area of interest (similar to the Poisson hardcore process), obtaining the EO and geomorphological information for each sample, doing the point-wise prediction for each sample, and aggregating the predictions to represent the average mosquito abundance of the area. We quantify the performance of the transformation from the pointlevel to the area-level predictions, and we analyze it in order to understand which parameters have a positive or negative impact on it. The goal of this study is to propose a methodology that predicts the mosquito abundance of a given area by relying on point-level prediction and to provide qualitative insights regarding the expected performance of the area-level prediction. We applied our methodology to historical data (of Culex pipiens) of two areas of interest (Veneto region of Italy and Central Macedonia of Greece). In both cases, the results were consistent. The mean mosquito abundance of a given area can be estimated with similar accuracy to the point-level predictor, sometimes even better. The density of the samples that we use to represent one area has a positive effect on the performance in contrast to the actual number of sampling points which is not informative at all regarding the performance without the size of the area. Additionally, we saw that the distance between the sampling points and the real in-situ measurements that were used for training did not strongly affect the performance.Keywords: mosquito abundance, supervised machine learning, culex pipiens, spatial sampling, west nile virus, earth observation data
Procedia PDF Downloads 14116090 Groundwater Level Prediction Using hybrid Particle Swarm Optimization-Long-Short Term Memory Model and Performance Evaluation
Authors: Sneha Thakur, Sanjeev Karmakar
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This paper proposed hybrid Particle Swarm Optimization (PSO) – Long-Short Term Memory (LSTM) model for groundwater level prediction. The evaluation of the performance is realized using the parameters: root mean square error (RMSE) and mean absolute error (MAE). Ground water level forecasting will be very effective for planning water harvesting. Proper calculation of water level forecasting can overcome the problem of drought and flood to some extent. The objective of this work is to develop a ground water level forecasting model using deep learning technique integrated with optimization technique PSO by applying 29 years data of Chhattisgarh state, In-dia. It is important to find the precise forecasting in case of ground water level so that various water resource planning and water harvesting can be managed effectively.Keywords: long short-term memory, particle swarm optimization, prediction, deep learning, groundwater level
Procedia PDF Downloads 7016089 Improving Part-Time Instructors’ Academic Outcomes with Gamification
Authors: Jared R. Chapman
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This study introduces a type of motivational information system called an educational engagement information system (EEIS). An EEIS draws on principles of behavioral economics, motivation theory, and learning cognition theory to design information systems that help students want to improve their performance. This study compares academic outcomes for course sections taught by part- and full-time instructors both with and without an EEIS. Without an EEIS, students in the part-time instructor's course sections demonstrated significantly higher failure rates (a 143.8% increase) and dropout rates (a 110.4% increase) with significantly fewer students scoring a B- or higher (39.8% decrease) when compared to students in the course sections taught by a full-time instructor. It is concerning that students in the part-time instructor’s course without an EEIS had significantly lower academic outcomes, suggesting less understanding of the course content. This could impact retention and continuation in a major. With an EEIS, when comparing part- and full-time instructors, there was no significant difference in failure and dropout rates or in the number of students scoring a B- or higher in the course. In fact, with an EEIS, the failure and dropout rates were statistically identical for part- and full-time instructor courses. When using an EEIS (compared with not using an EEIS), the part-time instructor showed a 62.1% decrease in failures, a 61.4% decrease in dropouts, and a 41.7% increase in the number of students scoring a B- or higher in the course. We are unaware of other interventions that yield such large improvements in academic performance. This suggests that using an EEIS such as Delphinium may compensate for part-time instructors’ limitations of expertise, time, or rewards that can have a negative impact on students’ academic outcomes. The EEIS had only a minimal impact on failure rates (7.7% decrease) and dropout rates (18.8% decrease) for the full-time instructor. This suggests there is a ceiling effect for the improvements that an EEIS can make in student performance. This may be because experienced instructors are already doing the kinds of things that an EEIS does, such as motivating students, tracking grades, and providing feedback about progress. Additionally, full-time instructors have more time to dedicate to students outside of class than part-time instructors and more rewards for doing so. Using adjunct and other types of part-time instructors will likely remain a prevalent practice in higher education management courses. Given that using part-time instructors can have a negative impact on student graduation and persistence in a field of study, it is important to identify ways we can augment part-time instructors’ performance. We demonstrated that when part-time instructors use an EEIS, it can result in significantly lower students’ failure and dropout rates and an increase in the rate of students earning a B- or above; and bring their students’ performance to parity with the performance of students taught by a full-time instructor.Keywords: gamification, engagement, motivation, academic outcomes
Procedia PDF Downloads 6316088 Effects of Practical Activities on Performance among Biology Students in Zaria Education Zone, Kaduna State Nigeria
Authors: Abdullahi Garba
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The study investigated the effects of practical activities on performance among biology students in Zaria education zone, Kaduna State, Nigeria. The population consists of 18 public schools in the Zaria Education Zone with a total number of 4,763 students. A random sample of 115 students was selected from the population in the study area. The study design was quasi-experimental, which adopted the pre-test, post-test experimental, and control group design. The experimental group was exposed to practical activities, while the control group was taught with the lecture method. A validated instrument, a biology performance test (BPT) with a reliability coefficient of 0.82, was used to gather data which were analyzed using a t-test and paired sample t-test. Two research questions and hypotheses guided the study. The hypotheses were tested at p≤0.05 level of significance. Findings revealed that: there was a significant difference in the academic performance of students exposed to practical activities compared to their counterparts; there was no significant difference in performance between male and female Biology students exposed to practical activities. The recommendation given was that practical activities should be encouraged in the teaching and learning of Biology for better understanding. The Federal and State Ministry of Education should sponsor biology teachers for training and retraining of teachers to improve the academic performance of students in the subject.Keywords: biology, practical, activity, performance
Procedia PDF Downloads 7316087 Greening the Academic Library: Analysis of the Effectiveness of Sustainable Online Services Towards Reducing the Environmental Impact of Academic Libraries
Authors: George Clifford Yamson
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As institutions across the world become more focused on sustainability, academic libraries are considering ways to reduce their environmental impact. One strategy is the use of sustainable online services, which can reduce the need for physical materials and transportation. This study aims to analyze the effectiveness of sustainable online services in reducing the environmental impact of academic libraries. Using a mixed-methods approach, the survey will be used to solicit information from library staff and users to gather data on their attitudes towards sustainable online services and their usage patterns. A comparative analysis will be conducted on the costs of traditional library services versus sustainable online services. The findings of this study will contribute to the growing body of literature on green academic libraries and provide insights into the potential of sustainable online services to reduce the environmental impact of academic libraries.Keywords: sustainability, environmental sustainability, academic libraries, green printing, green copying, online services
Procedia PDF Downloads 6916086 Assisted Prediction of Hypertension Based on Heart Rate Variability and Improved Residual Networks
Authors: Yong Zhao, Jian He, Cheng Zhang
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Cardiovascular diseases caused by hypertension are extremely threatening to human health, and early diagnosis of hypertension can save a large number of lives. Traditional hypertension detection methods require special equipment and are difficult to detect continuous blood pressure changes. In this regard, this paper first analyzes the principle of heart rate variability (HRV) and introduces sliding window and power spectral density (PSD) to analyze the time domain features and frequency domain features of HRV, and secondly, designs an HRV-based hypertension prediction network by combining Resnet, attention mechanism, and multilayer perceptron, which extracts the frequency domain through the improved ResNet18 features through a modified ResNet18, its fusion with time-domain features through an attention mechanism, and the auxiliary prediction of hypertension through a multilayer perceptron. Finally, the network was trained and tested using the publicly available SHAREE dataset on PhysioNet, and the test results showed that this network achieved 92.06% prediction accuracy for hypertension and outperformed K Near Neighbor(KNN), Bayes, Logistic, and traditional Convolutional Neural Network(CNN) models in prediction performance.Keywords: feature extraction, heart rate variability, hypertension, residual networks
Procedia PDF Downloads 9516085 Teaching Academic Vocabulary: A Recent and Old Approach
Authors: Sara Fine-Meltzer
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An obvious, but ill-addressed hindrance to reading comprehension in academic English is poor vocabulary. Unfortunately, dealing with the problem is usually delayed until university entrance. It is the contention of this paper that the chore should be confronted much earlier and by using a very old-fashioned method. This presentation is accompanied by vocabulary lists for advanced level university students with explanations concerning the content and justification for the 500-word lists: how they change over time in accordance with evolving styles of academic writing. There are also sample quizzes and methods to ensure that the words are “absorbed” over time. There is a discussion of other vocabulary acquisition methods and conclusions drawn from the drawbacks of such methods. The paper concludes with the rationale for beginning the study of “academic” vocabulary earlier than is generally acceptable.Keywords: academic vocabulary, old-fashioned methods, quizzes, vocabulary lists
Procedia PDF Downloads 11616084 Day-To-Day Variations in Health Behaviors and Daily Functioning: Two Intensive Longitudinal Studies
Authors: Lavinia Flueckiger, Roselind Lieb, Andrea H. Meyer, Cornelia Witthauer, Jutta Mata
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Objective: Health behaviors tend to show a high variability over time within the same person. However, most existing research can only assess a snapshot of a person’s behavior and not capture this natural daily variability. Two intensive longitudinal studies examine the variability in health behavior over one academic year and their implications for other aspects of daily life such as affect and academic performance. Can already a single day of increased physical activity, snacking, or improved sleep have beneficial effects? Methods: In two intensive longitudinal studies with up to 65 assessment days over an entire academic year, university students (Study 1: N = 292; Study 2: N = 304) reported sleep quality, physical activity, snacking, positive and negative affect, and learning goal achievement. Results: Multilevel structural equation models showed that on days on which participants reported better sleep quality or more physical activity than usual, they also reported increased positive affect, decreased negative affect, and better learning goal achievement. Higher day-to-day snacking was only associated with increased positive affect. Both, increased day-to-day sleep quality and physical activity were indirectly associated with better learning goal achievement through changes in positive and negative affect; results for snacking were mixed. Importantly, day-to-day sleep quality was a stronger predictor for affect and learning goal achievement than physical activity or snacking. Conclusion: One day of better sleep or more physical activity than usual is associated with improved affect and academic performance. These findings have important implications for low-threshold interventions targeting the improvement of daily functioning.Keywords: sleep quality, physical activity, snacking, affect, academic performance, multilevel structural equation model
Procedia PDF Downloads 57316083 Neural Network Based Approach of Software Maintenance Prediction for Laboratory Information System
Authors: Vuk M. Popovic, Dunja D. Popovic
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Software maintenance phase is started once a software project has been developed and delivered. After that, any modification to it corresponds to maintenance. Software maintenance involves modifications to keep a software project usable in a changed or a changing environment, to correct discovered faults, and modifications, and to improve performance or maintainability. Software maintenance and management of software maintenance are recognized as two most important and most expensive processes in a life of a software product. This research is basing the prediction of maintenance, on risks and time evaluation, and using them as data sets for working with neural networks. The aim of this paper is to provide support to project maintenance managers. They will be able to pass the issues planned for the next software-service-patch to the experts, for risk and working time evaluation, and afterward to put all data to neural networks in order to get software maintenance prediction. This process will lead to the more accurate prediction of the working hours needed for the software-service-patch, which will eventually lead to better planning of budget for the software maintenance projects.Keywords: laboratory information system, maintenance engineering, neural networks, software maintenance, software maintenance costs
Procedia PDF Downloads 34816082 A Multilayer Perceptron Neural Network Model Optimized by Genetic Algorithm for Significant Wave Height Prediction
Authors: Luis C. Parra
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The significant wave height prediction is an issue of great interest in the field of coastal activities because of the non-linear behavior of the wave height and its complexity of prediction. This study aims to present a machine learning model to forecast the significant wave height of the oceanographic wave measuring buoys anchored at Mooloolaba of the Queensland Government Data. Modeling was performed by a multilayer perceptron neural network-genetic algorithm (GA-MLP), considering Relu(x) as the activation function of the MLPNN. The GA is in charge of optimized the MLPNN hyperparameters (learning rate, hidden layers, neurons, and activation functions) and wrapper feature selection for the window width size. Results are assessed using Mean Square Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE). The GAMLPNN algorithm was performed with a population size of thirty individuals for eight generations for the prediction optimization of 5 steps forward, obtaining a performance evaluation of 0.00104 MSE, 0.03222 RMSE, 0.02338 MAE, and 0.71163% of MAPE. The results of the analysis suggest that the MLPNNGA model is effective in predicting significant wave height in a one-step forecast with distant time windows, presenting 0.00014 MSE, 0.01180 RMSE, 0.00912 MAE, and 0.52500% of MAPE with 0.99940 of correlation factor. The GA-MLP algorithm was compared with the ARIMA forecasting model, presenting better performance criteria in all performance criteria, validating the potential of this algorithm.Keywords: significant wave height, machine learning optimization, multilayer perceptron neural networks, evolutionary algorithms
Procedia PDF Downloads 10216081 A Research on Flipped-Classroom Teaching Model in English for Academic Purpose Teaching
Authors: Li Shuang
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With rigid teaching procedures and limited academic performance assessment methods, traditional teaching model stands in the way of college English reform in China, which features EAP (English for Academic Purpose) teaching. Flipped-classroom teaching, which has been extensively applied to science subjects teaching, however, covers the shortage of traditional teaching model in EAP teaching, via creatively inverting traditional teaching procedures. Besides, the application of flipped-classroom teaching model in EAP teaching also proves that this new teaching philosophy is not confined to science subjects teaching; it goes perfectly well with liberal-arts subjects teaching. Data analysis, desk research survey, and comparative study are referred to in the essay so as to prove its feasibility and advantages in EAP teaching.Keywords: EAP, traditional teaching method, flipped-classroom teaching model, teaching model design
Procedia PDF Downloads 30616080 Development of the Academic Model to Predict Student Success at VUT-FSASEC Using Decision Trees
Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho
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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine
Procedia PDF Downloads 19616079 Aerodynamic Prediction and Performance Analysis for Mars Science Laboratory Entry Vehicle
Authors: Tang Wei, Yang Xiaofeng, Gui Yewei, Du Yanxia
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Complex lifting entry was selected for precise landing performance during the Mars Science Laboratory entry. This study aims to develop the three-dimensional numerical method for precise computation and the surface panel method for rapid engineering prediction. Detailed flow field analysis for Mars exploration mission was performed by carrying on a series of fully three-dimensional Navier-Stokes computations. The static aerodynamic performance was then discussed, including the surface pressure, lift and drag coefficient, lift-to-drag ratio with the numerical and engineering method. Computation results shown that the shock layer is thin because of lower effective specific heat ratio, and that calculated results from both methods agree well with each other, and is consistent with the reference data. Aerodynamic performance analysis shows that CG location determines trim characteristics and pitch stability, and certain radially and axially shift of the CG location can alter the capsule lifting entry performance, which is of vital significance for the aerodynamic configuration des0ign and inner instrument layout of the Mars entry capsule.Keywords: Mars entry capsule, static aerodynamics, computational fluid dynamics, hypersonic
Procedia PDF Downloads 29416078 Effects of in silico (Virtual Lab) And in vitro (inside the Classroom) Labs in the Academic Performance of Senior High School Students in General Biology
Authors: Mark Archei O. Javier
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The Fourth Industrial Revolution (FIR) is a major industrial era characterized by the fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. Since this era teaches us how to thrive in the fast-paced developing world, it is important to be able to adapt. With this, there is a need to make learning and teaching in the bioscience laboratory more challenging and engaging. The goal of the research is to find out if using in silico and in vitro laboratory activities compared to the conventional conduct laboratory activities would have positive impacts on the academic performance of the learners. The potential contribution of the research is that it would improve the teachers’ methods in delivering the content to the students when it comes to topics that need laboratory activities. This study will develop a method by which teachers can provide learning materials to the students. A one-tailed t-Test for independent samples was used to determine the significant difference in the pre- and post-test scores of students. The tests of hypotheses were done at a 0.05 level of significance. Based on the results of the study, the gain scores of the experimental group are greater than the gain scores of the control group. This implies that using in silico and in vitro labs for the experimental group is more effective than the conventional method of doing laboratory activities.Keywords: academic performance, general biology, in silico laboratory, in vivo laboratory, virtual laboratory
Procedia PDF Downloads 188