Search results for: computer course unit
677 Text Emotion Recognition by Multi-Head Attention based Bidirectional LSTM Utilizing Multi-Level Classification
Authors: Vishwanath Pethri Kamath, Jayantha Gowda Sarapanahalli, Vishal Mishra, Siddhesh Balwant Bandgar
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Recognition of emotional information is essential in any form of communication. Growing HCI (Human-Computer Interaction) in recent times indicates the importance of understanding of emotions expressed and becomes crucial for improving the system or the interaction itself. In this research work, textual data for emotion recognition is used. The text being the least expressive amongst the multimodal resources poses various challenges such as contextual information and also sequential nature of the language construction. In this research work, the proposal is made for a neural architecture to resolve not less than 8 emotions from textual data sources derived from multiple datasets using google pre-trained word2vec word embeddings and a Multi-head attention-based bidirectional LSTM model with a one-vs-all Multi-Level Classification. The emotions targeted in this research are Anger, Disgust, Fear, Guilt, Joy, Sadness, Shame, and Surprise. Textual data from multiple datasets were used for this research work such as ISEAR, Go Emotions, Affect datasets for creating the emotions’ dataset. Data samples overlap or conflicts were considered with careful preprocessing. Our results show a significant improvement with the modeling architecture and as good as 10 points improvement in recognizing some emotions.Keywords: text emotion recognition, bidirectional LSTM, multi-head attention, multi-level classification, google word2vec word embeddings
Procedia PDF Downloads 174676 A Comparative Study on Deep Learning Models for Pneumonia Detection
Authors: Hichem Sassi
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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.Keywords: deep learning, computer vision, pneumonia, models, comparative study
Procedia PDF Downloads 64675 Sustainable Design for Building Envelope in Hot Climates: A Case Study for the Role of the Dome as a Component of an Envelope in Heat Exchange
Authors: Akeel Noori Almulla Hwaish
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Architectural design is influenced by the actual thermal behaviour of building components, and this in turn depends not only on their steady and periodic thermal characteristics, but also on exposure effects, orientation, surface colour, and climatic fluctuations at the given location. Design data and environmental parameters should be produced in an accurate way for specified locations, so that architects and engineers can confidently apply them in their design calculations that enable precise evaluation of the influence of various parameters relating to each component of the envelope, which indicates overall thermal performance of building. The present paper will be carried out with an objective of thermal behaviour assessment and characteristics of the opaque and transparent parts of one of the very unique components used as a symbolic distinguished element of building envelope, its thermal behaviour under the impact of solar temperatures, and its role in heat exchange related to a specific U-value of specified construction materials alternatives. The research method will consider the specified Hot-Dry weather and new mosque in Baghdad, Iraq as a case study. Also, data will be presented in light of the criteria of indoor thermal comfort in terms of design parameters and thermal assessment for a“model dome”. Design alternatives and considerations of energy conservation, will be discussed as well using comparative computer simulations. Findings will be incorporated to outline the conclusions clarifying the important role of the dome in heat exchange of the whole building envelope for approaching an indoor thermal comfort level and further research in the future.Keywords: building envelope, sustainable design, dome impact, hot-climates, heat exchange
Procedia PDF Downloads 475674 Stability of Concrete Moment Resisting Frames in View of Current Codes Requirements
Authors: Mahmoud A. Mahmoud, Ashraf Osman
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In this study, the different approaches currently followed by design codes to assess the stability of buildings utilizing concrete moment resisting frames structural system are evaluated. For such purpose, a parametric study was performed. It involved analyzing group of concrete moment resisting frames having different slenderness ratios (height/width ratios), designed for different lateral loads to vertical loads ratios and constructed using ordinary reinforced concrete and high strength concrete for stability check and overall buckling using code approaches and computer buckling analysis. The objectives were to examine the influence of such parameters that directly linked to frames’ lateral stiffness on the buildings’ stability and evaluates the code approach in view of buckling analysis results. Based on this study, it was concluded that, the most susceptible buildings to instability and magnification of second order effects are buildings having high aspect ratios (height/width ratio), having low lateral to vertical loads ratio and utilizing construction materials of high strength. In addition, the study showed that the instability limits imposed by codes are mainly mathematical to ensure reliable analysis not a physical ones and that they are in general conservative. Also, it has been shown that the upper limit set by one of the codes that second order moment for structural elements should be limited to 1.4 the first order moment is not justified, instead, the overall story check is more reliable.Keywords: buckling, lateral stability, p-delta, second order
Procedia PDF Downloads 256673 Experimental Proof of Concept for Piezoelectric Flow Harvesting for In-Pipe Metering Systems
Authors: Sherif Keddis, Rafik Mitry, Norbert Schwesinger
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Intelligent networking of devices has rapidly been gaining importance over the past years and with recent advances in the fields of microcontrollers, integrated circuits and wireless communication, low power applications have emerged, enabling this trend even more. Connected devices provide a much larger database thus enabling highly intelligent and accurate systems. Ensuring safe drinking water is one of the fields that require constant monitoring and can benefit from an increased accuracy. Monitoring is mainly achieved either through complex measures, such as collecting samples from the points of use, or through metering systems typically distant to the points of use which deliver less accurate assessments of the quality of water. Constant metering near the points of use is complicated due to their inaccessibility; e.g. buried water pipes, locked spaces, which makes system maintenance extremely difficult and often unviable. The research presented here attempts to overcome this challenge by providing these systems with enough energy through a flow harvester inside the pipe thus eliminating the maintenance requirements in terms of battery replacements or containment of leakage resulting from wiring such systems. The proposed flow harvester exploits the piezoelectric properties of polyvinylidene difluoride (PVDF) films to convert turbulence induced oscillations into electrical energy. It is intended to be used in standard water pipes with diameters between 0.5 and 1 inch. The working principle of the harvester uses a ring shaped bluff body inside the pipe to induce pressure fluctuations. Additionally the bluff body houses electronic components such as storage, circuitry and RF-unit. Placing the piezoelectric films downstream of that bluff body causes their oscillation which generates electrical charge. The PVDF-film is placed as a multilayered wrap fixed to the pipe wall leaving the top part to oscillate freely inside the flow. The warp, which allows for a larger active, consists of two layers of 30µm thick and 12mm wide PVDF layered alternately with two centered 6µm thick and 8mm wide aluminum foil electrodes. The length of the layers depends on the number of windings and is part of the investigation. Sealing the harvester against liquid penetration is achieved by wrapping it in a ring-shaped LDPE-film and welding the open ends. The fabrication of the PVDF-wraps is done by hand. After validating the working principle using a wind tunnel, experiments have been conducted in water, placing the harvester inside a 1 inch pipe at water velocities of 0.74m/s. To find a suitable placement of the wrap inside the pipe, two forms of fixation were compared regarding their power output. Further investigations regarding the number of windings required for efficient transduction were made. Best results were achieved using a wrap with 3 windings of the active layers which delivers a constant power output of 0.53µW at a 2.3MΩ load and an effective voltage of 1.1V. Considering the extremely low power requirements of sensor applications, these initial results are promising. For further investigations and optimization, machine designs are currently being developed to automate the fabrication and decrease tolerance of the prototypes.Keywords: maintenance-free sensors, measurements at point of use, piezoelectric flow harvesting, universal micro generator, wireless metering systems
Procedia PDF Downloads 193672 Image Ranking to Assist Object Labeling for Training Detection Models
Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman
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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.Keywords: computer vision, deep learning, object detection, semiconductor
Procedia PDF Downloads 136671 Assessment of E-Readiness in Libraries of Public Sector Universities Khyber Pakhtunkhwa-Pakistan
Authors: Saeed Ullah Jan
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This study has examined the e-readiness in libraries of public sector universities in Khyber Pakhtunkhwa. Efforts were made to evaluate the availability of human resources, electronic infrastructure, and network services and programs in the public sector university libraries. The population of the study was the twenty-seven public sector university libraries of Khyber Pakhtunkhwa. A quantitative approach was adopted, and a questionnaire-based survey was conducted to collect data from the librarian/in charge of public sector university libraries. The collected data were analyzed using Statistical Package for Social Sciences version 22 (SPSS). The mean score of the knowledge component interpreted magnitudes below three which indicates that the respondents are poorly or moderately satisfied regards knowledge of libraries. The satisfaction level of the respondents about the other components, such as electronic infrastructure, network services and programs, and enhancers of the networked world, was rated as average or below. The study suggested that major aspects of existing public-sector university libraries require significant transformation. For this purpose, the government should provide all the required resources and facilities to meet the population's informational and recreational demands. The Information Communication Technology (ICT) infrastructure of public university libraries needs improvement in terms of the availability of computer equipment, databases, network servers, multimedia projectors, digital cameras, uninterruptible power supply, scanners, and backup devices such as hard discs and Digital Video Disc/Compact Disc.Keywords: ICT-libraries, e-readiness-libraries, e-readiness-university libraries, e-readiness-Pakistan
Procedia PDF Downloads 88670 Artificial Intelligence Based Abnormality Detection System and Real Valuᵀᴹ Product Design
Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong
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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring
Procedia PDF Downloads 86669 A Neurofeedback Learning Model Using Time-Frequency Analysis for Volleyball Performance Enhancement
Authors: Hamed Yousefi, Farnaz Mohammadi, Niloufar Mirian, Navid Amini
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Investigating possible capacities of visual functions where adapted mechanisms can enhance the capability of sports trainees is a promising area of research, not only from the cognitive viewpoint but also in terms of unlimited applications in sports training. In this paper, the visual evoked potential (VEP) and event-related potential (ERP) signals of amateur and trained volleyball players in a pilot study were processed. Two groups of amateur and trained subjects are asked to imagine themselves in the state of receiving a ball while they are shown a simulated volleyball field. The proposed method is based on a set of time-frequency features using algorithms such as Gabor filter, continuous wavelet transform, and a multi-stage wavelet decomposition that are extracted from VEP signals that can be indicative of being amateur or trained. The linear discriminant classifier achieves the accuracy, sensitivity, and specificity of 100% when the average of the repetitions of the signal corresponding to the task is used. The main purpose of this study is to investigate the feasibility of a fast, robust, and reliable feature/model determination as a neurofeedback parameter to be utilized for improving the volleyball players’ performance. The proposed measure has potential applications in brain-computer interface technology where a real-time biomarker is needed.Keywords: visual evoked potential, time-frequency feature extraction, short-time Fourier transform, event-related spectrum potential classification, linear discriminant analysis
Procedia PDF Downloads 138668 Numerical Simulation of Free Surface Water Wave for the Flow Around NACA 0012 Hydrofoil and Wigley Hull Using VOF Method
Authors: Omar Imine, Mohammed Aounallah, Mustapha Belkadi
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Steady three-dimensional and two free surface waves generated by moving bodies are presented, the flow problem to be simulated is rich in complexity and poses many modeling challenges because of the existence of breaking waves around the ship hull, and because of the interaction of the two-phase flow with the turbulent boundary layer. The results of several simulations are reported. The first study was performed for NACA0012 of hydrofoil with different meshes, this section is analyzed at h/c= 1, 0345 for 2D. In the second simulation, a mathematically defined Wigley hull form is used to investigate the application of a commercial CFD code in prediction of the total resistance and its components from tangential and normal forces on the hull wetted surface. The computed resistance and wave profiles are used to estimate the coefficient of the total resistance for Wigley hull advancing in calm water under steady conditions. The commercial CFD software FLUENT version 12 is used for the computations in the present study. The calculated grid is established using the code computer GAMBIT 2.3.26. The shear stress k-ωSST model is used for turbulence modeling and the volume of the fluid technique is employed to simulate the free-surface motion. The second order upwind scheme is used for discretizing the convection terms in the momentum transport equations, the Modified HRICscheme for VOF discretization. The results obtained compare well with the experimental data.Keywords: free surface flows, breaking waves, boundary layer, Wigley hull, volume of fluid
Procedia PDF Downloads 376667 A Study to Explore the Views of Students regarding E-Learning as an Instructional Tool at University Level
Authors: Zafar Iqbal
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This study involved students of 6th semester enrolled in a Bachelor of Computer Science Program at university level. In this era of science and technology, e-learning can be helpful for grassroots in providing them access to education tenant in less developed areas. It is a potential substitute of face-to-face teaching being used in different countries. The purpose of the study was to explore the views of students about e-learning (Facebook) as an instructional tool. By using purposive sampling technique an intact class of 30 students included both male and female were selected where e-learning was used as an instructional tool. The views of students were explored through qualitative approach by using focus group interviews. The approach was helpful to develop comprehensive understanding of students’ views towards e- learning. In addition, probing questions were also asked and recorded. Data was transcribed, generated nodes and then coded text against these nodes. For this purpose and further analysis, NVivo 10 software was used. Themes were generated and tangibly presented through cluster analysis. Findings were interesting and provide sufficient evidence that face book is a subsequent e-learning source for students of higher education. Students acknowledged it as best source of learning and it was aligned with their academic and social behavior. It was not time specific and therefore, feasible for students who work day time and can get on line access to the material when they got free time. There were some distracters (time wasters) reported by the students but can be minimized by little effort. In short, e-learning is need of the day and potential learning source for every individual who have access to internet living at any part of the globe.Keywords: e-learning, facebook, instructional tool, higher education
Procedia PDF Downloads 374666 Interaction Evaluation of Silver Ion and Silver Nanoparticles with Dithizone Complexes Using DFT Calculations and NMR Analysis
Authors: W. Nootcharin, S. Sujittra, K. Mayuso, K. Kornphimol, M. Rawiwan
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Silver has distinct antibacterial properties and has been used as a component of commercial products with many applications. An increasing number of commercial products cause risks of silver effects for human and environment such as the symptoms of Argyria and the release of silver to the environment. Therefore, the detection of silver in the aquatic environment is important. The colorimetric chemosensor is designed by the basic of ligand interactions with a metal ion, leading to the change of signals for the naked-eyes which are very useful method to this application. Dithizone ligand is considered as one of the effective chelating reagents for metal ions due to its high selectivity and sensitivity of a photochromic reaction for silver as well as the linear backbone of dithizone affords the rotation of various isomeric forms. The present study is focused on the conformation and interaction of silver ion and silver nanoparticles (AgNPs) with dithizone using density functional theory (DFT). The interaction parameters were determined in term of binding energy of complexes and the geometry optimization, frequency of the structures and calculation of binding energies using density functional approaches B3LYP and the 6-31G(d,p) basis set. Moreover, the interaction of silver–dithizone complexes was supported by UV–Vis spectroscopy, FT-IR spectrum that was simulated by using B3LYP/6-31G(d,p) and 1H NMR spectra calculation using B3LYP/6-311+G(2d,p) method compared with the experimental data. The results showed the ion exchange interaction between hydrogen of dithizone and silver atom, with minimized binding energies of silver–dithizone interaction. However, the result of AgNPs in the form of complexes with dithizone. Moreover, the AgNPs-dithizone complexes were confirmed by using transmission electron microscope (TEM). Therefore, the results can be the useful information for determination of complex interaction using the analysis of computer simulations.Keywords: silver nanoparticles, dithizone, DFT, NMR
Procedia PDF Downloads 207665 Memristor-A Promising Candidate for Neural Circuits in Neuromorphic Computing Systems
Authors: Juhi Faridi, Mohd. Ajmal Kafeel
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The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS. Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.Keywords: analog circuits, digital circuits, memristors, neuromorphic computing systems
Procedia PDF Downloads 174664 Managing Fake News for Sustainable Democracy in Enugu State, Nigeria
Authors: Gloria Ebere Amadi, Emeka Promise Ugwunwotti
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The study was carried out to determine the strategies for managing fake news for sustainable democracy in Enugu State, Nigeria. Two research questions and two null hypotheses guided the study. A survey research design was used for the study. The population for the study consisted of 100 respondents (from Enugu state House of Assembly). Of the entire population, 24 elected law makers and 76 staff were used; hence there was no sampling since the population was manageable. A 28-item structured questionnaire developed by the researcher was used for data collection. The instrument entitled Managing Fake News Questionnaire (MFNQ) was validated by three experts, two from the Department of Computer Science and one from the Department of Maths and Statistics, all from Enugu State University of Science and Technology. Cronbach Alpha was used to determine the reliability coefficient of the two sections of the instrument, and they are 0.67 and 0.82, while the reliability coefficient of the whole instrument gave a value of 0.81. Mean with standard deviation was used to answer research questions, while the null hypotheses at 0.5 level of significance at 98 degrees of freedom were tested with a t-test. The findings of the study revealed that the respondents agreed that government and citizens-related strategies improve the management of fake news for sustainable democracy in Enugu State. Again, there was no significant difference between the mean response of the lawmakers and staff on government and citizens-related strategies for managing fake news for sustainable democracy in Enugu State. Based on the findings, it was recommended, among others, that there should be regular workshops on the management of fake news for citizens.Keywords: fake news, sustainability, democracy, management
Procedia PDF Downloads 70663 Effect of Dual Wavelength Light Exposure on Regeneration of Dugesia dorotocephala
Authors: Zayedali Shaikh
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Increasingly now more than ever, UV damage brings with it a litany of minor deformities that can range from mild lesions and discoloring to cataracts and blindness. Pluripotent stem cells in planaria and human skin can be used to treat wounds and skin damage, with the primary limitations being inadequate growth factors. Photobiomodulation therapy in the form of low-intensity red light therapy has been proven to provide helpful benefits in the healing of skin that displays some of the symptoms of UV damage, such as burns and lesions, along with stimulating the proliferation of stem cells in recellularizing tissue. This paper puts forth an alternate means by which to treat the effects of UV damage using the freshwater planarian model system, Dugesia dorotocephala, known for its regenerative abilities and abundance of pluripotent stem cells, which allow for the rapid growth and repair of missing or damaged structures. Our work consisted of exposing planaria to different types of light: red light, blue light, white light, darkness, red and blue light together, UV light, and finally, red and UV light together. The primary focus of this research was on the red and UV lights, with six controls acting as metrics to compare our findings. Through computer-assisted morphological analysis, the results show that there is no significant difference in the rates of regeneration of planaria treated with simultaneous exposure to red and UV light versus planaria in darkness (p > .05), a representation of their preferred natural habitat. Our research suggests the viability of red-light therapy in actively combating UV damage and expediting the growth of epidermal stem cells by acting as another growth factor.Keywords: regenerative medicine, stem cells, planaria, photobiomodulation
Procedia PDF Downloads 77662 An Extensible Software Infrastructure for Computer Aided Custom Monitoring of Patients in Smart Homes
Authors: Ritwik Dutta, Marylin Wolf
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This paper describes the trade-offs and the design from scratch of a self-contained, easy-to-use health dashboard software system that provides customizable data tracking for patients in smart homes. The system is made up of different software modules and comprises a front-end and a back-end component. Built with HTML, CSS, and JavaScript, the front-end allows adding users, logging into the system, selecting metrics, and specifying health goals. The back-end consists of a NoSQL Mongo database, a Python script, and a SimpleHTTPServer written in Python. The database stores user profiles and health data in JSON format. The Python script makes use of the PyMongo driver library to query the database and displays formatted data as a daily snapshot of user health metrics against target goals. Any number of standard and custom metrics can be added to the system, and corresponding health data can be fed automatically, via sensor APIs or manually, as text or picture data files. A real-time METAR request API permits correlating weather data with patient health, and an advanced query system is implemented to allow trend analysis of selected health metrics over custom time intervals. Available on the GitHub repository system, the project is free to use for academic purposes of learning and experimenting, or practical purposes by building on it.Keywords: flask, Java, JavaScript, health monitoring, long-term care, Mongo, Python, smart home, software engineering, webserver
Procedia PDF Downloads 390661 Factors Influencing the Enjoyment and Performance of Students in Statistics Service Courses: A Mixed-Method Study
Authors: Wilma Coetzee
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Statistics lecturers experience that many students who are taking a service course in statistics do not like statistics. Students in these courses tend to struggle and do not perform well. This research takes a look at the student’s perspective, with the aim to determine how to change the teaching of statistics so that students will enjoy it more and perform better. Questionnaires were used to determine the perspectives of first year service statistics students at a South African university. Factors addressed included motivation to study, attitude toward statistics, statistical anxiety, mathematical abilities and tendency to procrastinate. Logistic regression was used to determine what contributes to students performing badly in statistics. The results show that the factors that contribute the most to students performing badly are: statistical anxiety, not being motivated and having had mathematical literacy instead of mathematics in secondary school. Two open ended questions were included in the questionnaire: 'I will enjoy statistics more if…' and 'I will perform better in statistics if…'. The answers to these questions were analyzed using qualitative methods. Frequent themes were identified for each of the questions. A simulation study incorporating bootstrapping was done to determine the saturation of the themes. The majority of the students indicated that they would perform better in statistics if they studied more, managed their time better, had a flare for mathematics and if the lecturer was able to explain difficult concepts better. They also want more active learning. To ensure that students enjoy statistics more, they want an active learning experience. They want fun activities, more interaction with the lecturer and with one another, more computer based problems, and more challenges. They want a better understanding of the subject, want to understand the relevance of statistics to their future career and want excellent lecturers. These findings can be used to direct the improvement of the tuition of statistics.Keywords: active learning, performance in statistics, statistical anxiety, statistics education
Procedia PDF Downloads 147660 The Impact of Supporting Productive Struggle in Learning Mathematics: A Quasi-Experimental Study in High School Algebra Classes
Authors: Sumeyra Karatas, Veysel Karatas, Reyhan Safak, Gamze Bulut-Ozturk, Ozgul Kartal
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Productive struggle entails a student's cognitive exertion to comprehend mathematical concepts and uncover solutions not immediately apparent. The significance of productive struggle in learning mathematics is accentuated by influential educational theorists, emphasizing its necessity for learning mathematics with understanding. Consequently, supporting productive struggle in learning mathematics is recognized as a high-leverage and effective mathematics teaching practice. In this study, the investigation into the role of productive struggle in learning mathematics led to the development of a comprehensive rubric for productive struggle pedagogy through an exhaustive literature review. The rubric consists of eight primary criteria and 37 sub-criteria, providing a detailed description of teacher actions and pedagogical choices that foster students' productive struggles. These criteria encompass various pedagogical aspects, including task design, tool implementation, allowing time for struggle, posing questions, scaffolding, handling mistakes, acknowledging efforts, and facilitating discussion/feedback. Utilizing this rubric, a team of researchers and teachers designed eight 90-minute lesson plans, employing a productive struggle pedagogy, for a two-week unit on solving systems of linear equations. Simultaneously, another set of eight lesson plans on the same topic, featuring identical content and problems but employing a traditional lecture-and-practice model, was designed by the same team. The objective was to assess the impact of supporting productive struggle on students' mathematics learning, defined by the strands of mathematical proficiency. This quasi-experimental study compares the control group, which received traditional lecture- and practice instruction, with the treatment group, which experienced a productive struggle in pedagogy. Sixty-six 10th and 11th-grade students from two algebra classes, taught by the same teacher at a high school, underwent either the productive struggle pedagogy or lecture-and-practice approach over two-week eight 90-minute class sessions. To measure students' learning, an assessment was created and validated by a team of researchers and teachers. It comprised seven open-response problems assessing the strands of mathematical proficiency: procedural and conceptual understanding, strategic competence, and adaptive reasoning on the topic. The test was administered at the beginning and end of the two weeks as pre-and post-test. Students' solutions underwent scoring using an established rubric, subjected to expert validation and an inter-rater reliability process involving multiple criteria for each problem based on their steps and procedures. An analysis of covariance (ANCOVA) was conducted to examine the differences between the control group, which received traditional pedagogy, and the treatment group, exposed to the productive struggle pedagogy, on the post-test scores while controlling for the pre-test. The results indicated a significant effect of treatment on post-test scores for procedural understanding (F(2, 63) = 10.47, p < .001), strategic competence (F(2, 63) = 9.92, p < .001), adaptive reasoning (F(2, 63) = 10.69, p < .001), and conceptual understanding (F(2, 63) = 10.06, p < .001), controlling for pre-test scores. This demonstrates the positive impact of supporting productive struggle in learning mathematics. In conclusion, the results revealed the significance of the role of productive struggle in learning mathematics. The study further explored the practical application of productive struggle through the development of a comprehensive rubric describing the pedagogy of supporting productive struggle.Keywords: effective mathematics teaching practice, high school algebra, learning mathematics, productive struggle
Procedia PDF Downloads 51659 Using Vertical Electrical Soundings Data to Investigate and Assess Groundwater Resources for Irrigation in the Canal Command Area
Authors: Vijaya Pradhan, S. M. Deshpande, D. G. Regulwar
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Intense hydrogeological research has been prompted by the rising groundwater demand in typical hard rock terrain. In the current study, groundwater resources for irrigation in the canal command of the Jayakwadi Reservoir in the Indian state of Maharashtra are located using Vertical Electrical Soundings (VES). A Computer Resistivity Monitor is used to monitor the geoelectric field (CRM). Using Schlumberger setups, the investigation was carried out at seven different places in the region. Plotting of the sounding curves is the outcome of the data processing. The underlying layers and groundwater potential in the research region have been examined by analyzing these curves using curve-matching techniques, also known as partial curve matching. IPIWin2 is used to examine the relationship between resistivity and electrode spacing. The resistivity value in a geological formation is significantly reduced when groundwater is present. Up to a depth of 35 meters, the resistivity readings are minimal; beyond that, they continuously increase, suggesting a lack of water in deeper strata. As a result, the wells may only receive water up to a depth of 35 meters. In addition, the trap may occasionally fracture at deeper depths, retaining a limited amount of water in the cracks and producing a low yield. According to the findings, weathered basalt or soil make up the top layer (5–10 m), which is followed by a layer of amygdaloidal basalt (10–35 m) that is somewhat cracked and either hard basalt or compact basalt underneath.Keywords: vertical electrical soundings (VES), resistivity, electrode spacing, Schlumberger configurations, partial curve matching.
Procedia PDF Downloads 23658 Simulation Aided Life Cycle Sustainability Assessment Framework for Manufacturing Design and Management
Authors: Mijoh A. Gbededo, Kapila Liyanage, Ilias Oraifige
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Decision making for sustainable manufacturing design and management requires critical considerations due to the complexity and partly conflicting issues of economic, social and environmental factors. Although there are tools capable of assessing the combination of one or two of the sustainability factors, the frameworks have not adequately integrated all the three factors. Case study and review of existing simulation applications also shows the approach lacks integration of the sustainability factors. In this paper we discussed the development of a simulation based framework for support of a holistic assessment of sustainable manufacturing design and management. To achieve this, a strategic approach is introduced to investigate the strengths and weaknesses of the existing decision supporting tools. Investigation reveals that Discrete Event Simulation (DES) can serve as a rock base for other Life Cycle Analysis frameworks. Simio-DES application optimizes systems for both economic and competitive advantage, Granta CES EduPack and SimaPro collate data for Material Flow Analysis and environmental Life Cycle Assessment, while social and stakeholders’ analysis is supported by Analytical Hierarchy Process, a Multi-Criteria Decision Analysis method. Such a common and integrated framework creates a platform for companies to build a computer simulation model of a real system and assess the impact of alternative solutions before implementing a chosen solution.Keywords: discrete event simulation, life cycle sustainability analysis, manufacturing, sustainability
Procedia PDF Downloads 279657 Analyzing the Usage of Social Media: A Study on Elderly in Malaysia
Authors: Chan Eang Teng, Tang Mui Joo
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In the beginning of the prevalence of social media, it would be an obvious trend that the young adult age group has the highest population among the users on social media. However, apart from the age group of the users are becoming younger and younger, the elderly group has become a new force on social media, and this age group has increased rapidly. On top of that, the influence of social media towards the elderly is becoming more significant and it is even trending among them. This is because basic computer knowledge is not instilled into their life when they were young. This age group tends to be engrossed more than the young as this is something new for them, and they have the mindset that it is a new platform to approach things, and they tend to be more engrossed when they start getting in touch with the social media. Generally, most of the social media has been accepted and accessed by teenagers and young adult, but it is reasonable to believe that the social media is not really accepted among the elderly. Surprisingly, the elderlies are more addicted to the social media than the teenagers. Therefore, this study is to determine and understand the relationship between the elderly and social media, and how they employ social media in their lives. An online survey on 200 elderly aged 45-80 and an interview with a media expert are conducted to answer the main questions in the research paper. Uses and Gratification Approach is employed in theoretical framework. Finding revealed that majority of the respondents use social media to connect with family, friends, and for leisure purposes. The finding concluded that the elderly use social media differently according to their needs and wants which is in par with the highlight of Uses and Gratification theory. Considering the significantly large role social media plays in our culture and daily life today, the finding will shed some light on the effect of social media on the elderly or senior citizens who are usually relegated into a minority group in today’s age where the internet and social media are of great importance to our society and humanity in general. This may also serve to be useful in understanding behavioral patterns and preference in terms of social media usage among the elderly.Keywords: elderly, Facebook, Malaysia, social media
Procedia PDF Downloads 365656 A Comparative Study of Morphine and Clonidine as an Adjunct to Ropivacaine in Paravertebral Block for Modified Radical Mastectomy
Authors: Mukesh K., Siddiqui A. K., Abbas H., Gupta R.
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Background: General Anesthesia is a standard for breast onco-surgery. The issue of postoperative pain and the occurrence of nausea and vomiting has prompted the quest for a superior methodology with fewer complications. Over the recent couple of years, paravertebral block (PVB) has acquired huge fame either in combination with GA or alone for anesthetic management. In this study, we aim to evaluate the efficacy of morphine and clonidine as an adjunct to ropivacaine in a paravertebral block in breast cancer patients undergoing modified radical mastectomy. Methods: In this study, total 90 patients were divided into three groups (30 each) on the basis of computer-generated randomization. Group C (Control): Paravertebral block with 0.25% ropivacaine (19ml) and 1 ml saline; Group M- Paravertebral block with 0.25% ropivacaine(19ml) + 20 microgram/kg body weight morphine; Group N: Paravertebral block with 0.25% ropivacaine(19ml) +1.0 microgram/kg body weight clonidine. The postoperative pain intensity was recorded using the visual analog scale (VAS) and Sedation was observed by the Ramsay Sedation score (RSS). Results: The VAS was similar at 0hr, 2hr and 4 hr in the postoperative period among all the groups. There was a significant (p=0.003) difference in VAS from 6 hr to 20 hr in the postoperative period among the groups. A significant (p<0.05) difference was observed among the groups at 8 hr to 20 hr). The first requirement of analgesia was significantly (p=0.001) higher in Group N (7.70±1.74) than in Group C (4.43±1.43) and Group M (7.33±2.21). Conclusion: The morphine in the paravertebral block provides better postoperative analgesia. The consumption of rescue analgesia was significantly reduced in the morphine group as compared to the clonidine group. The procedure also proved to be safe as no complication was encountered in the paravertebral block in our study.Keywords: ropivacaine, morphine, clonidine, paravertebral block
Procedia PDF Downloads 117655 Numerical Investigation of a Spiral Bladed Tidal Turbine
Authors: Mohammad Fereidoonnezhad, Seán Leen, Stephen Nash, Patrick McGarry
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From the perspective of research innovation, the tidal energy industry is still in its early stages. While a very small number of turbines have progressed to utility-scale deployment, blade breakage is commonly reported due to the enormous hydrodynamic loading applied to devices. The aim of this study is the development of computer simulation technologies for the design of next-generation fibre-reinforced composite tidal turbines. This will require significant technical advances in the areas of tidal turbine testing and multi-scale computational modelling. The complex turbine blade profiles are designed to incorporate non-linear distributions of airfoil sections to optimize power output and self-starting capability while reducing power fluctuations. A number of candidate blade geometries are investigated, ranging from spiral geometries to parabolic geometries, with blades arranged in both cylindrical and spherical configurations on a vertical axis turbine. A combined blade element theory (BET-start-up model) is developed in MATLAB to perform computationally efficient parametric design optimisation for a range of turbine blade geometries. Finite element models are developed to identify optimal fibre-reinforced composite designs to increase blade strength and fatigue life. Advanced fluid-structure-interaction models are also carried out to compute blade deflections following design optimisation.Keywords: tidal turbine, composite materials, fluid-structure-interaction, start-up capability
Procedia PDF Downloads 122654 The Impact of E-Learning on the Performance of History Learners in Eswatini General Certificate of Secondary Education
Authors: Joseph Osodo, Motsa Thobekani Phila
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The study investigated the impact of e-learning on the performance of history learners in Eswatini general certificate of secondary education in the Manzini region of Eswatini. The study was guided by the theory of connectivism. The study had three objectives which were to find out the significance of e-learning during the COVID-19 era in learning History subject; challenges faced by history teachers’ and learners’ in e-learning; and how the challenges were mitigated. The study used a qualitative research approach and descriptive research design. Purposive sampling was used to select eight History teachers and eight History learners from four secondary schools in the Manzini region. Data were collected using face to face interviews. The collected data were analyzed and presented in thematically. The findings showed that history teachers had good knowledge on what e-learning was, while students had little understanding of e-learning. Some of the forms of e-learning that were used during the pandemic in teaching history in secondary schools included TV, radio, computer, projectors, and social media especially WhatsApp. E-learning enabled the continuity of teaching and learning of history subject. The use of e-learning through the social media was more convenient to the teacher and the learners. It was concluded that in some secondary school in the Manzini region, history teacher and learners encountered challenges such as lack of finances to purchase e-learning gadgets and data bundles, lack of skills as well as access to the Internet. It was recommended that History teachers should create more time to offer additional learning support to students whose performance was affected by the COVID-19 pandemic effects.Keywords: e-learning, performance, COVID-19, history, connectivism
Procedia PDF Downloads 76653 Analysis of Composite Health Risk Indicators Built at a Regional Scale and Fine Resolution to Detect Hotspot Areas
Authors: Julien Caudeville, Muriel Ismert
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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.Keywords: health risk, environment, composite indicator, hotspot areas
Procedia PDF Downloads 247652 Ergosterol Biosynthesis: Non-Conventional Method for Improving Process
Authors: Madalina Postaru, Alexandra Tucaliuc, Dan Cascaval, Anca Irina Galaction
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Ergosterol (ergosta-5,7,22-trien-3β-ol) is the precursor of vitamin D2 (ergocalciferol), known as provitamin D2 as it is converted under UV radiation to this vitamin. The natural sources of ergosterol are mainly the yeasts (Saccharomyces sp., Candida sp.), but it can be also found in fungus (Claviceps sp.) or plants (orchids). As ergosterol is mainly accumulated in yeast cell membranes, especially in free form in the plasma-membrane, and the chemical synthesis of ergosterol does not represent an efficient method for its production, this study aimed to analyze the influence of aeration efficiency on ergosterol production by S. cerevisiae in batch and fed-batch fermentations, by considering different levels of mixing intensity, aeration rate, and n-dodecane concentration. Our previous studies on ergosterol production by S. cerevisiae in batch and fed-batch fermentation systems indicated that the addition of n-dodecane led to the increase of almost 50% of this sterol concentration, the highest productivity being reached for the fed-batch process. The experiments were carried out in a laboratory stirred bioreactor, provided with computer-controlled and recorded parameters. In batch fermentation system, the study indicated that the oxygen mass transfer coefficient, kLa, is amplified for about 3 times by increasing the volumetric concentration of n-dodecane from 0 to 15%. Moreover, the increase of dissolved oxygen concentration by adding n-dodecane leads to the diminution for 3.5 times of the produced alcohol amount. In fed-batch fermentation process, the positive influence of hydrocarbon on oxygen transfer rate is amplified mainly at its higher concentration level, as the result of the increased yeasts cells amount. Thus, by varying n-dodecane concentration from 0 to 15% vol., the kLa value increase becomes more important than for the batch fermentation, being of 4 timesKeywords: ergosterol, yeast fermentation, n-dodecane, oxygen-vector
Procedia PDF Downloads 119651 Multimedia Technologies Utilisation as Predictors of Lecturers’ Teaching Effectiveness in Colleges of Education in South-West, Nigeria
Authors: Abel Olusegun Egunjobi, Olusegun Oyeleye Adesanya
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Teaching effectiveness of lecturers in a tertiary institution in Nigeria is one of the determinants of the lecturer’s productivity. In this study, therefore, lecturers’ teaching effectiveness was examined vis-à-vis their multimedia technologies utilisation in Colleges of Education (CoE) in South-West, Nigeria. This is for the purpose of ascertaining the relationship and contribution of multimedia technologies utilisation to lecturers’ teaching effectiveness in Nigerian colleges of education. The descriptive survey research design was adopted in the study, while a multi-stage sampling procedure was used in the study. A stratified sampling technique was used to select colleges of education, and a simple random sampling method was employed to select lecturers from the selected colleges of education. A total of 862 lecturers (627 males and 235 females) were selected from the colleges of education used for the study. The instrument used was lecturers’ questionnaire on multimedia technologies utilisation and teaching effectiveness with a reliability coefficient of 0.85 at 0.05 level of significance. The data collected were analysed using descriptive statistics, multiple regression, and t-test. The findings showed that the level of multimedia technologies utilisation in colleges of education was low, whereas lecturers’ teaching effectiveness was high. Findings also revealed that the lecturers used multimedia technologies purposely for personal and professional developments, so also for up to date news on economic and political matters. Also, findings indicated that laptop, Ipad, CD-ROMs, and computer instructional software were the multimedia technologies frequently utilised by the lecturers. There was also a significant difference in the teaching effectiveness between lecturers in the Federal and State COE. The government should, therefore, make adequate provision for multimedia technologies in the COE in Nigeria for lecturers’ utilisation in their instructions so as to boost their students’ learning outcomes.Keywords: colleges of education, lecturers’ teaching effectiveness, multimedia technologies utilisation, Southwest Nigeria
Procedia PDF Downloads 140650 Two-Dimensional Observation of Oil Displacement by Water in a Petroleum Reservoir through Numerical Simulation and Application to a Petroleum Reservoir
Authors: Ahmad Fahim Nasiry, Shigeo Honma
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We examine two-dimensional oil displacement by water in a petroleum reservoir. The pore fluid is immiscible, and the porous media is homogenous and isotropic in the horizontal direction. Buckley-Leverett theory and a combination of Laplacian and Darcy’s law are used to study the fluid flow through porous media, and the Laplacian that defines the dispersion and diffusion of fluid in the sand using heavy oil is discussed. The reservoir is homogenous in the horizontal direction, as expressed by the partial differential equation. Two main factors which are observed are the water saturation and pressure distribution in the reservoir, and they are evaluated for predicting oil recovery in two dimensions by a physical and mathematical simulation model. We review the numerical simulation that solves difficult partial differential reservoir equations. Based on the numerical simulations, the saturation and pressure equations are calculated by the iterative alternating direction implicit method and the iterative alternating direction explicit method, respectively, according to the finite difference assumption. However, to understand the displacement of oil by water and the amount of water dispersion in the reservoir better, an interpolated contour line of the water distribution of the five-spot pattern, that provides an approximate solution which agrees well with the experimental results, is also presented. Finally, a computer program is developed to calculate the equation for pressure and water saturation and to draw the pressure contour line and water distribution contour line for the reservoir.Keywords: numerical simulation, immiscible, finite difference, IADI, IDE, waterflooding
Procedia PDF Downloads 331649 Effective Student Engaging Strategies to Enhance Academic Learning in Middle Eastern Classrooms: An Action Research Approach
Authors: Anjum Afrooze
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The curriculum at General Sciences department in Prince Sultan University includes ‘Physical science’ for Computer Science, Information Technology and Business courses. Students are apathetic towards Physical Science and question, as to, ‘How this course is related to their majors?’ English is not a native language for the students and also for many instructors. More than sixty percent of the students come from institutions where English is not the medium of instruction, which makes student learning and academic achievement challenging. After observing the less enthusiastic student cohort for two consecutive semesters, the instructor was keen to find effective strategies to enhance learning and further encourage deep learning by engaging students in different tasks to empower them with necessary skills and motivate them. This study is participatory action research, in which instructor designs effective tasks to engage students in their learning. The study is conducted through two semesters with a total of 200 students. The effectiveness of this approach is studied using questionnaire at the end of each semester and teacher observation. Major outcomes of this study were overall improvement in students attitude towards science learning, enhancement of multiple skills like note taking, problem solving, language proficiency and also fortifying confidence. This process transformed instructor into engaging and reflecting practitioner. Also, these strategies were implemented by other instructors teaching the course and proved effective in opening a path to changes in related areas of the course curriculum. However, refinement in the strategies could be done based on student evaluation and instructors observation.Keywords: group activity, language proficiency, reasoning skills, science learning
Procedia PDF Downloads 145648 Investigating the Effectiveness of a 3D Printed Composite Mold
Authors: Peng Hao Wang, Garam Kim, Ronald Sterkenburg
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In composite manufacturing, the fabrication of tooling and tooling maintenance contributes to a large portion of the total cost. However, as the applications of composite materials continue to increase, there is also a growing demand for more tooling. The demand for more tooling places heavy emphasis on the industry’s ability to fabricate high quality tools while maintaining the tool’s cost effectiveness. One of the popular techniques of tool fabrication currently being developed utilizes additive manufacturing technology known as 3D printing. The popularity of 3D printing is due to 3D printing’s ability to maintain low material waste, low cost, and quick fabrication time. In this study, a team of Purdue University School of Aviation and Transportation Technology (SATT) faculty and students investigated the effectiveness of a 3D printed composite mold. A steel valve cover from an aircraft reciprocating engine was modeled utilizing 3D scanning and computer-aided design (CAD) to create a 3D printed composite mold. The mold was used to fabricate carbon fiber versions of the aircraft reciprocating engine valve cover. The carbon fiber valve covers were evaluated for dimensional accuracy and quality while the 3D printed composite mold was evaluated for durability and dimensional stability. The data collected from this study provided valuable information in the understanding of 3D printed composite molds, potential improvements for the molds, and considerations for future tooling design.Keywords: additive manufacturing, carbon fiber, composite tooling, molds
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