Search results for: Learning materials

Authors: Jutharat Sunprasert, Ekapong Hirunsirisawat, Narongrit Waraporn, Somporn Peansukmanee

Abstract:

Metal Ship and Robotic Car is one of the hands-on activities in the course, the Fundamental of Engineering that can be divided into three parts. The first part, the metal ships, was made by using engineering drawings, physics and mathematics knowledge. The second part is where the students learned how to construct a robotic car and control it using computer programming. In the last part, the students had to combine the workings of these two objects in the final testing. This aim of study was to investigate the effectiveness of hands-on activity by integrating Science, Technology, Engineering and Mathematics (STEM) concepts to develop scientific and engineering skills. The results showed that the majority of students felt this hands-on activity lead to an increased confidence level in the integration of STEM. Moreover, 48% of all students engaged well with the STEM concepts. Students could obtain the knowledge of STEM through hands-on activities with the topics science and mathematics, engineering drawing, engineering workshop and computer programming; most students agree and strongly agree with this learning process. This indicated that the hands-on activity: “Metal Ship and Robotic Car” is a useful tool to integrate each aspect of STEM. Furthermore, hands-on activities positively influence a student’s interest which leads to increased learning achievement and also in developing scientific and engineering skills.

Keywords: hands-on activity, STEM education, computer programming, metal work

Procedia PDF Downloads 448

Authors: Tahmina Huq

Abstract:

This paper presents the findings of an action research study that aimed to investigate the efficacy of a visual dialogue strategy in assisting autistic students with intellectual disabilities in managing their immediate emotions and improving their academic achievements. The research sought to explore the effectiveness of teaching self-regulation techniques as an alternative to traditional approaches involving segregation. The study identified visual dialogue as a valuable tool for promoting self-regulation in this specific student population. Action research was chosen as the methodology due to its suitability for immediate implementation of the findings in the classroom. Autistic students with intellectual disabilities often face challenges in controlling their emotions, which can disrupt their learning and academic progress. Conventional methods of intervention, such as isolation and psychologist-assisted approaches, may result in missed classes and hindered academic development. This study introduces the utilization of visual dialogue between students and teachers as an effective self-regulation strategy, addressing the limitations of traditional approaches. Action research was employed as the methodology for this study, allowing for the direct application of the findings in the classroom. The study observed two 15-year-old autistic students with intellectual disabilities who exhibited difficulties in emotional regulation and displayed aggressive behaviors. The research question focused on the effectiveness of visual dialogue in managing the emotions of these students and its impact on their learning outcomes. Data collection methods included personal observations, log sheets, personal reflections, and visual documentation. The study revealed that the implementation of visual dialogue as a self-regulation strategy enabled the students to regulate their emotions within a short timeframe (10 to 30 minutes). Through visual dialogue, they were able to express their feelings and needs in socially appropriate ways. This finding underscores the significance of visual dialogue as a tool for promoting emotional regulation and facilitating active participation in classroom activities. As a result, the students' learning outcomes and social interactions were positively impacted. The findings of this study hold significant implications for educators working with autistic students with intellectual disabilities. The use of visual dialogue as a self-regulation strategy can enhance emotional regulation skills and improve overall academic progress. The action research approach outlined in this paper provides practical guidance for educators in effectively implementing self-regulation strategies within classroom settings. In conclusion, the study demonstrates that visual dialogue is an effective strategy for enhancing emotional regulation in autistic students with intellectual disabilities. By employing visual communication, students can successfully regulate their emotions and actively engage in classroom activities, leading to improved learning outcomes and social interactions. This paper underscores the importance of implementing self-regulation strategies in educational settings to cater to the unique needs of autistic students.

Keywords: action research, self-regulation, autism, visual communication

Procedia PDF Downloads 49

Authors: Hanjun Yun, Gun Bae, Nabin Paul, Cheolhee Moon

Abstract:

Flexible OLED is an important technology for the next generation display over various kinds of applications. However, the organic materials of OLEDs degrade rapidly under the invasion of oxygen and water moisture. The degradation causes the formation of non-emitting areas which gradually suppress the device brightness, ultimately the lifetime of the device decreasing rapidly. Until now, the most suitable sealing process of the flexible OLED devices is a thin film encapsulation (TFE). However, TFE consists of a multilayer thin-film structure with organic-inorganic materials, so the cost is expensive and the process time is long. Another problem is that the blocking characteristics from the moisture and oxygen are not perfect. Therefore, the encapsulation of the flexible OLED device is a still key technical issue for the successful market entry. In this study, we are to introduce an auxiliary sealing line between the two flexible substrates. The electrode lines were formed on the substrates which have a SiNx barrier coating layer. To induce the solid phase diffusion process between the SiNx layer and the electrode lines, the electrode materials were determined as Al-Si composition. Thermal energy was supplied for both the SiNx layer and Al-Si electrode lines within the furnace to induce the interfacial bonding through the solid phase diffusion of Si. We printed a test pattern for the edge of the flexible PET substrate of 3cm*3cm size. Experimental conditions such as heating temperature, heating time were optimized to get enough adhesion strength which was estimated through the competitive bending test. Finally, OLED devices with flexible PET substrate of 3cm*3cm size were manufactured to investigate the blocking characteristics as an encapsulation layer.

Keywords: barrier, encapsulation, OLED, solid phase diffusion

Procedia PDF Downloads 224

Authors: Alagie Salieu Nankey

Abstract:

Flood-resistant house is the key mechanism to withstand flood hazards in Ebo-Town. It emerged simple yet powerful way of mitigating flooding in the community of Ebo- Town. Even though there are different types of buildings, little is known yet how and why flood affects building severely. In this paper, we examine three different types of flood-resistant buildings that are suitable for Ebo Town. We gather content and contextual features from six (6) respondents and used this data set to identify factors that are significantly associated with the flood-resistant house. Moreover, we built a suitable design concept. We found that amongst all the theories studied in the literature study Slit or Elevated House is the most suitable building design in Ebo-Town and Pile foundation is the most appropriate foundation type in the study area. Amongst contextual features, local materials are the most economical materials for the proposed design. This research proposes a framework that explains the theoretical relationships between flood hazard zones and flood-resistant houses in Ebo Town. Moreover, this research informs the design of sense-making and analytics tools for the resistant house.

Keywords: flood-resistant, slit, flood hazard zone, pile foundation

Procedia PDF Downloads 15

Authors: Yash Bingi, Yiqiao Yin

Abstract:

Reduction of child mortality is an ongoing struggle and a commonly used factor in determining progress in the medical field. The under-5 mortality number is around 5 million around the world, with many of the deaths being preventable. In light of this issue, Cardiotocograms (CTGs) have emerged as a leading tool to determine fetal health. By using ultrasound pulses and reading the responses, CTGs help healthcare professionals assess the overall health of the fetus to determine the risk of child mortality. However, interpreting the results of the CTGs is time-consuming and inefficient, especially in underdeveloped areas where an expert obstetrician is hard to come by. Using a support vector machine (SVM) and oversampling, this paper proposed a model that classifies fetal health with an accuracy of 99.59%. To further explain the CTG measurements, an algorithm based on Randomized Input Sampling for Explanation ((RISE) of Black-box Models was created, called Feature Alteration for explanation of Black Box Models (FAB), and compared the findings to Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME). This allows doctors and medical professionals to classify fetal health with high accuracy and determine which features were most influential in the process.

Keywords: machine learning, fetal health, gradient boosting, support vector machine, Shapley values, local interpretable model agnostic explanations

Procedia PDF Downloads 128

Authors: Kaixuan Feng, Ruixiang Lin, Yuyan Hu, Yuheng Feng, Dezhen Chen, Tongcheng Cao

Abstract:

In this study, we propose a reaction system for the low-temperature reduction of NO by H₂ on carbon-based materials decorated with 5%wt. Ni. This cost-effective catalyst system efficiently utilizes pyrolysis carbon-based materials and waste hydrogen. Additionally, it yields environmentally friendly products without requiring extra heat sources in practical SCR devices. Density functional theory elucidates the mechanism of NO heterogeneous reduction by H₂ on Ni-decorated char surfaces. Two distinct reaction paths were identified, one involving the intermediate product N₂O and the other not. These pathways exhibit different rate-determination steps and activation energies. Kinetic analysis indicates that the N₂O byproduct pathway has a lower activation energy. Experimental results corroborate the theoretical findings. Thus, this research enhances our mechanistic understanding of the NO-H₂ reaction over char and offers insights for optimizing catalyst design in low-temperature NO reduction.

Keywords: char-based catalysis, NO reduction, DFT study, heterogeneous reaction, low-temperature H₂-reduction

Procedia PDF Downloads 59

Authors: Akpokiere Ugbede Roseline

Abstract:

Chemistry is an activity oriented subject in which many students achievement over the years are not encouraging. Among the reasons found to be responsible for student’s poor performance in chemistry are ineffective teaching strategies. This study, therefore, sought to determine the effect of guided inquiry, guided inquiry with demonstration, and demonstration with conventional approach on pre-service teachers’ cognitive attainment and practical skills acquisition on stoichiometry and chemical reactions in practical chemistry, Two research questions and hypotheses were each answered and tested respectively. The study was a quasi-experimental research involving 50 students in each of the experimental groups and 50 students in the control group. Out of the five instruments used for the study, three were on stimulus and two on response (Test of Cognitive Attainment and Test of Practical Skills in Chemistry) instruments administered, and dataobtained were analyzed with t-test and Analysis of Variance. Findings revealed, among others, that there was a significant effect of treatments on students' cognitive attainment and on practical skills acquisition. Students exposed to guided inquiry (with/without demonstration) strategies achieved better than those exposed to demonstration with conventional strategy. It is therefore recommended, among others, that Lecturers in Colleges of Education should utilize the guided inquiry strategy for teaching concepts in chemistry.

Keywords: instructional strategy, practical chemistry, learning outcomes, pre-service teachers

Procedia PDF Downloads 89

Authors: Mingxin Li, Liya Ni

Abstract:

Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

Procedia PDF Downloads 124

Authors: Cláudia Moço, Maria Santos, Carlos Arsénio, Débora Mendes, Miguel Oliveira. José Paulo Da Silva

Abstract:

Construction industry generates large amounts of waste all over the world. About 450 million tons of construction and demolition wastes (C&DW) are produced annually in the European Union. C&DW are highly heterogeneous materials in size and composition, which imposes strong difficulties on their management. Directive n.º 2008/98/CE, of the European Parliament and of the Council of 6 November establishes that 70 % of the C&DW have to be recycled by 2020. To evaluate possible applications of these materials, a detailed physical, chemical and environmental characterization is necessary. Multi Triagem, Lda. is a company located in Algarve (Portugal) and was supported by the European Regional Development Fund (grant QREN 30307 Multivalor) to quantify and characterize the received C&DW, in order to evaluate their possible applications. This evaluation, performed in collaboration with the University of Algarve, involves a physical, chemical and environmental detailed characterization of the received C&DW. In this work we report on the amounts, trial procedures and properties of the C&DW received over a period of fifteen month. In this period the company received C&DW coming from 393 different origins. The total amount was 32.458 tons, mostly mixtures containing concrete, masonry/mortar and soil/rock. Most of C&DW came from demodulation constructions and diggings. The organic/inert component, namely metal, glass, wood and plastics, were screened first and account for about 3 % of the received materials. The remaining materials were screened and grouped according to their origin and contents, the latter evaluated by visual inspection. Twenty five samples were prepared and submitted to a detailed physical, chemical and environmental analysis. The C&DW aggregates show lower quality properties than natural aggregates for concrete preparation and unbound layers of road pavements. However, chemical analyzes indicated that most samples are environmentally safe. A continuous monitoring of the presence of heavy metals and organic compounds is needed in order to perform a proper screening of the C&DW. C&DW aggregates provide a good alternative to natural aggregates.

Keywords: construction and demolition wastes, waste classification, waste composition, waste screening

Procedia PDF Downloads 335

Authors: Ahmed Cherif Megri, HossamEldin ElSherif

Abstract:

In a power plant, the header pipe plays a pivotal role in optimizing the performance of diverse systems by serving as a central conduit for the collection and distribution of steam within the plant. This paper investigates the significance of header pipes within power plant setups, highlighting their critical influence on reliability, efficiency, and the performance of the power plant as a whole. The concept of shape optimization emerges as a crucial factor in power plant design and operation, with the potential to maximize performance while minimizing the use of materials. Shape optimization not only enhances efficiency but also contributes to reducing the environmental footprint of power plant installations. In this paper, we initially developed a methodology designed for optimizing header shapes with the primary goal of reducing the usage of costly new alloy materials and lowering the overall maintenance operation expenses. Secondly, we conducted a case study based on an authentic header sourced from an operational power plant.

Keywords: shape optimization, header, power plant, inconel alloy, CFD, structural optimization

Procedia PDF Downloads 53

Authors: Anamika Devi

Abstract:

Based on Vygotsky’s cultural, historical theory and Hedegaard’s concept of transition, this study aims to investigate to propose strategies to maintain digital wellbeing of children and parents during and post COVID pandemic. Due COVID 19 pandemic, children and families have been facing new challenges and sudden changes in their everyday life. While children are juggling to adjust themselves in new circumstance of onsite and online learning settings, parents are juggling with their work-life balance. A number of papers have identified that the COVID-19 pandemic has affected the lives of many families around the world in many ways, for example, the stress level of many parents increased, families faced financial difficulties, uncertainty impacted on long term effects on their emotional and social wellbeing. After searching and doing an intensive literature review from 2020 and 2021, this study has found some scholarly articles provided solution or strategies of reducing stress levels of parents and children in this unprecedented time. However, most of them are not underpinned by proper theoretical lens to ensure they validity and success. Therefore, this study has proposed strategies that are underpinned by theoretical lens to ensure their impact on children’s and parents' emotional wellbeing during and post COVID-19 era. The strategies will highlight on activities for positive coping strategies to the best use of family values and digital technologies.

Keywords: onsite and online learning, strategies, emotional wellbeing, tips, and strategies, COVID19

Procedia PDF Downloads 154

Authors: Zachary Huffman, Joana Rocha

Abstract:

Wall-pressure fluctuations induced by the turbulent boundary layer (TBL) developed over aircraft are a significant source of aircraft cabin noise. Since the power spectral density (PSD) of these pressure fluctuations is directly correlated with the amount of sound radiated into the cabin, the development of accurate empirical models that predict the PSD has been an important ongoing research topic. The sound emitted can be represented from the pressure fluctuations term in the Reynoldsaveraged Navier-Stokes equations (RANS). Therefore, early TBL empirical models (including those from Lowson, Robertson, Chase, and Howe) were primarily derived by simplifying and solving the RANS for pressure fluctuation and adding appropriate scales. Most subsequent models (including Goody, Efimtsov, Laganelli, Smol’yakov, and Rackl and Weston models) were derived by making modifications to these early models or by physical principles. Overall, these models have had varying levels of accuracy, but, in general, they are most accurate under the specific Reynolds and Mach numbers they were developed for, while being less accurate under other flow conditions. Despite this, recent research into the possibility of using alternative methods for deriving the models has been rather limited. More recent studies have demonstrated that an artificial neural network model was more accurate than traditional models and could be applied more generally, but the accuracy of other machine learning techniques has not been explored. In the current study, an original model is derived using a stepwise regression algorithm in the statistical programming language R, and TBL wall-pressure fluctuations PSD data gathered at the Carleton University wind tunnel. The theoretical advantage of a stepwise regression approach is that it will automatically filter out redundant or uncorrelated input variables (through the process of feature selection), and it is computationally faster than machine learning. The main disadvantage is the potential risk of overfitting. The accuracy of the developed model is assessed by comparing it to independently sourced datasets.

Keywords: aircraft noise, machine learning, power spectral density models, regression models, turbulent boundary layer wall-pressure fluctuations

Procedia PDF Downloads 126

Authors: Victoria L. Malakhova

Abstract:

The research is devoted to multimodal content and its effectiveness in developing students’ linguistic and intercultural communicative competences as an indefeasible constituent of their future professional activity. Description of multimodal content both as a linguistic and didactic phenomenon makes the study relevant. The objective of the article is the analysis of creolized texts and the effect they have on fostering higher education students’ skills and their productivity. The main methods used are linguistic text analysis, qualitative and quantitative methods, deduction, generalization. The author studies texts with full and partial creolization, their features and role in composing multimodal textual space. The main verbal and non-verbal markers and paralinguistic means that enhance the linguo-pragmatic potential of creolized texts are covered. To reveal the efficiency of multimodal content application in English teaching, the author conducts an experiment among both undergraduate students and teachers. This allows specifying main functions of creolized texts in the process of language learning, detecting ways of enhancing students’ competences, and increasing their motivation. The described stages of using creolized texts can serve as an algorithm for work with multimodal content in teaching English as a foreign language. The findings contribute to improving the efficiency of the academic process.

Keywords: creolized text, English language learning, higher education, language and communication competences, multimodal content

Procedia PDF Downloads 101

Authors: Richard White, Anne Drabble, Maureen O’Neill

Abstract:

The University of the Sunshine Coast (USC) offers secondary school students in the final two years of school (Years 11 and 12, 16 – 18 years of age) an opportunity to participate in a program which provides an accelerated pathway to tertiary studies. Whilst still at secondary school, the students undertake two first year university subjects that are required subjects in USC undergraduate degree programs. The program is called Integrated Learning Pathway (ILP) and offers a range of disciplines, including business, design, drama, education, and engineering. Between 2010 and 2014, 38% of secondary students who participated in an ILP program commenced undergraduate studies at USC following completion of secondary school studies. The research reported here considers “before and after” literacy and numeracy competencies of students to determine what impact participation in the ILP program has had on their academic skills. Qualitative and quantitative data has been gathered via numeracy and literacy testing of the students, and a survey asking the students to self-evaluate their numeracy and literacy skills, and reflect on their views of these academic skills. The research will enable improved targeting of teaching strategies so that students will acquire not only course-specific learning outcomes but also collateral academic skills. This enhancement of academic skills will improve undergraduate experience and improve student retention.

Keywords: academic skills enhancement, accelerated pathways, improved teaching, student retention

Procedia PDF Downloads 294

Authors: Shilpagauri Prasad Ganpule

Abstract:

The teaching of drama is considered as the most significant and noteworthy area in an ESL classroom. Diverse innovative techniques can be used to make the teaching of drama worthwhile and interesting. The paper presents the different innovative techniques that can be used while teaching Henrik Ibsen’s A Doll’s House [2007]. The innovative techniques facilitate students’ understanding and comprehension of the text. The use of the innovative techniques makes them explore the dramatic text and uncover a multihued arena of meanings hidden in it. They arouse the students’ interest and assist them overcome the difficulties created by the second language. The diverse innovative techniques appeal to the imagination of the students and increase their participation in the classroom. They help the students in the appreciation of the dramatic text and make the teaching learning situation a fruitful experience for both the teacher and students. The students successfully overcome the problem of L2 comprehension and grasp the theme, story line and plot-structure of the play effectively. The innovative techniques encourage a strong sense of participation on the part of the students and persuade them to learn through active participation. In brief, the innovative techniques promote the students to perform various tasks and expedite their learning process. Thus the present paper makes an attempt to present varied innovative techniques that can be used while teaching drama. It strives to demonstrate how the use of innovative techniques improve and enhance the students’ understanding and appreciation of Ibsen’s A Doll’s House [2007].

Keywords: ESL classroom, innovative techniques, students’ participation, teaching of drama

Procedia PDF Downloads 611

Authors: Esra Turker, Umit Hakan Yildiz, Ahu Arslan Yildiz

Abstract:

The key of regenerative medicine is mimicking natural three dimensional (3D) microenvironment of tissues by utilizing appropriate biomaterials. In this study, a synthetic biodegradable polymer; poly (L-lactide-co-ε-caprolactone) (PLLCL) and a natural polymer; collagen was used to mimic the biochemical structure of the natural extracellular matrix (ECM), and by means of electrospinning technique the real physical structure of ECM has mimicked. PLLCL/Collagen biocomposite scaffolds enables cell attachment, proliferation and nutrient transport through fabrication of micro to nanometer scale nanofibers. Biocomposite materials are commonly preferred due to limitations of physical and biocompatible properties of natural and synthetic materials. Combination of both materials improves the strength, degradation and biocompatibility of scaffold. Literature studies have shown that collagen is mostly solved with heavy chemicals, which is not suitable for cell culturing. To overcome this problem, a new approach has been developed in this study where polyvinylpyrrolidone (PVP) is used as co-electrospinning agent. PVP is preferred due to its water solubility, so PLLCL/collagen biocomposite scaffold can be easily and rapidly produced. Hydrolytic and enzymatic biodegradation as well as mechanical strength of scaffolds were examined in vitro. Cell adhesion, proliferation and cell morphology characterization studies have been performed as well. Further, on-chip drug screening analysis has been performed over 3D tumor models. Overall, the developed biocomposite scaffold was used for 3D tumor model formation and obtained results confirmed that developed model could be used for drug screening studies to predict clinical efficacy of a drug.

Keywords: biomaterials, 3D cell culture, drug screening, electrospinning, lab-on-a-chip, tissue engineering

Procedia PDF Downloads 298

Authors: Claire Xu, Welton Wang, Manasvi Pinnaka, Anqi Pan, Michael Han

Abstract:

Hospitalizations account for one-third of the total health care spending in the US. Early risk detection and intervention can reduce this high cost and increase the satisfaction of both patients and physicians. Due to the lack of awareness of the potential arising risks in home environment, the opportunities for patients to seek early actions of clinical visits are dramatically reduced. This research aims to offer a highly personalized remote patients monitoring and risk assessment AI framework to identify the potentially preventable hospitalization for both acute as well as chronic diseases. A hybrid-AI framework is trained with data from clinical setting, patients surveys, as well as online databases. 20+ risk factors are analyzed ranging from activities, biometric info, demographic info, socio-economic info, hospitalization history, medication info, lifestyle info, etc. The AI model yields high performance of 87% accuracy and 88 sensitivity with 20+ features. This hybrid-AI framework is proven to be effective in identifying the potentially preventable hospitalization. Further, the high indicative features are identified by the models which guide us to a healthy lifestyle and early intervention suggestions.

Keywords: hospitalization prevention, machine learning, remote patient monitoring, risk prediction

Procedia PDF Downloads 204

Authors: G. Singer, M. Golan

Abstract:

Providing students with learning disabilities (LD) with extra time to grant them equal access to the exam is a necessary but insufficient condition to compensate for their LD; there should also be a clear indication that the additional time was actually used. For example, if students with LD use more time than students without LD and yet receive lower grades, this may indicate that a different accommodation is required. If they achieve higher grades but use the same amount of time, then the effectiveness of the accommodation has not been demonstrated. The main goal of this study is to evaluate the effect of including parameters related to LD and extended exam time, along with other commonly-used characteristics (e.g., student background and ability measures such as high-school grades), on the ability of ordinal decision-tree algorithms to predict exam performance. We use naturally-occurring data collected from hundreds of undergraduate engineering students. The sub-goals are i) to examine the improvement in prediction accuracy when the indicator of exam performance includes 'actual time used' in addition to the conventional indicator (exam grade) employed in most research; ii) to explore the effectiveness of extended exam time on exam performance for different courses and for LD students with different profiles (i.e., sets of characteristics). This is achieved by using the patterns (i.e., subgroups) generated by the algorithms to identify pairs of subgroups that differ in just one characteristic (e.g., course or type of LD) but have different outcomes in terms of exam performance (grade and time used). Since grade and time used to exhibit an ordering form, we propose a method based on ordinal decision-trees, which applies a weighted information-gain ratio (WIGR) measure for selecting the classifying attributes. Unlike other known ordinal algorithms, our method does not assume monotonicity in the data. The proposed WIGR is an extension of an information-theoretic measure, in the sense that it adjusts to the case of an ordinal target and takes into account the error severity between two different target classes. Specifically, we use ordinal C4.5, random-forest, and AdaBoost algorithms, as well as an ensemble technique composed of ordinal and non-ordinal classifiers. Firstly, we find that the inclusion of LD and extended exam-time parameters improves prediction of exam performance (compared to specifications of the algorithms that do not include these variables). Secondly, when the indicator of exam performance includes 'actual time used' together with grade (as opposed to grade only), the prediction accuracy improves. Thirdly, our subgroup analyses show clear differences in the effect of extended exam time on exam performance among different courses and different student profiles. From a methodological perspective, we find that the ordinal decision-tree based algorithms outperform their conventional, non-ordinal counterparts. Further, we demonstrate that the ensemble-based approach leverages the strengths of each type of classifier (ordinal and non-ordinal) and yields better performance than each classifier individually.

Keywords: actual exam time usage, ensemble learning, learning disabilities, ordinal classification, time extension

Procedia PDF Downloads 92

Authors: Seongcheol Kwon, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.

Keywords: situation-awareness, smart home, IoT, machine learning, classifier

Procedia PDF Downloads 407

Authors: A. Mohammed, R. Lewis, M. Marshall

Abstract:

Commonly used coatings to protect tools in die casting were used. A heat treatment and then surface coating can have a large effect on erosion damage. Samples have been tested to evaluate their resistances to erosive wear and to assess how this compares with behaviour seen for untreated material. Five commercial (PN + TiN), (PN + TiAlCN), (TiN X 2), (TiN), and (TiAlCN) coatings have been evaluated for their wear resistance. The objective was to permit an optimized selection of coatings to be used to give good resistance to erosive wear. A test-Rig has been developed to study the erosive wear in aluminium die casting and provide an environment similar to industrial operation that is more practical than using actual machines. These surfaces were analysed using a Scanning Electron Microscope (SEM) and Optical Microscopes each with a different level of resolution. Examination of coating materials revealed an important parameter associated with the failure of the coating materials.This was adhesion of the coating material to the substrate surface. A well-adhered coating withstands wear much better compared to the poorest-adhering coating.

Keywords: solid particle erosion, PVD-coatings, steel, erosion testing

Procedia PDF Downloads 230

Authors: A. A. Bajad, B. P. Sharma, Y. C. Gupta, B. S. Dilt, R. K. Gupta

Abstract:

The present investigations were carried out at the experimental farm of Department of Floriculture and Landscape Architecture, Dr. Y. S. Parmar University of Horticulture and Forestry, Nauni, Solan, H.P. during 2015 and 2016. The experiment was laid out in a Randomized Block Design (factorial) consisting of 48 treatment combinations of four planting dates viz., D1- mid March, D2-mid April, D3-mid May and D4- mid June and two cultivars namely V1- Kamini and V2 -Poornima with six mulching materials M¬0¬- without mulch, M1- Black plastic mulch (100 µ), M2- Silver plastic mulch (100 µ), M3¬- Transparent plastic mulch (100 µ), M3-Transparent plastic mulch (100 µ), M4¬- Pine needle (100 µ) and M5- Grass (1 inch layer). Among different planting times, D4 i.e. mid June planting obtained best results for number of seed per flower (179.38), germination percent (83.92 %), electrical conductivity (0.97 ds/m), seedling length (7.93 cm), seedling dry weight (7.09 mg), seedling vigour index I (763.79), moisture content (7.83 %) and 1000 seed weight (1.94 g). However, seed yield per plant (14.30 g) was recorded to be maximum in mid of March. Among the cultivars, cv. ‘Poornima’ gave best results for number of seed per plant (187.30). However, cv. ‘Kamini’ recorded the best result for seed yield per plant (12.55), electrical conductivity (1.11 ds/m), germination percent (80.47 %), seedling length (6.39 cm), seedling dry weight (5.11 mg), seedling vigour index I (649.49), moisture content (9.28 %) and 1000 seed weight (1.70 g). Silver plastic obtained best results for number of seed per flower (170.10), seed yield per plant (15.66 g), germination percent (80.17 %), electrical conductivity (1.26 ds/m), seedling length (5.88 cm), seedling dry weight (4.46 mg), seedling vigour index I (616.78), Moisture content (9.35 %) and 100 seed weight (1.97 g).

Keywords: cultivars, mulch materials, planting times, flowers

Procedia PDF Downloads 259

Authors: Wajid Mumtaz, Aamir Saeed Malik, Syed Saad Azhar Ali, Mohd Azhar Mohd Yasin

Abstract:

In this paper, a technique based on electroencephalogram (EEG) analysis is presented, aiming for diagnosing major depressive disorder (MDD) among a potential population of MDD patients and healthy controls. EEG is recognized as a clinical modality during applications such as seizure diagnosis, index for anesthesia, detection of brain death or stroke. However, its usability for psychiatric illnesses such as MDD is less studied. Therefore, in this study, for the sake of diagnosis, 2 groups of study participants were recruited, 1) MDD patients, 2) healthy people as controls. EEG data acquired from both groups were analyzed involving inter-hemispheric asymmetry and composite permutation entropy index (CPEI). To automate the process, derived quantities from EEG were utilized as inputs to classifier such as logistic regression (LR) and support vector machine (SVM). The learning of these classification models was tested with a test dataset. Their learning efficiency is provided as accuracy of classifying MDD patients from controls, their sensitivities and specificities were reported, accordingly (LR =81.7 % and SVM =81.5 %). Based on the results, it is concluded that the derived measures are indicators for diagnosing MDD from a potential population of normal controls. In addition, the results motivate further exploring other measures for the same purpose.

Keywords: major depressive disorder, diagnosis based on EEG, EEG derived features, CPEI, inter-hemispheric asymmetry

Procedia PDF Downloads 533

Authors: Rahul R. Gurpude, Pallvita Yadav, Amrut Mulay

Abstract:

In recent years, there has been a growing focus on advanced manufacturing processes, and one such emerging process is wire electric discharge machining (WEDM). WEDM is a precision machining process specifically designed for cutting electrically conductive materials with exceptional accuracy. It achieves material removal from the workpiece metal through spark erosion facilitated by electricity. Initially developed as a method for precision machining of hard materials, WEDM has witnessed significant advancements in recent times, with numerous studies and techniques based on electrical discharge phenomena being proposed. These research efforts and methods in the field of ED encompass a wide range of applications, including mirror-like finish machining, surface modification of mold dies, machining of insulating materials, and manufacturing of micro products. WEDM has particularly found extensive usage in the high-precision machining of complex workpieces that possess varying hardness and intricate shapes. During the cutting process, a wire with a diameter ranging from 0.18mm is employed. The evaluation of EDM performance typically revolves around two critical factors: material removal rate (MRR) and surface roughness (SR). To comprehensively assess the impact of machining parameters on the quality characteristics of EDM, an Analysis of Variance (ANOVA) was conducted. This statistical analysis aimed to determine the significance of various machining parameters and their relative contributions in controlling the response of the EDM process. By undertaking this analysis, optimal levels of machining parameters were identified to achieve desirable material removal rates and surface roughness.

Keywords: WEDM, MRR, optimization, surface roughness

Procedia PDF Downloads 63

Authors: Juhanita Jiman

Abstract:

This paper aims to demonstrate how androgogical approach can help educators to facilitate animation students with better understanding of their acquired technical knowledge and skills while introducing them to crucial content and ethical values. In this borderless world, it is important for the educators to know that they are dealing with young adults who are heavily influenced by their surroundings. Naturally, educators are not only handling academic issues, they are also burdened with social obligations. Appropriate androgogical approach can be beneficial for both educators and students to tackle these problems. We used to think that teaching pedagogy is important at all level of age. Unfortunately, pedagogical approach is not entirely applicable to university students because they are no longer children. Pedagogy is a teaching approach focusing on children, whereas andragogy is specifically focussing on teaching adults and helping them to learn better. As adults mature, they become increasingly independent and responsible for their own actions. In many ways, the pedagogical model is not really suitable for such developmental changes, and therefore, produces tension, dissatisfaction, and resistance in individual student. The ever-changing technology has resulted in animation students to be very competitive in acquiring their technical skills, making them forget and neglecting the importance of the core values of a story. As educators, we have to guide them not only to excel in achieving knowledge, skills and technical expertise but at the same time, show them what is right or wrong and encourage them to inculcate moral values in their work.

Keywords: andragogy, animation, artistic contents, productive learning environment

Procedia PDF Downloads 265

Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun

Abstract:

Speech emotion recognition (SER) is for recognizing human subjective emotions through audio data in-depth analysis. From speech audios, how to comprehensively extract emotional information and how to effectively fuse extracted features remain challenging. This paper presents a dual-stream SER framework that embraces both full training and transfer learning of different networks for thorough feature encoding. Besides, a plug-and-play cross-attention fusion (CAF) module is implemented for the valid integration of the dual-stream encoder output. The effectiveness of the proposed CAF module is compared to the other three fusion modules (feature summation, feature concatenation, and feature-wise linear modulation) on two databases (RAVDESS and IEMO-CAP) using different dual-stream encoders (full training network, DPCNN or TextRCNN; transfer learning network, HuBERT or Wav2Vec2). Experimental results suggest that the CAF module can effectively reconcile conflicts between features from different encoders and outperform the other three feature fusion modules on the SER task. In the future, the plug-and-play CAF module can be extended for multi-branch feature fusion, and the dual-stream SER framework can be widened for multi-stream data representation to improve the recognition performance and generalization capacity.

Keywords: speech emotion recognition, cross-attention fusion, dual-stream, pre-trained

Procedia PDF Downloads 55

Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

Abstract:

Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

Procedia PDF Downloads 120

Authors: Sibel Daglilar, Isil Kerti, Murat Karagoz, Fatih Dumludag, Oguzhan Gunduz, Faik Nuzhet Oktar

Abstract:

Hydroxyapatite (HA) materials have common use in bone repairing due to its ability to accelerate the bone growth around the implant. In spite of being a biocompatible and bioactive material, HA has a limited usage as an implant material because of its weak mechanical properties. HA based composites are required to improve the strength and toughness properties of the implant materials without compromising of biocompatibility. The excellent mechanical properties and higher biocompatibilities are expected from each of biomedical composites. In this study, HA composites were synthesized by using bovine bone reinforced doped with different amount of (wt.%) Li2O. The pressed pellets were sintered at various sintering temperatures between 1000ºC and 1300°C, and mechanical, electrical properties of the obtained products were characterized. In addition to that, in vitro stimulated body fluid (SBF) tests for these samples were conducted. The most suitable composite composition for biomedical applications was discussed among the composites studied.

Keywords: biocomposites, sintering temperature, biocompatibility, electrical property, conductivity, mechanical property

Procedia PDF Downloads 386

Authors: Abdul Basit Kiani, Maryam Kiani

Abstract:

Online developers now have the tools necessary to create online apps that are not only reliable but also highly interactive, thanks to the introduction of JavaScript frameworks and APIs. The objective is to give a broad overview of the recent advances in the area. The fusion of machine learning (ML) and artificial intelligence (AI) has expanded the possibilities for web development. Modern websites now include chatbots, clever recommendation systems, and customization algorithms built in. In the rapidly evolving landscape of modern websites, it has become increasingly apparent that user engagement and personalization are key factors for success. To meet these demands, websites now incorporate a range of innovative technologies. One such technology is chatbots, which provide users with instant assistance and support, enhancing their overall browsing experience. These intelligent bots are capable of understanding natural language and can answer frequently asked questions, offer product recommendations, and even help with troubleshooting. Moreover, clever recommendation systems have emerged as a powerful tool on modern websites. By analyzing user behavior, preferences, and historical data, these systems can intelligently suggest relevant products, articles, or services tailored to each user's unique interests. This not only saves users valuable time but also increases the chances of conversions and customer satisfaction. Additionally, customization algorithms have revolutionized the way websites interact with users. By leveraging user preferences, browsing history, and demographic information, these algorithms can dynamically adjust the website's layout, content, and functionalities to suit individual user needs. This level of personalization enhances user engagement, boosts conversion rates, and ultimately leads to a more satisfying online experience. In summary, the integration of chatbots, clever recommendation systems, and customization algorithms into modern websites is transforming the way users interact with online platforms. These advanced technologies not only streamline user experiences but also contribute to increased customer satisfaction, improved conversions, and overall website success.

Keywords: Javascript, machine learning, artificial intelligence, web development

Procedia PDF Downloads 60

Authors: Hoora Dehghani, Meisam Shahbazi, Reza Zare

Abstract:

During the previous decade, a significant evolution has occurred in the number of private educational centers and, accordingly, the increase in the number of providers and students of these centers around the world. The number of language teaching institutes in Iran that are considered private educational sectors is also growing exponentially as the request for learning foreign languages has extremely increased in recent years. This fact caused competition among the institutions in improving better services tailored to the students’ demands to win the competition. Along with the growth in the industry of education, higher education institutes should apply the marketing-related concepts and view students as customers because students’ outlooks are similar to consumers with education. Studying the influential factors in the selection of an institute has multiple benefits. Firstly, it acknowledges the institutions of the students’ choice factors. Secondly, the institutions use the obtained information to improve their marketing methods. It also helps institutions know students’ outlooks that can be applied to expand the student know-how. Moreover, it provides practical evidence for educational centers to plan useful amenities and programs, and use efficient policies to cater to the market, and also helps them execute the methods that increase students’ feeling of contentment and assurance. Thus, this study explored the influencing factors in the selection of a language learning institute by language learners and examined and compared the importance among the varying age groups and genders. In the first phase of the study, the researchers selected 15 language learners as representative cases within the specified age ranges and genders purposefully and interviewed them to explore the comprising elements in their language institute selection process and analyzed the results qualitatively. In the second phase, the researchers identified elements as specified items of a questionnaire, and 1000 English learners across varying educational contexts rated them. The TOPSIS method was used to analyze the data quantitatively by representing the level of importance of the items for the participants generally and specifically in each subcategory; genders and age groups. The results indicated that the educational quality, teaching method, duration of training course, establishing need-oriented courses, and easy access were the most important elements. On the other hand, offering training in different languages, the specialized education of only one language, the uniform and appropriate appearance of office staff, having native professors to the language of instruction, applying Computer or online tests instead of the usual paper tests respectively as the least important choice factors in selecting a language institute. Besides, some comparisons among different groups’ ratings of choice factors were made, which revealed the differences among different groups' priorities in choosing a language institute.

Keywords: choice factors, EFL institute selection, english learning, need analysis, TOPSIS

Procedia PDF Downloads 149

Authors: Eser Yarar, Fahri Vatansever, A. Tamer Erturk, Sedat Karabay

Abstract:

In this study, drilling behavior of multi-layer orthotropic polyester composites reinforced with woven polyester fiber and PTFE particle was investigated. Conventional drilling methods have low cost and ease of use. Therefore, it is one of the most preferred machining methods. The increasing range of use of composite materials in many areas has led to the investigation of the machinability performance of these materials. The drilling capability of the synthetic polymer composite material was investigated by measuring the cutting forces using different tool diameters, feed rate and high cutting speed parameters. Cutting forces were measured using a dynamometer in the experiments. In order to evaluate the results of the experiment, the Taguchi experimental design method was used. According to the results, the optimum cutting parameters were obtained for 0.1 mm/rev, 1070 rpm and 2 mm diameter drill bit. Verification tests were performed for the optimum cutting parameters obtained according to the model. Verification experiments showed the success of the established model.

Keywords: cutting force, drilling, polimer composite, Taguchi

Procedia PDF Downloads 152