Search results for: artificial teacher

Authors: Edgar Mauricio Ruiz Osuna, Claudia Yaneth Herrera Bolivar, Sandra Liliana Gomez Vasquez

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The increasing needs of professionals with skills in software development in industry are incremental, therefore, the relevance of an educational process in line with the strengthening of these competencies, are part of the responsibilities of universities with careers related to the area of Informatics and Systems. In this sense, it is important to consider that in the National Science, Technology and Innovation Plan for the development of the Electronics, Information Technologies and Communications (2013) sectors, it is established as a weakness in the SWOT Analysis of the Software sector and Services, Deficiencies in training and professional training. Accordingly, UNIMINUTO's Computer Technology Program has addressed the analysis of students' performance in software development, identifying various problems such as dropout in programming subjects, academic averages, as well as deficiencies in strategies and competencies developed in the area of programming. As a result of this analysis, it was determined to design a collaborative learning platform in basic programming using heat maps as a tool to support didactic feedback. The pilot phase allows to evaluate in a programming course the ALGORINFO platform as a didactic resource, through an interactive and collaborative environment where students can develop basic programming practices and in turn, are fed back through the analysis of time patterns and difficulties frequent in certain segments or program cycles, by means of heat maps. The result allows the teacher to have tools to reinforce and advise critical points generated on the map, so that students and graduates improve their skills as software developers.

Keywords: collaborative platform, learning, feedback, programming, heat maps

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Authors: Promise Ekpo Osaine, Daniel Melesse

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Image captioning is an active area of research in the multi-modal artificial intelligence (AI) community as it connects vision and language understanding, especially in settings where it is required that a model understands the content shown in an image and generates semantically and grammatically correct descriptions. In this project, we followed a standard approach to a deep learning-based image captioning model, injecting architecture for the encoder-decoder setup, where the encoder extracts image features, and the decoder generates a sequence of words that represents the image content. As such, we investigated image encoders, which are ResNet101, InceptionResNetV2, EfficientNetB7, EfficientNetV2M, and CLIP. As a caption generation structure, we explored long short-term memory (LSTM). The CLIP-LSTM model demonstrated superior performance compared to the encoder-decoder models, achieving a BLEU-1 score of 0.904 and a BLEU-4 score of 0.640. Additionally, among the CNN-LSTM models, EfficientNetV2M-LSTM exhibited the highest performance with a BLEU-1 score of 0.896 and a BLEU-4 score of 0.586 while using a single-layer LSTM.

Keywords: multi-modal AI systems, image captioning, encoder, decoder, BLUE score

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Authors: Rabia Korkmaz Tan, Şebnem Bora

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The major problem encountered when modeling complex systems with agent-based modeling and simulation techniques is the existence of large parameter spaces. A complex system model cannot be expected to reflect the whole of the real system, but by specifying the most appropriate parameters, the actual system can be represented by the model under certain conditions. When the studies conducted in recent years were reviewed, it has been observed that there are few studies for parameter tuning problem in agent based simulations, and these studies have focused on tuning parameters of a single model. In this study, an approach of parameter tuning is proposed by using metaheuristic algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colonies (ABC), Firefly (FA) algorithms. With this hybrid structured study, the parameter tuning problems of the models in the different fields were solved. The new approach offered was tested in two different models, and its achievements in different problems were compared. The simulations and the results reveal that this proposed study is better than the existing parameter tuning studies.

Keywords: parameter tuning, agent based modeling and simulation, metaheuristic algorithms, complex systems

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Authors: Hannah Kolano, Paul Nadan, Jeremy Ryan, Sophia Nielsen

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The hooves of goats and other ruminants, or the family Ruminantia, are uniquely structured to adapt to rough terrain. Their hooves possess a hard outer shell and a soft interior that allow them to both conform to uneven surfaces and hook onto prominent features. In an effort to apply this unique mechanism to a robotics context, artificial feet for a hexapedal robot have been designed based on the hooves of ruminants to improve the robot’s ability to traverse unstructured environments such as those found on a rocky planet or asteroid, as well as in earth-based environments such as rubble, caves, and mountainous regions. The feet were manufactured using a combination of 3D printing and polyurethane casting techniques and attached to a commercially available hexapedal robot. The robot was programmed with a terrain-adaptive gait and proved capable of traversing a variety of uneven surfaces and inclines. This development of more adaptable robotic feet allows legged robots to operate in a wider range of environments and expands their possible applications.

Keywords: biomimicry, legged locomotion, robotic foot design, ruminant feet, unstructured terrain navigation

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Authors: Ahmed M. Noureldin, Khaled M. Naguib

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This experimental investigation tries to identify the root cause of the black sand issue in one of the man-made lakes in a well-known Hurghada resort. The lake is nourished by the underground wells' source, which continuously empties into the Red Sea. Chemical testing was done by looking at spots of stinky black sand beneath the sandy lake surface. The findings on samples taken from several locations (wells, lake bottom sand samples, and clean sand with exact specifications as bottom sand) indicated the existence of organic sulfur bacteria that are responsible for the phenomena of black sand. Approximately 39.139 mg/kg of sulfide in the form of hydrogen sulfide was present in the lake bottom sand, while 1.145 mg/kg, before usage, was in the bare sand. The study also involved modeling with the GPS-X program for cleaning bottom sand that uses hydro cyclones as a physical-mechanical treatment method. The modeling findings indicated a Total Organic Carbon (TOC) removal effectiveness of 0.65%. The research recommended using hydro cyclones to routinely mechanically clear the sand from lake bottoms.

Keywords: man-made lakes, organic sulfur bacteria, total organic carbon, hydro cyclone

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Authors: Adam Beaunoyer, Cory Beaunoyer, Mohammed Elmorsy, Hanan Saleh

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This research aims to create a reinforcement learning agent capable of racing in challenging simulated environments with a low collision count. We present a reinforcement learning agent that can navigate challenging tracks using both a Deep Q-Network (DQN) and a Soft Actor-Critic (SAC) method. A challenging track includes curves, jumps, and varying road widths throughout. Using open-source code on Github, the environment used in this research is based on the 1995 racing game WipeOut. The proposed reinforcement learning agent can navigate challenging tracks rapidly while maintaining low racing completion time and collision count. The results show that the SAC model outperforms the DQN model by a large margin. We also propose an alternative multiple-car model that can navigate the track without colliding with other vehicles on the track. The SAC model is the basis for the multiple-car model, where it can complete the laps quicker than the single-car model but has a higher collision rate with the track wall.

Keywords: reinforcement learning, soft actor-critic, deep q-network, self-driving cars, artificial intelligence, gaming

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Authors: Maria Lina Garrido

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This paper aims to reflect upon instruction in English classes with the specific purpose of reading comprehension development, having as its paradigm the considerations presented by William Grabe, in his book Reading in a Second Language: Moving from theory to practice. His concerns regarding the connection between research findings and instructional practices have stimulated the present author to re-evaluate both her long practice as an English reading teacher and as the author of two reading textbooks for graduate students. Elements of the reading process such as linguistic issues, prior knowledge, reading strategies, critical evaluation, and motivation are the main foci of this analysis as far as the activities developed in the classroom are concerned. The experience with university candidates on postgraduate courses with different levels of English knowledge in Bahia, Brazil, has definitely demanded certain adjustments to this author`s classroom setting. Word recognition based on cognates, for example, has been emphasized given the fact that academic texts use many Latin words which have the same roots as the Brazilian Portuguese lexicon. Concerning syntactic parsing, the tenses/verbal aspects, modality and linking words are included in the curriculum, but not with the same depth as the general English curricula. Reading strategies, another essential predictor for developing reading skills, have been largely stimulated in L2 classes in order to compensate for a lack of the appropriate knowledge of the foreign language. This paper presents results that demonstrate that this author`s teaching practice is compatible with the implications and instruction concerning the reading process outlined by Grabe, however, it admits that each class demands specific instructions to meet the needs of that particular group.

Keywords: classroom practice, instructional activities, reading comprehension, reading skills

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Authors: Jing Yuan, Hongwei Yang

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This paper aims to understand U.S. middle school students’ mathematics achievements by examining relevant student and school-level predictors. Through a variance component analysis, the study first identifies evidence supporting the use of multilevel modeling. Then, a multilevel analysis is performed under Bayesian statistical inference where prior information is incorporated into the modeling process. During the analysis, independent variables are entered sequentially in the order of theoretical importance to create a hierarchy of models. By evaluating each model using Bayesian fit indices, a best-fit and most parsimonious model is selected where Bayesian statistical inference is performed for the purpose of result interpretation and discussion. The primary dataset for Bayesian modeling is derived from the Program for International Student Assessment (PISA) in 2012 with a secondary PISA dataset from 2003 analyzed under the traditional ordinary least squares method to provide the information needed to specify informative priors for a subset of the model parameters. The dependent variable is a composite measure of mathematics literacy, calculated from an exploratory factor analysis of all five PISA 2012 mathematics achievement plausible values for which multiple evidences are found supporting data unidimensionality. The independent variables include demographics variables and content-specific variables: mathematics efficacy, teacher-student ratio, proportion of girls in the school, etc. Finally, the entire analysis is performed using the MCMCpack and MCMCglmm packages in R.

Keywords: Bayesian multilevel modeling, mathematics education, PISA, multilevel

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Authors: Suttipong Phosuksirikul, Rawichar Chaipojjana, Arunsri Leejeerajumnean

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The aim of research was to define the relations between volatile compounds, some parameters (pH, titratable acidity (TA), total soluble solid (TSS), lactic acid bacteria count) and consumer preference of commercial fermented milks. These relations tend to be used for controlling and developing new fermented milk product. Three leading commercial brands of fermented milks in Thailand were evaluated by consumers (n=71) using hedonic scale for four attributes (sweetness, sourness, flavour, and overall liking), volatile compounds using headspace-solid phase microextraction (HS-SPME) GC-MS, pH, TA, TSS and LAB count. Then the relations were analyzed by principal component analysis (PCA). The PCA data showed that all of four attributes liking scores were related to each other. They were also related to TA, TSS and volatile compounds. The related volatile compounds were mainly on fermented produced compounds including acetic acid, furanmethanol, furfural, octanoic acid and the volatiles known as artificial fruit flavour (beta pinene, limonene, vanillin, and ethyl vanillin). These compounds were provided the information about flavour addition in commercial fermented milk in Thailand.

Keywords: fermented milk, volatile compounds, preference, PCA

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Authors: Aghbalou Nihad, Charki Abderafi, Saida Rahali, Reklaoui Kamal

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Maximize the benefit from the wind energy potential is the most interest of the wind power stakeholders. As a result, the wind tower size is radically increasing. Nevertheless, choosing an appropriate wind turbine for a selected site require an accurate estimate of vertical wind profile. It is also imperative from cost and maintenance strategy point of view. Then, installing tall towers or even more expensive devices such as LIDAR or SODAR raises the costs of a wind power project. Various models were developed coming within this framework. However, they suffer from complexity, generalization and lacks accuracy. In this work, we aim to investigate the ability of neural network trained using the Bayesian Regularization technique to estimate wind speed profile up to height of 100 m based on knowledge of wind speed lower heights. Results show that the proposed approach can achieve satisfactory predictions and proof the suitability of the proposed method for generating wind speed profile and probability distributions based on knowledge of wind speed at lower heights.

Keywords: bayesian regularization, neural network, wind shear, accuracy

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Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

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Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: evolutionary algorithms, chemical reaction optimization, traveling salesman, board drilling

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Authors: Shailendra Kumar Patidar

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Eutrophication of surface water is one of the most widespread environmental problems at present. Large number of pilgrims and tourists visit sacred artificial tank known as “Brahma Sarover” located at Kurukshetra, India to take holy dip and perform religious ceremonies. The sources of pollutants include impurities in feed water, mass bathing, religious offerings and windblown particulate matter. Studies so far have focused mainly on assessing water quality for bathing purpose by using physico-chemical and bacteriological parameters. No effort has been made to assess nutrient concentration and trophic status of the tank to take more appropriate measures for improving water quality on long term basis. In the present study, total nitrogen, total phosphorous and chlorophyll a measurements have been done to assess the nutrient level and trophic status of the tank. The results show presence of high concentration of nutrients and Chlorophyll a indicating mesotrophic and eutrophic state of the tank. Phosphorous has been observed as limiting nutrient in the tank water.

Keywords: Brahma Sarover, eutrophication, nutrients, trophic status

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Authors: Chuanbo Xu, Xinying Li, Gejirifu De, Yunna Wu

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Energy Internet (EI) is a new form that deeply integrates the Internet and the entire energy process from production to consumption. The assessment of energy efficient performance is of vital importance for the long-term sustainable development of EI project. Although the newly proposed fuzzy integrated cloud evaluation algorithm considers the randomness of uncertainty, it relies too much on the experience and knowledge of experts. Fortunately, the enrichment of EI data has enabled the utilization of data-driven methods. Therefore, the main purpose of this work is to assess the energy efficient of park-level EI by using a combination of a data-driven method with the fuzzy integrated cloud evaluation algorithm. Firstly, the indicators for the energy efficient are identified through literature review. Secondly, the artificial neural network (ANN)-based data-driven method is employed to cluster the values of indicators. Thirdly, the energy efficient of EI project is calculated through the fuzzy integrated cloud evaluation algorithm. Finally, the applicability of the proposed method is demonstrated by a case study.

Keywords: energy efficient, energy internet, data-driven, fuzzy integrated evaluation, cloud model

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Authors: Mahyar Mehrafarin, Reza Mehrafarin

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The Sistan region in eastern Iran is a significant archaeological area in Iran and the Middle East, encompassing 10,000 square kilometers. Previous archeological field surveys have identified 1662 ancient sites dating from prehistoric periods to the Islamic period. Research Aim: This article aims to explore the utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, and the benefits derived from their implementation. Methodology: The research employs a descriptive-analytical approach combined with field methods. New technologies and software, such as GPS, drones, magnetometers, equipped cameras, satellite images, and software programs like GIS, Map source, and Excel, were utilized to collect information and analyze data. Findings: The use of modern technologies and computers in archaeological field surveys proved to be essential. Traditional archaeological activities, such as excavation and field surveys, are time-consuming and costly. Employing modern technologies helps in preserving ancient sites, accurately recording archaeological data, reducing errors and mistakes, and facilitating correct and accurate analysis. Creating a comprehensive and accessible database, generating statistics, and producing graphic designs and diagrams are additional advantages derived from the use of efficient technologies in archaeology. Theoretical Importance: The integration of computers and modern technologies in archaeology contributes to interdisciplinary collaborations and facilitates the involvement of specialists from various fields, such as geography, history, art history, anthropology, laboratory sciences, and computer engineering. The utilization of computers in archaeology spanned across diverse areas, including database creation, statistical analysis, graphics implementation, laboratory and engineering applications, and even artificial intelligence, which remains an unexplored area in Iranian archaeology. Data Collection and Analysis Procedures: Information was collected using modern technologies and software, capturing geographic coordinates, aerial images, archeogeophysical data, and satellite images. This data was then inputted into various software programs for analysis, including GIS, Map source, and Excel. The research employed both descriptive and analytical methods to present findings effectively. Question Addressed: The primary question addressed in this research is how the use of modern technologies and computers in archeological field surveys in Sistan, Iran, can enhance archaeological data collection, preservation, analysis, and accessibility. Conclusion: The utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, has proven to be necessary and beneficial. These technologies aid in preserving ancient sites, accurately recording archaeological data, reducing errors, and facilitating comprehensive analysis. The creation of accessible databases, statistics generation, graphic designs, and interdisciplinary collaborations are further advantages observed. It is recommended to explore the potential of artificial intelligence in Iranian archaeology as an unexplored area. The research has implications for cultural heritage organizations, archaeology students, and universities involved in archaeological field surveys in Sistan and Baluchistan province. Additionally, it contributes to enhancing the understanding and preservation of Iran's archaeological heritage.

Keywords: archaeological surveys, computer use, iran, modern technologies, sistan

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Authors: Pei Luen Jiang

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Oysters (Ostreidae) and hard clams (Meretrix lusoria) are important shallow sea-cultured shellfish in Taiwan, and are mainly farmed in Changhua, Yunlin, Chiayi and Tainan. As these shellfish are fed primarily on natural plankton, the artificial feed is not required, leading to high economic value in aquatic farming. However, in recent years, though mariculture production areas have expanded steadily, large-scale deaths of farmed shellfish have also become increasingly common due to climate change and human factors. Through studies over the past few years, our research team has determined the impact of nitrogen deprivation on growth and morphological variations in algae and sea anemones (Actiniaria) and identified the target genes affected by adverse environmental factors. In mariculture, high-density farming is commonly adopted, which results in elevated concentrations of nitrogenous waste in the water. In addition, excessive carbon dioxide from the atmosphere also dissolves in seawater, causing a steady decrease in the pH of seawater, leading to acidification. This study to observe the impact of high concentrations of nitrogen sources and carbon dioxide on algae.

Keywords: algae, shellfish, nitrogen, acidification

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Authors: Muhammad Adamu Kwankwaso

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Early childhood is a critical period of rapid physical, cognitive and psycho-social development of a child. The quality of care and Education which a child receives at this crucial age will determine to a great extent the level of his/her physical and cognitive development in the future. In Nigeria, Early Childhood Care and Education (ECCE) is a fundamental aspect or form of Education for children between the age of 3-6. It was started after independence as pre-primary Education or early child development as contained in the 1977 National Policy on Education. The trends towards ECCE in Nigeria and the northwestern part of the country in particular keep up changing as in the case of other part of the world. The current trends are now towards expansions, inclusiveness, redefinition, early literacy, increased government participation and the unprecedented societal response and awareness towards the Education of the younger children. While all hands are on deck to ensure successful implementation of the ECCE programme, it is unfortunate that, ECCE is facing some challenges. This paper therefore, examines the trends in Early Childhood Care and Education and the major challenges in the north west of Nigeria. Some of the major challenges include, inadequate trained ECCE teachers, lack of unified curriculum, teacher pupil’s ratio, and the medium of instructions and inadequate infrastructural and teaching facilities respectively. To improve the situation the paper offered the following recommendations; establishment of more ECCE classes, enforcement for the use of mothers’ tongue or the languages of the immediate community as a medium of instructions, and adequate provision of infrastructural facilities and the unified curriculum across the northwestern States of Nigeria.

Keywords: early childhood care, education, trends, challenges

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Authors: Meruert Serik, Nassipzhan Duisegaliyeva, Danara Tleumagambetova

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The article highlights and describes the characteristic features of real-time face detection in images and videos using machine learning algorithms. Students of educational programs reviewed the research work "6B01511-Computer Science", "7M01511-Computer Science", "7M01525- STEM Education," and "8D01511-Computer Science" of Eurasian National University named after L.N. Gumilyov. As a result, the advantages and disadvantages of Haar Cascade (Haar Cascade OpenCV), HoG SVM (Histogram of Oriented Gradients, Support Vector Machine), and MMOD CNN Dlib (Max-Margin Object Detection, convolutional neural network) detectors used for face detection were determined. Dlib is a general-purpose cross-platform software library written in the programming language C++. It includes detectors used for determining face detection. The Cascade OpenCV algorithm is efficient for fast face detection. The considered work forms the basis for the development of machine learning methods by future computer science teachers.

Keywords: algorithm, artificial intelligence, education, machine learning

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Authors: Javier Barrachina, Piedad Garrido, Manuel Fogue, Julio A. Sanguesa, Francisco J. Martinez

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It is very common to observe, especially in Computer Science studies that students have difficulties to correctly understand how some mechanisms based on Artificial Intelligence work. In addition, the scope and limitations of most of these mechanisms are usually presented by professors only in a theoretical way, which does not help students to understand them adequately. In this work, we focus on the problems found when teaching Evolutionary Algorithms (EAs), which imitate the principles of natural evolution, as a method to solve parameter optimization problems. Although this kind of algorithms can be very powerful to solve relatively complex problems, students often have difficulties to understand how they work, and how to apply them to solve problems in real cases. In this paper, we present two interactive graphical applications which have been specially designed with the aim of making Evolutionary Algorithms easy to be understood by students. Specifically, we present: (i) TSPS, an application able to solve the ”Traveling Salesman Problem”, and (ii) FotEvol, an application able to reconstruct a given image by using Evolution Strategies. The main objective is that students learn how these techniques can be implemented, and the great possibilities they offer.

Keywords: education, evolutionary algorithms, evolution strategies, interactive learning applications

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Authors: Ruijuan Bi

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Discrimination in insurance pricing is a topic of increasing concern, particularly in the context of the rapid development of big data and artificial intelligence. There is a need to explore the various forms of discrimination, such as direct and indirect discrimination, proxy discrimination, algorithmic discrimination, and unfair discrimination, and understand their implications in insurance pricing models. This paper aims to analyze and interpret the definitions of discrimination in insurance pricing and explore measures to reduce discrimination. It utilizes a textual analysis methodology, which involves gathering qualitative data from relevant literature on definitions of discrimination. The research methodology focuses on exploring the various forms of discrimination and their implications in insurance pricing models. Through textual analysis, this paper identifies the specific characteristics and implications of each form of discrimination in the general insurance industry. This research contributes to the theoretical understanding of discrimination in insurance pricing. By analyzing and interpreting relevant literature, this paper provides insights into the definitions of discrimination and the laws and regulations surrounding it. This theoretical foundation can inform future empirical research on discrimination in insurance pricing using relevant theories of probability theory.

Keywords: algorithmic discrimination, direct and indirect discrimination, proxy discrimination, unfair discrimination, insurance pricing

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Authors: L. Rakesh, T. Y. Heblekar

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This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

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Authors: Alice Morenike Olagunju, Olufemi A. Fakolade, Abiodun Ezekiel Adesina, Olufemi Akinloye Bolaji, Oriyomi Rabiu

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The use of computer-assisted instruction(CAI) has been suggested as a way out of the problem of Colleges of Education (CoE) in Southwest, Nigeria persistent high failure rate in and negative attitude towards Agricultural Economics (AE).The impacts of this are yet unascertained on high-flyers. This study, therefore, determined the impacts of CAI onhigh-flyers pre-service teachers’ attitude towards AE concepts in Southwest, Nigeria. The study adopted pretest-posttest, control group, quasi-experimental design. Six CoE with e-library facilities were purposively selected. Fourty-nine 200 level Agricultural education students offering introduction to AE course across the six CoE were participants. The participants were assigned to two groups (CAI, 22 and control, 27). Treatment lasted eight weeks. The AE Attitude Scale(r=0.80), Instructional guides and Teacher Performance Assessment Sheets were used for data collection. Data were analysed using t-test. The participants were 62.8% male with mean age of 22 years. Treatment had significant effects on high-flyers pre-service teachers’ attitude (t = 17.44; df = 47, p < .5). Participants in CAI ( =71.03) had higher post attitude mean score compared to those in control ( = 64.92) groups. Gender had no significant effect on attitude (t= 3.06; df= 47, p > .5). The computer assisted instructional mode enhanced students’ attitude towards Agricultural Economics concepts. Therefore, CAI should be adopted for improved attitude towards agricultural economics concepts among high-flyers pre-service teachers.

Keywords: attitude towards agricultural economics concepts, colleges of education in southwest Nigeria, computer-assisted instruction, high-flyers pre-service teachers

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Authors: Igwenagu Chinelo Mercy

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This study is on the concept of Neurostatistics in relation to neuroscience. Neuroscience also known as neurobiology is the scientific study of the nervous system. In the study of neuroscience, it has been noted that brain function and its relations to the process of acquiring knowledge and behaviour can be better explained by the use of various interrelated methods. The scope of neuroscience has broadened over time to include different approaches used to study the nervous system at different scales. On the other hand, Neurostatistics based on this study is viewed as a statistical concept that uses similar techniques of neuron mechanisms to solve some problems especially in the field of life science. This study is imperative in this era of Artificial intelligence/Machine leaning in the sense that clear understanding of the technique and its proper application could assist in solving some medical disorder that are mainly associated with the nervous system. This will also help in layman’s understanding of the technique of the nervous system in order to overcome some of the health challenges associated with it. For this concept to be well understood, an illustrative example using a brain associated disorder was used for demonstration. Structural equation modelling was adopted in the analysis. The results clearly show the link between the techniques of statistical model and nervous system. Hence, based on this study, the appropriateness of Neurostatistics application in relation to neuroscience could be based on the understanding of the behavioural pattern of both concepts.

Keywords: brain, neurons, neuroscience, neurostatistics, structural equation modeling

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Authors: Miron Wolnicki

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In the past 75 years the world was either influenced by, competing with or learning from U.S. corporations. This is no longer true. As the economic power shifts from the West to the East, U.S. corporations are lagging behind Asian competitors. Moreover, U.S. statecraft fails to address this decline. In a world dominated by interventionist and neo-mercantilist states, having an ineffective non-activist government becomes a costly neoclassic delusion which weakens the world’s largest economy. American conservative economists continue talking about the superiority of the free market system in generating new technologies. The reality is different. The U.S. is sliding further into an overregulated, over-taxed, anti-business state. This paper argues that in order to maintain its economic strength and technological leadership, the U.S. must reform federal institutions to increase support for artificial intelligence and other cutting-edge technologies. The author outlines a number of institutional reforms, under one umbrella, which he calls the American Entrepreneurial State (AES). The AES will improve productivity and bring about coherent business strategies for the next 10-15 years. The design and inspiration for the AES come from the experience of successful statecraft examples in Asia and also other parts the global economy.

Keywords: post-neoliberal system, entrepreneurial state, government and economy, American entrepreneurial state

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Authors: Cimen Ozburak

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Pollution and the consumption of natural resources are significant global concerns. These problems have to be resolved in order to create a cleaner environment for the world. It is believed that sustainable building designs may reduce environmental problems throughout the world. It is known that if children receive environmental education in early childhood, they will be more likely to construct sustainable living systems and environment when they are older. School buildings can be used as educational material for teaching the natural and artificial environment in environmental education. In this study, the effect of school buildings on environmental education is examined by using the literature review method along with various examples. The selected examples in the study were analyzed according to 4 main criteria of LEED green building certification systems. These are the use of sustainable utilization of land, efficient utilization of water, efficient utilization of energy and efficient utilization of materials. According to the literature review, children who are educated in buildings designed according to these criteria, they will be environmentally sensitive individuals when they are older.

Keywords: clean future, educational sustainable pre-schools, environmental education, sustainable systems

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Authors: Joseph Abiodun Ayo

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The main purpose of this study was to investigate the science laboratory management practices employed in some colleges of education in Kano State, Nigeria. Four specific objectives were stated to guide the study, four research questions were investigated, four null hypothesis were tested at 0.05 level of significance. A survey design was used and science laboratory management questionnaires which solicit responses that was used in answering the research questions and testing of hypotheses. These questionnaires were distributed to the respective respondents in the sampled colleges. The respondents for the study comprised biology chemistry, physics, integrated science teacher trainers and the paraprofessionals. Data were analyzed using mean and standard deviation to answer the questions. Chi-square statistical technique was used to test the hypothesis. The findings of the study revealed that all procedures on control of laboratory activities were rarely observed. Safety procedures were occasionally practiced. On provision and procurement of laboratory equipment and materials it was observed that both academic and the paraprofessional were not fully involved. While maintenance measures were occasionally observed, furthermore science laboratory management procedures are not frequently practiced. Hence making the acquisition of science process skills by students becoming difficult. To arrest these anomalies, it is recommended that direct labor in the maintenance of laboratory equipment and other apparatus by paraprofessional is crucial. Training of academic and paraprofessional through workshops to acquire technical skills in maintenance of science laboratory equipment be instituted to increase professionalism. Periodic supervision of activities in the science laboratories should be done promptly.

Keywords: laboratory, management, standard, facility

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Authors: Syed Zameer, Mohamed Haneef

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Hip joint plays very important role in human beings as it takes up the whole body forces generated due to various activities. These loads are repetitive and fluctuating depending on the activities such as standing, sitting, jogging, stair casing, climbing, etc. which may lead to failure of Hip joint. Hip joint modification and replacement are common in old aged persons as well as younger persons. In this research study static and Fatigue analysis of Hip joint model was carried out using finite element software ANSYS. Stress distribution obtained from result of static analysis, material properties and S-N curve data of fabricated Ultra High molecular weight polyethylene / 50 wt% short E glass fibres + 40 wt% TiO2 Polymer matrix composites specimens were used to estimate fatigue life of Hip joint using stiffness Degradation model for polymer matrix composites. The stress distribution obtained from static analysis was found to be within the acceptable range.The factor of safety calculated from linear Palmgren linear damage rule is less than one, which indicates the component is safe under the design.

Keywords: hip joint, polymer matrix composite, static analysis, fatigue analysis, stress life approach

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Authors: Chan Ka Lok Sobel

Abstract:

The rapid evolution of digital media platforms has given rise to new forms of narrative engagement, particularly through multi-channel storytelling. This research focuses on exploring the teaching pedagogy and effectiveness of multi-channel storytelling for social media, cinema, games, and streaming platforms. The study employs case studies of the popular series "Squid Game" to investigate the diverse pedagogical approaches and strategies used in teaching multi-channel storytelling. Through qualitative research methods, including interviews, surveys, and content analysis, the research assesses the effectiveness of these approaches in terms of student engagement, knowledge acquisition, critical thinking skills, and the development of digital literacy. The findings contribute to understanding best practices for incorporating multi-channel storytelling into educational contexts and enhancing learning outcomes in the digital media landscape.

Keywords: digital literacy, game-based learning, artificial intelligence, animation production, educational technology

Procedia PDF Downloads 66

Authors: Sangeeta Palekar, Neeraj Rangwani, Akash Poddar, Jayu Kalambe

Abstract:

The bio-medical analysis is an indispensable procedure for identifying health-related diseases like diabetes. Monitoring the glucose level in our body regularly helps us identify hyperglycemia and hypoglycemia, which can cause severe medical problems like nerve damage or kidney diseases. This paper presents a method for predicting the glucose concentration in blood samples using image processing and machine learning algorithms. The glucose solution is prepared by the glucose oxidase (GOD) and peroxidase (POD) method. An experimental database is generated based on the colorimetric technique. The image of the glucose solution is captured by the raspberry pi camera and analyzed using image processing by extracting the RGB, HSV, LUX color space values. Regression algorithms like multiple linear regression, decision tree, RandomForest, and XGBoost were used to predict the unknown glucose concentration. The multiple linear regression algorithm predicts the results with 97% accuracy. The image processing and machine learning-based approach reduce the hardware complexities of existing platforms.

Keywords: artificial intelligence glucose detection, glucose oxidase, peroxidase, image processing, machine learning

Procedia PDF Downloads 171

Authors: A. M. Benomair, M. O. Tokhi

Abstract:

This paper presents the investigation on a system model for the stabilization of a Magnetic Levitation System (Maglev’s). The magnetic levitation system is a challenging nonlinear mechatronic system in which an electromagnetic force is required to suspend an object (metal sphere) in air space. The electromagnetic force is very sensitive to the noise which can create acceleration forces on the metal sphere, causing the sphere to move into the unbalanced region. Maglev’s give the contribution in industry and this system has reduce the power consumption, has increase the power efficiency and reduce the cost maintenance. The common applications for Maglev’s Power Generation (e.g. wind turbine), Maglev’s trains and Medical Device (e.g. Magnetically suspended Artificial Heart Pump). This paper presents the comparison between dynamic response and robust characteristic for both conventional PD and Fuzzy PD controller. The main contribution of this paper is the proof of fuzzy PD type stabilization and robustness. By use of a method to tune the scaling factors of the linear PD type fuzzy controller from an equivalent tuned conventional PD.

Keywords: magnetic levitation system, PD controller, Fuzzy Logic Control, Fuzzy PD

Procedia PDF Downloads 254

Authors: C. P. Providakis, G. M. Angeli, M. J. Favvata, N. A. Papadopoulos, C. E. Chalioris, C. G. Karayannis

Abstract:

An effort for the detection of damages in the reinforcement bars of reinforced concrete members using PZTs is presented. The damage can be the result of excessive elongation of the steel bar due to steel yielding or due to local steel corrosion. In both cases the damage is simulated by considering reduced diameter of the rebar along the damaged part of its length. An integration approach based on both electromechanical admittance methodology and guided wave propagation technique is used to evaluate the artificial damage on the examined longitudinal steel bar. Two actuator PZTs and a sensor PZT are considered to be bonded on the examined steel bar. The admittance of the Sensor PZT is calculated using COMSOL 3.4a. Fast Furrier Transformation for a better evaluation of the results is employed. An effort for the quantification of the damage detection using the root mean square deviation (RMSD) between the healthy condition and damage state of the sensor PZT is attempted. The numerical value of the RSMD yields a level for the difference between the healthy and the damaged admittance computation indicating this way the presence of damage in the structure. Experimental measurements are also presented.

Keywords: concrete reinforcement, damage detection, electromechanical admittance, experimental measurements, finite element method, guided waves, PZT

Procedia PDF Downloads 232