Search results for: online learning activities

Authors: F. A. Thomas, M. Schrafl-Altermatt, R. Treier, S. Kaufmann

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Stroke is the main cause of adult disability. Especially upper limb function is affected in most patients. Recently, cooperative hand movements have been shown to be a promising type of upper limb training in stroke rehabilitation. In these movements, which are frequently found in activities of daily living (e.g. opening a bottle, winding up a blind), the force of one upper limb has to be equally counteracted by the other limb to successfully accomplish a task. The use of standardized and reliable clinical assessments is essential to evaluate the efficacy of therapy and the functional outcome of a patient. Many assessments for upper limb function or impairment are available. However, the evaluation of cooperative hand movement tasks are rarely included in those. Thus, the aim of this study was (i) to develop a novel clinical assessment (CASA - Cooperative Activity Stroke Assessment) for the evaluation of patients’ capacity to perform cooperative hand movements and (ii) to test its inter- and interrater reliability. Furthermore, CASA scores were compared to current gold standard assessments for upper extremity in stroke patients (i.e. Fugl-Meyer Assessment, Box & Blocks Test). The CASA consists of five cooperative activities of daily living including (1) opening a jar, (2) opening a bottle, (3) open and closing of a zip, (4) unscrew a nut and (5) opening a clipbox. Here, the goal is to accomplish the tasks as fast as possible. In addition to the quantitative rating (i.e. time) which is converted to a 7-point scale, also the quality of the movement is rated in a 4-point scale. To test the reliability of CASA, fifteen stroke subjects were tested within a week twice by the same two raters. Intra-and interrater reliability was calculated using the intraclass correlation coefficient (ICC) for total CASA score and single items. Furthermore, Pearson-correlation was used to compare the CASA scores to the scores of Fugl-Meyer upper limb assessment and the box and blocks test, which were assessed in every patient additionally to the CASA. ICC scores of the total CASA score indicated an excellent- and single items established a good to excellent inter- and interrater reliability. Furthermore, the CASA score was significantly correlated to the Fugl-Meyer and Box & Blocks score. The CASA provides a reliable assessment for cooperative hand movements which are crucial for many activities of daily living. Due to its non-costly setup, easy and fast implementation, we suggest it to be well suitable for clinical application. In conclusion, the CASA is a useful tool in assessing the functional status and therapy related recovery in cooperative hand movement capacity in stroke patients.

Keywords: activitites of daily living, clinical assessment, cooperative hand movements, reliability, stroke

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Authors: Alejandro Paz Parra, Jose Luis Oslinger Gutierrez, Javier Olaya Ochoa

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In the present paper, five electric current based methods to analyze electric faults on the stator of induction motors (IM) are used and compared. The analysis tries to extend the application of the multiple reference frames diagnosis technique. An eccentricity indicator is presented to improve the application of the Park’s Vector Approach technique. Most of the fault indicators are validated and some others revised, agree with the technical literatures and published results. A tri-phase 3hp squirrel cage IM, especially modified to establish different fault levels, is used for validation purposes.

Keywords: motor fault diagnosis, induction motor, MCSA, ESA, Extended Park´s vector approach, multiparameter analysis

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Authors: Isaac Benning

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Using technology to expand the learning space is critical for a productive mathematical discourse. This is a case study of two teachers who developed and enacted GeoGebra-based mathematics lessons following their engagement in a two-year professional development. The didactical and semiotic affordance of GeoGebra in widening the learning space for a productive mathematical discourse was explored. The approach of thematic analysis was used for lesson artefact, lesson observation, and interview data. The results indicated that constructing tools in GeoGebra provided a didactical milieu where students used them to explore mathematical concepts with little or no support from their teacher. The prompt feedback from the GeoGebra motivated students to practice mathematical concepts repeatedly in which they privately rethink their solutions before comparing their answers with that of their colleagues. The constructing tools enhanced self-discovery, team spirit, and dialogue among students. With regards to the semiotic construct, the tools widened the physical and psychological atmosphere of the classroom by providing animations that served as virtual concrete to enhance the recording, manipulation, testing of a mathematical idea, construction, and interpretation of geometric objects. These findings advance the discussion of widening the classroom for a productive mathematical discourse within the context of the mathematics curriculum of Ghana and similar Sub-Saharan African countries.

Keywords: GeoGebra, theory of didactical situation, semiotic mediation, mathematics laboratory, mathematical discussion

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Authors: Shital Patil, Surendra Bhosale

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Cardiac diseases are the leading causes of mortality and morbidity in the world, from recent few decades accounting for a large number of deaths have emerged as the most life-threatening disorder globally. Machine learning and Artificial intelligence have been playing key role in predicting the heart diseases. A relevant set of feature can be very helpful in predicting the disease accurately. In this study, we proposed a comparative analysis of 4 different features selection methods and evaluated their performance with both raw (Unbalanced dataset) and sampled (Balanced) dataset. The publicly available Z-Alizadeh Sani dataset have been used for this study. Four feature selection methods: Data Analysis, minimum Redundancy maximum Relevance (mRMR), Recursive Feature Elimination (RFE), Chi-squared are used in this study. These methods are tested with 8 different classification models to get the best accuracy possible. Using balanced and unbalanced dataset, the study shows promising results in terms of various performance metrics in accurately predicting heart disease. Experimental results obtained by the proposed method with the raw data obtains maximum AUC of 100%, maximum F1 score of 94%, maximum Recall of 98%, maximum Precision of 93%. While with the balanced dataset obtained results are, maximum AUC of 100%, F1-score 95%, maximum Recall of 95%, maximum Precision of 97%.

Keywords: cardio vascular diseases, machine learning, feature selection, SMOTE

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Authors: Jiangbo Hu, Frances Hoyte, Haiquan Huang

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Research identifies that mealtime talk can be a significant learning context that provides children with rich experiences to foster their language and cognitive development. Middle-classed parents create an extended learning discourse for their children through sophisticated vocabulary, narrative and explanation genres at dinner table. However, mealtime opportunities vary with some parents having little interaction with their children and some parents focusing on directive of children’s behaviors. This study investigated five Chinese families’ parent-child interaction during mealtime that was rarely reported in the literature. The five families differ in terms of their living styles. Three families are from professional background where both mothers the fathers work in Australian companies and both of them present at dinner time. The other two families own business. The mothers are housemakers and the fathers are always absent at dinner time due to their busy business life. Employing case study method, the five Chinese families’ parent-child interactions at dinner table were recorded using a video camera. More than 3000 clauses were analyzed with the framework of 'systems of clause complexing' from systemic functional linguistic theory. The finding shows that mothers played a critical role in the interaction with their children by initiating most conversations. The three mothers from professional background tended to use more language in extending and expanding pattern that is beneficial for children’s language development and high level of thinking (e.g., logical thinking). The two house making mothers’ language focused more on the directive of their children’s social manners and dietary behaviors. The fathers though seemed to be less active, contributing to the richness of the conversation through their occasional props such as asking open questions or initiating a new topic. In general, the families from professional background were more advantaged in providing learning opportunities for their children at dinner table than the families running business were. The home experiences of Chinese children is an important topic in research due to the rapidly increasing number of Chinese children in Australia and other English speaking countries. Such research assist educators in the education of Chinese children with more awareness of Chinese children experiences at home that could be very unlike the settings in English schools. This study contributes to the research in this area through the analysis of language in parent-child interaction during mealtime, which is very different from previous research that mainly investigated Chinese families through survey and interview. The finding of different manners in language use between the professional families and business families has implication for the understanding of the variation of Chinese children’s home experiences that is influenced not only by parents’ socioeconomic status but their lifestyles.

Keywords: Chinese children, Chinese parents, mealtime talk, parent-child interaction

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Authors: B. Adcock, H. van Rensburg

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Education is ever-changing to keep up with innovative technological development and the rapid acceleration of globalisation. This chapter introduces the historical development and transformation of teaching in distance education from correspondence to on-line learning in Queensland universities. It furthermore investigates changes to the delivery models of distance education that have impacted on teaching at tertiary level in Queensland, and reflects on the social changes that have taken place during the past 100 years. This includes an analysis of the following five different periods in time: Foundation period (1911-1919) including World War I; 1920-1939 including the Great Depression; 1940-1970s, including World War II and the post war reconstruction; and the current technological era (1980s to present). In Queensland, the concept of distance education was begun by the University of Queensland (UQ) in 1911, when it began offering extension courses. The introduction of modern technology, in the form of electronic delivery, dramatically changed tertiary distance education due to political initiatives. The inclusion of electronic delivery in education signifies change at many levels, including policy, pedagogy, curriculum and governance. Changes in delivery not only affect the way study materials are delivered, but also the way courses are be taught and adjustments made by academics to their teaching methods.

Keywords: distance education, innovative technological development, on line education, tertiary education

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Authors: Carly Cummings, Maria Soledad Peresin

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Alabama has a long history of racial injustice and unsatisfactory educational performance. In the 1870s Jim Crow laws segregated public schools and disproportionally allocated funding and resources to white institutions across the South. Despite the Supreme Court ruling to integrate schools following Brown vs. the Board of Education in 1954, Alabama’s school system continued to exhibit signs of segregation, compounded by “white flight” and the establishment of exclusive private schools, which still exist today. This discriminatory history has had a lasting impact of the state’s education system, reflected in modern school demographics and achievement data. It is well known that Alabama struggles with education performance, especially in science education. On average, minority groups scored the lowest in science proficiency. In Alabama, minority populations are concentrated in a region known as the Black Belt, which was once home to countless slave plantations and was the epicenter of the Civil Rights Movement. Today the Black Belt is characterized by a high density of woodlands and plays a significant role in Alabama’s leading economic industry-forest products. Given the economic importance of forestry and agriculture to the state, environmental science proficiency is essential to its stability; however, it is neglected in areas where it is needed most. To better understand the inequity of science education within Alabama, our study first investigates how geographic location, demographics and school funding relate to science achievement scores using ArcGIS and Pearson’s correlation coefficient. Additionally, our study explores the implementation of a relevant, problem-based, active learning lesson in schools. Relevant learning engages students by connecting material to their personal experiences. Problem-based active learning involves real-world problem-solving through hands-on experiences. Given Alabama’s significant woodland coverage, educational materials on forest products were developed with consideration of its relevance to students, especially those located in the Black Belt. Furthermore, to incorporate problem solving and active learning, the lesson centered around students using forest products to solve environmental challenges, such as water pollution- an increasing challenge within the state due to climate change. Pre and post assessment surveys were provided to teachers to measure the effectiveness of the lesson. In addition to pedagogical practices, community and mentorship programs are known to positively impact educational achievements. To this end, our work examines the results of surveys measuring educational professionals’ attitudes toward a local mentorship group within the Black Belt and its potential to address environmental and science literacy. Additionally, our study presents survey results from participants who attended an educational community event, gauging its effectiveness in increasing environmental and science proficiency. Our results demonstrate positive improvements in environmental awareness and science literacy with relevant pedagogy, mentorship, and community involvement. Implementing these practices can help provide equitable and inclusive learning environments and can better equip students with the skills and knowledge needed to bridge this historic educational gap within Alabama.

Keywords: equitable education, environmental science, environmental education, science education, racial injustice, sustainability, rural education

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Authors: Suja Karkada, Jayanthi Radhakrishnan, Jansi Natarajan, Gerald, Amandu Matua, Sujatha Shanmugasundaram

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Simulation-based learning is an educational strategy designed to simulate actual clinical situations in a safe environment. Globally, simulation is recognized by several landmark studies as an effective teaching-learning method. A systematic review of the literature on simulation revealed simulation as a useful strategy in creating a learning environment which contributes to knowledge, skills, safety, and confidence. However, to the best of the author's knowledge, there are no studies on assessing the anxiety of the students undergoing simulation. Hence the researchers undertook a study with the aim to evaluate the effectiveness of simulation on anxiety and knowledge among novice nursing students. This quasi-experimental study had a total sample of 69 students (35- Intervention group with simulation and 34- Control group with case scenario) consisting of all the students enrolled in the Fundamentals of Nursing Laboratory course during Spring 2016 and Fall 2016 semesters at a college of nursing in Oman. Ethical clearance was obtained from the Institutional Review Board (IRB) of the college of nursing. Informed consent was obtained from every participant. Study received the Dean’s fund for research. The data were collected regarding the demographic information, knowledge and anxiety levels before and after the use of simulation and case scenario for the procedure nasogastric tube feeding in intervention and control group respectively. The intervention was performed by four faculties who were the core team members of the course. Results were analyzed in SPSS using descriptive and inferential statistics. Majority of the students’ in intervention (82.9%) and control (89.9%) groups were equal to or below the age of 20 years, were females (71%), 76.8% of them were from rural areas and 65.2% had a GPA of more than 2.5. The selection of the samples to either the experimental or the control group was from a homogenous population (p > 0.05). There was a significant reduction of anxiety among the students of control group (t (67) = 2.418, p = 0.018) comparing to the experimental group, indicating that simulation creates anxiety among Novice nursing students. However, there was no significant difference in the mean scores of knowledge. In conclusion, the study was useful in that it will help the investigators better understand the implications of using simulation in teaching skills to novice students. Since previous studies with students indicate better knowledge acquisition; this study revealed that simulation can increase anxiety among novice students possibly it is the first time they are introduced to this method of teaching.

Keywords: anxiety, knowledge, novice students, simulation

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Authors: Lawan Ja’afar Tahir

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This research work centered on the problem of free Arms flow around the Nigeria and Chad Border. The whole of the northeastern Nigerian region has been devastated by the crisis of insecurity facilitated by more than a decade of insurgency. One of the major issues of concern to security experts and personnel in the country is how the insurgents are getting access to weapons, which gave them more strength to fight the war for this long period, which has become so difficult to overcome. Among the possible avenues that continue to strengthen the enemies is the easy access to the arms flow from the neighboring countries, especially the Republic of Chad, which borders Nigeria to the east, where Boko Haram gained firm roots. This paper, therefore, looked at the nature of the waterway of the Nigeria/Chad Border, which has become a source of strength to the insurgents as the flow of weapons is one of the cheapest things on the Border. The availability of such arms flow has also led to the People abandoning their lands and economic and commercial activities, especially those settlements between the Border of these two countries. For more than eight years now, they have suspended their livelihood activities, roads were blocked and chances of survival in the rural areas were minimal due to the frequent attacks carried out by the insurgents. However, this research looks at the causes of the arms flow along the Border of these neighboring countries, the extent of damage done as a result of the availability of the weapons, and how far the Nigerian government has gone in curtailing the menace of the flow of dangerous weapons into the country. The research looked at the ways arm dealers are conniving with settlers along the border as well as the various ways they followed to reach their target. The work provided suggestion as to how the fragile Border should be managed with the view to reduce the influx of arms without control, which, according to this research, is the central factor that continues to unleash and give terror groups the opportunity to destroy people for more than a decade.

Keywords: border, insecurity, weapons, management

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Authors: Fatima Muhammad Shitu

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In language learning, Second language learners like their native speaker counter parts, commit errors in their attempt to achieve competence in the target language. The realm of Collocation has to do with meaning relation between lexical items. In all human language, there is a kind of ‘natural order’ in which words are arranged or relate to one another in sentences so much so that when a word occurs in a given context, the related or naturally co -occurring word will automatically come to the mind. It becomes an error, therefore, if students inappropriately pair or arrange such ‘naturally’ co – occurring lexical items in a text. It has been observed that most of the second language learners in this research group commit collocational errors. A study of this kind is very significant as it gives insight into the kinds of errors committed by learners. This will help the language teacher to be able to identify the sources and causes of such errors as well as correct them thereby guiding, helping and leading the learners towards achieving some level of competence in the language. The aim of the study is to understand the nature of these errors as stumbling blocks to effective essay writing. The objective of the study is to identify the errors, analyse their structural compositions so as to determine whether there are similarities between students in this regard and to find out whether there are patterns to these kinds of errors which will enable the researcher to understand their sources and causes. As a descriptive research, the researcher samples some nine hundred essays collected from three hundred undergraduate learners of English as a second language in the Federal College of Education, Kano, North- West Nigeria, i.e. three essays per each student. The essays which were given on three different lecture times were of similar thematic preoccupations (i.e. same topics) and length (i.e. same number of words). The essays were written during the lecture hour at three different lecture occasions. The errors were identified in a systematic manner whereby errors so identified were recorded only once even if they occur severally in students’ essays. The data was collated using percentages in which the identified number of occurrences were converted accordingly in percentages. The findings from the study indicates that there are similarities as well as regular and repeated errors which provided a pattern. Based on the pattern identified, the conclusion is that students’ collocational errors are attributable to poor teaching and learning which resulted in wrong generalisation of rules.

Keywords: collocations, errors, second language learning, ESL students

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Amina Babou

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Gender and language is a moot and miscellaneous arena in the sphere of sociolinguistics, which has been proliferated so widely and rapidly in recent years. The dawn of research on gender and foreign language education was against the feminist researchers who allowed space for the bustling concourse of voices and perspectives in the arena of gender and language differences, in the early to the mid-1970. The objective of this scrutiny is to explore to what extent teaching gender and language in the English as a Foreign Language (EFL) classroom plays a pivotal role in learning language information and skills. And the gist of this paper is to investigate how EFL students in Algeria conflate their gender identities with the linguistic practices and scholastic expertise. To grapple with the full range of issues about the EFL students’ awareness about the negotiation of meanings in the classroom, we opt for observing, interviewing, and questioning later to check using ‘how-do-you do’ procedure. The analysis of the EFL classroom discourse, from five Algerian universities, reveals that speaking strategies such as the manners students make an abrupt topic shifts, respond spontaneously to the teacher, ask more questions, interrupt others to seize control of conversations and monopolize the speaking floor through denying what others have said, do not sit very lightly on 80.4% of female students’ shoulders. The data indicate that female students display the assertive style as a strategy of learning to subvert the norms of femininity, especially in the speaking module.

Keywords: gender identities, EFL students, classroom discourse, linguistics

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Authors: Ozlem Bahadir Acikara, Mert Ilhan, Ekin Kurtul, Karel Smejkal, Esra Kupeli Akkol

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Present study is aimed to investigate in vitro inhibitory effects of the extracts prepared from the aerial parts of Podospermum canum (Asteraceae) on hyaluronidase, collagenase, and elastase enzymes using a bioassay-guided fractionation. Inhibitory effects of the extract, sub-extracts, fractions obtained by column chromatography, and isolated compounds on collagenase, elastase, and hyaluronidase were performed by using in vitro enzyme inhibitory assays based on spectrophotometric evaluation. The ethyl acetate and remaining water extracts prepared from the plant displayed significant inhibitory activities on collagenase and elastase, while petroleum ether and chloroform extracts did not show any inhibitory activity. Eleven known compounds: arbutin, 6'-O-caffeoylarbutin, cichoriin, 3,5-dicaffeoylquinic acid methyl ester, apigenin-7-O-β-glucoside, luteolin-7-O-β-glucoside, apigenin-7-O-β-rutinoside, isoorientin, orientin, vitexin, procatechuic acid, and compound 4-hydroxy-benzoic acid 4-(6-O-α-rhamnopyranosyl-β-glucopyranosyl) benzyl ester have been obtained from ethyl acetate sub-extract of the plant through bioassay-guided fractionation and isolation. Results of the present study have revealed that among the isolated compounds, apigenin-7-O-β-glucoside, luteolin-7-O-β-glucoside, apigenin-7-O-β-rutinoside and isoorientin showed potent enzyme inhibitory activities. However, methanolic extract of P. canum displayed a greater inhibitory activity than fractions and isolated compounds both on collagenase and elastase.

Keywords: Asteraceae, collagenase, elastase, hyaluronidase, Podospermum canum

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Authors: Ahmad E. Aldousaria, Abdulla Al Kafy

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Urbanization is an incessant process that involves the transformation of land use/land cover (LULC), resulting in a reduction of cool land covers and thermal comfort zones (TCZs). This study explores the directional shrinkage of TCZs in Kuwait using Landsat satellite data from 1991 – 2021 to predict the future LULC and TCZ distribution for 2026 and 2031 using cellular automata (CA) and artificial neural network (ANN) algorithms. Analysis revealed a rapid urban expansion (40 %) in SE, NE, and NW directions and TCZ shrinkage in N – NW and SW directions with 25 % of the very uncomfortable area. The predicted result showed an urban area increase from 44 % in 2021 to 47 % and 52 % in 2026 and 2031, respectively, where uncomfortable zones were found to be concentrated around urban areas and bare lands in N – NE and N – NW directions. This study proposes an effective and sustainable framework to control TCZ shrinkage, including zero soil policies, planned landscape design, manmade water bodies, and rooftop gardens. This study will help urban planners and policymakers to make Kuwait an eco–friendly, functional, and sustainable country.

Keywords: land cover change, thermal environment, green cover loss, machine learning, remote sensing

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Authors: Hang Yang, Jiahao Liu, Jichao Li, Kewei Yang, Minghao Li, Bingfeng Ge

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The system-of-systems (SoS) are utilized to characterize networks formed by integrating individual complex systems that demonstrate interdependence and interconnectedness. Research on the disintegration issue in SoS is significant in improving network survivability, maintaining network security, and optimizing SoS architecture. Accordingly, this study proposes an integrated framework called resilience-oriented disintegration in SoS (SoSRD), for modeling and solving the issue of SoS disintegration. Firstly, a SoS disintegration index (SoSDI) is presented to evaluate the disintegration effect of SoS. This index provides a practical description of the disintegration process and is the first integration of the network disintegration model and resilience models. Subsequently, we propose a resilience-oriented disintegration method based on reinforcement learning (RDRL) to enhance the efficiency of SoS disintegration. This method is not restricted by the problem scenario as well as considering the coexistence of disintegration (node/link removal) and recovery (node/link addition) during the process of SoS disintegration. Finally, the effectiveness and superiority of the proposed SoSRD are demonstrated through a case study. We demonstrate that our proposed framework outperforms existing indexes and methods in both node and link disintegration scenarios, providing a fresh perspective on network disintegration. The findings provide crucial insights into dismantling harmful SoS and designing a more resilient SoS.

Keywords: system-of-systems, disintegration index, resilience, reinforcement learning

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Authors: Aliyu Aminu Baba, Mustapha Makama

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Tertiary institutions are citadel of learning and societal orientation. Due to the huge investment of various government to tertiary institutions, these institutions are solely financed by the government alone. As stakeholders of society, corporations have to have to intervene and provide corporate social responsibility. The study intends to investigate the role of Entrepreneurs in incorporating social Responsibility. Tertiary institutions are citadel of learning and societal orientation. Due to the huge investment of various government to tertiary institutions, the study intends to investigate the role of businesses and Entrepreneurs, which could be among the important contributions of businesses and Entrepreneurs on corporate social Responsibility to Tertiary Institutions in Bauchi State. Corporate social responsibility is vital in enhancing the infrastructural development of the tertiary institution as almost all individuals and corporate bodies benefit from this tertiary institutions. The study intends to examine the impact of corporate social responsibility to tertiary institutions and entrepreneurs in Bauchi state Nigeria. Questionnaires would be distributed to tertiary institutions and entrepreneurs in the Bauchi metropolis. The data collected will be analyzed with the help of SPSS version 23. The main objective is to investigate the role of businesses and Entrepreneurs, which could be among the important contributions of businesses and entrepreneurs on corporate social Responsibility to Tertiary Institutions in Bauchi State.

Keywords: corporate social responsibility, tertiary, institutions, profitability

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Authors: Galih Mediana

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Boarding school can helps students to turn all good qualities into habits. The process of forming one's personality can be done in various ways. In addition to gaining general knowledge at school during learning hours, teachers can instill values in students which can be done while in the dormitory when the learning process has ended. This shows the important role that must be played by boarding school’s teachers. Transformational leadership and a culture of innovation are things that can instill innovative behavior in teachers. This study aims to determine the effect of perceptions of transformational leadership and a culture of innovation on innovative work behavior among Islamic boarding school teachers. Respondents in this study amounted to 70 teachers. To measure transformational leadership, a modified measuring tool is used, namely the Multifactor Leadership Questionnaire (MLQ) by Bass (1985). To measure innovative work behavior, a measurement tool based on dimensions from Janssen (2000) is used. The innovation culture in this study will be measured using the innovation culture factor from Dobni (2008). This study uses multiple regression analysis to test the hypothesis. The results of this study indicate that there is an influence of perceptions of transformational leadership and innovation culture factors on innovative work behavior in Islamic boarding school’s teachers by 57.7%.

Keywords: transformational leadership, innovative work behavior, innovation culture, boarding school, teacher

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Authors: Nugzar Todua

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The paper studies the role of food labeling in order to promote healthy eating issue in Georgia. The main focus of the research is directed to consumer attitudes regarding food labeling. The methodology of the paper is based on the focus group work, as well as online and face to face surveys. The data analysis has been provided through ANOVA. The study proves that the impact of variables such as the interest, awareness, reliability, assurance and satisfaction of consumers' on buying decision, is statistically important. The study reveals that consumers’ perception regarding to food labeling is positive, but their level of knowledge and ability is rather low. It is urgent to strengthen marketing promotions strategies in the process of implementations of food security policy in Georgia.

Keywords: food labeling, buying decision, Georgian consumers, marketing research

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Authors: Hanene Sahli, Aymen Mouelhi, Marwa Hajji, Amine Ben Slama, Mounir Sayadi, Farhat Fnaiech, Radhwane Rachdi

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Fetal abnormality is still a public health problem of interest to both mother and baby. Head defect is one of the most high-risk fetal deformities. Fetal head categorization is a sensitive task that needs a massive attention from neurological experts. In this sense, biometrical measurements can be extracted by gynecologist doctors and compared with ground truth charts to identify normal or abnormal growth. The fetal head biometric measurements such as Biparietal Diameter (BPD), Occipito-Frontal Diameter (OFD) and Head Circumference (HC) needs to be monitored, and expert should carry out its manual delineations. This work proposes a new approach to automatically compute BPD, OFD and HC based on morphological characteristics extracted from head shape. Hence, the studied data selected at the same Gestational Age (GA) from the fetal Ultrasound images (US) are classified into two categories: Normal and abnormal. The abnormal subjects include hydrocephalus, microcephaly and dolichocephaly anomalies. By the use of a support vector machines (SVM) method, this study achieved high classification for automated detection of anomalies. The proposed method is promising although it doesn't need expert interventions.

Keywords: biometric measurements, fetal head malformations, machine learning methods, US images

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Authors: Olaniyan Rotimi Francis

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Agbabu Water, Oluwa River is used for artisanal fishing, ferrying and domestic activities in Odigbo Local Government Area (OLGA), Ondo State. The river receives bitumen spills and domestic and agricultural wastes, which could adversely impact on the water quality and resident biota. In spite of anthropogenic activities, there is a dearth of information on the limnology and biota of the river. Extensive bitumen spills, as well as uncontrolled discharge of domestic wastes have pollution implications as they alter prevailing conditions and destroy the habitats of aquatic organisms. The aim of this study was to investigate the physic-chemical parameters of Agbabu Water in order to provide baseline information for effective management. Monthly water samples were collected on the surface of Agbabu water, Oluwa River, for a period of 6 months (June,2024 to November,2024). All physic-chemicals were collected and analyzed according to APHA (2005) standard methods. Results showed that temperature ranged between 26.0-32.0oC, transparency (1.0-8.0 m), alkalinity (14.0-25.0 mg/l), electrical conductivity (18-105 µS/cm), dissolved oxygen (1.2-3.8 mg/l), sulphate (0.0 -4.0mg/l) and total dissolved solids (18-36). The parameters at the downstream (station A) accounted for the bulk of the highest values; there were, however, no significant differences between the stations at P<0.05. The results obtained from the physic-chemical parameters agree with the limits set by both national and international bodies for drinking and fish growth. It was recommended that urgent checks and monitoring by relevant agencies, government representatives, public health practitioners, and community leaders are required.

Keywords: physico-chemical, water, Agbabu, River

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Authors: Parimelazhagan Thangaraj

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Natural products serves human kind as a source of all drugs and higher plants provide most of these therapeutic agents. These products are widely recognized in the pharmaceutical industry for their broad structural diversity as well as their wide range of pharmacological activities. Euphorbiaceae is one of the important families with significant pharmacological activities, of which many species has been used traditionally for the treatment of various ailments. Breynia retusa belongs to the family Euphorbiaceae is used to cure ailments like body pain, skin inflammation, hyperglycaemia, diarrhoea, dysentery and toothache. Flowers and young leaves of B. retusa are cooked and eaten, roots are used for meningitis. The juice of the stem is used in conjunctivtis and leaves as poultice to hasten suppuration. Based on the strong evidences of traditional uses of Breynia retusa, the present study was focused on neutraceuticals evaluation of the species with special reference to oxidative stress and diabetes. Both leaves and stem of B. retusa were extracted with different solvents and analyzed for radical scavenging ability wherein ABTS.+ (8396.95±1529.01 µM TEAC/g extract), phosphomolybdenum (17.34±0.08 g AAE/100 g extract) and FRAP (6075.66±414.28 µM Fe (II) E/mg extract) assays showed good radical scavenging activity in stem. Furthermore, leaf extracts showed good radical inhibition in DPPH (2.4 µg/mL), metal ion (27.44±0.09 mg EDTAE/g extract) scavenging methods. The α-amylase and α-glucosidase inhibitors are currently used for diabetic treatment as oral hypoglycemic agents. The inhibitory effects of the B. retusa leaf and stem ethyl acetate extracts showed good inhibition on α-amylase (96.25% and 95.69 respectively) and α-glucosidase (54.50% and 50.87% respectively) enzymes compared to standard acarbose. The proximate composition analysis of B. retusa leaves contains higher amount of total carbohydrates (14.08 g Glucose equivalents/100 g sample), ash (19.04 %) and crude fibre (0.52 %). The examination of mineral profile explored that the leaves was rich in calcium (1891 ppm), sulphur (1406 ppm), copper (2600 ppm) and magnesium (778 ppm). Leaves sample revealed very minimal amount of anti-nutrient contents like trypsin (14.08±0.03 TIU/mg protein) and tannin (0.011±0.001 mg TAE/g sample). The low anti nutritional factors may not pose any serious nutritional problems when these leaves are consumed. In conclusion, it is very clear that dietary compounds from B. retusa are suitable and promising for the development of safe food products and natural additives. Based on the studies, it may be concluded that nutritional composition, antioxidant and anti-diabetic activities this species can be used as future therapeutic medicine.

Keywords: Breynia retusa, nutraceuticals, antioxidant, anti diabetic

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Authors: Nurul Bin Ibrahim

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Advancements in neural networks have offered valuable insights into Fluid Dynamics, notably in addressing turbulence-related challenges. In this research, we introduce multiple applications of models of neural networks, namely Feed-Forward and Recurrent Neural Networks, to explore the relationship between jet formations and stratified turbulence within stochastically excited Boussinesq systems. Using machine learning tools like TensorFlow and PyTorch, the study has created models that effectively mimic and show the underlying features of the complex patterns of jet formation and stratified turbulence. These models do more than just help us understand these patterns; they also offer a faster way to solve problems in stochastic systems, improving upon traditional numerical techniques to solve stochastic differential equations such as the Euler-Maruyama method. In addition, the research includes a thorough comparison with the Statistical State Dynamics (SSD) approach, which is a well-established method for studying chaotic systems. This comparison helps evaluate how well neural networks can help us understand the complex relationship between jet formations and stratified turbulence. The results of this study underscore the potential of neural networks in computational physics and fluid dynamics, opening up new possibilities for more efficient and accurate simulations in these fields.

Keywords: neural networks, machine learning, computational fluid dynamics, stochastic systems, simulation, stratified turbulence

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Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

Procedia PDF Downloads 198

Authors: Francisco Julio Batle Lorente

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The present paper aims at presenting a new category of role for academia: proactive creator/promoter of communities of practice in emerging areas of innovation. It is based in research among practitioners in three different areas: social entrepreneurship, alumni engaged in entrepreneurship and innovation, and digital nomads. The concept of CoP is related to an intentionally created space to share experiences and collectively reflect on the cases arising from practice. Such an endeavour is not contemplated in the literature on academic roles in an explicit way. The goal of the paper is providing a framework for this function and throw some light on the perception and priorities of members of emerging communities (78 alumni, 154 social entrepreneurs, and 231 digital nomads) regarding community, learning, engagement, and networking, areas in which the university can help and, by doing so, contributing to signal the emerging area and creating new opportunities for the academia. The research methodology was based in Survey research. It is a specific type of field study that involves the collection of data from a sample of elements drawn from a well-defined population through the use of a questionnaire. It was considered that survey research might be valuable to the present project and help outline the utility of various study designs and future projects with the emerging communities that are the object of the investigation. Open questions were used for different topics, as well as critical incident technique. It was used a standard technique for survey sampling and questionnaire design. Finally, it was defined a procedure for pretesting questionnaires and for data collection. The questionnaire was channelled by means of google forms. The results indicate that the members of emerging, innovative CoPs and learning such the ones that were selected for this investigation lack cohesion, inspiration, networking, opportunities for creation of social capital, opportunities for collaboration beyond their existing and close network. The opportunity that arises for the academia from proactively helping articulate CoP (and Communities of learning) are related to key elements of any CoP/ CoL: community construction approaches, technological infrastructure, benefits, participation issues and urgent challenges, trust, networking, technical ability/training/development and collaboration. Beyond training, other three areas (networking, collaboration and urgent challenges) were the ones in which the contribution of universities to the communities were considered more interesting and workable to practitioners. The analysis of the responses for the open questions related to perception of the universities offer options for terra incognita to be explored for universities (signalling new areas, establishing broader collaborations with research, government, media and corporations, attracting investment). Based on the findings from this research, there is some evidence that CoPs can offer a formal and informal method of professional and interprofessional development for member of any emerging and innovative community and can decrease social and professional isolation. The opportunity that it offers to academia can increase the entrepreneurial and engaged university identity. It also moves to academia into a realm of civic confrontation of present and future challenges in a more proactive way.

Keywords: social innovation, new roles of academia, community of learning, community of practice

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Authors: Branden Heng, Harsheni Siddharthan, Allison Tseng, Paul Toprac, Sarah Abraham, Etienne Vouga

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The goal of this project was to evaluate and document the capabilities and limitations of AI tools for empowering small teams to create high-budget, high-profile (AAA) 3D games typically developed by large studios. Two teams of novice game developers attempted to create two different games using AI and Unreal Engine 5.3. First, the teams evaluated 60 AI art, design, sound, and programming tools by considering their capability, ease of use, cost, and license restrictions. Then, the teams used a shortlist of 12 AI tools for game development. During this process, the following tools were found to be the most productive: (i) ChatGPT 4.0 for both game and narrative concepts and documentation; (ii) Dall-E 3 and OpenArt for concept art; (iii) Beatoven for music drafting; (iv) ChatGPT 4.0 and Github Copilot for generating simple code and to complement human-made tutorials as an additional learning resource. While current generative AI may appear impressive at first glance, the assets they produce fall short of AAA industry standards. Generative AI tools are helpful when brainstorming ideas such as concept art and basic storylines, but they still cannot replace human input or creativity at this time. Regarding programming, AI can only effectively generate simple code and act as an additional learning resource. Thus, generative AI tools are, at best, tools to enhance developer productivity rather than as a system to replace developers.

Keywords: AAA games, AI, automation tools, game development

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Authors: Duc V. Nguyen

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Induction motors are widely used in different industry areas and can experience various kinds of faults in stators and rotors. In general, fault detection and diagnosis techniques for induction motors can be supervised by measuring quantities such as noise, vibration, and temperature. The installation of mechanical sensors in order to assess the health conditions of a machine is typically only done for expensive or load-critical machines, where the high cost of a continuous monitoring system can be Justified. Nevertheless, induced current monitoring can be implemented inexpensively on machines with arbitrary sizes by using current transformers. In this regard, effective and low-cost fault detection techniques can be implemented, hence reducing the maintenance and downtime costs of motors. This work proposes a method for fault detection and diagnosis of induction motors, which combines classical fast Fourier transform and modern/advanced machine learning techniques. The proposed method is validated on real-world data and achieves a precision of 99.7% for fault detection and 100% for fault classification with minimal expert knowledge requirement. In addition, this approach allows users to be able to optimize/balance risks and maintenance costs to achieve the highest benet based on their requirements. These are the key requirements of a robust prognostics and health management system.

Keywords: fault detection, FFT, induction motor, predictive maintenance

Procedia PDF Downloads 179

Authors: Maria Paula Santos, Ana Lucas

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Organizations support their operations and decision making on the data they have at their disposal, so the quality of these data is remarkably important and Data Quality (DQ) is currently a relevant issue, the literature being unanimous in pointing out that poor DQ can result in large costs for organizations. The literature review identified and described 24 Critical Success Factors (CSF) for Data Quality Management (DQM) that were presented to a panel of experts, who ordered them according to their degree of importance, using the Delphi method with the Q-sort technique, based on an online questionnaire. The study shows that the five most important CSF for DQM are: definition of appropriate policies and standards, control of inputs, definition of a strategic plan for DQ, organizational culture focused on quality of the data and obtaining top management commitment and support.

Keywords: critical success factors, data quality, data quality management, Delphi, Q-Sort

Procedia PDF Downloads 222

Authors: Ming Fang Hsieh

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The purpose of this study was to investigate the reading responses of infants and toddlers across different contexts in nursery centers. The study adopted Sipe’s framework for children’s literacy education to explore the reading behavior of infants and toddlers. The study was conducted at two nurseries. The sample comprised 46 infants and toddlers and 6 caregivers. The methods of data collection included observation of various reading activities, including shared reading in a group, one-on-one reading, and unstructured reading activities, as well as interviews with caregivers. The data obtained through observations and interviews were transcribed and analyzed. The caregivers and the children’s parents signed an informed consent form before the start of the study. There was no risk anticipated during the course of the study. The analysis revealed five types of reading responses exhibited by the infants and toddlers: (1) linguistic- verbally responding to reading, repeating vocabulary, and answering questions; (2) affective- concentrating on reading or requesting for repeated reading, leaning on books, and gazing at caregivers; (3) explosive- children under 18 months were observed manipulating books through their bodies or different movements like flipping, rotating, or tapping on books; (4) social- during unstructured reading context, children were seen interacting with peers or following the rules of reading, sitting properly, and choosing one book at a time; and (5) distracted responses- paying attention to something else instead of reading, walking around, and playing, which was usually observed during shared reading in a group. The study concluded that children’s distraction and explosive reading behaviors may be a part of the process of their emergent reading behavior. As children develop, they demonstrate an increase in verbal responses, improved concentration, and better behavior. The study suggests that adults should continue to provide appropriate reading opportunities beginning from infancy to nurture children’s reading behaviors.

Keywords: reading response, infants and toddlers, early reading, picture books

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Authors: Roberto Cabezas H

Abstract:

The current work shows the methodology developed to create narrative lighting spaces for the multimedia performance piece 'cluster: the vanished paradise.' This empirical research is focused on exploring unconventional roles for machines in subjective creative processes, by delving into the semantics of data and machine intelligence algorithms in hybrid technological, creative contexts to expand epistemic domains trough human-machine cooperation. The creative process in scenic and performing arts is guided mostly by intuition; from that idea, we developed an approach to embed collective intuition in computational creative systems, by joining the properties of Generative Adversarial Networks (GAN’s) and Fuzzy Clustering based on a semi-supervised data creation and analysis pipeline. The model makes use of GAN’s to learn from phenomenological data (data generated from experience with lighting scenography) and algorithmic design data (augmented data by procedural design methods), fuzzy logic clustering is then applied to artificially created data from GAN’s to define narrative transitions built on membership index; this process allowed for the creation of simple and complex spaces with expressive capabilities based on position and light intensity as the parameters to guide the narrative. Hybridization comes not only from the human-machine symbiosis but also on the integration of different techniques for the implementation of the aided design system. Machine intelligence tools as proposed in this work are well suited to redefine collaborative creation by learning to express and expand a conglomerate of ideas and a wide range of opinions for the creation of sensory experiences. We found in GAN’s and Fuzzy Logic an ideal tool to develop new computational models based on interaction, learning, emotion and imagination to expand the traditional algorithmic model of computation.

Keywords: fuzzy clustering, generative adversarial networks, human-machine cooperation, hybrid collective data, multimedia performance

Procedia PDF Downloads 145

Authors: Maria Torres

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After the acknowledgment of contrastive analysis, Pit Coder’s establishment of error analysis revolutionized the way instructors analyze and examine students’ writing errors. One question that relates to error analysis with speakers of a first language, in this case, Spanish, who are learning a second language (English), is the type of errors that these learners make along with the causes of these errors. Many studies have looked at the way the native tongue influences second language acquisition, but this method does not take into account other possible sources of students’ errors. This paper examines writing samples from an advanced ESL class whose first language is Spanish at non-profit organization, Learning Quest Stanislaus Literacy Center. Through error analysis, errors in the students’ writing were identified, described, and classified. The purpose of this paper was to discover the type and origin of their errors which generated appropriate treatments. The results in this paper show that the most frequent errors in the advanced ESL students’ writing pertain to interlanguage and a small percentage from an intralanguage source. Lastly, the least type of errors were ones that originate from negative transfer. The results further solidify the idea that there are other errors and sources of errors to account for rather than solely focusing on the difference between the students’ mother and target language. This presentation will bring to light some strategies and techniques that address the issues found in this research. Taking into account the amount of error pertaining to interlanguage, an ESL teacher should provide metalinguistic awareness of the students’ errors.

Keywords: error analysis, ESL, interlanguage, intralangauge

Procedia PDF Downloads 299