Search results for: teaching report writing for innovative learning

Authors: Minna Theres James, Nirmal K Sebastian, Shoubhik Mandal, Pramita Mishra, R Ganesan, P S Anil Kumar

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We report the temperature-dependent evolution of Raman spectra of type-II Dirac semimetal (DSM) NiTe2 (001) in the form of bulk single crystal and a nanoflake (200 nm thick) for the first time. A physical model that can quantitatively explain the evolution of out of plane A1g and in-plane E1g Raman modes is used. The non-linear variation of peak positions of the Raman modes with temperature is explained by anharmonic three-phonon and four-phonon processes along with thermal expansion of the lattice. We also observe prominent effect of electron-phonon coupling from the variation of FWHM of the peaks with temperature, indicating the metallicity of the samples. Raman mode E1 1g corresponding to an in plane vibration disappears on decreasing the thickness from bulk to nanoflake.

Keywords: raman spectroscopy, type 2 dirac semimetal, nickel telluride, phonon-phonon coupling, electron phonon coupling, transition metal dichalcogonide

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Collins Ekpiwre Augustine

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Taking into account the impact of teacher training on primary and secondary teachers’ classroom competencies and practices, as revealed by many empirical studies, this study investigated the impact of teacher qualifications on the pedagogical competencies of university teachers in Northwest Nigeria.Four research questions were answered while four hypotheses were tested. Both descriptive statistic of frequencies/arithmetic mean and inferential statistic oft-test were used to analyze the data collected. In order to provide a focus to the study,an observational rating scale titled “University Teachers’ Pedagogical Competency Observation Rating Scale” (UTPCORS) was used to collect data for the study. The population for the study comprised all the university teachers in the three Federal Universities in Northwest Nigeria totaling about 3,401. However, this pilot study was administered on 8 teachers - with 4 participants in each comparison group in Bayero University, Kano.The findings of the study revealed that there was no significant difference in the four hypotheses postulated for the study.

Keywords: impact, university teachers, teachers' qualifications, competencies

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Authors: Amy Claridge, Tishra Beeson

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Background: Maternal depression is a serious health concern impacting between 10-16% of birthing persons. It is associated with difficulty in emotional interaction and the formation of attachment bonds between parent and infant. Longitudinally, maternal depression can have severe, lasting impacts on both parent and child, increasing the risk for mental, social, and physical health issues. Rates of prenatal depression have been higher among individuals who were pregnant during the first year of the COVID-19 pandemic. Pregnant persons are considered a high-risk group for poor clinical outcomes from COVID-19 infection and may also have faced or continue to face additional stressors such as financial burdens, loss of income or employment, and the benefits accompanying employment, especially among those in the United States (U.S.). It is less clear whether individuals who gave birth during the pandemic continue to experience high levels of depressive symptoms or whether symptoms have been reduced as a pandemic response has shifted. The current study examined longitudinal reports of depressive symptoms among individuals in the U.S. who gave birth between March 2020 and September 2021. Methods: This mixed-method study involved surveys and interviews with birthing persons (18-45 years old) in their third trimester of pregnancy and at 8 weeks postpartum. Participants also completed a follow-up survey at 12-18 months postpartum. Participants were recruited using convenience methods via an online survey. Survey participants included 242 U.S. women who self-reported depressive symptoms (10-item Edinburgh Postnatal Depression Scale) at each data collection wave. A subset of 23 women participated in semi-structured prenatal and 8-week postpartum qualitative interviews. Follow-up interviews are currently underway and will be integrated into the presentation. Preliminary Results: Prenatal depressive symptoms were significantly positively correlated to 8-week and 12-18-month postpartum depressive symptoms. Participants who reported clinical levels of depression prenatally were 3.29 times (SE = .32, p < .001) more likely to report clinical levels of depression at 18 months postpartum. Those who reported clinical depression at 8-weeks postpartum were 6.52 times (SE = .41, p < .001) more likely to report clinical levels of depression at 18 months postpartum. Participants who gave birth earlier in the pandemic reported significantly higher prenatal (t(103) = 2.84, p < .01) and 8-week postpartum depressive symptoms (t(126) = 3.31, p < .001). Data from qualitative interviews contextualize the findings. Participants reported negative emotions during pregnancy, including sadness, grief, and anxiety. They attributed this in part to their experiences of pregnancy during the pandemic and uncertainty related to the birth experience and postpartum period. Postpartum interviews revealed some stressors specific to childbirth during the COVID-19 pandemic; however, most women reflected on positive experiences of birth and postpartum. Conclusions: Taken together, findings reveal a pattern of persistent depressive symptoms among U.S. parents who gave birth during the pandemic. Depressive symptoms are of significant concern for the health of parents and children, and the findings of this study suggest a need for continued mental health intervention for parents who gave birth during the pandemic. Policy and practice implications will be discussed.

Keywords: maternal mental health, perinatal depression, postpartum depression, covid-19 pandemic

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Authors: Md. Anayet U. Patwari, Mohammad Ahsan Habib, Md. Tanzib Ehsan, Md Golam Ahnaf, Md. S. I. Chowdhury

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Surface roughness is one of the key quality parameters of the finished product. During any machining operation, high temperatures are generated at the tool-chip interface impairing surface quality and dimensional accuracy of products. Cutting fluids are generally applied during machining to reduce temperature at the tool-chip interface. However, usages of cutting fluids give rise to problems such as waste disposal, pollution, high cost, and human health hazard. Researchers, now-a-days, are opting towards dry machining and other cooling techniques to minimize use of coolants during machining while keeping surface roughness of products within desirable limits. In this paper, a concept of using peltier cooling effects during aluminium milling operation has been presented and adopted with an aim to improve surface roughness of the machined surface. Experimental evidence shows that peltier cooling effect provides better surface roughness of the machined surface compared to dry machining.

Keywords: aluminium, milling operation, peltier cooling effect, surface roughness

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Authors: Julia Braun, Sinikka Treuger, Magdalena Mißler-Behr

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The support of start-ups at German universities is an elementary part of the efforts of the universities. Targeted support for innovative and technology-oriented start-ups is an important prerequisite for successful founding. The present study provides in a first research information on whether German universities have concepts and strategies for promoting the internationalization of start-ups, with a focus on various international markets, and whether they have the ability to successfully raise venture capital. The question is clarified as to how many universities in Germany have programs or concepts for the promotion of start-ups and whether they have already established an internationalization concept for the start-ups. Furthermore, it is shown whether the concepts found focus on the acquisition of venture capital. For this research, a website-based search of the concepts at German universities is carried out and evaluated. In a second study, an online survey at a selected German university is used to evaluate whether there is a general interest in such a concept. After that, a possible concept is derived. The aim of the research is to show the current status of German universities and to give an elaborated example of an education concept for a university which can be adapted by other universities.

Keywords: education concept, german universities, internatinalization, start-ups, venture capital

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Authors: Cristina Costa-Lobo, Ana Campina, José Menezes

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Creativity implies originality, but originality does not imply the existence of creativity. Today, one of the challenges of the educational context is the development of educated, autonomous, prudent and competent citizens with a critical attitude, a well-founded questioning and a creative search for innovative alternatives and solutions. These supposedly cognitive capacities impose emotional analysis and decision making, and emotion is also considered as a creative act. Authors emphasize the importance of family and school in the creative manifestation of children and young people, and these agents can stimulate or impede creative expression. Thus, children entering the school system are faced with a barrier that blocks the externalization of this competence. This work deals with the implementation of specific strategies and promoters of an educational environment suitable for the development of creativity. The construct of creativity is discussed in a transdisciplinary perspective, and the importance of the construct is enhanced in psychoeducational practices, in challenging and multifaceted environments. It is assumed that the stimulation and early experience of creative thinking in an educational context are conditions that promote the development of problem-solving skills and future challenges.

Keywords: creativity, education, psychology, pedagogy

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Authors: Muhammad Rizwan Tabassum, Ao Xia, Jerry D. Murphy

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The aim of this work is to provide an overview of macroalgae as an alternative feedstock for gaseous fuel production and key innovative technologies. Climate change and continuously depleting resources are the key driving forces to think for alternative sources of energy. Macroalgae can be favored over land based energy crops because they are not in direct competition with food crops. However, some drawbacks, such as high moisture content, seasonal variation in chemical composition and process inhibition limit the economic practicability. Macroalgae, like brown seaweed can be converted into gaseous and liquid fuel by different conversion technologies. Biomethane via anaerobic digestion is the appealing technology due to its dual advantage of a commercially applicable and environment friendly technology. Other technologies like biodiesel and bioethanol conversion technologies from seaweed are still under progress. Screening of high yielding macroalgae species, peak harvesting season and process optimization make the technology economically feasible for alternative source of feedstock for biofuel production in future.

Keywords: anaerobic digestion, biofuels, bio-methane, advanced conversion technologies, macroalgae

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Authors: Turan Cetinkaya

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The aim of this study is to determine the relation of the level of social anxiety to various variables of the students in physical education and sports departments. 229 students who are studying at the departments of physical education and sports teaching, sports management and coaching in Ahi Evran University, College of Physical Education and Sports participate in the research. Personal information tool and social anxiety scale consisting 30 items were used as data collection tool in the research. Distribution, frequency, t-test and ANOVA test were used in the comparison of the related data. As a result of statistical analysis, social anxiety levels do not differ according to gender, income level, sports type and national player status.

Keywords: social anxiety, undergraduates, sport, unıversty

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Authors: Viyango Pandian, Kumaresh Athiyappan

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Pelvic congestion Syndrome (PCS) is usually seen in multiparous women who give history of chronic dull-aching pelvic pain. We report a case of a 17 year old unmarried female, who presented with acute onset of chronic dull-aching abdominal pain in the left iliac fossa, which particularly increased during menstruation and was finally diagnosed to be pelvic congestion syndrome. On ultrasonography, multiple tortuous and dilated veins were observed in the left adnexa. Both ovaries appeared normal in size, volume and echotexture. Computed tomography (CT) angiography was performed to precisely delineate the venous pathway and to assess any associated abnormality; which showed a dilated and tortuous left ovarian vein with an anomalous course around the left kidney and draining into the left renal vein. Clinical parameters and hormonal levels were within normal limits. This is a rare case of anomalous course of left ovarian vein associated with pelvic congestion syndrome.

Keywords: anomalous course of ovarian vein, computed tomography, pelvic congestion syndrome, ultrasonography

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Authors: Yu Chen

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In line with existing philosophical approaches, this research proposes a conceptual model with an innovative spatial vision and aesthetic principles for Artificial Intelligence (AI) application in brand advertising. The model first identifies the major constituencies in contemporary advertising on three spatial levels—physical, psychological, and symbolic. The model further incorporates the relationships among AI, aesthetics, branding, and advertising and their interactions with the major actors in all spaces. It illustrates that AI may follow the aesthetic principles-- beauty, elegance, and simplicity-- to reinforce brand identity and consistency in advertising, to collaborate with stakeholders, and to satisfy different advertising objectives on each level. It proposes that, with aesthetic guidelines, AI may assist consumers to emerge into the physical, psychological, and symbolic advertising spaces and helps transcend the tangible advertising messages to meaningful brand symbols. Conceptually, the research illustrates that even though consumers’ engagement with brand mostly begins with physical advertising and later moves to psychological-symbolic, AI-assisted advertising should start with the understanding of brand symbolic-psychological and consumer aesthetic preferences before the physical design to better resonate. Limits of AI and future AI functions in advertising are discussed.

Keywords: AI, spatial, aesthetic, brand advertising

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Authors: Piyaorn Wajanatinapart, Diane R. Lauver

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The number of persons with dementia (PWD) has increased. Informal caregivers are the major providing care. They can have perceived gains and burdens. Caregivers who reported high in perceived gains may report low in burdens and better health. Gaps of caregiving literature were: no report psychometrics in a few studies and unclear definitions of gains; most studies with no theory-guided and conducting in Western countries; not fully described relationships among caregiving variables: motivations, satisfaction with psychological needs, social support, gains, burdens, and physical and psycho-emotional health. Those gaps were filled by assessing psychometric properties of selected measures, providing clearly definitions of gains, using self-determination theory (SDT) to guide the study, and developing the study in Thailand. The study purposes were to evaluate six measures for internal consistency reliability, content validity, and construct validity. This study also examined relationships of caregiving variables: motivations (controlled and autonomous motivations), satisfaction with psychological needs (autonomy, competency, and relatedness), perceived social support, perceived gains, perceived burdens, and physical and psycho-emotional health. This study was a cross-sectional and correlational descriptive design with two convenience samples. Sample 1 was five Thai experts to assess content validity of measures. Sample 2 was 146 Thai caregivers of PWD to assess construct validity, reliability, and relationships among caregiving variables. Experts rated questionnaires and sent them back via e-mail. Caregivers answered questionnaires at clinics of four Thai hospitals. Data analysis was used descriptive statistics and bivariate and multivariate analyses using the composite indicator structural equation model to control measurement errors. For study results, most caregivers were female (82%), middle age (M =51.1, SD =11.9), and daughters (57%). They provided care for 15 hours/day with 4.6 years. The content validity indices of items and scales were .80 or higher for clarity and relevance. Experts suggested item revisions. Cronbach’s alphas were .63 to .93 of ten subscales of four measures and .26 to .57 of three subscales. The gain scale was acceptable for construct validity. With controlling covariates, controlled motivations, the satisfaction with three subscales of psychological needs, and perceived social support had positive relationships with physical and psycho-emotional health. Both satisfaction with autonomy subscale and perceived social support had negative relationship with perceived burdens. The satisfaction with three subscales of psychological needs had positive relationships among them. Physical and psycho-emotional health subscales had positive relationships with each other. Furthermore, perceived burdens had negative relationships with physical and psycho-emotional health. This study was the first use SDT to describe relationships of caregiving variables in Thailand. Caregivers’ characteristics were consistent with literature. Four measures were valid and reliable except two measures. Breadth knowledge about relationships was provided. Interpretation of study results was cautious because of using same sample to evaluate psychometric properties of measures and relationships of caregiving variables. Researchers could use four measures for further caregiving studies. Using a theory would help describe concepts, propositions, and measures used. Researchers may examine the satisfaction with psychological needs as mediators. Future studies to collect data with caregivers in communities are needed.

Keywords: caregivers, caregiving, dementia, measures

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Authors: Jo Kuys, Kirsten Day

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Improving urban transportation systems requires an emphasis on users’ end-to-end journey experience, from the moment the user steps out of their home to when they arrive at their destination. In considering such end-to-end experiences, human centred design (HCD) must be integrated from the very beginning to generate viable outcomes for the public. An HCD approach will encourage innovative outcomes while acknowledging all factors that need to be understood along the journey. We provide evidence to show that when designing for public transportation, it is not just about the physical manifestation of a particular outcome; moreover, it’s about the context and human behaviours that need to be considered throughout the design process. Humans and their behavioural factors are vitally important to successful implementation of sustainable public transport systems. Through an in-depth literature review of HCD approaches for urban transportation systems, we provide a base to exploit the benefits and highlight the importance of including HCD in public transportation projects for greater patronage, resulting in more sustainable cities. An HCD approach is critical to all public transportation projects to understand different levels of transportation design, from the setting of transport policy to implementation to infrastructure, vehicle, and interface design.

Keywords: human centred design, public transportation, urban planning, user experience

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Authors: Shohreh Ghasemi

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Introduction: Melanoma is a complex disease with various clinical and histopathological features that impact prognosis and treatment decisions. Traditional methods of melanoma prognosis involve manual examination and interpretation of clinical and histopathological data by dermatologists and pathologists. However, the subjective nature of these assessments can lead to inter-observer variability and suboptimal prognostic accuracy. AI, with its ability to analyze vast amounts of data and identify patterns, has emerged as a promising tool for improving melanoma prognosis. Methods: A comprehensive literature search was conducted to identify studies that employed AI techniques for melanoma prognosis. The search included databases such as PubMed and Google Scholar, using keywords such as "artificial intelligence," "melanoma," and "prognosis." Studies published between 2010 and 2022 were considered. The selected articles were critically reviewed, and relevant information was extracted. Results: The review identified various AI methodologies utilized in melanoma prognosis, including machine learning algorithms, deep learning techniques, and computer vision. These techniques have been applied to diverse data sources, such as clinical images, dermoscopy images, histopathological slides, and genetic data. Studies have demonstrated the potential of AI in accurately predicting melanoma prognosis, including survival outcomes, recurrence risk, and response to therapy. AI-based prognostic models have shown comparable or even superior performance compared to traditional methods.

Keywords: artificial intelligence, melanoma, accuracy, prognosis prediction, image analysis, personalized medicine

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Authors: Fatemeh Moradian, Razieh Ghorbani, Poria Biparva

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Growing resistance of microorganisms to potent antibiotics has renewed a great interest towards investigating bactericidal properties of nanoparticles and their Nano composites as an alternative. The use of metal nanoparticles to combat bacterial infections is one of the most wide spread applications of nanotechnology in the field of antibacterial. Nanomaterials have unique properties compared to their bulk counterparts. In this report, we demonstrate the antimicrobial activity of zerovalent Iron(ZVI) and Ag(silver) nanoparticles against Gram-negative bacteria E.coli(DH5α) and Pseudomonas aeruginosa. At first ZVI and Ag nanoparticles were synthesized by chemical reduction method and using scanning electron microscopy (SEM) the nanoparticle size determined. Different concentrations of Ag and ZVI nanoparticles were added to bacteria on nutrient agar medium. Minimum inhibitory concentration (MIC) of Ag and Fe nanoparticles for P. aeruginosa were 5µM and 1µg as well as for E.coli were 6µM. and 10 µg, respectively. Among the two nanoparticles, ZVI showed that the greatest antimicrobial activity against E.coli and Ag nanoparticle on P.aeruginosa. Results suggested that the bactericidal effect of metal nanoparticles has been attributed to their small size as well as high surface to volume ratio and NPs could be used as an effective antibacterial material.

Keywords: bactericidal properties, MIC, nanoparticle, SEM

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Authors: Kumar Shashvat, Amol P. Bhondekar

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In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

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Authors: D. Abdelrazek, M. NaguibAly, A. A. Badawi, Asmaa G. Abo Elnour, A. A. El-Kafas

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This work is developed within IAEA Coordinated Research Program 1496, “Innovative methods in research reactor analysis: Benchmark against experimental data on neutronics and thermal-hydraulic computational methods and tools for operation and safety analysis of research reactors.” The study investigates the capability of Code RELAP5/Mod3.4 to solve complex geometry complexity. Its results are compared to the results of PARET, a common code in thermal hydraulic analysis for research reactors, belonging to MTR-PC groups. The WWR-SM reactor at the Institute of Nuclear Physics (INP) in the Republic of Uzbekistan is simulated using both PARET and RELAP5 at steady state. Results from the two codes are compared. REALP5 code succeeded in solving the complex fuel geometry. The PARET code needed some calculations to obtain the final result. Although the final results from the PARET are more accurate, the small differences in both results makes using RELAP5 code recommended in case of complex fuel assemblies.

Keywords: complex fuel geometry, PARET, RELAP5, WWR-SM reactor

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Hen Friman

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Various categories of aqueous solutions are discharged within residential, institutional, commercial, and industrial structures. To safeguard public health and preserve the environment, it is imperative to subject wastewater to treatment processes that eliminate pathogens (such as bacteria and viruses), nutrients (such as nitrogen and phosphorus), and other compounds. Failure to address untreated sewage accumulation can result in an array of adverse consequences. Israel exemplifies a special case in wastewater management. Appropriate wastewater treatment significantly benefits sectors such as agriculture, tourism, horticulture, and industry. Nevertheless, untreated sewage in settlements lacking proper sewage collection or transportation networks remains an ongoing and substantial threat. Notably, the process of wastewater treatment entails substantial energy consumption. Consequently, this study explores the integration of solar energy as a renewable power source within the wastewater treatment framework. By incorporating renewable energy sources into the process, costs can be minimized, and decentralized facilities can be established even in areas lacking adequate infrastructure for traditional treatment methods.

Keywords: renewable energy, solar energy, innovative, wastewater treatment

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Authors: Olawale Johnson

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The cry and agitation for the creation of equal opportunities is one of the major reasons behind the social menace countries of the world experience. As the poor, continue to demand for the dividends of economic growth, countries of the world are in a state of dilemma because, despite impressive growth figures, the poor are still far below the empowerment line. However, evidence from the Asian Tigers has proven that with the adoption and efficient utilization of information technology, a growth miracle is not far-fetched. With the mind-boggling pace of technological innovation, the need to ensure that the innovative products are all connected has become vital. Technologies that did not exist a few years ago have become vital equipment used to underlie every aspect of our economy from medicine to banking to sports. The need to connect things sensors, actuators and smart systems with the aim of ensuring person-to-object, object-to-object communications has promoted the need of internet of things. As developing countries struggle with delivering inclusiveness, the Internet of Everything is perceived to be the miracle that will deliver this in no time. This paper examines how the Asian Tigers have been able to promote inclusive growth through the Internet of Everything.

Keywords: inclusive growth, internet of everything, innovation, embedded systems and smart technologies

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Authors: Ainur Bulasheva

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During the last decade, the dual learning system (DLS) has been actively introduced in various industries in Kazakhstan, including both vocational, post-secondary, and higher education levels. It is a relatively new practice-oriented approach to training qualified personnel in Kazakhstan, officially introduced in 2012. Dual learning was integrated from the German vocational education and training system, combining practical training with part-time work in production and training in an educational institution. The policy of DLS has increasingly focused on decreasing youth unemployment and the shortage of mid-level professionals by providing incentives for employers to involve in this system. By participating directly in the educational process, the enterprise strives to train its future personnel to meet fast-changing market demands. This study examines the effectiveness of DLS from the perspective of employers to understand the motivations of businesses to participate (invest) in this program. The human capital theory of Backer, which predicts that employers will invest in training their workers (in our case, dual students) when they expect that the return on investment will be greater than the cost - acts as a starting point. Further extensionists of this theory will be considered to understand investing intentions of businesses. By comparing perceptions of DLS employers and non-dual practices, this study determines the efficiency of promoted training approach for enterprises in the Kazakhstan agri-food industry.

Keywords: vocational and technical education, dualeducation, human capital theory, argi-food industry

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Authors: Parsa Naji

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Following the Iran Islamic Revolution in 1979 and the subsequent formation of a theocratic regime, the new regime implemented stringent regulations and a complicated censorship system in the film industry. Thereupon, the screening of films showing the relationships between males and females encountered numerous limitations. Not only did these limits encompass the physical portrayal of the relationship between males and females, but also the dialogues containing explicit sexual or even passionate romantic themes, resulting in a film being permanently consigned to archival storage. However, despite these limitations, Iranian filmmakers persevered in creating their interesting cinematic works. Throughout the years after the revolution, Iranian directors have navigated a series of challenges and obstacles, employing innovative and unconventional methods to bypass the rigorous censorship system imposed by the government, ensuring the screening of their films. This study aims to analyze the creative approaches employed by Iranian filmmakers to circumvent governmental censorship regulations.

Keywords: censorship, Iranian cinema, Islamic revolution, male-female relationship

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Authors: Dinesh Khanduja, Sahib Sartaj Singh

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In India, among the start ups, many new ventures fail and for the few that survive and grow, there are always numerous problems. In order to make these surviving units productive and cost effective-in today’s competitive environment, the traditional ways of supporting small enterprises and the related programs of governmental assistance need to be significantly transformed. In this context, ‘Business Incubation’ is emerging as one of the most innovative instruments to support small enterprise creation and development all over the world. Incubators, by providing on the-spot diagnosis and treatment of business problems, dramatically lower the early stage failure rate. In Europe, US and countries like China, Singapore, Thailand etc., the exceptionally fast growth of business incubators has baffled even the researchers. In this direction in India, following on the world pattern, several initiatives have been taken over the last decade to encourage the concept of business incubation. Besides profiling the existing ‘Business Incubators’ in India, the paper dwells upon a case study of SMEs in state of Punjab for exploring the relevance of business incubation for enhancing their productive capacity.

Keywords: business incubation, Technology Business Incubator (TBI), Rural Business Hub (RBH), entrepreneurship, Business Development Services (BDS), technology management

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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Advanced metering technologies coupled with informatics creates an opportunity to form digital multi-utility service providers. These providers will be able to concurrently collect a customers’ medium-high resolution water, electricity and gas demand data and provide user-friendly platforms to feed this information back to customers and supply/distribution utility organisations. With the emergence of blockchain technology, a new research area has been explored which helps bring this multi-utility service provider concept to a much higher level. This study aims at introducing a breakthrough system architecture where smart metering technology in water, energy, and gas (WEG) are combined with blockchain technology to provide customer a novel real-time consumption report and decentralized resource trading platform. A pilot study on 4 properties in Australia has been undertaken to demonstrate this system, where benefits for customers and utilities are undeniable.

Keywords: blockchain, digital multi-utility, end use, demand forecasting

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Authors: David M. Gilstrap

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Designing effective instructions is a critical dimension of effective teaching systems. Due to a void in interpersonal contact, online courses present new challenges in this regard, especially with large class sizes. This presentation is a case study in how the repetition of instructions within the course design was utilized to increase instructor efficiency in managing a rapid rise in enrollment. World of Turf is a two-credit, semester-long elective course for non-turfgrass majors at Michigan State University. It is taught entirely online and solely by the instructor without any graduate teaching assistants. Discussion forums about subject matter are designated for each lecture, and those forums are moderated by a few undergraduate turfgrass majors. The instructions as to the course structure, navigation, and grading are conveyed in the syllabus and course-introduction lecture. Regardless, students email questions about such matters, and the number of emails increased as course enrollment grew steadily during the first three years of its existence, almost to a point that the course was becoming unmanageable. Many of these emails occurred because the instructor was failing to update and operate the course in a timely and proper fashion because he was too busy answering emails. Some of the emails did help the instructor ferret out poorly composed instructions, which he corrected. Beginning in the summer semester of 2015, the instructor overhauled the course by segregating content into weekly modules. The philosophy envisioned and embraced was that there can never be too much repetition of instructions in an online course. Instructions were duplicated within each of these modules as well as associated modules for syllabus and schedules, getting started, frequently asked questions, practice tests, surveys, and exams. In addition, informational forums were created and set aside for questions about the course workings and each of the three exams, thus creating even more repetition. Within these informational forums, students typically answer each other’s questions, which demonstrated to the students that that information is available in the course. When needed, the instructor interjects with corrects answers or clarifies any misinformation which students might be putting forth. Increasing the amount of repetition of instructions and strategic enhancements to the course design have resulted in a dramatic decrease in the number of email replies necessitated by the instructor. The resulting improvement in efficiency allowed the instructor to raise enrollment limits thus effecting a ten-fold increase in enrollment over a five-year period with 1050 students registered during the most recent academic year, thus becoming easily the largest online course at the university. Because of the improvement in course-delivery efficiency, sufficient time was created that allowed the instructor to development and launch an additional online course, hence further enhancing his productivity and value in terms of the number of the student-credit hours for which he is responsible.

Keywords: design, efficiency, instructions, online, repetition

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Authors: Sofia Douklia

Abstract:

The present context paper aims to present the important role of ‘student voice’ and the music teacher in the classroom, which contributes to more student-centered music education. The aim is to focus on the functions of the student voice through the music spectrum, which has been born in the music classroom, and the teacher’s methodologies and techniques used in the music classroom. The music curriculum, the principles of student-centered music education, and the role of students and teachers as music ambassadors have been considered the major music parameters of student voice. The student- voice is a worth-mentioning aspect of a student-centered education, and all teachers should consider and promote its existence in their classroom.

Keywords: student's voice, student-centered education, music ambassadors, music teachers

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Authors: Omil Nady Mahrous Maximous

Abstract:

The construction industry is currently experiencing a shift towards digitisation. This transformation is driven by adopting technologies like Building Information Modelling (BIM), drones, and augmented reality (AR). These advancements are revolutionizing the process of designing, constructing, and operating projects. BIM, for instance, is a new way of communicating and exploiting technology such as software and machinery. It enables the creation of a replica or virtual model of buildings or infrastructure projects. It facilitates simulating construction procedures, identifying issues beforehand, and optimizing designs accordingly. Drones are another tool in this revolution, as they can be utilized for site surveys, inspections, and even deliveries. Moreover, AR technology provides real-time information to workers involved in the project. Implementing these technologies in the construction industry has brought about improvements in efficiency, safety measures, and sustainable practices. BIM helps minimize rework and waste materials, while drones contribute to safety by reducing workers' exposure to areas. Additionally, AR plays a role in worker safety by delivering instructions and guidance during operations. Although the digital transformation within the construction industry is still in its early stages, it holds the potential to reshape project delivery methods entirely. By embracing these technologies, construction companies can boost their profitability while simultaneously reducing their environmental impact and ensuring safer practices.

Keywords: architectural education, construction industry, digital learning environments, immersive learning BIM, digital construction, construction technologies, digital transformation artificial intelligence, collaboration, digital architecture, digital design theory, material selection, space construction

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Authors: Housein Deli, Loui Al-Shrouf, Hammoud Al Joumaa, Mohieddine Jelali

Abstract:

When forming metallic materials, fluctuations in material properties, process conditions, and wear lead to deviations in the component geometry. Several hundred features sometimes need to be measured, especially in the case of functional and safety-relevant components. These can only be measured offline due to the large number of features and the accuracy requirements. The risk of producing components outside the tolerances is minimized but not eliminated by the statistical evaluation of process capability and control measurements. The inspection intervals are based on the acceptable risk and are at the expense of productivity but remain reactive and, in some cases, considerably delayed. Due to the considerable progress made in the field of condition monitoring and measurement technology, permanently installed sensor systems in combination with machine learning and artificial intelligence, in particular, offer the potential to independently derive forecasts for component geometry and thus eliminate the risk of defective products - actively and preventively. The reliability of forecasts depends on the quality, completeness, and timeliness of the data. Measuring all geometric characteristics is neither sensible nor technically possible. This paper, therefore, uses the example of car seat rail production to discuss the necessary first step of feature selection and reduction by correlation analysis, as otherwise, it would not be possible to forecast components in real-time and inline. Four different car seat rails with an average of 130 features were selected and measured using a coordinate measuring machine (CMM). The run of such measuring programs alone takes up to 20 minutes. In practice, this results in the risk of faulty production of at least 2000 components that have to be sorted or scrapped if the measurement results are negative. Over a period of 2 months, all measurement data (> 200 measurements/ variant) was collected and evaluated using correlation analysis. As part of this study, the number of characteristics to be measured for all 6 car seat rail variants was reduced by over 80%. Specifically, direct correlations for almost 100 characteristics were proven for an average of 125 characteristics for 4 different products. A further 10 features correlate via indirect relationships so that the number of features required for a prediction could be reduced to less than 20. A correlation factor >0.8 was assumed for all correlations.

Keywords: long-term SHM, condition monitoring, machine learning, correlation analysis, component prediction, wear prediction, regressions analysis

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Authors: Ting Hsiang Chang, Cheng Zuo Tsai

Abstract:

In recent years, sports culture dominated in Taiwan, which spurred the rapid development of the sports industry. More innovative and high-tech sporting goods were developed to provide choices for consumers. Nowadays, Taiwan has gradually entered the aging society where people pay more attention to health promotion, delay of aging and other related issues among senior. However, it is an undeniable fact that moderate exercise is a great help to delay aging. Therefore, how senior select the appropriate sporting goods, including sports shoes, sportswear, sports equipment, and even the sports brands when engaged in various kinds of sports, are explored in this research. Therefore, this study sets the reference indicators by exploring the brands of sporting goods, that senior aged 50-70 choose in a fog peak district, the Taichung City, as the subjects of study by answering a questionnaire. Also, this study offers recommendations in terms of the design, marketing or selling of sporting goods for the senior, and how owners of sports brands or related sports industries should target them.

Keywords: senior, aging, sporting goods, sports brand

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Authors: Chux Gervase Iwu, Simon Nsengimane

Abstract:

Entrepreneurship stimulates socio-economic development in many countries, if not all. It creates jobs and decreases unemployment and inequality. There are other benefits that are accruable from entrepreneurship, namely the empowerment of women and the promotion of better livelihoods. Innovation has become a weapon for business competition, growth, and sustainability. Paradoxically, it is a threat to businesses because products can be duplicated; new products may decrease the market share of existing ones or delete them from the market. This creates a constant competitive environment that calls for updates, innovation, and the invention of new products and services. Thus, the importance of higher education in instilling a good entrepreneurial mindset in students has become even more critical. It can be argued that the business environment is under enormous pressure from several factors, including the fourth industrial revolution, which calls for the adoption and use of information and communication technology, which is the catalyst for many innovations and organisational changes. Therefore, it is crucial that higher education students are equipped with relevant knowledge and skills to respond effectively to the needs of the business environment and create a vibrant entrepreneurship ecosystem. In South Africa, entrepreneurship education or some form of it has been a privilege for economic and management fields of study, leaving behind other fields. Entrepreneurship should not be limited to business faculties but rather extended to other fields of study. This is perhaps the reason for low levels of entrepreneurship uptake among South African graduates if they are compared with the graduates in other countries. There may be other reasons for the low entrepreneurship uptake. Some of these have been documented in extant literature to include (1) not enough time was spent teaching entrepreneurship in the business faculties, (2) the skills components in the curricula are insufficient, and (3) the overall attitudes/mindsets necessary to establish and run sustainable enterprises seem absent. Therefore, four important areas are recognised as crucial for the effective implementation of entrepreneurship education: policy, private sector engagement, curriculum development, and teacher development. The purpose of this research is to better comprehend the views, aspirations, and expectations of students and faculty members to design an entrepreneurial teaching model for higher education institutions. A qualitative method will be used to conduct a purposive interview with undergraduate and graduate students in select higher institutions. Members of faculty will also be included in the sample as well as, where possible, two or more government personnel responsible for higher education policy development. At present, interpretative analysis is proposed for the analysis of the interviews with the support of Atlas Ti. It is hoped that an entrepreneurship education model in the South African context is realised through this study.

Keywords: entrepreneurship education, higher education institution, graduate unemployment, curriculum development

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