Search results for: Digital Learning

Authors: Yosra Mefteh Rekik

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A computational agent-based model of financial markets stresses interactions and dynamics among a very diverse set of traders. The growing body of research in this area relies heavily on computational tools which by-pass the restrictions of an analytical method. The main goal of this research is to understand how the stock market operates and behaves how to invest in the stock market and to study traders’ behavior within the context of the artificial stock markets populated by heterogeneous agents. All agents are characterized by adaptive learning behavior represented by the Artificial Neuron Networks. By using agent-based simulations on artificial market, we show that the existence of heterogeneous agents can explain the price dynamics in the financial market. We investigate the relation between market diversity and market efficiency. Our empirical findings demonstrate that greater market heterogeneity play key roles in market efficiency.

Keywords: agent-based modeling, artificial stock market, heterogeneous expectations, financial stylized facts, computational finance

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Authors: Manvelidze irakli, Iashvili Genadi

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Research has shown that public institutions in Autonomous Republic of Ajara try their best to make their official electronic data (web-pages, social websites) more informative and improve them. Part of public institutions offer interesting electronic services and initiatives to the public although they are seldom used in communication process. The statistical analysis of the use of web-pages and social websites of public institutions for example their facebook page show lack of activity. The reason could be the fact that public institutions give people less possibility of interaction in official web-pages. Second reason could be the fact that these web-pages are less known to the public and the third reason could be the fact that heads of these institutions lack awareness about the necessity of strengthening citizens’ involvement. In order to increase people’s involvement in this process it is necessary to have at least 23 e-services in one web-page. The research has shown that 11 of the 16 public institutions have only 5 services which are contact, social networks and hotline. Besides introducing innovative services government institutions should evaluate them and make them popular and easily accessible for the public. It would be easy to solve this problem if public institutions had concrete strategic plan of public relations which involved matters connected with maximum usage of electronic services while interaction with citizens. For this moment only one governmental body has a functioning action plan of public relations. As a result of the research organizational, social, methodological and technical problems have been revealed. It should be considered that there are many feedback possibilities like forum, RSS, blogs, wiki, twitter, social networks, etc. usage of only one or three of such instruments indicate that there is no strategy of regional electronic governance. It is necessary to develop more mechanisms of feedback which will increase electronic interaction, discussions and it is necessary to introduce the service of online petitions. It is important to reduce the so-called “digital inequality” and increase internet access for the public. State actions should decrease such problems. In the end if such shortcomings will be improved the role of electronic interactions in democratic processes will increase.

Keywords: e-Government, electronic services, information technology, regional government, regional government

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Authors: B. Mavhuru, N. S. Nethengwe

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Human activities on land degradation have triggered several environmental problems especially in rural areas that are underdeveloped. The main aim of this study is to analyze the contribution of different land uses to gully development and sediment load on the Nzhelele River Valley in the Limpopo Province. Data was collected using different methods such as observation, field data techniques and experiments. Satellite digital images, topographic maps, aerial photographs and the sediment load static model also assisted in determining how land use affects gully development and sediment load. For data analysis, the researcher used the following methods: Analysis of Variance (ANOVA), descriptive statistics, Pearson correlation coefficient and statistical correlation methods. The results of the research illustrate that high land use activities create negative changes especially in areas that are highly fragile and vulnerable. Distinct impact on land use change was observed within settlement area (9.6 %) within a period of 5 years. High correlation between soil organic matter and soil moisture (R=0.96) was observed. Furthermore, a significant variation (p ≤ 0.6) between the soil organic matter and soil moisture was also observed. A very significant variation (p ≤ 0.003) was observed in bulk density and extreme significant variations (p ≤ 0.0001) were observed in organic matter and soil particle size. The sand mining and agricultural activities has contributed significantly to the amount of sediment load in the Nzhelele River. A high significant amount of total suspended sediment (55.3 %) and bed load (53.8 %) was observed within the agricultural area. The connection which associates the development of gullies to various land use activities determines the amount of sediment load. These results are consistent with other previous research and suggest that land use activities are likely to exacerbate the development of gullies and sediment load in the Nzhelele River Valley.

Keywords: drainage basin, geomorphological processes, gully development, land degradation, riparian land use and sediment load

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Authors: Lillian M. Seo, Curtis L. Petersen, Ryan J. Halter, David Kotz, John A. Batsis

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Background: Resistance-based exercises effectively enhance muscle strength, which is especially important in older populations as it reduces the risk of disability. Our group developed a Bluetooth-enabled handle for resistance exercise bands that wirelessly transmits relative force data through low-energy Bluetooth to a local smartphone or similar device. The system has the potential to measure home-based exercise interventions, allowing health professionals to monitor compliance. Its feasibility has already been demonstrated in both clinical and field-based settings, but it remained unclear whether the system’s usability persisted upon repeated use. The current study sought to assess the usability of this system and its users’ satisfaction with repeated use by deploying the device among younger adults to gather formative information that can ultimately improve the device’s design for older adults. Methods: A usability study was conducted in which 32 participants used the above system. Participants executed 10 repetitions of four commonly performed exercises: bicep flexion, shoulder abduction, elbow extension, and triceps extension. Each completed three exercise sessions, separated by at least 24 hours to minimize muscle fatigue. At its conclusion, subjects completed an adapted version of the usefulness, satisfaction, and ease (USE) questionnaire – assessing the system across four domains: usability, satisfaction, ease of use, and ease of learning. The 20-item questionnaire examined how strongly a participant agrees with positive statements about the device on a seven-point Likert scale, with one representing ‘strongly disagree’ and seven representing ‘strongly agree.’ Participants’ data were aggregated to calculate mean response values for each question and domain, effectively assessing the device’s performance across different facets of the user experience. Summary force data were visualized using a custom web application. Finally, an optional prompt at the end of the questionnaire allowed for written comments and feedback from participants to elicit qualitative indicators of usability. Results: Of the n=32 participants, 13 (41%) were female; their mean age was 32.4 ± 11.8 years, and no participants had a physical impairment. No usability questions received a mean score < 5 of seven. The four domains’ mean scores were: usefulness 5.66 ± 0.35; satisfaction 6.23 ± 0.06; ease of use 6.25 ± 0.43; and ease of learning 6.50 ± 0.19. Representative quotes of the open-ended feedback include: ‘A non-rigid strap-style handle might be useful for some exercises,’ and, ‘Would need different bands for each exercise as they use different muscle groups with different strength levels.’ General impressions were favorable, supporting the expectation that the device would be a useful tool in exercise interventions. Conclusions: A simple usability assessment of a Bluetooth-enabled resistance exercise band supports a consistent and positive user experience among young adults. This study provides adequate formative data, assuring the next steps can be taken to continue testing and development for the target population of older adults.

Keywords: Bluetooth, exercise, mobile health, mHealth, usability

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Authors: Sujay Kotwale, Ramasubba Reddy M.

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Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

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Authors: Yang Zhang, Jian He

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Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

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Authors: Muhammad Awais Kiani, Maryam Kiani

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This abstract explores the confluence of these two domains and highlights the key factors driving success in sales marketing for electronics. The abstract begins by digging into the ever-evolving landscape of consumer electronics, emphasizing how technological advancements and the growth of smart devices have revolutionized the way people interact with electronics. This paradigm shift has created tremendous opportunities for sales and marketing professionals to engage with consumers on various platforms and channels. Next, the abstract discusses the pivotal role of effective sales marketing strategies in the electronics industry. It highlights the importance of understanding consumer behavior, market trends, and competitive landscapes and how this knowledge enables businesses to tailor their marketing efforts to specific target audiences. Furthermore, the abstract explores the significance of leveraging digital marketing techniques, such as social media advertising, search engine optimization, and influencer partnerships, to establish brand identity and drive sales in the electronics market. It emphasizes the power of storytelling and creating captivating content to engage with tech-savvy consumers. Additionally, the abstract emphasizes the role of customer relationship management (CRM) systems and data analytics in optimizing sales marketing efforts. It highlights the importance of leveraging customer insights and analyzing data to personalize marketing campaigns, enhance customer experience, and ultimately drive sales growth. Lastly, the abstract concludes by underlining the importance of adapting to the ever-changing landscape of the electronics industry. It encourages businesses to embrace innovation, stay informed about emerging technologies, and continuously evolve their sales marketing strategies to meet the evolving needs and expectations of consumers. Overall, this abstract sheds light on the captivating realm of sales marketing in the electronics industry, emphasizing the need for creativity, adaptability, and a deep understanding of consumers to succeed in this rapidly evolving market.

Keywords: marketing industry, electronics, sales impact, e-commerce

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Authors: N. Schneider, M. Bruchhage, M. Hartweg, G. Mutungi, J. O Regan, S. Deoni

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Observational neuroimaging studies suggest differences between breast-fed and formula-fed infants in developmental myelination, a key brain process for learning and cognitive development. However, the possible effects of a nutrient formulation on myelin development in healthy term infants in an intervention study have not been investigated. Objective was, therefore, to investigate the efficacy of a nutrient formulation with higher levels of myelin-relevant nutrients as compared to a control formulation with lower levels of the same nutrients on brain myelination and cognitive development in the first 6 months of life. The study is an ongoing randomized, controlled, double-blind, two-center, parallel-group clinical trial with a nonrandomized, non-blinded arm of exclusively breastfed infants. The current findings result from a staged statistical analysis at 6 months; the recruitment and intervention period has been completed for all participants. Follow-up visits at 12, 18 and 24 months are still ongoing. N= 81 enrolled full term, neurotypical infants of both sexes were randomized into either the investigational (N= 42) or the control group (N= 39), and N= 108 children in the breast-fed arm served as a natural reference group. The effect of a blend of docosahexaenoic acid, arachidonic acid, iron, vitamin B12, folic acid as well as sphingomyelin from a uniquely proceed whey protein concentrate enriched in alpha-lactalbumin and phospholipids in an infant nutrition product matrix was investigated. The main outcomes for the staged statistical analyses at 6 months included brain myelination measures derived from MRI. Additional outcomes were brain volume, cognitive development and safety. The full analyses set at 6 months comprised N= 66 infants. Higher levels of myelin-relevant nutrients compared to lower levels resulted in significant differences in myelin structure, volume, and rate of myelination as early as 3 and 6 months of life. The cross-sectional change of means between groups for whole-brain myelin volume was 8.4% for investigational versus control formulation (3.5% versus the breastfeeding reference) group at 3 months and increased to 36.4% for investigational versus control formulation (14.1% versus breastfeeding reference) at 6 months. No statistically significant differences were detected for early cognition scores. Safety findings were largely similar across groups. This is the first pediatric nutritional neuroimaging study demonstrating the efficacy of a myelin nutrient blend on developmental myelination in well-nourished term infants. Myelination is a critical process in learning and development. The effects were demonstrated across the brain, particularly in temporal and parietal regions, known to be functionally involved in sensory, motor and language skills. These first results add to the field of nutritional neuroscience by demonstrating early life nutrition benefits for brain architecture which may be foundational for later cognitive and behavioral outcomes. ClinicalTrials.gov Identifier: NCT03111927 (Infant Nutrition and Brain Development - Full-Text View - ClinicalTrials.gov).

Keywords: brain development, infant nutrition, MRI, myelination

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Authors: Nattamon Srithammee, Ratchanikorn Chonchaiya

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This study explores the impact of Augmented Reality (AR) technology on mathematics education, focusing on Area and Volume concepts at Phra Dabos School in Thailand. We developed a mobile augmented reality application to present these mathematical concepts innovatively. Using a mixed-methods approach, we assessed the knowledge of 79 students before and after using the application. The results showed a significant improvement in students' understanding of Area and Volume, with average test scores increasing from 3.70 to 9.04 (p < 0.001, Cohen's d = 2.05). Students also reported increased engagement and satisfaction. Our findings suggest that augmented reality technology can be a valuable tool in mathematics education, particularly for enhancing the understanding of abstract concepts like Area and Volume. This study contributes to research on educational technology in STEM education and provides insights for educators and educational technology developers.

Keywords: augmented reality, mathematics education, area and volume, educational technology, STEM education

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Authors: Bernabeo R. Alberto

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With the tremendous improvements in the processing power of computers, the possibilities of artificial intelligence will increasingly be used in aviation and make autonomous flights, preventive maintenance, ATM (Air Traffic Management) optimization, pilots, cabin crew, ground staff, and airport staff training possible in a cost-saving, less time-consuming and less polluting way. Through the use of artificial intelligence, we foresee an interviewing scenario where the interviewee will interact with the artificial intelligence tool to contextualize the character and the necessary information in a way that aligns reasonably with the character and the scenario. We are creating simulated scenarios connected with either an aviation incident or accident to enhance also the training of future accident/incident investigators integrating artificial intelligence and augmented reality tools. The project's goal is to improve the learning and teaching scenario through academic and professional expertise in aviation and in the artificial intelligence field. Thus, we intend to contribute to the needed high innovation capacity, skills, and training development and management of artificial intelligence, supported by appropriate regulations and attention to ethical problems.

Keywords: artificial intelligence, aviation accident, aviation incident, risk, safety

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Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

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Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

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Authors: Assem Abdel Hamed Mousa

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The Internet of Things probably already influences your life. And if it doesn’t, it soon will, say computer scientists; Ubiquitous computing names the third wave in computing, just now beginning. First were mainframes, each shared by lots of people. Now we are in the personal computing era, person and machine staring uneasily at each other across the desktop. Next comes ubiquitous computing, or the age of calm technology, when technology recedes into the background of our lives. Alan Kay of Apple calls this "Third Paradigm" computing. Ubiquitous computing is essentially the term for human interaction with computers in virtually everything. Ubiquitous computing is roughly the opposite of virtual reality. Where virtual reality puts people inside a computer-generated world, ubiquitous computing forces the computer to live out here in the world with people. Virtual reality is primarily a horse power problem; ubiquitous computing is a very difficult integration of human factors, computer science, engineering, and social sciences. The approach: Activate the world. Provide hundreds of wireless computing devices per person per office, of all scales (from 1" displays to wall sized). This has required new work in operating systems, user interfaces, networks, wireless, displays, and many other areas. We call our work "ubiquitous computing". This is different from PDA's, dynabooks, or information at your fingertips. It is invisible; everywhere computing that does not live on a personal device of any sort, but is in the woodwork everywhere. The initial incarnation of ubiquitous computing was in the form of "tabs", "pads", and "boards" built at Xerox PARC, 1988-1994. Several papers describe this work, and there are web pages for the Tabs and for the Boards (which are a commercial product now): Ubiquitous computing will drastically reduce the cost of digital devices and tasks for the average consumer. With labor intensive components such as processors and hard drives stored in the remote data centers powering the cloud , and with pooled resources giving individual consumers the benefits of economies of scale, monthly fees similar to a cable bill for services that feed into a consumer’s phone.

Keywords: internet, cloud computing, ubiquitous computing, big data

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Authors: R. Hasterok, A. Betekhtin, N. Borowska, A. Braszewska-Zalewska, E. Breda, K. Chwialkowska, R. Gorkiewicz, D. Idziak, J. Kwasniewska, M. Kwasniewski, D. Siwinska, A. Wiszynska, E. Wolny

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In contrast to animals, the organisation of plant genomes at the cytomolecular level is still relatively poorly studied and understood. However, the Brachypodium genus in general and B. distachyon in particular represent exceptionally good model systems for such study. This is due not only to their highly desirable ‘model’ biological features, such as small nuclear genome, low chromosome number and complex phylogenetic relations, but also to the rapidly and continuously growing repertoire of experimental tools, such as large collections of accessions, WGS information, large insert (BAC) libraries of genomic DNA, etc. Advanced cytomolecular techniques, such as fluorescence in situ hybridisation (FISH) with evermore sophisticated probes, empowered by cutting-edge microscope and digital image acquisition and processing systems, offer unprecedented insight into chromatin organisation at various phases of the cell cycle. A good example is chromosome painting which uses pools of chromosome-specific BAC clones, and enables the tracking of individual chromosomes not only during cell division but also during interphase. This presentation outlines the present status of molecular cytogenetic analyses of plant genome structure, dynamics and evolution using B. distachyon and some of its relatives. The current projects focus on important scientific questions, such as: What mechanisms shape the karyotypes? Is the distribution of individual chromosomes within an interphase nucleus determined? Are there hot spots of structural rearrangement in Brachypodium chromosomes? Which epigenetic processes play a crucial role in B. distachyon embryo development and selective silencing of rRNA genes in Brachypodium allopolyploids? The authors acknowledge financial support from the Polish National Science Centre (grants no. 2012/04/A/NZ3/00572 and 2011/01/B/NZ3/00177)

Keywords: Brachypodium, B. distachyon, chromosome, FISH, molecular cytogenetics, nucleus, plant genome organisation

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Authors: Thomas Ogilegwu Orohu

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This paper presents agricultural education as a vocational study, an impetus for youths, economic empowerment. The survival of Nigeria’s agriculture rests squarely on the youth who are the farmers and leaders of tomorrow. Hitherto, the teaching and learning of agriculture has proceeded in such a manner that graduates of such programs have failed to make the successful launch into the world of agricultural enterprises (entrepreneurship). Major constraints that predisposed this anomalous situation were identified to include poor policy framework, socio-economic pressures, undue parental and peer influences, improper value orientation and of course, the nature of curricula. In response to the situation, some programs and/or initiatives aimed at inculcating entrepreneurial skills were proposed by this paper with identified target beneficiaries. The initiatives bordered on curricular reorientation that integrate entrepreneurship/enterprise education, retraining of graduates, financial support system among others.

Keywords: Program initiatives. vocational agriculture, youths’ empowerment, introduction

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Authors: Sandra So, Mohd Roslan Ismail, Safurah Jaafar

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With the rapid proliferation of data in healthcare has provided an opportune platform creation of Artificial Intelligence (AI). AI has brought a paradigm shift for healthcare professionals, promising improvement in delivery and quality. This study aims to determine the perception of healthcare personnel on perceived ease of use, perceived usefulness, and subjective norm toward attitude for artificial intelligence acceptance. A cross-sectional single institutional study of employees’ perception of adopting AI in the hospital was conducted. The survey was conducted using a questionnaire adapted from Technology Acceptance Model and a four-point Likert scale was used. There were 96 or 75.5% of the total population responded. This study has shown the significant relationship and the importance of ease of use, perceived usefulness, and subjective norm to the acceptance of AI. In the study results, it concluded that the determining factor to the strong acceptance of AI in their practices is mostly those respondents with the most interaction with the patients and clinical management.

Keywords: artificial intelligence, machine learning, perceived ease of use, perceived usefulness, subjective norm

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Authors: S. Kawther, C. Marshall

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Educational neuroscience has the intention of transforming research findings of the underpinning neural processes of learning to educational practices. A main criticism of the field, hitherto, is that less focus has been put on studying the in-progress practical application of these findings. Therefore, this study aims to gain a better understanding of teachers’ perceptions of the practical application and utilization of brain knowledge. This was approached by investigating the answer to 'What are the facilitators and barriers for bringing research from neuroscience to bear on education?'. Following a qualitative design, semi-structured interviews were conducted with 12 teachers who had a proficient course in educational neuroscience. Thematic analysis was performed on the transcribed data applying Braun & Clark’s steps. Findings emerged with four main themes: time, knowledge, teacher’s involvement, and system. These themes revealed that some effective brain-based practices are being engaged in by the teachers. However, the lack of guidance and challenges regarding this implementation were also found. This study discusses findings in light of the development of educational neuroscience implementation.

Keywords: brain-based, educational neuroscience, neuroeducation, neuroscience-informed

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Authors: Jaidev Tripathy

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A human generation’s lifestyle, behaviors, habits, and actions are governed heavily by homogenous mindsets. But the current scenario is witnessing a rapid gap in this homogeneity as a result of an intervention, or rather, the dominance of the digital revolution in the human lifestyle. The current mindset for mass production, employment, multi-tasking, rapid involvement, and stiff competition to stay above the rest has led to a major shift in human consciousness. Architecture, as an entity, is being perceived differently. The screens are replacing the skies. The pace at which operation and evolution is taking place has increased. It is paradoxical, that time seems to be moving faster despite the intention to save time. Parallelly, there is an evident shift in architectural typologies spanning across different generations. The architecture of today is now seems influenced heavily from here and there. Mass production of buildings and over-exploitation of resources giving shape to uninspiring algorithmic designs, ambiguously catering to multiple user groups, has become a prevalent theme. Borrow-and-steal replaces influence, and the diminishing depth in today’s designs reflects a lack of understanding and connection. The digitally dominated world, perceived as an aid to connect and network, is making humans less capable of real-life interactions and understanding. It is not wrong, but it doesn’t seem right either. The engagement level between human beings and the built environment is a concern which surfaces. This leads to a question: Does human engagement drive architecture, or does architecture drive human engagement? This paper attempts to relook at architecture's capacity and its relativity with pace to influence the conscious decisions of a human being. Secondary research, supported with case examples, helps in understanding the translation of human engagement with the built environment through physicality of architecture. The procedure, or theme, is pace and the role of slowness in the context of human behaviors, thus bridging the widening gap between the human race and the architecture themselves give shape to, avoiding a possible future dystopian world.

Keywords: junkspace, pace, perception, slowness

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Authors: Thidilweli Denga, Bessie Malila, Lucretia Petersen

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The Coronavirus Disease of 2019 (COVID-19) pandemic should be taken as a wake-up call on the importance of hearing health care considering amongst other things the electronic methods of communication used. The World Health Organization (WHO) estimated that by 2050, there will be more than 2.5 billion people living with hearing loss. These numbers show that more people will need rehabilitation services. Studies have shown that most people living with hearing loss reside in Low-Middle Income Countries (LIMC). Innovative technological solutions such as digital health interventions that can be used to deliver hearing health services to remote areas now exist. Tele-audiology implementation can potentially enable the delivery of hearing loss services to rural and remote areas. This study aimed to establish the concurrent validity of the tele-audiology practice in school-based hearing screening. The study employed a cross-sectional design with a within-group comparison. The portable KUDUwave Audiometer was used to conduct hearing screening from 50 participants (n=50). In phase I of the study, the audiologist conducted on-site hearing screening, while the synchronous remote hearing screening (tele-audiology) using a 5G network was done in phase II. On-site hearing screening results were obtained for the first 25 participants (aged between 5-6 years). The second half started with the synchronous tele-audiology model to avoid order-effect. Repeated sample t-tests compared threshold results obtained in the left and right ears for onsite and remote screening. There was a good correspondence between the two methods with a threshold average within ±5 dB (decibels). The synchronous tele-audiology model has the potential to reduce the audiologists' case overload, while at the same time reaching populations that lack access due to distance, and shortage of hearing professionals in their areas of reach. With reliable and broadband connectivity, tele-audiology delivers the same service quality as the conventional method while reducing the travel costs of audiologists.

Keywords: hearing screening, low-resource communities, portable audiometer, tele-audiology

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Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

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The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

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Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

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Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

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Authors: KuiDong Kang, Hye Bin Yim, Su Ah Kim

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Purpose: Tectorigenin is an isoflavone derived from the rhizome of Belamacanda chinensis. In this study, oxygen-induced retinopathy was used to characterize the anti-angiogenic properties of tectorigenin in mice. Methods: ICR neonatal mice were exposed to 75% oxygen from postnatal day P7 until P12 and returned to room air (21% oxygen) for five days (P12 to P17). Mice were subjected to daily intraperitoneal injection of tectorigenin (1 mg/kg, 10 mg/kg) and vehicle from P12 to P17. Retro-orbital injection of FITC-dextran was performed and retinal flat mounts were viewed by fluorescence microscopy. The Central avascular area was quantified from the digital images in a masked fashion using image analysis software (NIH ImageJ). Neovascular tufts were quantified by using SWIFT_NV and neovascular lumens were quantified from a histologic section in a masked fashion. Immunohistochemistry and Western blot analysis were also performed to demonstrate the anti-angiogenic activity of this compound in vivo. Results: In the retina of tectorigenin injected mouse (10mg/kg), the central non-perfusion area was significantly decreased compared to the vehicle injected group (1.76±0.5 mm2 vs 2.85±0.6 mm2, P<0.05). In vehicle-injected group, 33.45 ± 5.51% of the total retinal area was avascular, whereas the retinas of pups treated with high-dose (10 mg/kg) tectorigenin showed avascular retinal areas of 21.25 ±4.34% (P<0.05). High dose of tectorigenin also significantly reduced the number of vascular lumens in the histologic section. Tectorigenin (10 mg/kg) significantly reduced the expression of vascular endothelial growth factor (VEGF), matrix metalloproteinase-2 (MMP-2), MMP-9, and angiotensin II compared to the vehicle injected group. Tectorigenin did not affect CD31 abundance at any tested dose. Conclusions: Our results show that tectorigenin possesses powerful anti-angiogenic properties and can attenuate new vessel formation in the retina after systemic administration. These results imply that this compound can be considered as a candidate substance for therapeutic inhibition of retinal angiogenesis.

Keywords: tectorigenin, anti-angiogenic, retinopathy, Belamacanda chinensis

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Authors: R. Meier, M. Pander

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In accordance with the industry 4.0 concept, manufacturing process steps as well as the materials themselves are going to be more and more digitalized within the next years. The “digital twin” representing the simulated and measured dataset of the (semi-finished) product can be used to control and optimize the individual processing steps and help to reduce costs and expenditure of time in product development, manufacturing, and recycling. In the present work, two material characterization methods based on Lamb waves were evaluated and compared. For demonstration purpose, both methods were shown at a standard industrial product - copper ribbons, often used in photovoltaic modules as well as in high-current microelectronic devices. By numerical approximation of the Rayleigh-Lamb dispersion model on measured phase velocities second order elastic constants (Young’s modulus, Poisson’s ratio) were determined. Furthermore, the effective third order elastic constants were evaluated by applying elastic, “non-destructive”, mechanical stress on the samples. In this way, small microstructural variations due to mechanical preconditioning could be detected for the first time. Both methods were compared with respect to precision and inline application capabilities. Microstructure of the samples was systematically varied by mechanical loading and annealing. Changes in the elastic ultrasound transport properties were correlated with results from microstructural analysis and mechanical testing. In summary, monitoring the elastic material properties of plate-like structures using Lamb waves is valuable for inline and non-destructive material characterization and manufacturing process control. Second order elastic constants analysis is robust over wide environmental and sample conditions, whereas the effective third order elastic constants highly increase the sensitivity with respect to small microstructural changes. Both Lamb wave based characterization methods are fitting perfectly into the industry 4.0 concept.

Keywords: lamb waves, industry 4.0, process control, elasticity, acoustoelasticity, microstructure

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Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

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Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

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Authors: Yogendra Sisodia

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Researchers are becoming more interested in extracting useful information from legal documents thanks to the development of large-scale language models in natural language processing (NLP), and deep learning has accelerated the creation of powerful text mining models. Legal fields like contracts benefit greatly from semantic text search since it makes it quick and easy to find related clauses. After collecting sentence embeddings, it is relatively simple to locate sentences with a comparable meaning throughout the entire legal corpus. The author of this research investigated two pre-trained language models for this task: MiniLM and Roberta, and further fine-tuned them on Legal Contracts. The author used Multiple Negative Ranking Loss for the creation of sentence transformers. The fine-tuned language models and sentence transformers showed promising results.

Keywords: legal contracts, multiple negative ranking loss, natural language inference, sentence transformers, semantic textual similarity

Procedia PDF Downloads 108

Authors: Lunliang Zhong, Bin Duan

Abstract:

The undergraduate graduation project is a vital part of the higher education curriculum, crucial for engineering accreditation. Current evaluations often summarize data without identifying underlying issues. This study applies the Peter-Clark algorithm to analyze causal relationships within the graduation project data of an Electronics and Information Engineering program, creating a causal model. Structural equation modeling confirmed the model's validity. The analysis reveals key teaching stages affecting project success, uncovering problems in the process. Introducing causal discovery and inference into project evaluation helps identify issues and propose targeted improvement measures. The effectiveness of these measures is validated by comparing the learning outcomes of two student cohorts, stratified by confounding factors, leading to improved teaching quality.

Keywords: causal discovery, causal inference, continuous improvement, Peter-Clark algorithm, structural equation modeling

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Authors: Amina Beldjazia, Djamel Alatou, Khaled Missaoui

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The forest of Mahouna is a part of the mountain range of the Tell Atlas in the northeast of Algeria. It is characterized by a significant biodiversity. The management of this resource requires thorough the understanding of the current state of the vegetation (inventories), degradation factors and ongoing monitoring of the various long-term ecological changes. Digital mapping is a very effective way to in-depth knowledge of natural resources. The realization of a vegetation map based on satellite images, aerial photographs and the use of geographic information system (GIS), shows large values results of the vegetation of the massif in the scientific view point (the development of a database of the different formations that exist on the site, ecological conditions) and economic (GIS facilitate our task of managing the various resources and diversity of the forest). The methodology is divided into three stages: the first involves an analysis of climate data (1988 to 2013); the second is to conduct field surveys (soil and phytoecological) during the months of June and July 2013 (10 readings), the third is based on the development of different themes and synthetic cards by software of GIS (ENVI 4.6 and 10 ARCMAP). The results show: cork oak covers an area of 1147 ha. Depending on the environmental conditions, it rests on sandstone and individualizes between 3 layers of vegetation from thermo-mediterranean (the North East part with 40ha), meso-Mediterranean (1061 ha) and finally the supra-Mediterranean (46ha ). The map shows the current actual state of the cork oak forest massif of Mahouna, it is an older forest (>150 years) where regeneration is absent because of several factors (fires, overgrazing, leaching, erosion, etc.). The cork oak is in the form of dense forest with Laburnum and heather as the dominant species. It may also present in open forest dominated by scrub species: Daphne gniduim, Erica arborea, Calycotome spinosa, Phillyrea angustifolia, Lavandula stoechas, Cistus salvifolius.

Keywords: biodiversity, environmental, Mahouna, Cork oak

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Authors: Hasan Ziari, Hassan Fazaeli, Seyed Javad Vaziri Kang Olyaei, Asma Sadat Dabiri

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The presence of cracks in concrete pavements is a place for the ingression of corrosive substances, acids, oils, and water into the pavement and reduces its long-term durability and level of service. One of the causes of early cracks in concrete pavements is the plastic shrinkage. This shrinkage occurs due to the formation of negative capillary pressures after the equilibrium of the bleeding and evaporation rates at the pavement surface. These cracks form if the tensile stresses caused by the restrained shrinkage exceed the tensile strength of the concrete. Different climate conditions change the rate of evaporation and thus change the balance time of the bleeding and evaporation, which changes the severity of cracking in concrete. The present study examined the relationship between the balance time of bleeding and evaporation and the area of cracking in the concrete slabs using the standard method ASTM C1579 in 27 different environmental conditions by using continuous video recording and digital image analyzing. The results showed that as the evaporation rate increased and the balance time decreased, the crack severity significantly increased so that by reducing the balance time from the maximum value to its minimum value, the cracking area increased more than four times. It was also observed that the cracking area- balance time curve could be interpreted in three sections. An examination of these three parts showed that the combination of climate conditions has a significant effect on increasing or decreasing these two variables. The criticality of a single factor cannot cause the critical conditions of plastic cracking. By combining two mild environmental factors with a severe climate factor (in terms of surface evaporation rate), a considerable reduction in balance time and a sharp increase in cracking severity can be prevented. The results of this study showed that balance time could be an essential factor in controlling and predicting plastic shrinkage cracking in concrete pavements. It is necessary to control this factor in the case of constructing concrete pavements in different climate conditions.

Keywords: bleeding and cracking severity, concrete pavements, climate conditions, plastic shrinkage

Procedia PDF Downloads 146

Authors: Getaneh Berie Tarekegn

Abstract:

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

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Authors: Lazzat M. Zhamaliyeva, Nurgul A. Abenova, Gauhar S. Dilmagambetova, Ziyash Zh. Tanbetova, Moldir B. Ahmetzhanova, Tatyana P. Ostretcova, Aliya A. Yegemberdiyeva

Abstract:

Introduction: There are many reasons for the weak training of family doctors in Kazakhstan: the unified national educational program is not focused on competencies, the role of a general practitioner (GP) is not clear, poor funding for the health care and education system, outdated teaching and assessment methods, inefficient management. We highlight two issues in particular. Firstly, academic teachers of family medicine (FM) in Kazakhstan do not practice as family doctors; most of them are narrow specialists (pediatricians, therapists, surgeons, etc.); they usually hold one-time consultations; clinical mentors from practical healthcare (non-academic teachers) do not have the teaching competences, and the vast majority of them are also narrow specialists. Secondly, clinical sites (polyclinics) are unprepared for general practice and do not follow the principles of family medicine; residents do not like to be in primary health care (PHC) settings due to the chaos that is happening there, as well as due to the lack of the necessary equipment for mastering and consolidating practical skills. Aim: We present the concept of the family physicians’ training office (FPTO), which is being created as a friendly learning environment for young general practitioners and for the involvement of academic teachers of family medicine in the practical work and innovative development of PHC. Methodology: In developing the conceptual framework and identifying practical activities, we drew on literature and expert input, and interviews. Results: The goal of the FPTO is to create a favorable educational and clinical environment for the development of the FM residents’ competencies, in which the residents with academic teachers and clinical mentors could understand and accept the principles of family medicine, improve clinical knowledge and skills, and gain experience in improving the quality of their practice in scientific basis. Three main areas of office activity are providing primary care to the patients, improving educational services for FM residents and other medical workers, and promoting research in PHC and innovations. The office arranges for residents to see outpatients at least 50% of the time, and teachers of FM departments at least 1/4 of their working time conduct general medical appointments next to residents. Taking into account the educational and scientific workload, the number of attached population for one GP does not exceed 500 persons. The equipment of the office allows FPTO workers to perform invasive and other manipulations without being sent to other clinics. In the office, training for residents is focused on their needs and aimed at achieving the required level of competence. International methodologies and assessment tools are adapted to local conditions and evaluated for their effectiveness and acceptability. Residents and their faculty actively conduct research in the field of family medicine. Conclusions: We propose to change the learning environment in order to create teams of like-minded people, to unite residents and teachers even more for the development of family medicine. The offices will also invest resources in developing and maintaining young doctors' interest in family medicine.

Keywords: educational environment, family medicine residents, family physicians’ training office, primary care research

Procedia PDF Downloads 134