Search results for: workforce diversity learning

Authors: Kwaku Damoah

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The agricultural sector is characterized by continuous transformation, driven by factors such as demographic shifts, evolving consumer preferences, climate change, and migration trends. This dynamic environment presents complex challenges for key stakeholders including farmers, governments, and investors, who must navigate these changes to achieve optimal investment returns. To effectively predict market trends and uncover promising investment opportunities, a systematic, data-driven approach is essential. This paper introduces the Structural Evolution Index (SEI), a machine learning-based methodology. SEI is specifically designed to analyse long-term trends and forecast the potential of emerging agricultural products for investment. Versatile in application, it evaluates various agricultural metrics such as production, yield, trade, land use, and consumption, providing a comprehensive view of the evolution within agricultural markets. By harnessing data from the UN Food and Agricultural Organisation (FAOSTAT), this study demonstrates the SEI's capabilities through Comparative Exploratory Analysis and evaluation of international trade in agricultural products, focusing on Malaysia and Singapore. The SEI methodology reveals intricate patterns and transitions within the agricultural sector, enabling stakeholders to strategically identify and capitalize on emerging markets. This predictive framework is a powerful tool for decision-makers, offering crucial insights that help anticipate market shifts and align investments with anticipated returns.

Keywords: agricultural investment, algorithm, comparative exploratory analytics, machine learning, market trends, predictive analytics, structural evolution index

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Authors: Atitallah Sofien, Bouyahia Olfa, Mohsen S., Boussetta Khadija, Khemiri Monia, Fitouri Zohra, Boukthir Samir

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Introduction: Megaloblastic anemia (MA) is rare in children. The diversity of its etiologies can lead to misdiagnosis and may, therefore, delay the treatment. The aim of this study was to describe the epidemiological and etiological characteristics of children followed for MA at the Tunis children's hospital. Methodology: This is a retrospective study over a period of 25 years of all cases of MA in children in the Children's Hospital of Tunis. The diagnosis of MA was confirmed by myelogram in all patients. Results: We collected 29 observations, with an incidence of 1.2 cases/year and a sex ratio of 1. Sixty percent of the children were aged between 3 months and 2 years. The consultation time was between 15 and 30 days in a third of the patients. The clinical examination showed hypotrophy in 13% of cases, hepatosplenomegaly in 6% of cases, neurological or neurosensory damage in 23% of cases, and cardiac damage in 10% of children. MA was associated with thrombocytopenia in 65% of cases and leukoneutropenia in 24% of cases. One in 5 children had pancytopenia. The etiologies were mainly thiamine deficiency, Immerslund disease (20%), nutritional deficiency (13%), and Biermer anemia (13%). One of the patients presented an MA revealing visceral leishmaniasis. The outcome under vitamin B12, the dose of which was adapted to each etiology, was favorable for all patients. Conclusion: MA is rare in children with multiple etiologies that are mainly dominated by hereditary conditions and nutritional deficiencies, mainly in vitamin B12. The association with visceral leishmaniasis seems to be a particularity in our country not reported in the literature.

Keywords: megaloblastic anemia, children, vitamin B12, anemia

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Authors: Franciele G. Esteves, Jose R. A. dos Santos-Pinto, Caroline L. de Souza, Mario S. Palma

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Orb-weaving spiders use a very strong, stickiness, and elastic web to catch the prey. These web properties would be enough for the entrapment of prey; however, these spiders may be hiding venomous secrets on the web, which are being revealed now. Here we provide strong proteome, peptidome, and transcriptomic evidence for the presence of toxic components on the web silk from Nephila clavipes. Our scientific outcomes revealed, both in the web silk and in the silk-producing glands, a wide diversity of toxins/neurotoxins, defensins, and proteolytic enzymes. These toxins/neurotoxins are similar to toxins isolated from animal venoms, such as Sphigomyelinase D, Latrotoxins, Zodatoxins, Ctenitoxin Pn and Pk, Agatoxins and Theraphotoxin. Moreover, the insect-toxicity results with the web silk crude extract demonstrated that these toxic components can be lethal and/or cause paralytic effects to the prey. Therefore, through OMICs approaches, the results presented until now may contribute to a better understanding of the chemical and ecological interaction of these compounds in insect-prey capture by spider web N. clavipes, demonstrating that the web is not only a simple mechanical tool but has a chemical-active involvement in prey capture. Moreover, the results can also contribute to future studies of possible development of a selective insecticide or even in possible pharmacological applications.

Keywords: web silk toxins, silk-produncing glands, de novo transcriptome assembly, LCMS-based proteomics

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Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

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Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

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Authors: Mirriam M. Moleko, Sekanse A. Ntsala

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Language in mathematics instruction enables the teacher to communicate mathematical knowledge to the learners with precision. It also enables the learner to deal with mathematical activities effectively. This scholarly piece was motivated by the fact that mathematics performance in the South African primary classrooms has not been satisfactory, and English, which is a Language of Learning and Teaching (LoLT) for the majority of the learners, has been singled out as one of the major impediments. This is not only on the part of the learners, but also on the part of the teachers as well. The study thus focused on the lack of competency in English among the primary school teachers as one of the possible causes of poor performance in mathematics in primary classrooms. The qualitative processes, which were premised on the social interaction theory as a lens, sourced the narratives of 10 newly qualified primary school mathematics teachers from the disadvantaged schools on the matter. This was achieved through the use of semi-structured interviews and focus group discussions. The data, which were analyzed thematically, highlighted the actuality that the challenges cut across the pre-service stage to the in-service stage. The findings revealed that the undergraduate mathematics courses in the number of the institutions neglect the importance of language. The study further revealed that the in-service mathematics teachers lack adequate linguistic command, thereby finding it difficult to successfully teach some mathematical concepts, or even to outline instructions clearly. The study thus suggests the need for training institutions to focus on improving the teachers’ English language competency. The need for intensive in-service training targeting the problem areas was also highlighted. The study thus contributes to the body of knowledge by providing suggestions on how the mathematics teachers’ language incompetency can be mitigated.

Keywords: Competency, English language proficiency, language of learning and teaching, primary mathematics teachers

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Authors: Huda Zakaria

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The concept of the glass ceiling persists as a barrier to women's advancement in leadership roles, shaped significantly by organizational culture and climate. This study examines the impact of organizational culture on advancing women to top leadership roles in the Egyptian banking sector. The research explores how varying organizational cultures and climates either facilitate or hinder women's progress in breaking through the glass ceiling. Data suggests that women are underrepresented in senior management positions globally, including in Egypt, indicating a barrier to their advancement. Organizational norms often align more with masculine traits, creating challenges for women in leadership. Stereotypes and biases affect how women are treated, leading to limited advancement opportunities and a lack of sponsors advocating for their skills. Female managers also exhibit lower levels of career confidence compared to male counterparts. To address these issues, organizations must tackle cultural biases and provide equal opportunities to promote genuine gender diversity and empower women in leadership roles. Understanding the impact of organizational culture is crucial for creating inclusive workplaces that foster gender equality and provide equal opportunities for women to succeed in leadership roles.

Keywords: glass ceiling, leadership, banking, bias

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Authors: Alfred Chen, Cheng Chieh Hsu, Yu-Pin Ma, Meng-Jie Lin, Fu Pai Chiu, Yi-Yan Sie

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This study is attempted to construct a human-computer interactive platform system that has mainly consisted of an augmented hardware system, a software system, a display table, and mixed media. This system has provided with human-computer interaction services through an interactive platform for the tourism industry. A well designed interactive platform, integrating of augmented reality and mixed media, has potential to enhance museum display quality and diversity. Besides, it will create a comprehensive and creative display mode for most museums and historical heritages. Therefore, it is essential to let public understand what the platform is, how it functions, and most importantly how one builds an interactive augmented platform. Hence the authors try to elaborate the construction process of the platform in detail. Thus, there are three issues to be considered, i.e.1) the theory and application of augmented reality, 2) the hardware and software applied, and 3) the mixed media presented. In order to describe how the platform works, Courtesy Door of Tainan Confucius Temple has been selected as case study in this study. As a result, a developed interactive platform has been presented by showing the physical entity object, along with virtual mixing media such as text, images, animation, and video. This platform will result in providing diversified and effective information that will be delivered to the users.

Keywords: human-computer interaction, mixed reality, mixed media, tourism

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Authors: D. P. Lawrence, T. M. M. D. Ariyarathna, W. N. K. De Silva, M. D. S. C. De Silva, Lasantha Abeysiri, Pradeep Abeygunawardhna

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Safari traveling is one of the most famous hobbies all over the world. In Sri Lanka, 'Yala' is the second-largest national park, which is a better place to go for a safari. Many number of local and foreign travelers are coming to go for a safari in 'Yala'. But 'Yala' does not have a mobile application that is made to facilitate the traveler with some important features that the traveler wants to achieve in the safari experience. To overcome these difficulties, the proposed mobile application by adding those identified features to make travelers, guiders, and administration's works easier. The proposed safari traveling guidance mobile application is called 'SMART SAFARI' for the 'Yala' National Park in Sri Lanka. There are four facilities in this mobile application that provide for travelers as well as the guiders. As the first facility, the guider and traveler can view the created map of the park, and the guider can add temporary locations of animals and special locations on the map. This is a Geographic Information System (GIS) to capture, analyze, and display geographical data. And as the second facility is to generate optimal paths according to the travelers' requirements through the park by using machine learning techniques. In the third part, the traveler can get information about animals using an animal identification system by capturing the animal. As in the other facility, the traveler will be facilitated to add reviews and a rate and view those comments under categorized sections and pre-defined score range. With those facilities, this user-friendly mobile application provides the user to get a better experience in safari traveling, and it will probably help to develop tourism culture in Sri Lanka.

Keywords: animal identification system, geographic information system, machine learning techniques, pre defined score range

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Authors: A. Javorova, M. Matusova, K. Velisek

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The article summarizes the experience of laboratory technical subjects teaching methodologies using a number of software products. The main aim is to modernize the teaching process in accordance with the requirements of today - based on information technology. Increasing of the study attractiveness and effectiveness is due to the introduction of CA technologies in the learning process. This paper discussed the areas where individual CA system used. Environment using CA systems are briefly presented in each chapter.

Keywords: education, CA systems, simulation, technology

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Authors: Munruchi Kaur

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Agarics are the fruiting bodies of the fungi falling under Phylum Basidiomycota of class Agaricomycetes. North Western parts of India which comprises of mighty Himalayas decorated with snow cap mountains, forested areas, grassland and the Gangetic plains with the altitude varying between 196m to 3600m have a huge potential of naturally growing wild agarics. These mushrooms lavishly grow in wet humid weather conditions that prevail in these parts of India during the monsoon which hits in the early June and continue up to mid-October. In this area, a diverse form of mixed vegetation is available which is represented by coniferous and angiospermic trees, shrubs, herbs, epiphytes, parasites, climbers etc. The vegetation, topography and climate of this area is quite favorable for the growth of agarics. Cedrus deodara, Pinus longifolia, P. roxburghii, P. wallichiana, Abies pindrow, A. spectabilis, Picea smithiana, Taxus sp., Rhododendron sp. and Quercus sp. occur in pure formations or as scattered patches or as mixed forests, whereas the Gangetic plains are dominated by the angiospermic trees and shrubs, they commonly occur along roadsides or in conserved areas or are the avenues plantations, common amongst these are Shorea robusta, Dalbergia sissoo, Melia azadirachta, Acacia sp., Ficus benghalensis, Eucalyptus sp. and Butea monosperma. These agarics can be categorized on the basis of the habitat in which they grow they are usually foliocolous, lignicolous, humicolous, coprophilous or termitophilous. A number of fungal forays were undertaken to different parts of North West India from time to time during the monsoon season with an aim to decipher the agarics diversity of this part of India. Along with collecting the various agarics from diverse habitat, the ethnomycological data was also collected along with by interacting with the local inhabitants of those areas. Based upon the ethnomycological data collected over the years, cataloging of the edible and inedible agarics has been done and cultures of such potential edible agarics were raised with an aim to domesticate these selected taxa. With an aim to reduce the local pressure on these natural resources, a low-cost technology was developed to make it available to the public for cultivation. As a result, 104 taxa were found edible such as Amanita hemibapha var. ochracea, A. chepangiana, A. banningiana, A. vaginata, Agrocybe parasitica, Author: Professor & Dean Faculty of Life Sciences Punjabi University, Patiala. Punjab, India [email protected] Agaricus bisporus, A. andrewii, A. campestris var. campestris, A. silvicola, A. subrutilescens, A. bernardii, A. abruptibulbus, A. fuscovelatus, A. brunnescens, A. augustus, A. silvaticus, A. arvensis, Volvariella bakeri, V. terastia, V. bombycina, V. diplasia, Psathyrella candolleana, Volvopluteus gloiocephalus, Russula cyanoxantha, R. atropurpurea, R. aurea, Clitocybe gibba,Lentinus transitus, L. kashmirinus, L. crinitus, L. ligrinus, Lactarius rubrilacteus, Pleurotus sapidus, Pluteus subcervinus, Macrocybe gigantea, etc. Cultures of various taxa viz. Pleurotus sajor-caju, Macrocybe gigantea, Pluteus petasatus and Lentinus tigrinus were raised and a proper protocol for the domestication of Pleurotus sajor-caju, Macrocybe gigantea, and Lentinus tigrinus has been developed using the locally available agro-wastes.

Keywords: Agaric, culture, domestication, edible

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Authors: Po-Ting Chen, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

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Classical molecular dynamics (CMD) simulations are highly efficient for material simulations but have limited accuracy. In contrast, ab initio molecular dynamics (AIMD) provides high precision by solving the Kohn–Sham equations yet requires significant computational resources, restricting the size of systems and time scales that can be simulated. To address these challenges, we employed NequIP, a machine learning model based on an E(3)-equivariant graph neural network, to accelerate molecular dynamics simulations of a 1M LiPF6 in EC/EMC (v/v 3:7) for Li battery applications. AIMD calculations were initially conducted using the Vienna Ab initio Simulation Package (VASP) to generate highly accurate atomic positions, forces, and energies. This data was then used to train the NequIP model, which efficiently learns from the provided data. NequIP achieved AIMD-level accuracy with significantly less training data. After training, NequIP was integrated into the LAMMPS software to enable molecular dynamics simulations of larger systems over longer time scales. This method overcomes the computational limitations of AIMD while improving the accuracy limitations of CMD, providing an efficient and precise computational framework. This study showcases NequIP’s applicability to electrolyte systems, particularly for simulating the dynamics of LiPF6 ionic mixtures. The results demonstrate substantial improvements in both computational efficiency and simulation accuracy, highlighting the potential of machine learning models to enhance molecular dynamics simulations.

Keywords: lithium-ion batteries, electrolyte simulation, molecular dynamics, neural network

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Authors: Bussabamintra Chalauisaeng

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The creative writing skill of Thai fourth year university learners majoring in English at Khon Kaen University, Thailand has been enhanced in an English creative writing course through the implementation of creative thinking process. The creative writing assignments cover writing a variety of short poems and a short story, bibliography and short play scripts. However, this study focuses mainly on writing short poems and short stories through the implementation of creative thinking process via action research design with on-going needs analysis and feedbacks to meet their learning needs for 45 hours. At the end of the course, forty two learners’ creative writing skill appeared to be significantly improved. Through the research instruments such as the tasks assigned both inside and outside the class as self –study including class observation, semi-conversational interviews and teacher feedback both in persons and on line including peer feedbacks. The research findings show that the target learners could produce better short poems and short story assessed by the set of criteria such as the creative and innovative short poems and short stories with complete and interesting elements of a short story like plot, theme, setting, symbolism and so on. This includes a higher level of the awareness of the pragmatic use of English writing in terms of word choices, grammar rules and writing styles. All of these outcomes reflect positive trends of success in terms of the learners’ improved creative writing skill as well as better attitudes to and motivation for learning to write English for pleasure. More interestingly, many learners claimed that this innovative teaching method through the implementation of creative thinking process integrated with creative writing help stretch their imaginations and inspire them to become a writer in the future.

Keywords: creative thinking process, creative writing skill, enhancing, implementing

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Authors: Neha Toppo

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Plans and programs for successful secondary education are incomplete without the inclusion of teaching English as an important area. Even after sixteen years of the formation of Jharkhand as a separate state, the students are still struggling to achieve quality education of English. This paper intends to account the present condition of teaching English in Jharkhand board secondary level schools through discussion on various issues of English language teaching, language need and learning challenges of its students. The study is to analyze whether the learning environment, teaching methods and materials, teaching resources, goals of language curriculum are appropriately convincing for the students of the board or require to be reanalyzed and also to provide appropriate suggestions for improvement. Immediate attention must be drawn towards the problem for benefitting those students, who despite their knowledge and talent are lagging behind in numerous fields only due to the lack of proficiency in English. The data and discussion provided are on the basis of a survey, in which semi structured interview with teachers, students and administrators in several schools including both rural and urban area has been taken. Questionnaire, observation and testing were used as important tools. The survey has been conducted in Ranchi district, as it covers large geographical area which includes number of villages and at the same time several towns. The district primarily possesses tribes as well as different class of people including immigrants from all over and outside Jharkhand with their social, economical strata. The observation makes it clear that the English language teaching at the state board is not complementing its context and the whole language teaching system should be re-examined to establish learner oriented environment.

Keywords: material, method, secondary level, teaching resources

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Authors: Syahidah N. Zulkifli, Herlina A. Rahim, Nurul A. M. Subha

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Sustaining water quality is critical in order to avoid any harmful health consequences for end-user consumers. The detection of microbial impurities at the household level is the foundation of water security. Water quality is now monitored only at water utilities or infrastructure, such as water treatment facilities or reservoirs. This research provides a first-hand scientific understanding of microbial composition presence in Malaysia’s household point-of-use (POUs) water supply influenced by seasonal fluctuations, standstill periods, and flow dynamics by using the NIR-Raman spectroscopic technique. According to the findings, 20% of water samples were contaminated by pathogenic bacteria, which are Legionella and Salmonella cells. A comparison of the spectra reveals significant signature peaks (420 cm⁻¹ to 1800 cm⁻¹), including species-specific bands. This demonstrates the importance of regularly monitoring POUs water quality to provide a safe and clean water supply to homeowners. Conventional Raman spectroscopy, up-to-date, is no longer suited for real-time monitoring. Therefore, this study introduced an alternative micro-spectrometer to give a rapid and sustainable way of monitoring POUs water quality. Assessing microbiological threats in water supply becomes more reliable and efficient by leveraging IoT protocol.

Keywords: microbial contaminants, water quality, water monitoring, Raman spectroscopy

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Authors: Khadija Rafi, Neha Jamil, Laiba Khalid, Meerub Nawaz, Mahwish Farooq

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Speech articulation is a complex process to produce intelligible sounds with the help of precise movements of various structures within the vocal tract. All these structures in the vocal tract are named as articulators, which comprise lips, teeth, tongue, and palate. These articulators work together to produce a range of distinct phonemes, which happen to be the basis of language. It starts with the airstream from the lungs passing through the trachea and into oral and nasal cavities. When the air passes through the mouth, the tongue and the muscles around it form such coordination it creates certain sounds. It can be seen when the tongue is placed in different positions- sometimes near the alveolar ridge, soft palate, roof of the mouth or the back of the teeth which end up creating unique qualities of each phoneme. We can articulate vowels with open vocal tracts, but the height and position of the tongue is different every time depending upon each vowel, while consonants can be pronounced when we create obstructions in the airflow. For instance, the alphabet ‘b’ is a plosive and can be produced only by briefly closing the lips. Articulation disorders can not only affect communication but can also be a hurdle in speech production. To improve articulation skills for such individuals, doctors often recommend speech therapy, which involves various kinds of exercises like jaw exercises and tongue twisters. However, this disorder is more common in children who are going through developmental articulation issues right after birth, but in adults, it can be caused by injury, neurological conditions, or other speech-related disorders. In short, speech articulation is an essential aspect of productive communication, which also includes coordination of the specific articulators to produce different intelligible sounds, which are a vital part of spoken language.

Keywords: linguistics, speech articulation, speech therapy, language learning

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Authors: Yathreb Sabsaby

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Energy efficiency retrofitting of existing buildings was long ignored by public authorities who favored energy efficiency policies in new buildings, which are easier to implement. Indeed, retrofitting is more complex and difficult to organize because of the extreme diversity in existing buildings, administrative situations and occupation. Energy efficiency retrofitting of existing buildings has now become indispensable in all economies—even emerging countries—given the constraints imposed by energy security and climate change, and because it represents considerable potential energy savings. Addressing energy efficiency in the existing building stock has been acknowledged as one of the most critical yet challenging aspects of reducing our environmental footprint on the ecosystem. Tripoli, Lebanon chosen as case study area is a typical Mediterranean metropolis in the North Lebanon, where multifamily residential buildings are all around the city. This generally implies that the density of energy demand is extremely high, even the renewable energy facilities are involved, they can just play as a minor energy provider at the current technology level in the single family house. It seems only the low energy design for buildings can be made possible, not the zero energy certainly in developing country. This study reviews the latest research and experience and provides recommendations for deep energy retrofits that aim to save more than 50% of the energy used in a typical Tripoli apartment building.

Keywords: energy-efficiency, existing building, multifamily residential building, retrofit

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Authors: Nuno Biga

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Artificial Intelligence (AI) has the potential to transform management into several impactful ways. It allows machines to interpret information to find patterns in big data and learn from context analysis, optimize operations, make predictions sensitive to each specific situation and support data-driven decision making. The introduction of an 'artificial brain' in organization also enables learning through complex information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) sensitive to context, that provides users useful suggestions to pursue the following operations such as: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time existing bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed and demonstrated through a pilot project (BIG-AI). Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of data is powered in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" (VA) that players can use during the Game. Each participant in the VA permanently asks himself about the decisions he should make during the game to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making, through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, as they gain a better understanding of the issues along time, reflect on good practice and rely on their own experience, capability and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator designated as “Serious Game Controller” (SGC) is responsible for supporting the players with further analysis. The recommended actions by the SGC may differ or be similar to the ones previously provided by the VA, ensuring a higher degree of robustness in decision-making. Additionally, all the information should be jointly analyzed and assessed by each player, who are expected to add “Emotional Intelligence”, an essential component absent from the machine learning process.

Keywords: artificial intelligence, gamification, key performance indicators, machine learning, management simulators, serious games, virtual assistant

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Authors: Omer Shujat Bhatti, Afshan Huma

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Online educational system were considered a great opportunity for distance learning. In recent days of COVID19 pandemic, it enable the continuation of educational activities at all levels of education, from primary school to the top level universities. One of the key considered element in supporting the online educational system is video lectures. The current research explored the usefulness of the video lectures delivered to technical students of masters level with a focus on MSc Sustainable Environmental design students who have diverse backgrounds in the formal educational system. Hence they were unable to cope right away with the online system and faced communication and understanding issues in the lecture session due to internet and allied connectivity issues. Researcher used self prepared video lectures for respective subjects and provided them to the students using Youtube channel and subject based Whatsapp groups. Later, students were asked about the usefulness of the lectures towards a better understanding of the subject and an overall enhanced learning experience. More than 80% of the students appreciated the effort and requested it to be part of the overall system. Data collection was done using an online questionnaire which was prior briefed to the students with the purpose of research. It was concluded that video lectures should be considered an integral part of the lecture sessions and must be provided prior to the lecture session, ensuring a better quality of delivery. It was also recommended that the existing system must be upgraded to support the availability of these video lectures through the portal. Teachers training must be provided to help develop quality video content ensuring that is able to cover the content and courses taught.

Keywords: video lectures, online distance education, synchronous instruction, asynchronous communication

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Authors: Mary Cheptanui Sambu

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Teaching practice is an integral component of students who are training to be teachers, as it provides them with an opportunity to gain experience in an actual teaching and learning environment. This study explored the experiences of trainee teachers from a local university in Kenya, undergoing a three-month teaching practice in Special Secondary schools in the country. The main aim of the study was to understand the trainees’ experiences, their expectations, and the realities encountered during the teaching practice period. The study focused on special secondary schools for learners with hearing impairment. A descriptive survey design was employed and a sample size of forty-four respondents from special secondary schools for learners with hearing impairment was purposively selected. A questionnaire was administered to the respondents and the data obtained analysed using the Statistical Package for the Social Sciences (SPSS). Preliminary analysis shows that challenges facing special secondary schools include inadequate teaching and learning facilities and resources, low academic performance among learners with hearing impairment, an overloaded curriculum and inadequate number of teachers for the learners. The study findings suggest that the Kenyan government should invest more in the education of special needs children, particularly focusing on increasing the number of trained teachers. In addition, the education curriculum offered in special secondary schools should be tailored towards the needs and interest of learners. These research findings will be useful to policymakers and curriculum developers, and will provide information that can be used to enhance the education of learners with hearing impairment; this will lead to improved academic performance, consequently resulting in better transitions and the realization of Vision 2030.

Keywords: hearing impairment, special secondary schools, trainee, teaching practice

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Authors: Vanaja T., Sravya P. K.

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Cooking and eating qualities have major roles in determining the quality characteristics of rice. Traditional rice varieties are highly diversified with each other with respect to unique nutrient, cooking, and eating characteristics, which can be used as parents for the development of high-quality varieties. In order to gather vital information for upcoming rice breeding programs, a study was conducted to assess the diversity of the cooking attributes and sensory evaluation of 28 traditional rice genotypes of Kerala, India, conserved at Regional Agricultural Research Station, Pilicode of Kerala Agricultural University. The cultivars ‘Kochuvithu’, ‘Jeerakachamba’, and ‘Rajameni’ exhibited the highest volume expansion ratio. The highest Kernel elongation ratio was recorded for ‘Gandhakasala’, ‘Rajameni’, and ‘Avadi’. A shorter cooking time based on Alkali spread value was shown by the cultivars ‘Kozhivalan’, ‘Kunhikayama’, ‘Rasagadham’, ‘Jadathi’, ‘Japanviolet’, ‘Nooravella’, ‘Punchavella’, ‘Avadi’, ‘Vadakan vellarikayama’, ‘Punchaparuthi’, ‘Shyamala’, ‘China Silk’, ‘Marathondi’, and ‘Gandhakasala’. Sensory evaluation revealed that the cultivars ‘Japanviolet’, ‘Kunhukunhu’, and ‘Kalladiyaran’ can be categorized under moderate to very much.

Keywords: rice, traditional rice varieties, cooking qualities, sensory evaluation, consumer acceptance

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Abdu Qayyum, Hafiz Muhammad Saeed, Mamoona Hanif, Etrat Noor, Waqas Malik, Shoaib Liaqat

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Salinity is extremely serious problem that has a drastic effect on maize crop, environment and causes economic losses of country. An advance technique to overcome salinity is to develop salt tolerant geno types which require screening of huge germ plasm to start a breeding program. Therefore, present study was undertaken to screen out 25 maize hybrids of different origin for salinity tolerance at seedling stage under three levels of salt stress 250 and 300 mM NaCl including one control. The existence of variation for tolerance to enhanced NaCl salinity levels at seedling stage in maize proved that hybrids had differing ability to grow under saline environment and potential variability within specie. Almost all the twenty five maize hybrids behaved varyingly in response to different salinity levels. However, the maize hybrids H6, H13, H21, H23 and H24 expressed better performance under salt stress in terms of all six characters and proved to be as highly tolerant while H22, H17 H20, H18, H4, H9, and H8 were identified as moderately tolerant. Hybrids H14, H5, H11 and H3 H12, H2, were expressed as most sensitive to salinity suggesting that screening is an effective tool to exploit genetic variation among maize hybrids and salt tolerance in maize can be enhanced through selection and breeding procedure.

Keywords: salinity, hybrids, maize, variation

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Authors: Deyadeen Ali Alshibani

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In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

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Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

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Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

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Authors: Hiba Mezaache

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The current study aimed to know the impact of using information and communication technology on the process of re-engineering small and medium enterprises, as the world witnessed the speed development of the latter in its field of work and the diversity of its objectives and programs, that also made its process important for the growth and development of the institution and also gaining the flexibility to face the changes that may occur in the environment of work, so in order to know the impact of information and communication technology on the success of this process, we prepared an electronic questionnaire that included (70) items, and we also used the SPSS statistical calendar to analyze the data obtained. In the end of our study, our conclusion was that there was a positive correlation between the four dimensions of information and communication technology, i.e., hardware and equipment, software, communication networks, databases, and the re-engineering process, in addition to the fact that the studied institutions attach great importance to formal communication, for its positive advantages that it achieves in reducing time and effort and costs in performing the business. We could also say that communication technology contributes to the process of formulating objectives related to the re-engineering strategy. Finally, we recommend the necessity of empowering workers to use information technology and communication more in enterprises, and to integrate them more into the activity of the enterprise by involving them in the decision-making process, and also to keep pace with the development in the field of software, hardware, and technological equipment.

Keywords: information and communication technology, re-engineering, small and medium enterprises, the impact

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Authors: Tamar Lazariashvili

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Introduction: The growth and development of the economy in the country depend on many factors, the most important of which is the use of innovation. The article analyzes the innovations and the potential of agricultural development in Georgia, presents the problems in the field, justifies the need to introduce innovations, shows the policy of innovation development, evaluates the positive and negative factors of the use of innovations in agriculture. Methodology: The article uses general and specific research methods, namely, analysis, synthesis, induction, deduction, comparison and statistical ones: selection, grouping, observation, trend. All these methods used together in the article reveal the main problems and challenges and their development trends. Main Findings: The introduction of innovations for the country has an impact if there is established state support system for business development and the State creates an effective environment for innovation development. As a result, the appropriate establishment gives incentives to increase budget revenues, create new jobs, increase export turnover and improve the overall economic situation in the country. Georgia has sufficient resource potential to create and develop new businesses in agriculture by introducing innovations and contribute to the further socio-economic development of the country. Political and economic stability, the existing legislation in the country, infrastructure, the proper functioning of financial institutions and the qualification of the workforce are crucial for the development of innovations. These criteria determine the political and economic ratings of all countries of the world, which are of great importance to foreign investors in the implementation of innovations. Conclusion: Enactment of agro-insurance will increase the interest and confidence of financial institutions in the farming sector, financial resources will be accessible to the farmers that will facilitate the stable development of the sector in the country. The size of the agro-insurance market in the country should be increased and the new territories should be covered. The State must have an obligation to ensure the risk of farmers and subsidize insurance companies. Based on an analysis of the insurance market the conclusions on agro-insurance issues and the relevant recommendations are proposed. The introduction of innovations in agriculture will have a great impact on the Georgian economy: it will improve the technological base, establish enterprises equipped with modern equipment and methodologies, retrain existing enterprises, promote to improve skills of workers and improve management systems. Based on the analysis, conclusions are made about the prospects for the development of innovation in agriculture and relevant recommendations are proposed.

Keywords: agriculture, development potential, innovation, optimal environment

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Authors: Sergio Andres Rojas, Julian Benavides Franco, Juan Tomas Sayago

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An increasing amount of research demonstrates how market mood affects financial markets, but their primary goal is to demonstrate how Trump's tweets impacted US interest rate volatility. Following that lead, this work evaluates the effect that Trump's tweets had during his presidency on local and international stock markets, considering not just volatility but the direction of the movement. Three indexes for Trump's tweets were created relating his activity with movements in the S&P500 using natural language analysis and machine learning algorithms. The indexes consider Trump's tweet activity and the positive or negative market sentiment they might inspire. The first explores the relationship between tweets generating negative movements in the S&P500; the second explores positive movements, while the third explores the difference between up and down movements. A pseudo-investment strategy using the indexes produced statistically significant above-average abnormal returns. The findings also showed that the pseudo strategy generated a higher return in the local market if applied to intraday data. However, only a negative market sentiment caused this effect on daily data. These results suggest that the market reacted primarily to a negative idea reflected in the negative index. In the international market, it is not possible to identify a pervasive effect. A rolling window regression model was also performed. The result shows that the impact on the local and international markets is heterogeneous, time-changing, and differentiated for the market sentiment. However, the negative sentiment was more prone to have a significant correlation most of the time.

Keywords: market sentiment, Twitter market sentiment, machine learning, natural dialect analysis

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Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Martina I. Reinhold, Theresa Bacon-Baguley

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A core challenge of physician assistant education is preparing professionals for lifelong learning. While this conventionally has encompassed scientific advances, students must also embrace new care delivery models and technologies. Telemedicine, the provision of care via two-way audio and video, is an example of a technological advance reforming health care. During a three-semester sequence of Hospital Community Experiences, physician assistant students were assigned experiences with Answer Health on Demand, a telemedicine collaborative. Preceding the experiences, the agency lectured on the application of telemedicine. Students were then introduced to the technology and partnered with a provider. Prior to observing the patient-provider interaction, patient consent was obtained. Afterwards, students completed a reflection paper on lessons learned and the potential impact of telemedicine on their careers. Thematic analysis was completed on the students’ reflection papers (n=13). Preceding the lecture and experience, over 75% of students (10/13) were unaware of telemedicine. Several stated they were 'skeptical' about the effectiveness of 'impersonal' health care appointments. After the experience, all students remarked that telemedicine will play a large role in the future of healthcare and will provide benefits by improving access in rural areas, decreasing wait time, and saving cost. More importantly, 30% of students (4/13) commented that telemedicine is a technology they can see themselves using in their future practice. Initial results indicate that collaborative interaction between students and telemedicine providers enhanced student learning and exposed students to technological advances in the delivery of care. Further, results indicate that students perceived telemedicine more favorably as a viable delivery method after the experience.

Keywords: collaboration, physician assistant education, teaching innovative health care delivery method, telemedicine

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Authors: Emilie Zimet

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During our department meetings for teachers of children with learning disabilities and difficulties, we often discuss the best practices for supporting students who come to school with literacy difficulties. After completing Sounds Write and Writing Revolution courses, it seems there is a possibility to link approaches and still maintain fidelity to a program and provide individualised instruction to support students with such difficulties and disabilities. In this case study, the researcher has been focussing on how best to use the knowledge acquired to provide quality intervention that targets the varied areas of challenge that students require support in. Students present to school with a variety of co-occurring reading and writing deficits and with complementary approaches, such as The Writing Revolution and Sounds Write, it is possible to support students to improve their fundamental skills in these key areas. Over the next twelve weeks, the researcher will collect data on current students with whom this approach will be trialled and then compare growth with students from last year who received support using Sounds-Write only. Maintaining fidelity may be a potential challenge as each approach has been tested in a specific format for best results. The aim of this study is to determine if approaches can be combined, so the implementation will need to incorporate elements of both reading (from Sounds Write) and writing (from The Writing Revolution). A further challenge is the time length of each session (25 minutes), so the researcher will need to be creative in the use of time to ensure both writing and reading are targeted while ensuring the programs are implemented. The implementation will be documented using student work samples and planning documents. This work will include a display of findings using student learning samples to demonstrate the importance of co-targeting the reading and writing challenges students come to school with.

Keywords: literacy difficulties, intervention, individual differences, methods of provision

Procedia PDF Downloads 54