Search results for: ubiquitous learning environment scaffolding

Authors: Wabinyai Fidel Raja, Gideon Lubisa

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Air pollution is becoming a growing concern in Africa due to rapid industrialization and urbanization, leading to implications for public health and the environment. Establishing a comprehensive air quality monitoring network is crucial to combat this issue. However, conventional methods of monitoring are insufficient in African cities due to the high cost of setup and maintenance. To address this, low-cost sensors (LCS) can be deployed in various urban areas through the use of participatory air quality network siting (PAQNS). PAQNS involves stakeholders from the community, local government, and private sector working together to determine the most appropriate locations for air quality monitoring stations. This approach improves the accuracy and representativeness of air quality monitoring data, engages and empowers community members, and reflects the actual exposure of the population. Implementing PAQNS in African cities can build trust, promote accountability, and increase transparency in the air quality management process. However, challenges to implementing this approach must be addressed. Nonetheless, improving air quality is essential for protecting public health and promoting a sustainable environment. Implementing participatory and data-informed air quality monitoring can take a significant step toward achieving these important goals in African cities and beyond.

Keywords: low-cost sensors, participatory air quality network siting, air pollution, air quality management

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Authors: Elias Kodjo Kekesi

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This study seeks to investigate a critical but neglected area in disaster and emergency management in Ghana. It explores aspects of work within one of the safety-critical work environments that expose workers to psychological, social and physical harm. With much attention to crises’ survivors, deceased and their families, this research attempts to answer a key question: ‘What happens to the rescuer’? Emergency response is associated with immense and unprecedented pressure that puts responders’ physical, mental and social well-being at risk. Despite the negative psychological outcomes, scholars argue that being in a traumatic situation may trigger positive outcomes for some people. Thus, the study also focuses on the positive impact of working in a risky crisis environment. Additionally, people’s interpretation of negative experiences or exposure to adverse conditions differ owing to their personal resources which explains why some people may be negatively affected whiles others are positively impacted. To examine these complex nuances, an exploratory sequential mixed method design is adopted. This paper will highlight the findings of study one, which explores the underlying themes emerging from the Ghanaian disaster and emergency response environment regarding psychosocial hazard exposures and the corresponding outcomes.

Keywords: psychosocial hazards, organisational outcomes, qualitative research, Ghana

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Authors: Tarek Dandashi

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WSNs may provide a fast and reliable solution for the early detection of environment events like forest fires. This is crucial for alerting and calling for fire brigade intervention. Sensor nodes communicate sensor data to a host station, which enables a global analysis and the generation of a reliable decision on a potential fire and its location. A WSN with TinyOS and nesC for the capturing and transmission of a variety of sensor information with controlled source, data rates, duration, and the records/displaying activity traces is presented. We propose a similarity distance (SD) between the distribution of currently sensed data and that of a reference. At any given time, a fire causes diverging opinions in the reported data, which alters the usual data distribution. Basically, SD consists of a metric on the Cumulative Distribution Function (CDF). SD is designed to be invariant versus day-to-day changes of temperature, changes due to the surrounding environment, and normal changes in weather, which preserve the data locality. Evaluation shows that SD sensitivity is quadratic versus an increase in sensor node temperature for a group of sensors of different sizes and neighborhood. Simulation of fire spreading when ignition is placed at random locations with some wind speed shows that SD takes a few minutes to reliably detect fires and locate them. We also discuss the case of false negative and false positive and their impact on the decision reliability.

Keywords: forest fire, WSN, wireless sensor network, algortihm

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Authors: Aboubakr Mashali

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Context: The paper focuses on the relationship between architecture and nature, emphasizing the importance of incorporating natural elements in design to reconnect individuals with the natural environment. It highlights the positive impact of a harmonious architecture on people's well-being and the environment, as well as the concept of sustainable architecture. Research aim: The aim of this research is to showcase how nature can be integrated into architectural designs, ultimately reestablishing a connection between humans and the natural world. Methodology: The research employs an in-depth approach, delving into the subject matter through extensive research and the analysis of case studies. These case studies provide practical examples and insights into successful architectural designs that have effectively incorporated nature. Findings: The findings suggest that when architecture and nature coexist harmoniously, it creates a positive atmosphere and enhances people's wellbeing. The use of materials obtained from nature in their raw or minimally refined form, such as wood, clay, stone, and bamboo, contributes to a natural atmosphere within the built environment. Additionally, a color palette inspired by nature, consisting of earthy tones, green, brown, and rusty shades, further enhances the harmonious relationship between individuals and their surroundings. The paper also discusses the concept of sustainable architecture, where materials used are renewable, and energy consumption is minimal. It acknowledges the efforts of organizations such as the US Green Building Council in promoting sustainable design practices. Theoretical importance: This research contributes to the understanding of the relationship between architecture and nature and highlights the importance of incorporating natural elements into design. It emphasizes the potential of naturefriendly architecture to create greener, resilient, and sustainable cities. Data collection and analysis procedures: The researcher gathered data through comprehensive research, examining existing literature, and studying relevant case studies. The analysis involved studying the successful implementation of nature in architectural design and its impact on individuals and the environment. Question addressed: The research addresses the question of how nature can be incorporated into architectural designs to reconnect humans with the nature. Conclusion: In conclusion, this research highlights the significance of architecture being in harmony with its surrounding, which in turn should be in harmony with nature. By incorporating nature in architectural designs, individuals can rediscover their connection with nature and experience its positive impact on their well-being. The use of natural materials and a color palette inspired by nature further enhances this relationship. Additionally, embracing sustainable design practices contributes to the creation of greener and more resilient cities. This research underscores the importance of integrating nature-friendly architecture to foster a healthier and more sustainable future.

Keywords: nature, architecture, reconnecting, greencities, sustainable, openspaces, landscape

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Authors: Su Hui Tsai, Weir Sen Lin, Rhay Hung Weng

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There are numerous outpatient departments at hospitals with enormous amounts of outpatients. Although the work of outpatient nursing staff does not include the ward, emergency and critical care units that involve patient life-threatening conditions, the work is cumbersome and requires facing and dealing with a large number of outpatients in a short period of time. Therefore, nursing staff often do not feel satisfied with their work and cannot identify with their professional role, leading to intentions to leave their job. Thus, the main purpose of this study is to explore the correlation between the job satisfaction and role identity of nursing staff with turnover intention. This research was conducted using a questionnaire, and the subjects were outpatient nursing staff in three regional hospitals in Southern Taiwan. A total of 175 questionnaires were distributed, and 166 valid questionnaires were returned. After collecting the data, the reliability and validity of the study variables were confirmed by confirmatory factor analysis. The influence of role identity and job satisfaction on nursing staff’s turnover intention was analyzed by descriptive analysis, one-way ANOVA, Pearson correlation analysis and multiple regression analysis. Results showed that 'role identity' had significant differences in different types of marriages. Job satisfaction of 'grasp of environment' had significant differences in different levels of education. Job satisfaction of 'professional growth' and 'shifts and days off' showed significant differences in different types of marriages. 'Role identity' and 'job satisfaction' were negatively correlated with turnover intention respectively. Job satisfaction of 'salary and benefits' and 'grasp of environment' were significant predictors of role identity. The higher the job satisfaction of 'salary and benefits' and 'grasp of environment', the higher the role identity. Job satisfaction of 'patient and family interaction' were significant predictors of turnover intention. The lower the job satisfaction of 'patient and family interaction', the higher the turnover intention. This study found that outpatient nursing staff had the lowest satisfaction towards salary structure. It is recommended that bonuses, promotion opportunities and other incentives be established to increase the role identity of outpatient nursing staff. The results showed that the higher the job satisfaction of 'salary and benefits' and 'grasp of environment', the higher the role identity. It is recommended that regular evaluations be conducted to reward nursing staff with excellent service and invite nursing staff to share their work experiences and thoughts, to enhance nursing staff’s expectation and identification of their occupational role, as well as instilling the concept of organizational service and organizational expectations of emotional display. The results showed that the lower the job satisfaction of 'patient and family interaction', the higher the turnover intention. It is recommended that interpersonal communication and workplace violence prevention educational training courses be organized to enhance the communication and interaction of nursing staff with patients and their families.

Keywords: outpatient, job satisfaction, turnover, intention

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Authors: Norah Alosayl

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English is considered the most important foreign language in the Kingdom of Saudi Arabia (KSA) because of the usefulness of English as a global language compared to Arabic. As students’ desire to improve their English language skills has grown, English writing has been identified as the most difficult problem for Saudi students in their language learning. Although the English language in Saudi Arabia is taught beginning in the seventh grade, many students have problems at the university level, especially in writing, due to a gap between what is taught in secondary and high schools and university expectations- pupils generally study English at school, based on one book with few exercises in vocabulary and grammar exercises, and there are no specific writing lessons. Moreover, from personal teaching experience at King Saud bin Abdulaziz University, students face real problems with their writing. This paper revolves around the blackboard-based collaborative writing to help the undergraduate Saudi EFL students, in their first year enrolled in two sections of ENGL 101 in the first semester of 2021 at King Saud bin Abdulaziz University, practice the most difficult skill they found in their writing through a small group. Therefore, a sequential mixed methods design will be suited. The first phase of the study aims to highlight the most difficult skill experienced by students from an official writing exam that is evaluated by their teachers through an official rubric used in King Saud bin Abdulaziz University. In the second phase, this study will intend to investigate the benefits of social interaction on the process of learning writing. Students will be provided with five collaborative writing tasks via discussion feature on Blackboard to practice a skill that they found difficult in writing. the tasks will be formed based on social constructivist theory and pedagogic frameworks. The interaction will take place between peers and their teachers. The frequencies of students’ participation and the quality of their interaction will be observed through manual counting, screenshotting. This will help the researcher understand how students actively work on the task through the amount of their participation and will also distinguish the type of interaction (on task, about task, or off-task). Semi-structured interviews will be conducted with students to understand their perceptions about the blackboard-based collaborative writing tasks, and questionnaires will be distributed to identify students’ attitudes with the tasks.

Keywords: writing difficulties, blackboard-based collaborative writing, process of learning writing, interaction, participations

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Authors: Simon Grossemy, Peggy P. Y. Chan, Pauline M. Doran

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Nerve tissue engineering is the main field of research aimed at finding an alternative to autografts as a treatment for nerve injuries. Scaffolds are used as a support to enhance nerve regeneration. In order to successfully design novel scaffolds and in vitro cell culture systems, a deep understanding of the factors affecting nerve regeneration processes is needed. Physical and biological parameters associated with the culture environment have been identified as potentially influential in nerve cell differentiation, including electrical stimulation, exposure to extracellular-matrix (ECM) proteins, dynamic medium conditions and co-culture with glial cells. The mechanisms involved in driving the cell to differentiation in the presence of these factors are poorly understood; the complexity of each of them raises the possibility that they may strongly influence each other. Some questions that arise in investigating nerve regeneration include: What are the best protein coatings to promote neural cell attachment? Is the scaffold design suitable for providing all the required factors combined? What is the influence of dynamic stimulation on cell viability and differentiation? In order to study these effects, scaffolds adaptable to bioreactor culture conditions were designed to allow electrical stimulation of cells exposed to ECM proteins, all within a dynamic medium environment. Gold coatings were used to make the surface of viscose rayon microfiber scaffolds (VRMS) conductive, and poly-L-lysine (PLL) and laminin (LN) surface coatings were used to mimic the ECM environment and allow the attachment of rat PC12 neural cells. The robustness of the coatings was analyzed by surface resistivity measurements, scanning electron microscope (SEM) observation and immunocytochemistry. Cell attachment to protein coatings of PLL, LN and PLL+LN was studied using DNA quantification with Hoechst. The double coating of PLL+LN was selected based on high levels of PC12 cell attachment and the reported advantages of laminin for neural differentiation. The underlying gold coatings were shown to be biocompatible using cell proliferation and live/dead staining assays. Coatings exhibiting stable properties over time under dynamic fluid conditions were developed; indeed, cell attachment and the conductive power of the scaffolds were maintained over 2 weeks of bioreactor operation. These scaffolds are promising research tools for understanding complex neural cell behavior. They have been used to investigate major factors in the physical culture environment that affect nerve cell viability and differentiation, including electrical stimulation, bioreactor hydrodynamic conditions, and combinations of these parameters. The cell and tissue differentiation response was evaluated using DNA quantification, immunocytochemistry, RT-qPCR and functional analyses.

Keywords: bioreactor, electrical stimulation, nerve differentiation, PC12 cells, scaffold

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Authors: Shohreh Ghasemi

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

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

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Authors: Kumar Shashvat, Amol P. Bhondekar

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

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

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Authors: Hamid Reza Zeraatpisheh, Ali Akbar Heidari, Soleiman Mohammadi Doust

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This study has examined the relationship between place attachment and sustainable development of urban spaces. To perform this, the components of place identity, emotional attachment, place attachment and social bonding which totally constitute the output of place attachment, by means of the standardized questionnaire measure place attachment in three domains of (cognitive) the place identity, (affective) emotional attachment and (behavioral) place attachment and social bonding. To measure sustainable development, three components of sustainable development, including society, economy and environment has been considered. The study is descriptive. The assessment instrument is the standard questionnaire of Safarnia which has been used to measure the variable of place attachment and to measure the variable of sustainable development, a questionnaire has been made by the researcher and been based on the combined theoretical framework. The statistical population of this research has been the city of Shiraz. The statistical sample has been Hafeziyeh. SPSS software has been used to analyze the data and examined the results of both descriptive and inferential statistics. In inferential statistics, Pearson correlation coefficient has been used to examine the hypotheses. In this study, the variable of place attachment is high and sustainable development is also in a high level. These results suggest a positive relationship between attachment to place and sustainable development.

Keywords: place attachment, sustainable development, economy-society-environment, Hafez's tomb

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Authors: Erick C. Valverde, Wansu Lim

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

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

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Authors: Aswathaman Vijayan, Manish Jha, Ullas Theertha

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Climate change and Global warming have become an issue for both developed and developing countries and perhaps the biggest threat to the environment. We at ITC Limited believe that a company’s performance must be measured by its Triple Bottom Line contribution to building economic, social and environmental capital. This Triple Bottom Line strategy focuses on - Embedding sustainability in business practices, Investing in social development and Adopting a low carbon growth path with a cleaner environment approach. The Agri Business Division - ILTD operates in the tobacco crop growing regions of Andhra Pradesh and Karnataka province of India. The Agri value chain of the company comprises of two distinct phases: First phase is Agricultural operations undertaken by ITC trained farmers and the second phase is Industrial operations which include marketing and processing of the agricultural produce. This research work covers the Greenhouse Gas (GHG) management strategy of ITC in the Agricultural operations undertaken by the farmers. The agriculture sector adds considerably to global GHG emissions through the use of carbon-based energies, use of fertilizers and other farming operations such as ploughing. In order to minimize the impact of farming operations on the environment, ITC has a taken a big leap in implementing system and process in reducing the GHG impact in farm value chain by partnering with the farming community. The company has undertaken a unique three-pronged approach for GHG management at the farm value chain: 1) GHG inventory at farm value chain: Different sources of GHG emission in the farm value chain were identified and quantified for the baseline year, as per the IPCC guidelines for greenhouse gas inventories. The major sources of emission identified are - emission due to nitrogenous fertilizer application during seedling production and main-field; emission due to diesel usage for farm machinery; emission due to fuel consumption and due to burning of crop residues. 2) Identification and implementation of technologies to reduce GHG emission: Various methodologies and technologies were identified for each GHG emission source and implemented at farm level. The identified methodologies are – reducing the consumption of chemical fertilizer usage at the farm through site-specific nutrient recommendation; Usage of sharp shovel for land preparation to reduce diesel consumption; implementation of energy conservation technologies to reduce fuel requirement and avoiding burning of crop residue by incorporation in the main field. These identified methodologies were implemented at farm level, and the GHG emission was quantified to understand the reduction in GHG emission. 3) Social and farm forestry for CO2 sequestration: In addition, the company encouraged social and farm forestry in the waste lands to convert it into green cover. The plantations are carried out with fast growing trees viz., Eucalyptus, Casuarina, and Subabul at the rate of 10,000 Ha of land per year. The above approach minimized considerable amount of GHG emission at the farm value chain benefiting farmers, community, and environment at a whole. In addition, the CO₂ stock created by social and farm forestry program has made the farm value chain to become environment-friendly.

Keywords: CO₂ sequestration, farm value chain, greenhouse gas, ITC limited

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Authors: Ainur Bulasheva

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

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

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Authors: Zelalem Zerihun

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In this study, attempts were made to assess the bank-specific, industry-specific, and macro-economic factors affecting bank profitability. Data were collected from ten commercial banks in Ethiopia, covering the period of 2008-2012. A mixed method research approach was adopted for this research. Documentary analysis and in-depth interview were also used to substantiate the data. The study found out that capital strength, income diversification, bank size and gross domestic product are statistically significant and they have a positive relationship with banks’ profitability. However, operational efficiency and asset quality have a negative relationship with banks’ profitability. The relationship for liquidity risk, concentration and inflation were found to be statistically insignificant. The study revealed that focusing and reengineering the banks in light of the key internal drivers could enhance the profitability as well as the performance of the commercial banks in Ethiopia. In addition to this, the study suggests that banks in Ethiopia should not only be concerned about internal structures but also they must consider both the internal environment and the macro-economic environment in designing strategies to improve their profit or their performance.

Keywords: Ethiopian banking industry, macro-economic factors, documentary analysis, capital strength, income diversification

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Authors: Zeinab Aliyas, Diba Mahboubi

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Leisure walking is known as one of the most common types of physical activity that perform in purpose of recreation or health, which in turn may affect resident’s health. In the recent years, promoting leisure walking activity in neighborhood areas become as one of the important issues regarding promoting mental and physical health, however; the level of physical inactivity is rising in many societies including Iran. As it was proven that the tendency to walk out of choice is not encouraging among Iranian people. Hence; understanding the main concern of residents regarding walking activity in their neighborhoods can help in increasing the tendency to do leisure activity among residents. Built environment, social and individual factors are known as the main factors that affect decision to walk, in this regard, the study aimed to investigate the influence of personal and social factors that prevent residents to walk for recreation or exercise in their neighborhoods. Hence the fear of crime and personal barriers were examined in the current research as social and personal factors respectively. To collect the required data, 500 questionnaires by using systematic sampling were distributed from March to May 2016 in four residential neighborhoods of Bandar Abbas in Iran out which 411 questionnaire turned out to be qualified to be used in the study. The Smart-PLS was used to analyze the data. The findings of the study revealed that personal and fear of crime both have significant influence on the level of recreation and exercise walking in the neighborhood areas. The study found that fear of crime has the higher influence on exercise and recreational walking behavior in comparison to individual factors. It was revealed that social factors such as fear of crime in the neighborhoods might be more important than the personal reason for walking optionally in the surrounding environment. The finding of this study can help urban and health researcher to know the significant influence of fear of crime and individual attitudes on the level of leisure walking activity, in addition, the findings of the study suggest that urban planners and designers, as well as public health promoters, need to highly consider the contribution of neighborhoods' social environment variables as well as individual variables to promote walking behavior changes among adult population.

Keywords: exercise walking, fear of crime, neighborhood, personal barriers, recreation walking

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Authors: Mina Bakhshi

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Nowadays, issues such as various types of pollution, problems caused by energy consumption, population density, social activities, difficulties related to urban access and communication, transportation, etc., have challenged different communities and become the subject of their discussions. In response to this issue, theories and movements have emerged to achieve sustainable urban development, including the smart growth movement. This theory emphasizes that the physical growth and expansion of cities should serve the community and the environment, aiming to improve the quality of life and promote the use of renewable energy resources for sustainability. The smart city network system not only improves the economic situation of the society and benefits the environment but also enables the achievement of important issues such as sustainable development, continuity, and diversity of energy resources. In this article, we investigate the impact of using renewable energy sources on optimizing energy consumption and reducing pollution caused by fossil fuels with the help of smart city development. The aim of this article is to introduce renewable energy sources and their utilization as a solution to address the energy crisis and reduce environmental pollution. This research has attempted to introduce the smart city and the use of renewable energy sources as a method for solving many urban problems and achieving efficient urban control and management.

Keywords: smart city, renewable energy sources, sustainable development, sustainable city

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Authors: Nicky Wilson, Graeme Ralph

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Legacy aerostructure assembly is defined by large components, low build rates, and manual assembly methods. With an increasing demand for commercial aircraft and emerging markets such as the eVTOL (electric vertical take-off and landing) market, current methods of manufacturing are not capable of efficiently hitting these higher-rate demands. This project will look at how legacy manufacturing processes can be rate enabled by taking a holistic view of data usage, focusing on how data can be collected to enable fully integrated digital factories and supply chains. The study will focus on how data is flowed both up and down the supply chain to create a digital thread specific to each part and assembly while enabling machine learning through real-time, closed-loop feedback systems. The study will also develop a bespoke architecture to enable connectivity both within the factory and the wider PLM (product lifecycle management) system, moving away from traditional point-to-point systems used to connect IO devices to a hub and spoke architecture that will exploit report-by-exception principles. This paper outlines the key issues facing legacy aircraft manufacturers, focusing on what future manufacturing will look like from adopting Industry 4 principles. The research also defines the data architecture of a PLM system to enable the transfer and control of a digital thread within the supply chain and proposes a standardised communications protocol to enable a scalable solution to connect IO devices within a production environment. This research comes at a critical time for aerospace manufacturers, who are seeing a shift towards the integration of digital technologies within legacy production environments, while also seeing build rates continue to grow. It is vital that manufacturing processes become more efficient in order to meet these demands while also securing future work for many manufacturers.

Keywords: Industry 4, digital transformation, IoT, PLM, automated assembly, connected factories

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Authors: Junaid C, Sabique MK

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Introduction: MES Mamapd College is an autonomous college established in 1964 affiliated with the University of Calicut run by the Muslim Educational Society Kerala. The department of Arabic of the college is having a pivotal role in promoting Arabic language learning, teaching, research, and other allied academic activities. State of Problem: Department of Arabic of the college introduced before the academic committee the culture of international seminars. The department connected the academic community with foreign scholars and introduced industry-academia collaboration programs which are beneficial to the job seekers. These practices and innovations should be documented. Objectives: Create awareness of innovative practices implemented for the promotion of the Arabic language. Infuse confidence in learners in learning of Arabic language. Showcase the distinctive academic programs initiated by the department Methodology: Data will be collected from archives, souvenirs, and reports. Survey methods and interviews with authorities and beneficiaries will be collected for the data analysis. Major results: MES Mampad College introduced before its stakeholders different unique academic practices related to the Arabic language and literature. When the unprecedented pandemic situation pulled back all of the academic community, the department come forward with numerous academic initiatives utilizing the virtual space. Both arenas will be documented. Conclusion: This study will help to make awareness on the promotion of the Arabic language studies and related practices initiated by the department of Arabic MES Mampad College. These practices and innovations can be modeled and replicated.

Keywords: teaching Arabic language, MES mampad college, Arabic webinars, pandemic impacts in literature

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Authors: Burhan Khan

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Objective: This study aims to enhance the body of knowledge about the vulnerabilities of child waste pickers in solid waste management. The primary objective of this research is to investigate the occupational menaces and their potential harm to the health of child waste pickers. Material and Methods: The present study design is descriptive in nature and involves children aged 5 through 14, who were rummaging through garbage in the roads and streets of Aligarh city, Uttar Pradesh. The researcher adopted an empirical approach to interview 65 participants (27 boys and 38 girls) across Aligarh city, Uttar Pradesh. The majority of the participants are Muslims (76.9 %), scheduled Castes (13.8 %), and Hindus (9.2 %). Out of 65 participants, 73.8% of children were migrated within the last five years. The primary data were analysed by utilising descriptive statistics, including frequencies, cross-tabs, means, and percentages. Results: The results show that the vast majority of children (87.7%) have experienced superficial injuries or open wound at their work. More than 32% were suffering from respiratory problems such as coughing, wheezing and short of breath, close to 37% reported skin problems like allergy, irritation and bruising and 4.6% had eye problems such as pain and irritation in eyes. Nearly 78% of children lift and carry a heavy load like large garbage bags. Over 83% informed that they sort through refuse in a filthy environment such as open dumpsites, effluents, and runnels. Conclusion: This research provides pieces of evidence of how children are being tormented in the rag-picking sector. It has been observed that child rag pickers are susceptible to injuries or illnesses due to work-related risks and toxic environment. In India, there is no robust policy to address the concerns of waste pickers and laws to protect their rights. Consequently, these deprived communities of rag pickers, especially children, have become more vulnerable over time in India. Hence, this research paper calls for a quick response to the exigencies of child rag picker by developing a holistic approach that deals with education, medical care, sanitation, and nutrition for child rag pickers.

Keywords: child rag pickers, health impairments, occupational hazards, toxic environment

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Authors: Omil Nady Mahrous Maximous

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

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

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Authors: Nahid Nariman

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The prosperity of any nation depends on its ability to use human potential, in particular, to offer an education that builds learners' competencies to become effective workforce participants and true citizens of the world. Ever since the Second World War, the United States has been a dominant player in the world politically, economically, socially, and culturally. The rapid rise of technological advancement and consumer technologies have made it clear that science, technology, engineering, and math (STEM) play a crucial role in today’s world economy. Exploring the top qualities demanded from new hires in the industry—i.e., problem-solving skills, teamwork, dependability, adaptability, technical and communication skills— sheds light on the kind of path that is needed for a successful educational system to effectively support STEM. The focus of 21st century education has been to build student competencies by preparing them to acquire and apply knowledge, to think critically and creatively, to competently use information, be able to work in teams, to demonstrate intellectual and moral values as well as cultural awareness, and to be able to communicate. Many educational reforms pinpoint various 'ideal' pathways toward STEM that educators, policy makers, and business leaders have identified for educating the workforce of tomorrow. This study will explore how problem-based learning (PBL), an instructional strategy developed in the medical field and adopted with many successful results in K-12 through higher education, is the proper approach to stimulate underrepresented high school students' interest in pursuing STEM careers. In the current study, the effect of a problem-based STEM model on students' attitudes and career interests was investigated using qualitative and quantitative methods. The participants were 71 low-income, native Hawaiian high school students who would be first-generation college students. They were attending a summer STEM camp developed as the result of a collaboration between the University of Hawaii and the Upward Bound Program. The project, funded by the National Science Foundation's Innovative Technology Experiences for Students and Teachers (ITEST) program, used PBL as an approach in challenging students to engage in solving hands-on, real-world problems in their communities. Pre-surveys were used before camp and post-surveys on the last day of the program to learn about the implementation of the PBL STEM model. A Career Interest Questionnaire provided a way to investigate students’ career interests. After the summer camp, a representative selection of students participated in focus group interviews to discuss their opinions about the PBL STEM camp. The findings revealed a significantly positive increase in students' attitudes towards STEM disciplines and STEM careers. The students' interview results also revealed that students identified PBL to be an effective form of instruction in their learning and in the development of their 21st-century skills. PBL was acknowledged for making the class more enjoyable and for raising students' interest in STEM careers, while also helping them develop teamwork and communication skills in addition to scientific knowledge. As a result, the integration of PBL and a STEM learning experience was shown to positively affect students’ interest in STEM careers.

Keywords: problem-based learning, science education, STEM, underrepresented students

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

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

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

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Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

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As we enter the new era of Artificial Intelligence (AI) and Cloud Computing, we mostly rely on the Machine and Natural Language Processing capabilities of AI, and Energy Efficient Hardware and Software Devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and sustaining the depletion of natural resources. The core pillars of sustainability are economic, environmental, and social, which is also informally referred to as the 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core Sustainability Model in the Enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand, there is also a growing concern in many industries on how to reduce carbon emissions and conserve natural resources while adopting sustainability in corporate business models and policies. In our paper, we would like to discuss the driving forces such as Climate changes, Natural Disasters, Pandemic, Disruptive Technologies, Corporate Policies, Scaled Business Models and Emerging social media and AI platforms that influence the 3 main pillars of Sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy-efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increasing recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (Shared IT services, Cloud computing, and Application Modernization) with the vision for a sustainable environment.

Keywords: climate change, pandemic, disruptive technology, government policies, business model, machine learning and natural language processing, AI, social media platform, cloud computing, advanced monitoring, metering infrastructure

Procedia PDF Downloads 92

Authors: Rudolph Carl Barrientos, Juwaln Diego Descallar, Rainer James Palmiano

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Household Appliance Scheduling Systems (HASS) coupled with a Time-of-Use (TOU) pricing scheme, a form of Demand Side Management (DSM), is not widely utilized in the Philippines’ residential electricity sector. This paper’s goal is to encourage distribution utilities (DUs) to adopt HASS and TOU by analyzing the effect of household schedulers on the electricity price and load profile in a residential environment. To establish this, a city based on an implemented survey is generated using Monte Carlo Analysis (MCA). Then, a Binary Particle Swarm Optimization (BPSO) algorithm-based HASS is developed considering user satisfaction, electricity budget, appliance prioritization, energy storage systems, solar power, and electric vehicles. The simulations were assessed under varying levels of user compliance. Results showed that the average electricity cost, peak demand, and peak-to-average ratio (PAR) of the city load profile were all reduced. Therefore, the deployment of the HASS and TOU pricing scheme is beneficial for both stakeholders.

Keywords: appliance scheduling, DSM, TOU, BPSO, city-wide simulation, electric vehicle, appliance prioritization, energy storage system, solar power

Procedia PDF Downloads 85

Authors: H. Jalahi, A. Yazdanpanah Nozari

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Background and Purpose: Assessment of learners’ performance is an important factors in teaching-learning process. When a factor is sensitive and has high influence on life, their assessment should be done precisely. Thinking dispositions are very important factors in medical education because of its specific condition. In this study a model is designed for fostering thinking dispositions of learners in which authentic assessment is an important element. Materials and Methods: Objective based research is developmental, and such a model was not designed for curricula. Data collection and comparing approaches about assessment and analyzing current assessments offered applied proposals. Results: Based on research findings, the current assessments are response-based, that is students instead of product of response, only offers the specific response which the teachers expects; but authentic assessment is a form of assessment in which students are asked to perform real-word tasks that demonstrate meaningful application of essential knowledge and skills. Conclusion: Because of the difficulties and unexpected problems in life and individuals needs to lifelong learning and conditions in medical course that require decision making in specific times, we must pay attention to reach thinking dispositions and it should be included in curriculum. Authentic assessment as an important aspect of curriculum can help fostering thinking dispositions of learners. Using this kind of assessments which focus on application of information and skills to solve real-word tasks have more important role in medical courses.

Keywords: assessment, authentic, medical courses, developmental

Procedia PDF Downloads 351

Authors: Cuma Şimşek

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Nowadays our globalized world is in a very rapid and sophisticated change. In the information age, notion of ‘information’ has begun to spread faster than ever also in this age, changes and transformation has gained tremendous momentum with technology boom. This continuous change and transformation, increased the competition between existing organizations and corporations. Besides, the organizations which show resistance to change has been put out of action in this competitive environment. It is not possible to sustain the existence of organizations without adapting to change and transformation by isolating itself from developments. As a consequence of improved communication and dialog possibilities by means of increasing knowledge level, there has been made a change of scene in administrative mentality, style and activation, especially in 21th century. Leaders emerge as the most important factor in this process of perception and success. At the same time it is not enough to adapt the alteration with conventional leadership abilities and behaviors. In parallel with alteration, new types of leadership are coming up. The optimal leadership type for our era and a trending topic "Transformational Leadership" is in great demand now. In this research, current situation of the Air Forces which use high-technology weapons efficiently, operates in an environment full of threats and is analyzed. It is evaluated that in order to be ready for war continuously and adjusting itself to changing terms of warfare atmosphere , Air Forces need ‘transformational leaders’ who are innovative, foreseeing and having a vision so that they can develop new methods and strategies for complex problems. Because it is the Air Force which is responsible for being the deterrent force of its country.

Keywords: transformational, change, air force, leadership

Procedia PDF Downloads 430

Authors: Karen Koellner, Nanette Seago, Jennifer Jacobs, Helen Garnier

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Although studies of teacher professional development (PD) are prevalent, surprisingly most have only produced incremental shifts in teachers’ learning and their impact on students. There is a critical need to understand what teachers take up and use in their classroom practice after attending PD and why we often do not see greater changes in learning and practice. This paper is based on a mixed methods efficacy study of the Learning and Teaching Geometry (LTG) video-based mathematics professional development materials. The extent to which the materials produce a beneficial impact on teachers’ mathematics knowledge, classroom practices, and their students’ knowledge in the domain of geometry through a group-randomized experimental design are considered. In this study, we examine a small group of teachers to better understand their interpretations of the workshops and their classroom uptake. The participants included 103 secondary mathematics teachers serving grades 6-12 from two states in different regions. Randomization was conducted at the school level, with 23 schools and 49 teachers assigned to the treatment group and 18 schools and 54 teachers assigned to the comparison group. The case study examination included twelve treatment teachers. PD workshops for treatment teachers began in Summer 2016. Nine full days of professional development were offered to teachers, beginning with the one-week institute (Summer 2016) and four days of PD throughout the academic year. The same facilitator-led all of the workshops, after completing a facilitator preparation process that included a multi-faceted assessment of fidelity. The overall impact of the LTG PD program was assessed from multiple sources: two teacher content assessments, two PD embedded assessments, pre-post-post videotaped classroom observations, and student assessments. Additional data was collected from the case study teachers including additional videotaped classroom observations and interviews. Repeated measures ANOVA analyses were used to detect patterns of change in the treatment teachers’ content knowledge before and after completion of the LTG PD, relative to the comparison group. No significant effects were found across the two groups of teachers on the two teacher content assessments. Teachers were rated on the quality of their mathematics instruction captured in videotaped classroom observations using the Math in Common Observation Protocol. On average, teachers who attended the LTG PD intervention improved their ability to engage students in mathematical reasoning and to provide accurate, coherent, and well-justified mathematical content. In addition, the LTG PD intervention and instruction that engaged students in mathematical practices both positively and significantly predicted greater student knowledge gains. Teacher knowledge was not a significant predictor. Twelve treatment teachers were self-selected to serve as case study teachers to provide additional videotapes in which they felt they were using something from the PD they learned and experienced. Project staff analyzed the videos, compared them to previous videos and interviewed the teachers regarding their uptake of the PD related to content knowledge, pedagogical knowledge and resources used.

Keywords: teacher learning, professional development, pedagogical content knowledge, geometry

Procedia PDF Downloads 157

Authors: Nita Mitra, Pranab Chanda

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In this paper, the issue of attitude-behavior consistency has been addressed in the context of climate change. Scientists (about 98 percent) opine that human behavior has a significant role in climate change. Such climate changes are harmful for human life. Thus, it is natural to conclude that only change of human behavior can avoid harmful consequences. Government and Non-Government Organizations are taking steps to bring in the desired changes in behavior. However, it seems that although the efforts are achieving changes in the attitudes to some degree, those steps are failing to materialize the corresponding behavioral changes. This has been a great concern for environmentalists. Psychologists have noticed the problem as a particular case of the general psychological problem of making attitude and behavior consistent with each other. The present study is in continuation of a previous work of the same author based upon descriptive research on the status of attitude and behavior of the people of a foot-hill region of the Himalayas in India regarding climate change. The observations confirm the mismatch of attitude and behavior of the people of the region with respect to climate change. While doing so an attitude-behavior mismatch has been noticed with respect to the acceptance of psychological findings by the public. People have been found to be interested in Psychology as an important subject, but they are reluctant to take the observations of psychologists seriously. A comparative study in this regard has been made with similar studies done elsewhere. Finally, an attempt has been made to perceive observations in the framework of observational learning due to Bandura's and behavior change due to Lewin.

Keywords: acceptance of psychological variables, attitude-behavior consistency, behavior change, climate change, observational learning

Procedia PDF Downloads 144

Authors: Huang Yajing

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Context: Computer-aided language learning (CALL) in China has undergone significant development over the past few decades, with distinct stages marking its evolution. This paper aims to provide a comprehensive review of the practice and research in this field in China, tracing its journey from the early stages of audio-visual education to the current multimedia network integration stage. Research Aim: The study aims to analyze the historical progression of CALL in China, identify key developments in the field, and provide recommendations for enhancing CALL practices in the future. Methodology: The research employs document analysis and literature review to synthesize existing knowledge on CALL in China, drawing on a range of sources to construct a detailed overview of the evolution of CALL practices and research in the country. Findings: The review highlights the significant advancements in CALL in China, showcasing the transition from traditional audio-visual educational approaches to the current integrated multimedia network stage. The study identifies key milestones, technological advancements, and theoretical influences that have shaped CALL practices in China. Theoretical Importance: The evolution of CALL in China reflects not only technological progress but also shifts in educational paradigms and theories. The study underscores the significance of cognitive psychology as a theoretical underpinning for CALL practices, emphasizing the learner's active role in the learning process. Data Collection and Analysis Procedures: Data collection involved extensive review and analysis of documents and literature related to CALL in China. The analysis was carried out systematically to identify trends, developments, and challenges in the field. Questions Addressed: The study addresses the historical development of CALL in China, the impact of technological advancements on teaching practices, the role of cognitive psychology in shaping CALL methodologies, and the future outlook for CALL in the country. Conclusion: The review provides a comprehensive overview of the evolution of CALL in China, highlighting key stages of development and emerging trends. The study concludes by offering recommendations to further enhance CALL practices in the Chinese context.

Keywords: English education, educational technology, computer-aided language teaching, applied linguistics

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Authors: Kemal Çomakli, Uğur Çakir, Ayşegül Çokgez Kuş, Erol Şahin

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Kind of energy that buildings need changes in various types, like heating energy, cooling energy, electrical energy and thermal energy for hot top water. Usually the processes or systems produce thermal energy causes emitting pollutant emissions while they produce heat because of fossil fuels they use. A lower consumption of thermal energy will contribute not only to a reduction in the running costs, but also in the reduction of pollutant emissions that contribute to the greenhouse effect and a lesser dependence of the hospital on the external power supply. Cogeneration or CHP (Combined heat and Power) is the system that produces power and usable heat simultaneously. Combined production of mechanical or electrical and thermal energy using a simple energy source, such as oil, coal, natural or liquefied gas, biomass or the sun; affords remarkable energy savings and frequently makes it possible to operate with greater efficiency when compared to a system producing heat and power separately. Because of the life standard of humanity in new age, energy sources must be continually and best qualified. For this reason the installation of a system for the simultaneous generation of electrical, heating and cooling energy would be one of the best solutions if we want to have qualified energy and reduce investment and operating costs and meet ecological requirements. This study aims to bring out the contributions of cogeneration systems to the environment and sustainability by saving the energy and reducing the emissions.

Keywords: sustainability, cogeneration systems, energy economy, energy saving

Procedia PDF Downloads 503