Search results for: teacher training institution

Authors: Pranav Gunhal., Krish Jhurani

Abstract:

This study tackles the significant computational challenge of predicting excited state dynamics in organic photovoltaic (OPV) materials—a pivotal factor in the performance of solar energy solutions. Time-dependent density functional theory (TDDFT), though effective, is computationally prohibitive for larger and more complex molecules. As a solution, the research explores the application of transformer neural networks, a type of artificial intelligence (AI) model known for its superior performance in natural language processing, to predict excited state dynamics in OPV materials. The methodology involves a two-fold process. First, the transformer model is trained on an extensive dataset comprising over 10,000 TDDFT calculations of excited state dynamics from a diverse set of OPV materials. Each training example includes a molecular structure and the corresponding TDDFT-calculated excited state lifetimes and key electronic transitions. Second, the trained model is tested on a separate set of molecules, and its predictions are rigorously compared to independent TDDFT calculations. The results indicate a remarkable degree of predictive accuracy. Specifically, for a test set of 1,000 OPV materials, the transformer model predicted excited state lifetimes with a mean absolute error of 0.15 picoseconds, a negligible deviation from TDDFT-calculated values. The model also correctly identified key electronic transitions contributing to the excited state dynamics in 92% of the test cases, signifying a substantial concordance with the results obtained via conventional quantum chemistry calculations. The practical integration of the transformer model with existing quantum chemistry software was also realized, demonstrating its potential as a powerful tool in the arsenal of materials scientists and chemists. The implementation of this AI model is estimated to reduce the computational cost of predicting excited state dynamics by two orders of magnitude compared to conventional TDDFT calculations. The successful utilization of transformer neural networks to accurately predict excited state dynamics provides an efficient computational pathway for the accelerated discovery and design of new OPV materials, potentially catalyzing advancements in the realm of sustainable energy solutions.

Keywords: transformer neural networks, organic photovoltaic materials, excited state dynamics, time-dependent density functional theory, predictive modeling

Procedia PDF Downloads 84

Authors: Rodrique Watong Tchounkeu

Abstract:

This paper investigated the implementation and impact of inclusive education practices in early childhood settings (ages 3-6) with the overarching aim of fostering a diverse learning environment. The primary objectives were to assess the then-current state of inclusive practices, identify effective methodologies for accommodating diverse learning needs, and evaluate the outcomes of implementing inclusive education in early childhood settings. To achieve these objectives, a mixed-methods approach was employed, combining qualitative interviews with early childhood educators and parents, along with quantitative surveys distributed to a diverse sample of participants. The qualitative phase involved semi-structured interviews with 30 educators and 50 parents, selected through purposive sampling. The interviews aimed to gather insights into the challenges faced in implementing inclusive education, the strategies employed, and the perceived benefits and drawbacks. The quantitative phase included surveys administered to 300 early childhood educators across various settings, measuring their familiarity with inclusive practices, their perceived efficacy, and their willingness to adapt teaching methods. The results revealed a significant gap between the theoretical understanding and practical implementation of inclusive education in early childhood settings. While educators demonstrated a high level of theoretical knowledge, they faced challenges in effectively translating these concepts into practice. Parental perspectives highlighted the importance of collaboration between educators and parents in supporting inclusive education. The surveys indicated a positive correlation between educators' familiarity with inclusive practices and their willingness to adapt teaching methods, emphasizing the need for targeted professional development. The implications of this study suggested the necessity for comprehensive training programs for early childhood educators focused on the practical implementation of inclusive education strategies. Additionally, fostering stronger partnerships between educators and parents was crucial for creating a supportive learning environment for all children. By addressing these findings, this research contributed to the advancement of inclusive education practices in early childhood settings, ultimately leading to more inclusive and effective learning environments for diverse groups of young learners.

Keywords: inclusive education, early childhood settings, diverse learning, young learners, practical implementation, parental collaboration

Procedia PDF Downloads 48

Authors: Stephens Oluyemi Adetunji, Nel Norma Margaret, Naidu Narainsamy

Abstract:

Empathy has been identified by researchers to be a crucial factor in helping adolescents to refrain from delinquent behavior. Adolescent delinquent behavior is a social problem that has become a source of concern to parents, psychologists, educators, correctional services, researchers as well as governments of nations. Empathy is a social skill that enables an individual to understand and to share another’s emotional state. An individual with a high level of empathy will avoid any act or behavior that will affect another person negatively. The need for this study is predicated on the fact that delinquent adolescent behavior could lead to adult criminality. This, in the long run, has the potential of resulting in an increase in crime rate thereby threatening public safety. It has therefore become imperative to explore the level of empathy of delinquent adolescents who have committed crime and are awaiting trial. It is the conjecture of this study that knowledge of the empathy level of delinquent adolescents will provide an opportunity to design an intervention strategy to remediate the deficit. This study was therefore designed to determine the level of empathy of delinquent adolescents. In addition, this study provides a better understanding of factors that may prevent adolescents from developing delinquent behavior, in this case, delinquents’ empathy levels. In the case of participants who have a low level of empathy, remediation strategies to improve their empathy level would be designed. Two research questions were raised to guide this study. A mixed methods research design was employed for the study. The sample consists of fifteen male adolescents who are between 13-18 years old with a mean age of 16.5 years old. The participants are adolescents who are awaiting trial. The non-probability sampling technique was used to obtain the sample for the quantitative study while purposive sampling was used in the case of the qualitative study. A self–report questionnaire and structured interview were used to assess the level of empathy of participants. The data obtained was analysed using the simple percentages for the quantitative data and transcribing the qualitative data. The result indicates that most of the participants have low level of empathy. It is also revealed that there is a difference in the empathy level on the basis of whether they are from parents living together and those whose parents are separated. Based on the findings of this study, it is recommended that the level of empathy of participants be improved through training and emphasizing the importance of stimulating family environment for children. It is also recommended that programs such as youth mentoring and youth sheltering be established by the government of South Africa to address the menace of delinquent adolescents.

Keywords: adolescents, behavior, delinquents, empathy

Procedia PDF Downloads 444

Authors: Habtamu Ayenew Asegie

Abstract:

Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

Procedia PDF Downloads 19

Authors: Sultan Mahmud, Qamar Zaman, Travis Esau, Young Chang

Abstract:

Strawberry powdery mildew (PM) is a serious disease that has a significant impact on strawberry production. Field scouting is still a major way to find PM disease, which is not only labor intensive but also almost impossible to monitor disease severity. To reduce the loss caused by PM disease and achieve faster automatic detection of the disease, this paper proposes an approach for detection of the disease, based on image texture and classified with support vector machines (SVMs) and k-nearest neighbors (kNNs). The methodology of the proposed study is based on image processing which is composed of five main steps including image acquisition, pre-processing, segmentation, features extraction and classification. Two strawberry fields were used in this study. Images of healthy leaves and leaves infected with PM (Sphaerotheca macularis) disease under artificial cloud lighting condition. Colour thresholding was utilized to segment all images before textural analysis. Colour co-occurrence matrix (CCM) was introduced for extraction of textural features. Forty textural features, related to a physiological parameter of leaves were extracted from CCM of National television system committee (NTSC) luminance, hue, saturation and intensity (HSI) images. The normalized feature data were utilized for training and validation, respectively, using developed classifiers. The classifiers have experimented with internal, external and cross-validations. The best classifier was selected based on their performance and accuracy. Experimental results suggested that SVMs classifier showed 98.33%, 85.33%, 87.33%, 93.33% and 95.0% of accuracy on internal, external-I, external-II, 4-fold cross and 5-fold cross-validation, respectively. Whereas, kNNs results represented 90.0%, 72.00%, 74.66%, 89.33% and 90.3% of classification accuracy, respectively. The outcome of this study demonstrated that SVMs classified PM disease with a highest overall accuracy of 91.86% and 1.1211 seconds of processing time. Therefore, overall results concluded that the proposed study can significantly support an accurate and automatic identification and recognition of strawberry PM disease with SVMs classifier.

Keywords: powdery mildew, image processing, textural analysis, color co-occurrence matrix, support vector machines, k-nearest neighbors

Procedia PDF Downloads 103

Authors: Som Pal Baliyan

Abstract:

Dairy enterprise has been a major source of employment and income generation in most of the economies worldwide. Botswana government has also identified dairy as one of the agricultural sectors towards diversification of the mineral dependent economy of the country. The huge gap between local demand and supply of milk and milk products indicated that there are not only constraints but also; opportunities exist in this sub sector of agriculture. Therefore, this study was an attempt to identify constraints and opportunities in dairy production industry in Botswana. The possible ways to mitigate the constraints were also identified. The findings should assist the stakeholders especially, policy makers in the formulation of effective policies for the growth of dairy sector in the country. This quantitative study adopted a survey research design. A final survey followed by a pilot survey was conducted for data collection. The purpose of the pilot survey was to collect basic information on the nature and extent of the constraints, opportunities and ways to mitigate the constraints in dairy production. Based on the information from pilot survey, a four point Likert’s scale type questionnaire was constructed, validated and tested for its reliability. The data for the final survey were collected from purposively selected twenty five dairy farms. The descriptive statistical tools were employed to analyze data. Among the twelve constraints identified; high feed costs, feed shortage and availability, lack of technical support, lack of skilled manpower, high prevalence of pests and diseases and, lack of dairy related technologies were the six major constraints in dairy production. Grain feed production, roughage feed production, manufacturing of dairy feed, establishment of milk processing industry and, development of transportation systems were the five major opportunities among the eight opportunities identified. Increasing production of animal feed locally, increasing roughage feed production locally, provision of subsidy on animal feed, easy access to sufficient financial support, training of the farmers and, effective control of pests and diseases were identified as the six major ways to mitigate the constraints. It was recommended that the identified constraints and opportunities as well as the ways to mitigate the constraints need to be carefully considered by the stakeholders especially, policy makers during the formulation and implementation of the policies for the development of dairy sector in Botswana.

Keywords: dairy enterprise, milk production, opportunities, production constraints

Procedia PDF Downloads 373

Authors: Averalda van Graan, Joelaine Chetty, Malory Links, Agness Mwangwela, Sitilitha Masangwi, Dalitso Chimwala, Shiban Ghosh, Elizabeth Marino-Costello

Abstract:

Food composition data is becoming increasingly important as dealing with food insecurity and malnutrition in its persistent form of under-nutrition is now coupled with increasing over-nutrition and its related ailments in the developing world, of which Malawi is not spared. In the absence of a food composition database (FCDB) inherent to our dietary patterns, efforts were made to develop a country-specific FCDB for nutrition practice, research, and programming. The main objective was to develop a multi-user, country-specific food composition database, and table from existing published and unpublished scientific literature. A multi-phased approach guided by the project framework was employed. Phase 1 comprised a scoping mission to assess the nutrition landscape for compilation activities. Phase 2 involved training of a compiler and data collection from various sources, primarily; institutional libraries, online databases, and food industry nutrient data. Phase 3 subsumed evaluation and compilation of data using FAO and IN FOODS standards and guidelines. Phase 4 concluded the process with quality assurance. 316 Malawian food items categorized into eight food groups for 42 components were captured. The majority were from the baby food group (27%), followed by a staple (22%) and animal (22%) food group. Fats and oils consisted the least number of food items (2%), followed by fruits (6%). Proximate values are well represented; however, the percent missing data is huge for some components, including Se 68%, I 75%, Vitamin A 42%, and lipid profile; saturated fat 53%, mono-saturated fat 59%, poly-saturated fat 59% and cholesterol 56%. A multi-phased approach following the project framework led to the development of the first Malawian FCDB and table. The table reflects inherent Malawian dietary patterns and nutritional concerns. The FCDB can be used by various professionals in nutrition and health. Rising over-nutrition, NCD, and changing diets challenge us for nutrient profiles of processed foods and complete lipid profiles.

Keywords: analytical data, dietary pattern, food composition data, multi-phased approach

Procedia PDF Downloads 66

Authors: Peter Hajnal

Abstract:

The need to combine serious training in disciplinary/scholarly approaches to problems of general significance with an educational experience that engages students with these very same problems on a personal level is one of the key challenges facing modern liberal education in the West. The typical approach to synthesizing these two goals, one highly abstract, the other elusively practical, proceeds by invoking ideals traditionally associated with Enlightenment and 19th century “humanism”. These ideas are in turn rooted in an approach to reality codified by Cartesianism and the rise of modern science. Articulating this connection of the modern humanist tradition with Cartesianism allows for demonstrating how the central problem of modern liberal education is rooted in the strict separation of knowledge and personal experience inherent in the dualism of Descartes. The question about the shape of contemporary liberal education is, therefore, the same as asking whether an anti-Cartesian version of liberal education is possible at all. Although the formulation of a general answer to this question is a tall order (whether in abstract or practical terms), and might take different forms (nota bene in Eastern and Western contexts), a key inspiration may be provided by a certain shift of attitude towards the Cartesian conception of the relationship of knowledge and experience required by discussion based close-reading of works of visual art. Taking the work of Stanley Cavell as its central inspiration, my paper argues that this shift of attitude in question is best described as a form of “second naïveté”, and that it provides a useful model of conceptualizing in more concrete terms the appeal for such a “second naïveté” expressed in recent writings on the role of various disciplines in organizing learning by philosophers of such diverse backgrounds and interests as Hilary Putnam and Bruno Latour. The adoption of naïveté so identified as an educational ideal may be seen as a key instrument in thinking of the educational context as itself a medium of synthesis of the contemplative and the practical. Moreover, it is helpful in overcoming the bad dilemma of ideological vs. conservative approaches to liberal education, as well as in correcting a certain commonly held false view of the historical roots of liberal education in the Renaissance, which turns out to offer much more of a sui generis approach to practice rather than represent a mere precursor to the Cartesian conception.

Keywords: liberal arts, philosophy, education, Descartes, naivete

Procedia PDF Downloads 177

Authors: Harithas Aruchchunan

Abstract:

Silage production is an essential aspect of dairy farming, used to provide high-quality feed to ruminants. However, dairy farmers in Northern Province Sri Lanka are facing multiple challenges that compromise the quality and quantity of silage produced. To tackle these challenges, promoting silage feeding has become an essential component of sustainable dairy farming practices. In this study, silage bale samples were collected from a newly started silage baling factory in Jaffna, Northern province and their quality was analysed at the Veterinary Research Institute laboratory in Kandy in March 2023. The results show the nutritional composition of three Napier grass cultivars: Super Napier, CO6, and Indian Red Napier (BH18). The main parameters analysed were dry matter, pH, lactic acid, soluble carbohydrate, ammonia nitrogen, ash, crude protein, NDF, and ADF. The results indicate that Super Napier and CO6 have higher crude protein content and lower ADF levels, making them suitable for producing high-quality silage. The pH levels of all three cultivars were safe, and the ammonia nitrogen levels were considered appropriate. However, laboratory results indicate that the quality of silage bales produced can be further enhanced. Dairy farmers should be encouraged to adopt these cultivars to achieve better yields as they are high in protein and are better suited to Northern Province's soil and climate. Therefore, it is vital to educate small-scale fodder producers, who supply the raw material to silage factories, on the best practices of cultivating these new cultivars. To improve silage bale production and quality in Northern Province Sri Lanka, we recommend increasing public awareness about silage feeding, providing education and training to dairy farmers and small-scale fodder producers on modern silage production techniques and improving the availability of raw materials for silage production. Additionally, Napier grass cultivars need to be promoted among dairy farmers for better production and quality of silage bales. Failing to improve the quality and quantity of silage bale production could not only lead to the decline of dairy farming in Northern Province Sri Lanka but also the negative impact on the economy

Keywords: silage bales, dairy farming, economic crisis, Sri Lanka

Procedia PDF Downloads 64

Authors: Bilha Paryente, Rivi Frei Landau

Abstract:

Autoethnography - a combination of autobiography and ethnography - focuses on the intersection of personal experiences and the culture in which they take place and is considered a viable method for exploring human experiences. The Russo-Ukrainian war has resulted in millions of forcibly displaced asylum-seeking refugees facing ambiguous loss. Whereas much is known about refugees' support needs, little is known about the needs and experiences of the humanitarian delegation members (HDM) who assist them. Through a debrief-based co-autoethnographic account of a female HDM who supported Ukrainian refugee mothers and children on the Polish borders, we explored the lived experiences involved in such a mission. Specifically, we conducted a transnational dyadic autoethnography debrief-based co-autoethnography which included both verbal and photo-based debriefing (8 two-hour sessions) alongside a reflexive (10-day) field diary analysis. Content analysis revealed cognitive dilemmas, emotional struggles, and practical adaptations occurring within the HDM's three identity-related domains: personal, professional (psychologist), and ethnic. The methodology presented and demonstrated in this paper enhances our theoretical understanding of the challenges faced by HDMs and may contribute to better future design of HDM training. Practically, the findings of the current study suggest the need for a three-stage accompaniment for HDMs relating to their personal, professional, and ethnic identities and considering their cognitive, emotional, and adaptive aspects. First, before leaving, HDMs should be briefed on personal and professional aspects of their experiences and ways of coping with them, as well as ethnic and religious affiliation issues. Second, while volunteering every evening their dilemmas, emotional struggles, and ways of adapting should be addressed for the three layers of identities. And finally, shortly after their return, there should be a final meeting to discuss all aspects of their identities and layers of personality. In this way, HDMs can become more effective in the important mission they fulfill. We hope that future HDMs and the bodies that send them on humanitarian missions of paramount importance will adopt these recommendations and generate proactive insights for members of future delegations.

Keywords: autoethnography, refugees, humanitarian delegation, ambiguous loss, Russo-Ukraine War, parenting

Procedia PDF Downloads 24

Authors: Yasser Ahmed Mahmoud Ali Helal

Abstract:

The use of CAD (Computer Aided Design) technology is ubiquitous in the architecture, engineering and construction (AEC) industry. This has led to its inclusion in the curriculum of architecture schools in Nigeria as an important part of the training module. This article examines the ethical issues involved in implementing CAD (Computer Aided Design) content into the architectural education curriculum. Using existing literature, this study begins with the benefits of integrating CAD into architectural education and the responsibilities of different stakeholders in the implementation process. It also examines issues related to the negative use of information technology and the perceived negative impact of CAD use on design creativity. Using a survey method, data from the architecture department of University was collected to serve as a case study on how the issues raised were being addressed. The article draws conclusions on what ensures successful ethical implementation. Millions of people around the world suffer from hepatitis C, one of the world's deadliest diseases. Interferon (IFN) is treatment options for patients with hepatitis C, but these treatments have their side effects. Our research focused on developing an oral small molecule drug that targets hepatitis C virus (HCV) proteins and has fewer side effects. Our current study aims to develop a drug based on a small molecule antiviral drug specific for the hepatitis C virus (HCV). Drug development using laboratory experiments is not only expensive, but also time-consuming to conduct these experiments. Instead, in this in silicon study, we used computational techniques to propose a specific antiviral drug for the protein domains of found in the hepatitis C virus. This study used homology modeling and abs initio modeling to generate the 3D structure of the proteins, then identifying pockets in the proteins. Acceptable lagans for pocket drugs have been developed using the de novo drug design method. Pocket geometry is taken into account when designing ligands. Among the various lagans generated, a new specific for each of the HCV protein domains has been proposed.

Keywords: drug design, anti-viral drug, in-silicon drug design, hepatitis C virus (HCV) CAD (Computer Aided Design), CAD education, education improvement, small-size contractor automatic pharmacy, PLC, control system, management system, communication

Procedia PDF Downloads 45

Authors: Kirill Filianin, Satu-Pia Reinikainen, Tuomo Sainio

Abstract:

Frequent measurements of product steam quality create a data overload that becomes more and more difficult to handle. In the current study, plant history data with multiple variables was successfully treated by principal component analysis to detect abnormal process behavior, particularly, in copper solvent extraction. The multivariate model is based on the concentration levels of main process metals recorded by the industrial on-stream x-ray fluorescence analyzer. After mean-centering and normalization of concentration data set, two-dimensional multivariate model under principal component analysis algorithm was constructed. Normal operating conditions were defined through control limits that were assigned to squared score values on x-axis and to residual values on y-axis. 80 percent of the data set were taken as the training set and the multivariate model was tested with the remaining 20 percent of data. Model testing showed successful application of control limits to detect abnormal behavior of copper solvent extraction process as early warnings. Compared to the conventional techniques of analyzing one variable at a time, the proposed model allows to detect on-line a process failure using information from all process variables simultaneously. Complex industrial equipment combined with advanced mathematical tools may be used for on-line monitoring both of process streams’ composition and final product quality. Defining normal operating conditions of the process supports reliable decision making in a process control room. Thus, industrial x-ray fluorescence analyzers equipped with integrated data processing toolbox allows more flexibility in copper plant operation. The additional multivariate process control and monitoring procedures are recommended to apply separately for the major components and for the impurities. Principal component analysis may be utilized not only in control of major elements’ content in process streams, but also for continuous monitoring of plant feed. The proposed approach has a potential in on-line instrumentation providing fast, robust and cheap application with automation abilities.

Keywords: abnormal process behavior, failure detection, principal component analysis, solvent extraction

Procedia PDF Downloads 288

Authors: Adel Khorramrouz, Monireh Ahmadi Bani, Ehsan Norouzi

Abstract:

Background:-Due to the essential role of the foot in movement, foot disorders (FDs) have significant impacts on activity and quality of life. Many studies confirmed the association between FDs and demographic characteristics. On the other hand, recent advances in data collection and statistical analysis led to an increase in the volume of databases. Analysis of patient’s data through the decision tree can be used to explore the relationship between demographic characteristics and FDs. Significance of the study: This study aimed to investigate the relationship between demographic characteristics with common FDs. The second purpose is to better inform foot intervention, we classify FDs based on demographic variables. Methodologies: We analyzed 2323 subjects with pes-planus (PP), pes-cavus (PC), hallux-valgus (HV) and plantar-fasciitis (PF) who were referred to a foot therapy clinic between 2015 and 2021. Subjects had to fulfill the following inclusion criteria: (1) weight between 14 to 150 kilogram, (2) height between 30 to 220, (3) age between 3 to 100 years old, and (4) BMI between 12 to 35. Medical archives of 2323 subjects were recorded retrospectively and all the subjects examined by an experienced physician. Age and BMI were classified into five and four groups, respectively. 80% of the data were randomly selected as training data and 20% tested. We build a decision tree model to classify FDs using demographic characteristics. Findings: Results demonstrated 981 subjects from 2323 (41.9%) of people who were referred to the clinic with FDs were diagnosed as PP, 657 (28.2%) PC, 628 (27%) HV and 213 (9%) identified with PF. The results revealed that the prevalence of PP decreased in people over 18 years of age and in children over 7 years. In adults, the prevalence depends first on BMI and then on gender. About 10% of adults and 81% of children with low BMI have PP. There is no relationship between gender and PP. PC is more dependent on age and gender. In children under 7 years, the prevalence was twice in girls (10%) than boys (5%) and in adults over 18 years slightly higher in men (62% vs 57%). HV increased with age in women and decreased in men. Aging and obesity have increased the prevalence of PF. We conclude that the accuracy of our approach is sufficient for most research applications in FDs. Conclusion:-The increased prevalence of PP in children is probably due to the formation of the arch of the foot at this age. Increasing BMI by applying high pressure on the foot can increase the prevalence of this disorder in the foot. In PC, the Increasing prevalence of PC from women to men with age may be due to genetics and innate susceptibility of men to this disorder. HV is more common in adult women, which may be due to environmental reasons such as shoes, and the prevalence of PF in obese adult women may also be due to higher foot pressure and housekeeping activities.

Keywords: decision tree, demographic characteristics, foot disorders, machine learning

Procedia PDF Downloads 240

Authors: Sylvie Michel, Emmanuelle Gagnou, Joanne Hamet

Abstract:

New major ethical dilemmas are posed by artificial intelligence. This article identifies an existing gap between the ethical questions that AI/robotics researchers grapple with in their research practice and those identified by literature review. The objective is to understand which ethical dilemmas are identified or concern AI researchers in order to compare them with the existing literature. This will enable to conduct training and awareness initiatives for AI researchers, encouraging them to consider these questions during the development of AI. Qualitative analyses were conducted based on direct observation of an AI/Robotics research team focused on collaborative robotics over several months. Subsequently, semi-structured interviews were conducted with 16 members of the team. The entire process took place during the first semester of 2023. The observations were analyzed using an analytical framework, and the interviews were thematically analyzed using Nvivo software. While the literature identifies three primary ethical concerns regarding AI—transparency, bias, and responsibility—the results firstly demonstrate that AI researchers are primarily concerned with the publication and valorization of their work, with the initial ethical concerns revolving around this matter. Questions arise regarding the extent to which to "market" publications and the usefulness of some publications. Research ethics are a central consideration for these teams. Secondly, another result shows that the researchers studied adopt a consequentialist ethics (though not explicitly formulated as such). They ponder the consequences of their development in terms of safety (for humans in relation to Robots/AI), worker autonomy in relation to the robot, and the role of work in society (can robots take over jobs?). Lastly, results indicate that the ethical dilemmas highlighted in the literature (responsibility, transparency, bias) do not explicitly appear in AI/Robotics research. AI/robotics researchers raise specific and pragmatic ethical questions, primarily concerning publications initially and consequentialist considerations afterward. Results demonstrate that these concerns are distant from the existing literature. However, the dilemmas highlighted in the literature also deserve to be explicitly contemplated by researchers. This article proposes that the journals these researchers target should mandate ethical reflection for all presented works. Furthermore, results suggest offering awareness programs in the form of short educational sessions for researchers.

Keywords: ethics, artificial intelligence, research, robotics

Procedia PDF Downloads 55

Authors: Margot Whitfield, Andrea Ducent, Marie Catherine Rombaut, Katia Iassinovskaia, Deborah Fels

Abstract:

Learning how to create inclusive media, such as closed captioning (CC) and audio description (AD), in North America is restricted to the private sector, proprietary company-based training. We are delivering (through synchronous and asynchronous online learning) the first Canadian post-secondary, practice-based continuing education course package in inclusive media for broadcast production and processes. Despite the prevalence of CC and AD taught within the field of translation studies in Europe, North America has no comparable field of study. This novel approach to audio visual translation (AVT) education develops evidence-based methodology innovations, stemming from user study research with blind/low vision and Deaf/hard of hearing audiences for television and theatre, undertaken at Ryerson University. Knowledge outcomes from the courses include a) Understanding how CC/AD fit within disability/regulatory frameworks in Canada. b) Knowledge of how CC/AD could be employed in the initial stages of production development within broadcasting. c) Writing and/or speaking techniques designed for media. d) Hands-on practice in captioning re-speaking techniques and open source technologies, or in AD techniques. e) Understanding of audio production technologies and editing techniques. The case study of the curriculum development and deployment, involving first-time online course delivery from academic and practitioner-based instructors in introductory Captioning and Audio Description courses (CDIM 101 and 102), will compare two different instructors' approaches to learning design, including the ratio of synchronous and asynchronous classroom time and technological engagement tools on meeting software platform such as breakout rooms and polling. Student reception of these two different approaches will be analysed using qualitative thematic and quantitative survey analysis. Thus far, anecdotal conversations with students suggests that they prefer synchronous compared with asynchronous learning within our hands-on online course delivery method.

Keywords: inclusive media theory, broadcasting practices, AVT post secondary education, respeaking, audio description, learning design, virtual education

Procedia PDF Downloads 165

Authors: Nassima Noufail, Sara Bouhali

Abstract:

In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

Procedia PDF Downloads 53

Authors: Diane M. Bender

Abstract:

In architecture and design education, students learn and understand their discipline through lecture courses and within studios. A studio is where the instructor works closely with students to help them understand design by doing design work. The final jury is the culmination of the studio learning experience. It’s value and significance are rarely questioned. Students present their work before their peers, instructors, and invited reviewers, known as jurors. These jurors are recognized experts who add a breadth of feedback to students mostly in the form of a verbal critique of the work. Since the design review or jury has been a common element of studio education for centuries, jurors themselves have been instructed in this format. Therefore, they understand its value from both a student and a juror perspective. To better understand how these reviewers see the value of a studio review, a survey was distributed to reviewers at a multi-disciplinary design school within the United States. Five design disciplines were involved in this case study: architecture, graphic design, industrial design, interior design, and landscape architecture. Respondents (n=108) provided written comments about their perceived value of the studio review system. The average respondent was male (64%), between 40-49 years of age, and has attained a master’s degree. Qualitative analysis with thematic coding revealed several themes. Reviewers view the final jury as important because it provides a variety of perspectives from unbiased external practitioners and prepares students for similar presentation challenges they will experience in professional practice. They also see it as a way to validate the assessment and evaluation of students by faculty. In addition, they see a personal benefit for themselves and their firm – the ability to network with fellow jurors, professors, and students (i.e., future colleagues). Respondents also provided additional feedback about the jury system and studio education in general. Typical responses included a desire for earlier engagement with students; a better explanation from the instructor about the project parameters, rubrics/grading, and guidelines for juror involvement; a way to balance giving encouraging feedback versus overly critical comments; and providing training for jurors prior to reviews. While this study focused on the studio review, the findings are equally applicable to other disciplines. Suggestions will be provided on how to improve the preparation of guests in the learning process and how their interaction can positively influence student engagement.

Keywords: assessment, design, jury, studio

Procedia PDF Downloads 46

Authors: Richard Roberts, Anna Kravtcova

Abstract:

Introduction: The realisation that personality can change over the course of a lifetime has led to a new companion model to the Big Five, the behavioural, emotional, and social skills approach (BESSA). BESSA hypothesizes that this set of skills represents how the individual is thinking, feeling, and behaving when the situation calls for it, as opposed to traits, which represent how someone tends to think, feel, and behave averaged across situations. The five major skill domains share parallels with the Big Five Factor (BFF) model creativity and innovation (openness), self-management (conscientiousness), social engagement (extraversion), cooperation (agreeableness), and emotional resilience (emotional stability) skills. We point to noteworthy limitations in the current operationalisation of BESSA skills (i.e., via Likert-type items) and offer up a different measurement approach: forced choice. Method: In this forced-choice paradigm, individuals were given three skill items (e.g., managing my time) and asked to select one response they believed they were “worst at” and “best at”. The Thurstonian IRT models allow these to be placed on a normative scale. Two multivariate studies (N = 1178) were conducted with a 22-item forced-choice version of the BESSA, a published measure of the BFF, and various criteria. Findings: Confirmatory factor analysis of the forced-choice assessment showed acceptable model fit (RMSEA<0.06), while reliability estimates were reasonable (around 0.70 for each construct). Convergent validity evidence was as predicted (correlations between 0.40 and 0.60 for corresponding BFF and BESSA constructs). Notable was the extent the forced-choice BESSA assessment improved upon test-criterion relationships over and above the BFF. For example, typical regression models find BFF personality accounting for 25% of the variance in life satisfaction scores; both studies showed incremental gains over the BFF exceeding 6% (i.e., BFF and BESSA together accounted for over 31% of the variance in both studies). Discussion: Forced-choice measurement models offer up the promise of creating equated test forms that may unequivocally measure skill gains and are less prone to fakability and reference bias effects. Implications for practitioners are discussed, especially those interested in selection, succession planning, and training and development. We also discuss how the forced choice method can be applied to other constructs like emotional immunity, cross-cultural competence, and self-estimates of cognitive ability.

Keywords: Big Five, forced-choice method, BFF, methods of measurements

Procedia PDF Downloads 71

Authors: Ndibarefinia Tobin

Abstract:

The UK construction industry has been under pressure for many years to produce economical buildings which offer value for money, not only during the construction phase, but more importantly, during the full life of the building. Whole life costing is considered as an economic analysis tool that takes into account the total investment cost in and ownership, operation and subsequent disposal of a product or system to which the whole life costing method is being applied. In spite of its importance, the practice is still crippled by the lack of tangible evidence, ‘know-how’ skills and knowledge of the practice i.e. the lack of professionals with the knowledge and training on the use of the practice in construction project, this situation is compounded by the absence of available data on whole life costing from relevant projects, lack of data collection mechanisms and so on. The aforementioned problems has forced many construction organisations to adopt project enhancement initiatives to boost their performance on the use of whole life costing techniques so as to produce economical buildings which offer value for money during the construction stage also the whole life of the building/asset. The management of knowledge in whole life costing is considered as one of the many project enhancement initiative and it is becoming imperative in the performance and sustainability of an organisation. Procuring building projects using whole life costing technique is heavily reliant on the knowledge, experience, ideas and skills of workers, which comes from many sources including other individuals, electronic media and documents. Due to the diversity of knowledge, capabilities and skills of employees that vary across an organisation, it is significant that they are directed and coordinated efficiently so as to capture, retrieve and share knowledge in order to improve the performance of the organisation. The implementation of knowledge management concept has different levels in each organisation. Measuring the maturity level of knowledge management in whole life costing practice will paint a comprehensible picture of how knowledge is managed in construction organisations. Purpose: The purpose of this study is to identify knowledge management maturity in UK construction organisations adopting whole life costing in construction project. Design/methodology/approach: This study adopted a survey method and conducted by distributing questionnaires to large construction companies that implement knowledge management activities in whole life costing practice in construction project. Four level of knowledge management maturity was proposed on this study. Findings: From the results obtained in the study shows that 34 contractors at the practiced level, 26 contractors at managed level and 12 contractors at continuously improved level.

Keywords: knowledge management, whole life costing, construction industry, knowledge

Procedia PDF Downloads 231

Authors: Leila Sadeghi

Abstract:

Gender equality is a critical concern in the workplace, particularly in Iran, where legal and social barriers contribute to significant disparities. This abstract presents a case study of Dahi Bondad Co., a company based in Tehran, Iran that recognized the urgency of addressing the gender gap within its organization. Through a comprehensive investigation, the company identified issues related to biased recruitment, pay disparities, promotion biases, internal barriers, and everyday boundaries. This abstract highlights the strategies implemented by Dahi Bondad Co. to combat these challenges and foster gender equality. The company revised its recruitment policies, eliminated gender-specific language in job advertisements, and implemented blind resume screening to ensure equal opportunities for all applicants. Comprehensive pay equity analyses were conducted, leading to salary adjustments based on qualifications and experience to rectify pay disparities. Clear and transparent promotion criteria were established, and training programs were provided to decision-makers to raise awareness about unconscious biases. Additionally, mentorship and coaching programs were introduced to support female employees in overcoming self-limiting beliefs and imposter syndrome. At the same time, practical workshops and gamification techniques were employed to boost confidence and encourage women to step out of their comfort zones. The company also recognized the importance of dress codes and allowed optional hijab-wearing, respecting local traditions while promoting individual freedom. As a result of these strategies, Dahi Bondad Co. successfully fostered a more equitable and empowering work environment, leading to increased job satisfaction for both male and female employees within a short timeframe. This case study serves as an example of practical approaches that human resource managers can adopt to address gender inequality in the workplace, providing valuable insights for organizations seeking to promote gender equality in similar contexts.

Keywords: gender equality, human resource strategies, legal barrier, social barrier, successful result, successful strategies, workplace in Iran

Procedia PDF Downloads 54

Authors: Rubina Jahan, Mohammad Zayeed Bin Alam, Sazzad Chowdhury, Sadia Chowdhury

Abstract:

Access to mental health services in Bangladesh is a tale of urban privilege and rural struggle. Mental health services in the country are primarily centered in urban medical hospitals, with only 260 psychiatrists for a population of more than 162 million, while rural populations face far more severe and daunting challenges. In alignment with the World Health Organization's perspective on mental health as a basic human right and a crucial component for personal, community, and socioeconomic development; SAJIDA Foundation a value driven non-government organization in Bangladesh has introduced a Community Based Mental Health (CMHI) program to fill critical gaps in mental health care, providing accessible and affordable community-based services to protect and promote mental health, offering support for those grappling with mental health conditions. The CMHI programme is being implemented in 3 districts in Bangladesh, 2 of them are remote and most climate vulnerable areas targeting total 6,797 individual. The intervention plan involves a screening of all participants using a 10-point vulnerability assessment tool to identify vulnerable individuals. The assumption underlying this is that individuals assessed as vulnerable is primarily due to biological, psychological, social and economic factors and they are at an increased risk of developing common mental health issues. Those identified as vulnerable with high risk and emergency conditions will receive Mental Health First Aid (MHFA) and undergo further screening with GHQ-12 to be identified as cases and non-cases. The identified cases are then referred to community lay counsellors with basic training and knowledge in providing 4-6 sessions on problem solving or behavior activation. In situations where no improvement occurs post lay counselling or for individuals with severe mental health conditions, a referral process will be initiated, directing individuals to ensure appropriate mental health care. In our presentation, it will present the findings from 6-month pilot implementation focusing on the community-based screening versus outcome of the lay counseling session and barriers and facilitators of implementing community based mental health care in a resource constraint country like Bangladesh.

Keywords: community-based mental health, lay counseling, rural bangladesh, treatment gap

Procedia PDF Downloads 12

Authors: Krzysztof J. Czarnocki, F. Silveira, E. Czarnocka, K. Szaniawska

Abstract:

Research background: Problems related to the occupational health and decreasing level of safety occur commonly in the construction industry. Important factor in the occupational safety in construction industry is scaffold use. All scaffolds used in construction, renovation, and demolition shall be erected, dismantled and maintained in accordance with safety procedure. Increasing demand for new construction projects unfortunately still is linked to high level of occupational accidents. Therefore, it is crucial to implement concrete actions while dealing with scaffolds and risk assessment in construction industry, the way on doing assessment and liability of assessment is critical for both construction workers and regulatory framework. Unfortunately, professionals, who tend to rely heavily on their own experience and knowledge when taking decisions regarding risk assessment, may show lack of reliability in checking the results of decisions taken. Purpose of the article: The aim was to indicate crucial parameters that could be modeling with Risk Assessment Model (RAM) use for improving both building enterprise productivity and/or developing potential and safety climate. The developed RAM could be a benefit for predicting high-risk construction activities and thus preventing accidents occurred based on a set of historical accident data. Methodology/Methods: A RAM has been developed for assessing risk levels as various construction process stages with various work trades impacting different spheres of enterprise activity. This project includes research carried out by teams of researchers on over 60 construction sites in Poland and Portugal, under which over 450 individual research cycles were carried out. The conducted research trials included variable conditions of employee exposure to harmful physical and chemical factors, variable levels of stress of employees and differences in behaviors and habits of staff. Genetic modeling tool has been used for developing the RAM. Findings and value added: Common types of trades, accidents, and accident causes have been explored, in addition to suitable risk assessment methods and criteria. We have found that the initial worker stress level is more direct predictor for developing the unsafe chain leading to the accident rather than the workload, or concentration of harmful factors at the workplace or even training frequency and management involvement.

Keywords: safety climate, occupational health, civil engineering, productivity

Procedia PDF Downloads 289

Authors: Christian Neunzig, Simon Fahle, Jürgen Schulz, Matthias Möller, Bernd Kuhlenkötter

Abstract:

Digitalisation in production technology is a driver for the application of machine learning methods. Through the application of predictive quality, the great potential for saving necessary quality control can be exploited through the data-based prediction of product quality and states. However, the serial use of machine learning applications is often prevented by various problems. Fluctuations occur in real production data sets, which are reflected in trends and systematic shifts over time. To counteract these problems, data preprocessing includes rule-based data cleaning, the application of dimensionality reduction techniques, and the identification of comparable data subsets to extract stable features. Successful process control of the target variables aims to centre the measured values around a mean and minimise variance. Competitive leaders claim to have mastered their processes. As a result, much of the real data has a relatively low variance. For the training of prediction models, the highest possible generalisability is required, which is at least made more difficult by this data availability. The implementation of a machine learning application can be interpreted as a production process. The CRoss Industry Standard Process for Data Mining (CRISP-DM) is a process model with six phases that describes the life cycle of data science. As in any process, the costs to eliminate errors increase significantly with each advancing process phase. For the quality prediction of hydraulic test steps of directional control valves, the question arises in the initial phase whether a regression or a classification is more suitable. In the context of this work, the initial phase of the CRISP-DM, the business understanding, is critically compared for the use case at Bosch Rexroth with regard to regression and classification. The use of cross-process production data along the value chain of hydraulic valves is a promising approach to predict the quality characteristics of workpieces. Suitable methods for leakage volume flow regression and classification for inspection decision are applied. Impressively, classification is clearly superior to regression and achieves promising accuracies.

Keywords: classification, CRISP-DM, machine learning, predictive quality, regression

Procedia PDF Downloads 120

Authors: Ella Sèdé Maforikan

Abstract:

Accurate land cover mapping is essential for effective environmental monitoring and natural resources management. This study focuses on assessing the classification performance of two satellite datasets and evaluating the impact of different input feature combinations on classification accuracy in the Beterou catchment, situated in the northern part of Benin. Landsat-8 and Sentinel-2 images from June 1, 2020, to March 31, 2021, were utilized. Employing the Random Forest (RF) algorithm on Google Earth Engine (GEE), a supervised classification categorized the land into five classes: forest, savannas, cropland, settlement, and water bodies. GEE was chosen due to its high-performance computing capabilities, mitigating computational burdens associated with traditional land cover classification methods. By eliminating the need for individual satellite image downloads and providing access to an extensive archive of remote sensing data, GEE facilitated efficient model training on remote sensing data. The study achieved commendable overall accuracy (OA), ranging from 84% to 85%, even without incorporating spectral indices and terrain metrics into the model. Notably, the inclusion of additional input sources, specifically terrain features like slope and elevation, enhanced classification accuracy. The highest accuracy was achieved with Sentinel-2 (OA = 91%, Kappa = 0.88), slightly surpassing Landsat-8 (OA = 90%, Kappa = 0.87). This underscores the significance of combining diverse input sources for optimal accuracy in land cover mapping. The methodology presented herein not only enables the creation of precise, expeditious land cover maps but also demonstrates the prowess of cloud computing through GEE for large-scale land cover mapping with remarkable accuracy. The study emphasizes the synergy of different input sources to achieve superior accuracy. As a future recommendation, the application of Light Detection and Ranging (LiDAR) technology is proposed to enhance vegetation type differentiation in the Beterou catchment. Additionally, a cross-comparison between Sentinel-2 and Landsat-8 for assessing long-term land cover changes is suggested.

Keywords: land cover mapping, Google Earth Engine, random forest, Beterou catchment

Procedia PDF Downloads 35

Authors: Salma Akter, Md. Kamal Uddin

Abstract:

Ashrayan (shelter) Prakalpa – a fully subsidized ‘integrated poverty eradication program’ through the provisioning of shelter of Bangladesh Government (GoB) targeting the internally displaced and homeless. In spite of the inclusiveness (poverty alleviation, employment opportunity, Tenure ship and training) of the shelter policy, dwellers are not merely questioned by the issue of 'the quality of life' .This study demonstrates how top-down policies, ambiguous ownership status of land and dwelling environments lead to ‘everyday compromise’ by the grassroots in both subjective (satisfaction, comfort and safety) and objective (physical design elements and physical environmental elements) issues in three respective scale macro (neighborhood) meso (shelter /built environment) and micro(family). It shows that by becoming subject to Government’s resettlements policies and after becoming user of its shelter units (although locally known as ‘barracks’ rather shelter or housing), the once displaced settlers assume a curious form of spatial practice where both social and spatial often bear slippery meanings. Thus, Policy-based shelter force the dwellers frequently compromise with their provided built environments and spaces within the settlements both in overtly and covertly. Compromises are made during the production of space and forms, whereas interesting new spaces and space-making practices emerge. The settlements under study are Dakshin Chandani Mahal Ashrayan Prakalpa located at the Eastern fringe area of Khulna, Bangladesh. In terms of methodology, this research is primarily exploratory and assumes a qualitative approach. Key tools used to obtain information are policy analysis, literature review, key informant interview, focus group discussion and participant observation at the level of dwelling and settlements. Necessary drawings and photographs have been taken to promote the study objective. Findings revealed that various shortages, inadequacies and negligence of policymakers make a compromising character of displaced by the means of 'quality of life' both in objective and subjective ground. Thus the study ends up with a recommendation to the policymakers to take an initiative to ensure the quality of life of the dwellers.

Keywords: Ashrayan, compromise, displaced people, quality of life

Procedia PDF Downloads 315

Authors: Meghan E. Murray, Carri R. Tolmie

Abstract:

This study aims to identify potential factors and widely applicable best practices that can contribute to improving corporate social responsibility (CSR) and corporate performance for firms by exploring the relationship between transformational leadership, spiritual intelligence, and emotional intelligence. Corporate social responsibility is when companies are cognizant of the impact of their actions on the economy, their communities, the environment, and the world as a whole while executing business practices accordingly. The prevalence of CSR has continuously strengthened over the past few years and is now a common practice in the business world, with such efforts coinciding with what stakeholders and the public now expect from corporations. Because of this, it is extremely important to be able to pinpoint factors and best practices that can improve CSR within corporations. One potential factor that may lead to improved CSR is spiritual intelligence (SQ), or the ability to recognize and live with a purpose larger than oneself. Spiritual intelligence is a measurable skill, just like emotional intelligence (EQ), and can be improved through purposeful and targeted coaching. This research project consists of two studies. Study 1 is a case study comparison of a benefit corporation and a non-benefit corporation. This study will examine the role of SQ and EQ as moderators in the relationship between the transformational leadership of employees within each company and the perception of each firm’s CSR and corporate performance. Project methodology includes creating and administering a survey comprised of multiple pre-established scales on transformational leadership, spiritual intelligence, emotional intelligence, CSR, and corporate performance. Multiple regression analysis will be used to extract significant findings from the collected data. Study 2 will dive deeper into spiritual intelligence itself by analyzing pre-existing data and identifying key relationships that may provide value to companies and their stakeholders. This will be done by performing multiple regression analysis on anonymized data provided by Deep Change, a company that has created an advanced, proprietary system to measure spiritual intelligence. Based on the results of both studies, this research aims to uncover best practices, including the unique contribution of spiritual intelligence, that can be utilized by organizations to help enhance their corporate social responsibility. If it is found that high spiritual and emotional intelligence can positively impact CSR effort, then corporations will have a tangible way to enhance their CSR: providing targeted employees with training and coaching to increase their SQ and EQ.

Keywords: corporate social responsibility, CSR, corporate performance, emotional intelligence, EQ, spiritual intelligence, SQ, transformational leadership

Procedia PDF Downloads 106

Authors: C. Brandt, R. Christopher, N. Damons

Abstract:

Background: Soccer is one of the most common sports in the world. It is associated with a significant chance of injury either during training or during the course of an actual match. Studies on the epidemiology of soccer injuries have been widely conducted, but methodological appraisal is lacking to make evidence-based decisions. Objectives: The purpose of this study was to conduct a systematic review of common injuries in soccer and their risk factors. Methods: A systematic review was performed based on the Joanna Briggs Institute procedure for conducting systematic reviews. Databases such as SPORT Discus, Cinahl, Medline, Science Direct, PubMed, and grey literature were searched. The quality of selected studies was rated, and data extracted and tabulated. Plot data analysis was done, and incidence rates and odds ratios were calculated, with their respective 95% confidence intervals. I² statistic was used to determine the proportion of variation across studies. Results: The search yielded 62 studies, of which 21 were screened for inclusion. A total of 16 studies were included for the analysis, ten for qualitative and six for quantitative analysis. The included studies had, on average, a low risk of bias and good methodological quality. The heterogeneity amongst the pooled studies was, however, statistically significant (χ²-p value < 0.001). The pooled results indicated a high incidence of soccer injuries at an incidence rate of 6.83 per 1000 hours of play. The pooled results also showed significant evidence of risk factors and the likelihood of injury occurrence in relation to these risk factors (OR=1.12 95% CI 1.07; 1.17). Conclusion: Although multiple studies are available on the epidemiology of soccer injuries and risk factors, only a limited number of studies were of sound methodology to be included in a review. There was also significant heterogeneity amongst the studies. The incidence rate of common soccer injuries was found to be 6.83 per 1000 hours of play. This incidence rate is lower than the values reported by the majority of previous studies on the occurrence of common soccer injuries. The types of common soccer injuries found by this review support the soccer injuries pattern reported in existing literature as muscle strain and ligament sprain of varying severity, especially in the lower limbs. The risk factors that emerged from this systematic review are predominantly intrinsic risk factors. The risk factors increase the risk of traumatic and overuse injuries of the lower extremities such as hamstrings and groin strains, knee and ankle sprains, and contusion.

Keywords: incidence, prevalence, risk factors, soccer injuries

Procedia PDF Downloads 165

Authors: Thippharat Wongsilarat, Parichat tuntilanon, Chonlakan Prataksitorn

Abstract:

Recurrent adverse drug reactions are harmful to patients with mild to fatal illnesses, and affect not only patients but also their relatives, and organizations. To compare safe use of medicine among patients before and after using the recurrent adverse drug reaction prevention program . Quasi-experimental research with the target population of 598 patients with drug allergy history. Data were collected through an observation form tested for its validity by three experts (IOC = 0.87), and analyzed with a descriptive statistic (percentage). The research was conducted jointly with a multidisciplinary team to analyze and determine the weak points and strong points in the recurrent adverse drug reaction prevention system during the past three years, and 546, 329, and 498 incidences, respectively, were found. Of these, 379, 279, and 302 incidences, or 69.4; 84.80; and 60.64 percent of the patients with drug allergy history, respectively, were found to have caused by incomplete warning system. In addition, differences in practice in caring for patients with drug allergy history were found that did not cover all the steps of the patient care process, especially a lack of repeated checking, and a lack of communication between the multidisciplinary team members. Therefore, the recurrent adverse drug reaction prevention program was developed with complete warning points in the information technology system, the repeated checking step, and communication among related multidisciplinary team members starting from the hospital identity card room, patient history recording officers, nurses, physicians who prescribe the drugs, and pharmacists. Including in the system were surveillance, nursing, recording, and linking the data to referring units. There were also training concerning adverse drug reactions by pharmacists, monthly meetings to explain the process to practice personnel, creating safety culture, random checking of practice, motivational encouragement, supervising, controlling, following up, and evaluating the practice. The rate of prescribing drugs to which patients were allergic per 1,000 prescriptions was 0.08, and the incidence rate of recurrent drug reaction per 1,000 prescriptions was 0. Surveillance of recurrent adverse drug reactions covering all service providing points can ensure safe use of medicine for patients.

Keywords: recurrent drug, adverse reaction, safety, use of medicine

Procedia PDF Downloads 434

Authors: Jamila Fakchich, Mostafa Jamila Lazaar Elachouri, Lakhder Fakchich, Fatna Ouali, Abd Errazzak Belkacem

Abstract:

Diabetes is a chronic metabolic disease that has a significant impact on the health, quality of life, and life expectancy of patients as well as the health care system. By its nature diabetes, is a multisystem disease with wide-ranging complication that span nearly all region of the body. This epidemic problem, however, is not unique to the industrialized society, but has also hardly struck the developing countries. In Morocco, as developing country, there is an epidemic rise in diabetes, with ensuing concern about the management and control of this disease; it began a chronic burdensome disease of largely middle-aged and elderly people, with a long course and serious complications often resulting in high death-rate, the treatment of diabetes spent vast amount of resources including medicines, diets, physical training. Treatment of this disease is considered problematic due to the lack of effective and safe drugs capable of inducing sustained clinical, biochemical, and histological cure. In Moroccan society, the phytoremedies are some times the only affordable sources of healthcare, particularly for the people in remote areas. In this paper, we present a synthesis work obtained from the ethnobotanical data reported in different specialized journals. A Synthesis of four published ethnobotanical studies that have been carried out in different region of Morocco by different team seekers during the period from 1997 to 2015. Medicinal plants inventoried by different seekers in four Moroccan’s areas have been regrouped and codified, then, Factorial Analysis (FA) and Principal Components Analysis (PCA) are used to analyse the aggregated data from the four studies and plants are classified according to their frequency of use by population. Our work deals with an attempt to gather information on some traditional uses of medicinal plants from different regions of Morocco, also, it was designed to give a set of medicinal plants commonly used by Moroccan people in the treatment of diabetes; In this paper, we intended to provide a basic knowledge about plant species used by Moroccan society for treatment of diabetes. One of the most interesting aspects of this type of works is to assess the relative cultural importance of medicinal plants for specific illnesses and exploring its usefulness in the context of diabetes.

Keywords: Morocco, medicinal plants, ethnobotanical, diabetes, phytoremedies

Procedia PDF Downloads 306

Authors: Dawa Wangmo

Abstract:

The anti-religious campaigns of the Soviet Union in the 1930s eradicated Kalmyk Buddhism from the public sphere. Following Perestroika, the Kalmyks retained a sense of being essentially Buddhist people. Nevertheless, since the collapse of the Soviet Communist regime, Kalmykia has been going through vigorous ethnic and cultural revitalization. The new Kalmyk government is reviving the religion with the building of Buddhist temples and the attempted training of Kalymk monks. Kalmykia, officially an autonomous republic within the Federation of Russia, is situated in the European part of Russia in the steppe region bordering the Caspian Sea in its southeast. According to the 2010 census, the Kalmyks, a people of Mongolian origin, constitute over 57 percent of the Republic’s population of less than 290000. Russians living in Kalmykia comprise around 30 percent, the remainder being various Slavic and Asian groups. Since the Kalmyks historically adhere to Buddhism, Kalmykia is often described in tourist brochures and proudly by the Kalmyks themselves as one of the three “traditional Buddhist republics” of Russia and “the only Buddhist region” in Europe. According to traditional Kalmyk Gelug Buddhism, monasticism is the central aspect; hence monastic Tibetans from India have been invited to the Republic to help revive Buddhism and their Buddhist identity in Russia as a whole. However, for the young post-soviets, the monastic way of life is proving too alien, and the subsequent labeling by these monks of ‘surviving’ Kalmyk Buddhist practices as superstitious, mistaken, or corrupt is an initial step in the purification of alternate views, leading to religious reform. This sentiment is also felt by younger Kalmyks who do not find sense in surviving Buddhism but believe more in the philosophical approach of Buddhism taught by the visiting Buddhist teachers at Dharma centers. By discussing this post-soviet shift in local notions of religious efficacy, an attempt will be made to shed light on how the social movements of both reform and revival arise as a collusion between contemporary Tibetan and Kalmyk views on the nature of true Buddhism. This work explores aspects of religious innovation that have developed since the early 1990s in the process of reconstitution of ethnic and religious identity in Kalmykia, a Republic in the southwest of Russia. Any attempts to study the history of Buddhism in Kalmykia would surely mean studying the “History of the most northern Dharma community in the World.”

Keywords: Kalmykia, Tibetan Buddhism, reform, revival, identity

Procedia PDF Downloads 53