Search results for: unsupervised training

Authors: A. Giannakopoulos, S. B. Buckley

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Problem solving in any field is recognised as a prerequisite for any advancement in knowledge. For example in South Africa it is one of the seven critical outcomes of education together with critical thinking. As a systematic way to problem solving was initiated in mathematics by the great mathematician George Polya (the father of problem solving), more detailed and comprehensive ways in problem solving have been developed. This paper is based on the findings by the author and subsequent recommendations for further research in problem solving and critical thinking. Although the study was done in mathematics, there is no doubt by now in almost anyone’s mind that mathematics is involved to a greater or a lesser extent in all fields, from symbols, to variables, to equations, to logic, to critical thinking. Therefore it stands to reason that mathematical principles and learning cannot be divorced from any field. In management of knowledge situations, the types of problems are similar to mathematics problems varying from simple to analogical to complex; from well-structured to ill-structured problems. While simple problems could be solved by employees by adhering to prescribed sequential steps (the process), analogical and complex problems cannot be proceduralised and that diminishes the capacity of the organisation of knowledge creation and innovation. The low efficiency in some organisations and the low pass rates in mathematics prompted the author to view problem solving as a product. The authors argue that using mathematical approaches to knowledge management problem solving and treating problem solving as a product will empower the employee through further training to tackle analogical and complex problems. The question the authors asked was: If it is true that problem solving and critical thinking are indeed basic skills necessary for advancement of knowledge why is there so little literature of knowledge management (KM) about them and how they are connected and advance KM?This paper concludes with a conceptual model which is based on general accepted principles of knowledge acquisition (developing a learning organisation), knowledge creation, sharing, disseminating and storing thereof, the five pillars of knowledge management (KM). This model, also expands on Gray’s framework on KM practices and problem solving and opens the doors to a new approach to training employees in general and domain specific areas problems which can be adapted in any type of organisation.

Keywords: critical thinking, knowledge management, mathematics, problem solving

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Authors: Helen Coronel, Will Brewer, Peggy Bergeron, Clarissa Hall, Victoria Casson

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Simulation-based training provides the nurse practitioner (NP) student with a safe and controlled environment in which they can practice a real-life scenario. This type of learning fosters critical thinking skills essential to practice. The expectation of this study was that students would have an increase in their competency and confidence after performing the simulation. Approximately 8.4% of Americans suffer from depression. The state of Alabama is ranked 47th out of 50 for access to mental health care. As a result of this significant shortage of mental health providers, primary care providers are frequently put in the position of screening for and treating mental health conditions, such as depression. Family nurse practitioners are often utilized as primary care providers, making their ability to assess, diagnose and treat these disorders a necessary skill. The expected outcome of this simulation is an increase in confidence, competency and the empowerment of the nurse practitioner student’s ability to assess, diagnose and treat a common mood disorder they may encounter in practice. The Kirkpatrick Module was applied for this study. A non-experimental design using descriptive statistical analysis was utilized. The simulation was based on a common psychiatric mood disorder frequently observed in primary care and mental health clinics. Students were asked to watch a voiceover power point presentation prior to their on-campus simulation. The presentation included training on the assessment, diagnosis, and treatment of a patient with depression. Prior to the simulation, the students completed a pre-test, then participated in the simulation, and completed a post-test when done. Apple iPads were utilized to access a simulated health record. Major findings of the study support an increase in students’ competency and confidence when assessing, diagnosing, and treating an adult patient with depression.

Keywords: advanced practice, nurse practitioner, simulation, primary care, depression

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Authors: Pedram Saadati, Zahra Nazari

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Today, the role and importance of financial technology businesses in Iran have increased significantly. Although, in Iran, there is no Islamic or non-Islamic personal financial planning field of study in the universities or educational centers, the profession of personal financial planning is not defined, and there is no software introduced in this regard for advisors or consumers. The largest sales network of financial services in Iran belongs to the insurance industry, and there is an untapped market for international companies in Iran that can contribute to 130 thousand representatives in the insurance industry and 28 million families by providing training and personal financial advisory software. To the best of the author's knowledge, despite the lack of previous internal studies in this field, the present study investigates the level of readiness of the salesforce of the insurance industry to accept this career and its technology. The statistical population of the research is made up of managers, insurance sales representatives, assistants and heads of sales departments of insurance companies. An 18-minute video was prepared that introduced and taught the job of Islamic personal financial planning and explained its difference from its non-Islamic model. This video was provided to the respondents. The data collection tool was a research-made questionnaire. To investigate the factors affecting technology acceptance and job change, independent T descriptive statistics and Pearson correlation were used, and Friedman's test was used to rank the effective factors. The results indicate the mental perception and very positive attitude of the insurance industry activists towards the usefulness of this job and its technology, and the studied sample confirmed the intention of training in this knowledge. Based on research results, the change in the customer's attitude towards the insurance advisor and the possibility of increasing income are considered as the reasons for accepting. However, Restrictions on using investment opportunities due to Islamic financial services laws and the uncertainty of the position of the central insurance in this regard are considered as the most important obstacles.

Keywords: fintech, insurance, personal financial planning, wealth management

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

Procedia PDF Downloads 119

Authors: Javier Muro, Anja Linstadter, Florian Manner, Lisa Schwarz, Stephan Wollauer, Paul Magdon, Gohar Ghazaryan, Olena Dubovyk

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Monitoring the trade-off between biomass production and biodiversity in grasslands is critical to evaluate the effects of management practices across environmental gradients. New generations of remote sensing sensors and machine learning approaches can model grasslands’ characteristics with varying accuracies. However, studies often fail to cover a sufficiently broad range of environmental conditions, and evidence suggests that prediction models might be case specific. In this study, biomass production and biodiversity indices (species richness and Fishers’ α) are modeled in 150 grassland plots for three sites across Germany. These sites represent a North-South gradient and are characterized by distinct soil types, topographic properties, climatic conditions, and management intensities. Predictors used are derived from Sentinel-1 & 2 and a set of topoedaphic variables. The transferability of the models is tested by training and validating at different sites. The performance of feed-forward deep neural networks (DNN) is compared to a random forest algorithm. While biomass predictions across gradients and sites were acceptable (r2 0.5), predictions of biodiversity indices were poor (r2 0.14). DNN showed higher generalization capacity than random forest when predicting biomass across gradients and sites (relative root mean squared error of 0.5 for DNN vs. 0.85 for random forest). DNN also achieved high performance when using the Sentinel-2 surface reflectance data rather than different combinations of spectral indices, Sentinel-1 data, or topoedaphic variables, simplifying dimensionality. This study demonstrates the necessity of training biomass and biodiversity models using a broad range of environmental conditions and ensuring spatial independence to have realistic and transferable models where plot level information can be upscaled to landscape scale.

Keywords: ecosystem services, grassland management, machine learning, remote sensing

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Authors: Godfrey Muiya Mukala

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This research looks at an array of fields in Sub-Saharan Africa comprising agriculture, food enterprises, medicine, organisms genetically modified, microbiology, and nanotechnology that can be gained from biotechnological research and development. Findings into dangerous organisms, mainly bacterial germs, rickettsia, fungi, parasites, or organisms that are genetically engineered, have immensely posed questions attributed to the biological danger they bring forth to human beings and the environment because of their uncertainties. In addition, the recurrence of previously managed diseases or the inception of new diseases are connected to biosafety challenges, especially in rural set-ups in low and middle-income countries. Notably, biotechnology laboratories are required to adopt biosafety measures to protect their workforce, community, environment, and ecosystem from unforeseen materials and organisms. Sensitization and inclusion of educational frameworks for laboratory workers are essential to acquiring a solid knowledge of harmful biological agents. This is in addition to human pathogenicity, susceptibility, and epidemiology to the biological data used in research and development. This article reviews and analyzes research intending to identify the proper implementation of universally accepted practices in laboratory safety and biological hazards. This research identifies ideal microbiological methods, adequate containment equipment, sufficient resources, safety barriers, specific training, and education of the laboratory workforce to decrease and contain biological hazards. Subsequently, knowledge of standardized microbiological techniques and processes, in addition to the employment of containment facilities, protective barriers, and equipment, is far-reaching in preventing occupational infections. Similarly, reduction of risks and prevention may be attained by training, education, and research on biohazards, pathogenicity, and epidemiology of the relevant microorganisms. In this technique, medical professionals in rural setups may adopt the knowledge acquired from the past to project possible concerns in the future.

Keywords: sub-saharan africa, biotechnology, laboratory, infections, health

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Authors: Akeel A. Shah, Tong Zhang

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Computational approaches to learning the properties of materials are commonplace, motivated by the need to screen or design materials for a given application, e.g., semiconductors and energy storage. Experimental approaches can be both time consuming and costly. Unfortunately, computational approaches such as ab-initio electronic structure calculations and classical or ab-initio molecular dynamics are themselves can be too slow for the rapid evaluation of materials, often involving thousands to hundreds of thousands of candidates. Machine learning assisted approaches have been developed to overcome the time limitations of purely physics-based approaches. These approaches, on the other hand, require large volumes of data for training (hundreds of thousands on many standard data sets such as QM7b). This means that they are limited by how quickly such a large data set of physics-based simulations can be established. At high fidelity, such as configuration interaction, composite methods such as G4, and coupled cluster theory, gathering such a large data set can become infeasible, which can compromise the accuracy of the predictions - many applications require high accuracy, for example band structures and energy levels in semiconductor materials and the energetics of charge transfer in energy storage materials. In order to circumvent this problem, multi-fidelity approaches can be adopted, for example the Δ-ML method, which learns a high-fidelity output from a low-fidelity result such as Hartree-Fock or density functional theory (DFT). The general strategy is to learn a map between the low and high fidelity outputs, so that the high-fidelity output is obtained a simple sum of the physics-based low-fidelity and correction, Although this requires a low-fidelity calculation, it typically requires far fewer high-fidelity results to learn the correction map, and furthermore, the low-fidelity result, such as Hartree-Fock or semi-empirical ZINDO, is typically quick to obtain, For high-fidelity outputs the result can be an order of magnitude or more in speed up. In this work, a new multi-fidelity approach is developed, based on a graph convolutional network (GCN) combined with semi-supervised learning. The GCN allows for the material or molecule to be represented as a graph, which is known to improve accuracy, for example SchNet and MEGNET. The graph incorporates information regarding the numbers of, types and properties of atoms; the types of bonds; and bond angles. They key to the accuracy in multi-fidelity methods, however, is the incorporation of low-fidelity output to learn the high-fidelity equivalent, in this case by learning their difference. Semi-supervised learning is employed to allow for different numbers of low and high-fidelity training points, by using an additional GCN-based low-fidelity map to predict high fidelity outputs. It is shown on 4 different data sets that a significant (at least one order of magnitude) increase in accuracy is obtained, using one to two orders of magnitude fewer low and high fidelity training points. One of the data sets is developed in this work, pertaining to 1000 simulations of quinone molecules (up to 24 atoms) at 5 different levels of fidelity, furnishing the energy, dipole moment and HOMO/LUMO.

Keywords: .materials screening, computational materials, machine learning, multi-fidelity, graph convolutional network, semi-supervised learning

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: E. Oliver, A. Cebolla, A. Dominguez, A. Gonzalez-Segura, E. de la Cruz, S. Albertini, L. Ferrini, K. Kronika, T. Nilsen, R. Baños

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The main objective of MEAL is to develop a pedagogical tool aimed to help teachers and nutritionists (students and professionals) to acquire, train, promote and deliver to children basic nutritional education and healthy eating behaviours competencies. MEAL is focused on eating behaviours and not only in nutritional literacy, and will use new technologies like Information and Communication Technologies (ICTs) and serious games (SG) platforms to consolidate the nutritional competences and habits.

Keywords: nutritional education, pedagogical ICT platform, serious games, training course

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Authors: Omar Bataineh

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Total productive maintenance (TPM) is a principle-based method that aims to get a high-level production with no breakdowns, no slow running and no defects. Key principles of TPM were applied in this work to improve the performance of the glass production line at United Beverage Company in Kuwait, which is producing bottles of soft drinks. Principles such as 5S as a foundation for TPM implementation, developing a program for equipment management, Cause and Effect Analysis (CEA), quality improvement, training and education of employees were employed. After the completion of TPM implementation, it was possible to increase the Overall Equipment Effectiveness (OEE) from 23% to 40%.

Keywords: OEE, TPM, FMEA, CEA

Procedia PDF Downloads 337

Authors: Helge Rupprich, Elke Knisel

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In a time of mediazation and reduced physical movement, it is important to change passivity (akinesa) into physical activity to improve health. The approach is to encourage children, junior athletes, recreational athletes, and semi-professional athletes to do sports while attending a top sport event. The concept has the slogan: get out off your seat and move! A top sport event of a series of professional beach volleyball tournaments with 330.000 life viewers, 13,70 million cumulative reach viewers and 215,13 million advertising contacts is used as framework for different sports didactic approaches, social integrative approaches and migration valuations. An important aim is to use the big radiant power of the top sport event to extract active participants from the viewers of the top sport event. Even if it is the goal to improve physical activity, it is necessary to differentiate between the didactic approaches. The first approach contains psycho motoric exercises with children (N=158) between two and five years which was used in the project ‘largest sandbox of the city’. The second approach is social integration and promotion of activity of students (N=54) in the form of a student beach volleyball tournament. The third approach is activity in companies. It is based on the idea of health motivation of employees (N=62) in a big beach volleyball tournament. Fourth approach is to improve the sports leisure time activities of recreational athletes (N=292) in different beach volleyball tournaments. Fifthly approach is to build a foreign friendly measure which is implemented in junior athlete training with the French and German junior national team (N=16). Sixthly approach is to give semi professional athletes a tournament to develop their relation to active life. Seventh approach is social integration for disadvantaged people (N=123) in form of training with professional athletes. The top sport beach volleyball tournament had 80 athletes (N=80) and 34.000 viewers. In sum 785 athletes (N=785) did sports in 13 days. Over 34.000 viewers where counted in the first three days of top sport event. The project was evaluated positively by the City of Dresden, Politics of Saxony and the participants and will be continued in Dresden and expanded for the season 2015 in Jena.

Keywords: beach volleyball, event, sports didactic, sports project

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Authors: Theodrose Sisay, Kindie Tesfaye, Mengistu Ketema, Nigussie Dechassa, Mezegebu Getnet

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Agriculture is a sector that is very vulnerable to the effects of climate change and contributes to anthropogenic greenhouse gas (GHG) emissions in the atmosphere. By lowering emissions and adjusting to the change, it can also help to reduce climate change. Utilizing Climate-Smart Agriculture (CSA) technology that can sustainably boost productivity, improve resilience, and lower GHG emissions is crucial. This study sought to identify the CSA technologies used by farmers and assess adoption levels and factors that influence them. In order to gather information from 384 smallholder farmers in the Great Rift Valley (GRV) of Ethiopia, a cross-sectional survey was carried out. Data were analysed using percentage, chi-square test, t-test, and multivariate probit model. Results showed that crop diversification, agroforestry, and integrated soil fertility management were the most widely practiced technologies. The results of the Chi-square and t-tests showed that there are differences and significant and positive connections between adopters and non-adopters based on various attributes. The chi-square and t-test results confirmed that households who were older had higher incomes, greater credit access, knowledge of the climate, better training, better education, larger farms, higher incomes, and more frequent interactions with extension specialists had a positive and significant association with CSA technology adopters. The model result showed that age, sex, and education of the head, farmland size, livestock ownership, income, access to credit, climate information, training, and extension contact influenced the selection of CSA technologies. Therefore, effective action must be taken to remove barriers to the adoption of CSA technologies, and taking these adoption factors into account in policy and practice is anticipated to support smallholder farmers in adapting to climate change while lowering emissions.

Keywords: climate change, climate-smart agriculture, smallholder farmers, multivariate probit model

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Authors: Mohsina Aktar, Bishawjit Mallick

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Bangladesh faces the multidimensional manifestations of climate change e.g. flood, cyclone, sea level rise, drainage congestion, salinity, etc. This study aimed at to find out the community’s perception of the perceived impact of climate change on their wetland resource based livelihood, to analyze their present livelihood scenario and to find out required institutional setup to strengthen present livelihood scenario. Therefore, this study required both quantitative analysis like quantification of wetland resources, occupation, etc. and also exploratory information like policy and institutional reform. For quantitative information 200 questionnaire survey and in some cases observation survey and for socially shareable qualitative and quantitative issues case study and focus group discussion were conducted. In-Depth interview was conducted for socially non-shareable qualitative issues. The overall findings of this study have been presented maintaining a sequence- perception about climate change effect, livelihood scenario and required institutional support of the wetland community. Flood has been ranked where cyclone effect is comparatively less disastrous in this area. Heavy rainfall comes after the cyclone. Female members responded almost same about the ranking and effects of frequently occurred and devastating effects of climate change. People are much more aware of the impact of climate change. Training of Care in RVCC project helps to increase their knowledge level. If the level of education can be increased, people can fight against calamity and poverty with more confidence. People seem to overcome the problems of water logging and thus besides involving in Hydroponics (33.3%) as prime occupation in monsoon; they are also engaged in other business related activities. January to May is the low-income season for the farmers. But some people don’t want to change their traditional occupation and their age is above 45. The young earning member wants to utilize their lean income period by alternative occupation. People who do not have own land and performing water transportation or other types of occupation are now interested about Hydroponics. People who give their land on rent are now thinking about renting their land in monsoon as through that they can earn a sound amount rather than get nothing. What they require is just seed, training, and capital. Present marketing system faces the problem of communication. So this sector needed to be developed. Involvement of women in income earning activity is very low (5.1%), and 100% women are housewives. They became inferior due to their educational level and dominance of their husband. Only one NGO named BCAS (Bangladesh Center for Advanced Studies) has been found engage training facilities and advocacy for this purpose. Upazilla agricultural extension office like other GO remains inactive to give support the community for extension and improvement of Hydroponics agriculture. If the community gets proper support and inspiration, they can fight against crisis of low-income and climate change, with the Hydroponics cultivation system successfully.

Keywords: wetland community, hydroponics, climate change adaptation, livelihood

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Authors: Trevor Stephen, Joshua D. Aceves, David Guyer, Jona Jacobson

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As a profession, social work has much to offer individuals, groups, and organizations. A multidisciplinary approach to understanding and solving complex challenges and a commitment to developing and training ethical practitioners outlines characteristics of a profession embedded with leadership skills. This presentation will take an overview of the historical context of social work leadership, examine social work as a unique leadership model composed of its qualities and theories that inform effective leadership capability as it relates to our code of ethics. Reflect critically on leadership theories and their foundational comparison. Finally, a look at recommendations and implementation to social work education and practice. Similar to defining leadership, there is no universally accepted definition of social work leadership. However, some distinct traits and characteristics are essential. Recent studies help set the stage for this research proposal because they measure views on effective social work leadership among social work and non-social leaders and followers. However, this research is interested in working backward from that approach and examining social workers' leadership preparedness perspectives based solely on social work training, competencies, values, and ethics. Social workers understand how to change complex structures and challenge resistance to change to improve the well-being of organizations and those they serve. Furthermore, previous studies align with the idea of practitioners assessing their skill and capacity to engage in leadership but not to lead. In addition, this research is significant because it explores aspiring social work leaders' competence to translate social work practice into direct leadership skills. The research question seeks to answer whether social work training and competencies are sufficient to determine whether social workers believe they possess the capacity and skill to engage in leadership practice. Aim 1: Assess whether social workers have the capacity and skills to assume leadership roles. Aim 2: Evaluate how the development of social workers is sufficient in defining leadership. This research intends to reframe the misconception that social workers do not possess the capacity and skills to be effective leaders. On the contrary, social work encompasses a framework dedicated to lifelong development and growth. Social workers must be skilled, competent, ethical, supportive, and empathic. These are all qualities and traits of effective leadership, whereas leaders are in relation with others and embody partnership and collaboration with followers and stakeholders. The proposed study is a cross-sectional quasi-experimental survey design that will include the distribution of a multi-level social work leadership model and assessment tool. The assessment tool aims to help define leadership in social work using a Likert scale model. A cross-sectional research design is appropriate for answering the research questions because the measurement survey will help gather data using a structured tool. Other than the proposed social work leadership measurement tool, there is no other mechanism based on social work theory and designed to measure the capacity and skill of social work leadership.

Keywords: leadership competencies, leadership education, multi-level social work leadership model, social work core values, social work leadership, social work leadership education, social work leadership measurement tool

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Authors: Junjira Mahaboon, Anongnard Boonpak, Nattakarn Worrasan, Busma Kama, Mujalin Saikliang, Siripor Dankachatarn

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Rubber wood processing is one of the most important industries in southern Thailand. The process has several safety hazards for example unsafe wood cutting machine guarding, wood dust, noise, and heavy lifting. However, workers’ occupational health and safety measures to promote their behaviors are still limited. This quasi-experimental research was to determine factors affecting workers’ safety behaviors using theory of planned behavior after implementing job safety intervention program. The purposes were to (1) determine factors affecting workers’ behaviors and (2) to evaluate effectiveness of the intervention program. The sample of study was 66 workers from a rubber wood processing factory. Factors in the Theory of Planned Behavior model (TPB) were measured before and after the intervention. The factors of TPB included attitude towards behavior, subjective norm, perceived behavioral control, intention, and behavior. Firstly, Job Safety Analysis (JSA) was conducted and Safety Standard Operation Procedures (SSOP) were established. The questionnaire was also used to collect workers’ characteristics and TPB factors. Then, job safety intervention program to promote workers’ behavior according to SSOP were implemented for a four month period. The program included SSOP training, personal protective equipment use, and safety promotional campaign. After that, the TPB factors were again collected. Paired sample t-test and independent t-test were used to analyze the data. The result revealed that attitude towards behavior and intention increased significantly after the intervention at p<0.05. These factors also significantly determined the workers’ safety behavior according to SSOP at p<0.05. However, subjective norm, and perceived behavioral control were not significantly changed nor related to safety behaviors. In conclusion, attitude towards behavior and workers’ intention should be promoted to encourage workers’ safety behaviors. SSOP intervention program e.g. short meeting, safety training, and promotional campaign should be continuously implemented in a routine basis to improve workers’ behavior.

Keywords: job safety analysis, rubber wood processing workers, safety standard operation procedure, theory of planned behavior

Procedia PDF Downloads 193

Authors: Kan Yu, Khui Hung Lee, Eben Afrifa-Yamoah, Jing Guo, Katrina Harrison, Jack Goldblatt, Nicholas Pachter, Jitian Xiao, Guicheng Brad Zhang

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Background and Significance of the Study: Congenital Heart Defects (CHDs) are the most common malformation at birth and one of the leading causes of infant death. Although the exact etiology remains a significant challenge, epigenetic modifications, such as DNA methylation, are thought to contribute to the pathogenesis of congenital heart defects. At present, no existing DNA methylation biomarkers are used for early detection of CHDs. The existing CHD diagnostic techniques are time-consuming and costly and can only be used to diagnose CHDs after an infant was born. The present study employed a machine learning technique to analyse genome-wide methylation data in children with and without CHDs with the aim to find methylation biomarkers for CHDs. Methods: The Illumina Human Methylation EPIC BeadChip was used to screen the genome‐wide DNA methylation profiles of 24 infants diagnosed with congenital heart defects and 24 healthy infants without congenital heart defects. Primary pre-processing was conducted by using RnBeads and limma packages. The methylation levels of top 600 genes with the lowest p-value were selected and further investigated by using a random forest approach. ROC curves were used to analyse the sensitivity and specificity of each biomarker in both training and test sample sets. The functionalities of selected genes with high sensitivity and specificity were then assessed in molecular processes. Major Findings of the Study: Three genes (MIR663, FGF3, and FAM64A) were identified from both training and validating data by random forests with an average sensitivity and specificity of 85% and 95%. GO analyses for the top 600 genes showed that these putative differentially methylated genes were primarily associated with regulation of lipid metabolic process, protein-containing complex localization, and Notch signalling pathway. The present findings highlight that aberrant DNA methylation may play a significant role in the pathogenesis of congenital heart defects.

Keywords: biomarker, congenital heart defects, DNA methylation, random forest

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Authors: Suraj Mehrotra

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The stock market is a volatile, bustling marketplace that is a cornerstone of economics. It defines whether companies are successful or in spiral. A thorough understanding of it is important - many companies have whole divisions dedicated to analysis of both their stock and of rivaling companies. Linking the world of finance and artificial intelligence (AI), especially the stock market, has been a relatively recent development. Predicting how stocks will do considering all external factors and previous data has always been a human task. With the help of AI, however, machine learning models can help us make more complete predictions in financial trends. Taking a look at the stock market specifically, predicting the open, closing, high, and low prices for the next day is very hard to do. Machine learning makes this task a lot easier. A model that builds upon itself that takes in external factors as weights can predict trends far into the future. When used effectively, new doors can be opened up in the business and finance world, and companies can make better and more complete decisions. This paper explores the various techniques used in the prediction of stock prices, from traditional statistical methods to deep learning and neural networks based approaches, among other methods. It provides a detailed analysis of the techniques and also explores the challenges in predictive analysis. For the accuracy of the testing set, taking a look at four different models - linear regression, neural network, decision tree, and naïve Bayes - on the different stocks, Apple, Google, Tesla, Amazon, United Healthcare, Exxon Mobil, J.P. Morgan & Chase, and Johnson & Johnson, the naïve Bayes model and linear regression models worked best. For the testing set, the naïve Bayes model had the highest accuracy along with the linear regression model, followed by the neural network model and then the decision tree model. The training set had similar results except for the fact that the decision tree model was perfect with complete accuracy in its predictions, which makes sense. This means that the decision tree model likely overfitted the training set when used for the testing set.

Keywords: machine learning, testing set, artificial intelligence, stock analysis

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Authors: Neeta Khurana, Ritu Sharma

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This paper is an impact assessment study of the rehabilitation work done for Chhara women in the rural precincts of Ahmedabad. The Chharas constitute a denotified tribe and live in abject poverty. The women of this community are infamous absconders of law and active bootleggers of locally made liquor. As part of a psychological study with a local NGO, the authors headed a training program aimed at rehabilitating and providing these women alternate modes of employment, thereby driving them away from a life of crime. The paper centers on the idea of women entrepreneurship and women empowerment. It notes the importance of handholding in a conflict situation. Most of the research on Chharas is either focused on victimising them for state-sponsored violence or mostly makes a plea on reconditioning them in the mainstream. Going against this trend, this paper which documents the study argues that making these poor women self-dependent is a panacea for their sluggish development. The alienation caused due to the demonisation of the community has made them abandon traditional modes of employment. This has further led the community astray into making illegal country liquor causing further damage to their reputation. Women are at the centre of this vicious circle facing much repression and ostracisation. The study conducted by the PDPU team was an attempt to change this dogmatic alienation of these poor women. It was found that with consistent support and reformist approach towards law, it is possible to drive these women away from a life of penury repression and crime. The aforementioned study uses empirical tools to verify this claim. Placed at the confluence of the sociology of gender and psychology, this paper is a good way to argue that law enforcement cannot be effective without sensitisation to the ground realities of conflict. The study conducted from which the paper borrows was a scientific survey focused on markers of gender and caste realities of the Chharas. The paper mentions various dynamics involved in the training program that paved the way for the successful employment of the women. In an attempt to explain its uniqueness, the paper also has a section on comparing similar social experiments.

Keywords: employment, gender, handholding, rehabilitation

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Authors: Mane Varosyan, Diana Tumanyan, Agnesa Martirosyan

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There are many catastrophic events that end with dire consequences, and to avoid them, people should be well-armed with the necessary information about these situations. During the last years, Serious Games have increasingly gained popularity for training people for different types of emergencies. The major discussed problem is the usage of gamification in education. Moreover, it is mandatory to understand how and what kind of gamified e-learning modules promote engagement. As the theme is emergency, we also find out people’s behavior for creating the final approach. Our proposed solution is an educational video game, “EZZRA”.

Keywords: gamification, education, emergency, serious games, game design, virtual reality, digitalisation

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Liang Cheng Chang, Wei Ju Huang, You Cheng Chen

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Investigation and research are keys for conjunctive use of surface and groundwater resources. The hydrogeological structure is an important base for groundwater analysis and simulation. Traditionally, the hydrogeological structure is artificially determined based on geological drill logs, the structure of wells, groundwater levels, and so on. In Taiwan, groundwater observation network has been built and a large amount of groundwater-level observation data are available. The groundwater level is the state variable of the groundwater system, which reflects the system response combining hydrogeological structure, groundwater injection, and extraction. This study applies analytical tools to the observation database to develop a methodology for the identification of confined and unconfined aquifers. These tools include frequency analysis, cross-correlation analysis between rainfall and groundwater level, groundwater regression curve analysis, and decision tree. The developed methodology is then applied to groundwater layer identification of two groundwater systems: Zhuoshui River alluvial fan and Pingtung Plain. The abovementioned frequency analysis uses Fourier Transform processing time-series groundwater level observation data and analyzing daily frequency amplitude of groundwater level caused by artificial groundwater extraction. The cross-correlation analysis between rainfall and groundwater level is used to obtain the groundwater replenishment time between infiltration and the peak groundwater level during wet seasons. The groundwater regression curve, the average rate of groundwater regression, is used to analyze the internal flux in the groundwater system and the flux caused by artificial behaviors. The decision tree uses the information obtained from the above mentioned analytical tools and optimizes the best estimation of the hydrogeological structure. The developed method reaches training accuracy of 92.31% and verification accuracy 93.75% on Zhuoshui River alluvial fan and training accuracy 95.55%, and verification accuracy 100% on Pingtung Plain. This extraordinary accuracy indicates that the developed methodology is a great tool for identifying hydrogeological structures.

Keywords: aquifer identification, decision tree, groundwater, Fourier transform

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Authors: Hsin-Chieh Lee, Fen-Ling Kuo, Jui-Chi Lin

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Background: Upper extremity functional impairment that occurs after stroke includes hemiplegia, synergy movement, muscle hypertonicity, and somatosensory impairment, which result in inefficient and inaccurate movement. Robot-assisted rehabilitation is an intensive training approach that is effective in sensorimotor and hand function recovery. However, these systems mostly focused on the proximal part of the upper limb rather than the distal part. The device used in our study was Gloreha Sinfonia, which focuses on the distal part of the upper limb and uses a dynamic support system to facilitate the whole limb function. The objective of this study was to investigate the effects of robot-assisted therapy (RT) with Gloreha device on sensorimotor, and ADLs in patients with stroke. Method: Patients with stroke (N=25) participated AB or BA (A = 12 RT sessions and B = 12 conventional therapy (CT) sessions) for 6 weeks (60 min at each session, twice a week), with 1-month break for washout period. The performance of the patients was assessed by a blinded assessor at 4 time points (pretest 1, posttest 1, pretest 2, posttest 2) which including the Fugl–Meyer Assessment-upper extremity (FMA-UE), box and block test, electromyography of the extensor digitorum communis (EDC) and brachioradialis, a grip dynamometer for motor evaluation; Semmes–Weinstein hand monofilament and Revision of the Nottingham Sensory Assessment for sensory evaluation; and the Modified Barthel Index (MBI) for assessing the ADL ability. Result: RT group significantly improved FMA-UE proximal scores (p = 0.038), FMA-UE total scores (p = 0.046), and MBI (p = 0.030). The EDC exhibited higher efficiency during the small block grasping task in the RT group than in the CT group (p = 0.050). Conclusions: RT with the Gloreha device might lead to beneficial effects on arm motor function, ADL ability, and EDC muscle recruitment efficacy in patients with subacute to chronic stroke.

Keywords: activities of daily living, hand function, robotic rehabilitation, stroke

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Authors: Asnakew Mulualem Tegegne, Tarun Kumar Lohani, Abunu Atlabachew Eshete

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Groundwater potential delineation is essential for efficient water resource utilization and long-term development. The scarcity of potable and irrigation water has become a critical issue due to natural and anthropogenic activities in meeting the demands of human survival and productivity. With these constraints, groundwater resources are now being used extensively in Ethiopia. Therefore, an innovative convolutional neural network (CNN) is successfully applied in the Gunabay watershed to delineate groundwater potential based on the selected major influencing factors. Groundwater recharge, lithology, drainage density, lineament density, transmissivity, and geomorphology were selected as major influencing factors during the groundwater potential of the study area. For dataset training, 70% of samples were selected and 30% were used for serving out of the total 128 samples. The spatial distribution of groundwater potential has been classified into five groups: very low (10.72%), low (25.67%), moderate (31.62%), high (19.93%), and very high (12.06%). The area obtains high rainfall but has a very low amount of recharge due to a lack of proper soil and water conservation structures. The major outcome of the study showed that moderate and low potential is dominant. Geodetoctor results revealed that the magnitude influences on groundwater potential have been ranked as transmissivity (0.48), recharge (0.26), lineament density (0.26), lithology (0.13), drainage density (0.12), and geomorphology (0.06). The model results showed that using a convolutional neural network (CNN), groundwater potentiality can be delineated with higher predictive capability and accuracy. CNN-based AUC validation platform showed that 81.58% and 86.84% were accrued from the accuracy of training and testing values, respectively. Based on the findings, the local government can receive technical assistance for groundwater exploration and sustainable water resource development in the Gunabay watershed. Finally, the use of a detector-based deep learning algorithm can provide a new platform for industrial sectors, groundwater experts, scholars, and decision-makers.

Keywords: CNN, geodetector, groundwater influencing factors, Groundwater potential, Gunabay watershed

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Authors: Madrine King'endo

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This study dealt with the influence of spelling errors on English language performance among learners with dysgraphia in public primary schools in West Embu, Embu County, Kenya. The study purposed to investigate the influence of spelling errors on the English language performance among the class three pupils with dysgraphia in public primary schools. The objectives of the study were to identify the spelling errors that learners with dysgraphia make when writing English words and classify the spelling errors they make. Further, the study will establish how the spelling errors affect the performance of the language among the study participants, and suggest the remediation strategies that teachers could use to address the errors. The study could provide the stakeholders with relevant information in writing skills that could help in developing a responsive curriculum to accommodate the teaching and learning needs of learners with dysgraphia, and probably ensure training of teachers in teacher training colleges is tailored within the writing needs of the pupils with dysgraphia. The study was carried out in Embu county because the researcher did not find any study in related literature review concerning the influence of spelling errors on English language performance among learners with dysgraphia in public primary schools done in the area. Moreover, besides being relatively populated enough for a sample population of the study, the area was fairly cosmopolitan to allow a generalization of the study findings. The study assumed the sampled schools will had class three pupils with dysgraphia who exhibited written spelling errors. The study was guided by two spelling approaches: the connectionist stimulation of spelling process and orthographic autonomy hypothesis with a view to explain how participants with learning disabilities spell written words. Data were collected through interviews, pupils’ exercise books, and progress records, and a spelling test made by the researcher based on the spelling scope set for class three pupils by the ministry of education in the primary education syllabus. The study relied on random sampling techniques in identifying general and specific participants. Since the study used children in schools as participants, voluntary consent was sought from themselves, their teachers and the school head teachers who were their caretakers in a school setting.

Keywords: dysgraphia, writing, language, performance

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Authors: N. Khanyile, P. Dlamini, M. Masenya

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Background: Most of the population in Africa is still dependent on indigenous medicinal knowledge for treating and managing ailments. Indigenous traditional knowledge owners/practitioners who own this knowledge are consulted by communities, but their knowledge is not known how they get it. The question of how knowledge is acquired and preserved remains one of the biggest challenges in traditional healing and treatment with herbal medicines. It is regrettable that despite the importance and recognition of indigenous medicinal knowledge globally, the details of acquirement, storing and transmission, and preservation techniques are not known. Hence this study intends to unveil the process of acquirement and transmission, and preservation techniques of indigenous medical knowledge by its owners. Objectives: This study aims to assess the process of acquiring and preservation of traditional medicinal knowledge by traditional medicinal knowledge owners/practitioners in uMhlathuze Municipality, in the province of KwaZulu-Natal, South Africa. The study was guided by four research objectives which were to: identify the types of traditional medicinal knowledge owners who possess this knowledge, establish the approach used by indigenous medicinal knowledge owners/healers for acquiring medicinal knowledge, identify the process of preservation of medicinal knowledge by indigenous medicinal knowledge owners/healers, and determine the challenges encountered in transferring the knowledge. Method: The study adopted a qualitative research approach, and a snowball sampling technique was used to identify the study population. Data was collected through semi-structured interviews with indigenous medicinal knowledge owners. Results: The findings suggested that uMhlathuze municipality had different types of indigenous medicinal knowledge owners who possess valuable knowledge. These are diviners (Izangoma), faith healers (Abathandazi), and herbalists (Izinyanga). The study demonstrated that indigenous medicinal knowledge is acquired in many different ways, including visions, dreams, and vigorous training. The study also revealed the acquired knowledge is preserved or shared with specially chosen children and trainees. Conclusion: The study concluded that this knowledge is gotten through vigorous training, which requires the learner to be attentive and eager to learn. It was recommended that a study of this nature be conducted but at a broader level to enhance an informed conclusion and recommendations.

Keywords: preserving, indigenous medicinal knowledge, indigenous knowledge, indigenous medicinal knowledge owners/practitioners, acquiring

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Authors: Ali Isa Danlami

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This study examined the coaching leadership behaviours preferred by athletes in individual and team sports in Nigeria that may lead to increased satisfaction and performance. Six leadership behaviours were identified; these are democratic, training and instruction, situational consideration, autocratic, social support and positive feedback. The six leadership behaviours relate to the preference of coaches by athletes that leads to increased performance were the focus of this study. The population of this study is comprised of male and female athletes of states sports councils in Nigeria. An ex-post facto research design was employed for this study. Stratified and purposive sampling techniques were used to select the sampled states according to the six geo-political zones of the country. Two states (North Central (FCT, Nasarawa), North East (Bauchi, Gombe), North West (Kaduna, Sokoto), South East (Anambra, Imo), South west (Ogun, Ondo), South South (Delta, and Rivers) were selected from each stratum. A modified questionnaire was used to collect data for this study, and the data collected were subjected to a reliability test using the Statistical Package for Social Science (SPSS) to analyse the data. A two sample Z-test procedure was used to test the significant differences because of the large number of subjects involved in the different groups. All hypotheses were tested at 0.05 alpha value. The findings of the study concluded that: Athletes in team and individual sports generally preferred coaches who were more disposed towards training and instructions, social support, positive feedback, situational consideration and democratic behaviours. It was also found that athletes in team sports have higher preference for coaches with democratic behaviour. The result revealed that athletes in team and individual sports did not have a preference for coaches disposed towards autocratic behaviour. Based on this, the following recommendations were made: Democratic behaviour by coaches should be encouraged in team and individual sports. Coaches should not be engaged in autocratic behaviours when coaching. These behaviours should be adopted by coaches to increase athletes’ satisfaction and enhancement in performance.

Keywords: leadership behaviour, preference, athletes, individual, team, coaches’

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Authors: Gaelle Candel, David Naccache

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t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embeddings. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n²) to O(n²=k), and the memory requirement from n² to 2(n=k)², which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution, and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning

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Authors: Andriana E. Tran, Anna Chur-Hansen

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Sexual health is an important aspect of overall wellbeing. This study aimed to explore the sexual health experiences of men aged 50 years and over from the perspective of health care professional participants who were specializing in sexual health care and who consulted with older men. A total of ten interviews were conducted. Eleven themes were identified regarding men’s experiences with sexual health care as reported by participants. 1) Biologically focused: older male clients focus largely on the biological aspect of their sexual health without consideration of other factors which might affect their functioning. 2) Psychological concerns: there is an interaction between mental and sexual health but older male clients do not necessarily see this. 3) Medicalization of sexual functioning: advances in medicine that aid with erectile difficulties which consequently mean that older men tend to favor a medical solution to their sexual concerns. 4) Masculine identity: sexual health concerns are linked to older male clients’ sense of masculinity. 5) Penile functionality: most concerns that older male clients have center on their penile functionality. 6) Relationships: many male clients seek sexual help as they believe it improves relationships. Conversely, having supportive partners may mean older male clients focus less on the physicality of sex. 7) Grief and loss: men experience grief and loss – the loss of their sexual functioning, grief from loss of a long-term partner, and loss of intimacy and privacy when moving from independent living to residential care. 8) Social stigma: older male clients experience stigma around aging sexuality and sex in general. 9) Help-seeking behavior: older male clients will usually seek mechanistic solution for biological sexual concerns, such as medication used for penile dysfunction. 10) Dismissed by health care professionals: many older male clients seek specialist sexual health care without the knowledge of their doctors as they feel dismissed due to lack of expertise, lack of time, and the doctor’s personal attitudes and characteristics. Finally, 11) Lack of resources: there is a distinct lack of resources and training to understand sexuality for healthy older men. These findings may inform future research, professional training, public health campaigns and policies for sexual health in older men.

Keywords: ageing, biopsychosocial model, men's health, sexual health

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Authors: Teresita Lopez Joy, Jose A. Acevedo Suarez, Martha I. Gomez Acosta, Ana Julia Acevedo Urquiaga

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Current trends in business competitiveness indicate the need to manage businesses as supply chains and not in isolation. The use of strategies aimed at maximum satisfaction of customers in a network and based on inter-company cooperation; contribute to obtaining successful joint results. In the Cuban economic context, the development of productive linkages to achieve integrated management of supply chains is considering a key aspect. In order to achieve this jump, it is necessary to develop acting capabilities in the entities that make up the chains through a systematic procedure that allows arriving at a management model in consonance with the environment. The objective of the research focuses on: designing a model and procedure for the development of integrated management of supply chains in economic entities. The results obtained are: the Model and the Procedure for the Development of the Supply Chains Integrated Management (MP-SCIM). The Model is based on the development of logistics in the network actors, the joint work between companies, collaborative planning and the monitoring of a main indicator according to the end customers. The application Procedure starts from the well-founded need for development in a supply chain and focuses on training entrepreneurs as doers. The characterization and diagnosis is done to later define the design of the network and the relationships between the companies. It takes into account the feedback as a method of updating the conditions and way to focus the objectives according to the final customers. The MP-SCIM is the result of systematic work with a supply chain approach in companies that have consolidated as coordinators of their network. The cases of the edible oil chain and explosives for construction sector reflect results of more remarkable advances since they have applied this approach for more than 5 years and maintain it as a general strategy of successful development. The edible oil trading company experienced a jump in sales. In 2006, the company started the analysis in order to define the supply chain, apply diagnosis techniques, define problems and implement solutions. The involvement of the management and the progressive formation of performance capacities in the personnel allowed the application of tools according to the context. The company that coordinates the explosives chain for construction sector shows adequate training with independence and opportunity in the face of different situations and variations of their business environment. The appropriation of tools and techniques for the analysis and implementation of proposals is a characteristic feature of this case. The coordinating entity applies integrated supply chain management to its decisions based on the timely training of the necessary action capabilities for each situation. Other cases of study and application that validate these tools are also detailed in this paper, and they highlight the results of generalization in the quantitative and qualitative improvement according to the final clients. These cases are: teaching literature in universities, agricultural products of local scope and medicine supply chains.

Keywords: integrated management, logistic system, supply chain management, tactical-operative planning

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Authors: Brenagh E. Schlingermann, Clare Lodge, Paula Rankin

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Background: Gaelic football, hurling and camogie are highly popular field games in Ireland. Research into the epidemiology of injury in Gaelic games revealed that approximately three quarters of the injuries in the games occur in the lower extremity. These injuries can have player, team and institutional impacts due to multiple factors including financial burden and time loss from competition. Research has shown it is possible to record injury data consistently with the GAA through a closed online recording system known as the GAA injury surveillance database. It has been established that determining the incidence of injury is the first step of injury prevention. The goals of this study were to create a dynamic GAA15 injury prevention programme which addressed five key components/goals; avoid positions associated with a high risk of injury, enhance flexibility, enhance strength, optimize plyometrics and address sports specific agilities. These key components are internationally recognized through the Prevent Injury, Enhance performance (PEP) programme which has proven reductions in ACL injuries by 74%. In national Gaelic games the programme is known as the GAA15 which has been devised from the principles of the PEP. No such injury prevention strategies have been published on this cohort in Gaelic games to date. This study will investigate the effects of the GAA15 on injury incidence and neuromuscular function in Gaelic games. Methods: A total of 154 players (mean age 20.32 ± 2.84) were recruited from the GAA teams within the Institute of Technology Carlow (ITC). Preseason and post season testing involved two objective screening tests; Y balance test and Three Hop Test. Practical workshops, with ongoing liaison, were provided to the coaches on the implementation of the GAA15. The programme was performed before every training session and game and the existing GAA injury surveillance database was accessed to monitor player’s injuries by the college sports rehabilitation athletic therapist. Retrospective analysis of the ITC clinic records were performed in conjunction with the database analysis as a means of tracking injuries that may have been missed. The effects of the programme were analysed by comparing the intervention groups Y balance and three hop test scores to an age/gender matched control group. Results: Year 1 results revealed significant increases in neuromuscular function as a result of the GAA15. Y Balance test scores for the intervention group increased in both the posterolateral (p=.005 and p=.001) and posteromedial reach directions (p= .001 and p=.001). A decrease in performance was determined for the three hop test (p=.039). Overall twenty-five injuries were reported during the season resulting in an injury rate of 3.00 injuries/1000hrs of participation; 1.25 injuries/1000hrs training and 4.25 injuries/1000hrs match play. Non-contact injuries accounted for 40% of the injuries sustained. Year 2 results are pending and expected April 2016. Conclusion: It is envisaged that implementation of the GAA15 will continue to reduce the risk of injury and improve neuromuscular function in collegiate Gaelic games athletes.

Keywords: GAA15, Gaelic games, injury prevention, neuromuscular training

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