Search results for: announcer training program

Authors: Raj Banerjee, Aniruddha Sengupta

Abstract:

An earthquake event, associated with a typical fault rupture, initiates at the source, propagates through a rock or soil medium and finally daylights at a surface which might be a populous city. The detrimental effects of an earthquake are often quantified in terms of the responses of superstructures resting on the soil. Hence, there is a need for the estimation of amplification of the bedrock motions due to the influence of local site conditions. In the present study, field borehole log data of Mangalwadi and Walkeswar sites in Mumbai city are considered. The data consists of variation of SPT N-value with the depth of soil. A correlation between shear wave velocity (Vₛ) and SPT N value for various soil profiles of Mumbai city has been developed using various existing correlations which is used further for site response analysis. MATLAB program is developed for studying the ground response analysis by performing two dimensional linear and equivalent linear analysis for some of the typical Mumbai soil sites using pure shear (Multi Point Constraint) boundary condition. The model is validated in linear elastic and equivalent linear domain using the popular commercial program, DEEPSOIL. Three actual earthquake motions are selected based on their frequency contents and durations and scaled to a PGA of 0.16g for the present ground response analyses. The results are presented in terms of peak acceleration time history with depth, peak shear strain time history with depth, Fourier amplitude versus frequency, response spectrum at the surface etc. The peak ground acceleration amplification factors are found to be about 2.374, 3.239 and 2.4245 for Mangalwadi site and 3.42, 3.39, 3.83 for Walkeswar site using 1979 Imperial Valley Earthquake, 1989 Loma Gilroy Earthquake and 1987 Whitter Narrows Earthquake, respectively. In the absence of any site-specific response spectrum for the chosen sites in Mumbai, the generated spectrum at the surface may be utilized for the design of any superstructure at these locations.

Keywords: deepsoil, ground response analysis, multi point constraint, response spectrum

Procedia PDF Downloads 168

Authors: Aline V. Arroteia, Gustavo G. Do Amaral, Simone Z. Kikuti, Norberto C. S. Moura, Silvio B. Melhado

Abstract:

Despite the significant advances made by the construction industry in recent years, the crystalized absence of integration between the design and construction phases is still an evident and costly problem in building construction. Globally, the construction industry has sought to adopt collaborative practices through new technologies to mitigate impacts of this fragmented process and to optimize its production. In this new technological business environment, professionals are required to develop new methodologies based on the notion of collaboration and integration of information throughout the building lifecycle. This scenario also represents the industry’s reality in developing nations, and the increasing need for overall efficiency has demanded new educational alternatives at the undergraduate and post-graduate levels. In countries like Brazil, it is the common understanding that Architecture, Engineering and Building Construction educational programs are being required to review the traditional design pedagogical processes to promote a comprehensive notion about integration and simultaneity between the phases of the project. In this context, the coherent inclusion of computation design to all segments of the educational programs of construction related professionals represents a significant research topic that, in fact, can affect the industry practice. Thus, the main objective of the present study was to comparatively measure the effectiveness of the Building Information Modeling courses offered by the University of Sao Paulo, the most important academic institution in Brazil, at the Schools of Architecture and Civil Engineering and the courses offered in well recognized BIM research institutions, such as the School of Design in the College of Architecture of the Georgia Institute of Technology, USA, to evaluate the dissemination of BIM knowledge amongst students in post graduate level. The qualitative research methodology was developed based on the analysis of the program and activities proposed by two BIM courses offered in each of the above-mentioned institutions, which were used as case studies. The data collection instruments were a student questionnaire, semi-structured interviews, participatory evaluation and pedagogical practices. The found results have detected a broad heterogeneity of the students regarding their professional experience, hours dedicated to training, and especially in relation to their general knowledge of BIM technology and its applications. The research observed that BIM is mostly understood as an operational tool and not as methodological project development approach, relevant to the whole building life cycle. The present research offers in its conclusion an assessment about the importance of the incorporation of BIM, with efficiency and in its totality, as a teaching method in undergraduate and graduate courses in the Brazilian architecture, engineering and building construction schools.

Keywords: building information modeling (BIM), BIM education, BIM process, design teaching

Procedia PDF Downloads 141

Authors: Pejman Taghibeikzadehbadr

Abstract:

Background and Aim: PGC-1 alpha is a transcription factor that was first detected in brown adipose tissue. Since its discovery, PGC-1 alpha has been known to facilitate beneficial adaptations such as mitochondrial biogenesis and increased angiogenesis in skeletal muscle following aerobic exercise. Therefore, the purpose of this study was to investigate the expression of PGC-1 alpha isoforms in response to eccentric and concentric resistance training in healthy subjects. Materials and Methods: Ten healthy men were randomly divided into two groups (5 patients in eccentric group - 5 in eccentric group). Isokinetic contraction protocols included eccentric and concentric knee extension with maximum power and angular velocity of 60 degrees per second. The torques assigned to each subject were considered to match the workload in both protocols, with a rotational speed of 60 degrees per second. Contractions consisted of a maximum of 12 sets of 10 repetitions for the right leg, a rest time of 30 seconds between each set. At the beginning and end of the study, biopsy of the lateral broad muscle tissue was performed. Biopsies were performed in both distal and proximal directions of the lateral flank. To evaluate the expression of PGC1α-1 and PGC1α-4 genes, tissue analysis was performed in each group using Real-Time PCR technique. Data were analyzed using dependent t-test and covariance test. SPSS21 software and Exell 2013 software were used for data analysis. Results: The results showed that intra-group changes of PGC1α-1 after one session of activity were not significant in eccentric (p = 0.168) and concentric (p = 0.959) groups. Also, inter-group changes showed no difference between the two groups (p = 0.681). Also, intra-group changes of PGC1α-4 after one session of activity were significant in an eccentric group (p = 0.012) and concentric group (p = 0.02). Also, inter-group changes showed no difference between the two groups (p = 0.362). Conclusion: It seems that the lack of significant changes in the desired variables due to the lack of exercise pressure is sufficient to stimulate the increase of PGC1α-1 and PGC1α-4. And with regard to reviewing the answer, it seems that the compatibility debate has different results that need to be addressed.

Keywords: eccentric contraction, concentric contraction, PGC1α-1 و PGC1α-4, human subject

Procedia PDF Downloads 67

Authors: Stephen L. Green, Alexander N. Gorban, Ivan Y. Tyukin

Abstract:

Within the past decade, using Convolutional Neural Networks (CNN)’s to create Deep Learning systems capable of translating Sign Language into text has been a breakthrough in breaking the communication barrier for deaf-mute people. Conventional research on this subject has been concerned with training the network to recognize the fingerspelling gestures of a given language and produce their corresponding alphanumerics. One of the problems with the current developing technology is that images are scarce, with little variations in the gestures being presented to the recognition program, often skewed towards single skin tones and hand sizes that makes a percentage of the population’s fingerspelling harder to detect. Along with this, current gesture detection programs are only trained on one finger spelling language despite there being one hundred and forty-two known variants so far. All of this presents a limitation for traditional exploitation for the state of current technologies such as CNN’s, due to their large number of required parameters. This work aims to present a technology that aims to resolve this issue by combining a pretrained legacy AI system for a generic object recognition task with a corrector method to uptrain the legacy network. This is a computationally efficient procedure that does not require large volumes of data even when covering a broad range of sign languages such as American Sign Language, British Sign Language and Chinese Sign Language (Pinyin). Implementing recent results on method concentration, namely the stochastic separation theorem, an AI system is supposed as an operate mapping an input present in the set of images u ∈ U to an output that exists in a set of predicted class labels q ∈ Q of the alphanumeric that q represents and the language it comes from. These inputs and outputs, along with the interval variables z ∈ Z represent the system’s current state which implies a mapping that assigns an element x ∈ ℝⁿ to the triple (u, z, q). As all xi are i.i.d vectors drawn from a product mean distribution, over a period of time the AI generates a large set of measurements xi called S that are grouped into two categories: the correct predictions M and the incorrect predictions Y. Once the network has made its predictions, a corrector can then be applied through centering S and Y by subtracting their means. The data is then regularized by applying the Kaiser rule to the resulting eigenmatrix and then whitened before being split into pairwise, positively correlated clusters. Each of these clusters produces a unique hyperplane and if any element x falls outside the region bounded by these lines then it is reported as an error. As a result of this methodology, a self-correcting recognition process is created that can identify fingerspelling from a variety of sign language and successfully identify the corresponding alphanumeric and what language the gesture originates from which no other neural network has been able to replicate.

Keywords: convolutional neural networks, deep learning, shallow correctors, sign language

Procedia PDF Downloads 87

Authors: M. Naidoo

Abstract:

Artificial intelligence often requires large amounts of good quality data. Within important fields, such as healthcare, the training of AI systems predominately relies on health and personal data; however, the usage of this data is complicated by various layers of law and ethics that seek to protect individuals’ privacy rights. This research seeks to establish the challenges AI and data sciences pose to (i) informational rights, (ii) privacy rights, and (iii) data protection. To solve some of the issues presented, various methods are suggested, such as embedding values in technological development, proper balancing of rights and interests, and others.

Keywords: artificial intelligence, data science, law, policy

Procedia PDF Downloads 93

Authors: Shaik Asha Begum, S. Joshna Rani, Shaik Abdul Rahaman

Abstract:

INTRODUCTION: Breast cancer is a disease that creates in breast cells. "KAP" study estimates the Knowledge, Attitude, and Practices of a local area. More than 1.5 million ladies (25% of all ladies with malignancy) are determined to have bosom disease consistently all through the world. Understanding the degrees of Knowledge, Attitude and Practice will empower a more effective cycle of mindfulness creation as it will permit the program to be custom-made all the more properly to the necessities of the local area. OBJECTIVES: The objective of this study is to assess the knowledge on signs and symptoms, risk factors, provide awareness on the practicing of the early detection techniques of breast cancer and provide knowledge on the overall breast cancer including preventive techniques. METHODOLOGY: This is an expressive cross-sectional investigation. This investigation of KAP was done in the Nirmala Educational Institutions from January to April 2021. A total of 300 participants are included from women students in pharmacy graduates & lecturers, and also from graduates other than the pharmacy. The examiners are taken from the BCAM (Breast Cancer Awareness Measure), tool compartment (Version 2). RESULT: According to the findings of the study, the majority of the participants were not well informed about breast cancer. A lump in the breast was the most commonly mentioned sign of breast cancer, followed by pain in the breast or nipple. The percentage of knowledge related to the breast cancer risk factors was also very less. The correct answers for breast cancer risk factors were radiation exposure (58.20 percent), a positive family history (47.6 percent), obesity (46.9 percent), a lack of physical activity (43.6 percent), and smoking (43.2 percent). Breast cancer screening, on the other hand, was uncommon (only 30 and 11.3 percent practiced clinical breast examination and mammography respectively). CONCLUSION: In this study, the knowledge on the signs and symptoms, risk factors of breast cancer - pharmacy graduates have more knowledge than the non-pharmacy graduates but in the preventive techniques and early detective tools of breast cancer -had poor knowledge in the pharmacy and non-pharmacy graduate. After the awareness program, pharmacy and non-pharmacy graduates got supportive knowledge on the preventive techniques and also practiced the early detective techniques of breast cancer.

Keywords: breast cancer, mammography, KAP study, early detection

Procedia PDF Downloads 125

Authors: Majda Ibrahim Aljaroudi, Jwaher Alburake

Abstract:

The study aimed to identify the active role of the teacher in the management of the effective classroom environment for high school students from the viewpoint of the teachers, and to identify whether there were statistically significant differences between the averages of the respondents regarding the active role of the high school teachers in managing effective classroom environment in Riyadh, and also the total score depending on the variables of the study (qualifications, years of experience, training and development programs). This study used the descriptive survey approach where a questionnaire has been built and consisted of (35) items about five areas as a tool to measure the teacher's role in the management of effective classroom environment for high school students. The study population consisted of (1313) high school teachers in the government schools in south of Riyadh. It consisted of (70) teachers who were selected randomly. It used the appropriate statistical methods to analyze data by using statistical packages (SPSS). The study found the following results: • Most of the study sample members agreed on their role in the effective classroom environment management for high school students in government schools in Riyadh with an average (3.91 out of 5), which falls in the fifth category of Quintet scale (from 3.41 to 4.20) that refers to the option "often". • There are statistically significant differences between the mean responses of the study sample about the active role of the teacher in the effective classroom environment management for high school students regarding the concept of order in the classroom depending on the variable of years of experience for the benefit of teachers who have over 10 years of experience. There are statistically significant differences between the mean responses of the study sample about the teacher's active role in the effective classroom environment management for high school students regarding the educational process for maintaining the order in the classroom depending on the variable of training and development programs for the benefit of the teachers who have more than (5) courses. Due to the results of the study the researcher recommended a number of recommendations to improve the teacher's role in the effective classroom environment management for high school students.

Keywords: effective management, active learning, educational sciences, pedagogical sciences

Procedia PDF Downloads 430

Authors: Renata Roma, Christine Tardif-Williams

Abstract:

Engaging in daily walks with a dog (f.e. Canis lupus familiaris) during the COVID-19 pandemic may be linked to feelings of greater social-connectedness and global self-worth, and lower stress after controlling for mental health issues, lack of physical contact with others, and other stressors associated with the current pandemic. Therefore, maintaining a routine of dog walking might mitigate the effects of stressors experienced during the pandemic and promote well-being. However, many dog owners do not walk their dogs for many reasons, which are related to the owner’s and the dog’s personalities. Note that the consistency of certain personality characteristics among dogs demonstrates that it is possible to accurately measure different dimensions of personality in both dogs and their human counterparts. In addition, behavioural ratings (e.g., the dog personality questionnaire - DPQ) are reliable tools to assess the dog’s personality. Clarifying the relevance of personality factors in the context of young adult-dog relationships can shed light on interactional aspects that can potentially foster protective behaviours and promote well-being among young adults during the pandemic. This study examines if and how nine combinations of dog- and young adult-related personality characteristics (e.g., neuroticism-fearfulness) can amplify the influence of personality factors in the context of dog walking during the COVID-19 pandemic. Responses to an online large-scale survey among 440 (389 females; 47 males; 4 nonbinaries, Mage=20.7, SD= 2.13 range=17-25) young adults living with a dog in Canada were analyzed using structural equation modeling (SEM). As extraversion, conscientiousness, and neuroticism, measured through the five-factor model (FFM) inventory, are related to maintaining a routine of physical activities, these dimensions were selected for this analysis. Following an approach successfully adopted in the field of dog-human interactions, the FFM was used as the organizing framework to measure and compare the human’s and the dog’s personality in the context of dog walking. The dog-related personality dimensions activity/excitability, responsiveness to training, and fearful were correlated dimensions captured through DPQ and were added to the analysis. Two questions were used to assess dog walking. The actor-partner interdependence model (APIM) was used to check if the young adult’s responses about the dog were biased; no significant bias was observed. Activity/excitability and responsiveness to training in dogs were greatly associated with dog walking. For young adults, high scores in conscientiousness and extraversion predicted more walks with the dog. Conversely, higher scores in neuroticism predicted less engagement in dog walking. For participants high in conscientiousness, the dog’s responsiveness to training (standardized=0.14, p=0.02) and the dog’s activity/excitability (standardized=0.15, p=0.00) levels moderated dog walking behaviours by promoting more daily walks. These results suggest that some combinations in young adult and dog personality characteristics are associated with greater synergy in the young adult-dog dyad that might amplify the impact of personality factors on young adults’ dog-walking routines. These results can inform programs designed to promote the mental and physical health of young adults during the Covid-19 pandemic by highlighting the impact of synergy and reciprocity in personality characteristics between young adults and dogs.

Keywords: Covid-19 pandemic, dog walking, personality, structural equation modeling, well-being

Procedia PDF Downloads 101

Authors: Ozge Tahran, Sevgi Sevi Yesilyaprak

Abstract:

Objective: The aim of the study was to investigate the effect of the Wilk’s modified two different stretching exercises on posterior shoulder tightness, pain, and dysfunction in patients with subacromial impingement syndrome (SIS). Method: This study was carried out on 67 patients who have more than 15° difference in shoulder internal rotation range of motion between two sides and had been diagnosed as SIS. Before treatment, all patients were randomly assigned into three groups. Standard physiotherapy programme was applied to the Group 3 (n=23), standard physiotherapy program with Wilk’s modified cross-body stretching exercises were applied to Group 1 (n=22), and standard physiotherapy program with Wilk’s modified sleeper stretching exercises were applied to Group 2 (n= 23). All the patients received 20 sessions of physiotherapy during 4 weeks, 5 days in a week by a physiotherapist. The patients continued their exercises at home at the weekends. Pain severity, shoulder rotation range of motion, posterior shoulder tightness, upper extremity functionality with Constant and Murley Score (CMS) and disability level with The Disabilities of the Arm, Shoulder and Hand Score (QuickDASH) were evaluated before and after physiotherapy programme. Results: Before treatment, demographic and anthropometric characteristics were similar in groups and there was no statistical difference (p > 0.05). It was determined that pain severity decreased, shoulder rotation range of motion, posterior shoulder tightness, upper extremity functionality, and disability were improved after physiotherapy in both groups (p < 0.05). Group 1 and 2 had better results in terms of reduction of pain severity during activity, increase in shoulder rotation range of motion, posterior shoulder mobility and upper extremity functionality and improvement in upper extremity disability, compared to Group 3 (p < 0.05). Conclusion: Modified posterior shoulder stretching exercises in addition to standard physiotherapy programme is more effective for reduction of pain during activity, to improve shoulder rotation range of motion, posterior shoulder mobility, and upper extremity functionality in patients with SIS compared to standard physiotherapy programme alone.

Keywords: modified posterior shoulder stretching exercises, posterior shoulder tightness, shoulder complex, subacromial impingement syndrome

Procedia PDF Downloads 163

Authors: S. Summart, C. Saetiaw, T. Thosdeekoraphat, C. Thongsopa

Abstract:

This article presents new current-mode oscillator circuits using CDTAs which is designed from block diagram. The proposed circuits consist of two CDTAs and two grounded capacitors. The condition of oscillation and the frequency of oscillation can be adjusted by electronic method. The circuits have high output impedance and use only grounded capacitors without any external resistor which is very appropriate to future development into an integrated circuit. The results of PSPICE simulation program are corresponding to the theoretical analysis.

Keywords: current-mode, quadrature oscillator, block diagram, CDTA

Procedia PDF Downloads 445

Authors: A. Giannakopoulos, S. B. Buckley

Abstract:

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

Procedia PDF Downloads 581

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

Abstract:

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

Procedia PDF Downloads 83

Authors: Pedram Saadati, Zahra Nazari

Abstract:

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

Procedia PDF Downloads 32

Authors: Afzal Hussain, Mohammad A. Altamimi, Syed Sarim Imam, Mudassar Shahid, Osamah Abdulrahman Alnemer

Abstract:

Exhaustive application of sulfamethoxazole (SUX) became as a global threat for human health due to water contamination through diverse sources. The addressed combined application of Hansen solubility (HSPiP software) parameters and Quality by Design tool for developing various green nanoemulsions. HSPiP program assisted to screen suitable excipients based on Hansen solubility parameters and experimental solubility data. Various green nanoemulsions were prepared and characterized for globular size, size distribution, zeta potential, and removal efficiency. Design Expert (DoE) software further helped to identify critical factors responsible to have direct impact on percent removal efficiency, size, and viscosity. Morphological investigation was visualized under transmission electron microscopy (TEM). Finally, the treated was studied to negate the presence of the tested drug employing ICP-OES (inductively coupled plasma optical emission microscopy) technique and HPLC (high performance liquid chromatography). Results showed that HSPiP predicted biocompatible lipid, safe surfactant (lecithin), and propylene glycol (PG). Experimental solubility of the drug in the predicted excipients were quite convincing and vindicated. Various green nanoemulsions were fabricated, and these were evaluated for in vitro findings. Globular size (100-300 nm), PDI (0.1-0.5), zeta potential (~ 25 mV), and removal efficiency (%RE = 70-98%) were found to be in acceptable range for deciding input factors with level in DoE. Experimental design tool assisted to identify the most critical variables controlling %RE and optimized content of nanoemulsion under set constraints. Dispersion time was varied from 5-30 min. Finally, ICP-OES and HPLC techniques corroborated the absence of SUX in the treated water. Thus, the strategy is simple, economic, selective, and efficient.

Keywords: quality by design, sulfamethoxazole, green nanoemulsion, water treatment, icp-oes, hansen program (hspip software

Procedia PDF Downloads 61

Authors: Irene Yi

Abstract:

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 102

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

Abstract:

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

Procedia PDF Downloads 204

Authors: Godfrey Muiya Mukala

Abstract:

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

Procedia PDF Downloads 64

Authors: Akeel A. Shah, Tong Zhang

Abstract:

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

Procedia PDF Downloads 9

Authors: Tigabu Dagne Akal

Abstract:

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

Procedia PDF Downloads 283

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

Abstract:

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

Procedia PDF Downloads 511

Authors: Helge Rupprich, Elke Knisel

Abstract:

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

Procedia PDF Downloads 475

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

Abstract:

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

Procedia PDF Downloads 106

Authors: Mohsina Aktar, Bishawjit Mallick

Abstract:

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

Procedia PDF Downloads 260

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

Abstract:

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

Procedia PDF Downloads 154

Authors: Giorgi Methodishvili, Iuliia Methodishvili

Abstract:

In this paper product development algorithm is used to determine the optimal management of financial resources in company. Aspects of financial management considered include put initial investment, examine all possible ways to solve the problem and the optimal rotation length of profit. The software of given problems is based using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

Procedia PDF Downloads 43

Authors: Nandu C. Nair, Kamal Bijlani

Abstract:

This paper proposes a concept-based assessment to track the performance of the students. The idea behind this approach is to map the exam questions with the concepts learned in the course. So at the end of the course, each student will know how well he learned each concept. This system will give a self assessment for the students as well as instructor. By analyzing the score of all students, instructor can decide some concepts need to be teaching again or not. The system’s efficiency is proved using three courses from M-tech program in E-Learning technologies and results show that the concept-wise assessment improved the score in final exam of majority students on various courses.

Keywords: assessment, concept, examination, question, score

Procedia PDF Downloads 449

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

Abstract:

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

Procedia PDF Downloads 144

Authors: Suraj Mehrotra

Abstract:

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

Procedia PDF Downloads 81

Authors: Maryam Tabrizi, Shahrzad Aarup

Abstract:

Objectives- Understanding the close association between oral health and overall health for older adults at the right time and right place, a person, focus treatment through Project ECHO telementoring. Methodology- Data from monthly ECHO telementoring sessions were provided for three years. Sessions including case presentations, overall health conditions, considering medications, organ functions limitations, including the level of cognition. Contributions- Providing the specialist level of providing care to all elderly regardless of their location and other health conditions and decreasing oral health inequity by increasing workforce via Project ECHO telementoring program worldwide. By 2030, the number of adults in the USA over the age of 65 will increase more than 60% (approx.46 million) and over 22 million (30%) of 74 million older Americans will need specialized geriatrician care. In 2025, a national shortage of medical geriatricians will be close to 27,000. Most individuals 65 and older do not receive oral health care due to lack of access, availability, or affordability. One of the main reasons is a significant shortage of Oral Health (OH) education and resources for the elderly, particularly in rural areas. Poor OH is a social stigma, a thread to quality and safety of overall health of the elderly with physical and cognitive decline. Poor OH conditions may be costly and sometimes life-threatening. Non-traumatic dental-related emergency department use in Texas alone was over $250 M in 2016. Most elderly over the age of 65 present with at least one or multiple chronic diseases such as arthritis, diabetes, heart diseases, and chronic obstructive pulmonary disease (COPD) are at higher risk to develop gum (periodontal) disease, yet they are less likely to get dental care. In addition, most older adults take both prescription and over-the-counter drugs; according to scientific studies, many of these medications cause dry mouth. Reduced saliva flow due to aging and medications may increase the risk of cavities and other oral conditions. Most dental schools have already increased geriatrics OH in their educational curriculums, but the aging population growth worldwide is faster than growing geriatrics dentists. However, without the use of advanced technology and creating a network between specialists and primary care providers, it is impossible to increase the workforce, provide equitable oral health to the elderly. Project ECHO is a guided practice model that revolutionizes health education and increases the workforce to provide best-practice specialty care and reduce health disparities. Training oral health providers for utilizing the Project ECHO model is a logical response to the shortage and increases oral health access to the elderly. Project ECHO trains general dentists & hygienists to provide specialty care services. This means more elderly can get the care they need, in the right place, at the right time, with better treatment outcomes and reduces costs.

Keywords: geriatric, oral health, project echo, chronic disease, oral health

Procedia PDF Downloads 159

Authors: Mane Varosyan, Diana Tumanyan, Agnesa Martirosyan

Abstract:

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

Procedia PDF Downloads 60