Search results for: conditional proportional reversed hazard rate model

Authors: Ma. Cecilia D. Licuan

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The pandemic situation continues to affect the lives of many people, including children with disabilities and their families, globally, especially in developing countries like the Philippines. The operations of health programs, industries, and economic sectors, as well as academic training institutions, are still challenged in terms of operations and delivery of services. The academic community of the Physical Therapy program is not spared by this circumstance. The restriction posted by the quarantine policies nearly terminated the onsite delivery of training programs for the senior internship level, which challenged the academic institutions to implement flexible learning programs to ensure the continuity of the instructional and learning processes with full consideration of safety and compliance to health protocols. This study aimed to develop a benchmark model that can be used by tertiary-level health institutions in the implementation of the Pediatric Senior Clinical Internship Training Program using Telerehabilitation. It is a descriptive-qualitative paper that utilized documentary analysis and focused on explaining the design, development, and implementation processes used by De La Salle Medical and Health Sciences Institute – College of Rehabilitation Sciences (DLSMHSI-CRS) Physical Therapy Department in its Pediatric Cluster Senior Clinical Internship Training Program covering the pandemic years spanning from the academic year 2020- 2021 to present anchored on needs analysis based on documentary reviews. Results of the study yielded the determination of the Pediatric Telerehabilitation Model; declaration of developed training program outcomes and thrusts and content; explanation of the process integral to the training program’s pedagogy in implementation; and the evaluation procedures conducted for the program. Since the study did not involve human participants, ethical considerations on the use of documents for review were done upon the endorsement of the management of the DLSMHSI-CRS to conduct the study. This paper presents the big picture of how a tertiary-level health sciences institution in the Philippines embraced the senior clinical internship challenges through the operations of its telerehabilitation program. It specifically presents the design, development and implementation processes used by De La Salle Medical and Health Sciences Institute – College of Rehabilitation Sciences Physical Therapy Department in its Pediatric Cluster Senior Clinical Internship Training Program, which can serve as a benchmark model for other institutions as they continue to serve their stakeholders amidst the pandemic.

Keywords: pediatric physical therapy, telerehabilitation, clinical internship, pandemic

Procedia PDF Downloads 130

Authors: Mohammed Abdullah Alrajhi

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The rapid growth in the number of mobile phone subscribers has resulted in an increased number of mobile base stations all over the world. Generally, mobile base stations are existing in huge numbers in populated areas than in non-populated ones to serve the largest number of users. The total number of mobile subscriptions in the Kingdom of Saudi Arabia reached around 50 million at the end of 2014, with a penetration rate of 165.1% according to the quarterly electronic newsletter issued by the Communications and Information Technology Commission. The current investigation was conducted primarily to measure the level of electromagnetic fields emitted from 400 mobile base stations for the purpose of environmental safety and radiation protection in light of national guidelines for public exposure as well as the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The outcomes of this investigation provide valuable comments and recommendation for safety and protection of electromagnetic fields emitted from mobile base stations.

Keywords: electromagnetic fields, mobile, safety, protection, ICNIRP

Procedia PDF Downloads 425

Authors: Chia-Yung Chou, Che-Chuan Cheng, Chin Chi Hsu, Chun-Hui Wu

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This study investigates the fluid of boundary layer flow as it flows through the superhydrophobic surface. The superhydrophobic surface will be assembled into an observation channel for fluid experiments. The fluid in the channel will be doped with visual flow field particles, which will then be pumped by the syringe pump and introduced into the experimentally observed channel through the pipeline. Through the polarized light irradiation, the movement of the particles in the channel is captured by a high-speed camera, and the velocity of the particles is analyzed by MATLAB to find out the particle velocity field changes caused on the fluid boundary layer. This study found that the superhydrophobic surface can effectively increase the velocity near the wall surface, and the faster with the flow rate increases. The superhydrophobic surface also had longer the slip length compared with the plan surface. In the calculation of the drag coefficient, the superhydrophobic surface produces a lower drag coefficient, and there is a more significant difference when the Re reduced in the flow field.

Keywords: hydrophobic, boundary layer, slip length, friction

Procedia PDF Downloads 150

Authors: Mohammad Shakir, Reshma Jolly, Mohammad Shoeb Khan, Noor-E-Iram

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A nanocomposite system incorporating dextrin into nano-hydroxyapatite/chitin matrix (n-HA/DX/CT) has been successfully synthesized via co-precipitation route at room temperature for the application in bone tissue engineering by investigating biocompatibility, cytotoxicity and mechanical properties. The FTIR spectra of n-HA/DX/CT nanocomposite indicated a considerable intermolecular interaction between the various components of the system. The results of XRD, TEM and TGA/DTA revealed that the crystallinity, size and thermal stability of the n-HA/DX/CT scaffold has decreased and increased respectively. The result of SEM image of the n-HA/DX/CT scaffold indicated that the incorporation of dextrin affected the surface morphology while considerable in-vitro bioactivity has been observed in n-HA/DX/CT based on SBF study, referring a step towards possibility of making direct bond to living bone if implanted. Moreover, MTT assay suggested the non-toxic nature of n-HA/DX/CT to murine fibroblast L929 cells. The swelling study of n-HA/DX/CT scaffold indicated the low swelling rate for n-HADX/CT. All these results have paved the way for n-HA/DX/CT to be used as a competent material for bone tissue engineering.

Keywords: autograft, chitin, dextrin, nanocomposite

Procedia PDF Downloads 538

Authors: P. J. Sweeney, T. Ahtoniemi, J. Puoliväli, T. Laitinen, K. Lehtimäki, A. Nurmi, D. Wells

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Duchenne muscular dystrophy (DMD) is caused by an X linked mutation in the dystrophin gene; lack of dystrophin causes a progressive muscle necrosis which leads to a progressive decrease in mobility in those suffering from the disease. The MDX mouse, a mutant mouse model which displays a frank dystrophinopathy, is currently widely employed in pre clinical efficacy models for treatments and therapies aimed at DMD. In general the end-points examined within this model have been based on invasive histopathology of muscles and serum biochemical measures like measurement of serum creatine kinase (sCK). It is established that a “critical period” between 4 and 6 weeks exists in the MDX mouse when there is extensive muscle damage that is largely sub clinical but evident with sCK measurements and histopathological staining. However, a full characterization of the MDX model remains largely incomplete especially with respect to the ability to aggravate of the muscle damage beyond the critical period. The purpose of this study was to attempt to aggravate the muscle damage in the MDX mouse and to create a wider, more readily translatable and discernible, therapeutic window for the testing of potential therapies for DMD. The study consisted of subjecting 15 male mutant MDX mice and 15 male wild-type mice to an intense chronic exercise regime that consisted of bi-weekly (two times per week) treadmill sessions over a 12 month period. Each session was 30 minutes in duration and the treadmill speed was gradually built up to 14m/min for the entire session. Baseline plasma creatine kinase (pCK), treadmill training performance and locomotor activity were measured after the “critical period” at around 10 weeks of age and again at 14 weeks of age, 6 months, 9 months and 12 months of age. In addition, kinematic gait analysis was employed using a novel analysis algorithm in order to compare changes in gait and fine motor skills in diseased exercised MDX mice compared to exercised wild type mice and non exercised MDX mice. In addition, a morphological and metabolic profile (including lipid profile), from the muscles most severely affected, the gastrocnemius muscle and the tibialis anterior muscle, was also measured at the same time intervals. Results indicate that by aggravating or exacerbating the underlying muscle damage in the MDX mouse by exercise a more pronounced and severe phenotype in comes to light and this can be picked up earlier by kinematic gait analysis. A reduction in mobility as measured by open field is not apparent at younger ages nor during the critical period, but changes in gait are apparent in the mutant MDX mice. These gait changes coincide with pronounced morphological and metabolic changes by non-invasive anatomical MRI and proton spectroscopy (1H-MRS) we have reported elsewhere. Evidence of a progressive asymmetric pathology in imaging parameters as well as in the kinematic gait analysis was found. Taken together, the data show that chronic exercise regime exacerbates the muscle damage beyond the critical period and the ability to measure through non-invasive means are important factors to consider when performing preclinical efficacy studies in the MDX mouse.

Keywords: Gait, muscular dystrophy, Kinematic analysis, neuromuscular disease

Procedia PDF Downloads 279

Authors: P. Hooshangitabrizi, I. Contreras, N. Bhuiyan

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This work presents an online scheduling problem which accommodates multiple requests of patients for chemotherapy treatments in a cancer center of a major metropolitan hospital in Canada. To solve the problem, an adaptive flexible approach is proposed which systematically combines two optimization models. The first model is intended to dynamically schedule arriving requests in the form of waiting lists whereas the second model is used to reschedule the already booked patients with the goal of finding better resource allocations when new information becomes available. Both models are created as mixed integer programming formulations. Various controllable and flexible parameters such as deviating the prescribed target dates by a pre-determined threshold, changing the start time of already booked appointments and the maximum number of appointments to move in the schedule are included in the proposed approach to have sufficient degrees of flexibility in handling arrival requests and unexpected changes. Several computational experiments are conducted to evaluate the performance of the proposed approach using historical data provided by the oncology clinic. Our approach achieves outstandingly better results as compared to those of the scheduling system being used in practice. Moreover, several analyses are conducted to evaluate the effect of considering different levels of flexibility on the obtained results and to assess the performance of the proposed approach in dealing with last-minute changes. We strongly believe that the proposed flexible adaptive approach is very well-suited for implementation at the clinic to provide better patient-care services and to utilize available resource more efficiently.

Keywords: chemotherapy scheduling, multi-appointment modeling, optimization of resources, satisfaction of patients, mixed integer programming

Procedia PDF Downloads 174

Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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Authors: Cheryl M. Bowen

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Understanding that children thrive in a multi-systems approach to mental health development, a growing number of schools often promote school-based positive youth development however, there is scant empirical evidence investigating effective school-based “wraparound” mental health services for low income, Latinx children and their families. This 10-month case study utilizes a sample of 281 low-income, Latinx parents and their children, and 23 K-5th grade teachers living in northern California to test the hypothesis that a school-based mental health program can strengthen students’ developmental asset attainment and positively impact the school environment. The study utilized triangulated data to ascertain the effects of two program levels - (a) mental health and (b) positive child development services. All services were site-based and meant to target a wide variety of families. Findings from the study report that the universal mental health program increased the developmental asset attainment in 5 out of 8 thriving indicators thus transforming the child within his/her environment. Data collected from the administrative referral report demonstrate that the project also positively impacted the school climate. Parents and teachers felt more connected to the school, and referrals were down for discipline (35%), academics (66%), and suspensions (51%). The study concludes that a transformational ecology model of positive child development is the most effective means to nurture connections to all socializing agencies in a child’s ecosystem.

Keywords: case study, child development, positive youth development, developmental assets, ecological systems theory

Procedia PDF Downloads 81

Authors: O. D. Adegbehingbe, S. D. Eyono Obono

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The education sector is constantly faced with rapid changes in technologies in terms of ensuring that the curriculum is up to date and in terms of making sure that students are aware of these technological changes. This challenge can be seen as the motivation for this study, which is to examine the factors affecting computing students’ awareness of the latest Information Technologies (ICTs). The aim of this study is divided into two sub-objectives which are: the selection of relevant theories and the design of a conceptual model to support it as well as the empirical testing of the designed model. The first objective is achieved by a review of existing literature on technology adoption theories and models. The second objective is achieved using a survey of computing students in the four universities of the KwaZulu-Natal province of South Africa. Data collected from this survey is analyzed using Statistical package for the Social Science (SPSS) using descriptive statistics, ANOVA and Pearson correlations. The main hypothesis of this study is that there is a relationship between the demographics and the prior conditions of the computing students and their awareness of general ICT trends and of Digital Switch Over (DSO) a new technology which involves the change from analog to digital television broadcasting in order to achieve improved spectrum efficiency. The prior conditions of the computing students that were considered in this study are students’ perceived exposure to career guidance and students’ perceived curriculum currency. The results of this study confirm that gender, ethnicity, and high school computing course affect students’ perceived curriculum currency while high school location affects students’ awareness of DSO. The results of this study also confirm that there is a relationship between students prior conditions and their awareness of general ICT trends and DSO in particular.

Keywords: education, information technologies, IDT, awareness

Procedia PDF Downloads 361

Authors: Deyadeen Ali Alshibani

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

Keywords: optimal, bandit problem, optimization, dynamic programming

Procedia PDF Downloads 456

Authors: Trang Huyen Nguyen, Thien Tri Huynh

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The objectives of this paper were to determine demographics of readers at Hochiminh city (HCMC), study reading motivation which affected citizens to read sports newspapers and measure readers’ satisfaction on issues related sports newspapers. Subjects of this survey were HCMC’s citizens. After collecting data, there were 568 useful feedbacks (the rate of response was 94.7%). The data analysis in the study included descriptive statistics and inferred statistics by SPSS 16.0 program for the research questions. The majority of respondents were male, from 24 to 32 years old, got the first degree and earned monthly from $US 150 to 300. Moreover, they were government officials and read newspaper from 11 to 20 times per month, bought newspapers by themselves. Finding information to predict results of sports matches was the highest motive affected readers; and the diversity information was the most pleasure that readers felt about sports newspapers. According to research findings, the board of editors could use the worthy information to make a strategic plan for newspaper on contents as well as design to meet the increasing demands of readers.

Keywords: motivation, satisfaction, readers, sports newspapers

Procedia PDF Downloads 307

Authors: Aura Alejandra Burbano Patino, Mariela Agotegaray, Veronica Lassalle, Fernanda Horst

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Water pollution is of worldwide concern due to its importance as an essential resource for life. Industrial and urbanistic growth are anthropogenic activities that have caused an increase of undesirable compounds in water. In the last decade, emerging pollutants have become of great interest since, at very low concentrations (µg/L and ng/L), they exhibit a hazardous effect on wildlife, aquatic ecosystems, and human organisms. One group of emerging pollutants that are a matter of study are pharmaceuticals. Their high consumption rate and their inappropriate disposal have led to their detection in wastewater treatment plant influent, effluent, surface water, and drinking water. In consequence, numerous technologies have been developed to efficiently treat these pollutants. Adsorption appears like an easy and cost-effective technology. One of the most used adsorbents of emerging pollutants removal is carbon-based materials such as hydrochars. This study aims to use a magnetic hydrochar nanocomposite to be employed as an adsorbent for diclofenac removal. Kinetics models and the adsorption efficiency in real water samples were analyzed. For this purpose, a magnetic hydrochar nanocomposite was synthesized through the hydrothermal carbonization (HTC) technique hybridized to co-precipitation to add the magnetic component into the hydrochar, based on iron oxide nanoparticles. The hydrochar was obtained from sunflower husk residue as the precursor. TEM, TGA, FTIR, Zeta potential as a function of pH, DLS, BET technique, and elemental analysis were employed to characterize the material in terms of composition and chemical structure. Adsorption kinetics were carried out in distilled water and real water at room temperature, pH of 5.5 for distilled water and natural pH for real water samples, 1:1 adsorbent: adsorbate dosage ratio, contact times from 10-120 minutes, and 50% dosage concentration of DCF. Results have demonstrated that magnetic hydrochar presents superparamagnetic properties with a saturation magnetization value of 55.28 emu/g. Besides, it is mesoporous with a surface area of 55.52 m²/g. It is composed of magnetite nanoparticles incorporated into the hydrochar matrix, as can be proven by TEM micrographs, FTIR spectra, and zeta potential. On the other hand, kinetic studies were carried out using DCF models, finding percent removal efficiencies up to 85.34% after 80 minutes of contact time. In addition, after 120 minutes of contact time, desorption of emerging pollutants from active sites took place, which indicated that the material got saturated after that t time. In real water samples, percent removal efficiencies decrease up to 57.39%, ascribable to a possible mechanism of competitive adsorption of organic or inorganic compounds, ions for active sites of the magnetic hydrochar. The main suggested adsorption mechanism between the magnetic hydrochar and diclofenac include hydrophobic and electrostatic interactions as well as hydrogen bonds. It can be concluded that the magnetic hydrochar nanocomposite could be valorized into a by-product which appears as an efficient adsorbent for DCF removal as a model emerging pollutant. These results are being complemented by modifying experimental variables such as pollutant’s initial concentration, adsorbent: adsorbate dosage ratio, and temperature. Currently, adsorption assays of other emerging pollutants are being been carried out.

Keywords: environmental remediation, emerging pollutants, hydrochar, magnetite nanoparticles

Procedia PDF Downloads 197

Authors: Jerlin George, R. Chitra

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The devices with sensors that can monitor your temperature, heart rate, and other vital signs and link to the internet, known as the Internet of Things (IoT), have completely transformed the way we control health. Providing real-time health data, these sensors improve diagnostics and treatment outcomes. Security and privacy matters when IoT comes into play in healthcare. Cyberattacks on centralized database systems are also a problem. To solve these challenges, the study uses blockchain technology coupled with proxy re-encryption to secure health data. ThingSpeak IoT cloud analyzes the collected data and turns them into blockchain transactions which are safely kept on the DriveHQ cloud. Transparency and data integrity are ensured by blockchain, and secure data sharing among authorized users is made possible by proxy re-encryption. This results in a health monitoring system that preserves the accuracy and confidentiality of data while reducing the safety risks of IoT-driven healthcare applications.

Keywords: internet of things, healthcare, sensors, electronic health records, blockchain, proxy re-encryption, data privacy, data security

Procedia PDF Downloads 23

Authors: Sang Ho Lee, Tae Heon Moon, Youn Taik Leem, Kwang Woo Nam

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Knowledge and IT inputs to other industrial production have become more important as a key factor for the competitiveness of national and regional economies, such as knowledge economies in smart cities. Knowledge and IT industries lead the industrial innovation and technical (r)evolution through low cost, high efficiency in production, and by creating a new value chain and new production path chains, which is referred as knowledge and IT dynamics. This study aims to investigate the knowledge and IT dynamics in Korea, which are analyzed through the input-output model and structural path analysis. Twenty-eight industries were reclassified into seven categories; Agriculture and Mining, IT manufacture, Non-IT manufacture, Construction, IT-service, Knowledge service, Non-knowledge service to take close look at the knowledge and IT dynamics. Knowledge and IT dynamics were analyzed through the change of input output coefficient and multiplier indices in terms of technical innovation, as well as the changes of the structural paths of the knowledge and IT to other industries in terms of new production value creation from 1985 and 2010. The structural paths of knowledge and IT explain not only that IT foster the generation, circulation and use of knowledge through IT industries and IT-based service, but also that knowledge encourages IT use through creating, sharing and managing knowledge. As a result, this paper found the empirical investigation on the knowledge and IT dynamics of the Korean economy. Knowledge and IT has played an important role regarding the inter-industrial transactional input for production, as well as new industrial creation. The birth of the input-output production path has mostly originated from the knowledge and IT industries, while the death of the input-output production path took place in the traditional industries from 1985 and 2010. The Korean economy has been in transition to a knowledge economy in the Smart City.

Keywords: knowledge and IT industries, input-output model, structural path analysis, dynamics of knowledge and it, knowledge economy, knowledge city and smart city

Procedia PDF Downloads 336

Authors: Kai-Wei Ji, Dung-Ying Lin

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This study investigates the impact of transportation on housing prices in regions surrounding Taiwan's science parks. As these parks evolve into crucial economic and population growth centers, they attract an increasing number of residents and workers, significantly influencing local housing markets. This demographic shift raises important questions about the role of transportation in shaping real estate values. Our research examines four major science parks in Taiwan, providing a comparative analysis of how transportation conditions and population dynamics interact to affect housing price premiums. We employ an origin-destination (OD) matrix derived from pervasive traffic data to model travel patterns and their effects on real estate values. The methodology utilizes a bi-level framework: a genetic algorithm optimizes OD demand estimation at the upper level, while a user equilibrium (UE) model simulates traffic flow at the lower level. This approach enables a nuanced exploration of how population growth impacts transportation conditions and housing price premiums. By analyzing the interplay between travel costs based on OD demand estimation and housing prices, we offer valuable insights for urban planners and policymakers. These findings are crucial for informed decision-making in rapidly developing areas, where understanding the relationship between mobility and real estate values is essential for sustainable urban development.

Keywords: demand estimation, genetic algorithm, housing price, transportation

Procedia PDF Downloads 27

Authors: Jane A. Luke

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Persistent pressure passed on to manufacturers from escalating consumer expectations and the ever growing global competitiveness have produced a rapidly increasing interest in the development of various manufacturing strategy models. Academic and industrial circles are taking keen interest in the field of manufacturing strategy. Many manufacturing strategies are currently centered on the traditional concepts of focused manufacturing capabilities such as quality, cost, dependability and innovation. Process capability indices was conducted assuming that the process under study is in statistical control and independent observations are generated over time. However, in practice, it is very common to come across processes which, due to their inherent natures, generate autocorrelated observations. The degree of autocorrelation affects the behavior of patterns on control charts. Even, small levels of autocorrelation between successive observations can have considerable effects on the statistical properties of conventional control charts. When observations are autocorrelated the classical control charts exhibit nonrandom patterns and lack of control. Many authors have considered the effect of autocorrelation on the performance of statistical process control charts. In this paper, the effect of autocorrelation on confidence intervals for different PCIs was included. Stationary Gaussian processes is explained. Effect of autocorrelation on PCIs is described in detail. Confidence intervals for Cp and Cpk are constructed for PCIs when data are both independent and autocorrelated. Confidence intervals for Cp and Cpk are computed. Approximate lower confidence limits for various Cpk are computed assuming AR(1) model for the data. Simulation studies and industrial examples are considered to demonstrate the results.

Keywords: autocorrelation, AR(1) model, Bissell’s approximation, confidence intervals, statistical process control, specification limits, stationary Gaussian processes

Procedia PDF Downloads 394

Authors: Sejin Jung, Dongho Kang, Byungsik Kim

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Assessing the impact of climate change requires the use of a multi-model ensemble (MME) to quantify uncertainties between scenarios and produce downscaled outlines for simulation of climate under the influence of different factors, including topography. This study decreases climate change scenarios from the 13 global climate models (GCMs) to assess the impacts of future climate change. Unlike South Korea, North Korea lacks in studies using climate change scenarios of the CoupledModelIntercomparisonProject (CMIP5), and only recently did the country start the projection of extreme precipitation episodes. One of the main purposes of this study is to predict changes in the average climatic conditions of North Korea in the future. The result of comparing downscaled climate change scenarios with observation data for a reference period indicates high applicability of the Multi-Model Ensemble (MME). Furthermore, the study classifies climatic zones by applying the Köppen-Geiger climate classification system to the MME, which is validated for future precipitation and temperature. The result suggests that the continental climate (D) that covers the inland area for the reference climate is expected to shift into the temperate climate (C). The coefficient of variation (CVs) in the temperature ensemble is particularly low for the southern coast of the Korean peninsula, and accordingly, a high possibility of the shifting climatic zone of the coast is predicted. This research was supported by a grant (MOIS-DP-2015-05) of Disaster Prediction and Mitigation Technology Development Program funded by Ministry of Interior and Safety (MOIS, Korea).

Keywords: MME, North Korea, Koppen–Geiger, climatic zones, coefficient of variation, CV

Procedia PDF Downloads 115

Authors: Gehan Labib Abuelenain, Azza Fahmi, Salma Awad Mahmoud

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Toxoplasmosis is a global parasitic disease caused by the protozoan Toxoplasma gondii (T. gondii), with a high infection rate that affects one third of the human population and results in severe implications in pregnant women, neonates, and immunocompromised patients. Anti-parasitic treatments and schemes available against toxoplasmosis have barely evolved over the last two decades. The available T. gondii therapeutics cannot completely eradicate tissue cysts produced by the parasite and are not well-tolerated by immunocompromised patients. This work aims to highlight new trends in Toxoplasma gondii diagnosis by providing a comprehensive overview of the field, summarizing recent findings, and discussing the new technological advancements in toxoplasma diagnosis and treatment. Advancements in therapeutics utilizing trends in molecular biophysics, such as biosensors, epigenetics, and artificial intelligence (AI), might provide solutions for disease management and prevention. These insights will provide tools to identify research gaps and proffer planning options for disease control.

Keywords: toxoplamosis, diagnosis, therapeutics, biosensors, AI

Procedia PDF Downloads 43

Authors: Abdallah Q. Bataineh

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The electronics market in Jordan is facing extraordinary expectations from consumers, whose opinions are progressively more essential and have effective power on the overall marketing strategy preparation and execution by electronics agents. This research aimed to explore the effect of price volatile, follow-up, maintenance and warranty policy on distributor’s retention. Focus group, in-depth interviews, and self-administered questionnaire were held with a total sample of 50 electronics distribution stores who have a direct contact and purchase frequently from electronic agencies. By using descriptive statistics and multiple regression tests, the main findings of this research is that there is an impact of price volatile, follow-up, maintenance and warranty policy on distributor’s retention, and the key predictor variable was price volatile. Thus, the researcher recommended flat rate pricing strategy to ensure that all distributors will sell the product on the same pricing base, regardless of the generated margin by each one of them. Moreover, conclusion and future research were also discussed.

Keywords: distributors retention, follow-up, maintenance, price volatile, warranty policy

Procedia PDF Downloads 241

Authors: Sun-Mi Park, Ji-Hyun Jung, Min-Jung Kang

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Software (SW) education is scheduled to be included in the National curriculum in South Korea by 2018. However, Korean national kindergarten curriculum has been excepted from the revision of the entire Korean national school curriculum including software education. Even though the SW education has not been considered a part of current national kindergarten curriculum, there is a growing interest of adopting software education into the ECE practice. Teachers might be a key element in introducing and implementing new educational change such as SW education. In preparation for the adoption of SW education in ECE, it might be necessary to figure out ECE teachers’ perception and attitudes toward early childhood software education. For this study, 219 ECE teachers’ concern level in SW education was surveyed by using the Stages of Concern Questionnaire (SoCQ). As a result, the teachers' concern level in SW education is the highest at stage 0-Unconcerned and is high level in stage 1-informational, stage 2-personal, and stage 3-management concern. Thus, a non-user pattern was mostly indicated. However, compared to a typical non-user pattern, the personal and informative concern level is slightly high. The 'tailing up' phenomenon toward stage 6-refocusing was shown. Therefore, the pattern aspect close to critical non-user ever appeared to some extent. In addition, a significant difference in concern level was shown at all stages depending on the awareness of necessity. Teachers with SW training experience showed higher intensity only at stage 0. There was statistically significant difference in stage 0 and 6 depending on the future implementation decision. These results will be utilized as a resource in building ECE teachers’ support system according to his or her concern level of SW education.

Keywords: concerns-based adoption model (CBAM), early childhood education teachers, software education, Stages of Concern (SoC)

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Authors: Minjung Park, Jimin Park, Youngwoon Kim, Hyungseop Han, Myoungryul Ok, Hojeong Jeon, Hyunkwang Seok, Yuchan Kim

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Magnesium is an essential element in human body and has unique characteristics such as bioabsorbable and biodegradable properties. Therefore, there has been much attention on studies on the implants based on magnesium to avoid subsequent surgery. However, high amount of hydrogen gas is generated by relatively severe corrosion of magnesium especially in aqueous condition with chloride ions. And it contributes to the causes of swelling of skin and causes consequent inflammation of soft tissue where is directly in contact with implants. Therefore, there is still concern about the safety of the using biodegradable magnesium alloys, which is limited to various applications. In this study, we analyzed the influence of coenzyme on corrosion behavior of magnesium. The analysis of corrosion rate was held by using Hanks’ balanced salt solution (HBSS) as a body stimulated fluid and in condition of 37°C. Thus, with deferring the concentration of the coenzyme used in this study, corrosion rates from 0.0654ml/ cm² to 0.0438ml/cm² were observed in immersion tests. Also, comparable results were obtained in electrochemical tests. Results showed that hydrogen gas produced from corrosion of magnesium can be controlled.

Keywords: biodegradable magnesium, biomaterials, coenzyme, corrosion

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Authors: Lydia Chan, Islam Shyha, Dale Dreyer, John Hamilton, Phil Hackney

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Nickel-based superalloys are generally known to be difficult to cut due to their strength, low thermal conductivity, and high work hardening tendency. Superalloy such as alloy 625 is often used in the oil and gas industry as a surfacing material to provide wear and corrosion resistance to components. The material is typically applied onto a metallic substrate through weld overlay cladding, an arc welding technique. Cladded surfaces are always rugged and carry a tough skin; this creates further difficulties to the machining process. The present work utilised design of experiment to optimise the internal cylindrical rough turning for weld overlay surfaces. An L27 orthogonal array was used to assess effects of the four selected key process variables: cutting insert, depth of cut, feed rate, and cutting speed. The optimal cutting conditions were determined based on productivity and the level of tool wear.

Keywords: cylindrical turning, nickel superalloy, turning of overlay, weld overlay

Procedia PDF Downloads 379

Authors: Shaibu Baanni Azumah, Ignatius Tindjina, Stella Obanyi, Tara N. Wood

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This study examined the effect of Urea Deep Placement (UDP) technology on the output of irrigated rice farmers in the northern region of Ghana. Multi-stage sampling technique was used to select 142 rice farmers from the Golinga and Bontanga irrigation schemes, around Tamale. A treatment effect model was estimated at two stages; firstly, to determine the factors that influenced farmers’ decision to adopt the UDP technology and secondly, to determine the effect of the adoption of the UDP technology on the output of rice farmers. The significant variables that influenced rice farmers’ adoption of the UPD technology were sex of the farmer, land ownership, off-farm activity, extension service, farmer group participation and training. The results also revealed that farm size and the adoption of UDP technology significantly influenced the output of rice farmers in the northern region of Ghana. In addition to the potential of the technology to improve yields, it also presents an employment opportunity for women and youth, who are engaged in the deep placement of Urea Super Granules (USG), as well as in the transplantation of rice. It is recommended that the government of Ghana work closely with the IFDC to embed the UDP technology in the national agricultural programmes and policies. The study also recommends an effective collaboration between the government, through the Ministry of Food and Agriculture (MoFA) and the International Fertilizer Development Center (IFDC) to train agricultural extension agents on UDP technology in the rice producing areas of the country.

Keywords: Northern Ghana, output , irrigation rice farmers, treatment effect model, urea deep placement

Procedia PDF Downloads 440

Authors: Yohannes Bisa Biramo

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This study examined the meditational role of surface acting and deep acting on the relationship between calling orientation and work engagement of teachers in secondary schools of Wolaita Zone, Wolaita, Ethiopia. A predictive non-experimental correlational design was performed among 300 secondary school teachers. Stratified random sampling followed by a systematic random sampling technique was used as the basis for selecting samples from the target population. To analyze the data, Structural Equation Modeling (SEM) was used to test the association between the independent variables and the dependent variables. Furthermore, the goodness of fit of the study variables was tested using SEM to see and explain the path influence of the independent variable on the dependent variable. Confirmatory factor analysis (CFA) was conducted to test the validity of the scales in the study and to assess the measurement model fit indices. The analysis result revealed that calling was significantly and positively correlated with surface acting, deep acting and work engagement. Similarly, surface acting was significantly and positively correlated with deep acting and work engagement. And also, deep acting was significantly and positively correlated with work engagement. With respect to mediation analysis, the result revealed that surface acting mediated the relationship between calling and work engagement and also deep acting mediated the relationship between calling and work engagement. Besides, by using the model of the present study, the school leaders and practitioners can identify a core area to be considered in recruiting and letting teachers teach, in giving induction training for newly employed teachers and in performance appraisal.

Keywords: calling, surface acting, deep acting, work engagement, mediation, teachers

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Authors: Hamdi Beji, Toufik Kanit, Tanguy Messager

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This study aims to construct a predictive model proficient in foreseeing the linear elastic and thermal characteristics of composite materials, drawing on a multitude of influencing parameters. These parameters encompass the shape of inclusions (circular, elliptical, square, triangle), their spatial coordinates within the matrix, orientation, volume fraction (ranging from 0.05 to 0.4), and variations in contrast (spanning from 10 to 200). A variety of machine learning techniques are deployed, including decision trees, random forests, support vector machines, k-nearest neighbors, and an artificial neural network (ANN), to facilitate this predictive model. Moreover, this research goes beyond the predictive aspect by delving into an inverse analysis using genetic algorithms. The intent is to unveil the intrinsic characteristics of composite materials by evaluating their thermomechanical responses. The foundation of this research lies in the establishment of a comprehensive database that accounts for the array of input parameters mentioned earlier. This database, enriched with this diversity of input variables, serves as a bedrock for the creation of machine learning and genetic algorithm-based models. These models are meticulously trained to not only predict but also elucidate the mechanical and thermal conduct of composite materials. Remarkably, the coupling of machine learning and genetic algorithms has proven highly effective, yielding predictions with remarkable accuracy, boasting scores ranging between 0.97 and 0.99. This achievement marks a significant breakthrough, demonstrating the potential of this innovative approach in the field of materials engineering.

Keywords: machine learning, composite materials, genetic algorithms, mechanical and thermal proprieties

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Authors: Rajkumar Ghosh

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Water scarcity is a significant challenge in urban areas, even in smart cities (Lucknow, Bangalore, Jaipur, etc.) where efficient resource management is prioritized. The depletion of groundwater resources in Gomti Nagar, Lucknow, Uttar Pradesh, India is particularly severe, posing a significant challenge for sustainable development in the region. This study focuses on addressing the water shortage by investigating the effectiveness of rooftop rainwater harvesting systems (RTRWHs) as a sustainable approach to bridge the gap between groundwater recharge and extraction. The aim of this study is to assess the effectiveness of RTRWHs in reducing aquifer depletion and addressing the water scarcity issue in the Gomti Nagar region. The research methodology involves the utilization of RTRWHs as the primary method for collecting rainwater. RTRWHs will be implemented in residential and commercial buildings to maximize the collection of rainwater. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. Statistical analysis and modelling techniques were employed to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The study reveals that the installation of RTRWHs in the Gomti Nagar region has a positive impact on addressing the water scarcity issue. Currently, RTRWHs cover only a small percentage of the total rainfall collected in the region. However, when RTRWHs are installed in all buildings, their influence on increasing water availability and reducing aquifer depletion will be significantly greater. The study also highlights the significant water imbalance in the region, emphasizing the urgent need for sustainable water management practices. This research contributes to the theoretical understanding of sustainable water management systems in smart cities. By highlighting the effectiveness of RTRWHs in reducing aquifer depletion, it emphasizes the importance of implementing such systems in urban areas. Data for this study were collected through various sources such as government reports, surveys, and existing groundwater abstraction patterns. The collected data were then analysed using statistical analysis and modelling techniques to assess the current water situation, groundwater depletion rate, and the potential impact of implementing RTRWHs. The findings of this study demonstrate that the implementation of RTRWHs can effectively mitigate the water scarcity crisis in Gomti Nagar. By reducing aquifer depletion and bridging the gap between groundwater recharge and extraction, RTRWHs offer a sustainable solution to the region's water scarcity challenges. Widespread adoption of RTRWHs in all buildings and integration into urban planning and development processes are crucial for efficient water management in smart cities like Gomti Nagar. These findings can serve as a basis for policymakers, urban planners, and developers to prioritize and incentivize the installation of RTRWHs as a potential solution to the water shortage crisis.

Keywords: water scarcity, urban areas, smart cities, resource management, groundwater depletion, rooftop rainwater harvesting systems, sustainable development, sustainable water management, mitigating water scarcity

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Authors: Karen Trimmer, Raelene Ward, Linda Wondunna-Foley

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Within Australian tertiary institutions, the subject of Aboriginal and Torres Strait Islander education has been a major concern for many years. Aboriginal and Torres Strait Islander teachers are significantly under-represented in Australian schools and universities. High attrition rates in teacher education and in the teaching industry have contributed to a minimal growth rate in the numbers of Aboriginal and Torres Strait Islander teachers in previous years. There was an increase of 500 Indigenous teachers between 2001 and 2008 but these numbers still only account for one percent of teaching staff in government schools who identified as Aboriginal and Torres Strait Islander Australians (Ministerial Council for Education, Early Childhood Development and Youth Affairs 2010). Aboriginal and Torres Strait Islander teachers are paramount in fostering student engagement and improving educational outcomes for Indigenous students. Increasing the numbers of Aboriginal and Torres Strait Islander teachers is also a key factor in enabling all students to develop understanding of and respect for Aboriginal and Torres Strait Islander histories, cultures, and language. An ambitious reform agenda to improve the recruitment and retention of Aboriginal and Torres Strait Islander teachers will be effective only through national collaborative action and co-investment by schools and school authorities, university schools of education, professional associations, and Indigenous leaders and community networks. Whilst the University of Southern Queensland currently attracts Indigenous students to its teacher education programs (61 students in 2013 with an average of 48 enrollments each year since 2010) there is significant attrition during pre-service training. The annual rate of exiting before graduation remains high at 22% in 2012 and was 39% for the previous two years. These participation and retention rates are consistent with other universities across Australia. Whilst aspirations for a growing number of Indigenous people to be trained as teachers is present, there is a significant loss of students during their pre-service training and within the first five years of employment as a teacher. These trends also reflect the situation where Aboriginal and Torres Strait Islander teachers are significantly under-represented, making up less than 1% of teachers in schools across Australia. Through a project conducted as part the nationally funded More Aboriginal and Torres Strait Islander Teachers Initiative (MATSITI) we aim to gain an insight into the reasons that impact Aboriginal and Torres Strait Islander student’s decisions to exit their program. Through the conduct of focus groups and interviews with two graduating cohorts of self-identified Aboriginal and Torres Strait Islander students, rich data has been gathered to gain an understanding of the barriers and enhancers to the completion of pre-service qualification and transition to teaching. Having a greater understanding of these reasons then allows the development of collaborative processes and procedures to increase retention and completion rates of new Indigenous teachers. Analysis of factors impacting on exit decisions and transitions has provided evidence to support change of practice, redesign and enhancement of relevant courses and development of policy/procedures to address identified issues.

Keywords: graduation, indigenous, pre-service teacher education, retention

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Authors: Aayushi Lyngwa, Bimal Kishore Sahoo

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The study discusses the relationship between cognitive ability and the level of education attained by the tribal street entrepreneurs on their financial literacy. It is driven by the objective of examining the effect of cognitive ability on financial ability on the one hand and determining the effect of the same on financial literacy on the other. A field experiment was conducted on 203 tribal street vendors in the north-eastern Indian state of Mizoram. This experiment's calculations are conditioned by providing each question scores like math score (cognitive ability), financial score and debt score (financial ability). After that, categories for each of the variables, like math category (math score), financial category (financial score) and debt category (debt score), are generated to run the regression model. Since the dependent variable is ordinal, an ordered logit regression model was applied. The study shows that street vendors' cognitive and financial abilities are highly correlated. It, therefore, confirms that cognitive ability positively affects the financial literacy of street vendors through the increase in attainment of educational levels. It is also found that concerning the type of street vendors, regular street vendors are more likely to have better cognitive abilities than temporary street vendors. Additionally, street vendors with more cognitive and financial abilities gained better monthly profits and performed habits of bookkeeping. The study attempts to draw a particular focus on a set-up which is economically and socially marginalized in the Indian economy. Its finding contributes to understanding financial literacy in an understudied area and provides policy implications through inclusive financial systems solutions in an economy limited to tribal street vendors.

Keywords: financial literacy, education, street entrepreneurs, tribals, cognitive ability, financial ability, ordered logit regression.

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Authors: Lassaad Smirani

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In this paper we propose a Neurosymbolic Learning System (NLS) as a channel estimator for Long Term Evolution Advanced (LTE-A) uplink. The proposed system main idea based on Neural Network has modules capable of performing bidirectional information transfer between symbolic module and connectionist module. We demonstrate various strengths of the NLS especially the ability to integrate theoretical knowledge (rules) and experiential knowledge (examples), and to make an initial knowledge base (rules) converted into a connectionist network. Also to use empirical knowledge witch by learning will have the ability to revise the theoretical knowledge and acquire new one and explain it, and finally the ability to improve the performance of symbolic or connectionist systems. Compared with conventional SC-FDMA channel estimation systems, The performance of NLS in terms of complexity and quality is confirmed by theoretical analysis and simulation and shows that this system can make the channel estimation accuracy improved and bit error rate decreased.

Keywords: channel estimation, SC-FDMA, neural network, hybrid system, BER, LTE-A

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Authors: Pavlo Selyshchev, Samuel Akintunde

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A theoretical approach to consider formation of chemical compound layer at the interface between initial substances A and B due to the interfacial interaction and diffusion is developed. It is considered situation when speed of interfacial interaction is large enough and diffusion of A-atoms through AB-layer is much more then diffusion of B-atoms. Atoms from A-layer diffuse toward B-atoms and form AB-atoms on the surface of B-layer. B-atoms are assumed to be immobile. The growth kinetics of the AB-layer is described by two differential equations with non-linear coupling, producing a good fit to the experimental data. It is shown that growth of the thickness of the AB-layer determines by dependence of chemical reaction rate on reactants concentration. In special case the thickness of the AB-layer can grow linearly or parabolically depending on that which of processes (interaction or the diffusion) controls the growth. The thickness of AB-layer as function of time is obtained. The moment of time (transition point) at which the linear growth are changed by parabolic is found.

Keywords: phase formation, binary systems, interfacial reaction, diffusion, compound layers, growth kinetics

Procedia PDF Downloads 574