Search results for: learning strategy
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10109

Search results for: learning strategy

2789 An Auxiliary Technique for Coronary Heart Disease Prediction by Analyzing Electrocardiogram Based on ResNet and Bi-Long Short-Term Memory

Authors: Yang Zhang, Jian He

Abstract:

Heart disease is one of the leading causes of death in the world, and coronary heart disease (CHD) is one of the major heart diseases. Electrocardiogram (ECG) is widely used in the detection of heart diseases, but the traditional manual method for CHD prediction by analyzing ECG requires lots of professional knowledge for doctors. This paper introduces sliding window and continuous wavelet transform (CWT) to transform ECG signals into images, and then ResNet and Bi-LSTM are introduced to build the ECG feature extraction network (namely ECGNet). At last, an auxiliary system for coronary heart disease prediction was developed based on modified ResNet18 and Bi-LSTM, and the public ECG dataset of CHD from MIMIC-3 was used to train and test the system. The experimental results show that the accuracy of the method is 83%, and the F1-score is 83%. Compared with the available methods for CHD prediction based on ECG, such as kNN, decision tree, VGGNet, etc., this method not only improves the prediction accuracy but also could avoid the degradation phenomenon of the deep learning network.

Keywords: Bi-LSTM, CHD, ECG, ResNet, sliding window

Procedia PDF Downloads 60
2788 Comparison of the Anthropometric Obesity Indices in Prediction of Cardiovascular Disease Risk: Systematic Review and Meta-analysis

Authors: Saeed Pourhassan, Nastaran Maghbouli

Abstract:

Statement of the problem: The relationship between obesity and cardiovascular diseases has been studied widely(1). The distribution of fat tissue gained attention in relation to cardiovascular risk factors during lang-time research (2). American College of Cardiology/American Heart Association (ACC/AHA) is widely and the most reliable tool to be used as a cardiovascular risk (CVR) assessment tool(3). This study aimed to determine which anthropometric index is better in discrimination of high CVR patients from low risks using ACC/AHA score in addition to finding the best index as a CVR predictor among both genders in different races and countries. Methodology & theoretical orientation: The literature in PubMed, Scopus, Embase, Web of Science, and Google Scholar were searched by two independent investigators using the keywords "anthropometric indices," "cardiovascular risk," and "obesity." The search strategy was limited to studies published prior to Jan 2022 as full-texts in the English language. Studies using ACC/AHA risk assessment tool as CVR and those consisted at least 2 anthropometric indices (ancient ones and novel ones) are included. Study characteristics and data were extracted. The relative risks were pooled with the use of the random-effect model. Analysis was repeated in subgroups. Findings: Pooled relative risk for 7 studies with 16,348 participants were 1.56 (1.35-1.72) for BMI, 1.67(1.36-1.83) for WC [waist circumference], 1.72 (1.54-1.89) for WHR [waist-to-hip ratio], 1.60 (1.44-1.78) for WHtR [waist-to-height ratio], 1.61 (1.37-1.82) for ABSI [A body shape index] and 1.63 (1.32-1.89) for CI [Conicity index]. Considering gender, WC among females and WHR among men gained the highest RR. The heterogeneity of studies was moderate (α²: 56%), which was not decreased by subgroup analysis. Some indices such as VAI and LAP were evaluated just in one study. Conclusion & significance: This meta-analysis showed WHR could predict CVR better in comparison to BMI or WHtR. Some new indices like CI and ABSI are less accurate than WHR and WC. Among women, WC seems to be a better choice to predict cardiovascular disease risk.

Keywords: obesity, cardiovascular disease, risk assessment, anthropometric indices

Procedia PDF Downloads 82
2787 A Nutrient Formulation Affects Brain Myelination in Infants: An Investigative Randomized Controlled Trial

Authors: N. Schneider, M. Bruchhage, M. Hartweg, G. Mutungi, J. O Regan, S. Deoni

Abstract:

Observational neuroimaging studies suggest differences between breast-fed and formula-fed infants in developmental myelination, a key brain process for learning and cognitive development. However, the possible effects of a nutrient formulation on myelin development in healthy term infants in an intervention study have not been investigated. Objective was, therefore, to investigate the efficacy of a nutrient formulation with higher levels of myelin-relevant nutrients as compared to a control formulation with lower levels of the same nutrients on brain myelination and cognitive development in the first 6 months of life. The study is an ongoing randomized, controlled, double-blind, two-center, parallel-group clinical trial with a nonrandomized, non-blinded arm of exclusively breastfed infants. The current findings result from a staged statistical analysis at 6 months; the recruitment and intervention period has been completed for all participants. Follow-up visits at 12, 18 and 24 months are still ongoing. N= 81 enrolled full term, neurotypical infants of both sexes were randomized into either the investigational (N= 42) or the control group (N= 39), and N= 108 children in the breast-fed arm served as a natural reference group. The effect of a blend of docosahexaenoic acid, arachidonic acid, iron, vitamin B12, folic acid as well as sphingomyelin from a uniquely proceed whey protein concentrate enriched in alpha-lactalbumin and phospholipids in an infant nutrition product matrix was investigated. The main outcomes for the staged statistical analyses at 6 months included brain myelination measures derived from MRI. Additional outcomes were brain volume, cognitive development and safety. The full analyses set at 6 months comprised N= 66 infants. Higher levels of myelin-relevant nutrients compared to lower levels resulted in significant differences in myelin structure, volume, and rate of myelination as early as 3 and 6 months of life. The cross-sectional change of means between groups for whole-brain myelin volume was 8.4% for investigational versus control formulation (3.5% versus the breastfeeding reference) group at 3 months and increased to 36.4% for investigational versus control formulation (14.1% versus breastfeeding reference) at 6 months. No statistically significant differences were detected for early cognition scores. Safety findings were largely similar across groups. This is the first pediatric nutritional neuroimaging study demonstrating the efficacy of a myelin nutrient blend on developmental myelination in well-nourished term infants. Myelination is a critical process in learning and development. The effects were demonstrated across the brain, particularly in temporal and parietal regions, known to be functionally involved in sensory, motor and language skills. These first results add to the field of nutritional neuroscience by demonstrating early life nutrition benefits for brain architecture which may be foundational for later cognitive and behavioral outcomes. ClinicalTrials.gov Identifier: NCT03111927 (Infant Nutrition and Brain Development - Full-Text View - ClinicalTrials.gov).

Keywords: brain development, infant nutrition, MRI, myelination

Procedia PDF Downloads 164
2786 A NoSQL Based Approach for Real-Time Managing of Robotics's Data

Authors: Gueidi Afef, Gharsellaoui Hamza, Ben Ahmed Samir

Abstract:

This paper deals with the secret of the continual progression data that new data management solutions have been emerged: The NoSQL databases. They crossed several areas like personalization, profile management, big data in real-time, content management, catalog, view of customers, mobile applications, internet of things, digital communication and fraud detection. Nowadays, these database management systems are increasing. These systems store data very well and with the trend of big data, a new challenge’s store demands new structures and methods for managing enterprise data. The new intelligent machine in the e-learning sector, thrives on more data, so smart machines can learn more and faster. The robotics are our use case to focus on our test. The implementation of NoSQL for Robotics wrestle all the data they acquire into usable form because with the ordinary type of robotics; we are facing very big limits to manage and find the exact information in real-time. Our original proposed approach was demonstrated by experimental studies and running example used as a use case.

Keywords: NoSQL databases, database management systems, robotics, big data

Procedia PDF Downloads 325
2785 X-Ray Diffraction and Crosslink Density Analysis of Starch/Natural Rubber Polymer Composites Prepared by Latex Compounding Method

Authors: Raymond Dominic Uzoh

Abstract:

Starch fillers were extracted from three plant sources namely amora tuber (a wild variety of Irish potato), sweet potato and yam starch and their particle size, pH, amylose, and amylopectin percentage decomposition determined accordingly by high performance liquid chromatography (HPLC). The starch was introduced into natural rubber in liquid phase (through gelatinization) by the latex compounding method and compounded according to standard method. The prepared starch/natural rubber composites was characterized by Instron Universal testing machine (UTM) for tensile mechanical properties. The composites was further characterized by x-ray diffraction and crosslink density analysis. The particle size determination showed that amora starch granules have the highest particle size (156 × 47 μm) followed by yam starch (155× 40 μm) and then the sweet potato starch (153 × 46 μm). The pH test also revealed that amora starch has a near neutral pH of 6.9, yam 6.8, and sweet potato 5.2 respectively. Amylose and amylopectin determination showed that yam starch has a higher percentage of amylose (29.68), followed by potato (22.34) and then amora starch with the lowest value (14.86) respectively. The tensile mechanical properties testing revealed that yam starch produced the best tensile mechanical properties followed by amora starch and then sweet potato starch. The structure, crystallinity/amorphous nature of the product composite was confirmed by x-ray diffraction, while the nature of crosslinking was confirmed by swelling test in toluene solvent using the Flory-Rehner approach. This research study has rendered a workable strategy for enhancing interfacial interaction between a hydrophilic filler (starch) and hydrophobic polymeric matrix (natural rubber) yielding moderately good tensile mechanical properties for further exploitation development and application in the rubber processing industry.

Keywords: natural rubber, fillers, starch, amylose, amylopectin, crosslink density

Procedia PDF Downloads 145
2784 Influence of Hydrophobic Surface on Flow Past Square Cylinder

Authors: S. Ajith Kumar, Vaisakh S. Rajan

Abstract:

In external flows, vortex shedding behind the bluff bodies causes to experience unsteady loads on a large number of engineering structures, resulting in structural failure. Vortex shedding can even turn out to be disastrous like the Tacoma Bridge failure incident. We need to have control over vortex shedding to get rid of this untoward condition by reducing the unsteady forces acting on the bluff body. In circular cylinders, hydrophobic surface in an otherwise no-slip surface is found to be delaying separation and minimizes the effects of vortex shedding drastically. Flow over square cylinder stands different from this behavior as separation can takes place from either of the two corner separation points (front or rear). An attempt is made in this study to numerically elucidate the effect of hydrophobic surface in flow over a square cylinder. A 2D numerical simulation has been done to understand the effects of the slip surface on the flow past square cylinder. The details of the numerical algorithm will be presented at the time of the conference. A non-dimensional parameter, Knudsen number is defined to quantify the slip on the cylinder surface based on Maxwell’s equation. The slip surface condition of the wall affects the vorticity distribution around the cylinder and the flow separation. In the numerical analysis, we observed that the hydrophobic surface enhances the shedding frequency and damps down the amplitude of oscillations of the square cylinder. We also found that the slip has a negative effect on aerodynamic force coefficients such as the coefficient of lift (CL), coefficient of drag (CD) etc. and hence replacing the no slip surface by a hydrophobic surface can be treated as an effective drag reduction strategy and the introduction of hydrophobic surface could be utilized for reducing the vortex induced vibrations (VIV) and is found as an effective method in controlling VIV thereby controlling the structural failures.

Keywords: drag reduction, flow past square cylinder, flow control, hydrophobic surfaces, vortex shedding

Procedia PDF Downloads 358
2783 Instant Fire Risk Assessment Using Artifical Neural Networks

Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

Abstract:

Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

Procedia PDF Downloads 109
2782 Territorial Brand as a Means of Structuring the French Wood Industry

Authors: Laetitia Dari

Abstract:

The brand constitutes a source of differentiation between competitors. It highlights specific characteristics that create value for the enterprise. Today the concept of a brand is not just about the product but can concern territories. The competition between territories, due to tourism, research, jobs, etc., leads territories to develop territorial brands to bring out their identity and specificity. Some territorial brands are based on natural resources or products characteristic of a territory. In the French wood sector, we can observe the emergence of many territorial brands. Supported by the inter-professional organization, these brands have the main objective of showcasing wood as a source of solutions at the local level in terms of construction and energy. The implementation of these collective projects raises the question of the way in which relations between companies are structured and animated. The central question of our work is to understand how the territorial brand promotes the structuring of a sector and the construction of collective relations between actors. In other words, we are interested in the conditions for the emergence of the territorial brand and the way in which it will be a means of mobilizing the actors around a common project. The objectives of the research are (1) to understand in which context a territorial brand emerges, (2) to analyze the way in which the territorial brand structures the collective relations between actors, (3) to give entry keys to the actors to successfully develop this type of project. Thus, our research is based on a qualitative methodology with semi-structured interviews conducted with the main territorial brands in France. The research will answer various academic and empirical questions. From an academic point of view, it brings elements of understanding to the construction of a collective project and to the way in which governance operates. From an empirical point of view, the interest of our work is to bring out the key success factors in the development of a territorial brand and how the brand can become an element of valuation for a territory.

Keywords: brand, marketing, strategy, territory, third party stakeholder, wood

Procedia PDF Downloads 45
2781 Development of Composite Materials for CO2 Reduction and Organic Compound Decomposition

Authors: H. F. Shi, C. L. Zhang

Abstract:

Visible-light-responsive g-C3N4/NaNbO3 nanowires photocatalysts were fabricated by introducing polymeric g-C3N4 on NaNbO3 nanowires. The microscopic mechanisms of interface interaction, charge transfer and separation, as well as the influence on the photocatalytic activity of g-C3N4/NaNbO3 composite were systematic investigated. The HR-TEM revealed that an intimate interface between C3N4 and NaNbO3 nanowires formed in the g-C3N4/NaNbO3 heterojunctions. The photocatalytic performance of photocatalysts was evaluated for CO2 reduction under visible-light illumination. Significantly, the activity of g-C3N4/NaNbO3 composite photocatalyst for photoreduction of CO2 was higher than that of either single-phase g-C3N4 or NaNbO3. Such a remarkable enhancement of photocatalytic activity was mainly ascribed to the improved separation and transfer of photogenerated electron-hole pairs at the intimate interface of g-C3N4/NaNbO3 heterojunctions, which originated from the well-aligned overlapping band structures of C3N4 and NaNbO3. Pt loaded NaNbO3-xNx (Pt-NNON), a visible-light-sensitive photocatalyst, was synthesized by an in situ photodeposition method from H2PtCl6•6H2O onto NaNbO3-xNx (NNON) sample. Pt-NNON exhibited a much higher photocatalytic activity for gaseous 2-propanol (IPA) degradation under visible-light irradiation in contrast to NNON. The apparent quantum efficiency (AQE) of Pt-NNON sample for IPA photodegradation achieved up to 8.6% at the wavelength of 419 nm. The notably enhanced photocatalytic performance was attributed to the promoted charge separation and transfer capability in the Pt-NNON system. This work suggests that surface nanosteps possibly play an important role as an electron transfer at high way, which facilitates to the charge carrier collection onto Pt rich zones and thus suppresses recombination between photogenerated electrons and holes. This method can thus be considered as an excellent strategy to enhance photocatalytic activity of organic decomposition in addition to the commonly applied noble metal doping method.

Keywords: CO2 reduction, NaNbO3, nanowires, g-C3N4

Procedia PDF Downloads 179
2780 Youths Economic Empowerment through Vocational Agricultural Enterprises (Entrepreneurship) for Sustainable Agriculture in Nigeria: Constraints and Initiatives for Improvement

Authors: Thomas Ogilegwu Orohu

Abstract:

This paper presents agricultural education as a vocational study, an impetus for youths, economic empowerment. The survival of Nigeria’s agriculture rests squarely on the youth who are the farmers and leaders of tomorrow. Hitherto, the teaching and learning of agriculture has proceeded in such a manner that graduates of such programs have failed to make the successful launch into the world of agricultural enterprises (entrepreneurship). Major constraints that predisposed this anomalous situation were identified to include poor policy framework, socio-economic pressures, undue parental and peer influences, improper value orientation and of course, the nature of curricula. In response to the situation, some programs and/or initiatives aimed at inculcating entrepreneurial skills were proposed by this paper with identified target beneficiaries. The initiatives bordered on curricular reorientation that integrate entrepreneurship/enterprise education, retraining of graduates, financial support system among others.

Keywords: Program initiatives. vocational agriculture, youths’ empowerment, introduction

Procedia PDF Downloads 285
2779 Exploring Acceptance of Artificial Intelligence Software Solution Amongst Healthcare Personnel: A Case in a Private Medical Centre

Authors: Sandra So, Mohd Roslan Ismail, Safurah Jaafar

Abstract:

With the rapid proliferation of data in healthcare has provided an opportune platform creation of Artificial Intelligence (AI). AI has brought a paradigm shift for healthcare professionals, promising improvement in delivery and quality. This study aims to determine the perception of healthcare personnel on perceived ease of use, perceived usefulness, and subjective norm toward attitude for artificial intelligence acceptance. A cross-sectional single institutional study of employees’ perception of adopting AI in the hospital was conducted. The survey was conducted using a questionnaire adapted from Technology Acceptance Model and a four-point Likert scale was used. There were 96 or 75.5% of the total population responded. This study has shown the significant relationship and the importance of ease of use, perceived usefulness, and subjective norm to the acceptance of AI. In the study results, it concluded that the determining factor to the strong acceptance of AI in their practices is mostly those respondents with the most interaction with the patients and clinical management.

Keywords: artificial intelligence, machine learning, perceived ease of use, perceived usefulness, subjective norm

Procedia PDF Downloads 198
2778 The Facilitators and Barriers to the Implementation of Educational Neuroscience: Teachers’ Perspectives

Authors: S. Kawther, C. Marshall

Abstract:

Educational neuroscience has the intention of transforming research findings of the underpinning neural processes of learning to educational practices. A main criticism of the field, hitherto, is that less focus has been put on studying the in-progress practical application of these findings. Therefore, this study aims to gain a better understanding of teachers’ perceptions of the practical application and utilization of brain knowledge. This was approached by investigating the answer to 'What are the facilitators and barriers for bringing research from neuroscience to bear on education?'. Following a qualitative design, semi-structured interviews were conducted with 12 teachers who had a proficient course in educational neuroscience. Thematic analysis was performed on the transcribed data applying Braun & Clark’s steps. Findings emerged with four main themes: time, knowledge, teacher’s involvement, and system. These themes revealed that some effective brain-based practices are being engaged in by the teachers. However, the lack of guidance and challenges regarding this implementation were also found. This study discusses findings in light of the development of educational neuroscience implementation.

Keywords: brain-based, educational neuroscience, neuroeducation, neuroscience-informed

Procedia PDF Downloads 136
2777 Low-Impact Development Strategies Assessment for Urban Design

Authors: Y. S. Lin, H. L. Lin

Abstract:

Climate change and land-use change caused by urban expansion increase the frequency of urban flooding. To mitigate the increase in runoff volume, low-impact development (LID) is a green approach for reducing the area of impervious surface and managing stormwater at the source with decentralized micro-scale control measures. However, the current benefit assessment and practical application of LID in Taiwan is still tending to be development plan in the community and building site scales. As for urban design, site-based moisture-holding capacity has been common index for evaluating LID’s effectiveness of urban design, which ignore the diversity, and complexity of the urban built environments, such as different densities, positive and negative spaces, volumes of building and so on. Such inflexible regulations not only probably make difficulty for most of the developed areas to implement, but also not suitable for every different types of built environments, make little benefits to some types of built environments. Looking toward to enable LID to strength the link with urban design to reduce the runoff in coping urban flooding, the research consider different characteristics of different types of built environments in developing LID strategy. Classify the built environments by doing the cluster analysis based on density measures, such as Ground Space Index (GSI), Floor Space Index (FSI), Floors (L), and Open Space Ratio (OSR), and analyze their impervious surface rates and runoff volumes. Simulate flood situations by using quasi-two-dimensional flood plain flow model, and evaluate the flood mitigation effectiveness of different types of built environments in different low-impact development strategies. The information from the results of the assessment can be more precisely implement in urban design. In addition, it helps to enact regulations of low-Impact development strategies in urban design more suitable for every different type of built environments.

Keywords: low-impact development, urban design, flooding, density measures

Procedia PDF Downloads 310
2776 Theoretical Comparisons and Empirical Illustration of Malmquist, Hicks–Moorsteen, and Luenberger Productivity Indices

Authors: Fatemeh Abbasi, Sahand Daneshvar

Abstract:

Productivity is one of the essential goals of companies to improve performance, which as a strategy-oriented method, determines the basis of the company's economic growth. The history of productivity goes back centuries, but most researchers defined productivity as the relationship between a product and the factors used in production in the early twentieth century. Productivity as the optimal use of available resources means that "more output using less input" can increase companies' economic growth and prosperity capacity. Also, having a quality life based on economic progress depends on productivity growth in that society. Therefore, productivity is a national priority for any developed country. There are several methods for calculating productivity growth measurements that can be divided into parametric and non-parametric methods. Parametric methods rely on the existence of a function in their hypotheses, while non-parametric methods do not require a function based on empirical evidence. One of the most popular non-parametric methods is Data Envelopment Analysis (DEA), which measures changes in productivity over time. The DEA evaluates the productivity of decision-making units (DMUs) based on mathematical models. This method uses multiple inputs and outputs to compare the productivity of similar DMUs such as banks, government agencies, companies, airports, Etc. Non-parametric methods are themselves divided into the frontier and non frontier approaches. The Malmquist productivity index (MPI) proposed by Caves, Christensen, and Diewert (1982), the Hicks–Moorsteen productivity index (HMPI) proposed by Bjurek (1996), or the Luenberger productivity indicator (LPI) proposed by Chambers (2002) are powerful tools for measuring productivity changes over time. This study will compare the Malmquist, Hicks–Moorsteen, and Luenberger indices theoretically and empirically based on DEA models and review their strengths and weaknesses.

Keywords: data envelopment analysis, Hicks–Moorsteen productivity index, Leuenberger productivity indicator, malmquist productivity index

Procedia PDF Downloads 162
2775 Microbial and Oocyst Count in Feacal Material of Broilers Birds Administered Phytochemicals (Naringin and Hesperidin)

Authors: Adeleye Oluwagbemmiga, Obuotor Tolulope, Dosumu Adebisi, Opowoye I., Olasoju M., Kolawole Amos, Egbeyale Lawrence

Abstract:

Gut Microbiota plays a vital role in animal health and welfare. This study investigated the effect of naringin and hesperidin administration on broiler birds. A total of 80 day – old broiler chicks were randomly divided into eight groups, with ten birds per group. Four groups were not inoculated but administered coccidiostat (1A), hesperidin alone (2A), naringin alone (3A) and a combination of naringin and hesperidin (4A) from day eight (8) to day fourteen (14) while four other groups (5A – 8A) were inoculated with 2 x 10⁴ oocysts per 0.5ml of Eimeria tenella on the 16th and 19th day of age after they were administered conventional antibiotics and coccidiostat, naringin (50mg/body weight), hesperidin (50mg/body weight) and a combination from day 8 - 14. McMaster counting technique was used to count the oocysts, while pour plate technique was used to determine the bacterial load. The results showed a significant increase in their performance with an average weight ranging from 1.55kg – 2.00kg, microbial load also improved with colony count values from 3.5 x 104 - 4.5 x 10⁴ CFU/ml. The study also found that the inclusion of naringin and hesperidin in the diets of broiler birds inoculated with coccidia oocysts significantly reduced the fecal oocyst counts, with the lowest count in combined treatment (8A) (10%) and indicating a lower degree of coccidiosis infection in the treated groups whereas control group (5A) had the highest oocyst count (35%). Mortality and Morbidity rate was 0% as none of the bird showed signs and symptoms. The reduction in oocyst counts could help to strengthen the immune system of broiler birds and limit the severity of coccidiosis infection, which could be an effective strategy for improving performance, immune function and mitigating the impact of coccidiosis infection in broiler birds.

Keywords: gut colonization, naringin, hesperidin, eimeria tenella, broilers

Procedia PDF Downloads 47
2774 How Autonomous Vehicles Transform Urban Policies and Cities

Authors: Adrián P. Gómez Mañas

Abstract:

Autonomous vehicles have already transformed urban policies and cities. This is the main assumption of our research, which aims to understand how the representations of the possible arrival of autonomous vehicles already transform priorities or actions in transport and more largely, urban policies. This research is done within the framework of a Ph.D. doctorate directed by Professor Xavier Desjardins at the Sorbonne University of Paris. Our hypotheses are: (i) the perspectives, representations, and imaginaries on autonomous vehicles already affect the stakeholders of urban policies; (ii) the discourses on the opportunities or threats of autonomous vehicles reflect the current strategies of the stakeholders. Each stakeholder tries to integrate a discourse on autonomous vehicles that allows them to change as little as possible their current tactics and strategies. The objective is to eventually make a comparison between three different cases: Paris, United Arab Emirates, and Bogota. We chose those territories because their contexts are very different, but they all have important interests in mobility and innovation, and they all have started to reflect on the subject of self-driving mobility. The main methodology used is to interview actors of the metropolitan area (local officials, leading urban and transport planners, influent experts, and private companies). This work is supplemented with conferences, official documents, press articles, and websites. The objective is to understand: 1) What they know about autonomous vehicles and where does their knowledge come from; 2) What they expect from autonomous vehicles; 3) How their ideas about autonomous vehicles are transforming their action and strategy in managing daily mobility, investing in transport, designing public spaces and urban planning. We are going to present the research and some preliminary results; we will show that autonomous vehicles are often viewed by public authorities as a lever to reach something else. We will also present that speeches are very influenced by local context (political, geographical, economic, etc.), creating an interesting balance between global and local influences. We will analyze the differences and similarities between the three cases and will try to understand which are the causes.

Keywords: autonomous vehicles, self-driving mobility, urban planning, urban mobility, transport, public policies

Procedia PDF Downloads 163
2773 Health Literacy and Knowledge Related to Tuberculosis among Outpatients at a Referral Hospital in Lima, Peru

Authors: Rosalina Penaloza, Joanna Navarro, Pauline Jolly, Anna Junkins, Carlos Seas, Larissa Otero

Abstract:

Background: Tuberculosis (TB) case detection in Peru relies on passive case finding. This strategy relies on the assumption that the community is aware that a persistent cough is a possible symptom of TB and that formal health care needs to be sought. Despite its importance, health knowledge specific to TB is underexplored in Peru. This study aimed to assess health literacy and level of TB knowledge among outpatients attending a referral hospital in Lima, Peru. The goal was to ascertain knowledge gaps in key areas relating to TB, to identify and prioritize subgroups for intervention, and to provide insight for policy and community interventions considering health literacy. Methods: An observational cross-sectional study was conducted using a survey to measure sociodemographic factors, tuberculosis knowledge, and health literacy. Bivariate and Multivariate logistic regression was performed to study the associations between variables and to account for potential confounders. The study was conducted at Hospital Cayetano Heredia in Lima, Peru from June – August 2017. Results: 272 participants were included in the analysis. 57.7% knew someone who had had TB before, 9% had had TB in the past. Two weeks a cough was correctly identified as a symptom that could be TB by 69.1%. High TB knowledge was found among 149 (54.8%) participants. High health literacy was found among 193 (71.0%) participants. Health literacy and TB knowledge were not significantly associated (OR 0.9 (95%CI 0.5-1.5)). After controlling for sex, age, district, education, health insurance, frequency of hospital visits and previous TB diagnosis: High TB knowledge was associated with knowing someone with TB (aOR 2.7 (95%CI 1.6-4.7)) and being a public transport driver, (aOR 0.2 (95%CI 0.05-0.9)). Not being poor was the single factor associated with high health literacy (aOR 3.8 (95%CI 1.6-8.9)). Conclusions: TB knowledge was fair, though 30% did not know the most important symptom of TB. Tailoring educational strategies to risk groups may enhance passive case detection especially amongst transport workers in Lima, Peru.

Keywords: health literacy, Peru, tuberculosis, tuberculosis knowledge

Procedia PDF Downloads 471
2772 Application of Harris Hawks Optimization Metaheuristic Algorithm and Random Forest Machine Learning Method for Long-Term Production Scheduling Problem under Uncertainty in Open-Pit Mines

Authors: Kamyar Tolouei, Ehsan Moosavi

Abstract:

In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

Procedia PDF Downloads 75
2771 An Interpretable Data-Driven Approach for the Stratification of the Cardiorespiratory Fitness

Authors: D.Mendes, J. Henriques, P. Carvalho, T. Rocha, S. Paredes, R. Cabiddu, R. Trimer, R. Mendes, A. Borghi-Silva, L. Kaminsky, E. Ashley, R. Arena, J. Myers

Abstract:

The continued exploration of clinically relevant predictive models continues to be an important pursuit. Cardiorespiratory fitness (CRF) portends clinical vital information and as such its accurate prediction is of high importance. Therefore, the aim of the current study was to develop a data-driven model, based on computational intelligence techniques and, in particular, clustering approaches, to predict CRF. Two prediction models were implemented and compared: 1) the traditional Wasserman/Hansen Equations; and 2) an interpretable clustering approach. Data used for this analysis were from the 'FRIEND - Fitness Registry and the Importance of Exercise: The National Data Base'; in the present study a subset of 10690 apparently healthy individuals were utilized. The accuracy of the models was performed through the computation of sensitivity, specificity, and geometric mean values. The results show the superiority of the clustering approach in the accurate estimation of CRF (i.e., maximal oxygen consumption).

Keywords: cardiorespiratory fitness, data-driven models, knowledge extraction, machine learning

Procedia PDF Downloads 263
2770 Fecal Prevalence, Serotype Distribution and Antimicrobial Resistance of Salmonella in Dairy Cattle in Central Ethiopia

Authors: Tadesse Eguale, Ephrem Engdawork, Wondwossen Gebreyes, Dainel Asrat, Hile Alemayehu, John Gunn

Abstract:

Salmonella is one of the major zoonotic pathogens affecting wide range of vertebrates and humans worldwide. Consumption of contaminated dairy products and contact with dairy cattle represent the common sources of non-typhoidal Salmonella infection in humans. Fecal samples were collected from 132 dairy herds in central Ethiopia and cultured for Salmonella to determine the prevalence, serotype distribution and antimicrobial susceptibility. Salmonella was recovered from the feces of at least one cattle in 10(7.6%) of the dairy farms. Out of 1193 fecal samples 30(2.5%) were positive for Salmonella. Large farm size, detection of diarrhea in one or more animals during sampling and keeping animals completely indoor compared to occasional grazing outside were associated with Salmonella positivity of the farms. Farm level prevalence of Salmonella was significantly higher in young animals below 6 months of age compared to other age groups(X2=10.24; p=0.04). Nine different serotypes were isolated. The four most frequently recovered serotypes were S. Typhimurium (23.3%),S. Saintpaul (20%) and S. Kentucky and S. Virchow (16.7%) each. All isolates were resistant or intermediately resistant to at least one of the 18 drugs tested. Twenty-six (86.7%), 20(66.7%), 18(60%), 16(53.3%) of the isolates were resistant to streptomycin, nitrofurantoin, sulfisoxazole and tetracycline respectively. Resistance to 2 drugs was detected in 93.3% of the isolates. Resistance to 3 or more drugs were detected in 21(70%) of the total isolates while multi-drug resistance (MDR) to 7 or more drugs were detected in 12 (40%) of the isolates. The rate of occurrence of MDR in Salmonella strains isolated from dairy farms in Addis Ababa was significantly higher than those isolated from farms outside of Addis Ababa((p= 0.009). The detection of high MDR in Salmonella isolates originating from dairy farms warrants the need for strict pathogen reduction strategy in dairy cattle and spread of these MDR strains to human population.

Keywords: salmonella, antimicrobial resistance, fecal prevalence

Procedia PDF Downloads 456
2769 Practical Experiences in the Development of a Lab-Scale Process for the Production and Recovery of Fucoxanthin

Authors: Alma Gómez-Loredo, José González-Valdez, Jorge Benavides, Marco Rito-Palomares

Abstract:

Fucoxanthin is a carotenoid that exerts multiple beneficial effects on human health, including antioxidant, anti-cancer, antidiabetic and anti-obesity activity; making the development of a whole process for its production and recovery an important contribution. In this work, the lab-scale production and purification of fucoxanthin in Isocrhysis galbana have been studied. In batch cultures, low light intensities (13.5 μmol/m2s) and bubble agitation were the best conditions for production of the carotenoid with product yields of up to 0.143 mg/g. After fucoxanthin ethanolic extraction from biomass and hexane partition, further recovery and purification of the carotenoid has been accomplished by means of alcohol – salt Aqueous Two-Phase System (ATPS) extraction followed by an ultrafiltration (UF) step. An ATPS comprised of ethanol and potassium phosphate (Volume Ratio (VR) =3; Tie-line Length (TLL) 60% w/w) presented a fucoxanthin recovery yield of 76.24 ± 1.60% among the studied systems and was able to remove 64.89 ± 2.64% of the carotenoid and chlorophyll pollutants. For UF, the addition of ethanol to the original recovered ethanolic ATPS stream to a final relation of 74.15% (w/w) resulted in a reduction of approximately 16% of the protein contents, increasing product purity with a recovery yield of about 63% of the compound in the permeate stream. Considering the production, extraction and primary recovery (ATPS and UF) steps, around a 45% global fucoxanthin recovery should be expected. Although other purification technologies, such as Centrifugal Partition Chromatography are able to obtain fucoxanthin recoveries of up to 83%, the process developed in the present work does not require large volumes of solvents or expensive equipment. Moreover, it has a potential for scale up to commercial scale and represents a cost-effective strategy when compared to traditional separation techniques like chromatography.

Keywords: aqueous two-phase systems, fucoxanthin, Isochrysis galbana, microalgae, ultrafiltration

Procedia PDF Downloads 396
2768 Assessment of Multi-Domain Energy Systems Modelling Methods

Authors: M. Stewart, Ameer Al-Khaykan, J. M. Counsell

Abstract:

Emissions are a consequence of electricity generation. A major option for low carbon generation, local energy systems featuring Combined Heat and Power with solar PV (CHPV) has significant potential to increase energy performance, increase resilience, and offer greater control of local energy prices while complementing the UK’s emissions standards and targets. Recent advances in dynamic modelling and simulation of buildings and clusters of buildings using the IDEAS framework have successfully validated a novel multi-vector (simultaneous control of both heat and electricity) approach to integrating the wide range of primary and secondary plant typical of local energy systems designs including CHP, solar PV, gas boilers, absorption chillers and thermal energy storage, and associated electrical and hot water networks, all operating under a single unified control strategy. Results from this work indicate through simulation that integrated control of thermal storage can have a pivotal role in optimizing system performance well beyond the present expectations. Environmental impact analysis and reporting of all energy systems including CHPV LES presently employ a static annual average carbon emissions intensity for grid supplied electricity. This paper focuses on establishing and validating CHPV environmental performance against conventional emissions values and assessment benchmarks to analyze emissions performance without and with an active thermal store in a notional group of non-domestic buildings. Results of this analysis are presented and discussed in context of performance validation and quantifying the reduced environmental impact of CHPV systems with active energy storage in comparison with conventional LES designs.

Keywords: CHPV, thermal storage, control, dynamic simulation

Procedia PDF Downloads 212
2767 Small Text Extraction from Documents and Chart Images

Authors: Rominkumar Busa, Shahira K. C., Lijiya A.

Abstract:

Text recognition is an important area in computer vision which deals with detecting and recognising text from an image. The Optical Character Recognition (OCR) is a saturated area these days and with very good text recognition accuracy. However the same OCR methods when applied on text with small font sizes like the text data of chart images, the recognition rate is less than 30%. In this work, aims to extract small text in images using the deep learning model, CRNN with CTC loss. The text recognition accuracy is found to improve by applying image enhancement by super resolution prior to CRNN model. We also observe the text recognition rate further increases by 18% by applying the proposed method, which involves super resolution and character segmentation followed by CRNN with CTC loss. The efficiency of the proposed method shows that further pre-processing on chart image text and other small text images will improve the accuracy further, thereby helping text extraction from chart images.

Keywords: small text extraction, OCR, scene text recognition, CRNN

Procedia PDF Downloads 99
2766 Efficacy of Light-Emitting Diode-Mediated Photobiomodulation in Tendon Healing in a Murine Model

Authors: Sukwoong Kang

Abstract:

Background: The application of light-emitting diode (LED)-dependent photobiomodulation (PBM) in promoting post-tendon injury healing has been recently reported. Despite the establishment of a theoretical basis for ligament restoration through PBM, the lack of any empirical evidence deems this therapeutic strategy contentious. Therefore, the aim of this study was to investigate the potency of LED-based PBM in facilitating tendon healing in a murine model. Methods: Migration kinetics were analyzed at two specific wavelengths: 630 and 880 nm. The Achilles tendon in the hind limbs of Balb/c mice was severed via Achilles tendon transection. Subsequently, the mice were randomized into LED non-irradiation and LED irradiation groups. Mice with intact tendons were employed as healthy controls. The wounds were LED-irradiated for 20 min daily for two days. Histological properties, tendon healing mediators, and inflammatory mediators were screened on day 14. Results: The roundness of the nuclei and fiber structure, indicating the degree of infiltrated inflammatory cells and severity of fiber fragmentation, respectively, were considerably lower in the LED irradiation group than in the LED non-irradiation group. Immunohistochemical analysis depicted an increase in tenocytes (SCX+ cells) and a recovery of wounds with reduced fibrosis (lower collagen 3 and TGF-β1) in the LED irradiation group during healing; conversely, the LED non-irradiation group exhibited tissue fibrosis. The ratio of M2 macrophages to total macrophages was higher in the LED irradiation group than in the injured group. Conclusion: LED-based PBM in the Achilles tendon rupture murine model effectuated a rapid restoration of histological and immunochemical outcomes. The aforementioned findings suggest that LED-based PBM presents remarkable potential as an adjunct therapeutic for tendon healing and warrants further research to standardize various parameters to advance and establish it as a reliable treatment regime.

Keywords: photobiomodulation, light-emitting diode, tendon, regeneration

Procedia PDF Downloads 19
2765 Fabrication Methodologies for Anti-Microbial Polypropylene Surfaces with Leachable and Non-leachable Anti-Microbial Agents

Authors: Saleh Alkarri, Dimple Sharma, Teresa M. Bergholz, Muhammad Rabnawaz

Abstract:

Aims: Develop a methodology for the fabrication of anti-microbial polypropylene (PP) surfaces with (i) leachable copper, (II) chloride dihydrate (CuCl₂·₂H₂O) and (ii) non-leachable magnesium hydroxide (Mg(OH)₂) biocides. Methods and Results: Two methodologies are used to develop anti-microbial PP surfaces. One method involves melt-blending and subsequent injection molding, where the biocide additives were compounded with PP and subsequently injection-molded. The other method involves the thermal embossing of anti-microbial agents on the surface of a PP substrate. The obtained biocide-bearing PP surfaces were evaluated against E. coli K-12 MG1655 for 0, 4, and 24 h to evaluate their anti-microbial properties. The injection-molded PP bearing 5% CuCl2·₂H₂O showed a 6-log reduction of E. coli K-12 MG1655 after 24 h, while only 1 log reduction was observed for PP bearing 5% Mg(OH)2. The thermally embossed PP surfaces bearing CuCl2·2H2O and Mg(OH)₂ particles (at a concentration of 10 mg/mL) showed 3 log and 4 log reduction, respectively, against E.coli K-12 MG1655 after 24 h. Conclusion: The results clearly demonstrate that CuCl₂·2H₂O conferred anti-microbial properties to PP surfaces that were prepared by both injection molding as well as thermal embossing approaches owing to the presence of leachable copper ions. In contrast, the non-leachable Mg(OH)₂ imparted anti-microbial properties only to the surface prepared via the thermal embossing technique. Significance and Impact of The Study: Plastics with leachable biocides are effective anti-microbial surfaces, but their toxicity is a major concern. This study provides a fabrication methodology for non-leachable PP-based anti-microbial surfaces that are potentially safer. In addition, this strategy can be extended to many other plastics substrates.

Keywords: anti-microbial activity, E. coli K-12 MG1655, copper (II) chloride dihydrate, magnesium hydroxide, leachable, non-leachable, compounding, thermal embossing

Procedia PDF Downloads 56
2764 Fabrication Methodologies for Anti-microbial Polypropylene Surfaces with Leachable and Non-leachable Anti-microbial Agents

Authors: Saleh Alkarri, Dimple Sharma, Teresa M. Bergholz, Muhammad Rabnawa

Abstract:

Aims: Develop a methodology for the fabrication of anti-microbial polypropylene (PP) surfaces with (i) leachable copper (II) chloride dihydrate (CuCl2·2H2O) and (ii) non-leachable magnesium hydroxide (Mg(OH)2) biocides. Methods and Results: Two methodologies are used to develop anti-microbial PP surfaces. One method involves melt-blending and subsequent injection molding, where the biocide additives were compounded with PP and subsequently injection-molded. The other method involves the thermal embossing of anti-microbial agents on the surface of a PP substrate. The obtained biocide-bearing PP surfaces were evaluated against E. coli K-12 MG1655 for 0, 4, and 24 h to evaluate their anti-microbial properties. The injection-molded PP bearing 5% CuCl2·2H2O showed a 6-log reduction of E. coli K-12 MG1655 after 24 h, while only 1 log reduction was observed for PP bearing 5% Mg(OH)2. The thermally embossed PP surfaces bearing CuCl2·2H2O and Mg(OH)2 particles (at a concentration of 10 mg/mL) showed 3 log and 4 log reduction, respectively, against E.coli K-12 MG1655 after 24 h. Conclusion: The results clearly demonstrate that CuCl2·2H2O conferred anti-microbial properties to PP surfaces that were prepared by both injection molding as well as thermal embossing approaches owing to the presence of leachable copper ions. In contrast, the non-leachable Mg(OH)2 imparted anti-microbial properties only to the surface prepared via the thermal embossing technique. Significance and Impact of The Study: Plastics with leachable biocides are effective anti-microbial surfaces, but their toxicity is a major concern. This study provides a fabrication methodology for non-leachable PP-based anti-microbial surfaces that are potentially safer. In addition, this strategy can be extended to many other plastics substrates.

Keywords: anti-microbial activity, E. coli K-12 MG1655, copper (II) chloride dihydrate, magnesium hydroxide, leachable, non-leachable, compounding, thermal embossing

Procedia PDF Downloads 57
2763 Plant Leaf Recognition Using Deep Learning

Authors: Aadhya Kaul, Gautam Manocha, Preeti Nagrath

Abstract:

Our environment comprises of a wide variety of plants that are similar to each other and sometimes the similarity between the plants makes the identification process tedious thus increasing the workload of the botanist all over the world. Now all the botanists cannot be accessible all the time for such laborious plant identification; therefore, there is an urge for a quick classification model. Also, along with the identification of the plants, it is also necessary to classify the plant as healthy or not as for a good lifestyle, humans require good food and this food comes from healthy plants. A large number of techniques have been applied to classify the plants as healthy or diseased in order to provide the solution. This paper proposes one such method known as anomaly detection using autoencoders using a set of collections of leaves. In this method, an autoencoder model is built using Keras and then the reconstruction of the original images of the leaves is done and the threshold loss is found in order to classify the plant leaves as healthy or diseased. A dataset of plant leaves is considered to judge the reconstructed performance by convolutional autoencoders and the average accuracy obtained is 71.55% for the purpose.

Keywords: convolutional autoencoder, anomaly detection, web application, FLASK

Procedia PDF Downloads 137
2762 Synthesis of a Hybrid of PEG-b-PCL and G1-PEA Dendrimer Based Six-Armed Star Polymer for Nano Delivery of Vancomycin

Authors: Calvin A. Omolo, Rahul S. Kalhapure, Mahantesh Jadhav, Sanjeev Rambharose, Chunderika Mocktar, Thirumala Govender

Abstract:

Treatment of infections is compromised by limitations of conventional dosage forms and drug resistance. Nanocarrier system is a strategy to overcome these challenges and improve therapy. Thus, the development of novel materials for drug delivery via nanocarriers is essential. The aim of the study was to synthesize a multi-arm polymer (6-mPEPEA) for enhanced activity of vancomycin (VM) against susceptible and resistant Staphylococcus aureus (MRSA). The synthesis steps of the star polymer followed reported procedures. The synthesized 6-mPEPEA was characterized by FTIR, ¹H and ¹³CNMR and MTT assays. VM loaded micelles were prepared from 6-mPEPEA and characterized for size, polydispersity index (PI) and surface charge (ZP) (Dynamic Light Scattering), morphology by TEM, drug loading (UV Spectrophotometry), drug release (dialysis bag), in vitro and in vivo efficacy against sensitive and resistant S. aureus. 6-mPEPEA was synthesized, and its structure was confirmed. MTT assays confirmed its nontoxic nature with a high cell viability (77%-85%). Unimolecular spherical micelles were prepared. Size, PI, and ZP was 52.48 ± 2.6 nm, 0.103 ± 0.047, -7.3 ± 1.3 mV, respectively and drug loading was 62.24 ± 3.8%. There was a 91% drug release from VCM-6-mPEPEA after 72 hours. In vitro antibacterial test revealed that VM-6-mPEPEA had 8 and 16-fold greater activity against S. aureus and MRSA when compared to bare VM. Further investigations using flow cytometry showed that VM-6-mPEPEA had 99.5% killing rate of MRSA at the MIC concentration. In vivo antibacterial activity revealed that treatment with VM-6-mPEPEA had a 190 and a 15-fold reduction in the MRSA load in untreated and VM treated respectively. These findings confirmed the potential of 6-mPEPEA as a promising bio-degradable nanocarrier for antibiotic delivery to improve treatment of bacterial infections.

Keywords: biosafe, MRSA, nanocarrier, resistance, unimolecular-micelles

Procedia PDF Downloads 157
2761 Tourism Development and Its Role in the Urban Expansion of Al-Khomse City, Libya

Authors: Khaled Klib, Yousri Azzam, Ibrahim Maarouf

Abstract:

Tourism is one of the most important and fastest growing economic activities in the world, which has a prominent role in the growth and development of countries and has become increasingly important as business and trade after the World War II. The tourism development is one of the most important aspects of urban development, which aims to plan and develop tourist attractions and improve the urban environment within cities. Tourism development has become a priority for the urban development policy of cities, particularly those which have many tourist potentials. Complementary services, such as infrastructure, roads’ networks, transportation, and communications are needed for these potentials to function properly. In order to achieve these functionalities, also a new planning for the new areas as an expansion is required, or developing and renovating the existing urban areas according to pre-prepared plans to avoid random expansion of the urban structure of the city. This paper aims to determine the tourist attractions of Al-Khomse city, by reviewing the most important tourist attractions such as the Roman city (Leptis Magna), the geographical location on the Mediterranean coast, the temperate climate and diversity of the natural environment. The paper also examines the reality of the infrastructure and tourist services in the city and its suitability to serve the tourism sector. The paper also includes a proposed for tourism development in the city as one of the city's urban expansion trends, which can guide the development strategy in the future. The paper concludes with a vision for the tourism development areas as one of the trends for urban expansion in the future. The paper also concludes tourism development will have an effective role in the growth and development of urban, economic and social, in addition to preserving the natural environment. The paper recommended the need to emphasize the role of tourism development as one of the pillars and trends for the development policy and expansion of Al-Khomse city, preservation of tourist attractions and natural resources and developing infrastructure and tourist services such as accommodation, entertainment, mobility, and accessibility.

Keywords: tourism, tourist attractions, tourism development, urban expansion

Procedia PDF Downloads 217
2760 Factors Associated with Uptake of Influenza and Pertussis Vaccination in Pregnant Women

Authors: Hassen Mohammed, Michelle Clarke, Helen Marshall

Abstract:

Maternal immunization is an effective strategy to protect pregnant women and their offspring from vaccine-preventable diseases. Despite the recommendation of maternal influenza and more recently pertussis immunization in Australia, uptake of these vaccines has been suboptimal. Monitoring the impact of the current funded vaccine programs for pregnant women is limited. The study aimed to assess the impact of the funded program and determine factors associated with vaccine uptake in pregnant women. This observational prospective study was undertaken between November 2014 and July 2016 at the Women’s and Children’s Hospital in South Australia (WCH). Demographic details and vaccination history from South Australian pregnant women who attended the WCH were reviewed. A standardized self-reported survey was conducted in antenatal care with a follow up telephone interview at 8-10 weeks post-delivery. A midwife delivered immunization program for pregnant women in antenatal clinic commenced in April 2015. Of the 180 pregnant women who completed the survey questionnaire, 75.5% and 80.5 % received maternal influenza and pertussis vaccines respectively. First-time mothers had twice the odds of having received influenza vaccine during pregnancy than multiparous women (OR 2.4; CI 1.14 - 4.94; p= 0.021). The proportion of women who received pertussis vaccine during pregnancy, following the introduction of the midwife delivered pertussis vaccination program (140/155, 90.3%) was significantly higher compared with women who received maternal pertussis vaccination prior to the introduction of the program (5/22, 23.7%, p < 0.001). The odds of women receiving maternal pertussis vaccine following the implementation of the midwife delivered program were 31 times higher than women who delivered babies prior to the program (OR 31.7, CI 10.24- 98.27; p < 0.001). High uptake of influenza and pertussis vaccines during pregnancy can be attained with health care provider recommendation and inclusion of maternal immunization as part of standard antenatal care.

Keywords: influenza, maternal immunization, pertussis, provider recommendation

Procedia PDF Downloads 247