Search results for: entrepreneurial framework conditions (EFCs)

Authors: Steven Arcidiacono, Robert Stote, Erin Anderson, Molly Richards

Abstract:

There are numerous standard test methods for antimicrobial textiles that measure activity against specific microorganisms. However, many times these results do not translate to the performance of treated textiles when worn by individuals. Standard test methods apply a single target organism grown under optimal conditions to a textile, then recover the organism to quantitate and determine activity; this does not reflect the actual performance environment that consists of polymicrobial communities in less than optimal conditions or interaction of the textile with the skin substrate. Here we propose the development of in vitro skin model method to bridge the gap between lab testing and wear studies. The model will consist of a defined polymicrobial community of 5-7 commensal microbes simulating the skin microbiome, seeded onto a solid tissue platform to represent the skin. The protocol would entail adding a non-commensal test organism of interest to the defined community and applying a textile sample to the solid substrate. Following incubation, the textile would be removed and the organisms recovered, which would then be quantitated to determine antimicrobial activity. Important parameters to consider include identification and assembly of the defined polymicrobial community, growth conditions to allow the establishment of a stable community, and choice of skin surrogate. This model could answer the following questions: 1) is the treated textile effective against the target organism? 2) How is the defined community affected? And 3) does the textile cause unwanted effects toward the skin simulant? The proposed model would determine activity under conditions comparable to the intended application and provide expanded knowledge relative to current test methods.

Keywords: antimicrobial textiles, defined polymicrobial community, in vitro skin model, skin microbiome

Procedia PDF Downloads 137

Authors: Abdulrahman M. Homadi

Abstract:

This study focuses on how to control the outlet temperature of a solar air heater in a way simpler than the existing methods. In this work, five cases have been studied by using ANSYS Fluent based on a CFD numerical method. All the cases have been simulated by utilizing the same criteria and conditions like the temperature, materials, areas except the geometry. The case studies are conducted in Little Rock (LR), AR, USA during the winter time supposedly on 15^th of December. A fresh air that is flowing with a velocity of 0.5 m/s and a flow rate of 0.009 m³/s. The results prove the possibility of achieving a controlled temperature just by changing the geometric shape of the heater. This geometry guarantees that the absorber plate always has a normal component of the solar radiation at any time during the day. The heater has a sectarian shape with a radius of 150 mm where the outlet temperature remains almost constant for six hours.

Keywords: solar energy, air heater, control of temperature, CFD

Procedia PDF Downloads 337

Authors: Calvin Stephen, Biswajit Basu, Aonghus McNabola

Abstract:

Market liberalization in the power sector has led to the emergence of micro-hydropower schemes that are dependent on the use of pumps-as-turbines in applications that were not suitable as potential hydropower sites in earlier years. These applications include energy recovery in water supply networks, sewage systems, irrigation systems, alcohol breweries, underground mining and desalination plants. As a result, there has been an accelerated adoption of pumpsas-turbine technology due to the economic advantages it presents in comparison to the conventional turbines in the micro-hydropower space. The performance of this machines under cavitation conditions, however, is not well understood as there is a deficiency of knowledge in literature focused on their turbine mode of operation. In hydraulic machines, cavitation is a common occurrence which needs to be understood to safeguard them and prolong their operation life. The overall purpose of this study is to investigate the effects of cavitation on the performance of a pumps-as-turbine system over its entire operating range. At various operating speeds, the cavitating region is identified experimentally while monitoring the effects this has on the power produced by the machine. Initial results indicate occurrence of cavitation at higher flow rates for lower operating speeds and at lower flow rates at higher operating speeds. This implies that for cavitation free operation, low speed pumps-as-turbine must be used for low flow rate conditions whereas for sites with higher flow rate conditions high speed turbines should be adopted. Such a complete understanding of pumps-as-turbine suction performance can aid avoid cavitation induced failures hence improved reliability of the micro-hydropower plant.

Keywords: cavitation, micro-hydropower, pumps-as-turbine, system design

Procedia PDF Downloads 119

Authors: Cheng Fang, Lingwei Quan, Cunyue Lu

Abstract:

Human pose estimation and tracking are to accurately identify and locate the positions of human joints in the video. It is a computer vision task which is of great significance for human motion recognition, behavior understanding and scene analysis. There has been remarkable progress on human pose estimation in recent years. However, more researches are needed for human pose tracking especially for online tracking. In this paper, a framework, called PoseSRPN, is proposed for online single-person pose estimation and tracking. We use Siamese network attaching a pose estimation branch to incorporate Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) into one framework. The pose estimation branch has a simple network structure that replaces the complex upsampling and convolution network structure with deconvolution. By augmenting the loss of fully convolutional Siamese network with the pose estimation task, pose estimation and tracking can be trained in one stage. Once trained, PoseSRPN only relies on a single bounding box initialization and producing human joints location. The experimental results show that while maintaining the good accuracy of pose estimation on COCO and PoseTrack datasets, the proposed method achieves a speed of 59 frame/s, which is superior to other pose tracking frameworks.

Keywords: computer vision, pose estimation, pose tracking, Siamese network

Procedia PDF Downloads 153

Authors: Yunus Emre Karakaya, Sebahattin Devecioglu, Bilal Coban

Abstract:

Today, information technology’s presence is felt in every field of life. Fields of education and sports sciences have their own share too. Especially developments in informatics technologies changed the perspectives of these fields. The altered technological conditions made distance education argumentative in these fields. Due to advantages distance education provides to students, they can access the desired education without concerns about time and place. Education facilities are seen to head for distance education in this manner and expedite the process. Distance education applications, which was first started to be applied in the mid-1800s, have been implemented in Turkey since 1970s and still continues today. In this study, the historical development of distance education in the world and Turkey and the problems athletes face in education were discussed. Accordingly, suggestions were made evaluating the importance and requirements of distance education in sports education facilities at higher education level. Additionally, Questions of “Is distance education important in sports education in Turkey?”, “What are the problems of athletes in the education field in Turkey?” and similar questions were attempted to be answered. Finally, in Turkey, distance sports education applications in universities should be launched to ensure that athletes’ educations are not deficit and unfinished. Within this framework, legal regulations should be implemented by “Council of Higher Education” to develop the distance sports education in Turkey and utilize distance education efficiently in solving the sports education problems. By ensuring the advancement of athletes with this method, it is expected for athletes to contribute to sports in the country in both government and the private sector in the medium and long terms. Individuals who participated in the distance sports education will set an example in extending the country’s youth to national and international fields.

Keywords: athletes, distance education, higher education, sports education, Turkey

Procedia PDF Downloads 350

Authors: Stamatis Zoras, Vasilis Evagelopoulos, Theodoros Staurakas

Abstract:

The association between elevated air pollution levels and extreme climate conditions (temperature, particulate matter, ozone levels, etc.) and mental consequences has been, recently, the focus of significant number of studies. It varies depending on the time of the year it occurs either during the hot period or cold periods but, specifically, when extreme air pollution and weather events are observed, e.g. air pollution episodes and persistent heatwaves. It also varies spatially due to different effects of air quality and climate extremes to human health when considering metropolitan or rural areas. An air pollutant concentration and a climate extreme are taking a different form of impact if the focus area is countryside or in the urban environment. In the built environment the climate extreme effects are driven through the formed microclimate which must be studied more efficiently. Variables such as biological, age groups etc may be implicated by different environmental factors such as increased air pollution/noise levels and overheating of buildings in comparison to rural areas. Gridded air quality and climate variables derived from the land surface observations network of West Macedonia in Greece will be analysed against mortality data in a spatial format in the region of West Macedonia. Artificial intelligence (AI) tools will be used for data correction and prediction of health deterioration with climatic conditions and air pollution at local scale. This would reveal the built environment implications against the countryside. The air pollution and climatic data have been collected from meteorological stations and span the period from 2000 to 2009. These will be projected against the mortality rates data in daily, monthly, seasonal and annual grids. The grids will be operated as AI-based warning models for decision makers in order to map the health conditions in rural and urban areas to ensure improved awareness of the healthcare system by taken into account the predicted changing climate conditions. Gridded data of climate conditions, air quality levels against mortality rates will be presented by AI-analysed gridded indicators of the implicated variables. An Al-based gridded warning platform at local scales is then developed for future system awareness platform for regional level.

Keywords: air quality, artificial inteligence, climatic conditions, mortality

Procedia PDF Downloads 113

Authors: Chenyao Shen, Jie Shen

Abstract:

The rating system provides an effective framework for assessing building environmental performance and integrating sustainable development into building and construction processes; as it can be used as a design tool by developing appropriate sustainable design strategies and determining performance measures to guide the sustainable design and decision-making processes. Healthcare buildings are resource (water, energy, etc.) intensive. To maintain high-cost operations and complex medical facilities, they require a great deal of hazardous and non-hazardous materials, stringent control of environmental parameters, and are responsible for producing polluting emission. Compared with other types of buildings, the impact of healthcare buildings on the full cycle of the environment is particularly large. With broad recognition among designers and operators that energy use can be reduced substantially, many countries have set up their own green rating systems for healthcare buildings. There are four main green healthcare building evaluation systems widely acknowledged in the world - Green Guide for Health Care (GGHC), which was jointly organized by the United States HCWH and CMPBS in 2003; BREEAM Healthcare, issued by the British Academy of Building Research (BRE) in 2008; the Green Star-Healthcare v1 tool, released by the Green Building Council of Australia (GBCA) in 2009; and LEED Healthcare 2009, released by the United States Green Building Council (USGBC) in 2011. In addition, the German Association of Sustainable Building (DGNB) has also been developing the German Sustainable Building Evaluation Criteria (DGNB HC). In China, more and more scholars and policy makers have recognized the importance of assessment of sustainable development, and have adapted some tools and frameworks. China’s first comprehensive assessment standard for green building (the GBTs) was issued in 2006 (lately updated in 2014), promoting sustainability in the built-environment and raise awareness of environmental issues among architects, engineers, contractors as well as the public. However, healthcare building was not involved in the evaluation system of GBTs because of its complex medical procedures, strict requirements of indoor/outdoor environment and energy consumption of various functional rooms. Learn from advanced experience of GGHC, BREEAM, and LEED HC above, China’s first assessment criteria for green hospital/healthcare buildings was finally released in December 2015. Combined with both quantitative and qualitative assessment criteria, the standard highlight the differences between healthcare and other public buildings in meeting the functional needs for medical facilities and special groups. This paper has focused on the assessment criteria framework for sustainable healthcare buildings, for which the comparison of different rating systems is rather essential. Descriptive analysis is conducted together with the cross-matrix analysis to reveal rich information on green assessment criteria in a coherent manner. The research intends to know whether the green elements for healthcare buildings in China are different from those conducted in other countries, and how to improve its assessment criteria framework.

Keywords: assessment criteria framework, green building design, healthcare building, building performance rating tool

Procedia PDF Downloads 146

Authors: Shayan Mohajer Hamidi

Abstract:

Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

Procedia PDF Downloads 75

Authors: Stanley Yap, Mahadevan Supramaniam, Chong Wei Ying, Fatemeh Kimiyaghalam

Abstract:

Purpose: The paper shows the framework of financial planning in a different paradigm. It highlights the results from a focus group on retirement planning in the aspect of financial literacy and wealth accumulation in Malaysia. Design/methodology/approach: A focus group consisted of thirty individuals and divided into six different clusters amongst 25 to 55 years old. The selection of focus group members is pertaining to retirement planning behavior and saving profile from the different level of educations. Findings: Our results show, firstly, the focus group reflects individual capacity on saving attitude, financial literacy and awareness towards financial products. Secondly, availability, accessibility and affordability which are the significant factors that influence saving attitude, financial literacy and awareness on personal retirement planning behavior. Practical implications: The participants express the concerns of retirement planning during their golden years and the current financial products in the Malaysian financial market. Originality/value: This study is a different approach that recognizes the needs of the consumers in the context of retirement planning and wealth accumulation. Therefore, customers should obtain financial services and products from financial providers to achieve financial independence.

Keywords: retirement planning, wealth accumulation, financial literacy, focus group, saving attitude, availability, accessibility, affordability

Procedia PDF Downloads 357

Authors: Muhammad Atif, Cang Yan

Abstract:

The enhancement of low-light images is a significant area of study aimed at enhancing the quality of captured images in challenging lighting environments. Recently, methods based on convolutional neural networks (CNN) have gained prominence as they offer state-of-the-art performance. However, many approaches based on CNN rely on increasing the size and complexity of the neural network. In this study, we propose an alternative method for improving low-light images using an autoencoder-based multiscale knowledge transfer model. Our method leverages the power of three autoencoders, where the encoders of the first two autoencoders are directly connected to the decoder of the third autoencoder. Additionally, the decoder of the first two autoencoders is connected to the encoder of the third autoencoder. This architecture enables effective knowledge transfer, allowing the third autoencoder to learn and benefit from the enhanced knowledge extracted by the first two autoencoders. We further integrate the proposed model into the PIX to PIX GAN framework. By integrating our proposed model as the generator in the GAN framework, we aim to produce enhanced images that not only exhibit improved visual quality but also possess a more authentic and realistic appearance. These experimental results, both qualitative and quantitative, show that our method is better than the state-of-the-art methodologies.

Keywords: low light image enhancement, deep learning, convolutional neural network, image processing

Procedia PDF Downloads 80

Authors: Phillip Thebe

Abstract:

African traders in China have generated magnanimous attention from scholars because of their choices to take short-term trips to Guangzhou and other places in search of cheaper products taking advantage of the status of China as a "global manufacturing hub". Nevertheless, their activities only gained traction at the turn of the millennium, with their presence in China incrementally dwindling over the next two decades. Now, with the devastating effects of COVID-19, their journeys have had to be totally cut short by unending lockdowns and stiff migration rules due to China's zero-tolerance of COVID-19 policy. This unfortunate yet untimely occurrence has left many scholars wondering if this marks the end of African traders in China and, indeed, the end of their business careers. Between March and September 2022, 20 traders were followed back to Africa, Zimbabwe, to find out what they are doing after having been shut out of China. Data was collected through ethnographic immersion and purposive in-depth interviewing in and around the city of Bulawayo. Snowballing was employed to reach out to the traders until a saturation point was reached and interview transcripts were filed for analysis. The findings revealed that some still trading online in China, report different opinions and feelings about doing business during COVID-19. Others have left the Chinese marketplace, now pursuing European industries in Turkey and other places. Others are still getting Chinese goods but in African countries such as Tanzania, Mozambique, South Africa, and Botswana. Some are now into the second-hand clothing trade, whereas others have stopped doing business to pursue other life-course interests. These and other issues are addressed in this paper from the anthropology of migration and globalization perspectives.

Keywords: entrepreneurship, African traders, China, COVID-19, Africans in China

Procedia PDF Downloads 93

Authors: Miral Selim, May Haggag, Ibrahim Abotaleb

Abstract:

The aging of transportation infrastructure presents significant challenges, particularly concerning the monitoring and maintenance of bridges. This study investigates the application of Random Forest algorithms for predictive modeling of bridge conditions, utilizing data from the US National Bridge Inventory (NBI). The research is significant as it aims to improve bridge management through data-driven insights that can enhance maintenance strategies and contribute to overall safety. Random Forest is chosen for its robustness, ability to handle complex, non-linear relationships among variables, and its effectiveness in feature importance evaluation. The study begins with comprehensive data collection and cleaning, followed by the identification of key variables influencing bridge condition ratings, including age, construction materials, environmental factors, and maintenance history. Random Forest is utilized to examine the relationships between these variables and the predicted bridge conditions. The dataset is divided into training and testing subsets to evaluate the model's performance. The findings demonstrate that the Random Forest model effectively enhances the understanding of factors affecting bridge conditions. By identifying bridges at greater risk of deterioration, the model facilitates proactive maintenance strategies, which can help avoid costly repairs and minimize service disruptions. Additionally, this research underscores the value of data-driven decision-making, enabling better resource allocation to prioritize maintenance efforts where they are most necessary. In summary, this study highlights the efficiency and applicability of Random Forest in predictive modeling for bridge management. Ultimately, these findings pave the way for more resilient and proactive management of bridge systems, ensuring their longevity and reliability for future use.

Keywords: data analysis, random forest, predictive modeling, bridge management

Procedia PDF Downloads 22

Authors: Nuri Caglayan, H. Kursat Celik

Abstract:

There are many factors that influence the health and productivity of the animals in livestock production fields, including temperature, humidity, carbon dioxide (CO2), ammonia (NH3), hydrogen sulfide (H2S), physical activity and particulate matter. High NH3 concentrations reduce feed consumption and cause daily weight gain. At high concentrations, H2S causes respiratory problems and CO2 displace oxygen, which can cause suffocation or asphyxiation. Good air quality in livestock facilities can have an impact on the health and well-being of animals and humans. Air quality assessment basically depends on strictly given limits without taking into account specific local conditions between harmful gases and other meteorological factors. The stated limitations may be eliminated. using controlling systems based on neural networks and fuzzy logic. This paper describes a fuzzy logic based ventilation algorithm, which can calculate different fan speeds under pre-defined boundary conditions, for removing harmful gases from the production environment. In the paper, a fuzzy logic model has been developed based on a Mamedani’s fuzzy method. The model has been built on MATLAB software. As the result, optimum fan speeds under pre-defined boundary conditions have been presented.

Keywords: air quality, fuzzy logic model, livestock housing, fan speed

Procedia PDF Downloads 372

Authors: Marisa Catarina da Conceição Dinis

Abstract:

The commercial companies’ management has suffered an important material and legal transformation in the last years, mainly related to the changes in the Portuguese legal framework and because of the fact they were recently object of great expansion. In fact, next to the smaller family businesses, whose management is regularly assumed by partners, companies with social investment highly scattered, whose owners are completely out from administration, are now arising. In those particular cases, the business transactions are much more complex and require from the companies’ managers a highly technical knowledge and some specific professionals’ skills and abilities. This kind of administration carries a high-level risk that can both result in great success or in great losses. Knowing that the administration performance can result in important losses to the companies, the Portuguese legislator has created a legal structure to impute them some responsibilities and sanctions. The main goal of this study is to analyze the Portuguese law and some jurisprudence about companies’ management rules and about the conflicts between the directors and the company. In order to achieve these purposes we have to consider, on the one hand, the legal duties directly connected to the directors’ functions and on the other hand the disrespect for those same rules. The Portuguese law in this matter, influenced by the common law, determines that the directors’ attitude should be guided by loyalty and honesty. Consequently, we must reflect in which cases the administrators should respond to losses that they might cause to companies as a result of their duties’ disrespect. In this way is necessary to study the business judgment rule wich is a rule that refers to a liability exclusion rule. We intend, in the same way, to evaluate if the civil liability that results from the directors’ duties disrespect can extend itself to those who have elected them ignoring or even knowing that they don´t have the necessary skills or appropriate knowledge to the position they hold. To charge directors’, without ruining entrepreneurship, charging, in the same way, those who select them reinforces the need for more responsible and cautious attitudes which will lead consequently to more confidence in the markets.

Keywords: business judgment rule, civil liability of directors, duty of care, duty of care, Portuguese legal framework

Procedia PDF Downloads 347

Authors: Yazid Abdullahi Abubakar, Jay Mitra

Abstract:

This paper is concerned with entrepreneurial high-impact firms, which are firms that generate ‘both’ disproportionate levels of employment and sales growth, and have high levels of innovative activity. It investigates differences in factors influencing high-impact growth between indigenous and foreign firms. The study is based on an analysis of data from United Kingdom (UK) Innovation Scoreboard on 865 firms, which were divided into high-impact firms (those achieving positive growth in both sales and employment) and low-impact firms (negative or no growth in sales or employment); in order to identifying the critical differences in regional, sectorial and size related factors that facilitate knowledge spillovers and high-impact growth between indigenous and foreign firms. The findings suggest that: 1) Firms’ access to regional knowledge spillovers (from businesses and higher education institutions) is more significantly associated with high-impact growth of UK firms in comparison to foreign firms, 2) Because high-tech sectors have greater use of knowledge spillovers (compared to low-tech sectors), high-tech sectors are more associated with high-impact growth, but the relationship is stronger for UK firms compared to foreign firms, 3) Because small firms have greater need for knowledge spillovers (relative to large firms), there is a negative relationship between firm size and high-impact growth, but the negative relationship is greater for UK firms in comparison to foreign firms.

Keywords: entrepreneurship, high-growth, indigenous firms, foreign firms, small firms, large firms

Procedia PDF Downloads 429

Authors: Anucha Taiwong, Nirobol Kanogsunthornrat

Abstract:

This predictive research aimed to investigate the symptom clusters that influence the quality of life among patients with chronic kidney disease, as indicated in the Theory of Unpleasant Symptoms. The purposive sample consisted of 150 patients with stage 3-4 chronic kidney disease who received care at an outpatient chronic kidney disease clinic of a tertiary hospital in Roi-Et province. Data were collected from January to March 2016 by using a patient general information form, unpleasant symptom form, and quality of life (SF-36) and were analyzed by using descriptive statistics, factor analysis, and multiple regression analysis. Findings revealed six core symptom clusters including symptom cluster of the mental and emotional conditions, peripheral nerves abnormality, fatigue, gastro-intestinal tract, pain and, waste congestion. Significant predictors for quality of life were the two symptom clusters of pain (Beta = -.220; p < .05) and the mental and emotional conditions (Beta=-.204; p<.05) which had predictive value of 19.10% (R2=.191, p<.05). This study indicated that the symptom cluster of pain and the mental and emotional conditions would worsen the patients’ quality of life. Nurses should be attentive in managing the two symptom clusters to facilitate the quality of life among patients with chronic kidney disease.

Keywords: chronic kidney disease, symptom clusters, predictors of quality of life, pre-dialysis

Procedia PDF Downloads 318

Authors: Kamaran Fathulla

Abstract:

Human creativity knows no bounds. More than a millennia ago humans have expressed their knowledge on cave walls and on clay artefacts. Using visuals such as diagrams and paintings have always provided us with a natural and intuitive medium for expressing such creativity. Making sense of human generated visualisation has been influenced by western scientific philosophies which are often reductionist in their nature. Theoretical frameworks such as those delivered by Peirce dominated our views of how to make sense of visualisation where a visual is seen as an emergent property of our thoughts. Others have reduced the richness of human-generated visuals to mere shapes drawn on a piece of paper or on a screen. This paper introduces an alternate framework where the centrality of human functioning is given explicit and richer consideration through the multi aspectual philosophical works of Herman Dooyeweerd. Dooyeweerd's framework of understanding reality was based on fifteen aspects of reality, each having a distinct core meaning. The totality of the aspects formed a ‘rainbow’ like spectrum of meaning. The thesis of this approach is that meaningful human functioning in most cases involves the diversity of all aspects working in synergy and harmony. Illustration of the foundations and applicability of this approach is underpinned in the case of humans use of diagramming for creative purposes, particularly within an educational context. Diagrams play an important role in education. Students and lecturers use diagrams as a powerful tool to aid their thinking. However, research into the role of diagrams used in education continues to reveal difficulties students encounter during both processes of interpretation and construction of diagrams. Their main problems shape up students difficulties with diagrams. The ever-increasing diversity of diagrams' types coupled with the fact that most real-world diagrams often contain a mix of these different types of diagrams such as boxes and lines, bar charts, surfaces, routes, shapes dotted around the drawing area, and so on with each type having its own distinct set of static and dynamic semantics. We argue that the persistence of these problems is grounded in our existing ways of understanding diagrams that are often reductionist in their underpinnings driven by a single perspective or formalism. In this paper, we demonstrate the limitations of these approaches in dealing with the three problems. Consequently, we propose, discuss, and demonstrate the potential of a nonreductionist framework for understanding diagrams based on Symbolic and Spatial Mappings (SySpM) underpinned by Dooyeweerd philosophy. The potential of the framework to account for the meaning of diagrams is demonstrated by applying it to a real-world case study physics diagram.

Keywords: SySpM, drawing style, mapping

Procedia PDF Downloads 238

Authors: Seun Mayowa Sunday

Abstract:

Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

Procedia PDF Downloads 135

Authors: Nuo Duan, Yi Pik Cheng

Abstract:

This paper presents the data of a series of two-dimensional Discrete Element Method (DEM) simulations of a large-diameter rigid monopile subjected to cyclic loading under a high gravitational force. At present, monopile foundations are widely used to support the tall and heavy wind turbines, which are also subjected to significant from wind and wave actions. A safe design must address issues such as rotations and changes in soil stiffness subject to these loadings conditions. Design guidance on the issue is limited, so are the availability of laboratory and field test data. The interpretation of these results in sand, such as the relation between loading and displacement, relies mainly on empirical correlations to pile properties. Regarding numerical models, most data from Finite Element Method (FEM) can be found. They are not comprehensive, and most of the FEM results are sensitive to input parameters. The micro scale behaviour could change the mechanism of the soil-structure interaction. A DEM model was used in this paper to study the cyclic lateral loads behaviour. A non-dimensional framework is presented and applied to interpret the simulation results. The DEM data compares well with various set of published experimental centrifuge model test data in terms of lateral deflection. The accumulated permanent pile lateral displacements induced by the cyclic lateral loads were found to be dependent on the characteristics of the applied cyclic load, such as the extent of the loading magnitudes and directions.

Keywords: cyclic loading, DEM, numerical modelling, sands

Procedia PDF Downloads 320

Authors: Rahisham Abd Rahman

Abstract:

In this paper, a nonlinear pollution model has been proposed to compute electric field distribution over the polymeric insulator surface under wet contaminated conditions. A 2D axial-symmetric insulator geometry, energized with 11kV was developed and analysed using Finite Element Method (FEM). A field-dependent conductivity with simplified assumptions was established to characterize the electrical properties of the pollution layer. Comparative field studies showed that simulation of dynamic pollution model results in a more realistic field profile, offering better understanding on how the electric field behaves under wet polluted conditions.

Keywords: electric field distributions, pollution layer, dynamic model, polymeric outdoor insulators, finite element method (FEM)

Procedia PDF Downloads 400

Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

Abstract:

Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by density-based time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., mean value, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one class classifier (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, a new anomaly detector strategy is proposed, namely one class classifier neural network two (OCCNN2), which exploit the classification capability of standard classifiers in an anomaly detection problem, finding the standard class (the boundary of the features space in normal operating conditions) through a two-step approach: coarse and fine boundary estimation. The coarse estimation uses classics OCC techniques, while the fine estimation is performed through a feedforward neural network (NN) trained that exploits the boundaries estimated in the coarse step. The detection algorithms vare then compared with known methods based on principal component analysis (PCA), kernel principal component analysis (KPCA), and auto-associative neural network (ANN). In many cases, the proposed solution increases the performance with respect to the standard OCC algorithms in terms of F1 score and accuracy. In particular, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 96% with the proposed method.

Keywords: anomaly detection, frequencies selection, modal analysis, neural network, sensor network, structural health monitoring, vibration measurement

Procedia PDF Downloads 123

Authors: Zhenming Wang, Jun Zhu, Yuchen Yang, Ning Zhao

Abstract:

In the present paper, an alternative framework is proposed to construct a class of finite difference multi-resolution nested weighted essentially non-oscillatory (WENO) schemes with an increasingly higher order of accuracy for solving inviscid Euler equations. These WENO schemes firstly obtain a set of reconstruction polynomials by a hierarchy of nested central spatial stencils, and then recursively achieve a higher order approximation through the lower-order precision WENO schemes. The linear weights of such WENO schemes can be set as any positive numbers with a requirement that their sum equals one and they will not pollute the optimal order of accuracy in smooth regions and could simultaneously suppress spurious oscillations near discontinuities. Numerical results obtained indicate that these alternative finite-difference multi-resolution nested WENO schemes with different accuracies are very robust with low dissipation and use as few reconstruction stencils as possible while maintaining the same efficiency, achieving the high-resolution property without any equivalent multi-resolution representation. Besides, its finite volume form is easier to implement in unstructured grids.

Keywords: finite-difference, WENO schemes, high order, inviscid Euler equations, multi-resolution

Procedia PDF Downloads 145

Authors: Aleksandra Y. Sazonova, Valentina M. Raeva

Abstract:

The aim of this work was to apply extractive distillation for acetonitrile removal from water solutions, to validate thermodynamic criterion based on excess Gibbs energy to entrainer selection process for acetonitrile – water mixture separation and show its potential efficiency at isothermal conditions as well as at isobaric (conditions of real distillation process), to simulate and analyze an extractive distillation process with chosen entrainers: optimize amount of trays and feeds, entrainer/original mixture and reflux ratios. Equimolar composition of the feed stream was chosen for the process, comparison of the energy consumptions was carried out. Glycerol was suggested as the most energetically and ecologically suitable entrainer.

Keywords: acetonitrile, entrainer, extractive distillation, water

Procedia PDF Downloads 267

Authors: Agata Chudzicka-Czupała, Nadiya Hapon, Liudmyla Karamushka, Marta żywiołek-Szeja

Abstract:

Objectives: The study is about the determinants of coping with stress connected with volunteer activity for Russo-Ukrainian war 2022 refugees. We examined the mental health reactions, chosen psychological traits, and motivational functions of volunteers working in Poland and Ukraine in relation to their coping with stress styles. The study was financed with funds from the Foundation for Polish Science in the framework of the FOR UKRAINE Programme. Material and Method: The study was conducted in 2022. The study was a quantitative, questionnaire-based survey. Data was collected through an online survey. The volunteers were asked to assess their propensity to use different styles of coping with stress connected with their activity for Russo-Ukrainian war refugees using The Brief Coping Orientation to Problems Experienced Inventory (Brief-COPE) questionnaire. Depression, anxiety, and stress were measured using the Depression, Anxiety, and Stress (DASS)-21 item scale. Chosen psychological traits, psychological capital and hardiness, were assessed by The Psychological Capital Questionnaire and The Norwegian Revised Scale of Hardiness (DRS-15R). Then The Volunteer Function Inventory (VFI) was used. The significance of differences between the variable means of the samples was tested by the Student's t-test. We used multivariate linear regression to identify factors associated with coping with stress styles separately for each national sample. Results: The sample consisted of 720 volunteers helping war refugees (in Poland, 435 people, and 285 in Ukraine). The results of the regression analysis indicate variables that are significant predictors of the propensity to use particular styles of coping with stress (problem-focused style, emotion-focused style and avoidant coping). These include levels of depression and stress, individual psychological characteristics and motivational functions, different for Polish and Ukrainians. Ukrainian volunteers are significantly more likely to use all three coping with stress styles than Polish ones. The results also prove significant differences in the severity of anxiety, stress and depression, the selected psychological traits and motivational functions studied, which led volunteers to participate in activities for war refugees. Conclusions: The results show that depression and stress severity, as well as psychological capital and hardiness, and motivational factors are connected with coping with stress behavior. The results indicate the need for increased attention to the well-being of volunteers acting under stressful conditions. They also prove the necessity of guiding the selection of people for specific types of volu

Keywords: anxiety, coping with stress styles, depression, hardiness, mental health, motivational functions, psychological capital, resilience, stress, war, volunteer, civil society

Procedia PDF Downloads 71

Authors: Salami Ayobami Taofeek, Ajayi Adeola

Abstract:

Rural tourism entrepreurship is a tourist industry which revolutionizes businesses and prompting economic development across the globe. It encompasses huge range activities, natural or man-made attractions, amenities and facilities, transportation, marketing and information systems. It is also an important export for 83% of the developing countries and the main export for one third of them. In 2000, developing countries recorded 142.6 million international arrivals an increase of 95% compared to the figures of 1990. However, only developing countries with effective natural and man-made tourism supporting and enhancing infrastructure have been able to develop their tourism sector and seize the attendance advantages. Rural areas of Nigeria possess some distinctive peculiarities which can be transformed into attractive tourist centers. In spite of all these, rural tourism areas are still faced with myriad problems which include poor finance inadequate awareness and education, lack of progress in developing the rural of progress in developing the rural tourism potentials inadequate legislation, insecurity, entrepreneurial inertness, over-dependent on oil among others. This paper focuses on the impact and challenges of rural tourism entrepreneurship as strategy for economic development in Nigeria. It reviews literature rural tourism, tourism entrepreneurship potentials and classifications of Nigerians tourism potential’s destinations. The paper concludes that Nigeria Government should encourage rural based tourism entrepreneurship development by addressing the challenges facing rural tourism entrepreneurship in the country.

Keywords: entrepreneurship, economic development, rural tourism, tourism destinations tourism potentials

Procedia PDF Downloads 431

Authors: Anna Fowler

Abstract:

When considering assets that may need protection, the mind begins to contemplate homes, cars, and investment funds. In most cases, the protection of those assets can be covered through security systems and insurance. Data is not the first thought that comes to mind that would need protection, even though data is at the core of most supply chain operations. It includes trade secrets, management of personal identifiable information (PII), and consumer data that can be used to enhance the overall experience. Data is considered a critical element of success for supply chains and should be one of the most critical areas to protect. In the supply chain industry, there are two major misconceptions about protecting data: (i) We do not manage or store confidential/personally identifiable information (PII). (ii) Reliance on Third-Party vendor security. These misconceptions can significantly derail organizational efforts to adequately protect data across environments. These statistics can be exciting yet overwhelming at the same time. The first misconception, “We do not manage or store confidential/personally identifiable information (PII)” is dangerous as it implies the organization does not have proper data literacy. Enterprise employees will zero in on the aspect of PII while neglecting trade secret theft and the complete breakdown of information sharing. To circumvent the first bullet point, the second bullet point forges an ideology that “Reliance on Third-Party vendor security” will absolve the company from security risk. Instead, third-party risk has grown over the last two years and is one of the major causes of data security breaches. It is important to understand that a holistic approach should be considered when protecting data which should not involve purchasing a Data Loss Prevention (DLP) tool. A tool is not a solution. To protect supply chain data, start by providing data literacy training to all employees and negotiating the security component of contracts with vendors to highlight data literacy training for individuals/teams that may access company data. It is also important to understand the origin of the data and its movement to include risk identification. Ensure processes effectively incorporate data security principles. Evaluate and select DLP solutions to address specific concerns/use cases in conjunction with data visibility. These approaches are part of a broader solutions framework called Data Security Assurance (DSA). The DSA Framework looks at all of the processes across the supply chain, including their corresponding architecture and workflows, employee data literacy, governance and controls, integration between third and fourth-party vendors, DLP as a solution concept, and policies related to data residency. Within cloud environments, this framework is crucial for the supply chain industry to avoid regulatory implications and third/fourth party risk.

Keywords: security by design, data security architecture, cybersecurity framework, data security assurance

Procedia PDF Downloads 88

Authors: Szabó Renáta Andrea

Abstract:

In 2012 Japan created a new plan in order to become a tourism nation. The number of foreign tourists rises rapidly year by year, and with the upcoming Olympics in 2020, tourism turned into a prioritized national strategy. This paper offers a new perspective of tourism research: instead of focusing on the host nation or the inbound tourists, it represents an emerging in-between group: foreign entrepreneur residents. Despite the fact that Japan continuously scores as one of the lowest in East and South Asia related to entrepreneurial activity, in recent years, the activity of foreign entrepreneur residents is on the rise. This study is focused on Kyoto - the former capital of Japan and a popular tourist destination - and applies the mixed embeddedness model, which was used to understand this new phenomena and explore this emerging mediator group between locals and foreign tourists. Immigrant entrepreneurship is often related to a disadvantageous situation, and the businesses are introduced as the sole purpose of making a profit. The study seeks to argue with this point of view and augment the standard approaches to immigrant entrepreneurship. The findings introduce the key factors of this lifestyle choice besides profit and present how entrepreneurship is becoming an escape route to avoid standard working environment while living in Japan. It also shows the gap in the visa system and raises awareness about the emerging trend.

Keywords: immigrant entrepreneurship, Japan, lifestyle entrepreneurship, mixed embeddedness model, tourism

Procedia PDF Downloads 134

Authors: Tanvir Hasan, Minhaz Uddin, Anwar Sadat Anik

Abstract:

A pressurizer is a safety-related reactor component that maintains the reactor operating pressure to guarantee safety. Its structure is usually made of high thermal and pressure resistive material. The mechanical structure of these components should be maintained in all working settings, including transient to severe accidents conditions. The goal of this study is to examine the structural integrity and stress of the pressurizer in order to ensure its design integrity towards transient situations. For this, the finite element method (FEM) was used to analyze the mechanical stress on pressurizer components in this research. ANSYS MECHANICAL tool was used to analyze a 3D model of the pressurizer. The material for the body and safety relief nozzle is selected as low alloy steel i.e., SA-508 Gr.3 Cl.2. The model was put into ANSYS WORKBENCH and run under the boundary conditions of (internal Pressure, -17.2 MPa, inside radius, -1348mm, the thickness of the shell, -127mm, and the ratio of the outside radius to an inside radius, - 1.059). The theoretical calculation was done using the formulas and then the results were compared with the simulated results. When stimulated at design conditions, the findings revealed that the pressurizer stress analysis completely fulfilled the ASME standards.

Keywords: pressurizer, stress analysis, finite element method, nuclear reactor

Procedia PDF Downloads 158

Authors: Oustani Mabrouka, Halilat Md Tahar, Hannachi Slimane

Abstract:

This study was conducted on representative and contrasting soils of arid regions. It focuses on the compared influence of two organic fertilizers: poultry manure (PM) and bovine manure (BM) on improving the microbial functioning of non-saline (SS) and saline (SSS) soils, in particularly, the process of mineralization of nitrogen and carbon. The microbiological activity was estimated by respirometric test (CO2–C emissions) and the extraction of two forms of mineral nitrogen (NH4+-N and NO3--N). Thus, after 56 days of incubation under controlled conditions (28 degrees and 80 per cent of the field capacity), the two types of manures showed that the mineralization activity varies according to type of soil and the organic substrate itself. However, the highest cumulative quantities of CO2–C, NH4+–N and NO3-–N obtained at the end of incubation were recorded in non-saline (SS) soil treated with poultry manure with 1173.4, 4.26 and 8.40 mg/100 g of dry soil, respectively. The reductions in rates of release of CO2–C and of nitrification under saline conditions were 21 and 36, 78 %, respectively. The influence of organic substratum on the microbial density shows a stimulating effect on all microbial groups studied. The whole results show the usefulness of two types of manures for the improvement of the microbiological functioning of arid soils.

Keywords: Salinity, Organic matter, Microorganisms, Mineralization, Nitrogen, Carbon, Arid regions

Procedia PDF Downloads 280

Authors: Diana Gibson

Abstract:

Aim: The first aim of the study was to ascertain the percentage of people who had been diagnosed with High Blood Pressure and/ or Type2 Diabetes Mellitus in Matzikama municipal district, Western Cape, South Africa. These two conditions are reportedly very high in this particular province, even though few statistics are available. A second aim was to gain insight into the understanding of these two conditions among sufferers. A third aim was to determine their allopathic use as well as indigenous medicinal plants to manage these conditions. A fourth aim was to understand how users of medicinal plants attend to their materiality and relationality as a continuum between humans and plants. The final aim was to ascertain the conservation status of medicinal plants utilised. Methods: One thousand one hundred and eighty-four (1184) respondents were interviewed. Semi-structured surveys were utilised to gather data on the percentage of people who had been medically diagnosed with High Blood Pressure and/or Type 2 Diabetes Mellitus. Local healers and knowledgeable old people were subsequently selected through a non-probability snowball sampling method. They were helped with plant collection. The plants were botanically identified. Results: The study found that people who have been diagnosed with High Blood Pressure or Type 2 Diabetes Mellitus drew on and continuously moved between biomedical and local understandings of these conditions. While they followed biomedical treatment regimens as far as possible they also drew on alternative ways of managing it through the use of medicinal plants. The most commonly used plant species overall were Lessertia frutescens, Tulbaghia violacea, Artemisia afra and Leonotus leonurus. For the users, medicinal plants were not mere material entities, they were actants in social networks where knowledge was produced through particular practices in specific places. None of the identified plants are currently threatened. Significance: Sufferers had a good understanding of the symptoms of and biomedical treatment regime for both conditions, but in everyday life they adhered to their local understandings and medicinal plants for treatment. The majority used reportedly used prescribed medication as well as plant alternatives.

Keywords: diabetes, high blood pressure, medicine, plants

Procedia PDF Downloads 244