Search results for: Two dimensional network

Authors: Mohd Najib Mansor, Nur Syamilah Md. Noor, Abdul Rahim Anuar, Shazida Jan Mohd Khan, Ahmad Zubir Ibrahim, Badariah Hj Din, Abu Sufian Abu Bakar, Kalsom Kayat, Wan Nurmahfuzah Jannah Wan Mansor

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This study aimed and focused on the behavior of youth entrepreneurs’ especially entrepreneurial self-efficacy and the performance in micro SMEs in Malaysia. Entrepreneurship development calls for support from various quarters, and mostly the need exists to initiate a youth entrepreneurship culture and drive amongst the youth in the society. Although backed up by the government and non-government organizations, micro-entrepreneurs are still facing challenges which greatly delay their progress, growth and consequently their input towards economic advancement. Micro-entrepreneurs are confronted with unique difficulties such as uncertainty, innovation, and evolution. Reviews on the development of entrepreneurial characteristics such as need for achievement, internal locus of control, risk-taking and innovation and have been recognized as highly associated with entrepreneurial behavior. The data in this study was obtained from the Department of Statistics, Malaysia. A random sampling of 830 respondents was distributed to 14 states that involve of micro-entrepreneurs. The study adopted a quantitative approach whereby a set of questionnaire was used to gather data. Multiple regression analysis was chosen as a method of analysis testing. The result of this study is expected to provide insight into the factor affecting entrepreneurial behavior and performance of youth entrepreneurs in micro SMEs. The finding showed that the Malaysian youth entrepreneurs do not have the entrepreneurial self-efficacy within themselves in order to accomplish greater success in their business venture. The establishment of entrepreneurial schools to allow our youth to be exposed to entrepreneurship from an early age and the development of special training focuses on the creation of business network so that the continuous entrepreneurial culture is crafted.

Keywords: youth entrepreneurs, micro entrepreneurs, entrepreneurial self-efficacy, entrepreneurial performance

Procedia PDF Downloads 277

Authors: Chang-Jen Lan

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Current Level of Service (LOS) index adopted in Highway Capacity Manual (HCM) for signalized intersections on surface streets is based on the intersection average delay. The delay thresholds for defining LOS grades are subjective and is unrelated to critical traffic condition. For example, an intersection delay of 80 sec per vehicle for failing LOS grade F does not necessarily correspond to the intersection capacity. Also, a specific measure of average delay may result from delay minimization, delay equality, or other meaningful optimization criteria. To that end, a reliability version of the intersection critical degree of saturation (v/c) as the LOS index is introduced. Traditionally, the level of saturation at a signalized intersection is defined as the ratio of critical volume sum (per lane) to the average saturation flow (per lane) during all available effective green time within a cycle. The critical sum is the sum of the maximal conflicting movement-pair volumes in northbound-southbound and eastbound/westbound right of ways. In this study, both movement volume and saturation flow are assumed log-normal distributions. Because, when the conditions of central limit theorem obtain, multiplication of the independent, positive random variables tends to result in a log-normal distributed outcome in the limit, the critical degree of saturation is expected to be a log-normal distribution as well. Derivation of the risk index predictive limits is complex due to the maximum and absolute value operators, as well as the ratio of random variables. A fairly accurate functional form for the predictive limit at a user-specified significant level is yielded. The predictive limit is then compared with the designated LOS thresholds for the intersection critical degree of saturation (denoted as X

Keywords: reliability analysis, level of service, intersection critical degree of saturation, risk based index

Procedia PDF Downloads 119

Authors: Ali Mirtaghavi, Andy Baldwin, Rajendarn Muthuraj, Jack Luo

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Recent advances in biomaterials have led to utilizing biopolymers to develop 3D scaffolds in tissue regeneration. One of the major challenges of designing biomaterials for 3D scaffolds is to mimic the building blocks similar to the extracellular matrix (ECM) of the native tissues. Biopolymer based aerogels obtained by freeze-drying have shown to provide structural similarities to the ECM owing to their 3D format and a highly porous structure with interconnected pores, similar to the ECM. Gelatin (GEL) is known to be a promising biomaterial with inherent regenerative characteristics owing to its chemical similarities to the ECM in native tissue, biocompatibility abundance, cost-effectiveness and accessible functional groups, which makes it facile for chemical modifications with other biomaterials to form biocomposites. Despite such advantages, gelatin offers poor mechanical properties, sensitive enzymatic degradation and high viscosity at room temperature which limits its application and encourages its use to develop biocomposites. Hydrophilic biomass-based cellulose nanofibrous (CNF) has been explored to use as suspension for biocomposite aerogels for the development of 3D porous structures with excellent mechanical properties, biocompatibility and slow enzymatic degradation. In this work, CNF biocomposite aerogels with various ratios of CNF:GEL) (90:10, 70:30 and 50:50) were prepared by freeze-drying technique, and their properties were investigated in terms of physicochemical, mechanical and biological characteristics. Epichlorohydrin (EPH) was used to investigate the effect of chemical crosslinking on the molecular interaction of CNF: GEL, and its effects on physicochemical, mechanical and biological properties of the biocomposite aerogels. Ultimately, chemical crosslinking helped to improve the mechanical resilience of the resulting aerogels. Amongst all the CNF-GEL composites, the crosslinked CNF: GEL (70:30) biocomposite was found to be favourable for cell attachment and viability. It possessed highly porous structure (porosity of ~93%) with pore sizes ranging from 16-110 µm, adequate mechanical properties (compression modulus of ~47 kPa) and optimal biocompatibility both in-vitro and in-vivo, as well as controlled enzymatic biodegradation, high water penetration, which could be considered a suitable option for wound healing application. In-vivo experiments showed improvement on inflammation and foreign giant body cell reaction for the crosslinked CNF: GEL (70:30) compared to the other samples. This could be due to the superior interaction of CNF with gelatin through chemical crosslinking, resulting in more optimal in-vivo improvement. In-vitro cell culture investigation on human dermal fibroblasts showed satisfactory 3D cell attachment over time. Overall, it has been observed that the developed CNF: GEL aerogel can be considered as a potential scaffold for soft tissue regeneration application.

Keywords: 3D scaffolds, aerogels, Biocomposites , tissue engineering

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Authors: Tayebeh Jameh-Bozorgi, M. Soleymani

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In this research, the role of social networks in promoting ethics in Iranian sports was investigated. The research adopted a descriptive-analytic method, and the survey’s population consisted of all the athletes invited to the national football, volleyball, wrestling and taekwondo teams. Considering the limited population, the size of the society was considered as the sample size. After the distribution of the questionnaires, 167 respondents answered the questionnaires correctly. The data collection tool was chosen according to Hamid Ghasemi`s, standard questionnaire for social networking and mass media, which has 28 questions. Reliability of the questionnaire was calculated using Cronbach's alpha coefficient (94%). The content validity of the questionnaire was also approved by the professors. In this study, descriptive statistics and inferential statistical methods were used to analyze the data using statistical software. The benchmark tests used in this research included the following: Binomial test, Friedman test, Spearman correlation coefficient, Vermont Creamers, Good fit test and comparative prototypes. The results showed that athletes believed that social network has a significant role in promoting sport ethics in the community. Telegram has been known to play a big role than other social networks. Moreover, the respondents' view on the role of social networks in promoting sport ethics was significantly different in both men and women groups. In fact, women had a more positive attitude towards the role of social networks in promoting sport ethics than men. The respondents' view of the role of social networks in promoting the ethics of sports in the study groups also had a significant difference. Additionally, there was a significant and reverse relationship between the sports experience and the attitude of national athletes regarding the role of social networks in promoting ethics in sports.

Keywords: ethics, social networks, mass media, Iranian sports, internet

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Authors: Satish Kumar, Spandan Sahu, Sarjati Sahoo, K. K. Khatua

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An experimental investigation has been carried out in a tilting flume of 2 m wide, 13 m long, and 0.3 m deep to study the effect of flow on the formation of braided channel pattern. Sediment flow is recirculated through the flume, which passes from the headgate to the sediment/water collecting tank through the tailgate. Further, without altering the geometry of the sand bed channel, the discharge is varied to study the effect of the formation of the braided pattern with time. Then the flow rate is varied to study the effect of flow on the formation of the braided pattern. Sediment transport rate is highly variable and was found to be a nonlinear function of flow rate, aspect ratio, longitudinal slope, and time. Total braided intensity (BIT) for each discharge case is found to be more than the active braided intensity (BIA). Both the parameters first increase and then decrease as the time progresses following a similar pattern for all the observed discharge cases. When the flow is increased, the movement of sediment also increases since the active braided intensity is found to adjust quickly. The measurement of velocity and boundary shear helps to study the erosion and sedimentation processes in the channel and formation of small meandering channels and then the braided channel for different discharge conditions of a sediment river. Due to regime properties of rivers, both total braided Intensity and active braided intensity become stable for a given channel and flow conditions. In the present case, the trend of the ratio of BIA to BIT is found to be asymptotic against the time with a value of 0.4. After the particular time elapses off the flow, new small channels are also found to be formed with changes in the sinuosity of the active channels, thus forming the braided network. This is due to the continuous erosion and sedimentation processes occurring for the flow process for the flow and sediment conditions.

Keywords: active braided intensity, bed load, sediment transport, shear stress, total braided intensity

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Authors: Dario Barsi, Marina Ubaldi, Pietro Zunino, Robert Fink

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A design and optimization procedure is proposed and developed to provide the geometry of a high efficiency compact hydraulic propeller turbine for low head. For the preliminary design of the machine, classic design criteria, based on the use of statistical correlations for the definition of the fundamental geometric parameters and the blade shapes are used. These relationships are based on the fundamental design parameters (i.e., specific speed, flow coefficient, work coefficient) in order to provide a simple yet reliable procedure. Particular attention is paid, since from the initial steps, on the correct conformation of the meridional channel and on the correct arrangement of the blade rows. The preliminary geometry thus obtained is used as a starting point for the hydrodynamic optimization procedure, carried out using a CFD calculation software coupled with a genetic algorithm that generates and updates a large database of turbine geometries. The optimization process is performed using a commercial approach that solves the turbulent Navier Stokes equations (RANS) by exploiting the axial-symmetric geometry of the machine. The geometries generated within the database are therefore calculated in order to determine the corresponding overall performance. In order to speed up the optimization calculation, an artificial neural network (ANN) based on the use of an objective function is employed. The procedure was applied for the specific case of a propeller turbine with an innovative design of a modular type, specific for applications characterized by very low heads. The procedure is tested in order to verify its validity and the ability to automatically obtain the targeted net head and the maximum for the total to total internal efficiency.

Keywords: renewable energy conversion, hydraulic turbines, low head hydraulic energy, optimization design

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Authors: Arash Parehkar, S. Jamshid Mousavi, Shoubo Bayazidi, Vahid Karami, Laleh Shahidi, Arash Azaranfar, Ali Moridi, M. Shabakhti, Tayebeh Ariyan, Mitra Tofigh, Kaveh Masoumi, Alireza Motahari

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Water resource systems modelling have constantly been a challenge through history for human being. As the innovative methodological development is evolving alongside computer sciences on one hand, researches are likely to confront more complex and larger water resources systems due to new challenges regarding increased water demands, climate change and human interventions, socio-economic concerns, and environment protection and sustainability. In this research, an automatic calibration scheme has been applied on the Gilan’s large-scale water resource model using mathematical programming. The water resource model’s calibration is developed in order to attune unknown water return flows from demand sites in the complex Sefidroud irrigation network and other related areas. The calibration procedure is validated by comparing several gauged river outflows from the system in the past with model results. The calibration results are pleasantly reasonable presenting a rational insight of the system. Subsequently, the unknown optimized parameters were used in a basin-scale linear optimization model with the ability to evaluate the system’s performance against a reduced inflow scenario in future. Results showed an acceptable match between predicted and observed outflows from the system at selected hydrometric stations. Moreover, an efficient operating policy was determined for Sefidroud dam leading to a minimum water shortage in the reduced inflow scenario.

Keywords: auto-calibration, Gilan, large-scale water resources, simulation

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Authors: Anthony D. Rhodes, Manan Goel

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We provide a high fidelity deep learning algorithm (HyperSeg) for interactive video segmentation tasks using a dense convolutional network with context-aware skip connections and compressed, 'hypercolumn' image features combined with a convolutional tessellation procedure. In order to maintain high output fidelity, our model crucially processes and renders all image features in high resolution, without utilizing downsampling or pooling procedures. We maintain this consistent, high grade fidelity efficiently in our model chiefly through two means: (1) we use a statistically-principled, tensor decomposition procedure to modulate the number of hypercolumn features and (2) we render these features in their native resolution using a convolutional tessellation technique. For improved pixel-level segmentation results, we introduce a boundary loss function; for improved temporal coherence in video data, we include temporal image information in our model. Through experiments, we demonstrate the improved accuracy of our model against baseline models for interactive segmentation tasks using high resolution video data. We also introduce a benchmark video segmentation dataset, the VFX Segmentation Dataset, which contains over 27,046 high resolution video frames, including green screen and various composited scenes with corresponding, hand-crafted, pixel-level segmentations. Our work presents a improves state of the art segmentation fidelity with high resolution data and can be used across a broad range of application domains, including VFX pipelines and medical imaging disciplines.

Keywords: computer vision, object segmentation, interactive segmentation, model compression

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Authors: Eszter Hamza

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The competitiveness of economic operators is based on interoperability, which is relatively low in Hungary. The development of co-operation is high priority in Common Agricultural Policy 2014-2020. The aim of the paper to assess co-operations in Hungarian agriculture, estimate the economic outputs and benefits of co-operations, based on statistical data processing and literature. Further objective is to explore the potential of agricultural co-operation with the help of interviews and questionnaire survey. The research seeks to answer questions as to what fundamental factors play role in the development of co-operation, and what are the motivations of the actors and the key success factors and pitfalls. The results were analysed using econometric methods. In Hungarian agriculture we can find several forms of co-operation: cooperatives, producer groups (PG) and producer organizations (PO), machinery cooperatives, integrator companies, product boards and interbranch organisations. Despite the several appearance of the agricultural co-operation, their economic weight is significantly lower in Hungary than in western European countries. Considering the agricultural importance, the integrator companies represent the most weight among the co-operations forms. Hungarian farmers linked to co-operations or organizations mostly in relation to procurement and sales. Less than 30 percent of surveyed farmers are members of a producer organization or cooperative. The trust level is low among farmers. The main obstacle to the development of formalized co-operation, is producers' risk aversion and the black economy in agriculture. Producers often prefer informal co-operation instead of long-term contractual relationships. The Hungarian agricultural co-operations are characterized by non-dynamic development, but slow qualitative change. For the future, one breakout point could be the association of producer groups and organizations, which in addition to the benefits of market concentration, in the dissemination of knowledge, advisory network operation and innovation can act more effectively.

Keywords: agriculture, co-operation, producer organisation, trust level

Procedia PDF Downloads 378

Authors: Louise Moles, Steve Riley, Sarah D. Lichenstein, Marzieh Babaeianjelodar, Robert Kohler, Annie Cheng, Corey Horien Abigail Greene, Wenjing Luo, Jonathan Ahern, Bohan Xu, Yize Zhao, Chun Chieh Fan, R. Todd Constable, Sarah W. Yip

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Background: Risks for depression are myriad and include both genetic and brain-based factors. However, relationships between these systems are poorly understood, limiting understanding of disease etiology, particularly at the developmental level. Methods: We use a data-driven machine learning approach connectome-based predictive modeling (CPM) to identify functional connectivity signatures associated with polygenic risk scores for depression (DEP-PRS) among youth from the Adolescent Brain and Cognitive Development (ABCD) study across diverse brain states, i.e., during resting state, during affective working memory, during response inhibition, during reward processing. Results: Using 10-fold cross-validation with 100 iterations and permutation testing, CPM identified connectivity signatures of DEP-PRS across all examined brain states (rho’s=0.20-0.27, p’s<.001). Across brain states, DEP-PRS was positively predicted by increased connectivity between frontoparietal and salience networks, increased motor-sensory network connectivity, decreased salience to subcortical connectivity, and decreased subcortical to motor-sensory connectivity. Subsampling analyses demonstrated that model accuracies were robust across random subsamples of N’s=1,000, N’s=500, and N’s=250 but became unstable at N’s=100. Conclusions: These data, for the first time, identify neural networks of polygenic depression risk in a large sample of youth before the onset of significant clinical impairment. Identified networks may be considered potential treatment targets or vulnerability markers for depression risk.

Keywords: genetics, functional connectivity, pre-adolescents, depression

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Authors: Arezoo Assarian, Reza Javaherdashti

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Microbiologically influenced corrosion (MIC) is an electrochemical process that can affect both metals and non-metals. The cost of MIC can amount to 40% of the cost of corrosion. MIC is enhanced via factors such as but not limited to the presence of certain bacteria and archaea as well as mechanisms such as external electron transfer. There are five methods by which electrochemical corrosion, including MIC, can be prevented, of which coatings are an effective method due to blinding anode, cathode and, electrolyte from each other. Conventional ordinary coatings may themselves become nutrient sources for the bacteria and therefore show low efficiency in dealing with MIC. Recently our works on polyaspartic coating (DTM) have shown promising results, therefore nominating DTM as the most appropriate coating material to manage both MIC and general electrochemical corrosion very efficiently. Nanosilver particles are known for their antimicrobial properties that make them of desirable distractive impacts on any germs. This coating will be formulated based on Nanosilver phosphate and copper II oxide in the resin network and co-reactant. The nanoparticles are light and heat-sensitive agents. The method which is used to keep nanoparticles in the film coating is the encapsulation of active ingredients. By this method, it will prevent incompatibility between different particles. For producing microcapsules, the interfacial cross-linking method will be used. This is achieved by adding an active ingredient to an aqueous solution of the cross-linkable polymer. In this paper, we will first explain the role of coating materials in controlling and preventing electrochemical corrosion. We will explain MIC and some of its fundamental principles, such as bacteria establishment (biofilm) and the role they play in enhancing corrosion via mechanisms such as the establishment of differential aeration cells. Later we will explain features of DTM coatings that highly contribute to preventing biofilm formation and thus microbial corrosion.

Keywords: biofilm, corrosion, microbiologically influenced corrosion(MIC), nanosilver particles, polyaspartic coating (DTM)

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Authors: Antonia Hoffmann, Andrea Stübner

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Resource scarcity and rising material prices are forcing companies to rethink their business models. The conventional linear system of economic growth and rising social needs further exacerbates the problem of resource scarcity. Therefore, it is necessary to separate economic growth from resource consumption. This can be achieved through the circular economy (CE), which focuses on sustainable product life cycles. However, companies face challenges in implementing CE into their businesses. Small and medium-sized enterprises are particularly affected by these problems, as they have a limited resource base. Collaboration and social interaction between different actors can help to overcome these obstacles. Based on a self-generated sample of 1,023 German small and medium-sized enterprises, we use a questionnaire to investigate the influence of social capital and its three dimensions - structural, relational, and cognitive capital - on the implementation of CE and the mediating effect of dynamic capabilities in explaining these relationships. Using regression analyses and structural equation modeling, we find that social capital is positively associated with CE implementation and dynamic capabilities partially mediate this relationship. Interestingly, our findings suggest that not all social capital dimensions are equally important for CE implementation. We theoretically and empirically explore the network forms of social capital and extend the CE literature by suggesting that dynamic capabilities help organizations leverage social capital to drive the implementation of CE practices. The findings of this study allow us to suggest several implications for managers and institutions. From a practical perspective, our study contributes to building circular production and service capabilities in small and medium-sized enterprises. Various CE activities can transform products and services to contribute to a better and more responsible world.

Keywords: circular economy, dynamic capabilities, SMEs, social capital

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Authors: Md Maruf Hossain Koli

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The issue of child labor is enormous and cannot be ignored in Bangladesh. The problem of child exploitation is a socio-economic reality of Bangladesh. This paper will indicate the causes, consequences, and possibilities of using microfinance as remedies of hazardous child labor in Bangladesh. Poverty is one of the main reasons for children to become child laborers. It is an indication of economic vulnerability, inadequate law, and enforcement system and cultural and social inequities along with the inaccessible and low-quality educational system. An attempt will be made in this paper to explore and analyze child labor scenario in Bangladesh and will explain holistic intervention of BRAC, the largest nongovernmental organization in the world to address child labor through promoting incubation support to youth-led enterprises. A combination of research methods were used to write this paper. These include non-reactive observation in the form of literature review, desk studies as well as reactive observation like site visits and, semi-structured interviews. Hazardous Child labor is a multi-dimensional and complex issue. This paper was guided by the answer following research questions to better understand the current context of hazardous child labor in Bangladesh, especially in Dhaka city. The author attempted to figure out why child labor should be considered as a development issue? Further, it also encountered why child labor in Bangladesh is not being reduced at an expected pace? And finally what could be a sustainable solution to eradicate this situation. One of the most challenging characteristics of child labor is that it interrupts a child’s education and cognitive development hence limiting the building of human capital and fostering intergenerational reproduction of poverty and social exclusion. Children who are working full-time and do not attend school, cannot develop the necessary skills. This leads them and their future generation to remain in poor socio-economic condition as they do not get a better paying job. The vicious cycle of poverty will be reproduced and will slow down sustainable development. The outcome of the research suggests that most of the parents send their children to work to help them to increase family income. In addition, most of the youth engaged in hazardous work want to get training, mentoring and easy access to finance to start their own business. The intervention of BRAC that includes classroom and on the job training, tailored mentoring, health support, access to microfinance and insurance help them to establish startup. This intervention is working in developing business and management capacity through public-private partnerships and technical consulting. Supporting entrepreneurs, improving working conditions with micro, small and medium enterprises and strengthening value chains focusing on youth and children engaged with hazardous child labor.

Keywords: child labour, enterprise development, microfinance, youth entrepreneurship

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Authors: Si-yang Zhang, Chi Zhao

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Comprehensive transportation hubs are important nodes of the transportation network, and their internal signage the functions as guidance and distribution assistance, which directly affects the operational efficiency of traffic in and around the hubs. Reasonably installed signage effectively attracts the visual focus of travelers and improves wayfinding efficiency. Among the elements of signage, the visual guidance effect is the key factor affecting the information conveyance, whom should be evaluated during design and optimization process. However, existing evaluation methods mostly focus on the layout, and are not able to fully understand if signage caters travelers’ need. This study conducted field investigations and developed panoramic videos for multiple transportation hubs in China, and designed survey accordingly. Human subjects are recruited to watch panoramic videos via virtual reality (VR) and respond to the surveys. In this paper, Pudong Airport and Xi'an North Railway Station were studied and compared as examples due to their high traveler volume and relatively well-developed traveler service systems. Visual attention was captured by eye tracker and subjective satisfaction ratings were collected through surveys. Entropy Weight Method (EWM) was utilized to evaluate the effectiveness of signage elements and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to further rank the importance of the elements. The results show that the degree of visual attention of travelers significantly affects the evaluation results of guidance signage. Key factors affecting visual attention include accurate legibility, obstruction and defacement rates, informativeness, and whether signage is set up in a hierarchical manner.

Keywords: traveler guidance signage, panoramic video, visual attention, entropy weight method, TOPSIS

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Authors: Abiola A. Ojesanmi, Eric O. Amonsou

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The formation of soluble complexes is usually within a narrow pH range characterized by weak interactions. Moreover, the rigid conformation of globular proteins restricts the number of charged groups capable of interacting with polysaccharides, thereby limiting food applications. Hence, this study investigated the impact of tryptic-limited hydrolysis on the formation of Bambara protein-gum arabic soluble complexes formation. The electrostatic interactions were monitored through turbidimetry analysis. The Bambara protein hydrolysates at a specified degree of hydrolysis, and DHs (2, 5, and 7.5) were characterized using size exclusion chromatography, zeta potential, surface hydrophobicity, and intrinsic fluorescence. The stability of the complexes was investigated using differential scanning calorimetry and rheometry. The limited tryptic hydrolysis significantly widened the pH range of the formation of soluble complexes, with DH 5 having a wider range (pH 7.0 - 4.3) compared to DH 2 and DH 7.5, while there was no notable difference in the optimum complexation pH of the insoluble complexes. Larger peptides (140, 118 kDa) were detected in DH 2 relative to 144, 70, and 61 kDa in DH 5, which were larger than 140, 118, 48, and 32 kDa in DH 7. 5. An increase in net negative charge (- 30 Mv for DH 7.5) and a slight shift in the net neutrality (from pH 4.9 to 4.3) of the hydrolysates were observed which consequently impacted the electrostatic interaction with gum arabic. There was exposure of the hydrophobic amino acids up to 4-fold in comparison with the isolate and a red shift in maximum fluorescence wavelength in DH dependent manner following the hydrolysis. The denaturation temperature of the soluble complex from the hydrolysates shifted to higher values, having DH 5 with the maximum temperature (94.24 °C). A highly interconnected gel-like soluble complex network was formed having DH 5 with a better structure relative to DH 2 and 7.5. The study showed the use of limited tryptic hydrolysis at DH 5 as an effective approach to modify Bambara protein and provided a more stable and wider pH range of formation for soluble complex, thereby enhancing the food application.

Keywords: Bambara groundnut, gum arabic, interaction, soluble complex

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Authors: Benjamin Castillo, Luis Pastenes, Fernando Cordova

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The pathogen growth in animal source foods is a common problem in the food industry, causing monetary losses due to the spoiling of products or food intoxication outbreaks in the community. In this sense, the quality of the product is reflected by the population of deteriorating agents present in it, which are mainly bacteria. The factors which are likely associated with freshness in animal source foods are temperature and processing, storage, and transport times. However, the level of deterioration of products depends, in turn, on the characteristics of the bacterial population, causing the decomposition or spoiling, such as pH level and toxins. Knowing the growth dynamics of the agents that are involved in product contamination allows the monitoring for more efficient processing. This means better quality and reasonable costs, along with a better estimation of necessary time and temperature intervals for transport and storage in order to preserve product quality. The objective of this project is to design a secondary model that allows measuring the impact on temperature bacterial growth and the competition for pH adequacy and release of bacteriocins in order to describe such phenomenon and, thus, estimate food product half-life with the least possible risk of deterioration or spoiling. In order to achieve this objective, the authors propose an analysis of a three-dimensional ordinary differential which includes; logistic bacterial growth extended by the inhibitory action of bacteriocins including the effect of the medium pH; change in the medium pH levels through an adaptation of the Luedeking-Piret kinetic model; Bacteriocin concentration modeled similarly to pH levels. These three dimensions are being influenced by the temperature at all times. Then, this differential system is expanded, taking into consideration the variable temperature and the concentration of pulsed bacteriocins, which represent characteristics inherent of the modeling, such as transport and storage, as well as the incorporation of substances that inhibit bacterial growth. The main results lead to the fact that temperature changes in an early stage of transport increased the bacterial population significantly more than if it had increased during the final stage. On the other hand, the incorporation of bacteriocins, as in other investigations, proved to be efficient in the short and medium-term since, although the population of bacteria decreased, once the bacteriocins were depleted or degraded over time, the bacteria eventually returned to their regular growth rate. The efficacy of the bacteriocins at low temperatures decreased slightly, which equates with the fact that their natural degradation rate also decreased. In summary, the implementation of the mathematical model allowed the simulation of a set of possible bacteria present in animal based products, along with their properties, in various transport and storage situations, which led us to state that for inhibiting bacterial growth, the optimum is complementary low constant temperatures and the initial use of bacteriocins.

Keywords: bacterial growth, bacteriocins, mathematical modelling, temperature

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Authors: Viveka Jackson, Erouscilla Joseph, Denise Beckles, Thomas Christopher

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Sulphur Dioxide (SO2) has been defined as a non-flammable, non-explosive, colourless gas, having a pungent, irritating odour, and is one of the main gases emitted from volcanoes. Sulphur dioxide has been recorded in concentrations hazardous to humans (0.25 – 0.5 ppm (~650 – 1300 μg/m3), downwind of many volcanoes and hence warrants constant air-quality monitoring around these sites. It has been linked to an increase in chronic respiratory disease attributed to long-term exposures and alteration in lung and other physiological functions attributed to short-term exposures. Sulphur Springs in Saint Lucia is a highly active geothermal area, located within the Soufrière Volcanic Centre, and is a park widely visited by tourists and locals. It is also a current source of continuous volcanic emissions via its many fumaroles and bubbling pools, warranting concern by residents and visitors to the park regarding the effects of exposure to these gases. In this study, we introduce a novel SO2 measurement system for the monitoring and quantification of ambient levels of airborne volcanic SO2 using low-cost technology. This work involves the extensive production of low-cost SO2 monitors/samplers, as well as field examination in tandem with standard commercial samplers (SO2 diffusion tubes). It also incorporates community involvement in the volcanic monitoring process as non-professional users of the instrument. We intend to present the preliminary monitoring results obtained from the low-cost samplers, to identify the areas in the Park exposed to high concentrations of ambient SO2, and to assess the feasibility of the instrument for non-professional use and application in volcanic settings

Keywords: ambient SO2, community-based monitoring, risk-reduction, sulphur springs, low-cost

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Authors: Chaitanya H. Acharya, Pavan Kumar P., Gopalakrishna Narayana

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In the realm of aerodynamics, numerous vehicles incorporate moving components to enhance their performance. For instance, airliners deploy hydraulically operated flaps and ailerons during take-off and landing, while Formula 1 racing cars utilize hydraulic tubes and actuators for various components, including the Drag Reduction System (DRS). The DRS, consisting of a rear wing and adjustable flaps, plays a crucial role in overtaking manoeuvres. The DRS has two positions: the default position with the flaps down, providing high downforce, and the lifted position, which reduces drag, allowing for increased speed and aiding in overtaking. Swift deployment of the DRS during races is essential for overtaking competitors. The fluid flow over the rear wing flap becomes intricate during deployment, involving flow reversal and operational changes, leading to unsteady flow physics that significantly influence aerodynamic characteristics. Understanding the drag and downforce during DRS deployment is crucial for determining race outcomes. While experiments can yield accurate aerodynamic data, they can be expensive and challenging to conduct across varying speeds. Computational Fluid Dynamics (CFD) emerges as a cost-effective solution to predict drag and downforce across a range of speeds, especially with the rapid deployment of the DRS. This study employs the finite volume-based solver Ansys Fluent, incorporating dynamic mesh motions and a turbulent model to capture the complex flow phenomena associated with the moving rear wing flap. A dedicated section for the rare wing-flap is considered in the present simulations, and the aerodynamics of these sections closely resemble S1223 aerofoils. Before delving into the simulations of the rare wing-flap aerofoil, numerical results undergo validation using experimental data from an NLR flap aerofoil case, encompassing different flap angles at two distinct angles of attack was carried out. The increase in flap angle as increase in lift and drag is observed for a given angle of attack. The simulation methodology for the rare-wing-flap aerofoil case involves specific time durations before lifting the flap. During this period, drag and downforce values are determined as 330 N and 1800N, respectively. Following the flap lift, a noteworthy reduction in drag to 55 % and a decrease in downforce to 17 % are observed. This understanding is critical for making instantaneous decisions regarding the deployment of the Drag Reduction System (DRS) at specific speeds, thereby influencing the overall performance of the Formula 1 racing car. Hence, this work emphasizes the utilization of dynamic mesh motion methodology to predict the aerodynamic characteristics during the deployment of the DRS in a Formula 1 racing car.

Keywords: DRS, CFD, drag, downforce, dynamics mesh motion

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Authors: Jinan Fiaidhi, Sabah Mohammed, Petros Zezos

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Capsule endoscopy (CE) is an established noninvasive diagnostic modality in investigating small bowel disease. CE has a pivotal role in assessing patients with suspected bleeding or identifying evidence of active Crohn's disease in the small bowel. However, CE produces lengthy videos with at least eighty thousand frames, with a frequency rate of 2 frames per second. Gastroenterologists cannot dedicate 8 to 15 hours to reading the CE video frames to arrive at a diagnosis. This is why the issue of analyzing CE videos based on modern artificial intelligence techniques becomes a necessity. However, machine learning, including deep learning, has failed to report robust results because of the lack of large samples to train its neural nets. In this paper, we are describing a thick data approach that learns from a few anchor images. We are using sound datasets like KVASIR and CrohnIPI to filter candidate frames that include interesting anomalies in any CE video. We are identifying candidate frames based on feature extraction to provide representative measures of the anomaly, like the size of the anomaly and the color contrast compared to the image background, and later feed these features to a decision tree that can classify the candidate frames as having a condition like the Crohn's Disease. Our thick data approach reported accuracy of detecting Crohn's Disease based on the availability of ulcer areas at the candidate frames for KVASIR was 89.9% and for the CrohnIPI was 83.3%. We are continuing our research to fine-tune our approach by adding more thick data methods for enhancing diagnosis accuracy.

Keywords: thick data analytics, capsule endoscopy, Crohn’s disease, siamese neural network, decision tree

Procedia PDF Downloads 129

Authors: A. Miškinytė, A. Dėdelė

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Road traffic is one of the main sources of air pollution in urban areas associated with adverse effects on human health and environment. Nitrogen dioxide (NO2) is considered as traffic-related air pollutant, which concentrations tend to be higher near highways, along busy roads and in city centres and exceedances are mainly observed in air quality monitoring stations located close to traffic. Atmospheric dispersion models can be used to examine emissions from many various sources and to predict the concentration of pollutants emitted from these sources into the atmosphere. The study aim was to compare modelled concentrations of nitrogen dioxide using ADMS-Urban dispersion model with air quality monitoring network in cold and warm seasons in Kaunas city. Modelled average seasonal concentrations of nitrogen dioxide for 2011 year have been verified with automatic air quality monitoring data from two stations in the city. Traffic station is located near high traffic street in industrial district and background station far away from the main sources of nitrogen dioxide pollution. The modelling results showed that the highest nitrogen dioxide concentration was modelled and measured in station located near intensive traffic street, both in cold and warm seasons. Modelled and measured nitrogen dioxide concentration was respectively 25.7 and 25.2 µg/m3 in cold season and 15.5 and 17.7 µg/m3 in warm season. While the lowest modelled and measured NO2 concentration was determined in background monitoring station, respectively 12.2 and 13.3 µg/m3 in cold season and 6.1 and 7.6 µg/m3 in warm season. The difference between monitoring station located near high traffic street and background monitoring station showed that better agreement between modelled and measured NO2 concentration was observed at traffic monitoring station.

Keywords: air pollution, nitrogen dioxide, modelling, ADMS-Urban model

Procedia PDF Downloads 392

Authors: Chen Jun-Hong, He Pu, Tao Wen-Quan

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Proton exchange membrane fuel cell (PEMFC) is the most promising future energy source owing to its low operating temperature, high energy efficiency, high power density, and environmental friendliness. In this paper, a comprehensive PEMFC system control-oriented model is developed in the Matlab/Simulink environment, which includes the hydrogen supply subsystem, air supply subsystem, and thermal management subsystem. Besides, Improved Artificial Bee Colony (IABC) is used in the parameter identification of PEMFC semi-empirical equations, making the maximum relative error between simulation data and the experimental data less than 0.4%. Operation temperature is essential for PEMFC, both high and low temperatures are disadvantageous. In the thermal management subsystem, water pump and fan are both controlled with the PID controller to maintain the appreciate operation temperature of PEMFC for the requirements of safe and efficient operation. To improve the control effect further, fuzzy control is introduced to optimize the PID controller of the pump, and the Radial Basis Function (RBF) neural network is introduced to optimize the PID controller of the fan. The results demonstrate that Fuzzy-PID and RBF-PID can achieve a better control effect with 22.66% decrease in Integral Absolute Error Criterion (IAE) of T_st (Temperature of PEMFC) and 77.56% decrease in IAE of T_in (Temperature of inlet cooling water) compared with traditional PID. In the end, a novel thermal management structure is proposed, which uses the cooling air passing through the main radiator to continue cooling the secondary radiator. In this thermal management structure, the parasitic power dissipation can be reduced by 69.94%, and the control effect can be improved with a 52.88% decrease in IAE of T_in under the same controller.

Keywords: PEMFC system, parameter identification, temperature control, Fuzzy-PID, RBF-PID, parasitic power

Procedia PDF Downloads 64

Authors: Hussain Sajid, Jung-Hun Shin, Kum-Won Cho

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Image super-resolution is the most common computer vision problem with many important applications. Generative adversarial networks (GANs) have promoted remarkable advances in single-image super-resolution (SR) by recovering photo-realistic images. However, high memory requirements of GAN-based SR (mainly generators) lead to performance degradation and increased energy consumption, making it difficult to implement it onto resource-constricted devices. To relieve such a problem, In this paper, we introduce an optimized and highly efficient architecture for SR-GAN (generator) model by utilizing model compression techniques such as Knowledge Distillation and pruning, which work together to reduce the storage requirement of the model also increase in their performance. Our method begins with distilling the knowledge from a large pre-trained model to a lightweight model using different loss functions. Then, iterative weight pruning is applied to the distilled model to remove less significant weights based on their magnitude, resulting in a sparser network. Knowledge Distillation reduces the model size by 40%; pruning then reduces it further by 18%. To accelerate the learning process, we employ the Horovod framework for distributed training on a cluster of 2 nodes, each with 8 GPUs, resulting in improved training performance and faster convergence. Experimental results on various benchmarks demonstrate that the proposed compressed model significantly outperforms state-of-the-art methods in terms of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and image quality for x4 super-resolution tasks.

Keywords: single-image super-resolution, generative adversarial networks, knowledge distillation, pruning

Procedia PDF Downloads 65

Authors: K. Omkar, D. Nayan

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Rapid urbanization is one of the consequences of rapid population explosion, which has also led to massive increase in number of motorized vehicles essential for carrying out all activities needed for sustaining urban livelihood. With this increased use of motorized vehicles over the time there has also been an increase in number of accidents. Study of road network and geometric features are essential to tackle problems of road accidents in any district or town. The increase in road accidents is one of the burning issues in the present society. Records show that there is one death at every 3.7 minutes because of road accident. It has been found from the research that, accidents occur due to, mistakes of the driver (86%) followed by bad street condition (5%), mistake of pedestrian (4%), as well as technical and maintenance defects (1%). Here, case study of Ahmedabad, Gujarat is taken up where first road safety level is assessed considering various parameters. The study confined to accident characteristics of all types of vehicles. For deeper analysis, road safety index for various stretches in Ahmedabad was found out. Crash rate for same stretches was found out. Based on various parameters priority was decided so that which stretch should be look out first to minimize road accidents on that stretch and which stretch should look out last. The major findings of the study are that accident severity of Ahmedabad has increased, but accident fatality risk has decreased; thus there is need to undertake some traffic engineering measures or make some traffic rules that are strictly followed by traffic. From the above study and literature studied it is found that Ahmedabad is suffering from similar problem of accidents and injuries and deaths caused by them, after properly investigating the issue short-term and long-term solutions to minimize road accidents have been presented in this paper.

Keywords: accident severity index, accident fatality rate, accident fatality risk, accident risk, road safety index

Procedia PDF Downloads 123

Authors: Nguyen Tien Thanh, Günter Meon

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Precipitation plays a key role in water cycle, defining the local climatic conditions and in ecosystem. It is also an important input parameter for water resources management and hydrologic models. With spatial continuous data, a certainty of discharge predictions or other environmental factors is unquestionably better than without. This is, however, not always willingly available to acquire for a small basin, especially for coastal region in Vietnam due to a low network of meteorological stations (30 stations) on long coast of 3260 km2. Furthermore, available gridded precipitation datasets are not fine enough when applying to hydrologic models. Under conditions of global warming, an application of spatial interpolation methods is a crucial for the climate change impact studies to obtain the spatial continuous data. In recent research projects, although some methods can perform better than others do, no methods draw the best results for all cases. The objective of this paper therefore, is to investigate different spatial interpolation methods for daily precipitation over a small basin (approximately 400 km2) located in coastal region, Southern Vietnam and find out the most efficient interpolation method on this catchment. The five different interpolation methods consisting of cressman, ordinary kriging, regression kriging, dual kriging and inverse distance weighting have been applied to identify the best method for the area of study on the spatio-temporal scale (daily, 10 km x 10 km). A 30-year precipitation database was created and merged into available gridded datasets. Finally, observed changes in constructed precipitation were performed. The results demonstrate that the method of ordinary kriging interpolation is an effective approach to analyze the daily precipitation. The mixed trends of increasing and decreasing monthly, seasonal and annual precipitation have documented at significant levels.

Keywords: interpolation, precipitation, trend, vietnam

Procedia PDF Downloads 264

Authors: Yin-Chen Liu, Chih-Chun Wu, Mei-He Shih

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In this technology society, using ICT(Information and communications technology) to contact each other is very common. Interpersonal ICT communication maintains social support. Therefore, the study investigated the ICT communication between undergraduates and their parents, and gender differences were also detected. The sample size was 1,209 undergraduates, including 624(51.6%) males, 584(48.3%) females, and 1 gender unidentified. In the sample, 91.8% of the sample used phones to contact their fathers and 93.8% of them use phones to contact their mothers. 78.5% and 87.6% of the sample utilized LINE to contact their fathers and mothers respectively. As for Facebook, only 13.4% and 16.5% of the sample would use to contact their fathers and mothers respectively. Aforementioned results implied that the undergraduates nowadays use phone and LINE to contact their parents more common than Facebook. According to results from Pearson correlations, the more undergraduates refused to add their fathers as their Facebook friends, the more they refused to add their mothers as Facebook friends. The possible reasons for it could be that to distinguish different social network such as family and friends. Another possible reason could be avoiding parents’ controlling. It could be why the kids prefer to use phone and LINE to Facebook when contacting their parents. Result from Pearson correlations showed that the more undergraduates actively contact their fathers, the more they actively contact their mothers. On the other hand, the more their fathers actively contact them, the more their mothers actively contact them. Based on the results, this study encourages both parents and undergraduates to contact each other, for any contact between any two family members is associated with contact between other two family members. Obviously, the contact between family members is bidirectional. Future research might want to investigate if this bidirectional contact is associated with the family relation. For gender differences, results from the independent t-tests showed that compared to sons, daughters actively contacted their parents more. Maybe it is because parents keep saying that it is dangerous out there for their daughters, so they build up the habit for their daughters to contact them more. Results from paired sample t-tests showed that the undergraduates agreed that talking to mother on the phone had more satisfaction, felt more intimacy and supported than fathers.

Keywords: family ICT communication, parent-child ICT communication, FACEBOOK and LINE, gender differences

Procedia PDF Downloads 186

Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health-related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores to text, ranging from positive, neutral, and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing and tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial, and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced, and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process and substituting the Naive Bayes for a deep learning neural network model.

Keywords: sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model

Procedia PDF Downloads 81

Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: direct search, DFIG, equivalent circuit parameters, optimization

Procedia PDF Downloads 238

Authors: Nicoly Coelho, Eduardo Vieira Vilas Boas, Paulo Orestes Formigoni

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Faced with the remarkable developments in the various segments of modern engineering, provided by the increasing technological development, professionals of all educational areas need to overcome the difficulties generated due to the good understanding of those who are starting their academic journey. Aiming to overcome these difficulties, this article aims at an introduction to the basic study of numerical methods applied to fluid mechanics and thermodynamics, demonstrating the modeling and simulations with its substance, and a detailed explanation of the fundamental numerical solution for the use of finite difference method, using SCILAB, a free software easily accessible as it is free and can be used for any research center or university, anywhere, both in developed and developing countries. It is known that the Computational Fluid Dynamics (CFD) is a necessary tool for engineers and professionals who study fluid mechanics, however, the teaching of this area of knowledge in undergraduate programs faced some difficulties due to software costs and the degree of difficulty of mathematical problems involved in this way the matter is treated only in postgraduate courses. This work aims to bring the use of DFC low cost in teaching Transport Phenomena for graduation analyzing a small classic case of fundamental thermodynamics with Scilab® program. The study starts from the basic theory involving the equation the partial differential equation governing heat transfer problem, implies the need for mastery of students, discretization processes that include the basic principles of series expansion Taylor responsible for generating a system capable of convergence check equations using the concepts of Sassenfeld, finally coming to be solved by Gauss-Seidel method. In this work we demonstrated processes involving both simple problems solved manually, as well as the complex problems that required computer implementation, for which we use a small algorithm with less than 200 lines in Scilab® in heat transfer study of a heated plate in rectangular shape on four sides with different temperatures on either side, producing a two-dimensional transport with colored graphic simulation. With the spread of computer technology, numerous programs have emerged requiring great researcher programming skills. Thinking that this ability to program DFC is the main problem to be overcome, both by students and by researchers, we present in this article a hint of use of programs with less complex interface, thus enabling less difficulty in producing graphical modeling and simulation for DFC with an extension of the programming area of experience for undergraduates.

Keywords: numerical methods, finite difference method, heat transfer, Scilab

Procedia PDF Downloads 362

Authors: Anjali Kanagali, Astha Sinha

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Climate change is the greatest threat being faced by mankind in the 21st century. It no longer is merely an environmental, scientific or economic issue but is a humanitarian issue as well. Paris Agreement put great pressure on the businesses to reduce carbon emissions and mitigate the impact of climate change. However, the already increased climate variability and extreme weather are aggravating emergency humanitarian needs. According to the Intergovernmental Panel on Climate Change (IPCC), if efficient policy changes are not made in time to combat the climate change issues, the situation will deteriorate with an estimated global temperature rise of 4 degrees. The existing international network of Humanitarian system is not adequately structured to handle the projected natural disasters and climate change crisis. The 2030 Agenda which embraces the 17 Sustainable Development Goals (SGDs) discussed the relationship between the climate change and humanitarian assistance. The Humanitarian law aims to protect, amongst other things, ‘internally displaced persons’ which includes people displaced due to natural hazard related disasters engulfing the hazards of climate change. ‘Legal protection’ of displaced people to protect their rights is becoming a pressing need in such times. In this paper, attempts will be made to analyze the causes of the displacement, identify areas where the effect of the climate change is most likely to occur and to examine the character of forced displacement triggering population movement. We shall discuss the pressure on the Humanitarian system and assistance due to climate change issues and the need for vesting powers to the local communities or local government players to deal with the climate changes. We shall also discuss the possibility of setting up a new framework where non-state actors could be set up for climate change impact and its governance.

Keywords: humanitarian assistance to climate change, humanitarian crisis, internally displaced person, legal framework for climate migrants, non-state actors

Procedia PDF Downloads 301

Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

Procedia PDF Downloads 173