Search results for: atmospheric physics models
1976 Hydrodynamic and Sediment Transport Analysis of Computational Fluid Dynamics Designed Flow Regulating Liner (Smart Ditch)
Authors: Saman Mostafazadeh-Fard, Zohrab Samani, Kenneth Suazo
Abstract:
Agricultural ditch liners are used to prevent soil erosion and reduce seepage losses. This paper introduced an approach to validate a computational fluid dynamics (CFD) platform FLOW-3D code and its use to design a flow-regulating corrugated agricultural ditch liner system (Smart Ditch (SM)). Hydrodynamic and sediment transport analyses were performed on the proposed liner flow using the CFD platform FLOW-3D code. The code's hydrodynamic and scour and sediment transport models were calibrated and validated using lab data with an accuracy of 94 % and 95%, respectively. The code was then used to measure hydrodynamic parameters of sublayer turbulent intensity, kinetic energy, dissipation, and packed sediment mass normalized with respect to sublayer flow velocity. Sublayer turbulent intensity, kinetic energy, and dissipation in the SM flow were significantly higher than CR flow. An alternative corrugated liner was also designed, and sediment transport was measured and compared to SM and CR flows. Normalized packed sediment mass with respect to average sublayer flow velocity was 27.8 % lower in alternative flow compared to SM flow. CFD platform FLOW-3D code could effectively be used to design corrugated ditch liner systems and perform hydrodynamic and sediment transport analysis under various corrugation designs.Keywords: CFD, hydrodynamic, sediment transport, ditch, liner design
Procedia PDF Downloads 1161975 Empowering the Citizens: The Potential of Zimbabwean Library and Information Science Schools in Contributing towards Socio-Economic Transformation
Authors: Collence Takaingenhamo Chisita, Munyaradzi Shoko
Abstract:
Library and Information Science Schools play significant roles in socio–economic transformation but in most cases they are downplayed or overshadowed by other institutions, and professions. Currently Zimbabwe boasts of high literacy rate in Africa and this success would have been impossible without the contributions of library schools and related institutions. Libraries and librarians are at the epicentre of socio-economic development and their role cannot be downplayed. It is out of this context that the writer will explore the extent to which library schools are contributing towards socio-economic transformation, for example, human capital development and facilitating access to information. The writer will seek to explain and clarify how LIS schools are engaged in socio-economic transformation through supporting education and culture through community engagement. The paper will examine the LIS education models, for example, general education and Technical Vocational Education and Training (TVET) or Competency Based Education and Training (CBET). It will also seek to find out how LIS Schools are contributing to the information/knowledge economy through education, training and research. The writer will also seek to find out how LIS Education is responding to socio-economic and political dynamics in Zimbabwe amidst forces of globalisation and cultural identities. Furthermore, the writer will explore the extent to which LIS education can help to reposition Zimbabwe in the global knowledge economy. The author will examine how LIS schools integrate culture and technology.Keywords: development, information/knowledge economy, culture, empowerment, collaboration, globalisation
Procedia PDF Downloads 3131974 Batch Adsorption Studies for the Removal of Textile Dyes from Aqueous Solution on Three Different Pine Bark
Authors: B. Cheknane, F. Zermane
Abstract:
The main objective of the present study is the valorization of natural raw materials of plant origin for the treatment of textile industry wastewater. Selected bark was: maritime (MP), pinyon (PP) and Aleppo pine (AP) bark. The efficiency of these barks were tested for the removal of three dye; rhodamine B (RhB), Green Malachite (GM) and X Methyl Orange (MO). At the first time we focus to study the different parameters which can influence the adsorption processes such as: nature of the adsorbents, nature of the pollutants (dyes) and the effect of pH. Obtained results reveals that the speed adsorption is strongly influencing by the pH medium and the comparative study show that adsorption is favorable in the acidic medium with amount adsorbed of (Q=40mg/g) for rhodamine B and (Q=46mg/g) for orange methyl. Results of adsorption kinetics reveals that the molecules of GM are adsorbed better (Q=48mg/g) than the molecules of RhB (Q=46mg/g) and methyl orange (Q=18mg/g), with equilibrium time of 6 hours. The results of adsorption isotherms show clearly that the maritime pine bark is the most effective adsorbents with adsorbed amount of (QRhB=200mg/g) and (QMO=88mg/g) followed by pinyon pine (PP) with (QRhB=184mg/g) and (QMO=56mg/g) and finally Aleppo pine (AP) bark with (QRhB=131mg/g) and (QMO= 46mg/g). The different obtained isotherms were modeled using the Langmuir and Freundlich models and according to the adjustment coefficient values R2, the obtained isotherms are well represented by Freundlich model.Keywords: maritime pine bark (MP), pinyon pine bark (PP), Aleppo pine (AP) bark, adsorption, dyes
Procedia PDF Downloads 3141973 Student Debt Loans and Labor Market Outcomes: A Lesson in Unintended Consequences
Authors: Sun-Ki Choi
Abstract:
The U.S. student loan policy was initiated to improve the equality of educational opportunity and help low-income families to provide higher education opportunities for their children. However, with the increase in the average student loan amount, college graduates with student loans experience problems and restrictions in their early-career choices. This study examines the early career labor market choices of college graduates who obtained student loans to finance their higher education. In this study, National Survey of College Graduates (NSCG) data for 2017 and 2019 was used to estimate the effects of student loans on the employment status and current job wages of graduates with student loans. In the analysis, two groups of workers, those with student loans and those without loans, were compared. Using basic models and Mahalanobis distance matching, it was found that graduates who rely on student loans to finance their education are more likely to participate in the labor market than those who do not. Moreover, in entry-level jobs, graduates with student loans receive lower salaries than those without student loans. College graduates make job-related decisions based on their current and future wages and fringe benefits. Graduates with student loans tend to demonstrate risk-averse behaviors due to their financial restrictions. Thus, student loan debt creates inequity in the early-career labor market for college graduates. Furthermore, this study has implications for policymakers and researchers in terms of the student loan policy.Keywords: student loan, wage differential, unintended consequences, mahalanobis distance matching
Procedia PDF Downloads 1091972 Using Risk Management Indicators in Decision Tree Analysis
Authors: Adel Ali Elshaibani
Abstract:
Risk management indicators augment the reporting infrastructure, particularly for the board and senior management, to identify, monitor, and manage risks. This enhancement facilitates improved decision-making throughout the banking organization. Decision tree analysis is a tool that visually outlines potential outcomes, costs, and consequences of complex decisions. It is particularly beneficial for analyzing quantitative data and making decisions based on numerical values. By calculating the expected value of each outcome, decision tree analysis can help assess the best course of action. In the context of banking, decision tree analysis can assist lenders in evaluating a customer’s creditworthiness, thereby preventing losses. However, applying these tools in developing countries may face several limitations, such as data availability, lack of technological infrastructure and resources, lack of skilled professionals, cultural factors, and cost. Moreover, decision trees can create overly complex models that do not generalize well to new data, known as overfitting. They can also be sensitive to small changes in the data, which can result in different tree structures and can become computationally expensive when dealing with large datasets. In conclusion, while risk management indicators and decision tree analysis are beneficial for decision-making in banks, their effectiveness is contingent upon how they are implemented and utilized by the board of directors, especially in the context of developing countries. It’s important to consider these limitations when planning to implement these tools in developing countries.Keywords: risk management indicators, decision tree analysis, developing countries, board of directors, bank performance, risk management strategy, banking institutions
Procedia PDF Downloads 531971 A Study on the Waiting Time for the First Employment of Arts Graduates in Sri Lanka
Authors: Imali T. Jayamanne, K. P. Asoka Ramanayake
Abstract:
Transition from tertiary level education to employment is one of the challenges that many fresh university graduates face after graduation. The transition period or the waiting time to obtain the first employment varies with the socio-economic factors and the general characteristics of a graduate. Compared to other fields of study, Arts graduates in Sri Lanka, have to wait a long time to find their first employment. The objective of this study is to identify the determinants of the transition from higher education to employment of these graduates using survival models. The study is based on a survey that was conducted in the year 2016 on a stratified random sample of Arts graduates from Sri Lankan universities who had graduated in 2012. Among the 469 responses, 36 (8%) waiting times were interval censored and 13 (3%) were right censored. Waiting time for the first employment varied between zero to 51 months. Initially, the log-rank and the Gehan-Wilcoxon tests were performed to identify the significant factors. Gender, ethnicity, GCE Advanced level English grade, civil status, university, class received, degree type, sector of first employment, type of first employment and the educational qualifications required for the first employment were significant at 10%. The Cox proportional hazards model was fitted to model the waiting time for first employment with these significant factors. All factors, except ethnicity and type of employment were significant at 5%. However, since the proportional hazard assumption was violated, the lognormal Accelerated failure time (AFT) model was fitted to model the waiting time for the first employment. The same factors were significant in the AFT model as in Cox proportional model.Keywords: AFT model, first employment, proportional hazard, survey design, waiting time
Procedia PDF Downloads 3051970 Numerical Analysis of NOₓ Emission in Staged Combustion for the Optimization of Once-Through-Steam-Generators
Authors: Adrien Chatel, Ehsan Askari Mahvelati, Laurent Fitschy
Abstract:
Once-Through-Steam-Generators are commonly used in the oil-sand industry in the heavy fuel oil extraction process. They are composed of three main parts: the burner, the radiant and convective sections. Natural gas is burned through staged diffusive flames stabilized by the burner. The heat generated by the combustion is transferred to the water flowing through the piping system in the radiant and convective sections. The steam produced within the pipes is then directed to the ground to reduce the oil viscosity and allow its pumping. With the rapid development of the oil-sand industry, the number of OTSG in operation has increased as well as the associated emissions of environmental pollutants, especially the Nitrous Oxides (NOₓ). To limit the environmental degradation, various international environmental agencies have established regulations on the pollutant discharge and pushed to reduce the NOₓ release. To meet these constraints, OTSG constructors have to rely on more and more advanced tools to study and predict the NOₓ emission. With the increase of the computational resources, Computational Fluid Dynamics (CFD) has emerged as a flexible tool to analyze the combustion and pollutant formation process. Moreover, to optimize the burner operating condition regarding the NOx emission, field characterization and measurements are usually accomplished. However, these kinds of experimental campaigns are particularly time-consuming and sometimes even impossible for industrial plants with strict operation schedule constraints. Therefore, the application of CFD seems to be more adequate in order to provide guidelines on the NOₓ emission and reduction problem. In the present work, two different software are employed to simulate the combustion process in an OTSG, namely the commercial software ANSYS Fluent and the open source software OpenFOAM. RANS (Reynolds-Averaged Navier–Stokes) equations combined with the Eddy Dissipation Concept to model the combustion and closed by the k-epsilon model are solved. A mesh sensitivity analysis is performed to assess the independence of the solution on the mesh. In the first part, the results given by the two software are compared and confronted with experimental data as a mean to assess the numerical modelling. Flame temperatures and chemical composition are used as reference fields to perform this validation. Results show a fair agreement between experimental and numerical data. In the last part, OpenFOAM is employed to simulate several operating conditions, and an Emission Characteristic Map of the combustion system is generated. The sources of high NOₓ production inside the OTSG are pointed and correlated to the physics of the flow. CFD is, therefore, a useful tool for providing an insight into the NOₓ emission phenomena in OTSG. Sources of high NOₓ production can be identified, and operating conditions can be adjusted accordingly. With the help of RANS simulations, an Emission Characteristics Map can be produced and then be used as a guide for a field tune-up.Keywords: combustion, computational fluid dynamics, nitrous oxides emission, once-through-steam-generators
Procedia PDF Downloads 1071969 Effect of Class V Cavity Configuration and Loading Situation on the Stress Concentration
Authors: Jia-Yu Wu, Chih-Han Chang, Shu-Fen Chuang, Rong-Yang Lai
Abstract:
Objective: This study was to examine the stress distribution of tooth with different class V restorations under different loading situations and geometry by 3D finite element (FE) analysis. `Methods: A series of FE models of mandibular premolars containing class V cavities were constructed using micro-CT. The class V cavities were assigned as the combinations of different cavity depths x occlusal -gingival heights: 1x2, 1x4, 2x2, and 2x4 mm. Three alveolar bone loss conditions were examined: 0, 1, and 2 mm. 200 N force was exerted on the buccal cusp tip under various directions (vertical, V; obliquely 30° angled, O; oblique and parallel the individual occlusal cavity wall, P). A 3-D FE analysis was performed and the von-Mises stress was used to summarize the data of stress distribution and maximum stress. Results: The maximal stress did not vary in different alveolar bone heights. For each geometry, the maximal stress was found at bilateral corners of the cavity. The peak stress of restorations was significantly higher under load P compared to those under loads V and O while the latter two were similar. 2x2mm cavity exhibited significantly increased (2.88 fold) stress under load P compared to that under load V, followed by 1x2mm (2.11 fold), 2x4mm (1.98 fold) and 1x4mm (1.1fold). Conclusion: Load direction causes the greatest impact on the results of stress, while the effect of alveolar bone loss is minor. Load direction parallel to the cavity wall may enhance the stress concentration especially in deep and narrow class cavities.Keywords: class v restoration, finite element analysis, loading situation, stress
Procedia PDF Downloads 2391968 Emerging Cyber Threats and Cognitive Vulnerabilities: Cyberterrorism
Authors: Oludare Isaac Abiodun, Esther Omolara Abiodun
Abstract:
The purpose of this paper is to demonstrate that cyberterrorism is existing and poses a threat to computer security and national security. Nowadays, people have become excitedly dependent upon computers, phones, the Internet, and the Internet of things systems to share information, communicate, conduct a search, etc. However, these network systems are at risk from a different source that is known and unknown. These network systems risk being caused by some malicious individuals, groups, organizations, or governments, they take advantage of vulnerabilities in the computer system to hawk sensitive information from people, organizations, or governments. In doing so, they are engaging themselves in computer threats, crime, and terrorism, thereby making the use of computers insecure for others. The threat of cyberterrorism is of various forms and ranges from one country to another country. These threats include disrupting communications and information, stealing data, destroying data, leaking, and breaching data, interfering with messages and networks, and in some cases, demanding financial rewards for stolen data. Hence, this study identifies many ways that cyberterrorists utilize the Internet as a tool to advance their malicious mission, which negatively affects computer security and safety. One could identify causes for disparate anomaly behaviors and the theoretical, ideological, and current forms of the likelihood of cyberterrorism. Therefore, for a countermeasure, this paper proposes the use of previous and current computer security models as found in the literature to help in countering cyberterrorismKeywords: cyberterrorism, computer security, information, internet, terrorism, threat, digital forensic solution
Procedia PDF Downloads 911967 Approach for Updating a Digital Factory Model by Photogrammetry
Authors: R. Hellmuth, F. Wehner
Abstract:
Factory planning has the task of designing products, plants, processes, organization, areas, and the construction of a factory. The requirements for factory planning and the building of a factory have changed in recent years. Regular restructuring is becoming more important in order to maintain the competitiveness of a factory. Restrictions in new areas, shorter life cycles of product and production technology as well as a VUCA world (Volatility, Uncertainty, Complexity & Ambiguity) lead to more frequent restructuring measures within a factory. A digital factory model is the planning basis for rebuilding measures and becomes an indispensable tool. Short-term rescheduling can no longer be handled by on-site inspections and manual measurements. The tight time schedules require up-to-date planning models. Due to the high adaptation rate of factories described above, a methodology for rescheduling factories on the basis of a modern digital factory twin is conceived and designed for practical application in factory restructuring projects. The focus is on rebuild processes. The aim is to keep the planning basis (digital factory model) for conversions within a factory up to date. This requires the application of a methodology that reduces the deficits of existing approaches. The aim is to show how a digital factory model can be kept up to date during ongoing factory operation. A method based on photogrammetry technology is presented. The focus is on developing a simple and cost-effective solution to track the many changes that occur in a factory building during operation. The method is preceded by a hardware and software comparison to identify the most economical and fastest variant.Keywords: digital factory model, photogrammetry, factory planning, restructuring
Procedia PDF Downloads 1091966 Determination of Cohesive Zone Model’s Parameters Based On the Uniaxial Stress-Strain Curve
Authors: Y. J. Wang, C. Q. Ru
Abstract:
A key issue of cohesive zone models is how to determine the cohesive zone model (CZM) parameters based on real material test data. In this paper, uniaxial nominal stress-strain curve (SS curve) is used to determine two key parameters of a cohesive zone model: the maximum traction and the area under the curve of traction-separation law (TSL). To this end, the true SS curve is obtained based on the nominal SS curve, and the relationship between the nominal SS curve and TSL is derived based on an assumption that the stress for cracking should be the same in both CZM and the real material. In particular, the true SS curve after necking is derived from the nominal SS curve by taking the average of the power law extrapolation and the linear extrapolation, and a damage factor is introduced to offset the true stress reduction caused by the voids generated at the necking zone. The maximum traction of the TSL is equal to the maximum true stress calculated based on the damage factor at the end of hardening. In addition, a simple specimen is simulated by Abaqus/Standard to calculate the critical J-integral, and the fracture energy calculated by the critical J-integral represents the stored strain energy in the necking zone calculated by the true SS curve. Finally, the CZM parameters obtained by the present method are compared to those used in a previous related work for a simulation of the drop-weight tear test.Keywords: dynamic fracture, cohesive zone model, traction-separation law, stress-strain curve, J-integral
Procedia PDF Downloads 5071965 Design, Synthesis and Anti-Inflammatory Activity of Some Coumarin and Flavone Derivatives Containing 1,4 Dioxane Ring System
Authors: Asif Husain, Shah Alam Khan
Abstract:
Coumarins and flavones are oxygen containing heterocyclic compounds which are present in various biologically active compounds. Both the heterocyclic rings are associated with diverse biological actions, therefore considered as an important scaffold for the design of molecules of pharmaceutical interest. Aim: To synthesize and evaluate the in vivo anti-inflammatory activity of few coumrain and flavone derivatives containing 1,4 dioxane ring system. Materials and methods: Coumarin derivatives (3a-d) were synthesized by reacting 7,8 dihydroxy coumarin (2a) and its 4-methyl derivative (2b) with epichlorohydrin/ethylene dibromide. The flavone derivatives (10a-d) were prepared by using quercetin and 3,4 dihydroxy flavones. Compounds of both the series were also evaluated for their anti-inflammatory, analgesic activity and ulcerogenicity in animal models by reported methods. Results and Discussion: The structures of all newly synthesized compounds were confirmed with the help of IR, 1H NMR, 13C NMR and Mass spectral studies. Elemental analyses data for each element analyzed (C, H, N) was found to be within acceptable range of ±0.4 %. Flavone derivatives, but in particular quercetin containing 1,4 dioxane ring system (10d) showed better anti-inflammatory and analgesic activity along with reduced gastrointestinal toxicity as compared to other synthesized compounds. The results of anti-inflammatory and analgesic activities of both the series are comparable with the positive control, diclofenac. Conclusion: Compound 10d, a quercetin derivative, emerged as a lead molecule which exhibited potent anti-inflammatory and analgesic activity with significant reduced gastric toxicity.Keywords: analgesic, anti-inflammatory, 1, 4 dioxane, coumarin, flavone
Procedia PDF Downloads 3211964 Finite Element Modeling of Two-Phase Microstructure during Metal Cutting
Authors: Junior Nomani
Abstract:
This paper presents a novel approach to modelling the metal cutting of duplex stainless steels, a two-phase alloy regarded as a difficult-to-machine material. Calculation and control of shear strain and stresses during cutting are essential to achievement of ideal cutting conditions. Too low or too high leads to higher required cutting force or excessive heat generation causing premature tool wear failure. A 2D finite element cutting model was created based on electron backscatter diffraction (EBSD) data imagery of duplex microstructure. A mesh was generated using ‘object-oriented’ software OOF2 version V2.1.11, converting microstructural images to quadrilateral elements. A virtual workpiece was created on ABAQUS modelling software where a rigid body toolpiece advanced towards workpiece simulating chip formation, generating serrated edge chip formation cutting. Model results found calculated stress strain contour plots correlated well with similar finite element models tied with austenite stainless steel alloys. Virtual chip form profile is also similar compared experimental frozen machining chip samples. The output model data provides new insight description of strain behavior of two phase material on how it transitions from workpiece into the chip.Keywords: Duplex stainless steel, ABAQUS, OOF2, Chip formation
Procedia PDF Downloads 961963 Foodborne Pathogens in Different Types of Milk: From the Microbiome to Risk Assessment
Authors: Pasquali Frederique, Manfreda Chiara, Crippa Cecilia, Indio Valentina, Ianieri Adriana, De Cesare Alessandra
Abstract:
Microbiological hazards can be transmitted to humans through milk. In this study, we compared the microbiome composition and presence of foodborne pathogens in organic milk (n=6), organic hay milk (n=6), standard milk (n=6) and high-quality milk (n=6). The milk samples were collected during six samplings between December 2022 to January 2023 and between April and May 2024 to take into account seasonal variations. The 24 milk samples were submitted to DNA extraction and library preparation before shotgun sequencing on the Illumina HiScan™ SQ System platform. The total sequencing output was 600 GB. In all the milk samples, the phyla with the highest relative abundances were Pseudomonadota, Bacillota, Ascomycota, Actinomycetota and Apicomplexa, while the most represented genera were Pseudomonas, Streptococcus, Geotrichum, Acinetobacter and Babesia. The alpha and beta diversity indexes showed a clear separation between the microbiome of high-quality milk and those of the other milk types. Moreover, in the high-quality milk, the relative abundance of Staphylococcus (4.4%), Campylobacter (4.5%), Bacillus (2.5%), Enterococcus (2.4%), Klebsiella (1.3%) and Escherichia (0 .7%) was significantly higher in comparison to other types of milk. On the contrary, the relative abundance of Geotrichum (0.5%) was significantly lower. The microbiome results collected in this study showed significant differences in terms of the relative abundance of bacteria genera, including foodborne pathogen species. These results should be incorporated into risk assessment models tailored to different types of milk.Keywords: raw milk, foodborne pathogens, microbiome, risk assessment
Procedia PDF Downloads 171962 Anomaly Detection in Financial Markets Using Tucker Decomposition
Authors: Salma Krafessi
Abstract:
The financial markets have a multifaceted, intricate environment, and enormous volumes of data are produced every day. To find investment possibilities, possible fraudulent activity, and market oddities, accurate anomaly identification in this data is essential. Conventional methods for detecting anomalies frequently fail to capture the complex organization of financial data. In order to improve the identification of abnormalities in financial time series data, this study presents Tucker Decomposition as a reliable multi-way analysis approach. We start by gathering closing prices for the S&P 500 index across a number of decades. The information is converted to a three-dimensional tensor format, which contains internal characteristics and temporal sequences in a sliding window structure. The tensor is then broken down using Tucker Decomposition into a core tensor and matching factor matrices, allowing latent patterns and relationships in the data to be captured. A possible sign of abnormalities is the reconstruction error from Tucker's Decomposition. We are able to identify large deviations that indicate unusual behavior by setting a statistical threshold. A thorough examination that contrasts the Tucker-based method with traditional anomaly detection approaches validates our methodology. The outcomes demonstrate the superiority of Tucker's Decomposition in identifying intricate and subtle abnormalities that are otherwise missed. This work opens the door for more research into multi-way data analysis approaches across a range of disciplines and emphasizes the value of tensor-based methods in financial analysis.Keywords: tucker decomposition, financial markets, financial engineering, artificial intelligence, decomposition models
Procedia PDF Downloads 561961 Optimization Based Extreme Learning Machine for Watermarking of an Image in DWT Domain
Authors: RAM PAL SINGH, VIKASH CHAUDHARY, MONIKA VERMA
Abstract:
In this paper, we proposed the implementation of optimization based Extreme Learning Machine (ELM) for watermarking of B-channel of color image in discrete wavelet transform (DWT) domain. ELM, a regularization algorithm, works based on generalized single-hidden-layer feed-forward neural networks (SLFNs). However, hidden layer parameters, generally called feature mapping in context of ELM need not to be tuned every time. This paper shows the embedding and extraction processes of watermark with the help of ELM and results are compared with already used machine learning models for watermarking.Here, a cover image is divide into suitable numbers of non-overlapping blocks of required size and DWT is applied to each block to be transformed in low frequency sub-band domain. Basically, ELM gives a unified leaning platform with a feature mapping, that is, mapping between hidden layer and output layer of SLFNs, is tried for watermark embedding and extraction purpose in a cover image. Although ELM has widespread application right from binary classification, multiclass classification to regression and function estimation etc. Unlike SVM based algorithm which achieve suboptimal solution with high computational complexity, ELM can provide better generalization performance results with very small complexity. Efficacy of optimization method based ELM algorithm is measured by using quantitative and qualitative parameters on a watermarked image even though image is subjected to different types of geometrical and conventional attacks.Keywords: BER, DWT, extreme leaning machine (ELM), PSNR
Procedia PDF Downloads 3061960 Identifying Common Sports Injuries in Karate and Presenting a Model for Preventing Identified Injuries (A Case Study of East Azerbaijan, Iranian Karatekas)
Authors: Nadia Zahra Karimi Khiavi, Amir Ghiami Rad
Abstract:
Due to the high likelihood of injuries in karate, karatekas' injuries warrant special treatment. This study explores the prevalence of karate injuries in East Azerbaijan, Iran and provides a model for karatekas to use in the prevention of such injuries. This study employs a descriptive approach. Male and female participants with a brown belt or above in either control or non-control styles in East Azerbaijan province are included in the study's statistical population. A statistical sample size of 100 people was computed using the tools employed (smartpls), and the samples were drawn at random from all clubs in the province with the assistance of the Karate Board in order to give a model for the prevention of karate injuries. Information was gathered by means of a survey that made use of the Standard Questionnaire for Australian Sports Medicine Injury Reports. The information is presented in the form of tables and samples, and descriptive statistics were used to organise and summarise the data. Control and non-control independent t-tests were conducted using SPSS version 20, and structural equation modelling (pls) was utilised for injury prevention modelling at a 0.05 level of significance. The results showed that the most common areas of injury among the control groups were the upper limbs (46.15%), lower limbs (34.61%), trunk (15.38%), and head and neck (3.84%). The most common types of injuries were broken bones (34.61%), sprain or strain (23.13%), bruising and contusions (23.13%), trauma to the face and mouth (11.53%), and damage to the nerves (69.69%). Uncontrolled committees are most likely to sustain injuries to the head and neck (33.33%), trunk (25.92%), upper limbs (22.22%), and lower limbs (18.51%). The most common injuries were to the mouth and face (33.33%), dislocations and fractures (22.22%), aspirin and strain (22.22%), bruises and contusions (18.51%), and nerves (70%), in that order. Among those who practice control kata, injuries to the upper limb account for 45.83%, the lower limb for 41.666%, the trunk for 8.33%, and the head and neck for 4.166%. The most common types of injuries are dislocations and fractures (41.66 per cent), aspirin and strain (29.16 per cent), bruising and bruises (16.66 per cent), and nerves (12.5%). Injuries to the face and mouth were not reported among those practising the control kata. By far, the most common sites of injury for those practising uncontrolled kata were the lower limb (43.74%), upper limb (39.13%), trunk (13.14%), and head and neck (4.34%). The most common types of injuries were dislocations and fractures (34.82%), aspirin and strain (26.08%), bruises and contusions (21.73%), mouth and face (13.14%), and nerves. Teaching the concepts of cooling and warming (0.591) and enhancing the degree of safety in the sports environment (0.413) were shown to play the most essential roles in reducing sports injuries among karate practitioners of controlling and uncontrolled styles, respectively. Use of common sports gear (0.390), Modification of training programme principles (0.341), Formulation of an effective diet plan for athletes (0.284), Evaluation of athletes' physical anatomy, physiology, chemistry, and physics (0.247).Keywords: sports injuries, karate, prevention, cooling and warming
Procedia PDF Downloads 941959 Cross- Cultural Cooperation and Innovation: An Exploration of Chinese Foreign Direct Investment in Europe
Authors: Yongsheng Guo, Shuchao Li
Abstract:
This study explores Chinese foreign direct investment (FDI) in Europe and the cross-cultural cooperation between Chinese and European managers. The aim of this research is to shed light on the phenomenon of investments in developed countries from an emerging market and to gain insights into the cooperation process. A grounded theory approach is adopted, and 46 semi-structured interviews were conducted with 10 case companies in Germany and 13 case companies in the UK. Grounded theory models are developed from primary data and interview quotes are used to support the themes. The interviewees perceived differences between the two parties in cultural traits, management concepts, knowledge structure and resource endowment between the two parties. Chinese and European partners can take advantage of different resources and cooperate in innovative ways to improve corporate performance. Moreover, both parties appreciate different ethical and cultural characteristics and complement each other to develop a combined organizational culture. This study proposes an ethical and cultural diversity theory in international management arguing that a team with diversified values and behaviors may be more excited and motivated. This study suggests that “resource complement” and “cross-cultural cooperation” might be an advantage for international investment. Firms are encouraged to open their minds and cooperate with partners with different resources and cultures. The authorities may review the FDI policies to reduce social and political barriers.Keywords: cross-culture, FDI, cooperation, innovation, China, Europe
Procedia PDF Downloads 921958 Business Education and Passion: The Place of Amore, Consciousness, Discipline, and Commitment as Holonomic Constructs in Pedagogy, A Conceptual Exploration
Authors: Jennifer K. Bowerman, Rhonda L. Reich
Abstract:
The purpose of this paper is to explore the concepts ACDC (Amore, Consciousness, Discipline, and Commitment) which the authors first discovered as a philosophy and framework for recruitment and organizational development in a successful start-up tech company in Brazil. This paper represents an exploration of these concepts as a potential pedagogical foundation for undergraduate business education in the classroom. It explores whether their application has potential to build emotional and practical resilience in the face of constant organizational and societal change. Derived from Holonomy this paper explains the concepts and develops a narrative around how change influences the operation of organizations. Using examples from leading edge organizational theorists, it explains why a different educational approach grounded in ACDC concepts may not only have relevance for the working world, but also for undergraduates about to enter that world. The authors propose that in the global context of constant change, it makes sense to develop an approach to education, particularly business education, beyond cognitive knowledge, models and tools, in such a way that emotional and practical resilience and creative thinking may be developed. Using the classroom as an opportunity to explore these concepts, and aligning personal passion with the necessary discipline and commitment, may provide students with a greater sense of their own worth and potential as they venture into their ever-changing futures.Keywords: ACDC, holonomic thinking, organizational learning, organizational change, business pedagogy
Procedia PDF Downloads 2351957 Python Implementation for S1000D Applicability Depended Processing Model - SALERNO
Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky
Abstract:
The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.Keywords: aeronautics, big data, data processing, machine learning, S1000D
Procedia PDF Downloads 1381956 Modeling Fertility and Production of Hazelnut Cultivars through the Artificial Neural Network under Climate Change of Karaj
Authors: Marziyeh Khavari
Abstract:
In recent decades, climate change, global warming, and the growing population worldwide face some challenges, such as increasing food consumption and shortage of resources. Assessing how climate change could disturb crops, especially hazelnut production, seems crucial for sustainable agriculture production. For hazelnut cultivation in the mid-warm condition, such as in Iran, here we present an investigation of climate parameters and how much they are effective on fertility and nut production of hazelnut trees. Therefore, the climate change of the northern zones in Iran has investigated (1960-2017) and was reached an uptrend in temperature. Furthermore, the descriptive analysis performed on six cultivars during seven years shows how this small-scale survey could demonstrate the effects of climate change on hazelnut production and stability. Results showed that some climate parameters are more significant on nut production, such as solar radiation, soil temperature, relative humidity, and precipitation. Moreover, some cultivars have produced more stable production, for instance, Negret and Segorbe, while the Mervill de Boliver recorded the most variation during the study. Another aspect that needs to be met is training and predicting an actual model to simulate nut production through a neural network and linear regression simulation. The study developed and estimated the ANN model's generalization capability with different criteria such as RMSE, SSE, and accuracy factors for dependent and independent variables (environmental and yield traits). The models were trained and tested while the accuracy of the model is proper to predict hazelnut production under fluctuations in weather parameters.Keywords: climate change, neural network, hazelnut, global warming
Procedia PDF Downloads 1241955 Comparing Machine Learning Estimation of Fuel Consumption of Heavy-Duty Vehicles
Authors: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi
Abstract:
Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing
Procedia PDF Downloads 1741954 Review on Crew Scheduling of Bus Transit: A Case Study in Kolkata
Authors: Sapan Tiwari, Namrata Ghosh
Abstract:
In urban mass transit, crew scheduling always plays a significant role. It deals with the formulation of work timetables for its staff so that an organization can meet the demand for its products or services. The efficient schedules of a specified timetable have an enormous impact on staff demand. It implies that an urban mass transit company's financial outcomes are strongly associated with planning operations in the region. The research aims to demonstrate the state of the crew scheduling studies and its practical implementation in mass transit businesses in metropolitan areas. First, there is a short overview of past studies in the field. Subsequently, the restrictions and problems with crew scheduling and some models, which have been developed to solve the related issues with their mathematical formulation, are defined. The comments are completed by a description of the solution opportunities provided by computer-aided scheduling program systems for operational use and exposures from urban mass transit organizations. Furthermore, Bus scheduling is performed using the Hungarian technique of problem-solving tasks and mathematical modeling. Afterward, the crew scheduling problem, which consists of developing duties using predefined tasks with set start and end times and places, is resolved. Each duty has to comply with a set line of work. The objective is to minimize a mixture of fixed expenses (number of duties) and varying costs. After the optimization of cost, the outcome of the research is that the same frequency can be provided with fewer buses and less workforce.Keywords: crew scheduling, duty, optimization of cost, urban mass transit
Procedia PDF Downloads 1431953 Understanding the Linkages of Human Development and Fertility Change in Districts of Uttar Pradesh
Authors: Mamta Rajbhar, Sanjay K. Mohanty
Abstract:
India's progress in achieving replacement level of fertility is largely contingent on fertility reduction in the state of Uttar Pradesh as it accounts 17% of India's population with a low level of development. Though the TFR in the state has declined from 5.1 in 1991 to 3.4 by 2011, it conceals large differences in fertility level across districts. Using data from multiple sources this paper tests the hypothesis that the improvement in human development significantly reduces the fertility levels in districts of Uttar Pradesh. The unit of analyses is district, and fertility estimates are derived using the reverse survival method(RSM) while human development indices(HDI) are are estimated using uniform methodology adopted by UNDP for three period. The correlation and linear regression models are used to examine the relationship of fertility change and human development indices across districts. Result show the large variation and significant change in fertility level among the districts of Uttar Pradesh. During 1991-2011, eight districts had experienced a decline of TFR by 10-20%, 30 districts by 20-30% and 32 districts had experienced decline of more than 30%. On human development aspect, 17 districts recorded increase of more than 0.170 in HDI, 18 districts in the range of 0.150-0.170, 29 districts between 0.125-0.150 and six districts in the range of 0.1-0.125 during 1991-2011. Study shows significant negative relationship between HDI and TFR. HDI alone explains 70% variation in TFR. Also, the regression coefficient of TFR and HDI has become stronger over time; from -0.524 in 1991, -0.7477 by 2001 and -0.7181 by 2010. The regression analyses indicate that 0.1 point increase in HDI value will lead to 0.78 point decline in TFR. The HDI alone explains 70% variation in TFR. Improving the HDI will certainly reduce the fertility level in the districts.Keywords: Fertility, HDI, Uttar Pradesh
Procedia PDF Downloads 2431952 Case Study: Optimization of Contractor’s Financing through Allocation of Subcontractors
Authors: Helen S. Ghali, Engy Serag, A. Samer Ezeldin
Abstract:
In many countries, the construction industry relies heavily on outsourcing models in executing their projects and expanding their businesses to fit in the diverse market. Such extensive integration of subcontractors is becoming an influential factor in contractor’s cash flow management. Accordingly, subcontractors’ financial terms are important phenomena and pivotal components for the well-being of the contractor’s cash flow. The aim of this research is to study the contractor’s cash flow with respect to the owner and subcontractor’s payment management plans, considering variable advance payment, payment frequency, and lag and retention policies. The model is developed to provide contractors with a decision support tool that can assist in selecting the optimum subcontracting plan to minimize the contractor’s financing limits and optimize the profit values. The model is built using Microsoft Excel VBA coding, and the genetic algorithm is utilized as the optimization tool. Three objective functions are investigated, which are minimizing the highest negative overdraft value, minimizing the net present worth of overdraft, and maximizing the project net profit. The model is validated on a full-scale project which includes both self-performed and subcontracted work packages. The results show potential outputs in optimizing the contractor’s negative cash flow values and, in the meantime, assisting contractors in selecting suitable subcontractors to achieve the objective function.Keywords: cash flow optimization, payment plan, procurement management, subcontracting plan
Procedia PDF Downloads 1241951 Facilitation of Digital Culture and Creativity through an Ideation Strategy: A Case Study with an Incumbent Automotive Manufacturer
Authors: K. Ö. Kartal, L. Maul, M. Hägele
Abstract:
With the development of new technologies come additional opportunities for the founding of companies and new markets to be created. The barriers to entry are lowered and technology makes old business models obsolete. Incumbent companies have to be adaptable to this quickly changing environment. They have to start the process of digital maturation and they have to be able to adapt quickly to new and drastic changes that might arise. One of the biggest barriers for organizations in order to do so is their culture. This paper shows the core elements of a corporate culture that supports the process of digital maturation in incumbent organizations. Furthermore, it is explored how ideation and innovation can be used in a strategy in order to facilitate these core elements of culture that promote digital maturity. Focus areas are identified for the design of ideation strategies, with the aim to make the facilitation and incitation process more effective, short to long term. Therefore, one in-depth case study is conducted with data collection from interviews, observation, document review and surveys. The findings indicate that digital maturity is connected to cultural shift and 11 relevant elements of digital culture are identified which have to be considered. Based on these 11 core elements, five focus areas that need to be regarded in the design of a strategy that uses ideation and innovation to facilitate the cultural shift are identified. These are: Focus topics, rewards and communication, structure and frequency, regions and new online formats.Keywords: digital transformation, innovation management, ideation strategy, creativity culture, change
Procedia PDF Downloads 1851950 A Conceptual Model of Social Entrepreneurial Intention Based on the Social Cognitive Career Theory
Authors: Anh T. P. Tran, Harald Von Korflesch
Abstract:
Entrepreneurial intention play a major role in entrepreneurship academia and practice. The spectrum ranges from the first model of the so-called Entrepreneurial Event, then the Theory of Planned Behavior, the Theory of Planned Behavior Entrepreneurial Model, and the Social Cognitive Career Theory to some typical empirical studies with more or less diverse results. However, little is known so far about the intentions of entrepreneurs in the social areas of venture creation. It is surprising that, since social entrepreneurship is an emerging field with growing importance. Currently, all around the world, there is a big challenge with a lot of urgent soaring social and environmental problems such as poor households, people with disabilities, HIV/AIDS infected people, the lonely elderly, or neglected children, some of them even actual in the Western countries. In addition, the already existing literature on entrepreneurial intentions demonstrates a high level of theoretical diversity in general, especially the missing link to the social dimension of entrepreneurship. Seeking to fill the mentioned gaps in the social entrepreneurial intentions literature, this paper proposes a conceptual model of social entrepreneurial intentions based on the Social Cognitive Career Theory with two main factors influencing entrepreneurial intentions namely self-efficacy and outcome expectation. Moreover, motives, goals and plans do not arise from empty nothingness, but are shaped by interacting with the environment. Hence, personalities (i.e., agreeableness, conscientiousness, extraversion, neuroticism, openness) as well as contextual factors (e.g., role models, education, and perceived support) are also considered as the antecedents of social entrepreneurship intentions.Keywords: entrepreneurial intention, social cognitive career theory, social entrepreneurial intention, social entrepreneurship
Procedia PDF Downloads 4691949 Monte Carlo Estimation of Heteroscedasticity and Periodicity Effects in a Panel Data Regression Model
Authors: Nureni O. Adeboye, Dawud A. Agunbiade
Abstract:
This research attempts to investigate the effects of heteroscedasticity and periodicity in a Panel Data Regression Model (PDRM) by extending previous works on balanced panel data estimation within the context of fitting PDRM for Banks audit fee. The estimation of such model was achieved through the derivation of Joint Lagrange Multiplier (LM) test for homoscedasticity and zero-serial correlation, a conditional LM test for zero serial correlation given heteroscedasticity of varying degrees as well as conditional LM test for homoscedasticity given first order positive serial correlation via a two-way error component model. Monte Carlo simulations were carried out for 81 different variations, of which its design assumed a uniform distribution under a linear heteroscedasticity function. Each of the variation was iterated 1000 times and the assessment of the three estimators considered are based on Variance, Absolute bias (ABIAS), Mean square error (MSE) and the Root Mean Square (RMSE) of parameters estimates. Eighteen different models at different specified conditions were fitted, and the best-fitted model is that of within estimator when heteroscedasticity is severe at either zero or positive serial correlation value. LM test results showed that the tests have good size and power as all the three tests are significant at 5% for the specified linear form of heteroscedasticity function which established the facts that Banks operations are severely heteroscedastic in nature with little or no periodicity effects.Keywords: audit fee lagrange multiplier test, heteroscedasticity, lagrange multiplier test, Monte-Carlo scheme, periodicity
Procedia PDF Downloads 1371948 Estimation of Bio-Kinetic Coefficients for Treatment of Brewery Wastewater
Authors: Abimbola M. Enitan, J. Adeyemo
Abstract:
Anaerobic modeling is a useful tool to describe and simulate the condition and behaviour of anaerobic treatment units for better effluent quality and biogas generation. The present investigation deals with the anaerobic treatment of brewery wastewater with varying organic loads. The chemical oxygen demand (COD) and total suspended solids (TSS) of the influent and effluent of the bioreactor were determined at various retention times to generate data for kinetic coefficients. The bio-kinetic coefficients in the modified Stover–Kincannon kinetic and methane generation models were determined to study the performance of anaerobic digestion process. At steady-state, the determination of the kinetic coefficient (K), the endogenous decay coefficient (Kd), the maximum growth rate of microorganisms (µmax), the growth yield coefficient (Y), ultimate methane yield (Bo), maximum utilization rate constant Umax and the saturation constant (KB) in the model were calculated to be 0.046 g/g COD, 0.083 (dˉ¹), 0.117 (d-¹), 0.357 g/g, 0.516 (L CH4/gCODadded), 18.51 (g/L/day) and 13.64 (g/L/day) respectively. The outcome of this study will help in simulation of anaerobic model to predict usable methane and good effluent quality during the treatment of industrial wastewater. Thus, this will protect the environment, conserve natural resources, saves time and reduce cost incur by the industries for the discharge of untreated or partially treated wastewater. It will also contribute to a sustainable long-term clean development mechanism for the optimization of the methane produced from anaerobic degradation of waste in a close system.Keywords: brewery wastewater, methane generation model, environment, anaerobic modeling
Procedia PDF Downloads 2591947 Patient Service Improvement in Public Emergency Department Using Discrete Event Simulation
Authors: Dana Mohammed, Fatemah Abdullah, Hawraa Ali, Najat Al-Shaer, Rawan Al-Awadhi, , Magdy Helal
Abstract:
We study the patient service performance at the emergency department of a major Kuwaiti public hospital, using discrete simulation and lean concepts. In addition to the common problems in such health care systems (over crowdedness, facilities planning and usage, scheduling and staffing, capacity planning) the emergency department suffered from several cultural and patient behavioural issues. Those contributed significantly to the system problems and constituted major obstacles in maintaining the performance in control. This led to overly long waiting times and the potential of delaying providing help to critical cases. We utilized the visual management tools to mitigate the impact of the patients’ behaviours and attitudes and improve the logistics inside the system. In addition a proposal is made to automate the date collection and communication within the department using RFID-based barcoding system. Discrete event simulation models were developed as decision support systems; to study the operational problems and assess achieved improvements. The simulation analysis resulted in cutting the patient delays to about 35% of their current values by reallocating and rescheduling the medical staff. Combined with the application of the visual management concepts, this provided the basis to improving patient service without any major investments.Keywords: simulation, visual management, health care system, patient
Procedia PDF Downloads 466