Search results for: dynamic multi-objective optimization

Authors: Melissa Dickinson

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In the context of intense global competitiveness and urban transformations, today’s cities are faced with enormous challenges. There is increasing pressure among cities and regions to respond promptly and efficiently to fierce market progressions, to offer a competitive advantage, higher flexibility, and to be pro-active in creating future markets. Consequently, competition among cities and regions within the dynamics of a worldwide spatial economic system is growing fiercer, amplifying the importance of intangible capital in shaping the competitive and dynamic economic performance of organisations and firms. Accordingly, this study addresses how intangible capital influences urban economic development within an urban environment. Despite substantial research on the economic, and strategic determinants of urban economic development this multidimensional phenomenon remains to be one of the greatest challenges for economic geographers. The research provides a unique contribution, exploring intangible capital through the lenses of entrepreneurial capital and social-network capital. Drawing on business surveys and in-depth interviews with key stakeholders in the case of the three UK Core Cities Birmingham, Bristol and Cardiff. This paper critically considers how entrepreneurial capital and social-network capital is a crucial source of competitiveness and urban economic development. This paper deals with questions concerning the complexity of operationalizing ‘network capital’ in different urban settings and the challenges that reside in characterising its effects. The paper will highlight the role of institutions in facilitating urban economic development. Particular emphasis will be placed on exploring the roles formal and informal institutions have in delivering, supporting and nurturing entrepreneurial capital and social-network capital, to facilitate urban economic development. Discussions will then consider how institutions moderate and contribute to the economic development of urban areas, to provide implications in terms of future policy formulation in the context of large and medium sized cities.

Keywords: urban economic development, network capital, entrepreneurialism, institutions

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Authors: Felipe Henao, Yeny Rodriguez, Juan P. Viteri, Isaac Dyner

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Colombia is rich in natural resources and greatly focuses on the exploitation of water for hydroelectricity purposes. Alternative cleaner energy sources, such as solar and wind power, have been largely neglected despite: a) its abundance, b) the complementarities between hydro, solar and wind power, and c) the cost competitiveness of renewable technologies. The current limited mix of energy sources creates considerable weaknesses for the system, particularly when facing extreme dry weather conditions, such as El Niño event. In the past, El Niño have exposed the truly consequences of a system heavily dependent on hydropower, i.e. loss of power supply, high energy production costs, and loss of overall competitiveness for the country. Nonetheless, it is expected that the participation of hydroelectricity will increase in the near future. In this context, this paper proposes a stochastic lineal programming model to optimize the insertion of renewable energy systems (RES) into the Colombian electricity sector. The model considers cost-based generation competition between traditional energy technologies and alternative RES. This work evaluates the financial, environmental, and technical implications of different combinations of technologies. Various scenarios regarding the future evolution of costs of the technologies are considered to conduct sensitivity analysis of the solutions – to assess the extent of the participation of the RES in the Colombian power sector. Optimization results indicate that, even in the worst case scenario, where costs remain constant, the Colombian power sector should diversify its portfolio of technologies and invest strongly in solar and wind power technologies. The diversification through RES will contribute to make the system less vulnerable to extreme weather conditions, reduce the overall system costs, cut CO2 emissions, and decrease the chances of having national blackout events in the future. In contrast, the business as usual scenario indicates that the system will turn more costly and less reliable.

Keywords: energy policy and planning, stochastic programming, sustainable development, water management

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Authors: Bogale Tadesse, Krutik Parikh, Ndagha Mkandawire, Boris Albijanic, Nimal Subasinghe

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It is well established that the floatability and selectivity of mineral particles are highly dependent on the particle size. Generally, a particle size of 10 micron is considered as the critical size below which both flotation selectivity and recovery decline sharply. It is widely accepted that the majority of ultrafine particles, including highly liberated valuable minerals, will be lost in tailings during a conventional flotation process. This is highly undesirable particularly in the processing of finely disseminated complex and refractory ores where there is a requirement for fine grinding in order to liberate the valuable minerals. In addition, the continuing decline in ore grade worldwide necessitates intensive processing of low grade mineral deposits. Recent advances in comminution allow the economic grinding of particles down to 10 micron sizes to enhance the probability of liberating locked minerals from low grade ores. Thus, it is timely that the flotation of fine and ultrafine particles is improved in order to reduce the amount of valuable minerals lost as slimes. It is believed that the use of fine bubbles in flotation increases the bubble-particle collision efficiency and hence the flotation performance. Electroflotation, where bubbles are generated by the electrolytic breakdown of water to produce oxygen and hydrogen gases, leads to the formation of extremely finely dispersed gas bubbles with dimensions varying from 5 to 95 micron. The sizes of bubbles generated by this method are significantly smaller than those found in conventional flotation (> 600 micron). In this study, microbubbles generated by electrolysis of water were injected into a bench top flotation cell to assess the performance electroflotation in enhancing the flotation of fine and ultrafine pyrite particles of sizes ranging from 5 to 53 micron. The design of the cell and the results from optimization of the process variables such as current density, pH, percent solid and particle size will be presented at this conference.

Keywords: electroflotation, fine bubbles, pyrite, ultrafine particles

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Authors: Azad Mohammed Ali Saber, Lanja Saeed Omer

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The present study deals with numerical method (FE) and experimental investigations on the vibration behavior of carbon fiber-polyester laminated plates. Finite element simulation is done using APDL (Ansys Parametric Design Language) macro codes software version 19. Solid185 layered structural element, including eight nodes, is adopted in this analysis. The experimental work is carried out using (Hand Layup method) to fabricate different layers and orientation angles of composite laminate plates. Symmetric samples include four layers (00/900)s and six layers (00/900/00)s, (00/00/900)s. Antisymmetric samples include one layer (00), (450), two layers (00/900), (-450/450), three layers (00/900/00), four layers (00/900)2, (-450/450)2, five layers (00/900)2.5, and six layers (00/900)3, (-450/450)3. An experimental investigation is carried out using a modal analysis technique with a Fast Fourier Transform Analyzer (FFT), Pulse platform, impact hammer, and accelerometer to obtain the frequency response functions. The influences of different parameters such as the number of layers, aspect ratio, modulus ratio, ply orientation, and different boundary conditions on the dynamic behavior of the CFRPs are studied, where the 1st, 2nd, and 3rd natural frequencies are observed to be the minimum for cantilever boundary condition (CFFF) and the maximum for full clamped boundary condition (CCCC). Experimental results show that the natural frequencies of laminated plates are significantly reliant on the type of boundary conditions due to the restraint effect at the edges. Good agreement is achieved among the finite element and experimental results. All results indicate that any increase in aspect ratio causes a decrease in the natural frequency of the CFRPs plate, while any increase in the modulus ratio or number of layers causes an increase in the fundamental natural frequency of vibration.

Keywords: vibration, composite materials, finite element, APDL ANSYS

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Authors: Wayne DeFehr

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This study is rooted in a pedagogical approach that emphasizes student engagement as fundamental to meaningful learning in the classroom. This approach creates a paradigmatic shift, from a teaching practice that reinforces the teacher’s central authority to a practice that disperses that authority among the students in the classroom through networks that they themselves develop. The methodology of this study about creating optimal conditions for learning in the classroom includes providing a conceptual framework within which the students work, as well as providing clearly stated expectations for work standards, content quality, group methodology, and learning outcomes. These learning conditions are nurtured in a variety of ways. First, nearly every class includes a lecture from the professor with key concepts that students need in order to complete their work successfully. Secondly, students build on this scholarly material by forming their own networks, where students face each other and engage with each other in order to collaborate their way to solving a particular problem relating to the course content. Thirdly, students are given short, medium, and long-term goals. Short term goals relate to the week’s topic and involve workshopping particular issues relating to that stage of the course. The medium-term goals involve students submitting term assignments that are evaluated according to a well-defined rubric. And finally, long-term goals are achieved by creating a capstone project, which is celebrated and shared with classmates and interested friends on the final day of the course. The essential conclusions of the study are drawn from courses that focus on video game narrative. Enthusiastic student engagement is created not only with the dynamic energy and expertise of the instructor, but also with the inter-dependence of the students on each other to build knowledge, acquire skills, and achieve successful results.

Keywords: collaboration, education, learning networks, video games

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Authors: Burcu Doymus, Fatma N. Kok, Sakip Onder

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Titanium and titanium-based materials are commonly used to replace or regenerate the injured or lost tissues because of accidents or illnesses. Hospital infections and strong bond formation at the implant-tissue interface are directly affecting the success of the implantation as weak bonding with the native tissue and hospital infections lead to revision surgery. The purpose of the presented study is to modify the surface of the titanium substrates with nano/microspheres for local drug delivery and to prevent hospital infections. Firstly, titanium surfaces were silanized with APTES (3-Triethoxysilylpropylamine) following the negatively charged oxide layer formation. Then characterization studies using Scanning Electron Microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) were done on the modified surfaces. Secondly, microspheres/nanospheres were prepared with chitosan that is a natural polymer and having valuable properties such as non-toxicity, high biocompatibility, low allergen city and biodegradability for biomedical applications. Antibiotic (ciprofloxacin) loaded micro/nanospheres have been fabricated using emulsion cross-linking method and have been immobilized onto the titanium surfaces with different immobilization techniques such as covalent bond and entrapment. Optimization studies on size and drug loading capacities of micro/nanospheres were conducted before the immobilization process. Light microscopy and SEM were used to visualize and measure the size of the produced micro/nanospheres. Loaded and released drug amounts were determined by using UV- spectrophotometer at 278 nm. Finally, SEM analysis and drug release studies on the micro/nanospheres coated Ti surfaces were done. As a conclusion, it was shown that micro/nanospheres were immobilized onto the surfaces successfully and drug release from these surfaces was in a controlled manner. Moreover, the density of the micro/nanospheres after the drug release studies was higher on the surfaces where the entrapment technique was used for immobilization. Acknowledgement: This work is financially supported by The Scientific and Technological Research Council Of Turkey (Project # 217M220)

Keywords: chitosan, controlled drug release, nanosphere, nosocomial infections, titanium

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Authors: Aibek Kukpayev, Dhawal Shah

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Combustion of sour fuels containing high amount of sulfur leads to the formation of sulfur oxides, which adversely harm the environment and has a negative impact on human health. Considering this, several legislations have been imposed to bring down the sulfur content in fuel to less than 10 ppm. In recent years, novel deep eutectic solvents (DESs) have been developed to achieve deep desulfurization, particularly to extract thiophenic compounds from liquid fuels. These novel DESs, considered as analogous to ionic liquids are green, eco-friendly, inexpensive, and sustainable. We herein, using molecular dynamic simulation, analyze the interactions of metal-based DESs with model oil consisting of thiophenic compounds. The DES used consists of polyethylene glycol (PEG-200) as a hydrogen bond donor, choline chloride (ChCl) or tetrabutyl ammonium chloride (TBAC) as a hydrogen bond acceptor, and cobalt chloride (CoCl₂) as metal salt. In particular, the combination of ChCl: PEG-200:CoCl₂ at a ratio 1:2:1 and the combination of TBAC:PEG-200:CoCl₂ at a ratio 1:2:0.25 were simulated, separately, with model oil consisting of octane and thiophenes at 25ᵒC and 1 bar. The results of molecular dynamics simulations were analyzed in terms of interaction energies between different components. The simulations revealed a stronger interaction between DESs/thiophenes as compared with octane/thiophenes, suggestive of an efficient desulfurization process. In addition, our analysis suggests that the choice of hydrogen bond acceptor strongly influences the efficiency of the desulfurization process. Taken together, the results also show the importance of the metal ion, although present in small amount, in the process, and the role of the polymer in desulfurization of the model fuel.

Keywords: deep eutectic solvents, desulfurization, molecular dynamics simulations, thiophenes

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Authors: Thi. A. D. Tran, Matthieu Arnold, Dominique Adolphe, Laurence Schcher, Guillaume Reys

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During daily oral health cares, dental surgeons are in contact with numerous potentially infectious germs from patients' saliva and blood. In order to take into account these risks, a product development process has been unrolled to propose to the dental surgeon a personal protection equipment that is suitable with their expectations in terms of images, protection and comfort. After a consumer study, to evaluate how the users wear the garment and their expectations, specifications have been carried out and technical solutions have been developed in order to answer to the maximum of the desiderata. Thermal studies and comfort studies have been performed. The obtained results lead to define the technical solutions concerning the design of the new scrub. Three main functions have been investigated, the ergonomic aspect, the protection and the thermal comfort. In terms of ergonomic aspect, instrumented garments have been worn and pressure measurements have been done. The results highlight that a raglan shape for the sleeves has to be selected for a better dynamic comfort. Moreover, spray tests helped us to localize the potential contamination area and therefore protection devices have been placed on the garment. Concerning the thermal comfort, an I-R study was conducted in consulting room under the real working conditions; the heating zones have been detected. Based on these results, solutions have been proposed and implemented in a new gown. This new gown is currently composed of three different parts; a protective layer placed in the chest area to avoid contamination; a breathable layer placed in the back and in the armpits and a normal PET/Cotton fabric for the rest of the gown. Through the fitting tests conducted in hospital, it was obtained that the new design was highly appreciated. Some points can nevertheless be further improved. A final product will be produced based on necessary improvements.

Keywords: comfort, dentists, garment, thermal

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

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

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

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Authors: Yebeen Ji, Jimin Yun, Kwonhoo Kim

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Magnesium alloys were limited for industrial applications due to having a limited slip system and high plastic anisotropy. It has been known that specific textures were formed during processing (rolling, etc.), and These textures cause poor formability. To solve these problems, many researchers have studied controlling texture by adding rare-earth elements. However, the high cost limits their use; therefore, alternatives are needed to replace them. Although Pb addition doesn’t directly improve magnesium properties, it has been known to suppress the diffusion of other alloying elements and reduce grain boundary energy. These characteristics are similar to the additions of rare-earth elements, and a similar texture behavior is expected as well. However, there is insufficient research on this. Therefore, this study investigates the behavior of texture and microstructure development after adding Pb to magnesium. This study compared and analyzed AZ61 alloy and Mg-15wt%Pb alloy to determine the effect of adding solute elements. The alloy was hot rolled and annealed to form a single phase and initial texture. Afterward, the specimen was set to contraction and elongate parallel to the rolling surface and the rolling direction and then subjected to high-temperature plane strain compression under the conditions of 723K and 0.05/s. Microstructural analysis and texture measurements were performed by SEM-EBSD. The peak stress in the true strain-stress curve after compression was higher in AZ61, but the shape of the flow curve was similar for both alloys. For both alloys, continuous dynamic recrystallization was confirmed to occur during the compression process. The basal texture developed parallel to the compressed surface, and the pole density was lower in the Mg-15wt%Pb alloy. It is confirmed that this change in behavior is because the orientation distribution of recrystallized grains has a more random orientation compared to the parent grains when Pb is added.

Keywords: Mg, texture, Pb, DRX

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Authors: Gargi Ghoshal, Ashay Jain, Deepika Thakur, U. S. Shivhare, O. P. Katare

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The main objectives of this work were the rheological characterization of dispersions, emulsions at different pH used in the microcapsules preparation and the microcapsules obtain from gum arabic (A), guar gum (G), casein (C) and whey protein isolate (W) to keep β-carotene protected from degradation using the complex coacervation microencapsulation technique (CCM). The evaluation of rheological properties of dispersions, emulsions of different pH and so obtained microencapsules manifest the changes occur in the molecular structure of wall materials during the encapsulation process of β-carotene. These dispersions, emulsions of different pH and formulated microencapsules were subjected to go through various conducted experiments (flow curve test, amplitude sweep, and frequency sweep test) using controlled stress dynamic rheometer. Flow properties were evaluated as a function of apparent viscosity under steady shear rate ranging from 0.1 to 100 s-1. The frequency sweep test was conducted to determine the extent of viscosity and elasticity present in the samples at constant strain under changing angular frequency range from 0.1 to 100 rad/s at 25ºC. The dispersions and emulsion exhibited a shear thinning non-Newtonian behavior whereas microencapsules are considered as shear-thickening respectively. The apparent viscosity for dispersion, emulsions were decreased at low shear rates 20 s-1 and for microencapsules, it decreases up to ~50 s-1 besides these value, it has shown constant pattern. Oscillatory shear experiments showed a predominant viscous liquid behavior up to crossover frequencies of dispersions of C, W, A at 49.47 rad/s, 57.60 rad/s and 21.45 rad/s emulsion sample of AW at pH 5.0 it was 17.85 rad/s and GW microencapsules 61.40 rad/s respectively whereas no such crossover was found in G dispersion, emulsion with C and microencapsules still it showed more viscous behavior. Storage and loss modulus decreases with time also a shift of the crossover towards lower frequencies for A, W and C was observed respectively. However, their microencapsules showed more viscous behavior as compared to samples prior to blending.

Keywords: viscosity, gums, proteins, frequency sweep test, apparent viscosity

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Authors: M. Jerold, V. Sivasubramanian, A. George, B.S. Ashik, S. S. Kumar

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Bioethanol is a sustainable biofuel that can be used alternative to fossil fuels. Today, third generation (3G) biofuel is gaining more attention than first and second-generation biofuel. The more lignin content in the lignocellulosic biomass is the major drawback of second generation biofuels. Algae are the renewable feedstock used in the third generation biofuel production. Algae contain a large number of carbohydrates, therefore it can be used for the fermentation by hydrolysis process. There are two groups of Algae, such as micro and macroalgae. In the present investigation, Macroalgae was chosen as raw material for the production of bioethanol. Two marine algae viz. Ulva Lactuca and Sargassum swartzii were used for the experimental studies. The algal biomass was characterized using various analytical techniques like Elemental Analysis, Scanning Electron Microscopy Analysis and Fourier Transform Infrared Spectroscopy to understand the physio-Chemical characteristics. The batch experiment was done to study the hydrolysis and operation parameters such as pH, agitation, fermentation time, inoculum size. The saccharification was done with acid and alkali treatment. The experimental results showed that NaOH treatment was shown to enhance the bioethanol. From the hydrolysis study, it was found that 0.5 M Alkali treatment would serve as optimum concentration for the saccharification of polysaccharide sugar to monomeric sugar. The maximum yield of bioethanol was attained at a fermentation time of 9 days. The inoculum volume of 1mL was found to be lowest for the ethanol fermentation. The agitation studies show that the fermentation was higher during the process. The percentage yield of bioethanol was found to be 22.752% and 14.23 %. The elemental analysis showed that S. swartzii contains a higher carbon source. The results confirmed hydrolysis was not completed to recover the sugar from biomass. The specific gravity of ethanol was found to 0.8047 and 0.808 for Ulva Lactuca and Sargassum swartzii, respectively. The purity of bioethanol also studied and found to be 92.55 %. Therefore, marine algae can be used as a most promising renewable feedstock for the production of bioethanol.

Keywords: algae, biomass, bioethaol, biofuel, pretreatment

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Authors: Susan Diamond

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Machine Learning workloads have traditionally been run in high-performance computing (HPC) environments, where users log in to dedicated machines and utilize the attached GPUs to run training jobs on huge datasets. Training of large neural network models is very resource intensive, and even after exploiting parallelism and accelerators such as GPUs, a single training job can still take days. Consequently, the cost of hardware is a barrier to entry. Even when upfront cost is not a concern, the lead time to set up such an HPC environment takes months from acquiring hardware to set up the hardware with the right set of firmware, software installed and configured. Furthermore, scalability is hard to achieve in a rigid traditional lab environment. Therefore, it is slow to react to the dynamic change in the artificial intelligent industry. Watson Deep Learning as a service, a cloud-based deep learning platform that mitigates the long lead time and high upfront investment in hardware. It enables robust and scalable sharing of resources among the teams in an organization. It is designed for on-demand cloud environments. Providing a similar user experience in a multi-tenant cloud environment comes with its own unique challenges regarding fault tolerance, performance, and security. Watson Deep Learning as a service tackles these challenges and present a deep learning stack for the cloud environments in a secure, scalable and fault-tolerant manner. It supports a wide range of deep-learning frameworks such as Tensorflow, PyTorch, Caffe, Torch, Theano, and MXNet etc. These frameworks reduce the effort and skillset required to design, train, and use deep learning models. Deep Learning as a service is used at IBM by AI researchers in areas including machine translation, computer vision, and healthcare. 

Keywords: deep learning, machine learning, cognitive computing, model training

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: Oluwaseun K. Oyebode, Josiah A. Adeyemo

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Hydrological modelling plays a crucial role in the planning and management of water resources, most especially in water stressed regions where the need to effectively manage the available water resources is of critical importance. However, due to the complex, nonlinear and dynamic behaviour of hydro-climatic interactions, achieving reliable modelling of water resource systems and accurate projection of hydrological parameters are extremely challenging. Although a significant number of modelling techniques (process-based and data-driven) have been developed and adopted in that regard, the field of hydrological modelling is still considered as one that has sluggishly progressed over the past decades. This is majorly as a result of the identification of some degree of uncertainty in the methodologies and results of techniques adopted. In recent times, evolutionary computation (EC) techniques have been developed and introduced in response to the search for efficient and reliable means of providing accurate solutions to hydrological related problems. This paper presents a comprehensive review of the underlying principles, methodological needs and applications of a promising evolutionary computation modelling technique – genetic programming (GP). It examines the specific characteristics of the technique which makes it suitable to solving hydrological modelling problems. It discusses the opportunities inherent in the application of GP in water related-studies such as rainfall estimation, rainfall-runoff modelling, streamflow forecasting, sediment transport modelling, water quality modelling and groundwater modelling among others. Furthermore, the means by which such opportunities could be harnessed in the near future are discussed. In all, a case for total embracement of GP and its variants in hydrological modelling studies is made so as to put in place strategies that would translate into achieving meaningful progress as it relates to modelling of water resource systems, and also positively influence decision-making by relevant stakeholders.

Keywords: computational modelling, evolutionary algorithms, genetic programming, hydrological modelling

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Authors: Jacob Hatherell, Jason Matthews, Arnaud Marmier

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Anvil Staking is a cold-forming process that is used in the assembly of plain spherical bearings into a rod-end housing. This process ensures that the bearing outer lip conforms to the chamfer in the matching rod end to produce a lightweight mechanical joint with sufficient strength to meet the pushout load requirement of the assembly. Finite Element (FE) analysis is being used extensively to predict the behaviour of metal flow in cold forming processes to support industrial manufacturing and product development. On-going research aims to validate FE models across a wide range of bearing and rod-end geometries by systematically isolating and understanding the uncertainties caused by variations in, material properties, load-dependent friction coefficients and strain rate sensitivity. The improved confidence in these models aims to eliminate the costly and time-consuming process of experimental trials in the introduction of new bearing designs. Previous literature has shown that friction coefficients do not remain constant during cold forming operations, however, the understanding of this phenomenon varies significantly and is rarely implemented in FE models. In this paper, a new approach to evaluate the normal contact pressure versus friction coefficient relationship is outlined using friction calibration charts generated via iterative FE models and ring compression tests. When compared to previous research, this new approach greatly improves the prediction of forming geometry and the forming load during the staking operation. This paper also aims to standardise the FE approach to modelling ring compression test and determining the friction calibration charts.

Keywords: anvil staking, finite element analysis, friction coefficient, spherical plain bearing, ring compression tests

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Authors: Tingke Wu, Man Yuan

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“National Territorial Planning (2016-2030)” was issued by the State Council of China in 2017. As an important initiative of putting it into effect, territorial planning at provincial level makes overall arrangement of territorial development, resources and environment protection, comprehensive renovation and security system construction. Hubei province, as the pivot of the “Rise of Central China” national strategy, is now confronted with great opportunities and challenges in territorial development, protection, and renovation. Territorial spatial pattern experiences long time evolution, influenced by multiple internal and external driving forces. It is not clear what are the main causes of its formation and what are effective ways of optimizing it. By analyzing land use data in 2016, this paper reveals present status of territory in Hubei. Combined with economic and social data and construction information, driving forces of territorial spatial pattern are then analyzed. Research demonstrates that the three types of territorial space aggregate distinctively. The four aspects of driving forces include natural background which sets the stage for main functions, population and economic factors which generate agglomeration effect, transportation infrastructure construction which leads to axial expansion and significant provincial strategies which encourage the established path. On this basis, targeted strategies for optimizing territory spatial pattern are then put forward. Hierarchical protection pattern should be established based on development intensity control as respect for nature. By optimizing the layout of population and industry and improving the transportation network, polycentric network-based development pattern could be established. These findings provide basis for Hubei Territorial Planning, and reference for future territorial planning in other provinces.

Keywords: driving forces, Hubei, optimizing strategies, spatial pattern, territory

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Authors: Yogeeta O. Agrawal, Hitendra S. Mahajan, Sanjay J. Surana

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Methotrexate is effective in controlling recalcitrant psoriasis when administered by the oral or parenteral route long-term. However, the systematic use of this drug may provoke any of a number of side effects, notably hepatotoxic effects. To reduce these effects, clinical studies have been done with topical MTx. It is useful in treating a number of cutaneous conditions, including psoriasis. A major problem in topical administration of MTx currently available in market is that the drug is hydrosoluble and is mostly in the dissociated form at physiological pH. Its capacity for passive diffusion is thus limited. Localization of MTx in effected layers of skin is likely to improve the role of topical dosage form of the drug as a supplementary to oral therapy for treatment of psoriasis. One of the possibilities for increasing the penetration of drugs through the skin is the use of Nanostructured lipid Carriers. The objective of the present study was to formulate and characterize Methotrexate loaded Nanostructured Lipid Carriers (MtxNLCs), to understand in vitro drug release and evaluate the role of the developed gel in the topical treatment of psoriasis. MtxNLCs were prepared by solvent diffusion technique using 3(2) full factorial design.The mean diameter and surface morphology of MtxNLC was evaluated. MtxNLCs were lyophilized and crystallinity of NLC was characterized by Differential Scanning Calorimtery (DSC) and powder X-Ray Diffraction (XRD). The NLCs were incorporated in 1% w/w Carbopol 934 P gel base and in vitro skin deposition studies in Human Cadaver Skin were conducted. The optimized MtxNLCs were spherical in shape, with average particle size of 253(±9.92)nm, zeta potential of -30.4 (±0.86) mV and EE of 53.12(±1.54)%. DSC and XRD data confirmed the formation of NLCs. Significantly higher deposition of Methotrexate was found in human cadaver skin from MtxNLC gel (71.52 ±1.23%) as compared to Mtx plain gel (54.28±1.02%). Findings of the studies suggest that there is significant improvement in therapeutic index in treatment of psoriasis by MTx-NLCs incorporated gel base developed in this investigation over plain drug gel currently available in the market.

Keywords: methotrexate, psoriasis, NLCs, hepatotoxic effects

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Authors: A. Akbarpour, M. R. Adib Ramezani, M. Zhian, N. Ghorbani Amirabad

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One way to improve the performance of structures against of earthquake is passive control which requires no external power source. In this research, tuned liquid column dampers which are among of systems with the capability to transfer energy between various modes of vibration, are used. For the first time, a liquid column damper for vibration control structure is presented. After modeling this structure in design building software and performing the static and dynamic analysis and obtaining the necessary parameters for the design of tuned liquid column damper, the whole structure will be analyzed in finite elements software. The tuned liquid column dampers are installed on the structure and nonlinear time-history analysis is done in two cases of structures; with and without dampers. Finally the seismic behavior of building in the two cases will be examined. In this study the nonlinear time-history analysis on a twelve-story steel structure equipped with damper subject to records of earthquake including Loma Prieta, Northridge, Imperiall Valley, Pertrolia and Landers was performed. The results of comparing between two cases show that these dampers have reduced lateral displacement and acceleration of levels on average of 10%. Roof displacement and acceleration also reduced respectively 5% and 12%. Due to structural asymmetric in the plan, the maximum displacements of surrounding structures as well as twisting were studied. The results show that the dampers lead to a 10% reduction in the maximum response of structure stories surrounding points. At the same time, placing the dampers, caused to reduce twisting on the floor plan of the structure, Base shear of structure in the different earthquakes also has been reduced on the average of 6%.

Keywords: retrofitting, passive control, tuned liquid column damper, finite element analysis

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Authors: Mohan Li

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Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: Catherine Mangan, Beth Anderson

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There has been a significant drive to use online or hybrid learning in Higher Education (HE) over recent years. HEs with a virtual presence offer their communities a range of benefits, including the potential for greater inclusivity, diversity, and collaboration; more flexible learning packages; and more engaging, dynamic content. Institutions can also experience significant challenges when seeking to extend learning spaces in this way, as can learners themselves. For example, staff members’ and learners’ digital literacy varies (as do their perceptions of technologies in use), and there can be confusion about optimal approaches to implementation. Furthermore, the speed with which HE institutions have needed to shift to fully online or hybrid models, owing to the COVID19 pandemic, has highlighted the significant barriers to successful implementation. HE environments have been shown to predict a range of organisational, academic, and experiential outcomes, both positive and negative. Much research has focused on the social aspect of virtual platforms, as well as the nature and effectiveness of the technologies themselves. There remains, however, a relative paucity of synthesised knowledge on the psychology of learners’ relationships with their institutions; specifically, how individual difference and interpersonal factors predict students’ ability and willingness to engage with novel virtual learning spaces. Accordingly, extending learning spaces remains challenging for institutions, and wholly remote courses, in particular, can experience high attrition rates. Focusing on the last five years, this pragmatic review summarises evidence from the psychological and pedagogical literature. In particular, the review highlights the importance of addressing the psychological and relational complexities of students’ shift from offline to online engagement. In doing so, it identifies considerations for HE institutions looking to deliver in this way.

Keywords: higher education, individual differences, interpersonal relationships, online learning, virtual environment

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Authors: Michelangelo Sofo, Giuseppe Labianca

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In recent years, the scientific community's interest in the exploratory analysis of biomedical data has increased exponentially. Considering the field of research of nutritional biologists, the curative process, based on the analysis of clinical data, is a very delicate operation due to the fact that there are multiple solutions for the management of pathologies in the food sector (for example can recall intolerances and allergies, management of cholesterol metabolism, diabetic pathologies, arterial hypertension, up to obesity and breathing and sleep problems). In this regard, in this research work a system was created capable of evaluating various dietary regimes for specific patient pathologies. The system is founded on a mathematical-numerical model and has been created tailored for the real working needs of an expert in human nutrition using the human-centered design (ISO 9241-210), therefore it is in step with continuous scientific progress in the field and evolves through the experience of managed clinical cases (machine learning process). DietAdhoc® is a decision support system nutrition specialists for patients of both sexes (from 18 years of age) developed with an agile methodology. Its task consists in drawing up the biomedical and clinical profile of the specific patient by applying two algorithmic optimization approaches on nutritional data and a symbolic solution, obtained by transforming the relational database underlying the system into a deductive database. For all three solution approaches, particular emphasis has been given to the explainability of the suggested clinical decisions through flexible and customizable user interfaces. Furthermore, the system has multiple software modules based on time series and visual analytics techniques that allow to evaluate the complete picture of the situation and the evolution of the diet assigned for specific pathologies.

Keywords: medical decision support, physiological data extraction, data driven diagnosis, human centered AI, symbiotic AI paradigm

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Authors: L. Gyansah, Yanfang Shen, Jiqiang Wang, Tianying Xiong

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SiCₚ/ pure Al composites with different SiC fractions (20 wt %, 30 wt %, and 40 wt %) were precisely cold sprayed, followed by hot axial-compression tests at deformation temperatures of 473 K to 673 K, leading to failure of specimens through routine crack propagation in their multiphase. The plastic deformation behaviour with respect to the SiCₚ contents and the deformation temperatures were studied at strain rate 1s-1.As-sprayed and post-failure specimens were analyzed by X-ray computed tomography (XCT), transmission electron microscopy (TEM), and scanning electron microscopy (SEM). Quasi-static thermomechanical testing results revealed that compressive strength (UTS = 228 MPa and 30.4 %) was the highest in the composites that was thermomechanically compressed at 473 K compared to those of the as-sprayed, while the as-sprayed exhibited a compressive strength of 182.8 MPa related to the increment in SiC fraction. Strength—plasticity synergy was promoted by dynamic recrystallization (DRX) through strengthening and refinement of the grains. The DRX degree depends relevantly on retainment of the uniformly ultrafine SiCₚ particulates, the pinning effects of the interfaces promoted by the ultrafine grain structures (UFG), and the higher deformation temperature. Reconstructed X-ray computed tomography data revealed different crack propagation mechanisms. A single-plane shear crack with multi-laminates fracture morphology yields relatively through the as-sprayed and as-deformed at 473 K deposits, while a multiphase plane shear cracks preeminently existed in high temperature deformed deposits resulting in multiphase-interface delaminations. Three pertinent strengthening mechanisms, videlicet, SiCp dispersed strengthening, refined grain strengthening, and dislocation strengthening, existed in the gradient microstructure, and their detailed contributions to the thermomechanical properties were discussed.

Keywords: cold spraying, hot deformation, deformation temperature, thermomechancal properties, SiC/Al composite

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Authors: Wahab Ali Shah, Junjia He

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Transferring electrical power without any wiring has been a dream since late 19^th century. There were some advances in this area as to know more about microwave systems. However, this subject has recently become very attractive due to their practiScal systems. There are low power applications such as charging the batteries of contactless tooth brushes or implanted devices, and higher power applications such as charging the batteries of electrical automobiles or buses. In the first group of applications operating frequencies are in microwave range while the frequency is lower in high power applications. In the latter, the concept is also called inductive power transfer. The aim of the paper is to have an overview of the inductive power transfer for electrical vehicles with a special concentration on coil design and power converter simulation for static charging. Coil design is very important for an efficient and safe power transfer. Coil design is one of the most critical tasks. Power converters are used in both side of the system. The converter on the primary side is used to generate a high frequency voltage to excite the primary coil. The purpose of the converter in the secondary is to rectify the voltage transferred from the primary to charge the battery. In this paper, an inductive power transfer system is studied. Inductive power transfer is a promising technology with several possible applications. Operation principles of these systems are explained, and components of the system are described. Finally, a single phase 2 kW system was simulated and results were presented. The work presented in this paper is just an introduction to the concept. A reformed compensation network based on traditional inductor-capacitor-inductor (LCL) topology is proposed to realize robust reaction to large coupling variation that is common in dynamic wireless charging application. In the future, this type compensation should be studied. Also, comparison of different compensation topologies should be done for the same power level.

Keywords: coil design, contactless charging, electrical automobiles, inductive power transfer, operating frequency

Procedia PDF Downloads 245

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

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Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

Procedia PDF Downloads 148

Authors: Paramvir Singh

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The locomotion of aquatic organisms has long fascinated biologists and engineers alike, with fish fins serving as a prime example of nature's remarkable adaptations for efficient underwater propulsion. This paper presents a comprehensive study focused on the hydrodynamic analysis of fish fin kinematics, employing an innovative approach that combines machine learning and image processing techniques. Through high-speed videography and advanced computational tools, we gain insights into the complex and dynamic motion of the fins of a Tilapia (Oreochromis Niloticus) fish. This study was initially done by experimentally capturing videos of the various motions of a Tilapia in a custom-made setup. Using deep learning and image processing on the videos, the motion of the Caudal and Pectoral fin was extracted. This motion included the fin configuration (i.e., the angle of deviation from the mean position) with respect to time. Numerical investigations for the flapping fins are then performed using a Computational Fluid Dynamics (CFD) solver. 3D models of the fins were created, mimicking the real-life geometry of the fins. Thrust Characteristics of separate fins (i.e., Caudal and Pectoral separately) and when the fins are together were studied. The relationship and the phase between caudal and pectoral fin motion were also discussed. The key objectives include mathematical modeling of the motion of a flapping fin at different naturally occurring frequencies and amplitudes. The interactions between both fins (caudal and pectoral) were also an area of keen interest. This work aims to improve on research that has been done in the past on similar topics. Also, these results can help in the better and more efficient design of the propulsion systems for biomimetic underwater vehicles that are used to study aquatic ecosystems, explore uncharted or challenging underwater regions, do ocean bed modeling, etc.

Keywords: biomimetics, fish fin kinematics, image processing, fish tracking, underwater vehicles

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Authors: Mahmoud Abdel Hameed Shahin

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Job demands that are incompatible with an employee's skills, resources, or needs cause unpleasant emotional and physical reactions known as job stress. Nurses offer care in hospital emergency rooms all around the world, and since they operate in such a dynamic and unpredictable setting, they are constantly under pressure. It has been discovered that job stress has harmful impacts on nurses' health as well as their capacity to handle the demands of their jobs. The purpose of this study was to evaluate the level of job stress experienced by the emergency department nurses at King Fahad Specialist Hospital in Buraidah City, Saudi Arabia. In October 2021, a cross-sectional descriptive study was conducted. 80 nurses were conveniently selected for the study, the bulk of them worked at King Fahad Specialist Hospital's emergency department. An electronic questionnaire with a sociodemographic data sheet and a job stress scale was given to the participating nurses after ethical approval was received from the Ministry of Health's representative bodies. Using SPSS Version 26, both descriptive and inferential statistics were employed to analyze and tabulate the acquired data. According to the findings, the factors that contributed to the most job stress in the clinical setting were having an excessive amount of work to do and working under arbitrary deadlines, whereas the factors that contributed to the least stress were receiving the proper recognition or rewards for good work. In the emergency room of King Fahad Specialist Hospital, nurses had a moderate level of stress (M=3.32 ± 0.567/5). Based on their experience, emergency nurses' levels of job stress varied greatly, with nurses with less than a year of experience notably experiencing the lowest levels of job stress. The amount of job stress did not differ significantly based on the emergency nurses' age, nationality, gender, marital status, position, or level of education. The causes and impact of stress on emergency nurses should be identified and alleviated by hospitals through the implementation of interventional programs.

Keywords: emergency nurses, job pressure, Qassim, Saudi Arabia, job stress

Procedia PDF Downloads 179

Authors: Manmeet Kaur, Madhu Vij

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The Board of Directors in a firm performs the primary role of an internal control mechanism. This Study seeks to understand the relationship between internal governance and performance of banks in India. The research paper investigates the effect of board structure (proportion of nonexecutive directors, gender diversity, board size and meetings per year) on the firm performance. This paper evaluates the impact of corporate governance mechanisms on bank’s financial performance using panel data for 28 listed banks in National Stock Exchange of India for the period of 2008-2014. Returns on Asset, Return on Equity, Tobin’s Q and Net Interest Margin were used as the financial performance indicators. To estimate the relationship among governance and bank performance initially the Study uses Pooled Ordinary Least Square (OLS) Estimation and Generalized Least Square (GLS) Estimation. Then a well-developed panel Generalized Method of Moments (GMM) Estimator is developed to investigate the dynamic nature of performance and governance relationship. The Study empirically confirms that two-step system GMM approach controls the problem of unobserved heterogeneity and endogeneity as compared to the OLS and GLS approach. The result suggests that banks with small board, boards with female members, and boards that meet more frequently tend to be more efficient and subsequently have a positive impact on performance of banks. The study offers insights to policy makers interested in enhancing the quality of governance of banks in India. Also, the findings suggest that board structure plays a vital role in the improvement of corporate governance mechanism for financial institutions. There is a need to have efficient boards in banks to improve the overall health of the financial institutions and the economic development of the country.

Keywords: board of directors, corporate governance, GMM estimation, Indian banking

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Authors: Christine Ysabelle G. Roman, Pauline Torres

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Background: Hypertrophic cardiomyopathy is a disease of marked heterogeneity. It is a genetically determined heart disease characterized by significant myocardium hypertrophy that results in diastolic dysfunction, left ventricular outflow tract obstruction, and an increased risk of arrhythmias. The primary treatment in patients with such conditions is negative inotropic drugs, such as beta-blockers, calcium channel antagonists, and disopyramide. However, for those who remain symptomatic and need septal reduction therapy, surgical septal myectomy or alcohol septal ablation are options. Case Summary: A 19 – year old female presented in the authors’ institution with easy fatigability. The consult was done a year prior, and 2D echocardiography was requested which showed concentric left ventricular hypertrophy, asymmetrically hypertrophied interventricular septum (IVS) with the largest diameter of 3.3cm & subaortic dynamic obstruction with a maximum gradient of 47 mmHg. A repeat echo a year later showed asymmetric septal hypertrophy (IVS measuring at 3cm) with the systolic anterior motion of anterior mitral valve leaflet and left ventricular outflow tract obstruction (peak gradient of 50mmHg). The patient then underwent alcohol septal ablation and was discharged stable after four days of admission. Conclusion: Hypertrophic obstructive cardiomyopathy, a cardiovascular genetic disease, results in various patterns of left ventricular hypertrophy and abnormality of mitral valve apparatus. The patient is managed medically initially. However, despite optimal drug therapy and significant left ventricular outflow tract obstruction, significant heart failure symptoms or syncope require invasive treatment.

Keywords: hypertrophic obstructive cardiomyopathy, left ventricular outflow tract obstruction, alcohol septal ablation, alcohol

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Authors: Dewi Retno Sari Saputro, Purnami Widyaningsih, Hendrika Handayani

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Extreme data on an observation can occur due to unusual circumstances in the observation. The data can provide important information that can’t be provided by other data so that its existence needs to be further investigated. The method for obtaining extreme data is one of them using maxima block method. The distribution of extreme data sets taken with the maxima block method is called the distribution of extreme values. Distribution of extreme values is Gumbel distribution with two parameters. The parameter estimation of Gumbel distribution with maximum likelihood method (ML) is difficult to determine its exact value so that it is necessary to solve the approach. The purpose of this study was to determine the parameter estimation of Gumbel distribution with quasi-Newton BFGS method. The quasi-Newton BFGS method is a numerical method used for nonlinear function optimization without constraint so that the method can be used for parameter estimation from Gumbel distribution whose distribution function is in the form of exponential doubel function. The quasi-New BFGS method is a development of the Newton method. The Newton method uses the second derivative to calculate the parameter value changes on each iteration. Newton's method is then modified with the addition of a step length to provide a guarantee of convergence when the second derivative requires complex calculations. In the quasi-Newton BFGS method, Newton's method is modified by updating both derivatives on each iteration. The parameter estimation of the Gumbel distribution by a numerical approach using the quasi-Newton BFGS method is done by calculating the parameter values that make the distribution function maximum. In this method, we need gradient vector and hessian matrix. This research is a theory research and application by studying several journals and textbooks. The results of this study obtained the quasi-Newton BFGS algorithm and estimation of Gumbel distribution parameters. The estimation method is then applied to daily rainfall data in Purworejo District to estimate the distribution parameters. This indicates that the high rainfall that occurred in Purworejo District decreased its intensity and the range of rainfall that occurred decreased.

Keywords: parameter estimation, Gumbel distribution, maximum likelihood, broyden fletcher goldfarb shanno (BFGS)quasi newton

Procedia PDF Downloads 318