Search results for: reduced order models

Authors: A. C. Dey, H. M. Ahsan

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Heterogeneous traffic composed of both motorized and non-motorized vehicles that are a common feature of urban Bangladeshi roads. Popular non-motorized vehicles include rickshaws, rickshaw-van, and bicycle. These modes performed an important role in moving people and goods in the absence of a dependable mass transport system. However, rickshaws play a major role in meeting the demand for door-to-door public transport services to the city dwellers. But there is no separate lane for non-motorized vehicles in this city. Non-motorized vehicles generally occupy the outermost or curb-side lanes, however, at intersections non-motorized vehicles get mixed with the motorized vehicles. That’s why the conventional models fail to analyze the situation completely. Microscopic traffic simulation software VISSIM 5.3, itself a lane base software but default behavioral parameters [such as driving behavior, lateral distances, overtaking tendency, CCO=0.4m, CC1=1.5s] are modified for calibrating a model to analyze the effects of non-motorized traffic at an intersection (Mirpur-10) in a non-lane based mixed traffic condition. It is seen from field data that NMV occupies an average 20% of the total number of vehicles almost all the link roads. Due to the large share of non-motorized vehicles, capacity significantly drop. After analyzing simulation raw data, significant variation is noticed. Such as the average vehicular speed is reduced by 25% and the number of vehicles decreased by 30% only for the presence of NMV. Also the variation of lateral occupancy and queue delay time increase by 2.37% and 33.75% respectively. Thus results clearly show the negative effects of non-motorized vehicles on capacity at an intersection. So special management technics or restriction of NMV at major intersections may be an effective solution to improve this existing critical condition.

Keywords: lateral occupancy, non lane based intersection, nmv, queue delay time, VISSIM 5.3

Procedia PDF Downloads 157

Authors: Sandeep Goyal, Sandeep Saluja

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Natural antioxidants have major role in maintenance of health. Green tea extract principally contains epigallocatechin-3-gallate (EGCG), as its abundant antioxidant constituent. Green tea is consumed daily worldwide as antioxidant to combat CNS diseases and has traditional importance also. EGCG has neuroprotective potential in various animal models of Parkinson disease, Alzheimer’s disease etc. but its exact mechanism has not been ruled out. The present study has been designed to investigate the anti-inflammatory, antioxidant and mitochondrial modulating mechanism of neuroprotective effect of epigallocatechin-3-gallate against rodent model of rotenone induced Parkinson’s disease (PD). The behavioural alterations were assessed by using open field test apparatus, Chatilon’s grip strength test apparatus and elevated plus maze for determining the locomotor activity, grip strength and cognition respectively. Biochemically, various parameters to assess oxidative stress, neuroinflammation and neurochemical estimations were performed on rat brain homogenates. A histological examination of rat brain striatum was done to check the neurodegeneration. Epigallocatechin-3-gallate (EGCG) at 10 & 20 mg/kg, were investigated for their neuroprotective potential along with levodopa as a standard agent. Minocycline, a microglial activation inhibitor, was administered alone and in combination with EGCG. EGCG and minocycline produced ameliorative effect against rotenone induced PD like symptoms by significantly reduced behavioral, biochemical and histological alterations. Results of our study reveal the neuroprotective effect of EGCG and minocycline against rotenone induced PD. Results of our study indicate that EGCG exerted neuroprotective effect against rotenone induced PD via its antioxidant, anti-inflammatory and mitochondrial modulating mechanisms and substantiate its previously reported and traditional claims for its use in CNS diseases.

Keywords: antioxidants, neurotoxicity, rotenone, EGCG

Procedia PDF Downloads 355

Authors: Martin Cermak, Tomas Karasek, Jaroslav Rojicek

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The key role in phenomenological modelling of cyclic plasticity is good understanding of stress-strain behaviour of given material. There are many models describing behaviour of materials using numerous parameters and constants. Combination of individual parameters in those material models significantly determines whether observed and predicted results are in compliance. Parameter identification techniques such as random gradient, genetic algorithm, and sensitivity analysis are used for identification of parameters using numerical modelling and simulation. In this paper genetic algorithm and sensitivity analysis are used to study effect of 4 parameters of modified AbdelKarim-Ohno cyclic plasticity model. Results predicted by Finite Element (FE) simulation are compared with experimental data from biaxial ratcheting test with semi-elliptical loading path.

Keywords: genetic algorithm, sensitivity analysis, inverse approach, finite element method, cyclic plasticity, ratcheting

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

Procedia PDF Downloads 386

Authors: Bülent Diken

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This paper looks to set Ridley Scott’s original film Blade Runner (1982) and Denis Villeneuve’s Blade Runner 2049 (2017) in order to provide an analysis of both films with respect to the new configurations of slavery in the 21st century. Both Blade Runner films present a de-politicized society that oscillates between two extremes: the spectral (the eye, optics, digital communications) and the biopolitical (the body, haptics). On the one hand, recognizing the subject only as a sign, the society of the spectacle registers, identifies, produces and reproduces the subject as a code. At the same time, though, the subject is constantly reduced to a naked body, to bare life, for biometric technologies to scan it as a biological body or body parts. Being simultaneously a pure code (word without body) and an instrument slave (body without word), the replicants are thus the paradigmatic subjects of this society. The paper focuses first on the similarity: both films depict a relationship between masters and slaves, that is, a despotic relationship. The master uses the (body of the) slave as an instrument, as an extension of his own body. Blade Runner 2019 frames the despotic relation in this classical way through its triangulation with the economy (the Tyrell Corporation) and the slave-replicants’ dissent (rejecting their reduction to mere instruments). In a counter-classical approach, in Blade Runner 2049, the focus shifts to another triangulation: despotism, economy (the Wallace Corporation) and consent (of replicants who no longer perceive themselves as slaves).

Keywords: Blade Runner, the spectacle, bio-politics, slavery, imstrumentalisation

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Authors: Owamah Hilary, O. C. Izinyon

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Many existing biogas kinetic models are difficult to apply to substrates they were not developed for, as they are substrate specific. Biodegradability kinetic (BIK) model and maximum biogas production potential and stability assessment (MBPPSA) model were therefore developed in this study for the anaerobic co-digestion of food waste and maize husk. Biodegradability constant (k) was estimated as 0.11d-1 using the BIK model. The results of maximum biogas production potential (A) obtained using the MBPPSA model corresponded well with the results obtained using the popular but complex modified Gompertz model for digesters B-1, B-2, B-3, B-4, and B-5. The (If) value of MBPPSA model also showed that digesters B-3, B-4, and B-5 were stable, while B-1 and B-2 were unstable. Similar stability observation was also obtained using the modified Gompertz model. The MBPPSA model can therefore be used as alternative model for anaerobic digestion feasibility studies and plant design.

Keywords: biogas, inoculum, model development, stability assessment

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Authors: Buddhi Arachchige, Hessam Ghasemnejad

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In this study, the post impact behavior of curved composite plates subjected to low velocity impact was studied analytically and numerically. Approaches to damage modelling are proposed through the degradation of stiffness in the damaged region by reduction of thickness in the damage region. Spring-mass models were used to model the impact response of the plate and impactor. The study involved designing two damage models to compare and contrast the model best fitted with the numerical results. The theoretical force-time responses were compared with the numerical results obtained through a detailed study carried out in LS-DYNA. The modified damage model established a good prediction with the analytical force-time response for different layups and geometry. This study provides a gateway in selecting the most effective layups for variable stiffness curved composite panels able to withstand a higher impact damage.

Keywords: analytical modelling, composite damage, impact, variable stiffness

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Authors: Mohsen Tehranizadeh, Mahboobe Forghani

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The impact of higher modes on the seismic response of dual structural system consist of concrete moment-resisting frame and with RC shear walls is investigated against near-field earthquakes in this paper. a 20 stories reinforced concrete shear wall-special moment frame structure is designed in accordance with ASCE7 requirements and The nonlinear model of the structure was performed on OpenSees platform. Nonlinear time history dynamic analysis with 3 near-field records are performed on them. In order to further understand the structural collapse behavior in the near field, the response of the structure at the moment of collapse especially the formation of plastic hinges is explored. The results revealed that the amplification of moment at top of the wall due to higher modes, the plastic hinge can form in the upper part of wall, even when designed and detailed for plastic hinging at the base only (according to ACI code).on the other hand, shear forces in excess of capacity design values can develop due to the contribution of the higher modes of vibration to dynamic response due to the near field can cause brittle shear or sliding failure modes. The past investigation on shear walls clearly shows the dual-hinge design concept is effective at reducing the effects of the second mode of response. An advantage of the concept is that, when combined with capacity design, it can result in relaxation of special reinforcing detailing in large portions of the wall. In this study, to investigate the implications of multi-design approach, 4 models with varies arrangement of hinge plastics at the base and height of the shear wall are considered. results base on time history analysis showed that the dual or multi plastic hinges approach can be useful in order to control the high moment and shear demand of higher mode effect.

Keywords: higher mode effect, Near-field earthquake, nonlinear time history analysis, multi plastic hinge design

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Authors: H. J. Joshi, Satyajeet Patil, Parth Dandavate, Mihir Kulkarni, Harshita Agrawal

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As the world looks towards a sustainable future, electric vehicles have become increasingly popular. Millions worldwide are looking to switch to Electric cars over the previously favored combustion engine-powered cars. This demand has seen an increase in Electric Vehicle Charging Stations. The big challenge is that the randomness of electrical energy makes it tough for these charging stations to provide an adequate amount of energy over a specific amount of time. Thus, it has become increasingly crucial to model these patterns and forecast the energy needs of power stations. This paper aims to analyze how different machine learning models perform on Electric Vehicle charging time-series data. The data set consists of authentic Electric Vehicle Data from the Netherlands. It has an overview of ten thousand transactions from public stations operated by EVnetNL.

Keywords: forecasting, smart grid, electric vehicle load forecasting, machine learning, time series forecasting

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Authors: Tin Thongthammachart, Wanida Jinsart

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Atmospheric particulate matter particles with a diameter less than 10 microns (PM₁₀) and less than 2.5 microns (PM₂.₅) have adverse health effect. The impact from PM was studied from both health and regulatory perspective. Ambient PM data was collected over ten years in Bangkok and vicinity areas of Thailand from 2007 to 2017. Statistical models were used to forecast PM concentrations from 2018 to 2020. Monitoring monthly data averaged concentration of PM₁₀ and PM₂.₅ were used as input to forecast the monthly average concentration of PM. The forecasting results were validated by root means square error (RMSE). The predicted results were used to determine hazard risk for the carcinogenic disease. The health risk values were interpolated with GIS with ordinary kriging technique to create hazard maps in Bangkok and vicinity area. GIS-based maps illustrated the variability of PM distribution and high-risk locations. These evaluated results could support national policy for the sake of human health.

Keywords: PM₁₀, PM₂.₅, statistical models, atmospheric particulate matter

Procedia PDF Downloads 162

Authors: Anne R. Fernandez, Mohammad Akmal Adnan, Tanes Prasat, Indu Bala Jaganath, Brian Kirby, Kamalan Jeevaratnam

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Introduction: Plants from the Phyllantus genus have been used indigenously for the treatment of a variety of ailments for generations. A cocktail of phytonutrients prepared from a plant of the genus Phyllanthus has demonstrated the potential to alleviate ailments which include cardiovascular disorders. In this study, we investigated the cholesterol modulating properties of a highly purified proprietary extract of a Phyllanthus species in hypercholesteraemic mice. Methods: Hypercholesteraemia was induced in ICR mice by ad-libitum feeding of high fat diet daily for six weeks. The mice were then divided into 3 groups and force fed with 10mg/kg of atorvastatin, 200mg/kg of the proprietary Phyllanthus extract and water respectively. Blood samples were taken at the end of fourth week of treatment by a tail prick. At the end of the eighth week of treatment, mice were sacrificed and serum levels of total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL) and triglycerides were measured. Results: The mean cholesterol levels in the mice fed with high fat diet were 44% (p < 0.05) higher than the mice on normal diet thus validating the model developed. The plasma HDL was significantly elevated in mice treated with the formulation (p ˂ 0.05) in comparison to the statin-treated and control mice. The total cholesterol levels in the mice treated with the proprietary extract were reduced significantly (p < 0.05) at the end of 4 weeks of treatment in comparison to the mice treated with atorvastatin. By the end of 8 weeks of treatment, there was no significant difference in the cholesterol levels of the mice in all groups. Conclusion: These results demonstrate that this proprietary extract from Phyllanthus species has the beneficial effect of reducing total cholesterol level more rapidly than atorvastatin and increasing HDL levels. Since an increase in the HDL cholesterol can reduce the risk of heart disease, this proprietary extract is a useful and safe therapeutic option compared to atorvastatin.

Keywords: high-density lipoprotein, hypercholesteraemic mice model, ICR mice, Phyllanthus spp.

Procedia PDF Downloads 447

Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

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Authors: Firas Mohamad Al-Sabek

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The Purpose of the paper is to examine the most critical and important factor which will affect the implementation of Total Quality Management (TQM) in the construction industry in the United Arab Emirates. It also examines the most effected Project outcome from implementing TQM. A framework was also proposed depending on the literature studies. The method used in this paper is a quantitative study. A survey with a sample of 60 respondents was created and distributed in a construction company in Abu Dhabi, which includes 15 questions to examine the most critical factor that will affect the implementation of TQM in addition to the most effected project outcome from implementing TQM. The survey showed that management commitment is the most important factor in implementing TQM in a construction company. Also it showed that Project cost is most effected outcome from the implementation of TQM. Management commitment is very important for implementing TQM in any company. If the management loose interest in quality then everyone in the organization will do so. The success of TQM will depend mostly on the top of the pyramid. Also cost is reduced and money is saved when the project team implement TQM. While if no quality measures are present within the team, the project will suffer a commercial failure. Based on literature, more factors can be examined and added to the model. In addition, more construction companies could be surveyed in order to obtain more accurate results. Also this study could be conducted outside the United Arab Emirates for further enchantment.

Keywords: construction project, total quality management, management commitment, cost, theoretical framework

Procedia PDF Downloads 428

Authors: Wendu Pang, Yaxin Luo, Junhong Li, Yu Zhao, Danni Cheng, Yufang Rao, Minzi Mao, Ke Qiu, Yijun Dong, Fei Chen, Jun Liu, Jian Zou, Haiyang Wang, Wei Xu, Jianjun Ren

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We aimed to compare the prognostic prediction value of positive lymph node number (PLNN) to the American Joint Committee on Cancer (AJCC) tumor, lymph node, and metastasis (TNM) staging system for patients with hypopharyngeal squamous cell carcinoma (HPSCC). A total of 826 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified and split into two independent cohorts: training (n=461) and validation (n=365). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects of PLNN in patients with HPSCC. We further applied six Cox regression models to compare the survival predictive values of the PLNN and AJCC TNM staging system. PLNN showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in both univariate and multivariable analyses, and was divided into three groups (PLNN 0, PLNN 1-5, and PLNN>5). In the training cohort, multivariate analysis revealed that the increased PLNN of HPSCC gave rise to significantly poor OS and CSS after adjusting for age, sex, tumor size, and cancer stage; this trend was also verified by the validation cohort. Additionally, the survival model incorporating a composite of PLNN and TNM classification (C-index, 0.705, 0.734) performed better than the PLNN and AJCC TNM models. PLNN can serve as a powerful survival predictor for patients with HPSCC and is a surrogate supplement for cancer staging systems.

Keywords: hypopharyngeal squamous cell carcinoma, positive lymph nodes number, prognosis, prediction models, survival predictive values

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Authors: Alan Wan

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In recent years, the body of literature on frequentist model averaging in statistics has grown significantly. Most of this work focuses on models with different mean structures but leaves out the variance consideration. In this paper, we consider a regression model with multiplicative heteroscedasticity and develop a model averaging method that combines maximum likelihood estimators of unknown parameters in both the mean and variance functions of the model. Our weight choice criterion is based on a minimisation of a plug-in estimator of the model average estimator's squared prediction risk. We prove that the new estimator possesses an asymptotic optimality property. Our investigation of finite-sample performance by simulations demonstrates that the new estimator frequently exhibits very favourable properties compared to some existing heteroscedasticity-robust model average estimators. The model averaging method hedges against the selection of very bad models and serves as a remedy to variance function misspecification, which often discourages practitioners from modeling heteroscedasticity altogether. The proposed model average estimator is applied to the analysis of two real data sets.

Keywords: heteroscedasticity-robust, model averaging, multiplicative heteroscedasticity, plug-in, squared prediction risk

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Authors: Fouzia Brihmat

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Economic planning models, which are used to build microgrids and distributed energy resources, are the current norm for expressing such confidence (DER). These models often decide both short-term DER dispatch and long-term DER investments. This research investigates the most cost-effective hybrid (photovoltaic-diesel) renewable energy system (HRES) based on Total Net Present Cost (TNPC) in an Algerian Saharan area, which has a high potential for solar irradiation and has a production capacity of 1GW/h. Lead-acid batteries have been around much longer and are easier to understand, but have limited storage capacity. Lithium-ion batteries last longer, are lighter, but generally more expensive. By combining the advantages of each chemistry, we produce cost-effective high-capacity battery banks that operate solely on AC coupling. The financial implications of this research describe the corrosion process that occurs at the interface between the active material and grid material of the positive plate of a lead-acid battery. The best cost study for the HRES is completed with the assistance of the HOMER Pro MATLAB Link. Additionally, during the course of the project's 20 years, the system is simulated for each time step. In this model, which takes into consideration decline in solar efficiency, changes in battery storage levels over time, and rises in fuel prices above the rate of inflation. The trade-off is that the model is more accurate, but it took longer to compute. As a consequence, the model is more precise, but the computation takes longer. We initially utilized the Optimizer to run the model without MultiYear in order to discover the best system architecture. The optimal system for the single-year scenario is the Danvest generator, which has 760 kW, 200 kWh of the necessary quantity of lead-acid storage, and a somewhat lower COE of $0.309/kWh. Different scenarios that account for fluctuations in the gasified biomass generator's production of electricity have been simulated, and various strategies to guarantee the balance between generation and consumption have been investigated. The technological optimization of the same system has been finished and is being reviewed in a recent paper study.

Keywords: battery, corrosion, diesel, economic planning optimization, hybrid energy system, lead-acid battery, multi-year planning, microgrid, price forecast, PV, total net present cost

Procedia PDF Downloads 91

Authors: Andrea ČopíKová

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Competency Based Management is a new approach to management, which solves organization’s challenges with complexity and with the aim to find and solve organization’s problems and learn how to avoid these in future. They teach the organizations to create, apart from the state of stability – that is temporary, vital organization, which is permanently able to utilize and profit from internal and external opportunities. The aim of this paper is to propose a process of competency model design, based on which a competency model for a financial department manager in a production company will be created. Competency models are very useful tool in many personnel processes in any organization. They are used for acquiring and selection of employees, designing training and development activities, employees’ evaluation, and they can be used as a guide for a career planning and as a tool for succession planning especially for managerial positions. When creating a competency model the method AHP (Analytic Hierarchy Process) and quantitative pair-wise comparison (Saaty’s method) will be used; these methods belong among the most used methods for the determination of weights, and it is used in the AHP procedure. The introduction part of the paper consists of the research results pertaining to the use of competency model in practice and then the issue of competency and competency models is explained. The application part describes in detail proposed methodology for the creation of competency models, based on which the competency model for the position of financial department manager in a foreign manufacturing company, will be created. In the conclusion of the paper, the final competency model will be shown for above mentioned position. The competency model divides selected competencies into three groups that are managerial, interpersonal and functional. The model describes in detail individual levels of competencies, their target value (required level) and the level of importance.

Keywords: analytic hierarchy process, competency, competency model, quantitative pairwise comparison

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Authors: Hollie Ashworth, Sarah Heath, Nick Bryan, Liam Abrahamsen, Simon Kellet

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Sellafield has a number of fuel storage ponds, some of which have been open to the air for a number of decades. This has caused corrosion of the fuel resulting in a release of some activity into solution, reduced water clarity, and accumulation of sludge at the bottom of the pond consisting of brucite (Mg(OH)2) and other uranium corrosion products. Both of these phases are also present as colloidal material. 90Sr and 137Cs are known to constitute a small volume of the radionuclides present in the pond, but a large fraction of the activity, thus they are most at risk of challenging effluent discharge limits. Organic molecules are known to be present also, due to the ponds being open to the air, with occasional algal blooms restricting visibility further. The contents of the pond need to be retrieved and safely stored, but dealing with such a complex, undefined inventory poses a unique challenge. This work aims to determine and understand the sorption-desorption interactions of 90Sr and 137Cs to brucite and uranium phases, with and without the presence of organic molecules from chemical degradation and bio-organisms. The influence of organics on these interactions has not been widely studied. Partitioning of these radionuclides and organic molecules has been determined through LSC, ICP-AES/MS, and UV-vis spectrophotometry coupled with ultrafiltration in both binary and ternary systems. Further detailed analysis into the surface and bonding environment of these components is being investigated through XAS techniques and PHREEQC modelling. Experiments were conducted in CO2-free or N2 atmosphere across a high pH range in order to best simulate conditions in the pond. Humic acid used in brucite systems demonstrated strong competition against 90Sr for the brucite surface regardless of the order of addition of components. Variance of pH did have a small effect, however this range (10.5-11.5) is close to the pHpzc of brucite, causing the surface to buffer the solution pH towards that value over the course of the experiment. Sorption of 90Sr to UO2 obeyed Ho’s rate equation and demonstrated a slow second-order reaction with respect to the sharing of valence electrons from the strontium atom, with the initial rate clearly dependent on pH, with the equilibrium concentration calculated at close to 100% sorption. There was no influence of humic acid seen when introduced to these systems. Sorption of 137Cs to UO3 was significant, with more than 95% sorbed in just over 24 hours. Again, humic acid showed no influence when introduced into this system. Both brucite and uranium based systems will be studied with the incorporation of cyanobacterial cultures harvested at different stages of growth. Investigation of these systems provides insight into, and understanding of, the effect of organics on radionuclide partitioning to brucite and uranium phases at high pH. The majority of sorption-desorption work for radionuclides has been conducted at neutral to acidic pH values, and mostly without organics. These studies are particularly important for the characterisation of legacy wastes at Sellafield, with a view to their safe retrieval and storage.

Keywords: caesium, legacy wastes, organics, sorption-desorption, strontium, uranium

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Authors: Chen-Yin Kuo, Yung-Hsin Lee

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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

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Authors: Sourabh Jain, Parul Madan

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Traffic noise pollution has become a challenging problem for all metro cities of India due to rapid urbanization, growing population and rising number of vehicles and transport development. In Delhi the prime source of noise pollution is vehicular traffic. In Delhi it is found that the ambient noise level (Leq) is exceeding the standard permissible value at all the locations. Noise barriers or enclosures are definitely useful in obtaining effective deduction of traffic noise disturbances in urbanized areas. US’s Federal Highway Administration Model (FHWA) and Calculation of Road Traffic Noise (CORTN) of UK are used to develop spread sheets for noise prediction. Spread sheets are also developed for evaluating effectiveness of existing boundary walls abutting houses in mitigating noise, redesigning them as noise barriers. Study was also carried out to examine the changes in noise level due to designed noise barrier by using both models FHWA and CORTN respectively. During the collection of various data it is found that receivers are located far away from road at Rithala and Moolchand sites and hence extra barrier height needed to meet prescribed limits was less as seen from calculations and most of the noise diminishes by propagation effect.On the basis of overall study and data analysis, it is concluded that FHWA and CORTN models under estimate noise levels. FHWA model predicted noise levels with an average percentage error of -7.33 and CORTN predicted with an average percentage error of -8.5. It was observed that at all sites noise levels at receivers were exceeding the standard limit of 55 dB. It was seen from calculations that existing walls are reducing noise levels. Average noise reduction due to walls at Rithala was 7.41 dB and at Panchsheel was 7.20 dB and lower amount of noise reduction was observed at Friend colony which was only 5.88. It was observed from analysis that Friends colony sites need much greater height of barrier. This was because of residential buildings abutting the road. At friends colony great amount of traffic was observed since it is national highway. At this site diminishing of noise due to propagation effect was very less.As FHWA and CORTN models were developed in excel programme, it eliminates laborious calculations of noise. There was no reflection correction in FHWA models as like in CORTN model.

Keywords: IFHWA, CORTN, Noise Sources, Noise Barriers

Procedia PDF Downloads 136

Authors: Pimrawee Rocharungsat

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The study of Phetchaburi Local Food Image in order to Support Tourism aimed 1) to overview Phetchaburi tourism images; and 2) to clarify Phetchaburi local food image. Both quantitative and qualitative analysis were used in this study. Questionnaires were delivered to sample group of 1,489 tourists from 8 districts of Phetchaburi. Results were found that Phetchaburi local food image could be as tool for tourism promotion. Strong place images were within Phetchaburi center city (35%) and in the markets (34.50%). As for satisfaction of local food comparing in descending order of excellent level mean score were its eminence, identity, quality, taste, creativity, and sanitation. Results of prominent images of well-known local food of Phetchaburi were Thai custard dessert, other desserts, palm and sugar palm drink and rice in ice water. The results can be applied as promotional tools for future food tourism in Phetchaburi.

Keywords: food tourism, image, tourist, Phetchaburi province

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Authors: Eva Nedeliakova, Juraj Camaj, Jaroslav Masek

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This contribution is focused on the methodology for identifying levels of quality and improving quality through new logistics model in railway transport. It is oriented on the application of dynamic quality models, which represent an innovative method of evaluation quality services. Through this conception, time factor, expected, and perceived quality in each moment of the transportation process within logistics chain can be taken into account. Various models describe the improvement of the quality which emphases the time factor throughout the whole transportation logistics chain. Quality of services in railway transport can be determined by the existing level of service quality, by detecting the causes of dissatisfaction employees but also customers, to uncover strengths and weaknesses. This new logistics model is able to recognize critical processes in logistic chain. It includes service quality rating that must respect its specific properties, which are unrepeatability, impalpability, their use right at the time they are provided and particularly changeability, which is significant factor in the conditions of rail transport as well. These peculiarities influence the quality of service regarding the constantly increasing requirements and that result in new ways of finding progressive attitudes towards the service quality rating.

Keywords: logistics model, quality, railway transport

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: P. S. Rajinikanth, Shobana Mariappan, Jestin Chellian

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The objective of the study was to prepare and characterize a water-in-oil nano emulsion of 5-Fluorouracil (5FU) to enhance the skin penetration. The present study describes a nano emulsion of 5FU using Capyrol PGMC, Transcutol HP and PEG 400 as oil, surfactant and co-surfactant, respectively. The optimized formulations were further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential in order to confirm the stability of the optimized nano emulsions. The in-vitro characterization results showed that the droplets of prepared formulation were ~100 nm with ± 15 zeta potential. In vitro skin permeation studies was conducted in albino mice skin. Significant increase in permeability parameters was also observed in nano emulsion formulations (P<0.05). The steady-state flux (Jss), enhancement ration and permeability coefficient (Kp) for optimized nano emulsion formulation (FU2, FU1, 1:1 S mix were found to be 24.21 ±2.45 μg/cm2/h, 3.28±0.87 & 19.52±1.87 cm/h, respectively), which were significant compared with conventional gel. The in vitro and in vivo skin deposition studies in rat indicated that the amount of drug deposited from the nano emulsion (292.45 µg/cm2) in skin was significant (P<0.05) an increased as compared to a conventional 5FU gel (121.42 µg/cm2). The skin irritation study using rat skin showed that the mean irritation index of the nano emulsion reduced significantly (P<0.05) as compared with conventional gel contain 1% 5FU. The results from this study suggest that a water-in-oil nano emulsion could be safely used to promote skin penetration of 5FU following topical application.

Keywords: nano emulsion, controlled release, 5 fluorouracil, skin penetration, skin irritation

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Authors: Baljinder Singh, Navneet Sharma

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Chromium is an essential nutrient involved in normal carbohydrate and lipid metabolism. It influences glucose metabolism by potentiating the action as taking part in insulin signal amplification mechanism. A placebo-controlled single blind, prospective study was carried out to investigate the effect of chromium supplementation on blood glucose, HbA1C and lipid profile in newly onset patients with type-2 diabetes. Total 40 newly onset type-2 diabetics were selected and after one month stabilization further randomly divided into two groups viz. study group and placebo group. The study group received 9 gm brewer’s yeast (42 μ Cr) daily and the other placebo group received yeast devoid of chromium for 3 months. Subjects were instructed not to change their normal eating and living habits. Fasting blood glucose, HbA1C and lipid profile were analyzed at beginning and completion of the study. Results revealed that fasting blood glucose level significantly reduced in the subjects consuming yeast supplemented with chromium (197.65±6.68 to 103.68±6.64 mg/dl; p<0.001). HbA1C values improved significantly from 9.51±0.26% to 6.86±0.28%; p<0.001 indicating better glycaemic control. In experimental group total cholesterol, TG and LDL levels were also significantly reduced from 199.66±3.11 to 189.26±3.01 mg/dl; p<0.02, 144.94±8.31 to 126.01±8.26; p<0.05 and 119.19±1.71 to 99.58±1.10; p<0.001 respectively. These data demonstrate beneficial effect of chromium supplementation on glycaemic control and lipid variables in subjects with newly onset type-2 diabetes.

Keywords: type-2 diabetes, chromium, glucose, HbA1C

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Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: N. Z. van Hierden, Q. Yu, F. Gauvin

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Cement manufacturing is, because of its production process, among the highest contributors to CO₂ emissions worldwide. As cement is one of the major components in 3D printed concrete, achieving sustainability and carbon neutrality can be particularly challenging. To improve the sustainability of 3D printed materials, different CO₂-reducing strategies can be used, each one with a distinct level of impact and complexity. In this work, we focus on the development of these sustainable mixtures and finding alternatives. Promising alternatives for cement and clinker replacement include the use of recycled building materials, amongst which (calcined) bricks and roof tiles. To study the potential of recycled clay-based building materials, the application of calcinated clay itself is studied as well. Compared to cement, the calcination temperature of clay-based materials is significantly lower, resulting in reduced CO₂ output. Reusing these materials is therefore a promising solution for utilizing waste streams while simultaneously reducing the cement content in 3D concrete mixtures. In addition, waste streams can be locally sourced, thereby reducing the emitted CO₂ during transportation. In this research, various alternative binders are examined, such as calcined clay blends (LC3) from recycled tiles and bricks, or locally obtained clay resources. Using various experiments, a high potential for mix designs including these resources has been shown with respect to material strength, while sustaining decent printability and buildability. Therefore, the defined strategies are promising and can lead to a more sustainable, low-CO₂ mixture suitable for 3D printing while using accessible materials.

Keywords: cement replacement, 3DPC, circular building materials, calcined clay, CO₂ reduction

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Authors: Suthida Panwong, Jeeraporn Pekkoh, Yingmanee Tragoolpua, Aussara Panya

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Dengue virus (DENV) infection is a major public health problem in many countries, especially in tropical and subtropical countries. DENV infection causes dengue fever that can progress to serious conditions of dengue hemorrhagic fever (DHF) or dengue shock syndrome (DSS), relevant to a high risk of mortality. However, there are no effective treatments available against the manifestation and fatalities. Currently, natural extracts have been widely used for the treatment of infectious diseases due to their safety, non-accumulation in the body, or lower side effects. Chlorella spp. is a microalgae with anti-viral activity, but there is not much report to support its ability to inhibit DENV infection. Thus, this study aimed to investigate the inhibitory effect of ethanolic extract from Chlorella sp. AARL G049, which was explored in Thailand on inhibition of DENV-2 infection. The inhibitory effect on viral infection was assessed using a foci-forming assay (FFA), which revealed that a concentration of 125 µg/mL could inhibit viral infection in Vero cells by 75.45±8.06% when treated at the same time as DENV-2 infection. Moreover, the extract at an equal concentration effectively reduced viral protein synthesis by 90.51±5.48% when assessed in human cell lines using enzyme-linked immunosorbent assay (ELISA). Concordantly, the number of infected cells after treatment was reduced as measured by immunofluorescent assay (IFA). Therefore, the finding of this study supports the potential use of Chlorella sp. extract to suppress DENV infection.

Keywords: viral infection, flavivirus, treatment, natural extract

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Authors: S. Fazelifar, M. Ghasemi

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Aim: Recent studies on cardiovascular risk factors have been focused on the new markers of inflammatory diseases such as C-reactive protein (CRP). Research evidence shows that physical activity along with other factors such as reduced smoking, controlling blood pressure, control blood lipids TC, LDL-c, HDL-c and having a healthy weight can reduce the risk of chronic heart disease (CHD) .Therefore, the aim of this study was to determine the effect of twelve weeks aerobic exercise and consumption of apple vinegar on cardiovascular risk factor in older women. Methodology: 28 inactive women (mean body weight 72.13 ± 8.6 kg, height 157 ± 7.4cm, age 48.06 ± 5.18 years and BMI 28.2 ± 3.2 kg/m2) by recall and notice of investigation, among of the eligible voters recruited and randomly divided in 4 groups: control, apple vinegar, exercise, exercise + apple vinegar. The training program includes a 20-minute warm-up and stretching, running for 15 minutes in the first session with an intensity of 80% of maximum heart rate and an increase in one-minute run time in next training session. Also, subjects in experimental groups received daily specified amount of 50 ml apple vinegar. Blood samples were collected from the brachial vein in before and after training to measure CRP and blood lipids (cholesterol, HDL, VLDL, LDL). The levels of CRP were measured by ELISA way. K-S test to determine the normality of the data and analysis of variance for repeated measures was used to analyze the data. A significant difference in the p < 0/05 accepted. Results: The results indicated that individual characteristics including height, weight, age, and body mass index were not significantly different among the four groups. The results showed that levels of CRP and LDL cholesterol were significantly reduced in all groups at post-test compared to the pre-test. The HDL levels increased significantly in all groups in post-test compared to the pre-test. Analysis of the data indicates that levels of CRP, TC, and LDL were significantly reduced in all groups compared to the control group, while the changes in the other groups were not significant relative to each other. Conclusion: Results of this study showed that twelve weeks of aerobic exercise with apple vinegar cause a significant decrease in CRP, cholesterol, LDL, and significantly increased HDL levels. According to the results of this study, it is possible that aerobic exercise with apple vinegar can inhibit CRP and undesirable fats. Considering the strong association between the inflammatory indices and the prevalence of cardiovascular diseases, every factor that decreases these indices can reduce the cardiovascular complications.

Keywords: aerobic exercise, apple vinegar, CRP, older women

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Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

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A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: bistatic radar cross section, passive radar, propagation losses, radar coverage

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