Search results for: GMM estimation
746 Sensor Monitoring of the Concentrations of Different Gases Present in Synthesis of Ammonia Based on Multi-Scale Entropy and Multivariate Statistics
Authors: S. Aouabdi, M. Taibi
Abstract:
The supervision of chemical processes is the subject of increased development because of the increasing demands on reliability and safety. An important aspect of the safe operation of chemical process is the earlier detection of (process faults or other special events) and the location and removal of the factors causing such events, than is possible by conventional limit and trend checks. With the aid of process models, estimation and decision methods it is possible to also monitor hundreds of variables in a single operating unit, and these variables may be recorded hundreds or thousands of times per day. In the absence of appropriate processing method, only limited information can be extracted from these data. Hence, a tool is required that can project the high-dimensional process space into a low-dimensional space amenable to direct visualization, and that can also identify key variables and important features of the data. Our contribution based on powerful techniques for development of a new monitoring method based on multi-scale entropy MSE in order to characterize the behaviour of the concentrations of different gases present in synthesis and soft sensor based on PCA is applied to estimate these variables.Keywords: ammonia synthesis, concentrations of different gases, soft sensor, multi-scale entropy, multivarite statistics
Procedia PDF Downloads 329745 Simultaneous Extraction and Estimation of Steroidal Glycosides and Aglycone of Solanum
Authors: Karishma Chester, Sarvesh Paliwal, Sayeed Ahmad
Abstract:
Solanumnigrum L. (Family: Solanaceae), is an important Indian medicinal plant and have been used in various traditional formulations for hepato-protection. It has been reported to contain significant amount of steroidal glycosides such as solamargine and solasonine as well as their aglycone part solasodine. Being important pharmacologically active metabolites of several members of Solanaceae these markers have been attempted various times for their extraction and quantification but separately for glycoside and aglycone part because of their opposite polarity. Here, we propose for the first time simultaneous extraction and quantification of aglycone (solasodine)and glycosides (solamargine and solasonine) inleaves and berries of S.nigrumusing solvent extraction followed by HPTLC analysis. Simultaneous extraction was carried out by sonication in mixture of chloroform and methanol as solvent. The quantification was done using silica gel 60F254HPTLC plates as stationary phase and chloroform: methanol: acetone: 0.5 % ammonia (7: 2.5: 1: 0.4 v/v/v/v) as mobile phaseat 400 nm, after derivatization with an isaldehydesul furic acid reagent. The method was validated as per ICH guideline for calibration, linearity, precision, recovery, robustness, specificity, LOD, and LOQ. The statistical data obtained for validation showed that method can be used routinely for quality control of various solanaceous drugs reported for these markers as well as traditional formulations containing those plants as an ingredient.Keywords: solanumnigrum, solasodine, solamargine, solasonine, quantification
Procedia PDF Downloads 326744 The Impact of Research and Development Cooperation Partner Diversity, Knowledge Source Diversity and Knowledge Source Network Embeddedness on Radical Innovation: Direct Relationships and Interaction with Non-Price Competition
Authors: Natalia Strobel, Jan Kratzer
Abstract:
In this paper, we test whether different types of research and development (R&D) alliances positively impact the radical innovation performance of firms. We differentiate between the R&D alliances without extern R&D orders and embeddedness in knowledge source network. We test the differences between the domestically diversified R&D alliances and R&D alliances diversified abroad. Moreover, we test how non-price competition influences the impact of domestically diversified R&D alliances, and R&D alliance diversified abroad on radical innovation performance. Our empirical analysis is based on the comprehensive Swiss innovation panel, which allowed us to study 3520 firms between the years between 1996 and 2011 in 3 years intervals. We analyzed the data with a linear estimation with Swamy-Aurora transformation using plm package in R software. Our results show as hypothesized a positive impact of R&D alliances diversity abroad as well as domestically on radical innovation performance. The effect of non-price interaction is in contrast to our hypothesis, not significant. This suggests that diversity of R&D alliances is highly advantageous independent of non-price competition.Keywords: R&D alliances, partner diversity, knowledge source diversity, non-price competition, absorptive capacity
Procedia PDF Downloads 360743 Feasibility Studies through Quantitative Methods: The Revamping of a Tourist Railway Line in Italy
Authors: Armando Cartenì, Ilaria Henke
Abstract:
Recently, the Italian government has approved a new law for public contracts and has been laying the groundwork for restarting a planning phase. The government has adopted the indications given by the European Commission regarding the estimation of the external costs within the Cost-Benefit Analysis, and has been approved the ‘Guidelines for assessment of Investment Projects’. In compliance with the new Italian law, the aim of this research was to perform a feasibility study applying quantitative methods regarding the revamping of an Italian tourist railway line. A Cost-Benefit Analysis was performed starting from the quantification of the passengers’ demand potentially interested in using the revamped rail services. The benefits due to the external costs reduction were also estimated (quantified) in terms of variations (with respect to the not project scenario): climate change, air pollution, noises, congestion, and accidents. Estimations results have been proposed in terms of the Measure of Effectiveness underlying a positive Net Present Value equal to about 27 million of Euros, an Internal Rate of Return much greater the discount rate, a benefit/cost ratio equal to 2 and a PayBack Period of 15 years.Keywords: cost-benefit analysis, evaluation analysis, demand management, external cost, transport planning, quality
Procedia PDF Downloads 213742 Determination of Economic and Ecological Potential of Bio Hydrogen Generated through Dark Photosynthesis Process
Authors: Johannes Full, Martin Reisinger, Alexander Sauer, Robert Miehe
Abstract:
The use of biogenic residues for the biotechnological production of chemical energy carriers for electricity and heat generation as well as for mobile applications is an important lever for the shift away from fossil fuels towards a carbon dioxide neutral post-fossil future. A multitude of promising biotechnological processes needs, therefore, to be compared against each other. For this purpose, a multi-objective target system and a corresponding methodology for the evaluation of the underlying key figures are presented in this paper, which can serve as a basis for decisionmaking for companies and promotional policy measures. The methodology considers in this paper the economic and ecological potential of bio-hydrogen production using the example of hydrogen production from fruit and milk production waste with the purple bacterium R. rubrum (so-called dark photosynthesis process) for the first time. The substrate used in this cost-effective and scalable process is fructose from waste material and waste deposits. Based on an estimation of the biomass potential of such fructose residues, the new methodology is used to compare different scenarios for the production and usage of bio-hydrogen through the considered process. In conclusion, this paper presents, at the example of the promising dark photosynthesis process, a methodology to evaluate the ecological and economic potential of biotechnological production of bio-hydrogen from residues and waste.Keywords: biofuel, hydrogen, R. rubrum, bioenergy
Procedia PDF Downloads 190741 A Range of Steel Production in Japan towards 2050
Authors: Reina Kawase
Abstract:
Japan set the goal of 80% reduction in GHG emissions by 2050. To consider countermeasures for reducing GHG emission, the production estimation of energy intensive materials, such as steel, is essential. About 50% of steel production is exported in Japan, so it is necessary to consider steel production including export. Steel productions from 2005-2050 in Japan were estimated under various global assumptions based on combination of scenarios such as goods trade scenarios and steel making process selection scenarios. Process selection scenarios decide volume of steel production by process (basic oxygen furnace and electric arc furnace) with considering steel consumption projection, supply-demand balance of steel, and scrap surplus. The range of steel production by process was analyzed. Maximum steel production was estimated under the scenario which consumes scrap in domestic steel production at maximum level. In 2035, steel production reaches 149 million ton because of increase in electric arc furnace steel. However, it decreases towards 2050 and amounts to 120 million ton, which is almost same as a current level. Minimum steel production is under the scenario which assumes technology progress in steel making and supply-demand balance consideration in each region. Steel production decreases from base year and is 44 million ton in 2050.Keywords: goods trade scenario, steel making process selection scenario, steel production, global warming
Procedia PDF Downloads 379740 Degree of Bending in Axially Loaded Tubular KT-Joints of Offshore Structures: Parametric Study and Formulation
Authors: Hamid Ahmadi, Shadi Asoodeh
Abstract:
The fatigue life of tubular joints commonly found in offshore industry is not only dependent on the value of hot-spot stress (HSS), but is also significantly influenced by the through-the-thickness stress distribution characterized by the degree of bending (DoB). The determination of DoB values in a tubular joint is essential for improving the accuracy of fatigue life estimation using the stress-life (S–N) method and particularly for predicting the fatigue crack growth based on the fracture mechanics (FM) approach. In the present paper, data extracted from finite element (FE) analyses of tubular KT-joints, verified against experimental data and parametric equations, was used to investigate the effects of geometrical parameters on DoB values at the crown 0˚, saddle, and crown 180˚ positions along the weld toe of central brace in tubular KT-joints subjected to axial loading. Parametric study was followed by a set of nonlinear regression analyses to derive DoB parametric formulas for the fatigue analysis of KT-joints under axial loads. The tubular KT-joint is a quite common joint type found in steel offshore structures. However, despite the crucial role of the DoB in evaluating the fatigue performance of tubular joints, this paper is the first attempt to study and formulate the DoB values in KT-joints.Keywords: tubular KT-joint, fatigue, degree of bending (DoB), axial loading, parametric formula
Procedia PDF Downloads 354739 Estimation of Transition and Emission Probabilities
Authors: Aakansha Gupta, Neha Vadnere, Tapasvi Soni, M. Anbarsi
Abstract:
Protein secondary structure prediction is one of the most important goals pursued by bioinformatics and theoretical chemistry; it is highly important in medicine and biotechnology. Some aspects of protein functions and genome analysis can be predicted by secondary structure prediction. This is used to help annotate sequences, classify proteins, identify domains, and recognize functional motifs. In this paper, we represent protein secondary structure as a mathematical model. To extract and predict the protein secondary structure from the primary structure, we require a set of parameters. Any constants appearing in the model are specified by these parameters, which also provide a mechanism for efficient and accurate use of data. To estimate these model parameters there are many algorithms out of which the most popular one is the EM algorithm or called the Expectation Maximization Algorithm. These model parameters are estimated with the use of protein datasets like RS126 by using the Bayesian Probabilistic method (data set being categorical). This paper can then be extended into comparing the efficiency of EM algorithm to the other algorithms for estimating the model parameters, which will in turn lead to an efficient component for the Protein Secondary Structure Prediction. Further this paper provides a scope to use these parameters for predicting secondary structure of proteins using machine learning techniques like neural networks and fuzzy logic. The ultimate objective will be to obtain greater accuracy better than the previously achieved.Keywords: model parameters, expectation maximization algorithm, protein secondary structure prediction, bioinformatics
Procedia PDF Downloads 472738 Flood Predicting in Karkheh River Basin Using Stochastic ARIMA Model
Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh
Abstract:
Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R2).Keywords: time series modelling, stochastic processes, ARIMA model, Karkheh river
Procedia PDF Downloads 283737 The Data-Driven Localized Wave Solution of the Fokas-Lenells Equation using PINN
Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy
Abstract:
The physics informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary condition to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful to study various optical phenomena.Keywords: deep learning, optical Soliton, neural network, partial differential equation
Procedia PDF Downloads 119736 An Insite to the Probabilistic Assessment of Reserves in Conventional Reservoirs
Authors: Sai Sudarshan, Harsh Vyas, Riddhiman Sherlekar
Abstract:
The oil and gas industry has been unwilling to adopt stochastic definition of reserves. Nevertheless, Monte Carlo simulation methods have gained acceptance by engineers, geoscientists and other professionals who want to evaluate prospects or otherwise analyze problems that involve uncertainty. One of the common applications of Monte Carlo simulation is the estimation of recoverable hydrocarbon from a reservoir.Monte Carlo Simulation makes use of random samples of parameters or inputs to explore the behavior of a complex system or process. It finds application whenever one needs to make an estimate, forecast or decision where there is significant uncertainty. First, the project focuses on performing Monte-Carlo Simulation on a given data set using U. S Department of Energy’s MonteCarlo Software, which is a freeware e&p tool. Further, an algorithm for simulation has been developed for MATLAB and program performs simulation by prompting user for input distributions and parameters associated with each distribution (i.e. mean, st.dev, min., max., most likely, etc.). It also prompts user for desired probability for which reserves are to be calculated. The algorithm so developed and tested in MATLAB further finds implementation in Python where existing libraries on statistics and graph plotting have been imported to generate better outcome. With PyQt designer, codes for a simple graphical user interface have also been written. The graph so plotted is then validated with already available results from U.S DOE MonteCarlo Software.Keywords: simulation, probability, confidence interval, sensitivity analysis
Procedia PDF Downloads 375735 Measurement of the Dynamic Modulus of Elasticity of Cylindrical Concrete Specimens Used for the Cyclic Indirect Tensile Test
Authors: Paul G. Bolz, Paul G. Lindner, Frohmut Wellner, Christian Schulze, Joern Huebelt
Abstract:
Concrete, as a result of its use as a construction material, is not only subject to static loads but is also exposed to variables, time-variant, and oscillating stresses. In order to ensure the suitability of construction materials for resisting these cyclic stresses, different test methods are used for the systematic fatiguing of specimens, like the cyclic indirect tensile test. A procedure is presented that allows the estimation of the degradation of cylindrical concrete specimens during the cyclic indirect tensile test by measuring the dynamic modulus of elasticity in different states of the specimens’ fatigue process. Two methods are used in addition to the cyclic indirect tensile test in order to examine the dynamic modulus of elasticity of cylindrical concrete specimens. One of the methods is based on the analysis of eigenfrequencies, whilst the other one uses ultrasonic pulse measurements to estimate the material properties. A comparison between the dynamic moduli obtained using the three methods that operate in different frequency ranges shows good agreement. The concrete specimens’ fatigue process can therefore be monitored effectively and reliably.Keywords: concrete, cyclic indirect tensile test, degradation, dynamic modulus of elasticity, eigenfrequency, fatigue, natural frequency, ultrasonic, ultrasound, Young’s modulus
Procedia PDF Downloads 169734 Denoising of Motor Unit Action Potential Based on Tunable Band-Pass Filter
Authors: Khalida S. Rijab, Mohammed E. Safi, Ayad A. Ibrahim
Abstract:
When electrical electrodes are mounted on the skin surface of the muscle, a signal is detected when a skeletal muscle undergoes contraction; the signal is known as surface electromyographic signal (EMG). This signal has a noise-like interference pattern resulting from the temporal and spatial summation of action potentials (AP) of all active motor units (MU) near electrode detection. By appropriate processing (Decomposition), the surface EMG signal may be used to give an estimate of motor unit action potential. In this work, a denoising technique is applied to the MUAP signals extracted from the spatial filter (IB2). A set of signals from a non-invasive two-dimensional grid of 16 electrodes from different types of subjects, muscles, and sex are recorded. These signals will acquire noise during recording and detection. A digital fourth order band- pass Butterworth filter is used for denoising, with a tuned band-pass frequency of suitable choice of cutoff frequencies is investigated, with the aim of obtaining a suitable band pass frequency. Results show an improvement of (1-3 dB) in the signal to noise ratio (SNR) have been achieved, relative to the raw spatial filter output signals for all cases that were under investigation. Furthermore, the research’s goal included also estimation and reconstruction of the mean shape of the MUAP.Keywords: EMG, Motor Unit, Digital Filter, Denoising
Procedia PDF Downloads 397733 Modeling Pan Evaporation Using Intelligent Methods of ANN, LSSVM and Tree Model M5 (Case Study: Shahroud and Mayamey Stations)
Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean
Abstract:
The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.Keywords: pan evaporation, intelligent methods, shahroud, mayamey
Procedia PDF Downloads 69732 Modeling of a UAV Longitudinal Dynamics through System Identification Technique
Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad
Abstract:
System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc. This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.Keywords: fixed wing UAV, system identification, black box modeling, longitudinal dynamics, least square error
Procedia PDF Downloads 320731 Colour Segmentation of Satellite Imagery to Estimate Total Suspended Solid at Rawa Pening Lake, Central Java, Indonesia
Authors: Yulia Chalri, E. T. P. Lussiana, Sarifuddin Madenda, Bambang Trisakti, Yuhilza Hanum
Abstract:
Water is a natural resource needed by humans and other living creatures. The territorial water of Indonesia is 81% of the country area, consisting of inland waters and the sea. The research object is inland waters in the form of lakes and reservoirs, since 90% of inland waters are in them, therefore the water quality should be monitored. One of water quality parameters is Total Suspended Solid (TSS). Most of the earlier research did direct measurement by taking the water sample to get TSS values. This method takes a long time and needs special tools, resulting in significant cost. Remote sensing technology has solved a lot of problems, such as the mapping of watershed and sedimentation, monitoring disaster area, mapping coastline change, and weather analysis. The aim of this research is to estimate TSS of Rawa Pening lake in Central Java by using the Lansat 8 image. The result shows that the proposed method successfully estimates the Rawa Pening’s TSS. In situ TSS shows normal water quality range, and so does estimation result of segmentation method.Keywords: total suspended solid (TSS), remote sensing, image segmentation, RGB value
Procedia PDF Downloads 401730 The Influence of Intellectual Capital Disclosures on Market Capitalization Growth
Authors: Nyoman Wijana, Chandra Arha
Abstract:
Disclosures of Intellectual Capital (IC) is a presentation of corporate information assets that are not recorded in the financial statements. This disclosures is very helpful because it provides inform corporate assets are intangible. In the new economic era, the company's intangible assets will determine company's competitive advantage. This study aimed to examine the effect of IC disclosures on market capitalization growth. Observational studies conducted over ten years in 2002-2011. The purpose of this study was to determine the effect for last ten years. One hundred samples of the company's largest market capitalization in 2011 traced back to last ten years. Data that used, are in 2011, 2008, 2005, and 2002 Method that’s used for acquiring the data is content analysis. The analytical method used is Ordinanary Least Square (OLS) and analysis tools are e views 7 This software using Pooled Least Square estimation parameters are specifically designed for panel data. The results of testing analysis showed inconsistent expression levels affect the growth of the market capitalization in each year of observation. The results of this study are expected to motivate the public company in Indonesia to do more voluntary IC disclosures and encourage regulators to make regulations in a comprehensive manner so that all categories of the IC must be disclosed by the company.Keywords: IC disclosures, market capitalization growth, analytical method, OLS
Procedia PDF Downloads 337729 Development of Prediction Models of Day-Ahead Hourly Building Electricity Consumption and Peak Power Demand Using the Machine Learning Method
Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas
Abstract:
To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.Keywords: building energy prediction, data mining, demand response, electricity market
Procedia PDF Downloads 312728 Estimation of Cholesterol Level in Different Brands of Vegetable Oils in Iraq
Authors: Mohammed Idaan Hassan Al-Majidi
Abstract:
An analysis of twenty one assorted brands of vegetable oils in Babylon Iraq, reveals varying levels of cholesterol content. Cholesterol was found to be present in most of the oil brands sampled using three standard methods. Cholesterol was detected in seventeen of the vegetable oil brands with concentration of less than 1 mg/ml while seven of the oil brands had cholesterol concentrations ranging between 1-4 mg/ml. Low iodine values were obtained in four of the vegetable oil brands and three of them had high acid values. High performance liquid chromatography (HPLC) confirmed the presence of cholesterol at varying concentrations in all the oil brands and gave the lowest detectable cholesterol values in all the oil brands. The Laser brand made from rapeseed had the highest cholesterol concentration of 3.2 mg/ml while Grand brand made from groundnuts had the least concentration (0.12 mg/ml) of cholesterol using HPLC analysis. Leibermann-Burchard method showed that Gino brand from palm kernel had the least concentration of cholesterol (3.86 mg/ml ±0.032) and the highest concentration of 3.996 mg/ml ±0.0404 was obtained in Sesame seed oil brand. This report is important in view of health implications of cholesterol in our diets. Consequently, we have been able to show that there is no cholesterol free oil in the market as shown on the vegetable oil brand labels. Therefore, companies producing and marketing vegetable oils are enjoined to desist from misleading the public by labeling their products as “cholesterol free”. They should indicate the amount of cholesterol present in the vegetable oil, no matter how small the quantity may be.Keywords: vegetable oils, heart diseases, leibermann-burchard, cholesterol
Procedia PDF Downloads 249727 A Study on Reliability of Gender and Stature Determination by Odontometric and Craniofacial Anthropometric Parameters
Authors: Churamani Pokhrel, C. B. Jha, S. R. Niraula, P. R. Pokharel
Abstract:
Human identification is one of the most challenging subjects that man has confronted. The determination of adult sex and stature are two of the four key factors (sex, stature, age, and race) in identification of an individual. Craniofacial and odontometric parameters are important tools for forensic anthropologists when it is not possible to apply advanced techniques for identification purposes. The present study provides anthropometric correlation of the parameters with stature and gender and also devises regression formulae for reconstruction of stature. A total of 312 Nepalese students with equal distribution of sex i.e., 156 male and 156 female students of age 18-35 years were taken for the study. Total of 10 parameters were measured (age, sex, stature, head circumference, head length, head breadth, facial height, bi-zygomatic width, mesio-distal canine width and inter-canine distance of both maxilla and mandible). Co-relation and regression analysis was done to find the association between the parameters. All parameters were found to be greater in males than females and each was found to be statistically significant. Out of total 312 samples, the best regressor for the determination of stature was head circumference and mandibular inter-canine width and that for gender was head circumference and right mandibular teeth. The accuracy of prediction was 83%. Regression equations and analysis generated from craniofacial and odontometric parameters can be a supplementary approach for the estimation of stature and gender when extremities are not available.Keywords: craniofacial, gender, odontometric, stature
Procedia PDF Downloads 184726 Earthquake Vulnerability and Repair Cost Estimation of Masonry Buildings in the Old City Center of Annaba, Algeria
Authors: Allaeddine Athmani, Abdelhacine Gouasmia, Tiago Ferreira, Romeu Vicente
Abstract:
The seismic risk mitigation from the perspective of the old buildings stock is truly essential in Algerian urban areas, particularly those located in seismic prone regions, such as Annaba city, and which the old buildings present high levels of degradation associated with no seismic strengthening and/or rehabilitation concerns. In this sense, the present paper approaches the issue of the seismic vulnerability assessment of old masonry building stocks through the adaptation of a simplified methodology developed for a European context area similar to that of Annaba city, Algeria. Therefore, this method is used for the first level of seismic vulnerability assessment of the masonry buildings stock of the old city center of Annaba. This methodology is based on a vulnerability index that is suitable for the evaluation of damage and for the creation of large-scale loss scenarios. Over 380 buildings were evaluated in accordance with the referred methodology and the results obtained were then integrated into a Geographical Information System (GIS) tool. Such results can be used by the Annaba city council for supporting management decisions, based on a global view of the site under analysis, which led to more accurate and faster decisions for the risk mitigation strategies and rehabilitation plans.Keywords: Damage scenarios, masonry buildings, old city center, seismic vulnerability, vulnerability index
Procedia PDF Downloads 445725 The Application of Insects in Forensic Investigations
Authors: Shirin Jalili, Hadi Shirzad, Samaneh Nabavi, Somayeh Khanjani
Abstract:
Forensic entomology is the science of study and analysis of insects evidences to aid in criminal investigation. Being aware of the distribution, biology, ecology and behavior of insects, which are founded at crime scene can provide information about when, where and how the crime has been committed. It has many application in criminal investigations. Its main use is estimation of the minimum time after death in suspicious death. The close association between insects and corpses and the use of insects in criminal investigations is the subject of forensic entomology. Because insects attack to the decomposing corpse and spawning on it from the initial stages. Forensic scientists can estimate the postmortem index by studying the insects population and the developing larval stages.In addition, toxicological and molecular studies of these insects can reveal the cause of death or even the identity of a victim. It also be used to detect drugs and poisons, and determination of incident location. Gathering robust entomological evidences is made possible for experts by recent Techniques. They can provide vital information about death, corpse movement or burial, submersion interval, time of decapitation, identification of specific sites of trauma, post-mortem artefacts on the body, use of drugs, linking a suspect to the scene of a crime, sexual molestations and the identification of suspects.Keywords: Forensic entomology, post mortem interval, insects, larvae
Procedia PDF Downloads 498724 Logical-Probabilistic Modeling of the Reliability of Complex Systems
Authors: Sergo Tsiramua, Sulkhan Sulkhanishvili, Elisabed Asabashvili, Lazare Kvirtia
Abstract:
The paper presents logical-probabilistic methods, models and algorithms for reliability assessment of complex systems, based on which a web application for structural analysis and reliability assessment of systems was created. The reliability assessment process included the following stages, which were reflected in the application: 1) Construction of a graphical scheme of the structural reliability of the system; 2) Transformation of the graphic scheme into a logical representation and modeling of the shortest ways of successful functioning of the system; 3) Description of system operability condition with logical function in the form of disjunctive normal form (DNF); 4) Transformation of DNF into orthogonal disjunction normal form (ODNF) using the orthogonalization algorithm; 5) Replacing logical elements with probabilistic elements in ODNF, obtaining a reliability estimation polynomial and quantifying reliability; 6) Calculation of weights of elements. Using the logical-probabilistic methods, models and algorithms discussed in the paper, a special software was created, by means of which a quantitative assessment of the reliability of systems of a complex structure is produced. As a result, structural analysis of systems, research and designing of optimal structure systems are carried out.Keywords: Complex systems, logical-probabilistic methods, orthogonalization algorithm, reliability, weight of element
Procedia PDF Downloads 64723 Phytochemial Screening, Anti-Microbial and Mineral Determination of Brysocarpus coccineus Root
Authors: I. L. Ibrahim, A. Mann, A. Ndanaimi
Abstract:
The research involved phytochemical screening, antibacterial activities and mineral determination by flame photometry of the crude extract of Brysocarpus coccineus schum indeed were carried out. The result of Phytochemical screening reveal tha saponins, alkaloids, cardiac glycosides, and anthraquinones were present. This suggests that the plant extract could be used as anti-inflammatory and anti-bleeding agents. Estimation of mineral content shows that the crude extract of B. coccineus contains 0.73 (Na+), 1.06 (K+) and 1.98 (Ca+) which justifies its use to be safe for hypertensive patients and could be used to lower blood pressure. The antibacterial properties of aqueous and ethanol extract were studied against some bacteria; pseudomonas aeruginosa, Escherichia coli, Bacilus subtilis, Klebsilla penmuoniae by disc diffusion method. The aqueous extract showed significant activity against the organisms while the ethanol at concentrations 5-10mg/ml ethanol extract showed significant zone of inhibition against the organisms, E. coli, (19 mm), B. cereus (12 mm), P. aeruginosa (11 mm), K. pnemuoniae (11 mm). Minimum inhibitory concentration (MIC) was carried with considerable effect of inhibition on the organisms. The MIC values observed were 1, 24, 16 and 19 mm against E. coli, B. cereus, P. aeruginosa and K. pnemuoniae respectively. Therefore, the plant could be a potential source of antibacterial agent although more pharmacological and clinical study may be recommended.Keywords: phytochemicals, microorganisms, screenings, mineral ions
Procedia PDF Downloads 409722 Developing Critical-Process Skills Integrated Assessment Instrument as Alternative Assessment on Electrolyte Solution Matter in Senior High School
Authors: Sri Rejeki Dwi Astuti, Suyanta
Abstract:
The demanding of the asessment in learning process was impact by policy changes. Nowadays, the assessment not only emphasizes knowledge, but also skills and attitude. However, in reality there are many obstacles in measuring them. This paper aimed to describe how to develop instrument of integrated assessment as alternative assessment to measure critical thinking skills and science process skills in electrolyte solution and to describe instrument’s characteristic such as logic validity and construct validity. This instrument development used test development model by McIntire. Development process data was acquired based on development test step and was analyzed by qualitative analysis. Initial product was observed by three peer reviewer and six expert judgment (two subject matter expert, two evaluation expert and two chemistry teacher) to acquire logic validity test. Logic validity test was analyzed using Aiken’s formula. The estimation of construct validity was analyzed by exploratory factor analysis. Result showed that integrated assessment instrument has 0,90 of Aiken’s Value and all item in integrated assessment asserted valid according to construct validity.Keywords: construct validity, critical thinking skills, integrated assessment instrument, logic validity, science process skills
Procedia PDF Downloads 260721 Plasma Treatment of a Lignite Using Water-Stabilized Plasma Torch at Atmospheric Pressure
Authors: Anton Serov, Alan Maslani, Michal Hlina, Vladimir Kopecky, Milan Hrabovsky
Abstract:
Recycling of organic waste is an increasingly hot topic in recent years. This issue becomes even more interesting if the raw material for the fuel production can be obtained as the result of that recycling. A process of high-temperature decomposition of a lignite (a non-hydrolysable complex organic compound) was studied on the plasma gasification reactor PLASGAS, where water-stabilized plasma torch was used as a source of high enthalpy plasma. The plasma torch power was 120 kW and allowed heating of the reactor to more than 1000 °C. The material feeding rate in the gasification reactor was selected 30 and 60 kg per hour that could be compared with small industrial production. An efficiency estimation of the thermal decomposition process was done. A balance of the torch energy distribution was studied as well as an influence of the lignite particle size and an addition of methane (CH4) in a reaction volume on the syngas composition (H2+CO). It was found that the ratio H2:CO had values in the range of 1,5 to 2,5 depending on the experimental conditions. The recycling process occurred at atmospheric pressure that was one of the important benefits because of the lack of expensive vacuum pump systems. The work was supported by the Grant Agency of the Czech Republic under the project GA15-19444S.Keywords: atmospheric pressure, lignite, plasma treatment, water-stabilized plasma torch
Procedia PDF Downloads 361720 Applying of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for Estimation of Flood Hydrographs
Authors: Amir Ahmad Dehghani, Morteza Nabizadeh
Abstract:
This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam
Procedia PDF Downloads 472719 Estimation of Optimum Parameters of Non-Linear Muskingum Model of Routing Using Imperialist Competition Algorithm (ICA)
Authors: Davood Rajabi, Mojgan Yazdani
Abstract:
Non-linear Muskingum model is an efficient method for flood routing, however, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed through this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used aiming at an available criterion to verdict ICA. In this regard, ICA was applied for Wilson flood routing; then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood that the target function was considered as the sum of squared deviation (SSQ) of observed and calculated discharges. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance, however, ICA was on first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be used as an appropriate method to evaluate the parameters of Muskingum non-linear model.Keywords: Doab Samsami river, genetic algorithm, imperialist competition algorithm, meta-exploratory algorithms, particle swarm optimization, Wilson flood
Procedia PDF Downloads 497718 Does Trade and Institutional Quality Play Any Significant Role on Environmental Quality in Sub-Saharan Africa?
Authors: Luqman Afolabi
Abstract:
This paper measures the impacts of trade and institutions on environmental quality in Sub-Saharan Africa (SSA). To examine the direction and the magnitude of the effects, the study employs the pooled mean group (PMG) estimation technique on the panel data obtained from the World Bank’s World Development and Governance Indicators, between 1996 and 2018. The empirical estimates validate the environmental Kuznets curve hypothesis (EKC) for the region, even though there have been inconclusive results on the environment – growth nexus. Similarly, a positive coefficient is obtained on the impact of trade on the environment, while the impact of the institutional indicators produce mixed results. A significant policy implication is that the governments of the SSA countries pursue policies that tend to increase economic growth, so that pollutants may be reduced. Such policies may include the provision of incentives for sustainable growth-driven industries in the region. In addition, the governance infrastructures should be improved in such a way that appropriate penalties are imposed on the pollutants, while advanced technologies that have the potentials to reduce environmental degradation should be encouraged. Finally, it is imperative from these findings that the governments of the region should promote their trade relations and the competitiveness of their local industries in order to keep pace with the global markets.Keywords: environmental quality, institutional quality sustainable development goals, trade
Procedia PDF Downloads 137717 Oxidative Stress Markers in Sports Related to Training
Authors: V. Antevska, B. Dejanova, L. Todorovska, J. Pluncevic, E. Sivevska, S. Petrovska, S. Mancevska, I. Karagjozova
Abstract:
Introduction: The aim of this study was to optimise the laboratory oxidative stress (OS) markers in soccer players. Material and methods: In a number of 37 soccer players (21±3 years old) and 25 control subjects (sedenters), plasma samples were taken for d-ROMs (reactive oxygen metabolites) and NO (nitric oxide) determination. The d-ROMs test was performed by measurement of hydroperoxide levels (Diacron, Italy). For NO determination the method of nitrate enzyme reduction with the Greiss reagent was used (OXIS, USA). The parameters were taken after the training of the soccer players and were compared with the control group. Training was considered as maximal exercise treadmill test. The criteria of maximum loading for each subject was established as >95% maximal heart rate. Results: The level of d-ROMs was found to be increased in the soccer players vs. control group but no significant difference was noticed. After the training d-ROMs in soccer players showed increased value of 299±44 UCarr (p<0.05). NO showed increased level in all soccer players vs. controls but significant difference was found after the training 102±29 μmol (p<0.05). Conclusion: Due to these results we may suggest that the measuring these OS markers in sport medicine may be useful for better estimation and evaluation of the training program. More oxidative stress should be used to clarify optimization of the training intensity program.Keywords: oxidative stress markers, soccer players, training, sport
Procedia PDF Downloads 441