Search results for: linear programming problem

Authors: Pedro A. Marques, Francisco Monteiro, Alessandra Zumbo, Alessia Simonini, Miguel A. Mendez

Abstract:

Cryogenic fuels such as Liquid Hydrogen (LH₂) must be transported and stored at extremely low temperatures. Without expensive active cooling solutions, preventing fuel boil-off over time is impossible. Hence, one must resort to venting systems at the cost of significant energy and fuel mass loss. These losses increase significantly in propellant tanks installed on vehicles, as the presence of external accelerations induces sloshing. Sloshing increases heat and mass transfer rates and leads to significant pressure oscillations, which might further trigger propellant venting. To make LH₂ economically viable, it is essential to minimize these factors by using advanced control techniques. However, these require accurate modelling and a full understanding of the tank's thermodynamics. The present research aims to implement a simple thermodynamic model capable of predicting the state of a cryogenic fuel tank under different operating conditions (i.e., filling, pressurization, fuel extraction, long-term storage, and sloshing). Since this model relies on a set of closure parameters to drive the system's transient response, it must be calibrated using experimental or numerical data. This work focuses on the former approach, wherein the model is calibrated through an experimental campaign carried out on a reduced-scale model of a cryogenic tank. The thermodynamic model of the system is composed of three control volumes: the ullage, the liquid, and the insulating walls. Under this lumped formulation, the governing equations are derived from energy and mass balances in each region, with mass-averaged properties assigned to each of them. The gas-liquid interface is treated as an infinitesimally thin region across which both phases can exchange mass and heat. This results in a coupled system of ordinary differential equations, which must be closed with heat and mass transfer coefficients between each control volume. These parameters are linked to the system evolution via empirical relations derived from different operating regimes of the tank. The derivation of these relations is carried out using an inverse method to find the optimal relations that allow the model to reproduce the available data. This approach extends classic system identification methods beyond linear dynamical systems via a nonlinear optimization step. Thanks to the data-driven assimilation of the closure problem, the resulting model accurately predicts the evolution of the tank's thermodynamics at a negligible computational cost. The lumped model can thus be easily integrated with other submodels to perform complete system simulations in real time. Moreover, by setting the model in a dimensionless form, a scaling analysis allowed us to relate the tested configurations to a representative full-size tank for naval applications. It was thus possible to compare the relative importance of different transport phenomena between the laboratory model and the full-size prototype among the different operating regimes.

Keywords: destratification, hydrogen, modeling, pressure-drop, pressurization, sloshing, thermodynamics

Procedia PDF Downloads 87

Authors: Md. Nazmul Haque, Mahinur Rahman

Abstract:

The objective of the research is to determine the quantity of household waste generated and forecast the future condition of Ward No 24 (Nirala). For performing that, three core issues are focused: (i) the capacity and service area of the dumping stations; (ii) the present waste generation amount per capita per day; (iii) the responsibility of the local authority in the household waste collection. This research relied on field survey-based data collection from all stakeholders and GIS-based secondary analysis of waste collection points and their coverage. However, these studies are mostly based on the inherent forecasting approaches, cannot predict the amount of waste correctly. The findings of this study suggest that Nirala is a formal residential area introducing a better approach to the waste collection - self-controlled and collection system. Here, a forecasting model proposed for waste generation as Y = -2250387 + 1146.1 * X, where X = year.

Keywords: eco-friendly environment, household waste, linear regression, waste management

Procedia PDF Downloads 278

Authors: Mercedes Bertotto, Marcelo Bello, Hector Goicoechea, Veronica Fusca

Abstract:

The National Service of Agri-Food Health and Quality (SENASA), controls honey to detect contamination by synthetic or natural chemical substances and establishes and controls the traceability of the product. The utility of near-infrared spectroscopy for the detection of adulteration of honey with high fructose corn syrup (HFCS) was investigated. First of all, a mixture of different authentic artisanal Argentinian honey was prepared to cover as much heterogeneity as possible. Then, mixtures were prepared by adding different concentrations of high fructose corn syrup (HFCS) to samples of the honey pool. 237 samples were used, 108 of them were authentic honey and 129 samples corresponded to honey adulterated with HFCS between 1 and 10%. They were stored unrefrigerated from time of production until scanning and were not filtered after receipt in the laboratory. Immediately prior to spectral collection, honey was incubated at 40°C overnight to dissolve any crystalline material, manually stirred to achieve homogeneity and adjusted to a standard solids content (70° Brix) with distilled water. Adulterant solutions were also adjusted to 70° Brix. Samples were measured by NIR spectroscopy in the range of 650 to 7000 cm⁻¹. The technique of specular reflectance was used, with a lens aperture range of 150 mm. Pretreatment of the spectra was performed by Standard Normal Variate (SNV). The ant colony optimization genetic algorithm sample selection (ACOGASS) graphical interface was used, using MATLAB version 5.3, to select the variables with the greatest discriminating power. The data set was divided into a validation set and a calibration set, using the Kennard-Stone (KS) algorithm. A combined method of Potential Functions (PF) was chosen together with Partial Least Square Linear Discriminant Analysis (PLS-DA). Different estimators of the predictive capacity of the model were compared, which were obtained using a decreasing number of groups, which implies more demanding validation conditions. The optimal number of latent variables was selected as the number associated with the minimum error and the smallest number of unassigned samples. Once the optimal number of latent variables was defined, we proceeded to apply the model to the training samples. With the calibrated model for the training samples, we proceeded to study the validation samples. The calibrated model that combines the potential function methods and PLSDA can be considered reliable and stable since its performance in future samples is expected to be comparable to that achieved for the training samples. By use of Potential Functions (PF) and Partial Least Square Linear Discriminant Analysis (PLS-DA) classification, authentic honey and honey adulterated with HFCS could be identified with a correct classification rate of 97.9%. The results showed that NIR in combination with the PT and PLS-DS methods can be a simple, fast and low-cost technique for the detection of HFCS in honey with high sensitivity and power of discrimination.

Keywords: adulteration, multivariate analysis, potential functions, regression

Procedia PDF Downloads 117

Authors: Ayobami Solomon Popoola

Abstract:

Yam is majorly a carbohydrate food grown in most parts of the world. It could be boiled, fried or roasted for consumption in a variety of ways. Blanching is an established heat pre-treatment given to fruits and vegetables prior to further processing such as dehydration, canning, freezing etc. Losses of soluble solids during blanching has been a great problem because a reasonable quantity of the water-soluble nutrients are inevitably leached into the blanching water. Without blanching, the high residual levels of reducing sugars after extended storage produce a dark, bitter-tasting product because of the Maillard reactions of reducing sugars at frying temperature. Measurement and prediction of such losses are necessary for economic efficiency in production and to establish the level of effluent treatment of the blanching water. This paper aims at resolving this problem by investigating the effects of cube size and temperature on the rate of diffusional losses of reducing sugars and total sugars during hot water blanching of water-yam. The study was carried out using four temperature levels (65, 70, 80 and 90 °C) and two cubes sizes (0.02 m³ and 0.03 m³) at 4 times intervals (5, 10, 15 and 20 mins) respectively. Obtained data were fitted into Fick’s non-steady equation from which diffusion coefficients (Da) were obtained. The Da values were subsequently fitted into Arrhenius plot to obtain activation energies (Ea-values) for diffusional losses. The diffusion co-efficient were independent of cube size and time but highly temperature dependent. The diffusion coefficients were ≥ 1.0 ×10⁻⁹ m²s⁻¹ for reducing sugars and ≥ 5.0 × 10⁻⁹ m²s⁻¹ for total sugars. The Ea values ranged between 68.2 to 73.9 KJmol⁻¹ and 7.2 to 14.30 KJmol⁻¹ for reducing sugars and total sugars losses respectively. Predictive equations for estimating amount of reducing sugars and total sugars with blanching time of water-yam at various temperatures were also presented. The equation could be valuable in process design and optimization. However, amount of other soluble solids that might have leached into the water along with reducing and total sugars during blanching was not investigated in the study.

Keywords: blanching, kinetics, sugar losses, water yam

Procedia PDF Downloads 162

Authors: Solaine Hachem, Frédéric Bourquin, Dominique Siegert

Abstract:

The brutal collapse of bridges is mainly due to scour. Indeed, the soil erosion in the riverbed around a pier modifies the embedding conditions of the structure, reduces its overall stiffness and threatens its stability. Hence, finding an efficient technique that allows early scour detection becomes mandatory. Vibration analysis is an indirect method for scour detection that relies on real-time monitoring of the bridge. It tends to indicate the presence of a scour based on its consequences on the stability of the structure and its dynamic response. Most of the research in this field has focused on the dynamic behavior of a single pile and has examined the depth of the scour. In this paper, a bridge is fully modeled with all piles and spans and the scour is represented by a reduction in the foundation's stiffnesses. This work aims to identify the vibration modes sensitive to the rigidity’s loss in the foundations so that their variations can be considered as a scour indicator: the decrease in soil-structure interaction rigidity leads to a decrease in the natural frequencies’ values. By using the first-order perturbation method, the expression of sensitivity, which depends only on the selected vibration modes, is established to determine the deficiency of foundations stiffnesses. The solutions are obtained by using the singular value decomposition method for the regularization of the inverse problem. The propagation of uncertainties is also calculated to verify the efficiency of the inverse problem method. Numerical simulations describing different scenarios of scour are investigated on a simplified model of a real composite steel-concrete bridge located in France. The results of the modal analysis show that the modes corresponding to in-plane and out-of-plane piers vibrations are sensitive to the loss of foundation stiffness. While the deck bending modes are not affected by this damage.

Keywords: bridge’s piers, inverse problems, modal sensitivity, scour detection, vibration analysis

Procedia PDF Downloads 97

Authors: Parvin Goli, Amirhosein Kefayat, Rezvan Goli

Abstract:

Background: It is well established that parents can influence their offspring's neurodevelopment. It is shown that paternal environment and lifestyle is beneficial for the progeny's fitness and might affect their metabolic mechanisms; however, the effects of paternal exercise on the brain in the offspring have not been explored in detail. Objective: This study aims to review the impact of paternal physical exercise on memory and learning, neuroplasticity, as well as DNA methylation levels in the off-spring's hippocampus. Study design: In this systematic review and meta-analysis, an electronic literature search was conducted in databases including PubMed, Scopus, and Web of Science. Eligible studies were those with an experimental design, including an exercise intervention arm, with the assessment of any type of memory function, learning ability, or any type of brain plasticity as the outcome measures. Standardized mean difference (SMD) and 95% confidence intervals (CI) were computed as effect size. Results: The systematic review revealed the important role of environmental enrichment in the behavioral development of the next generation. Also, offspring of exercised fathers displayed higher levels of memory ability and lower level of brain-derived neurotrophic factor. A significant effect of paternal exercise on the hippocampal volume was also reported in the few available studies. Conclusion: These results suggest an intergenerational effect of paternal physical activity on cognitive benefit, which may be associated with hippocampal epigenetic programming in offspring. However, the biological mechanisms of this modulation remain to be determined.

Keywords: hippocampal plasticity, learning ability, memory, parental exercise

Procedia PDF Downloads 205

Authors: Felix Damilola Ajibade, Opeyemi O. Enoch, Taiwo Paul Fajusigbe

Abstract:

This paper is centered on conducting an inquiry into the stability of the F* iterative algorithm to the fixed point of a strongly pseudo-contractive mapping in the framework of uniformly convex Banach spaces. To achieve the desired result, certain existing inequalities in convex Banach spaces were utilized, as well as the stability criteria of Harder and Hicks. Other necessary conditions for the stability of the F* algorithm on strong pseudo-contractive mapping were also obtained. Through a numerical approach, we prove that the F* iterative algorithm is H-stable for strongly pseudo-contractive mapping. Finally, the solution of the mixed-type Volterra-Fredholm functional non-linear integral equation is estimated using our results.

Keywords: stability, F* -iterative algorithm, pseudo-contractive mappings, uniformly convex Banach space, mixed-type Volterra-Fredholm integral equation

Procedia PDF Downloads 95

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 65

Authors: R. J. Chang

Abstract:

A cyclostationary Gaussian linearization method is formulated for investigating the time average response of nonlinear system under sinusoidal signal and white noise excitation. The quantitative measure of cyclostationary mean, variance, spectrum of mean amplitude, and mean power spectral density of noise is analyzed. The qualitative response behavior of stochastic jump and bifurcation are investigated. The validity of the present approach in predicting the quantitative and qualitative statistical responses is supported by utilizing Monte Carlo simulations. The present analysis without imposing restrictive analytical conditions can be directly derived by solving non-linear algebraic equations. The analytical solution gives reliable quantitative and qualitative prediction of mean and noise response for the Duffing system subjected to both sinusoidal signal and white noise excitation.

Keywords: cyclostationary, duffing system, Gaussian linearization, sinusoidal, white noise

Procedia PDF Downloads 478

Authors: E. Shahsavari, R. Ghasemi, A. Akramizadeh

Abstract:

This paper presents a new method to design nonlinear feedback linearization controller for polymer electrolyte membrane fuel cells (PEMFCs). A nonlinear controller is designed based on nonlinear model to prolong the stack life of PEM fuel cells. Since it is known that large deviations between hydrogen and oxygen partial pressures can cause severe membrane damage in the fuel cell, feedback linearization is applied to the PEM fuel cell system so that the deviation can be kept as small as possible during disturbances or load variations. To obtain an accurate feedback linearization controller, tuning the linear parameters are always important. So in proposed study NSGA_II method was used to tune the designed controller in aim to decrease the controller tracking error. The simulation result showed that the proposed method tuned the controller efficiently.

Keywords: nonlinear dynamic model, polymer electrolyte membrane fuel cells, feedback linearization, optimal control, NSGA_II

Procedia PDF Downloads 511

Authors: Abolfazl Zaraki, Yoshikatsu Hayashi, Harry Thorpe, Vincent Strong, Gisle-Andre Larsen, William Holderbaum

Abstract:

Thanks to the high maneuverability of the cable-driven hyper-redundant manipulators (HRMs), this class of robots has shown a superior capability in highly confined and unstructured space applications. Although the large number of degrees of freedom (DOF) of HRMs enhances the motion flexibility and the robot’s reachability range, it highly increases the complexity of the kinematic configuration which makes the kinematic control problem very challenging or even impossible to solve. This paper presents our current progress achieved on the development of a kinematic-based leader-follower control system which is designed to control not only the robot’s body posture but also to control the trajectory of the robot’s movement in a semi-autonomous manner (the human operator is retained in the robot’s control loop). To obtain the forward kinematic model, the coordinate frames are established by the classical Denavit–Hartenburg (D-H) convention for a hyper-redundant serial manipulator which has a controlled cables-driven mechanism. To solve the inverse kinematics of the robot, unlike the conventional methods, a leader-follower mechanism, based on the sequential inverse kinematic, is followed. Using this mechanism, the inverse kinematic problem is solved for all sequential joints starting from the head joint to the base joint of the robot. To verify the kinematic design and simulate the robot motion, the MATLAB robotic toolbox is used. The simulation result demonstrated the promising capability of the proposed leader-follower control system in controlling the robot motion and trajectory in our confined space application.

Keywords: hyper-redundant robots, kinematic analysis, semi-autonomous control, serial manipulators

Procedia PDF Downloads 153

Authors: Akram Alfantazi, Tirdad Nickchi

Abstract:

Magnesium galvanic corrosion plays an important role in the commercialization of Mg alloys in the automobile industry. This study aims at visualizing the electrochemical activity of the magnesium surface being coupled with pure iron in sulfate-chloride solutions. Scanning electrochemical microscopy was used to monitor the chemical activity of the surface and the data was compared with the conventional corrosion results such as potentiodynamic polarization, linear polarization, and immersion tests. The SECM results showed that the chemical reactivity of Mg is higher than phosphate-permanganate-coated Mg. Regions in the vicinity of the galvanic couple boundary are very active in the magnesium phase and fully protected in the iron phase. Scanning electrochemical microscopy results showed that the conversion coating provided good corrosion resistance for magnesium in the short-term but fails at long-term testing.

Keywords: corrosion, galvanic corrosion, magnesium, scanning electrochemical microscopy

Procedia PDF Downloads 284

Authors: Walter M. Millanzi, Stephen M. Kibusi

Abstract:

Background: Currently, there has been a progressive shortage not only to the number but also the quality of medical practitioners for the most of nursing. Despite that, those who are present exhibit unethical and illegal practices, under standard care and malpractices. The concern is raised in the ways they are prepared, or there might be something missing in nursing curricula or how it is delivered. There is a need for transforming or testing new teaching modalities to enhance competent health workforces. Objective: to investigate the Effect of Facilitation in a Problem-based Environment (FPBE) on metacognition, self-directed learning and learning motivation to undergraduate nurse student in Tanzanian higher learning institutions. Methods: quasi-experimental study (quantitative research approach). A purposive sampling technique was employed to select institutions and achieving a sample size of 401 participants (interventional = 134 and control = 267). Self-administered semi-structured questionnaire; was the main data collection methods and the Statistical Package for Service Solution (v. 20) software program was used for data entry, data analysis, and presentations. Results: The pre-post test results between groups indicated noticeably significant change on metacognition in an intervention (M = 1.52, SD = 0.501) against the control (M = 1.40, SD = 0.490), t (399) = 2.398, p < 0.05). SDL in an intervention (M = 1.52, SD = 0.501) against the control (M = 1.40, SD = 0.490), t (399) = 2.398, p < 0.05. Motivation to learn in an intervention (M = 62.67, SD = 14.14) and the control (n = 267, M = 57.75), t (399) = 2.907, p < 0.01). A FPBE teaching pedagogy, was observed to be effective on the metacognition (AOR = 1.603, p < 0.05), SDL (OR = 1.729, p < 0.05) and Intrinsic motivation in learning (AOR = 1.720, p < 0.05) against conventional teaching pedagogy. Needless, was less likely to enhance Extrinsic motivation (AOR = 0.676, p > 0.05) and Amotivation (AOR = 0.538, p > 0.05). Conclusion and recommendation: FPBE teaching pedagogy, can improve student’s metacognition, self-directed learning and intrinsic motivation to learn among nurse students. Nursing curricula developers should incorporate it to produce 21st century competent and qualified nurses.

Keywords: facilitation, metacognition, motivation, self-directed

Procedia PDF Downloads 184

Authors: Abdelhadi Elharfi

Abstract:

A problem of boundary feedback (exponential) stabilization of an overhead crane model represented by a PDE is considered. For any $r>0$, the exponential stability at the desired decay rate $r$ is solved in semi group setting by a collocated-type stabiliser of a target system combined with a term involving the solution of an appropriate PDE.

Keywords: feedback stabilization, semi group and generator, overhead crane system

Procedia PDF Downloads 401

Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi

Abstract:

This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.

Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles

Procedia PDF Downloads 276

Authors: Mohamad Mohsen Homayouni, Niloofar Taghipour, Ahmad Reza Memar, Niloofar Khalaji, Hamed Kiani, Seyyed Javad Seyyed Tabaei

Abstract:

Background and Objective: Cryptosporidium is a coccidian protozoan parasite; its oocysts in surface water are a global health problem. Due to the low number of parasites in the water resources and the lack of laboratory culture, rapid and sensitive method for detection of the organism in the water resources is necessarily required. We applied modified acid-fast staining and PCR for the detection of the Cryptosporidium spp. and analysed the genotypes in 55 samples collected from surface water. Methods: Over a period of nine months, 55 surface water samples were collected from the five rivers in Tehran, Iran. The samples were filtered by using cellulose acetate membrane filters. By acid fast method, initial identification of Cryptosporidium oocyst were carried out on surface water samples. Then, nested PCR assay was designed for the specific amplification and analysed the genotypes. Results: Modified Ziehl-Neelsen method revealed 5–20 Cryptosporidium oocysts detected per 10 Liter. Five out of the 55 (9.09%) surface water samples were found positive for Cryptosporidium spp. by Ziehl-Neelsen test and seven (12.7%) were found positive by nested PCR. The staining results were consistent with PCR. Seven Cryptosporidium PCR products were successfully sequenced and five gp60 subtypes were detected. Our finding of gp60 gene revealed that all of the positive isolates were Cryptosporidium parvum and belonged to subtype families IIa and IId. Conclusion: Our investigations were showed that collection of water samples were contaminated by Cryptosporidium, with potential hazards for the significant health problem. This study provides the first report on detection and genotyping of Cryptosporidium species from surface water samples in Iran, and its result confirmed the low clinical incidence of this parasite on the community.

Keywords: Cryptosporidium spp., membrane filtration, subtype, surface water, Iran

Procedia PDF Downloads 406

Authors: Salma Aboussalam, Karima Khalil, Khalid Elkalay

Abstract:

An Ecopath model was employed to investigate the trophic structure, function, and current state of the Moroccan Mediterranean Sea ecosystem. The model incorporated 31 functional groups, including 21 fish species, 7 invertebrates, 2 primary producers, and a detritus group. The trophic interactions among these groups were analyzed, revealing an average trophic transfer efficiency of 23%. The results indicated that the ecosystem produced more energy than it consumed, with high respiration and consumption rates. Indicators of stability and development were low for the Finn cycle index (13.97), system omnivory index (0.18), and average Finn path length (3.09), indicating a disturbed ecosystem with a linear trophic structure. Keystone species were identified through the use of the keystone index and mixed trophic impact analysis, with demersal invertebrates, zooplankton, and cephalopods found to have a significant impact on other groups.

Keywords: Ecopath, food web, trophic flux, Moroccan Mediterranean Sea

Procedia PDF Downloads 96

Authors: Allé Dieng, Mamadou Bousso, Latif Dramani

Abstract:

The purpose of this work is to show the complexity behind economical interrelations in a country and provide a linear dynamic model of economical dependency evolution in a country. The model is based on National Transfer Account which is one of the most robust methodology developed in order to measure a level of demographic dividend captured in a country. It is built upon three major factors: demography, economical dependency and migration. The established mathematical model has been simulated using Netlogo software. The innovation of this study is in describing economical dependency as a complex system and simulating using mathematical equation the evolution of the two populations: the economical dependent and the non-economical dependent as defined in the National Transfer Account methodology. It also allows us to see the interactions and behaviors of both populations. The model can track individual characteristics and look at the effect of birth and death rates on the evolution of these two populations. The developed model is useful to understand how demographic and economic phenomenon are related

Keywords: ABM, demographic dividend, National Transfer Accounts (NTA), ODE

Procedia PDF Downloads 193

Authors: Soner Cubuk, Mirgul Kosif, M. Vezir Kahraman, Ece Kok Yetimoglu

Abstract:

Boron is an essential trace element for the completion of the life circle for organisms. Suitable methods for the determination of boron have been proposed, including acid - base titrimetric, inductively coupled plasma emission spectroscopy flame atomic absorption and spectrophotometric. However, the above methods have some disadvantages such as long analysis times, requirement of corrosive media such as concentrated sulphuric acid and multi-step sample preparation requirements and time-consuming procedures. In this study, a selective and reusable fluorescent sensor for boron based on glycosyloxyethyl methacrylate was prepared by photopolymerization. The response characteristics such as response time, pH, linear range, limit of detection were systematically investigated. The excitation/emission maxima of the membrane were at 378/423 nm, respectively. The approximate response time was measured as 50 sec. In addition, sensor had a very low limit of detection which was 0.3 ppb. The sensor was successfully used for the determination of boron in water samples with satisfactory results.

Keywords: boron, fluorescence, photopolymerization, polymeric sensor

Procedia PDF Downloads 277

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 83

Authors: Golamhassan Ghahramani Aghdam, Pedram Bavili Tabrizi

Abstract:

The aim of this research is to investigate the relationship between accounting information and the value of the companies accepted in Tehran Exchange Market. The dependent variable in this research is the value of a company that is measured by price coefficients, and the independent variables are balance sheet information, profit and loss information, cash flow state information, and profit quality characteristics. The profit quality characteristic index is to be related and to be on-time. This research is an application research, and the research population includes all companies that are active in Tehran exchange market. The number of 194 companies was selected by the systematic method as the statistics sample in the period of 2018-2019. The multi-variable linear regression model was used for the hypotheses test. The results show that there is no relationship between accounting information and companies’ value (stock value) that can be due to the lack of efficiency of the investment market and the inability to use the accounting information by investment market activists.

Keywords: accounting information, company value, profit quality characteristics, price coefficient

Procedia PDF Downloads 132

Authors: Jee-Sang Kim, Jong Ho Park

Abstract:

Geopolymer concretes are a new class of construction materials that have emerged as an alternative to Ordinary Portland cement concrete. Considerable researches have been carried out on material development of geopolymer concrete, however, a few studies have been reported on the structural use of them. This paper presents the bond behaviors of reinforcement embedded in fly ash based geopolymer concrete. The development lengths of reinforcement for various compressive strengths of concrete, 20, 30 and 40 MPa, and reinforcement diameters, 10, 16, and 25 mm are investigated. Total 27 specimens were manufactured and pull-out test according to EN 10080 was applied to measure bond strength and slips between concrete and reinforcements. The average bond strengths decreased from 23.06MPa to 17.26 MPa, as the diameters of reinforcements increased from 10mm to 25mm. The compressive strength levels of geopolymer concrete showed no significant influence on bond strengths in this study. Also, the bond-slip relations between geopolymer concrete and reinforcement are derived using non-linear regression analysis for various experimental conditions.

Keywords: bond-slip relation, bond strength, geopolymer concrete, pull-out test

Procedia PDF Downloads 344

Authors: Sally Selden, Jyoti Aggarwal

Abstract:

The research on generational expectations about leadership is developing, but little scholarship exists on this topic for public sector organizations. Given the size of the federal workforce, this research study fills an important gap in the knowledge base and will inform public organizations how to approach managing and leading a multigenerational workforce. The research objectives of this study are to explore leadership preferences and motivation within generations and to determine whether these qualities differ by type of federal agency (e.g., law enforcement, human services, etc.). This paper will review the research on generational differences, expectations, and leadership with a focus on studies of public organizations. Using hierarchical linear modeling (HLM), this study will examine how leadership and motivation vary by generation in the federal government workforce, controlling for other demographic characteristics. The study will also examine whether generational differences impact satisfaction and performance. The study will utilize the 2019 Federal Employee Viewpoint Survey.

Keywords: multigenerational workforce, leadership, generational differences, federal workforce

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Authors: Ehsan Sadie

Abstract:

Developments in the field of damping technology and advances in the area of dampers in equipping many structures have been the result of efforts and testing by researchers in this field. In this paper, a sample of a two-story building is simulated with the help of SAP2000 software, and the effect of a viscous damper on the performance of the structure is explained. The effect of dampers on the response of the structure is investigated. This response involves the horizontal displacement of floors. In this case, the structure is modeled once without a damper and again with a damper. In this regard, the results are presented in the form of tables and graphs. Since the seismic behavior of the structure is studied, the responses show the appropriate effect of viscous dampers in reducing the displacement of floors, and also the energy dissipation in the structure with dampers compared to structures without dampers is significant. Therefore, it is economical to use viscous dampers in areas that have a higher relative earthquake risk.

Keywords: bending frame, displacement criterion, dynamic response spectra, earthquake, non-linear history spectrum, SAP2000 software, structural response, viscous damper

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Authors: Shuenn-Yih Chang, Chiu-Li Huang

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Three structure-dependent integration methods have been developed for solving equations of motion, which are second-order ordinary differential equations, for structural dynamics and earthquake engineering applications. Although they generally have the same numerical properties, such as explicit formulation, unconditional stability and second-order accuracy, a different performance is found in solving the free vibration response to either linear elastic or nonlinear systems with high frequency modes. The root cause of this different performance in the free vibration responses is analytically explored herein. As a result, it is verified that a weak instability is responsible for the different performance of the integration methods. In general, a weak instability will result in an inaccurate solution or even numerical instability in the free vibration responses of high frequency modes. As a result, a weak instability must be prohibited for time integration methods.

Keywords: dynamic analysis, high frequency, integration method, overshoot, weak instability

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Authors: Ofole Ndidi

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Context: Empirical studies show that through dual primary attachment mothers and fathers contribute to children’s development and behaviours. While the contribution of mothers is well documented in past researches, fathers’ involvement in Nigeria has received much less attention. As such, exploring fathers’ involvement in sexual behaviours will provide insight for policy implementation and programming designed to delay sexual debut among sexually inexperienced young people in Nigeria. Objective of study: This study examined the extent to which father involvement (father’s parenting style, attitude, father-child communication, father’s marital status, and father’s socio-economic status) could predict delay in sexual debut of a representative sample of Nigeria adolescents in lower secondary. Materials and Methods: Multistage sampling technique was adopted to draw a cross section of 1023 adolescents with the age range of 10-23 years and mean years of 12±2.1 who reported sexually inexperience from six geographical zones in Nigeria. Multiple Regressions was used to analyze the data collected with four standardized self-report measures at 0.05 level of significance. Results: Findings of this study revealed that the independent variables (father’s parenting style, paternal attitudes, paternal–child communication, paternal marital status and paternal socio–economic status) contributed significantly to the delay of sexual debut. However, fathers’ attitude made the most potent contribution (β = 0.255, P < 0.05). Conclusions: The outcomes of this study have implications for programs that are designed to reduce high-risk behaviors among adolescents. It concluded that sexuality education and interventions should involve the fathers in a more integrated and collaborative fashion.

Keywords: father, sexual debut, adolescents, Nigeria

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Authors: Slavica P. Petrovic

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One of the key dimensions of management problems in organizations refers to the relations between stakeholders. The management problems that are characterized by conflict and coercion, in which participants do not agree on the ends and means, in which different groups, i.e., individuals, strive to – using the power they have – impose on others their favoured strategy and decisions represent the relevant research subject. Creatively managing the coercive problems in organizations, in which the sources of power can be identified, implies the emancipatory paradigm and the use of corresponding systems methodology. The main research aim is to critically reassess the theoretical foundations and methodological and methodical development of Critical Systems Heuristics (CSH) – as a valid representative of the emancipatory paradigm – in order to determine the conditions, ways, and achievements of its application in managing the coercive problems in organizations. The basic hypothesis is that CSH, as the emancipatory methodology, given its own theoretical foundations and methodological-methodical development, can be employed in a scientifically based and practically useful manner in creative addressing the coercive problems. The scientific instrumentarium corresponding to this research aim is critical systems thinking with its three key commitments to: a) Critical awareness of the strengths and weaknesses of each research instrument (theory, methodology, method, technique, model) for structuring the problem situations in organizations, b) Improvement of managing the coercive problems in organizations, and c) Pluralism – respect the different perceptions and interpretations of problem situations, and enable the combined use of research instruments. The relevant research result is that CSH – considering its theoretical foundations, methodological and methodical development – enables to reveal the normative content of the proposed or existing designs of organizational systems. Accordingly, it can be concluded that through the use of critically heuristic categories and dialectical debate between those involved and those affected by the designs, but who are not included in designing organizational systems, CSH endeavours to – in the application – support the process of improving position of all stakeholders.

Keywords: coercion and conflict in organizations, creative management, critical systems heuristics, the emancipatory systems methodology

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Authors: Saba Riaz, Syed A. Hussain

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This paper is addressing the estimation method of the unknown population variance of the variable of interest. A new generalized class of estimators of the finite population variance has been suggested using the auxiliary information. To improve the precision of the proposed class, known population variance of the auxiliary variable has been used. Mathematical expressions for the biases and the asymptotic variances of the suggested class are derived under large sample approximation. Theoretical and numerical comparisons are made to investigate the performances of the proposed class of estimators. The empirical study reveals that the suggested class of estimators performs better than the usual estimator, classical ratio estimator, classical product estimator and classical linear regression estimator. It has also been found that the suggested class of estimators is also more efficient than some recently published estimators.

Keywords: study variable, auxiliary variable, finite population variance, bias, asymptotic variance, percent relative efficiency

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Authors: Renata Masarova, Bohuslava Juhasova, Martin Juhas, Zuzana Sutova

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In dynamic system theory a mathematical model is often used to describe their properties. In order to find a transfer matrix of a dynamic system we need to calculate an inverse matrix. The paper contains the fusion of the classical theory and the procedures used in the theory of automated control for calculating the inverse matrix. The final part of the paper models the given problem by the Matlab.

Keywords: dynamic system, transfer matrix, inverse matrix, modeling

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Authors: Nino Paresashvili, Nino Abesadze

Abstract:

The modern world faces huge challenges. Globalization changed the socio-economic conditions of many countries. The current processes in the global environment have a different impact on countries with different cultures. However, an alleviation of poverty and improvement of living conditions is still the basic challenge for the majority of countries, because much of the population still lives under the official threshold of poverty. It is very important to stimulate youth employment. In order to prepare young people for the labour market, it is essential to provide them with the appropriate professional skills and knowledge. It is necessary to plan efficient activities for decreasing an unemployment rate and for developing the perfect mechanisms for regulation of a labour market. Such planning requires thorough study and analysis of existing reality, as well as development of corresponding mechanisms. Statistical analysis of unemployment is one of the main platforms for regulation of the labour market key mechanisms. The corresponding statistical methods should be used in the study process. Such methods are observation, gathering, grouping, and calculation of the generalized indicators. Unemployment is one of the most severe socioeconomic problems in Georgia. According to the past as well as the current statistics, unemployment rates always have been the most problematic issue to resolve for policy makers. Analytical works towards to the above-mentioned problem will be the basis for the next sustainable steps to solve the main problem. The results of the study showed that the choice of young people is not often due to their inclinations, their interests and the labour market demand. That is why the wrong professional orientation of young people in most cases leads to their unemployment. At the same time, it was shown that there are a number of professions in the labour market with a high demand because of the deficit the appropriate specialties. To achieve healthy competitiveness in youth employment, it is necessary to formulate regional employment programs with taking into account the regional infrastructure specifications.

Keywords: unemployment, analysis, methods, tendencies, regulation mechanisms

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