Search results for: applied pharmacology

Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

Procedia PDF Downloads 159

Authors: Catalina Iticescu, Lucian P. Georgescu, Mihaela Timofti, Gabriel Murariu

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Since the accumulation of large quantities of sewage sludge is producing serious environmental problems, numerous environmental specialists are looking for solutions to solve this problem. The sewage sludge obtained by treatment of municipal wastewater may be used as fertiliser on agricultural soils because such sludge contains large amounts of nitrogen, phosphorus and organic matter. In many countries, sewage sludge is used instead of chemical fertilizers in agriculture, this being the most feasible method to reduce the increasingly larger quantities of sludge. The use of sewage sludge on agricultural soils is allowed only with a strict monitoring of their physical and chemical parameters, because heavy metals exist in varying amounts in sewage sludge. Exceeding maximum permitted quantities of harmful substances may lead to pollution of agricultural soil and may cause their removal aside because the plants may take up the heavy metals existing in soil and these metals will most probably be found in humans and animals through food. The sewage sludge analyzed for the present paper was extracted from the Wastewater Treatment Station (WWTP) Galati, Romania. The physico-chemical parameters determined were: pH (upH), total organic carbon (TOC) (mg L⁻¹), N-total (mg L⁻¹), P-total (mg L⁻¹), N-NH₄ (mg L⁻¹), N-NO₂ (mg L⁻¹), N-NO₃ (mg L⁻¹), Fe-total (mg L⁻¹), Cr-total (mg L⁻¹), Cu (mg L⁻¹), Zn (mg L⁻¹), Cd (mg L⁻¹), Pb (mg L⁻¹), Ni (mg L⁻¹). The determination methods were electrometrical (pH, C, TSD) - with a portable HI 9828 HANNA electrodes committed multiparameter and spectrophotometric - with a Spectroquant NOVA 60 - Merck spectrophotometer and with specific Merck parameter kits. The tests made pointed out the fact that the sludge analysed is low heavy metal falling within the legal limits, the quantities of metals measured being much lower than the maximum allowed. The results of the tests made to determine the content of nutrients in the sewage sludge have shown that the existing nutrients may be used to increase the fertility of agricultural soils. Other tests were carried out on lands where sewage sludge was applied in order to establish the maximum quantity of sludge that may be used so as not to constitute a source of pollution. The tests were made on three plots: a first batch with no mud and no chemical fertilizers applied, a second batch on which only sewage sludge was applied, and a third batch on which small amounts of chemical fertilizers were applied in addition to sewage sludge. The results showed that the production increases when the soil is treated with sludge and small amounts of chemical fertilizers. Based on the results of the present research, a fertilization plan has been suggested. This plan should be reconsidered each year based on the crops planned, the yields proposed, the agrochemical indications, the sludge analysis, etc.

Keywords: agricultural use, crops, physico–chemical parameters, sewage sludge

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Authors: Luis Amador Jimenez, Md. Shohel Amin

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Pavement performance models are based on projections of observed traffic loads, which makes uncertain to study funding strategies in the long run if history does not repeat. Neural networks can be used to estimate deterioration rates but the learning rate and momentum have not been properly investigated, in addition, economic evolvement could change traffic flows. This study addresses both issues through a case study for roads of Montreal that simulates traffic for a period of 50 years and deals with the measurement error of the pavement deterioration model. Travel demand models are applied to simulate annual average daily traffic (AADT) every 5 years. Accumulated equivalent single axle loads (ESALs) are calculated from the predicted AADT and locally observed truck distributions combined with truck factors. A back propagation Neural Network (BPN) method with a Generalized Delta Rule (GDR) learning algorithm is applied to estimate pavement deterioration models capable of overcoming measurement errors. Linear programming of lifecycle optimization is applied to identify M&R strategies that ensure good pavement condition while minimizing the budget. It was found that CAD 150 million is the minimum annual budget to good condition for arterial and local roads in Montreal. Montreal drivers prefer the use of public transportation for work and education purposes. Vehicle traffic is expected to double within 50 years, ESALS are expected to double the number of ESALs every 15 years. Roads in the island of Montreal need to undergo a stabilization period for about 25 years, a steady state seems to be reached after.

Keywords: pavement management system, traffic simulation, backpropagation neural network, performance modeling, measurement errors, linear programming, lifecycle optimization

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Authors: Tariq Ahmad Dar, Moinuddin, M. Masroor A. Khan

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There is considerable need in enhancing the content and yield of active constituents of medicinal plants keeping in view their massive demand worldwide. Different strategies have been employed to enhance the active constituents of medicinal plants and the use of phytohormones has been proved effective in this regard. Gamma-irradiated Sodium alginate (ISA) is known to elicit an array of plant defense responses and biological activities in plants. Considering the medicinal importance, a pot experiment was conducted to explore the effect of ISA and phosphorus on growth, yield and quality of fenugreek (Trigonella foenum-graecum L.). ISA spray treatments (0, 40, 80 and 120 mg L-1) were applied alone and in combination with 40 kg P ha-1 (P40). Crop performance was assessed in terms of plant growth characteristics, physiological attributes, seed yield and the content of seed trigonelline. Of the ten-treatments, P40 + 80 mg L−1 of ISA proved the best. The results showed that foliar spray of ISA alone or in combination with P40 augmented the plant vegetative growth, enzymatic activities, trigonelline content, trigonelline yield and economic yield of fenugreek. Application of 80 mg L−1 of ISA applied with P40 gave the best results for almost all the parameters studied compared to control or to 80 mg L−1 of ISA applied alone. This treatment increased the total content of chlorophyll, carotenoids, leaf -N, -P and -K and trigonelline compared to the control by 24.85 and 27.40%, 15 and 23.52%, 18.70 and 16.84%, 15.88 and 18.92%, 12 and 14.44%, at 60 and 90 DAS respectively. The combined application of 80 mg L−1 of ISA along with P40 resulted in the maximum increase in seed yield, trigonelline content and trigonelline yield by146, 34 and 232.41%, respectively, over the control. Gel permeation chromatography revealed the formation of low molecular weight fractions in ISA samples, containing even less than 20,000 molecular weight oligomers, which might be responsible for plant growth promotion in this study. Trigonelline content was determined by reverse phase high performance liquid chromatography (HPLC) with C-18 column.

Keywords: gamma-irradiated sodium alginate, phosphorus, gel permeation chromatography, HPLC, trigonelline content, yield

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Authors: Alhulw H. Alshammari, Ahmed Iraqi, S. A. Saad, T. A. Taha

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In this work, we present for the first time the study of Raman spectra and dielectric relaxation of polyester polymer-CoFe₂O₄ (5.0, 10.0, 15.0, and 20.0 wt%) nanocomposites. Raman spectroscopy was applied as a sensitive structural identification technique to characterize the polyester-CoFe₂O₄ nanocomposites. The images of AFM confirmed the uniform distribution of CoFe₂O₄ inside the polymer matrix. Dielectric relaxation was employed as an important analytical technique to obtain information about the ability of the polymer nanocomposites to store and filter electrical signals. The dielectric relaxation analyses were carried out on the polyester-CoFe₂O₄ nanocomposites at different temperatures. An increase in dielectric constant ε₁ was observed for all samples with increasing temperatures due to the alignment of the electric dipoles with the applied electric field. In contrast, ε₁ decreased with increasing frequency. This is attributed to the difficulty for the electric dipoles to follow the electric field. The α relaxation peak that appeared at a high frequency shifted to higher frequencies when increasing the temperature. The activation energies for Maxwell-Wagner Sillar (MWS) changed from 0.84 to 1.01 eV, while the activation energies for α relaxations were 0.54 – 0.94 eV. The conduction mechanism for the polyester- CoFe₂O₄ nanocomposites followed the correlated barrier hopping (CBH) model.

Keywords: AC conductivity, activation energy, dielectric permittivity, polyester nanocomposites

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Authors: Mont Kumpugdee-Vollrath, Khaled Abdallah

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Liposomes and pegylated liposomes were widely used as drug delivery system in pharmaceutical field since a long time. However, in the former time, polyethylene glycol (PEG) was connected into phospholipid after the liposomes were already prepared. In this paper, we intend to study the possibility of applying phospholipids which already connected with PEG and then they were used to prepare liposomes. The model drug resveratrol was used because it can be applied against different diseases. Cholesterol was applied to stabilize the membrane of liposomes. The thin film technique in a laboratory scale was a preparation method. The liposomes were then characterized by nanoparticle tracking analysis (NTA), photon correlation spectroscopy (PCS) and light microscopic techniques. The stable liposomes can be produced and the particle sizes after filtration were in nanometers. The 2- and 3-chains-PEG-phospholipid (PL) caused in smaller particle size than the 4-chains-PEG-PL. Liposomes from PL 90G and cholesterol were stable during storage at 8 °C of 56 days because the particle sizes measured by PCS were almost not changed. There was almost no leakage of resveratrol from liposomes PL 90G with cholesterol after diffusion test in dialysis tube for 28 days. All liposomes showed the sustained release during measuring time of 270 min. The maximum release amount of 16-20% was detected with liposomes from 2- and 3-chains-PEG-PL. The other liposomes gave max. release amount of resveratrol only of 10%. The release kinetic can be explained by Korsmeyer-Peppas equation. 

Keywords: liposome, NTA, resveratrol, pegylation, cholesterol

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Authors: Nasim Babazadeh

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Growing demand for a quieter dwelling environment has turned the attention of construction companies to reducing the propagated noise of their project. In inner-city constructions, close distance between the construction site and surrounding buildings lessens the efficiency of passive noise control methods. Dwellers of the nearby areas may file complaints and lawsuits against the construction companies due to the emitted construction noise, thereby leading to the interruption of processes, compensation costs, or even suspension of the project. Therefore, construction noise should be predicted along with the project schedule. The advantage of managing the noise in the pre-construction phase is two-fold. Firstly, changes in the time plan and construction methods can be applied more flexibly. Thus, the costs related to rescheduling can be avoided. Secondly, noise-related legal problems are expected to be reduced. To implement noise mapping methods for the mentioned prediction, the required detailed information (such as the location of the noisy process, duration of the noisy work) can be exported from the 4D BIM model. The results obtained from the noise maps would be used to help the planners to define different work scenarios. The proposed approach has been applied for the foundation and earthwork of a site located in a residential area, and the obtained results are discussed.

Keywords: building information modeling, construction noise management, noise mapping, 4D BIM

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Authors: Mai Abdul Latif, Yuntian Feng

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Applied Element Method (AEM) is a method that was developed to aid in the analysis of the collapse of structures. Current available methods cannot deal with structural collapse accurately; however, AEM can simulate the behavior of a structure from an initial state of no loading until collapse of the structure. The elements in AEM are connected with sets of normal and shear springs along the edges of the elements, that represent the stresses and strains of the element in that region. The elements are rigid, and the material properties are introduced through the spring stiffness. Nonlinear dynamic analysis has been widely modelled using the finite element method for analysis of progressive collapse of structures; however, difficulties in the analysis were found at the presence of excessively deformed elements with cracking or crushing, as well as having a high computational cost, and difficulties on choosing the appropriate material models for analysis. The Applied Element method is developed and coded to significantly improve the accuracy and also reduce the computational costs of the method. The scheme works for both linear elastic, and nonlinear cases, including elasto-plastic materials. This paper will focus on elastic and elasto-plastic material behaviour, where the number of springs required for an accurate analysis is tested. A steel cantilever beam is used as the structural element for the analysis. The first modification of the method is based on the Gaussian Quadrature to distribute the springs. Usually, the springs are equally distributed along the face of the element, but it was found that using Gaussian springs, only up to 2 springs were required for perfectly elastic cases, while with equal springs at least 5 springs were required. The method runs on a Newton-Raphson iteration scheme, and quadratic convergence was obtained. The second modification is based on adapting the number of springs required depending on the elasticity of the material. After the first Newton Raphson iteration, Von Mises stress conditions were used to calculate the stresses in the springs, and the springs are classified as elastic or plastic. Then transition springs, springs located exactly between the elastic and plastic region, are interpolated between regions to strictly identify the elastic and plastic regions in the cross section. Since a rectangular cross-section was analyzed, there were two plastic regions (top and bottom), and one elastic region (middle). The results of the present study show that elasto-plastic cases require only 2 springs for the elastic region, and 2 springs for the plastic region. This showed to improve the computational cost, reducing the minimum number of springs in elasto-plastic cases to only 6 springs. All the work is done using MATLAB and the results will be compared to models of structural elements using the finite element method in ANSYS.

Keywords: applied element method, elasto-plastic, Gaussian springs, nonlinear

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Authors: Mesfin Nigussie Ibido

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The study is designed to explore the effects of land certification in securing women’s land rights of two rural villages in Robe district at Arsi Zone of Oromia regional state. The land is very critical assets for human life survival and the backbone for rural women livelihood. Equal access and control power to the land have given a chance for rural women to participate in different economic activities and improve their bargaining ability for decision making on their rights. Unfortunately, women were discriminated and marginalized from access and control of land for centuries through customary practices. However, in many countries, legal reform is used as a powerful tool for eliminating discriminatory provisions in property rights. Among other equity and efficiency concerns, the land certification program in Ethiopia attempts to address gender bias concerns of the current land-tenure system. The existed rural land policy was recognizing a women land rights and benefited by strengthened wives awareness of their land rights and contribute to the strong involvement of wives in decision making. However, harmful practices and policy implementation problems still against women do not fully exercise a provision of land rights in a different area of the country. Thus, this study is carried out to examine the effect of land certification in securing women’s land rights by eliminating the discriminatory nature of cultural abuses of study areas. Probability and non-probability sampling types were used, and the sample size was determined by using the sampling distribution of the proportion method. Systematic random sampling method was applied by taking the nth element of the sample frame. Both quantitative and qualitative research methods were applied, and survey respondents of 192 households were conducted and administering questionnaires in the quantitative method. The qualitative method was applied by interviews with focus group discussions with rural women, case stories, Village, and relevant district offices. Triangulation method was applied in data collection, data presentation and in the analysis of findings. Study finding revealed that the existence of land certification is affected by rural women positively by advancing their land rights, but still, some women are challenged by unsolved problems in the study areas. The study forwards recommendation on the existed problems or gaps to ensure women’s equal access to and control over land in the study areas.

Keywords: decision making, effects, land certification, land right, tenure security

Procedia PDF Downloads 207

Authors: Pratap Sriram Sundar, Chandan Chowdhury, Sagar Kamarthi

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Nature has perfected her designs over 3.5 billion years of evolution. Research fields such as biomimicry, biomimetics, bionics, bio-inspired computing, and nature-inspired designs have explored nature-made artifacts and systems to understand nature’s mechanisms and intelligence. Learning from nature, the researchers have generated sustainable designs and innovation in a variety of fields such as energy, architecture, agriculture, transportation, communication, and medicine. Axiomatic design offers a method to judge if a design is good. This paper analyzes design aspects of one of the nature’s amazing object: chicken egg. The functional requirements (FRs) of components of the object are tabulated and mapped on to nature-chosen design parameters (DPs). The ‘independence axiom’ of the axiomatic design methodology is applied to analyze couplings and to evaluate if eggs’ design is good (i.e., uncoupled design) or bad (i.e., coupled design). The analysis revealed that eggs design is a good design, i.e., uncoupled design. This approach can be applied to any nature’s artifacts to judge whether their design is a good or a bad. This methodology is valuable for biomimicry studies. This approach can also be a very useful teaching design consideration of biology and bio-inspired innovation.

Keywords: uncoupled design, axiomatic design, nature design, design evaluation

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Authors: Peter Sabev, Katalina Grigorova

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Test automation allows performing difficult and time consuming manual software testing tasks efficiently, quickly and repeatedly. However, development and maintenance of automated tests is expensive, so it needs a proper prioritization what to automate first. This paper describes a simple yet efficient approach for such prioritization of test cases based on the effort needed for both manual execution and software test automation. The suggested approach is very flexible because it allows working with a variety of assessment methods, and adding or removing new candidates at any time. The theoretical ideas presented in this article have been successfully applied in real world situations in several software companies by the authors and their colleagues including testing of real estate websites, cryptographic and authentication solutions, OSGi-based middleware framework that has been applied in various systems for smart homes, connected cars, production plants, sensors, home appliances, car head units and engine control units (ECU), vending machines, medical devices, industry equipment and other devices that either contain or are connected to an embedded service gateway.

Keywords: automated testing, manual testing, test automation, software testing, test prioritization

Procedia PDF Downloads 335

Authors: Naira Sahakyan, Margarit Petrosyan, Armen Trchounian

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One of the tasks in contemporary biotechnology, pharmacology and other fields of human activities is to obtain biologically active substances from plants. They are very essential in the treatment of many diseases due to their actually high therapeutic value without visible side effects. However, sometimes the possibility of obtaining the metabolites is limited due to the reduction of wild-growing plants. That is why the plant cell cultures are of great interest as alternative sources of biologically active substances. Besides, during the monitored cultivation, it is possible to obtain substances that are not synthesized by plants in nature. Isolated culture of Ajuga genevensis with high growth activity and ability of regeneration was obtained using MS nutrient medium. The agar-diffusion method showed that aqueous extracts of callus culture revealed high antimicrobial activity towards various gram-positive (Bacillus subtilis A1WT; B. mesentericus WDCM 1873; Staphylococcus aureus WDCM 5233; Staph. citreus WT) and gram-negative (Escherichia coli WKPM M-17; Salmonella typhimurium TA 100) microorganisms. The broth dilution method revealed that the minimal and half maximal inhibitory concentration values against E. coli corresponded to the 70 μg/mL and 140 μg/mL concentration of the extract respectively. According to the photochemiluminescent analysis, callus tissue extracts of leaf and root origin showed higher antioxidant activity than the same quantity of A. genevensis intact plant extract. A. genevensis intact plant and callus culture extracts showed no cytotoxic effect on K-562 suspension cell line of human chronic myeloid leukemia. The GC-MS analysis showed deep differences between the qualitative and quantitative composition of callus culture and intact plant extracts. Hexacosane (11.17%); n-hexadecanoic acid (9.33%); and 2-methoxy-4-vinylphenol (4.28%) were the main components of intact plant extracts. 10-Methylnonadecane (57.0%); methoxyacetic acid, 2-tetradecyl ester (17.75%) and 1-Bromopentadecane (14.55%) were the main components of A. genevensis callus culture extracts. Obtained data indicate that callus culture of A. genevensis can be used as an alternative source of biologically active substances.

Keywords: Ajuga genevensis, antibacterial activity, antioxidant activity, callus cultures

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Authors: L. Parisi

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In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.

Keywords: kinemic gait data, neural networks, hip joint implant, hip arthroplasty, rehabilitation engineering

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Authors: Amanda Aliende da Matta, Maria del Pilar Fogueiras Bertomeu, Valeria de Ormaechea Otalora, Maria Paz Sandin Esteban, Miriam Comet Donoso

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This communication presents the preliminary emerging themes in a research on political participation of young women. The study follows a qualitative methodology; in particular, the applied hermeneutic phenomenological method, and the general objective of the research is to give an account of the experience of political participation as young women. The study participants are women aged 18 to 35 who have experience in political participation. The techniques of data collection are the descriptive story and the phenomenological interview. With respect to the first methodological steps, these have been: 1) collect and select stories of lived experience in political participation, 2) select descriptions of lived experience (DLEs) in political participation of the chosen stories, 3) to prepare phenomenological interviews from the selected DLEs, 4) to conduct phenomenological thematic analysis (PTA) of the DLEs. We have so far initiated the PTA on 5 vignettes. Hermeneutic phenomenology as a research approach is based on phenomenological philosophy and applied hermeneutics. Phenomenology is a descriptive philosophy of pure experience and essences, through which we seek to capture an experience at its origins without categorizing, interpreting or theorizing it. Hermeneutics, on the other hand, may be defined as a philosophical current that can be applied to data analysis. Max Van Manen wrote that hermeneutic phenomenology is a method of abstemious reflection on the basic structures of the lived experience of human existence. In hermeneutic phenomenology we focus, then, on the way we experience “things” in the first person, seeking to capture the world exactly as we experience it, not as we categorize or conceptualize it. In this study, the empirical methods used were: Lived experience description (written) and conversational interview. For these short stories, participants were asked: “What was your lived experience of participation in politics as a young woman? Can you tell me any stories or anecdotes that you think exemplify or typify your experience?”. The questions were accompanied by a list of guidelines for writing descriptive vignettes. And the analytical method was PTA. Among the provisional results, we found preliminary emerging themes, which could in the advance of the investigation result in meaning structures of political participation of young women. They are the following: - Complicity may be inherent/essential in political participation as a young woman; - Feelings may be essential/inherent in political participation as a young woman; - Hope may be essential in authentic political participation as a young woman; - Frustration may be essential in authentic political participation as a young woman; - Satisfaction may be essential in authentic political participation as a young woman; - There may be tension between individual/collective inherent/essential in political participation as a young woman; - Political participation as a young woman may include moments of public demonstration.

Keywords: applied hermeneutic phenomenology, hermeneutics, phenomenology, political participation

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Authors: Kazuo Kiguchi, Kouta Ikegami

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In the case of physically weak persons, not only motor abilities, but also sensory abilities are sometimes deteriorated. The concept of perception-assist has been proposed to assist the sensory ability of the physically weak persons with a power-assist robot. Since upper-limb motion is very important in daily living, perception-assist for upper-limb motion has been proposed to assist upper-limb motion in daily living. A virtual tunnel was applied to modify the user’s upper-limb motion if it was necessary. In this paper, effective shape of the virtual tunnel which is applied in the perception-assist for upper-limb motion is proposed. Not only the position of the grasped tool but also the angle of the grasped tool are modified if it is necessary. Therefore, the upper-limb motion in daily living can be effectively modified to realize certain proper daily motion. The effectiveness of the proposed virtual tunnel was evaluated by performing the experiments.

Keywords: motion modification, power-assist robots, perception-assist, upper-limb motion

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Authors: Tamanna Goyal, Divya Bansal, Sanjeev Sofat

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In world-threatening terrorist attacks, where early detection, distinction, and prediction are effective diagnosis techniques and for functionally accurate and precise analysis of terrorism data, there are so many data mining & statistical approaches to assure accuracy. The computational extraction of derived patterns is a non-trivial task which comprises specific domain discovery by means of sophisticated algorithm design and analysis. This paper proposes an approach for similarity extraction by obtaining the useful attributes from the available datasets of terrorist attacks and then applying feature selection technique based on the statistical impurity measures followed by clustering techniques on the basis of similarity measures. On the basis of degree of participation of attributes in the rules, the associative dependencies between the attacks are analyzed. Consequently, to compute the similarity among the discovered rules, we applied a weighted similarity measure. Finally, the rules are grouped by applying using hierarchical clustering. We have applied it to an open source dataset to determine the usability and efficiency of our technique, and a literature search is also accomplished to support the efficiency and accuracy of our results.

Keywords: association rules, clustering, similarity measure, statistical approaches

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Authors: Kristina Pflug, Markus Busch

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Being able to predict polymer properties and processing behavior based on the applied operating reaction conditions in one of the key challenges in modern polymer reaction engineering. Especially, for cost-intensive processes such as the high-pressure polymerization of low-density polyethylene (LDPE) with high safety-requirements, the need for simulation-based process optimization and product design is high. A multi-scale modelling approach was set-up and validated via a series of high-pressure mini-plant autoclave reactor experiments. The approach starts with the numerical modelling of the complex reaction network of the LDPE polymerization taking into consideration the actual reaction conditions. While this gives average product properties, the complex polymeric microstructure including random short- and long-chain branching is calculated via a hybrid Monte Carlo-approach. Finally, the processing behavior of LDPE -its melt flow behavior- is determined in dependence of the previously determined polymeric microstructure using the branch on branch algorithm for randomly branched polymer systems. All three steps of the multi-scale modelling approach can be independently validated against analytical data. A triple-detector GPC containing an IR, viscosimetry and multi-angle light scattering detector is applied. It serves to determine molecular weight distributions as well as chain-length dependent short- and long-chain branching frequencies. 13C-NMR measurements give average branching frequencies, and rheological measurements in shear and extension serve to characterize the polymeric flow behavior. The accordance of experimental and modelled results was found to be extraordinary, especially taking into consideration that the applied multi-scale modelling approach does not contain parameter fitting of the data. This validates the suggested approach and proves its universality at the same time. In the next step, the modelling approach can be applied to other reactor types, such as tubular reactors or industrial scale. Moreover, sensitivity analysis for systematically varying process conditions is easily feasible. The developed multi-scale modelling approach finally gives the opportunity to predict and design LDPE processing behavior simply based on process conditions such as feed streams and inlet temperatures and pressures.

Keywords: low-density polyethylene, multi-scale modelling, polymer properties, reaction engineering, rheology

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Authors: Lukasz Mierczak, Patrick Denke, Piotr Klimczyk, Stefan Siebert

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Due to the high complexity of the magnetization in electrical machines and influence of the manufacturing processes on the magnetic properties of their components, the assessment and prediction of hysteresis and eddy current losses has remained a challenge. In the design process of electric motors and generators, the power losses of stators and rotors are calculated based on the material supplier’s data from standard magnetic measurements. This type of data does not include the additional loss from non-sinusoidal multi-harmonic motor excitation nor the detrimental effects of residual stress remaining in the motor laminations after manufacturing processes, such as punching, housing shrink fitting and winding. Moreover, in production, considerable attention is given to the measurements of mechanical dimensions of stator and rotor cores, whereas verification of their magnetic properties is typically neglected, which can lead to inconsistent efficiency of assembled motors. Therefore, to enable a comprehensive characterization of motor materials and components, Brockhaus Measurements developed a range of in-line and offline measurement technologies for testing their magnetic properties under actual motor operating conditions. Multiple sets of experimental data were obtained to evaluate the influence of various factors, such as elevated temperature, applied and residual stress, and arbitrary magnetization on the magnetic properties of different grades of non-oriented steel. Measured power loss for tested samples and stator cores varied significantly, by more than 100%, comparing to standard measurement conditions. Quantitative effects of each of the applied measurement were analyzed. This research and applied Brockhaus measurement methodologies emphasized the requirement for advanced characterization of magnetic materials used in electric drives and automotive applications.

Keywords: magnetic materials, measurement technologies, permanent magnets, stator and rotor cores

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Authors: Christian H. Sanabria-Montaña, Rodrigo Huerta-Quintanilla

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A lattice network is a special type of network in which all nodes have the same number of links, and its boundary conditions are periodic. The most basic lattice network is the ring, a one-dimensional network with periodic border conditions. In contrast, the Cartesian product of d rings forms a d-dimensional lattice network. An analytical expression currently exists for the clustering coefficient in this type of network, but the theoretical value is valid only up to certain connectivity value; in other words, the analytical expression is incomplete. Here we obtain analytically the clustering coefficient expression in d-dimensional lattice networks for any link density. Our analytical results show that the clustering coefficient for a lattice network with density of links that tend to 1, leads to the value of the clustering coefficient of a fully connected network. We developed a model on criminology in which the generalized clustering coefficient expression is applied. The model states that delinquents learn the know-how of crime business by sharing knowledge, directly or indirectly, with their friends of the gang. This generalization shed light on the network properties, which is important to develop new models in different fields where network structure plays an important role in the system dynamic, such as criminology, evolutionary game theory, econophysics, among others.

Keywords: clustering coefficient, criminology, generalized, regular network d-dimensional

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Authors: Mehdi Fuladipanah

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Sensitivity analysis as a technique is applied to determine influential input factors on model output. Variance-based sensitivity analysis method has more application compared to other methods because of including linear and non-linear models. In this paper, van Rijn’s movable bed roughness formula was selected to evaluate because of its reasonable results in sandy rivers. This equation contains four variables as: flow depth, sediment size,bBed form height and bed form length. These variable’s importance was determined using the first order of Fourier Amplitude Sensitivity Test. Sensitivity index was applied to evaluate importance of factors. The first order FAST based sensitivity indices test, explain 90% of the total variance that is indicating acceptance criteria of FAST application. More value of this index is indicating more important variable. Results show that bed form height, bed form length, sediment size and flow depth are more influential factors with sensitivity index: 32%, 24%, 19% and 15% respectively.

Keywords: sdensitivity analysis, variance, movable bed roughness formula, Sandy River

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Authors: Elif Tugce Aksun Tumerkan

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Fluorescent proteins (FPs) have become very popular since green fluorescent protein discovered from crystal jellyfish. It is known that Anthozoa species have a wide range of chromophore organisms, and the initial crystal structure for non-fluorescent chromophores obtained from the reef-building coral has been determined. There are also differently coloured pigments in non-bioluminescent Anthozoa zooxanthellate and azooxanthellate which are frequently members of the GFP-like protein family. The development of fluorescent proteins (FPs) and their applications is an outstanding example of basic science leading to practical biotechnological and medical applications. Fluorescent proteins have several applications in science and are used as important indicators in molecular biology and cell-based research. With rising interest in cell biology, FPs have used as biosensor indicators and probes in pharmacology and cell biology. Using fluorescent proteins in genetically encoded metabolite sensors has many advantages than chemical probes for metabolites such as easily introduced into any cell or organism in any sub-cellular localization and giving chance to fixing to fluoresce of different colours or characteristics. There are different factors effects to signalling mechanism when they used as a biosensor. While there are wide ranges of research have been done on the significance and applications of fluorescent proteins, the cell signalling response of FPs and target cell are less well understood. In this study, it was aimed to clarify the response of adaptive mechanisms of coral species such as pH, temperature and symbiotic relationship and target cells properties on the signalling capacity. Corals are a rich natural source of fluorescent proteins that change with environmental conditions such as light, heat stress and injury. Adaptation mechanism of coral species to these types of environmental variations is important factor due to FPs properties have affected by this mechanism. Since fluorescent proteins obtained from nature, their own ecological property like the symbiotic relationship is observed very commonly in coral species and living conditions have the impact on FPs efficiency. Target cell properties also have an effect on signalling and visualization. The dynamicity of detector that used for reading fluorescence and the level of background fluorescence are key parameters for the quality of the fluorescent signal. Among the factors, it can be concluded that coral species adaptive characteristics have the strongest effect on FPs signalling capacity.

Keywords: biosensor, cell biology, environmental conditions, fluorescent protein, sea anemone

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Authors: Zeina Bou Diab, Arij Daou

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The neural mechanisms of sequential behaviors are intensively studied, with songbirds a focus for learned vocal production. We are studying the premotor nucleus HVC at a nexus of multiple pathways contributing to song learning and production. The HVC consists of multiple classes of neuronal populations, each has its own cellular, electrophysiological and functional properties. During singing, a large subset of motor cortex analog-projecting HVCRA neurons emit a single 6-10 ms burst of spikes at the same time during each rendition of song, a large subset of basal ganglia-projecting HVCX neurons fire 1 to 4 bursts that are similarly time locked to vocalizations, while HVCINT neurons fire tonically at average high frequency throughout song with prominent modulations whose timing in relation to song remains unresolved. This opens the opportunity to define models relating explicit HVC circuitry to how these neurons work cooperatively to control learning and singing. We developed conductance-based Hodgkin-Huxley models for the three classes of HVC neurons (based on the ion channels previously identified from in vitro recordings) and connected them in several physiologically realistic networks (based on the known synaptic connectivity and specific glutaminergic and gabaergic pharmacology) via different architecture patterning scenarios with the aim to replicate the in vivo firing patterning behaviors. We are able, through these networks, to reproduce the in vivo behavior of each class of HVC neurons, as shown by the experimental recordings. The different network architectures developed highlight different mechanisms that might be contributing to the propagation of sequential neural activity (continuous or punctate) in the HVC and to the distinctive firing patterns that each class exhibits during singing. Examples of such possible mechanisms include: 1) post-inhibitory rebound in HVCX and their population patterns during singing, 2) different subclasses of HVCINT interacting via inhibitory-inhibitory loops, 3) mono-synaptic HVCX to HVCRA excitatory connectivity, and 4) structured many-to-one inhibitory synapses from interneurons to projection neurons, and others. Replication is only a preliminary step that must be followed by model prediction and testing.

Keywords: computational modeling, neural networks, temporal neural sequences, ionic currents, songbird

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Mateusz Mokrogulski, Piotr Śliwka

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The aim of this paper is the identification of periods of excessive credit growth in the Polish banking sector in years 2007-2014 using different methodologies. Due to the lack of precise guidance in CRD IV regarding methods of calculating the credit gap and related deviations from the long-term trends, a few filtering methods are applied, e.g. Hodrick-Prescott and Baxter-King. The solutions based on the switching model are also proposed. The next step represent computations of both the credit gap, and the counter cyclical capital buffer (CCB) rates on a quarterly basis. The calculations are carried out for the entire banking sector in Poland, as well as for its components (commercial and co-operative banks), and different types of loans. The calculations show vividly that in the analysed period there were the times of excessive credit growth. However, the results are different for the above mentioned sub-sectors. Of paramount importance here are mortgage loans, where the outcomes are distorted by high exchange rate fluctuations. The research on the CCB is now going to gain popularity as the buffer will soon become one of the tools of the macro prudential policy under CRD IV. Although the presented method is focused on the Polish banking sector, it can also be applied to other member states. Especially to the Central and Eastern European countries, that are usually characterized by smaller banking sectors compared to EU-15.

Keywords: countercyclical capital buffer, CRD IV, filtering methods, mortgage loans

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Authors: Djalal Boualili

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This article considers the problem of sizing prime movers for combined heating and power (CHP) systems operating at full load to satisfy a fraction of a facility's electric load, i.e. a base load. Prime mover sizing is examined using three criteria: operational cost, carbon dioxide emissions (CDE), and primary energy consumption (PEC). The sizing process leads to consider ratios of conversion factors applied to imported electricity to conversion factors applied to fuel consumed. These ratios are labelled RCost, R CDE, R PEC depending on whether the conversion factors are associated with operational cost, CDE, or PEC, respectively. Analytical results show that in order to achieve savings in operational cost, CDE, or PEC, the ratios must be larger than a unique constant R Min that only depends on the CHP components efficiencies. Savings in operational cost, CDE, or PEC due to CHP operation are explicitly formulated using simple equations. This facilitates the process of comparing the tradeoffs of optimizing the savings of one criterion over the other two – a task that has traditionally been accomplished through computer simulations. A hospital building, located in Chlef, Algeria, was used as an example to apply the methodology presented in this article.

Keywords: sizing, heating and power, ratios, energy consumption, carbon dioxide emissions

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Authors: Fatih Hattatoglu, Abdulrezzak Bakiş

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In this study, fiberless reactive powder concrete (RPC) was produced with high pressure and flexural strength. C30/37 concrete was chosen as the control sample. In this study, 9 different cure types were applied to fiberless RPC. the most suitable combined cure type was selected according to the pressure and flexure strength. Pressure and flexural strength tests were applied to these samples after curing. As a result of the study, the combined cure type with the highest pressure resistance was obtained. The highest pressure resistance was achieved with consecutive standard water cure at 20 °C for 7 days – hot water cure at 90 °C for 2 days - drying oven cure at 180 °C for 2 days. As a result of the study, the highest pressure resistance of fiberless RPC was found as 123 MPa with water cure at 20 °C for 7 days - hot water cure at 90 °C for 2 days - drying oven cure at 180 °C for 2 days; and the highest flexural resistance was found as 8.37 MPa for the same combined cure type.

Keywords: combined cure, flexural test, reactive powder concrete (RPC), rigid pavement, pressure test

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Authors: Somruedee Pongsena

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The purpose of this study is to follow up on the graduated students of Bachelor of Science in Applied Statistics from Suan Sunandha Rajabhat University (SSRU) during the 1999 – 2012 academic years and to provide the fundamental guideline for developing the current curriculum according to Thai Qualifications Framework for Higher Education (TQF: HEd). The sample was collected from 75 graduates by interview and online questionnaire. The content covered 5 subjects: ethics and moral, knowledge, cognitive skills, interpersonal skills and responsibility, numerical analysis as well as communication and information technology skills. Data were analyzed by using statistical methods as percentiles, means, standard deviation, t-tests, and F-tests. The findings showed that samples were mostly females younger than 26 years old. The majority of graduates had income in the range of 10,001-20,000 Baht and their experience range was 2-5 years. In addition, overall opinions from receiving knowledge to apply to work were at agree; mean score was 3.97 and standard deviation was 0.40. In terms of opinion difference, the hypothesis' testing results indicate gender only had different opinion at a significant level of 0.05.

Keywords: follow-up, graduates, knowledge, opinion, work performance.

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Authors: Md. Salim Kaiser

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In the present work, the effect of load and sliding distance on the performance tribology of commercially used aluminium-silicon engine block and piston was evaluated at ambient conditions with humidity of 80% under dry sliding conditions using a pin-on-disc with two different loads of 5N and 20N yielding applied pressure of 0.30MPa and 1.4MPa, respectively, at sliding velocity of 0.29ms-1 and with varying sliding distance ranging from 260m-4200m. Factors and conditions that had significant effect were identified. The results showed that the load and the sliding distance affect the wear rate of the alloys and the wear rate increased with increasing load for both the alloys. Wear rate also increases almost linearly at low loads and increase to a maximum then attain a plateau with increasing sliding distance. For both applied loads, the piston alloy showed the better performance due to higher Ni and Mg content. The worn surface and wear debris was characterized by optical microscope, SEM and EDX analyzer. The worn surface was characterized by surface with shallow grooves at loads while the groove width and depth increased as the loads increases. Oxidative wear was found to be the predominant mechanisms in the dry sliding of Al-Si alloys at low loads

Keywords: wear, friction, gravimetric analysis, aluminium-silicon alloys, SEM, EDX

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Authors: Valdênia Carvalho e Almeida

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The goal of the present study is to investigate the semantic preference of the most frequent adjectives in research articles through a corpus-based analysis of texts published in journals in Applied Linguistics (AL). The corpus used in this study contains texts published in the period from 2014 to 2018 in the three journals: Language Learning and Technology; English for Academic Purposes, and TESOL Quaterly, totaling more than one million words. A corpus-based analysis was carried out on the corpus to identify the most frequent adjectives that co-occurred in the three journals. By observing the concordance lines of the adjectives and analyzing the words they associated with, the semantic preferences of each adjective were determined. Later, the AL corpus analysis was compared to the investigation of the same adjectives in a corpus of Chemistry. This second part of the study aimed to identify possible differences and similarities between the two corpora in relation to the use of the adjectives in research articles from both areas. The results show that there are some preferences which seem to be closely related not only to the academic genre of the texts but also to the specific domain of the discipline and, to a lesser extent, to the context of research in each journal. This research illustrates a possible contribution of Corpus Linguistics to explore the concept of semantic preference in more detail, considering the complex nature of the phenomenon.

Keywords: applied linguistics, corpus linguistics, chemistry, research article, semantic preference

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Authors: Richard Byrne, Emma Mulliner

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Smart cities are a vision for the future that is increasingly becoming a reality. While a key concept of the smart city is the ability to capture, communicate, and process data that has long been produced through day-to-day activities of the city, much of the assessment models in place neglect this fact to focus on ‘smartness’ concepts. Although it is true technology often provides the opportunity to capture and communicate data in more effective ways, there are also human processes involved that are just as important. The growing importance with regards to the use and ownership of data in society can be seen by all with companies such as Facebook and Google increasingly coming under the microscope, however, why is the same scrutiny not applied to cities? The research area is therefore of great importance to the future of our cities here and now, while the findings will be of just as great importance to our children in the future. This research aims to understand the influence data is having on organisations operating throughout the smart cities sector and employs a mixed-method research approach in order to best answer the following question: Would a data-based evaluation model for smart cities be more appropriate than a smart-based model in assessing the development of the smart city? A fully comprehensive literature review concluded that there was a requirement for a data-driven assessment model for smart cities. This was followed by a documentary analysis to understand the root source of data integration to the smart city. A content analysis of city data platforms enquired as to the alternative approaches employed by cities throughout the UK and draws on best practice from New York to compare and contrast. Grounded in theory, the research findings to this point formulated a qualitative analysis framework comprised of: the changing environment influenced by data, the value of data in the smart city, the data ecosystem of the smart city and organisational response to the data orientated environment. The framework was applied to analyse primary data collected through the form of interviews with both public and private organisations operating throughout the smart cities sector. The work to date represents the first stage of data collection that will be built upon by a quantitative research investigation into the feasibility of data network effects in the smart city. An analysis into the benefits of data interoperability supporting services to the smart city in the areas of health and transport will conclude the research to achieve the aim of inductively forming a framework that can be applied to future smart city policy. To conclude, the research recognises the influence of technological perspectives in the development of smart cities to date and highlights this as a challenge to introduce theory applied with a planning dimension. The primary researcher has utilised their experience working in the public sector throughout the investigation to reflect upon what is perceived as a gap in practice of where we are today, to where we need to be tomorrow.

Keywords: data, planning, policy development, smart cities

Procedia PDF Downloads 310