Search results for: ideal profile method

Authors: M. Kubilay Önal

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The objective of this study was to determine the adaptabilities of native apricot materials collected from Southeast Anatolia region of Turkey to Aegean Region conditions. Different phenological and pomological characteristics of the cultivars were observed during study. Determination of promising types for adaptation trials were performed employing the 'weighed-ranking' method. To determine them the relative points were given to the characteristics such as yield, average fruit weight, attractiveness, soluble solid, seed ratio by weight and aroma. As a result of two-year evaluation studies on the phenological and pomological characteristics of 22 types, 9 out of them, viz., nos. 2235, 2236, 2237, 2239, 2242, 2244, 2246, 2249, 2257 were selected as promising ones.

Keywords: apricot, phenological characters, pomological characters, weight-ranking method

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Authors: In Hee Shim, Dong Sik Bae

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Introduction: Obesity and unfavorable lipid profile may be linked to depressive disorders. This study compared the levels of obesity, lipid profiles and depression severity of patients with depressive disorders. Methods: This study included 156 patients diagnosed with a depressive disorder who were hospitalized between March 2012 and February 2016. The patients were categorized into mild to moderate and severe depressive groups, based on Hamilton Depression Rating Scale scores (Mild to moderate depression 8-23 vs. severe depression ≥ 24). The charts of the patients were reviewed to evaluate body mass index and lipid profiles, including total cholesterol, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG), confounding factors, such as other general medical disorders (hypertension, diabetes mellitus, and dyslipidemia), except smoking status (insufficient data). Demographic and clinical characteristics, such as age, sex, comorbidities, family history of mood disorders, psychotic features, and prescription patterns were also assessed. Results: Compared to the mild to the moderate depressive group, patients with severe depression had significantly lower rate of male and comorbidity. The patients with severe depression had a significantly lower TG than patients in the mild to moderate depressive group. After adjustment for the sex and comorbidity, there were no significant differences between the two groups in terms of the obesity and lipid profiles, including TG. Conclusion: These results did not show a significant difference in the association between obesity, lipid profiles and the depression severity. The role of obesity and lipid profiles in the pathophysiology of depression remains to be clarified.

Keywords: depression, HAM-D, lipid profiles, obesity

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Authors: E. Tandis, E. Assareh

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Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

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Authors: Nevena Jakovčević Stor, Ivan Slapničar

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Any polynomial can be expressed as a characteristic polynomial of a complex symmetric arrowhead matrix. This expression is not unique. If the polynomial is real with only real distinct roots, the matrix can be chosen as real. By using accurate forward stable algorithm for computing eigen values of real symmetric arrowhead matrices we derive a forward stable algorithm for computation of roots of such polynomials in O(n^2 ) operations. The algorithm computes each root to almost full accuracy. In some cases, the algorithm invokes extended precision routines, but only in the non-iterative part. Our examples include numerically difficult problems, like the well-known Wilkinson’s polynomials. Our algorithm compares favorably to other method for polynomial root-finding, like MPSolve or Newton’s method.

Keywords: roots of polynomials, eigenvalue decomposition, arrowhead matrix, high relative accuracy

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Authors: Kishore Kumar R., Kaustav Sengupta, Shalini Sood Sehgal, Poornima Santhanam

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Fashion is a human expression that is constantly changing. One of the prime factors that consistently influences fashion is the change in colour preferences. The role of colour in our everyday lives is very significant. It subconsciously explains a lot about one’s mindset and mood. Analyzing the colours by extracting them from the outfit images is a critical study to examine the individual’s/consumer behaviour. Several research works have been carried out on extracting colours from images, but to the best of our knowledge, there were no studies that extract colours to specific apparel and identify colour patterns geographically. This paper proposes a framework for accurately extracting colours from T-shirt images and predicting dominant colours geographically. The proposed method consists of two stages: first, a U-Net deep learning model is adopted to segment the T-shirts from the images. Second, the colours are extracted only from the T-shirt segments. The proposed method employs the iMaterialist (Fashion) 2019 dataset for the semantic segmentation task. The proposed framework also includes a mechanism for gathering data and analyzing India’s general colour preferences. From this research, it was observed that black and grey are the dominant colour in different regions of India. The proposed method can be adapted to study fashion’s evolving colour preferences.

Keywords: colour analysis in t-shirts, convolutional neural network, encoder-decoder, k-means clustering, semantic segmentation, U-Net model

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Authors: Chih-Jer Lin, Jian-Hong Hou

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Industry 4.0 is a vision of integrated industry implemented by artificial intelligent computing, software, and Internet technologies. The main goal of industry 4.0 is to deal with the difficulty owing to competitive pressures in the marketplace. For today’s manufacturing factories, the type of production is changed from mass production (high quantity production with low product variety) to medium quantity-high variety production. To offer flexibility, better quality control, and improved productivity, robot manipulators are used to combine material processing, material handling, and part positioning systems into an integrated manufacturing system. To implement the automated system for sheet metal bending operations, motion planning of a 7-degrees of freedom (DOF) robot is studied in this paper. A virtual reality (VR) environment of a bending cell, which consists of the robot and a bending machine, is established using the virtual robot experimentation platform (V-REP) simulator. For sheet metal bending operations, the robot only needs six DOFs for the pick-and-place or tracking tasks. Therefore, this 7 DOF robot has more DOFs than the required to execute a specified task; it can be called a redundant robot. Therefore, this robot has kinematic redundancies to deal with the task-priority problems. For redundant robots, Pseudo-inverse of the Jacobian is the most popular motion planning method, but the pseudo-inverse methods usually lead to a kind of chaotic motion with unpredictable arm configurations as the Jacobian matrix lose ranks. To overcome the above problem, we proposed a method to formulate the motion planning problems as optimization problem. Moreover, a genetic algorithm (GA) based method is proposed to deal with motion planning of the redundant robot. Simulation results validate the proposed method feasible for motion planning of the redundant robot in an automated sheet-metal bending operations.

Keywords: redundant robot, motion planning, genetic algorithm, obstacle avoidance

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Authors: El Alia Boularas, H. Bekkar, H. Larachi, H. Rezk-kallah

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Introduction: Notwithstanding cosmetics are used in life every day, these products are not all innocuous and harmless, as they may contain ingredients responsible for allergic reactions and, possibly, for other health problems. Additionally, environmental pollution should be taken into account. Thus, it is time to investigate what is ‘hidden behind beauty’. Aims: 1.To investigate prevalence of 13 chemical ingredients in cosmetics being object of concern, which the Algerians use regularly. 2.To know the profile of questioned consumers and describe their opinion on cosmetics. Methods: The survey was carried out in year 2013 over a period of 3 months, among Algerian Internet users having an e-mail address or a Facebook account.The study investigated 13 chemical agents showing health and environmental problems, selected after analysis of the recent studies published on the subject, the lists of national and international regulatory references on chemical hazards, and querying the database Skin Deep presented by the Environmental Working Group. Results: 300 people distributed all over the Algerian territory participated in the survey, providing information about 731 cosmetics; 86% aged from 20 to 39 years, with a sex ratio=0,27. A percentage of 43% of the analyzed cosmetics contained at least one of the 13 toxic ingredients. The targeted ingredient that has been most frequently reported was ‘perfume’ followed by parabens and PEG.85% of the participants declared that cosmetics ‘can contain toxic substances’, 27% asserted that they verify regularly the list of ingredients when they buy cosmetics, 61% said that they try to avoid the toxic ingredients, among whom 24 % were more vigilant on the presence of parabens, 95% were in favour of the strengthening of the Algerian laws on cosmetics. Conclusion: The results of the survey provide the indication of a widespread presence of toxic chemical ingredients in personal care products that Algerians use daily.

Keywords: Algerians consumers, cosmetics, survey, toxic ingredients

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Authors: Zulfikar Dinar Wahidayat Putra

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Water scarcity become a major challenge in an arid area. One of the arid areas is La Serena city in the Northern Chile which become a case study of this paper. Based on that, this paper tries to identify a sustainable water system by using urban harvest approach as a method to achieve water self-sufficiency for a neighborhood area in the La Serena city. By using the method, it is possible to create sustainable water system in the neighborhood area by reducing up to 38% of water demand and 94% of wastewater production even though water self-sufficient cannot be fully achieved, because of its dependency to the drinking water supply from water treatment plant of La Serena city.

Keywords: arid area, sustainable water system, urban harvest approach, self-sufficiency

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: Sima Najafzadehkhoei, George Vega Yon

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This paper presents an approach for calibrating Agent-Based Models (ABMs) efficiently, utilizing Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. These machine learning techniques are applied to Susceptible-Infected-Recovered (SIR) models, which are a core framework in the study of epidemiology. Our method replicates parameter values from observed trajectory curves, enhancing the accuracy of predictions when compared to traditional calibration techniques. Through the use of simulated data, we train the models to predict epidemiological parameters more accurately. Two primary approaches were explored: one where the number of susceptible, infected, and recovered individuals is fully known, and another using only the number of infected individuals. Our method shows promise for application in other ABMs where calibration is computationally intensive and expensive.

Keywords: ABM, calibration, CNN, LSTM, epidemiology

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Authors: R. Devicharan

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In a short span 3D Printing is expected to play a vital role in our life. The possibility of creativity and speed in manufacturing through various 3D printing processes is infinite. This study is performed on the FDM (Fused Deposition Modelling) method of 3D printing, which is one of the pre-dominant methods of 3D printing technologies. This study focuses on physical properties of the objects produced by 3D printing which determine the applications of the 3D printed objects. This paper specifically aims at the study of the tensile strength and the folding endurance of the 3D printed objects through the FDM (Fused Deposition Modelling) method using the ABS (Acronitirile Butadiene Styrene) and PLA (Poly Lactic Acid) plastic materials. The study is performed on a controlled environment and the specific machine settings. Appropriate tables, graphs are plotted and research analysis techniques will be utilized to analyse, verify and validate the experiment results.

Keywords: FDM process, 3D printing, ABS for 3D printing, PLA for 3D printing, rapid prototyping

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Authors: Raghvendra Singh Yadav, Ivo Kuřitka, Jaromir Havlica, Zuzana Kozakova, Jiri Masilko, Lukas Kalina, Miroslava Hajdúchová, Vojtěch Enev, Jaromir Wasserbauer

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In this work, we investigated the structural and magnetic properties of CoFe2O4:Nd3+/Dy3+/Pr3+/Gd3+ nanoparticles synthesized by starch-assisted sol-gel combustion method. X-ray diffraction pattern confirmed the formation of cubic spinel structure of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) doped CoFe2O4 spinel ferrite nanoparticles. Raman and Fourier Transform Infrared spectroscopy study also confirmed cubic spinel structure of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles. The field emission scanning electron microscopy study revealed the effect of annealing temperature on size of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles and particles were in the range of 10-100 nm. The magnetic properties of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles were investigated by using vibrating sample magnetometer. The variation in saturation magnetization, coercivity and remanent magnetization with annealing temperature/ particle size of rare-earth ions (Nd3+, Dy3+, Pr3+, Gd3+) substituted CoFe2O4 nanoparticles was observed. Acknowledgment: This work was supported by the Ministry of Education, Youth and Sports of the Czech Republic – Program NPU I (LO1504).

Keywords: starch, sol-gel combustion method, rare-earth ions, spinel ferrite nanoparticles, magnetic properties

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Authors: N. K. Chougule, G. V. Parishwad

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The pin fin heat sink is a novel heat transfer device to transfer large amount of heat through with very small temperature differences and it also possesses large uniform cooling characteristics. Pin fins are widely used as elements that provide increased cooling for electronic devices. Increasing demands regarding the performance of such devices can be observed due to the increasing heat production density of electronic components. For this reason, extensive work is being carried out to select and optimize pin fin elements for increased heat transfer. In this paper, the effects of design parameters and the optimum design parameters for a Pin-Fin heat sink (PFHS) under multi-jet impingement case with thermal performance characteristics have been investigated by using Taguchi methodology based on the L9 orthogonal arrays. Various design parameters, such as pin-fin array size, gap between nozzle exit to impingement target surface (Z/d) and air velocity are explored by numerical experiment. The average convective heat transfer coefficient is considered as the thermal performance characteristics. The analysis of variance (ANOVA) is applied to find the effect of each design parameter on the thermal performance characteristics. Then the results of confirmation test with the optimal level constitution of design parameters have obviously shown that this logic approach can effective in optimizing the PFHS with the thermal performance characteristics. The analysis of the Taguchi method reveals that, all the parameters mentioned above have equal contributions in the performance of heat sink efficiency. Experimental results are provided to validate the suitability of the proposed approach.

Keywords: Pin Fin Heat Sink (PFHS), Taguchi method, CFD, thermal performance

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Authors: Gonzalez Carlos, Martinez Fransisco

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The creation of a seismic prediction model that considers all the regional variations and perfectly adjusts its results to the response spectra is very complicated. To achieve statistically acceptable results, it is necessary to process a sufficiently robust data set, and even if high efficiencies are achieved, this model will only work properly in this region. However, when using it in other regions, differences are found due to different parameters that have not been calibrated to other regions, such as the site effect. The fact that impedance contrasts, as well as other factors belonging to the site, have a great influence on the local response is well known, which is why this work, using the residual method, is intended to establish a regional calibration of the corresponding parameters site effect for the Spain region in the global GMPM BSSA 14.

Keywords: GMPM, seismic prediction equations, residual method, response spectra, impedance contrast

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Authors: So Young Kim, Eun-Young Kwon, Bora Choi, Mi Kyeong Yu, Seon Jeong Lee, Myung-Sook Choi

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Lemon (Citrus limon) has various beneficial effect. Eriocitrin (eriodictyol 7-rutinoside) is the main ingredient of lemon fruit and is known to have antioxidative effects. However, there has been little research about the effects of eriocitrin on obesity and regulation of lipid profiles levels. In the present study, we investigated the anti-obesity and lipid-lowering effects of eriocitrin in mice fed high-fat diet (HFD). The 4 week-old male C57BL/6 mice were randomly divided into two groups and were fed HFD (20% fat, w/w) and HFD supplemented with eriocitrin (0.005%, w/w, EC) for 16 weeks. Food intake, body weight and white adipose tissue weight (WAT) were measured and plasma free fatty acid (FFA), apolipoprotein (Apo) B100 level and hepatic enzyme activity were analyzed. No differences were shown between the HFD and EC groups in body weight and food intake. However EC supplementation significantly reduced the weights of epididymal, subcutaneous and total WAT. In addition, the levels of plasma FFA and Apo B100 were significantly decreased in the EC group compared with the HFD group. Moreover, the activities of glucose-6-phosphate dehydrogenase (G6PD) and malic enzyme (ME) related to fatty acids synthesis were significantly lower in the EC group than in the HFD group in liver. Therefore, this study indicates that eriocitrin has beneficial effects on adiposity and nonalcholic fatty liver diseases by modulating hepatic lipid-regulating enzyme activities and plasma lipid profile.

Keywords: antiobesity, eriocitrin, high fat diet, lipid lowering

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Authors: Saad M. Darwish, Mohamed A. El-Iskandarani, Guitar M. Shawkat

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Nowadays, the amount of available multimedia data is continuously on the rise. The need to find a required image for an ordinary user is a challenging task. Content based image retrieval (CBIR) computes relevance based on the visual similarity of low-level image features such as color, textures, etc. However, there is a gap between low-level visual features and semantic meanings required by applications. The typical method of bridging the semantic gap is through the automatic image annotation (AIA) that extracts semantic features using machine learning techniques. In this paper, a multi-label image annotation system guided by Firefly and Bayesian method is proposed. Firstly, images are segmented using the maximum variance intra cluster and Firefly algorithm, which is a swarm-based approach with high convergence speed, less computation rate and search for the optimal multiple threshold. Feature extraction techniques based on color features and region properties are applied to obtain the representative features. After that, the images are annotated using translation model based on the Net Bayes system, which is efficient for multi-label learning with high precision and less complexity. Experiments are performed using Corel Database. The results show that the proposed system is better than traditional ones for automatic image annotation and retrieval.

Keywords: feature extraction, feature selection, image annotation, classification

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Authors: Elbadawy A. Kamoun

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Magnetically responsive hydrogel nanocomposite (NCH) based on composites of superparamagnetic of Fe3O4 nano-particles and temperature responsive hydrogel matrices were developed. The nanocomposite hydrogel system based on the temperature sensitive N-isopropylacrylamide hydrogels crosslinked by poly(ethylene glycol)-400 dimethacrylate (PEG400DMA) incorporating with chitosan derivative, was synthesized and characterized. Likewise, the NCH system was synthesized by visible-light free radical photopolymerization, using carboxylated camphorquinone-amine system to avoid the common risks of the use of UV-light especially in hyperthermia treatment. Superparamagnetic of iron oxide nanoparticles were introduced into the hydrogel system by polymerizing mixture technique and monomer solution. FT-IR with Raman spectroscopy and Wide angle-XRD analysis were utilized to verify the chemical structure of NCH and exfoliation reaction for nanoparticles, respectively. Additionally, morphological structure of NCH was investigated using SEM and TEM photographs. The swelling responsive of the current nanocomposite hydrogel system with different crosslinking conditions, temperature, magnetic field efficiency, and the presence effect of magnetic nanoparticles were evaluated. Notably, hydrolytic degradation of this system was proved in vitro application. While, in-vivo release profile behavior is under investigation nowadays. Moreover, the compatibility and cytotoxicity tests were previously investigated in our studies for photoinitiating system. These systems show promised polymeric material candidate devices and are expected to have a wide applicability in various biomedical applications as mildly.

Keywords: hydrogel nanocomposites, tempretaure-responsive hydrogel, superparamagnetic nanoparticles, hyperthermia therapy

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Authors: Imen Soltani, Takoua Soltani, Taoufik Aguili

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Metamaterials crossover classic physical boundaries and gives rise to new phenomena and applications in the domain of beam steering and shaping. Where electromagnetic near and far field manipulations were achieved in an accurate manner. In this sense, 3D imaging is one of the beneficiaries and in particular Denis Gabor’s invention: holography. But, the major difficulty here is the lack of a suitable recording medium. So some enhancements were essential, where the 2D version of bulk metamaterials have been introduced the so-called metasurface. This new class of interfaces simplifies the problem of recording medium with the capability of tuning the phase, amplitude, and polarization at a given frequency. In order to achieve an intelligible wavefront control, the electromagnetic properties of the metasurface should be optimized by means of solving Maxwell’s equations. In this context, integral methods are emerging as an important method to study electromagnetic from microwave to optical frequencies. The method of moment presents an accurate solution to reduce the problem of dimensions by writing its boundary conditions in the form of integral equations. But solving this kind of equations tends to be more complicated and time-consuming as the structural complexity increases. Here, the use of equivalent circuit’s method exhibits the most scalable experience to develop an integral method formulation. In fact, for allaying the resolution of Maxwell’s equations, the method of Generalised Equivalent Circuit was proposed to convey the resolution from the domain of integral equations to the domain of equivalent circuits. In point of fact, this technique consists in creating an electric image of the studied structure using discontinuity plan paradigm and taken into account its environment. So that, the electromagnetic state of the discontinuity plan is described by generalised test functions which are modelled by virtual sources not storing energy. The environmental effects are included by the use of an impedance or admittance operator. Here, we propose a tunable metasurface composed of graphene-based elements which combine the advantages of reflectarrays concept and graphene as a pillar constituent element at Terahertz frequencies. The metasurface’s building block consists of a thin gold film, a dielectric spacer SiO₂ and graphene patch antenna. Our electromagnetic analysis is based on the method of moment combined with generalised equivalent circuit (MoM-GEC). We begin by restricting our attention to study the effects of varying graphene’s chemical potential on the unit cell input impedance. So, it was found that the variation of complex conductivity of graphene allows controlling the phase and amplitude of the reflection coefficient at each element of the array. From the results obtained here, we were able to determine that the phase modulation is realized by adjusting graphene’s complex conductivity. This modulation is a viable solution compared to tunning the phase by varying the antenna length because it offers a full 2π reflection phase control.

Keywords: graphene, method of moment combined with generalised equivalent circuit, reconfigurable metasurface, reflectarray, terahertz domain

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Authors: Zhenqiu Liu

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Visualizing the heterogeneity within cell-populations for single-cell RNA-seq data is crucial for studying the functional diversity of a cell. However, because of the high level of noises, outlier, and dropouts, it is very challenging to measure the cell-to-cell similarity (distance), visualize and cluster the data in a low-dimension. Minimum volume embedding (MVE) projects the data into a lower-dimensional space and is a promising tool for data visualization. However, it is computationally inefficient to solve a semi-definite programming (SDP) when the sample size is large. Therefore, it is not applicable to single-cell RNA-seq data with thousands of samples. In this paper, we develop an efficient algorithm with an accelerated proximal gradient method and visualize the single-cell RNA-seq data efficiently. We demonstrate that the proposed approach separates known subpopulations more accurately in single-cell data sets than other existing dimension reduction methods.

Keywords: single-cell RNA-seq, minimum volume embedding, visualization, accelerated proximal gradient method

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Authors: Jong-Jy Shyu, Soo-Chang Pei, Yun-Da Huang

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In this paper, design of wide-range variable fractional-delay (WR-VFD) finite impulse response (FIR) digital filters is proposed. With respect to the conventional VFD filter which is designed such that its delay is adjustable within one unit, the proposed VFD FIR filter is designed such that its delay can be tunable within a wider range. By the traces of coefficients of the fractional-delay FIR filter, it is found that the conventional method of polynomial substitution for filter coefficients no longer satisfies the design demand, and the circuits perform the sinc function (sinc converter) are added to overcome this problem. In this paper, least-squares method is adopted to design WR-VFD FIR filter. Throughout this paper, several examples will be proposed to demonstrate the effectiveness of the presented methods.

Keywords: digital filter, FIR filter, variable fractional-delay (VFD) filter, least-squares approximation

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Authors: Safia Rabaaoui, Héla Hachicha, Ezzeddine Zagrouba

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Nowadays, cloud computing is becoming the more popular technology to various companies and consumers, which benefit from its increased efficiency, cost optimization, data security, unlimited storage capacity, etc. One of the biggest challenges of cloud computing is resource allocation. Its efficiency directly influences the performance of the whole cloud environment. Finding an effective method to address these critical issues and increase cloud performance was necessary. This paper proposes a mobile agents-based framework for dynamic resource allocation in cloud computing to minimize both the cost of using virtual machines and the makespan. Furthermore, its impact on the best response time and power consumption has been studied. The simulation showed that our method gave better results than here.

Keywords: cloud computing, multi-agent system, mobile agent, dynamic resource allocation, cost, makespan

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Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil

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Authors: Mary Carmen Peloche Barrera

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Since its early years as an independent nation, the United States has been one of the main promoters regarding the recognition, legislation, and protection of human rights. In the matter of freedom, the founding father Thomas Jefferson envisioned the role of the U.S. as a defender of freedom and equality throughout the world. This founding ideal shaped America’s domestic and foreign policy in the 19th and the 20th century and became an aspiration of the ideals of the country to expand its values and institutions. The history of the emergence of human rights cannot be studied without making reference to leaders such as Woodrow Wilson, Franklin, and Eleanor Roosevelt, as well as Martin Luther King. Throughout its history, this country has proclaimed that the protection of the freedoms of men, both inside and outside its borders, is practically the reason for its existence. Although the United States was one of the first countries to recognize the existence of inalienable rights for individuals, as well as the main promoter of the Universal Declaration of Human Rights of 1948, the country has gone through critical moments that had led to questioning its commitment to the issue. Racial segregation, international military interventions, national security strategy, as well as national legislation on immigration, are some of the most controversial issues related to decisions and actions driven by the United States, which at the same time mismatched with its role as an advocate of human rights, both in the Americas and in the rest of the world. The aim of this paper is to study the swinging of the efforts and commitments of the United States towards human rights. The paper will analyze the history and evolution of human rights in the United States, to study the greatest challenges for the country in this matter. The paper will focus on both the domestic policy (related to demographic issues) and foreign policy (about its role in a post-war world). Currently, more countries are joining the multilateral efforts for the promotion and protection of human rights. At the same time, the United States is one of the least committed countries in this respect, having ratified only 5 of the 18 treaties emanating from the United Nations. The last ratification was carried out in 2002 and, since then, the country has been losing ground, in an increasingly vertiginous way, in its credibility and, even worse, in its role as leader of 'the free world'. With or without the United States, the protection of human rights should remain the main goal of the international community.

Keywords: United States, human rights, foreign policy, domestic policy

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Authors: Hayder H. Kareem

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Groundwater recharge is a crucial parameter for any groundwater management system. The variability of the recharge rates and the difficulty in estimating this factor in many processes by direct observation leads to the complexity of estimating the recharge value. Various methods are existing to estimate the groundwater recharge, with some limitations for each method to be able for application. This paper focuses particularly on a real study area, Al-Najaf City, Iraq. In this city, there are few groundwater aquifers, but the aquifer which is considered in this study is the closest one to the ground surface, the Dibdibba aquifer. According to the Aridity Index, which is estimated in the paper, Al-Najaf City is classified as a region located in an arid climate, and this identified that the most appropriate method to estimate the groundwater recharge is Thornthwaite's formula or Thornthwaite's method. From the calculations, the estimated average groundwater recharge over the period 1980-2014 for Al-Najaf City is 40.32 mm/year. Groundwater recharge is completely affected the groundwater table level (groundwater head). Therefore, to make sure that this value of recharge is true, the MODFLOW program has been used to apply this value through finding the relationship between the calculated and observed heads where a groundwater model for the Al-Najaf City study area has been built by MODFLOW to simulate this area for different purposes, one of these purposes is to simulate the groundwater recharge. MODFLOW results show that this value of groundwater recharge is extremely high and needs to be reduced. Therefore, a further sensitivity test has been carried out for the Al-Najaf City study area by the MODFLOW program through changing the recharge value and found that the best estimation of groundwater recharge value for this city is 16.5 mm/year where this value gives the best fitting between the calculated and observed heads with minimum values of RMSE % (13.175) and RSS m² (1454).

Keywords: Al-Najaf City, groundwater modelling, recharge estimation, visual MODFLOW

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Authors: Mark-Adam Kellerman

Abstract:

Proteins are capable of exploring vast mutational spaces. This makes it difficult for protein engineers to devise rational methods to improve stability and function via mutagenesis. Deciding which residues to mutate requires knowledge of the characteristics they elicit. We probed the characteristics of residues in granulocyte-colony stimulating factor (G-CSF) using a thermal melt (from 295K to 323K) to denature it in a 700 MHz Bruker spectrometer. These characteristics included dynamics, micro-environmental changes experienced/ induced during denaturing and structure-function relationships. 15N-1H HSQC experiments were performed at 2K increments along with this thermal melt. We observed that dynamic residues that also undergo a lot of change in their microenvironment were predominantly in unstructured regions. Moreover, we were able to identify four residues (G4, A6, T133 and Q134) that we class as high priority targets for mutagenesis, given that they all appear in both the top 10% of measures for environmental changes and dynamics (∑Δ and ∆PI). We were also able to probe these NMR observables and combine them with molecular dynamics (MD) to elucidate what appears to be an opening motion of G-CSFs binding site III. V48 appears to be pivotal to this opening motion, which also seemingly distorts the loop region between helices A and B. This observation is in agreement with previous findings that the conformation of this loop region becomes altered in an aggregation-prone state of G-CSF. Hence, we present here an approach to profile the characteristics of residues in order to highlight their potential as rational mutagenesis targets and their roles in important conformational changes. These findings present not only an opportunity to effectively make biobetters, but also open up the possibility to further understand epistasis and machine learn residue behaviours.

Keywords: protein engineering, rational mutagenesis, NMR, molecular dynamics

Procedia PDF Downloads 259

Authors: Anastasia K. Eleftheriadou, Athanasios Sfetsos, Nikolaos Gounaris

Abstract:

The present work examines the suitability of a seasonal forecasting model downscaled with a very high spatial resolution in order to assess the energy performance and requirements of buildings. The application of the developed model is applied on Greece for a period and with a forecast horizon of 5 months in the future. Greece, as a country in the middle of a financial crisis and facing serious societal challenges, is also very sensitive to climate changes. The commonly used method for the correlation of climate change with the buildings energy consumption is the concept of Degree Days (DD). This method can be applied to heating and cooling systems for a better management of environmental, economic and energy crisis, and can be used as medium (3-6 months) planning tools in order to predict the building needs and country’s requirements for residential energy use.

Keywords: downscaled seasonal models, degree days, energy performance

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Authors: R. Harman Dwi, Ryan Avirsa, P. Abraham Ivan

Abstract:

Understanding of temperatures in the past, present, and future temperatures can be possible to do by analysis abundance of fossil foraminifera. This research was conducted in Sambipitu Formation, Ngalang River, Nglipar, Gunung Kidul Regency. The research method is divided into 3 stages: 1) study of literature, research based on previous researchers, 2) spatial, observation and sampling every 5-10 meters, 3) descriptive, analyzing samples consisting of a 10-gram sample weight, washing sample using 30% peroxide, biostratigraphy analysis, paleotemperature analysis using abundance of fossil, diversity analysis using Simpson diversity index method, and comparing current temperature data. There are two phases based on the appearance of Globorotalia menardii and Pulleniatina obliqueculata pointed to Phase Tropical Area, and the appearance of fossil Globigerinoides ruber and Orbulina universa fossil shows the phase of Subtropical Area. Paleotemperatur based on the appearance of Globorotalia menardii, Globigerinoides trilobus, Globigerinoides ruber, Orbulina universa, and Pulleniatina obliqueculata pointed to Warm Water Area and Warm Water Area (average surface water approximate 25°C).

Keywords: abundance, biostratigraphy, Simpson diversity index method, paleotemperature

Procedia PDF Downloads 175

Authors: Hamed Seddighi Khavidak

Abstract:

Voluntary work has a lot of economic and social benefits for a country, but the economic value is ignored because it is voluntary. The aim of this study is reviewing Monetary Value of Voluntary Work methods and comparing opportunity cost method and replacement cost method both in theory and in practice. Beside monetary value, in this study, we discuss cost-benefit analysis of health and safety plan in the New Year that conducted by young volunteers of Red Crescent society of Iran. Method: We discussed eight methods for monetary value of voluntary work including: Alternative-Employment Wage Approach, Leisure-Adjusted OCA, Volunteer Judgment OCA, Replacement Wage Approach, Volunteer Judgment RWA, Supervisor Judgment RWA, Cost of Counterpart Goods and Services and Beneficiary Judgment. Also, for cost benefit analysis we drew on 'value audit and volunteer investment' (VIVA) technique that is used widely in voluntary organizations like international federation of Red Cross and Red Crescent societies. Findings: In this study, using replacement cost approach, voluntary work by 1034 youth volunteers was valued 938000000 Riyals and using Replacement Wage Approach it was valued 2268713232 Riyals. Moreover, Yazd Red Crescent Society spent 212800000 Riyals on food and other costs for these volunteers. Discussion and conclusion: In this study, using cost benefit analysis method that is Volunteer Investment and Value Audit (VIVA), VIVA rate showed that for every Riyal that the Red Crescent Society invested in the health and safety of New Year's travelers in its volunteer project, four Riyals returned, and using the wage replacement approach, 11 Riyals returned. Therefore, New Year's travelers health and safety project were successful and economically, it was worthwhile for the Red Crescent Society because the output was much bigger than the input costs.

Keywords: voluntary work, monetary value, youth, red crescent society

Procedia PDF Downloads 221

Authors: P. Ahuja, K. S. S. Sai Krishna

Abstract:

There is a concern over the energy shortage in the modern societies as it is one of the primary necessities. Renewable energy, mainly biomass, is found to be one feasible solution as it is inexhaustible and clean energy source all over the world. Out of various methods, thermo chemical conversion is considered to be the most common and convenient method to extract energy from biomass. The thermo-chemical methods that are employed are gasification, liquefaction and combustion. On gasification biomass yields biogas, on liquefaction biomass yields bio-oil and on combustion biomass yields bio-char. Any attempt to biomass gasification, liquefaction or combustion calls for a good understanding of biomass pyrolysis. So, Irrespective of the method used the first step towards the thermo-chemical treatment of biomass is pyrolysis. Pyrolysis mainly converts the solid mass into liquid with gas and residual char as the byproducts. Liquid is used for the production of heat, power and many other chemicals whereas the gas and char can be used as fuels to generate heat.

Keywords: biomass, fluidisation, pyrolysis, simulation

Procedia PDF Downloads 346

Authors: Orod Zarrin, Mohesn Ramezan Shirazi, Hassan Moniri

Abstract:

The use of pile foundations technique is developed to support structures and buildings on soft soil. The most important dynamic load that can affect the pile structure is earthquake vibrations. Pile foundations during earthquake excitation indicate that piles are subject to damage by affecting the superstructure integrity and serviceability. During an earthquake, two types of stresses can damage the pile head, inertial load that is caused by superstructure and deformation which caused by the surrounding soil. Soil deformation and inertial load are associated with the acceleration developed in an earthquake. The acceleration amplitude at the ground surface depends on the magnitude of earthquakes, soil properties and seismic source distance. According to the investigation, the damage is between the liquefiable and non-liquefiable layers and also soft and stiff layers. This damage crushes the pile head by increasing the inertial load which is applied by the superstructure. On the other hand, the cracks on the piles due to the surrounding soil are directly related to the soil profile and causes cracks from small to large. However, the large cracks reason have been listed such as liquefaction, lateral spreading, and inertial load. In the field of designing, elastic response of piles is always a challenge for designer in liquefaction soil, by allowing deflection at top of piles. Moreover, absence of plastic hinges in piles should be insured, because the damage in the piles is not observed directly. In this study, the performance and behavior of pile foundations during liquefaction and lateral spreading are investigated. In addition, emphasize on the soil behavior in the liquefiable and non-liquefiable layers by different aspect of piles damage such as ranking, location and degree of damage are going to discuss.

Keywords: pile, earthquake, liquefaction, non-liquefiable, damage

Procedia PDF Downloads 305