Search results for: rough kernel

Authors: Serge B. Provost

Abstract:

Numerous statistical inference and modeling methodologies are based on sample moments rather than the actual observations. A result justifying the validity of this approach is introduced. More specifically, it will be established that given the first n moments of a sample of size n, one can recover the original n sample points. This implies that a sample of size n and its first associated n moments contain precisely the same amount of information. However, it is efficient to make use of a limited number of initial moments as most of the relevant distributional information is included in them. Two types of density estimation techniques that rely on such moments will be discussed. The first one expresses a density estimate as the product of a suitable base density and a polynomial adjustment whose coefficients are determined by equating the moments of the density estimate to the sample moments. The second one assumes that the derivative of the logarithm of a density function can be represented as a rational function. This gives rise to a system of linear equations involving sample moments, the density estimate is then obtained by solving a differential equation. Unlike kernel density estimation, these methodologies are ideally suited to model ‘big data’ as they only require a limited number of moments, irrespective of the sample size. What is more, they produce simple closed form expressions that are amenable to algebraic manipulations. They also turn out to be more accurate as will be shown in several illustrative examples.

Keywords: density estimation, log-density, polynomial adjustments, sample moments

Procedia PDF Downloads 129

Authors: Tawfik Thelaidjia, Salah Chenikher

Abstract:

Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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Authors: Wei-Jong Yang, Yu-Siang Su, Pau-Choo Chung, Jar-Ferr Yang

Abstract:

Moving object detection (MOD) is an important issue in advanced driver assistance systems (ADAS). There are two important moving objects, pedestrians and scooters in ADAS. In real-world systems, there exist two important challenges for MOD, including the computational complexity and the detection accuracy. The histogram of oriented gradient (HOG) features can easily detect the edge of object without invariance to changes in illumination and shadowing. However, to reduce the execution time for real-time systems, the image size should be down sampled which would lead the outlier influence to increase. For this reason, we propose the histogram of uniformly-oriented gradient (HUG) features to get better accurate description of the contour of human body. In the testing phase, the support vector machine (SVM) with linear kernel function is involved. Experimental results show the correctness and effectiveness of the proposed method. With SVM classifiers, the real testing results show the proposed HUG features achieve better than classification performance than the HOG ones.

Keywords: moving object detection, histogram of oriented gradient, histogram of uniformly-oriented gradient, linear support vector machine

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Authors: Eman Alzahrani

Abstract:

Date palm trees are abundant and cheap natural resources in Saudi Arabia. In this study, an activated carbon was prepared from palm trunks by chemical processes. The chemical activation was performed by impregnation of the raw materials after grinding with H3PO4 solution (63%), followed by placing of the sample solution on a muffle furnace at 400ºC for 30 min, and then at 800ºC for 10 min. The morphology of the fabricated material was checked using scanning electron microscopy that showed the rough surfaces on the carbon samples. The use of fabricated activated carbon for removal of eosin dye from aqueous solutions at different contact time, initial dye concentration, pH and adsorbent doses was investigated. The experimental results show that the adsorption process attains equilibrium within 20 min. The adsorption isotherm equilibrium was studied by means of the Langmuir and Freundlich isotherms, and it was found that the data fit the Langmuir isotherm equation with maximum monolayer adsorption capacity of 126.58 mg g-1. The results indicated that the home made activated carbon prepared from palm trunks has the ability to remove eosin dye from aqueous solution and it will be a promising adsorbent for the removal of harmful dyes from waste water.

Keywords: activated carbon, date palm trunks, H3PO4 activation, adsorption, dye removal, eosin dye, isotherm

Procedia PDF Downloads 333

Authors: Fahim Kahlouche, Alaoua Bouaicha, Sihem Chaîbeddra, Sid-Ali Rafa, Abdelhamid Benouali

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A designing of a structure requires its realization on rough or sloping ground. Besides the problem of the stability of the landslide, the behavior of the foundations that are bearing the structure is influenced by the destabilizing effect of the ground’s slope. This article focuses on the analysis of the slope stability exposed to loading by introducing the different factors influencing the slope’s behavior on the one hand, and on the influence of this slope on the foundation’s behavior on the other hand. This study is about the elastoplastic modelization using FLAC 2D. This software is based on the finite difference method, which is one of the older methods of numeric resolution of differential equations system with initial and boundary conditions. It was developed for the geotechnical simulation calculation. The aim of this simulation is to demonstrate the notable effect of shear modulus « G », cohesion « C », inclination angle (edge) « β », and distance between the foundation and the head of the slope on the stability of the slope as well as the stability of the foundation. In our simulation, the slope is constituted by homogenous ground. The foundation is considered as rigid/hard; therefore, the loading is made by the application of the vertical strengths on the nodes which represent the contact between the foundation and the ground. 

Keywords: slope, shallow foundation, numeric method, FLAC 2D

Procedia PDF Downloads 259

Authors: Fan Yu

Abstract:

An atrium is a place for natural climate exchanging of indoor and outdoor space of buildings, which plays an active role in the overall energy conservation, climate control and environmental purification of buildings. Its greatest contribution is serving as a natural light collector and distributor to solve the problem of natural lighting in large and deep spaces. However, in real situations, the atrium space often results in energy consumption due to improper design in considering its big size and large amount use of glass. Based on the purpose of energy conservation of buildings, this paper emphasizes the significance of natural lighting of atriums. Through literature research, case analysis and other methods, four factors, namely: the light transmittance through the top of the atrium, the geometric proportion of the atrium space, the size and position of windows and the material of the surface of walls in the atrium, were studied, and the influence of different architectural compositions on the natural light distribution of the atrium is discussed. Relying on the analysis of relevant cases, it is proposed that when designing the natural lighting of the atrium, the height and width of the atrium should be paid attention to, the atrium walls are required being rough surfaces and the atrium top-level windows need to be minimized in order to introduce more natural light into the buildings and achieve the purpose of energy conservation.

Keywords: energy conservation, atrium, natural lighting, architectural design

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Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

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Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: clusters of microcalcifications, ductal carcinoma in situ, least-square support vector machine, particle swarm optimization

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Authors: Karel Šebesta, Jiří Žáček, Matuš Salva, Mohammad Housam

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Drivers of agricultural vehicles are exposed to continuous vibration caused by driving over rough terrain. The long-term effects of these vibrations could start with a decreased level of vigilance at work and could reach the level of several health problems. Therefore, eliminating the vibration to maximize the comfort of the driver is essential for better/longer performance. One of the modern damping systems, which can deal with this problem is the Semi-active (S/A) suspension system featuring a Magnetorheological (MR) damper. With this damper, the damping level can be adjusted using varying currents through the coil. Adjustments of the damping force can be carried out continuously based on the evaluated data (position and acceleration of seat) by the control algorithm. The advantage of this system is the wide dynamic range and the high speed of force response time. Compared to other S/A or active systems, the MR damper does not need as much electrical power, and the system is much simpler. This paper aims to prove the effectiveness of this damping system used in the tractor seat. The vibration testing stand was designed and manufactured specifically for this type of research, which is used to simulate vibrations with constant amplitude at variable frequency.

Keywords: magnetorheological damper, semi-active suspension, seat scissor mechanism, sky-hook

Procedia PDF Downloads 76

Authors: David F. Nettleton, Christian Wasiak, Jonas Dorissen, David Gillen, Alexandr Tretyak, Elodie Bugnicourt, Alejandro Rosales

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In this work, preliminary results are given for the modeling and calibration of two inline processes, pultrusion, and laser ablation, using machine learning techniques. The end product of the processes is the core of a medical guidewire, manufactured to comply with a user specification of diameter and flexibility. An ensemble approach is followed which requires training several models. Two state of the art machine learning algorithms are benchmarked: Kernel Recursive Least Squares (KRLS) and Support Vector Regression (SVR). The final objective is to build a precise digital model of the pultrusion and laser ablation process in order to calibrate the resulting diameter and flexibility of a medical guidewire, which is the end product while taking into account the friction on the forming die. The result is an ensemble of models, whose output is within a strict required tolerance and which covers the required range of diameter and flexibility of the guidewire end product. The modeling and automatic calibration of complex in-line industrial processes is a key aspect of the Industry 4.0 movement for cyber-physical systems.

Keywords: calibration, data modeling, industrial processes, machine learning

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Authors: N. Khiati

Abstract:

The present paper attempts to report on some findings that emerged out of a larger scale doctorate research into English language needs of a renowned Algerian company of Hydrocarbon industry. From a multifaceted English for specific purposes (ESP) research perspective, the paper considers the English needs of the finance/legal department staff in the midst of the conflicting needs perspectives involving both objective needs indicators (i.e., the pressure of globalised business) and the general negative attitudes among the administrative -mainly jurists- staff towards English (favouring a non-adaptation strategy). The researcher’s unearthing of the latter’s needs is an endeavour to concretise the concepts of unmet, or unconscious needs, among others. This is why, these initially uncovered hidden needs will be detailed questioning educational background, namely previous language of instruction; training experiences and expectations; as well as the actual communicative practices derived from the retrospective interviews and preliminary quantitative data of the questionnaire. Based on these rough clues suggesting real needs, the researcher will tentatively propose some implications for both pre-service and in-service training organisers as well as for educational policy makers in favour of an English course in legal English for the jurists mainly from pre-graduate phases to in-service training.

Keywords: English for specific purposes (ESP), legal and finance staff, needs analysis, unmet/unconscious needs, training implications

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Authors: Xia Huo

Abstract:

The composition and metabolites of the gut microbiota can be altered by environmental pollutants. However, the effect of co-exposure to multiple pollutants on the human gut microbiota has not been sufficiently studied. In this study, gut microorganisms and their metabolites were compared between 33 children from Guiyu and 34 children from Haojiang. The exposure level was assessed by estimating the daily intake (EDI) of polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs), 6PPD-quinone (6PPDQ), and metal(loid)s in dust. Significant correlations were found between the EDIs of 6PPDQ, BDE28, PCB52, Ni, Cu, and both the alpha diversity index and specific metabolites in single-element models. The study found that the Bayesian kernel machine regression (BKMR) model showed a negative correlation between the EDIs of five pollutants (6PPDQ, BDE28, PCB52, Ni, and Cu) and the Chao 1 index, particularly beyond the 55th percentile. Furthermore, the EDIs of these five pollutants were positively correlated with the levels of the metabolite 2,4-diaminobutyric acid while negatively correlated with the levels of d-erythro-sphingosine and d-threitol. Our research suggests that exposure to 6PPDQ, BDE28, PCB52, Ni, and Cu in kindergarten dust is associated with alterations in the gut microbiota and its metabolites. These alterations may be associated with neurodevelopmental abnormalities in children.

Keywords: gut microbiota, 6PPDQ, PBDEs, PCBs, metal(loid)s, BKMR

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Authors: Jaishree Ranganathan, Poonam Rajurkar, Angelina A. Tzacheva, Zbigniew W. Ras

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In today’s world, business often depends on the customer feedback and reviews. Sentiment analysis helps identify and extract information about the sentiment or emotion of the of the topic or document. Attribute selection is a challenging problem, especially with large datasets in actionable pattern mining algorithms. Action Rule Mining is one of the methods to discover actionable patterns from data. Action Rules are rules that help describe specific actions to be made in the form of conditions that help achieve the desired outcome. The rules help to change from any undesirable or negative state to a more desirable or positive state. In this paper, we present a Lexicon based weighted scheme approach to identify emotions from customer feedback data in the area of manufacturing business. Also, we use Rough sets and explore the attribute selection method for large scale datasets. Then we apply Actionable pattern mining to extract possible emotion change recommendations. This kind of recommendations help business analyst to improve their customer service which leads to customer satisfaction and increase sales revenue.

Keywords: actionable pattern discovery, attribute selection, business data, data mining, emotion

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Authors: Michael Sigruener, Dirk Muscat, Nicole Struebbe

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Fiber reinforcement is a state of the art to enhance mechanical properties in plastics. For concrete and civil engineering, steel reinforcements are commonly used. Steel reinforcements show disadvantages in their chemical resistance and weight, whereas polymer fibers' major problems are in fiber-matrix adhesion and mechanical properties. In spite of these facts, longevity and easy handling, as well as chemical resistance motivate researches to develop a polymeric material for fiber reinforced concrete. Adhesion and interfacial mechanism in fiber-polymer-composites are already studied thoroughly. For polymer fibers used as concrete reinforcement, the bonding behavior still requires a deeper investigation. Therefore, several differing polymers (e.g., polypropylene (PP), polyamide 6 (PA6) and polyetheretherketone (PEEK)) were spun into fibers via single screw extrusion and monoaxial stretching. Fibers then were embedded in a concrete matrix, and Single-Fiber-Pull-Out-Tests (SFPT) were conducted to investigate bonding characteristics and microstructural interface of the composite. Differences in maximum pull-out-force, displacement and slope of the linear part of force vs displacement-function, which depicts the adhesion strength and the ductility of the interfacial bond were studied. In SFPT fiber, debonding is an inhomogeneous process, where the combination of interfacial bonding and friction mechanisms add up to a resulting value. Therefore, correlations between polymeric properties and pull-out-mechanisms have to be emphasized. To investigate these correlations, all fibers were introduced to a series of analysis such as differential scanning calorimetry (DSC), contact angle measurement, surface roughness and hardness analysis, tensile testing and scanning electron microscope (SEM). Of each polymer, smooth and abraded fibers were tested, first to simulate the abrasion and damage caused by a concrete mixing process and secondly to estimate the influence of mechanical anchoring of rough surfaces. In general, abraded fibers showed a significant increase in maximum pull-out-force due to better mechanical anchoring. Friction processes therefore play a major role to increase the maximum pull-out-force. The polymer hardness affects the tribological behavior and polymers with high hardness lead to lower surface roughness verified by SEM and surface roughness measurements. This concludes into a decreased maximum pull-out-force for hard polymers. High surface energy polymers show better interfacial bonding strength in general, which coincides with the conducted SFPT investigation. Polymers such as PEEK or PA6 show higher bonding strength in smooth and roughened fibers, revealed through high pull-out-force and concrete particles bonded on the fiber surface pictured via SEM analysis. The surface energy divides into dispersive and polar part, at which the slope is correlating with the polar part. Only polar polymers increase their SFPT-function slope due to better wetting abilities when showing a higher bonding area through rough surfaces. Hence, the maximum force and the bonding strength of an embedded fiber is a function of polarity, hardness, and consequently surface roughness. Other properties such as crystallinity or tensile strength do not affect bonding behavior. Through the conducted analysis, it is now feasible to understand and resolve different effects in pull-out-behavior step-by-step based on the polymer properties itself. This investigation developed a roadmap on how to engineer high adhering polymeric materials for fiber reinforcement of concrete.

Keywords: fiber-matrix interface, polymeric fibers, fiber reinforced concrete, single fiber pull-out test

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Authors: Davyd Urbanas, Pranas Baltrenas

Abstract:

It is well-known that, despite the constant increase of alternative energy sources usage, today combustible fuels are still widely used in power engineering. As a result of fuel combustion, significant amounts of nitrogen oxides (NOx) and carbon monoxide (CO is a product of incomplete combustion) are supplied to the atmosphere. Also, these pollutants are formed in industry (chemical production, refining, and metal production). In this work, the investigation of nitrogen oxides CO-selective catalytic reduction using new grain load-type catalysts was carried out. The catalysts containing the substrate and a thin active coating made of transition metal (Mn, Cu, and Nb) oxides were prepared with the use of electroless chemical deposition method. Chemical composition, chemical state, and morphology of the formed active coating were investigated using ICP-OES, EDX, SEM, and XPS techniques. The obtained results revealed that the prepared catalysts (Cu-Mn-oxide and Cu-Mn-Nb-oxide) have rough and developed surface and can be successfully used for the flue gas catalytic purification. The significant advantage of prepared catalysts is their suitability from technological application point of view, which differs this work from others dedicated to gas purification by SCR.

Keywords: flue gas, nitrogen oxides, selective catalytic reduction, transition metal oxides

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Authors: Bingjie Wang, Su-Yeon Kwon, Ik-Joong Kang

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A Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). As for the gold-chitosan nanoshell, it is made by using chitosan nanoparticles crosslinking with sodium tripolyphosphate(TPP) for the first step to form the chitosan nanoparticles, which would be covered with the gold sequentially. The size of the fabricated product was around 100nm. Based on the method that the sulfur end of the MPA linked to gold can form the very strong S–Au bond, and the carboxyl group, the other end of the MPA, can easily absorb the GABA. GABA is the mainly inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability throughout the nervous system. When the system formed, it generated SERS, which made a clear difference in the intensity of Raman scattering within the range of GABA concentration. So it is obtained from the experiment that the calibration curve according to the GABA concentration relevant with the SERS scattering. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

Keywords: chitosan-gold nanoshell, mercaptopropionic acid, γ-aminobutyric acid, surface-enhanced Raman scattering

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Authors: Ritu Rani

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In this paper, we apply minimalistically upheld linear semi-orthogonal B-spline wavelets, exceptionally developed for the limited interim to rough the obscure function present in the integral equations. Semi-orthogonal wavelets utilizing B-spline uniquely developed for the limited interim and these wavelets can be spoken to in a shut frame. This gives a minimized help. Semi-orthogonal wavelets frame the premise in the space L²(R). Utilizing this premise, an arbitrary function in L²(R) can be communicated as the wavelet arrangement. For the limited interim, the wavelet arrangement cannot be totally introduced by utilizing this premise. This is on the grounds that backings of some premise are truncated at the left or right end purposes of the interim. Subsequently, an uncommon premise must be brought into the wavelet development on the limited interim. These functions are alluded to as the limit scaling functions and limit wavelet functions. B-spline wavelet method has been connected to fathom linear and nonlinear integral equations and their systems. The above method diminishes the integral equations to systems of algebraic equations and afterward these systems can be illuminated by any standard numerical methods. Here, we have connected Newton's method with suitable starting speculation for solving these systems.

Keywords: semi-orthogonal, wavelet arrangement, integral equations, wavelet development

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Authors: Rhoann Kerh, Chen-Fu Chien, Kuo-Yi Lin

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In the era of rapidly increasing notebook market, consumer electronics manufacturers are facing a highly dynamic and competitive environment. In particular, the product appearance is the first part for user to distinguish the product from the product of other brands. Notebook product should differ in its appearance to engage users and contribute to the user experience (UX). The UX evaluates various product concepts to find the design for user needs; in addition, help the designer to further understand the product appearance preference of different market segment. However, few studies have been done for exploring the relationship between consumer background and the reaction of product appearance. This study aims to propose a data mining framework to capture the user’s information and the important relation between product appearance factors. The proposed framework consists of problem definition and structuring, data preparation, rules generation, and results evaluation and interpretation. An empirical study has been done in Taiwan that recruited 168 subjects from different background to experience the appearance performance of 11 different portable computers. The results assist the designers to develop product strategies based on the characteristics of consumers and the product concept that related to the UX, which help to launch the products to the right customers and increase the market shares. The results have shown the practical feasibility of the proposed framework.

Keywords: consumers decision making, product design, rough set theory, user experience

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Authors: Mehrnaz Alibeikloo, Hadi Khabbaz, Behzad Fatahi

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The spectral random field method is one of the widely used methods to obtain more reliable and accurate results in geotechnical problems involving material variability. Karhunen-Loeve (K-L) expansion method was applied to perform random field discretization of cross-correlated creep parameters. Karhunen-Loeve expansion method is based on eigenfunctions and eigenvalues of covariance function adopting Kernel integral solution. In this paper, the accuracy of Karhunen-Loeve expansion was investigated to predict long-term settlement of soft soils adopting elastic visco-plastic creep model. For this purpose, a parametric study was carried to evaluate the effect of K-L expansion terms and spatial correlation length on the reliability of results. The results indicate that small values of spatial correlation length require more K-L expansion terms. Moreover, by increasing spatial correlation length, the coefficient of variation (COV) of creep settlement increases, confirming more conservative and safer prediction.

Keywords: Karhunen-Loeve expansion, long-term settlement, reliability analysis, spatial correlation length

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Authors: A. Bahrani

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In order to study the effect of restricted irrigation systems and different potassium fertilizer on water use efficiency and yield of rapeseed (Brassica napus L.), an experiment was conducted in an arid area in Khuzestan, Iran in 2013. The main plots consisted of three irrigation methods: FI (full irrigation), alternate furrow irrigation (AFI) and fixed furrow irrigation (FFI). Each subplot received three rates of K fertiliser application: 0, 150 or 300 kg ha-1. The results showed that the plots receiving the full irrigation resulted in significantly higher grain yields, 1000-kernel weight and grain number per pod than both alternate treatments. However, the highest WUE were obtained in alternate furrow irrigation and 300 kg K ha-1 and the lowest one was found in the FI treatment and 0 kg K ha-1. Potassium application increased RWC in alternate furrow irrigation and fixed furrow irrigation than FI treatment. Maximum oil content was observed in those treatments where full irrigation was applied while minimum oil content was produced in FFI irrigated treatments. Potassium fertilizer also increased grain oil by 15 % than control. Deficit irrigation reduced oleic acid and erucic acid. However, oleic acid and linoleic acid increased with increasing of potassium.

Keywords: erucic acid, irrigation methods, linoleic acid, oil percent, oleic acid

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Authors: Muhammad Jawad Hashmi

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The idea of nuclear terrorism is as old as nuclear weapons but the global concerns of likelihood of nuclear terrorism are uncertain. Post 9/11 trends manifest that terrorists are believers of massive causalities. Innovation in terrorist’s tactics, sophisticated weaponry, vulnerability, theft and smuggling of nuclear/radiological material, connections between terrorists, black market and rough regimes are signaling seriousness of upcoming challenges as well as global trends of “terror-transnationalism.” Furthermore, the International-Atomic-Energy-Agency’s database recorded 2734 incidents regarding misuse, unauthorized possession, trafficking of nuclear material etc. Since, this data also includes incidents from south Asia, so, there is every possibility to claim that such illicit activities may increase in future, mainly due to expansion of nuclear industry in South Asia. Moreover, due to such mishaps the region is vulnerable to threats of nuclear terrorism. This is also a reason that the region is in limelight along with issues such as rapidly growing nuclear arsenals, nuclear safety and security, terrorism and political instability. With this backdrop, this study is aimed to investigate the prevailing threats and challenges in South Asia vis a vis nuclear safety and security. A comparative analysis of the overall capabilities would be done to identify the areas of cooperation to eliminate the probability of nuclear/radiological terrorism in the region.

Keywords: nuclear terrorism, safety, security, South Asia, india, Pakistan

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Authors: Mohammed Idaan Hassan Al-Majidi

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An analysis of twenty one assorted brands of vegetable oils in Babylon Iraq, reveals varying levels of cholesterol content. Cholesterol was found to be present in most of the oil brands sampled using three standard methods. Cholesterol was detected in seventeen of the vegetable oil brands with concentration of less than 1 mg/ml while seven of the oil brands had cholesterol concentrations ranging between 1-4 mg/ml. Low iodine values were obtained in four of the vegetable oil brands and three of them had high acid values. High performance liquid chromatography (HPLC) confirmed the presence of cholesterol at varying concentrations in all the oil brands and gave the lowest detectable cholesterol values in all the oil brands. The Laser brand made from rapeseed had the highest cholesterol concentration of 3.2 mg/ml while Grand brand made from groundnuts had the least concentration (0.12 mg/ml) of cholesterol using HPLC analysis. Leibermann-Burchard method showed that Gino brand from palm kernel had the least concentration of cholesterol (3.86 mg/ml ±0.032) and the highest concentration of 3.996 mg/ml ±0.0404 was obtained in Sesame seed oil brand. This report is important in view of health implications of cholesterol in our diets. Consequently, we have been able to show that there is no cholesterol free oil in the market as shown on the vegetable oil brand labels. Therefore, companies producing and marketing vegetable oils are enjoined to desist from misleading the public by labeling their products as “cholesterol free”. They should indicate the amount of cholesterol present in the vegetable oil, no matter how small the quantity may be.

Keywords: vegetable oils, heart diseases, leibermann-burchard, cholesterol

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Authors: Chanh Nghia Nguyen, Yu Kurokawa, Hirotsugu Inoue

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The surface roughness is an important parameter for evaluating the quality of material surfaces since it affects functions and performance of industrial components. Although stylus and optical techniques are commonly used for measuring the surface roughness, they are applicable only to accessible surfaces. In practice, surface roughness measurement from the back side is sometimes demanded, for example, in inspection of safety-critical parts such as inner surface of pipes. However, little attention has been paid to the measurement of back surface roughness so far. Since back surface is usually inaccessible by stylus or optical techniques, ultrasonic technique is one of the most effective among others. In this research, an ultrasonic pulse-echo technique is considered for evaluating the pitch and the height of back surface having periodic triangular profile as a very first step. The pitch of the surface profile is measured by applying the diffraction grating theory for oblique incidence; then the height is evaluated by numerical analysis based on the Kirchhoff theory for normal incidence. The validity of the proposed method was verified by both numerical simulation and experiment. It was confirmed that the pitch is accurately measured in most cases. The height was also evaluated with good accuracy when it is smaller than a half of the pitch because of the approximation in the Kirchhoff theory.

Keywords: back side, inaccessible surface, periodic roughness, pulse-echo technique, ultrasonic NDE

Procedia PDF Downloads 251

Authors: Amirul Al-Ashraf Abdullah, Hema Ramachandran, Iszatty Ismail

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Oleochemical industry in Malaysia has been diversifying significantly due to the abundant supply of both palm and kernel oils as raw materials as well as the high demand for downstream products such as fatty acids, fatty alcohols and glycerine. However, environmental awareness is growing rapidly in Malaysia because oleochemical industry is one of the palm-oil based industries that possess risk to the environment. Glycerine pitch is one of the scheduled wastes generated from the fatty acid plants in Malaysia and its discharge may cause a serious environmental problem. Therefore, it is imperative to find alternative applications for this waste glycerine. Consequently, the aim of this research is to explore the application of glycerine pitch as direct fermentation substrate in the biosynthesis of poly(3-hydroxybutyrate-co-4-hydroxybutyrate) [P(3HB-co-4HB)] copolymer, aiming to contribute toward the sustainable production of biopolymer in the world. Utilization of glycerine pitch (10 g/l) together with 1,4-butanediol (5 g/l) had resulted in the achievement of 40 mol% 4HB monomer with the highest PHA concentration of 2.91 g/l. Synthesis of yellow pigment which exhibited antimicrobial properties occurred simultaneously with the production of P(3HB-co-4HB) through the use of glycerine pitch as renewable carbon resource. Utilization of glycerine pitch in the biosynthesis of P(3HB-co-4HB) will not only contribute to reducing society’s dependence on non-renewable resources but also will promote the development of cost efficiency microbial fermentation towards biosustainability and green technology.

Keywords: biopolymer, glycerine pitch, natural pigment, P(3HB-co-4HB)

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Authors: Bingjie Wang, Su-Yeon Kwon, Ik-Joong Kang

Abstract:

The goal of this experiment is to develop a sensor that can quickly check the concentration by using the nanoparticles made by chitosan and gold. Using chitosan nanoparticles crosslinking with sodium tripolyphosphate(TPP) is the first step to form the chitosan nanoparticles, which would be covered with the gold sequentially. The size of the fabricated product was around 100nm. Based on the method that the sulfur end of the MPA linked to gold can form the very strong S–Au bond, and the carboxyl group, the other end of the MPA, can easily absorb the GABA. As for the GABA, what is the primary inhibitory neurotransmitter in the mammalian central nervous system in the human body. It plays such significant role in reducing neuronal excitability pass through the nervous system. A Surface-enhanced Raman Scattering (SERS) as the principle for enhancing Raman scattering by molecules adsorbed on rough metal surfaces or by nanostructures is used to detect the concentration change of γ-Aminobutyric Acid (GABA). When the system is formed, it generated SERS, which made a clear difference in the intensity of Raman scattering within the range of GABA concentration. So it is obtained from the experiment that the calibration curve according to the GABA concentration relevant with the SERS scattering. In this study, DLS, SEM, FT-IR, UV, SERS were used to analyze the products to obtain the conclusion.

Keywords: mercaptopropionic acid, chitosan-gold nanoshell, γ-aminobutyric acid, surface-enhanced raman scattering

Procedia PDF Downloads 247

Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

Abstract:

Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine, Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis, and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: student performance, supervised machine learning, classification, cross-validation, prediction

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Authors: Jorge Gonzalez Camus, Carlos Lizama

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In this work is proved the existence of at least one globally attractive mild solution to the Cauchy problem, for fractional evolution equation of neutral type, involving the fractional derivate in Caputo sense. An almost sectorial operator on a Banach space X and a kernel belonging to a large class appears in the equation, which covers many relevant cases from physics applications, in particular, the important case of time - fractional evolution equations of neutral type. The main tool used in this work was the Hausdorff measure of noncompactness and fixed point theorems, specifically Darbo-type. Initially, the equation is a Cauchy problem, involving a fractional derivate in Caputo sense. Then, is formulated the equivalent integral version, and defining a convenient functional, using the analytic integral resolvent operator, and verifying the hypothesis of the fixed point theorem of Darbo type, give us the existence of mild solution for the initial problem. Furthermore, each mild solution is globally attractive, a property that is desired in asymptotic behavior for that solution.

Keywords: attractive mild solutions, integral Volterra equations, neutral type equations, non-local in time equations

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Authors: S. Saju, G. Thirugnanam

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In this paper, a medical image watermarking algorithm based on contourlet is proposed. Medical image watermarking is a special subcategory of image watermarking in the sense that images have special requirements. Watermarked medical images should not differ perceptually from their original counterparts because clinical reading of images must not be affected. Watermarking techniques based on wavelet transform are reported in many literatures but robustness and security using contourlet are better when compared to wavelet transform. The main challenge in exploring geometry in images comes from the discrete nature of the data. In this paper, original image is decomposed to two level using contourlet and the watermark is embedded in the resultant sub-bands. Sub-band selection is based on the value of Peak Signal to Noise Ratio (PSNR) that is calculated between watermarked and original image. To extract the watermark, Kernel ICA is used and it has a novel characteristic is that it does not require the transformation process to extract the watermark. Simulation results show that proposed scheme is robust against attacks such as Salt and Pepper noise, Median filtering and rotation. The performance measures like PSNR and Similarity measure are evaluated and compared with Discrete Wavelet Transform (DWT) to prove the robustness of the scheme. Simulations are carried out using Matlab Software.

Keywords: digital watermarking, independent component analysis, wavelet transform, contourlet

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Authors: Shafiullah Soomro

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Active contour is one of the image segmentation techniques and its goal is to capture required object boundaries within an image. In this paper, we propose a novel image segmentation method by using an active contour method based on anisotropic diffusion feature enhancement technique. The traditional active contour methods use only pixel information to perform segmentation, which produces inaccurate results when an image has some noise or complex background. We use Perona and Malik diffusion scheme for feature enhancement, which sharpens the object boundaries and blurs the background variations. Our main contribution is the formulation of a new SPF (signed pressure force) function, which uses global intensity information across the regions. By minimizing an energy function using partial differential framework the proposed method captures semantically meaningful boundaries instead of catching uninterested regions. Finally, we use a Gaussian kernel which eliminates the problem of reinitialization in level set function. We use several synthetic and real images from different modalities to validate the performance of the proposed method. In the experimental section, we have found the proposed method performance is better qualitatively and quantitatively and yield results with higher accuracy compared to other state-of-the-art methods.

Keywords: active contours, anisotropic diffusion, level-set, partial differential equations

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Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Joseph Thomas Eghwerido, Julian I. Mbegbu

Abstract:

In modelling environment processes, we apply multidisciplinary knowledge to explain, explore and predict the Earth's response to natural human-induced environmental changes. Thus, the analysis of spatial-time ecological and environmental studies, the spatial parameters of interest are always heterogeneous. This often negates the assumption of stationarity. Hence, the dispersion of the transportation of atmospheric pollutants, landscape or topographic effect, weather patterns depends on a good estimate of spatial covariance. The generalized linear mixed model, although linear in the expected value parameters, its likelihood varies nonlinearly as a function of the covariance parameters. As a consequence, computing estimates for a linear mixed model requires the iterative solution of a system of simultaneous nonlinear equations. In other to predict the variables at unsampled locations, we need to know the estimate of the present sampled variables. The geostatistical methods for solving this spatial problem assume covariance stationarity (locally defined covariance) and uniform in space; which is not apparently valid because spatial processes often exhibit nonstationary covariance. Hence, they have globally defined covariance. We shall consider different existing methods of solutions of spatial covariance of a space-time processes at unsampled locations. This stationary covariance changes with locations for multiple time set with some asymptotic properties.

Keywords: parametric, nonstationary, Kernel, Kriging

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