Search results for: sample extraction

Authors: Arezou Hajhashemi, Karim Asgari, Masoud Etemadifar, Maryam Keyvani, Ali Hekmatnia

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Multiple Sclerosis (MS) is one of the most prevalent demyelinating diseases in CNS. As in other chronic cerebral diseases, impairment in cognitive functioning and in memory is popular. Because of the inflammatory and demyelinating nature of the disease, the localization of plaques in different parts of the Prefrontal and Limbic System, may lead to memorial symptoms. This investigation was intended to study relationship between frequency of plaques and memorial symptoms arising from dysfunction limbic system and prefrontal of patients with MS. The sample was selected randomly from patients with MS with memory problem, who have been referred to Isfahan Multiple Sclerosis Society. Brain System Test and Memory Test was administered to the sample, and their MRI's were analyzed by specialist in order to indentify two different parts of plaques. The data was analyzed by SPSS. The results showed that there were significant relationship between MS plaques and prefrontal's dysfunction and memorial symptom related to prefrontal area; however, there were no significant relationship between MS plaques and limbic system's dysfunction and memorial symptoms related to limbic system area. The results of this study suggest that memorial symptoms due to injury regions of the brain have the most significant relationship to prefrontal. Better judgment about these results needs more studies in future.

Keywords: multiple sclerosis, magnetic image, brain injury, behavior disorder

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Authors: Saleem Z. Ramadan

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This paper discusses the effects of using progressive Type-I right censoring on the design of the Simple Step Accelerated Life testing using Bayesian approach for Weibull life products under the assumption of cumulative exposure model. The optimization criterion used in this paper is to minimize the expected pre-posterior variance of the PTH percentile time of failures. The model variables are the stress changing time and the stress value for the first step. A comparison between the conventional and the progressive Type-I right censoring is provided. The results have shown that the progressive Type-I right censoring reduces the cost of testing on the expense of the test precision when the sample size is small. Moreover, the results have shown that using strong priors or large sample size reduces the sensitivity of the test precision to the censoring proportion. Hence, the progressive Type-I right censoring is recommended in these cases as progressive Type-I right censoring reduces the cost of the test and doesn't affect the precision of the test a lot. Moreover, the results have shown that using direct or indirect priors affects the precision of the test.

Keywords: reliability, accelerated life testing, cumulative exposure model, Bayesian estimation, progressive type-I censoring, Weibull distribution

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Authors: Shatabdi Goon

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OBJECTIVE: To determine the prevalence and associations between breakfast skipping and health status for university professionals in Bangladesh. DESIGN: A cross-sectional descriptive study design was performed using information on respondent’s sociodemographic status and eating behavior. Factors associated with breakfast skipping were identified using multivariate regression models. SETTINGS: Data obtained from a representative sample (n 120) of university professionals randomly selected from two distinct universities in Dhaka city, Bangladesh. SUBJECT: A total number of one hundred and twenty university professionals with a mean age of 29 years. RESULT: Results indicated that approximately 35.8% of the sample skipped breakfast. Gender was the only statistically significant sociodemographic variable, with females skipping at over two times the rate of males (OR 95% CI: 1.9; 0.90-4.13). The reasons given for skipping breakfast were almost exclusively habit (39.5%), work pressure (23.2%) and lack of time (16.2%). Skippers were significantly more likely to be obese (OR 2.4; 95% CI 1.02- 5.7), less energetic (OR 3.5; 95% CI 1.5-8.6), associated with health problems (OR 4.3; 95% CI 1.8- 10.17) and eating tendency of fast food (OR 2.5; 95% CI 1.13 - 5.5). Gastric and heart burn (X2=4.19, p<0.05) and high blood pressure (X2=5.027, p<0.05) were detected among 34.9% and 27.9 % of those employees respectively identified as breakfast skippers and they showed significantly high prevalence. CONCLUSION: Breakfast skipping is highly prevalent among university professionals with significant association of different health problems in Bangladesh. Health promotion strategies should be used to encourage all adults to eat breakfast regularly.

Keywords: breakfast, healthy lifestyle, breakfast skipping, health status, university professionals

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Authors: Majid Habib Khan, Jinwei Zhao, Xinhong Hei, Liu Jiedong, Rana Shahzad Noor, Muhammad Imran

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Deep learning is increasingly employed in image classification, yet the scarcity and high cost of labeled data for training remain a challenge. Limited samples often lead to overfitting due to biased sample distribution. This paper introduces a dynamic distribution calibration method for few-shot learning. Initially, base and new class samples undergo normalization to mitigate disparate feature magnitudes. A pre-trained model then extracts feature vectors from both classes. The method dynamically selects distribution characteristics from base classes (both adjacent and remote) in the embedding space, using a threshold value approach for new class samples. Given the propensity of similar classes to share feature distributions like mean and variance, this research assumes a Gaussian distribution for feature vectors. Subsequently, distributional features of new class samples are calibrated using a corrected hyperparameter, derived from the distribution features of both adjacent and distant base classes. This calibration augments the new class sample set. The technique demonstrates significant improvements, with up to 4% accuracy gains in few-shot classification challenges, as evidenced by tests on miniImagenet and CUB datasets.

Keywords: deep learning, computer vision, image classification, few-shot learning, threshold

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Authors: M. Draman, S. Z. Muhamad Yassin, M. S. Alias, Z. Lambak, M. I. Zulkifli, S. N. Padhi, K. N. Baharim, F. Maskuriy, A. I. A. Rahim

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The performance of Malay automatic speech recognition (ASR) system for the call centre environment is presented. The system utilizes Kaldi toolkit as the platform to the entire library and algorithm used in performing the ASR task. The acoustic model implemented in this system uses a deep neural network (DNN) method to model the acoustic signal and the standard (n-gram) model for language modelling. With 80 hours of training data from the call centre recordings, the ASR system can achieve 72% of accuracy that corresponds to 28% of word error rate (WER). The testing was done using 20 hours of audio data. Despite the implementation of DNN, the system shows a low accuracy owing to the varieties of noises, accent and dialect that typically occurs in Malaysian call centre environment. This significant variation of speakers is reflected by the large standard deviation of the average word error rate (WERav) (i.e., ~ 10%). It is observed that the lowest WER (13.8%) was obtained from recording sample with a standard Malay dialect (central Malaysia) of native speaker as compared to 49% of the sample with the highest WER that contains conversation of the speaker that uses non-standard Malay dialect.

Keywords: conversational speech recognition, deep neural network, Malay language, speech recognition

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Authors: M. H. Pazandeh, M. Doudi, S. Barahimi, L. Rahimzadeh Torabi

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The use of antibiotics is essential in reducing the occurrence of adverse effects and inhibiting the emergence of antibiotic resistance in microbial populations. The necessity for a novel methodology concerning local administration of antibiotics has arisen, with particular focus on dealing with localized infections prompted by bacterial colonization of medical devices or implant materials. Bioactive glasses (BG) are extensively employed in the field of regenerative medicine, encompassing a diverse range of materials utilized for drug delivery systems. In the present investigation, various drug carriers for imipenem and tetracycline, namely single systems BG/SnO2, BG/NiO with varying proportions of metal oxide, and nanocomposite BG/SnO2/NiO, were synthesized through the sol-gel technique. The antibacterial efficacy of the synthesized samples was assessed through the utilization of the disk diffusion method with the aim of neutralizing Staphylococcus aureus as the bacterial model. The current study involved the examination of the bioactivity of two samples, namely BG10SnO2/10NiO and BG20SnO2, which were chosen based on their heightened bacterial inactivation properties. This evaluation entailed the employment of two techniques: the measurement of the pH of simulated body fluid (SBF) solution and the analysis of the sample tablets through X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared (FTIR) spectroscopy. The sample tablets were submerged in SBF for varying durations of 7, 14, and 28 days. The bioactivity of the composite bioactive glass sample was assessed through characterization of alterations in its surface morphology, structure, and chemical composition. This evaluation was performed using scanning electron microscopy (SEM), Fourier-transform infrared (FTIR) spectroscopy, and X-ray diffraction spectroscopy. Subsequently, the sample was immersed in simulated liquids to simulate its behavior in biological environments. The specific body fat percentage (SBF) was assessed over a 28-day period. The confirmation of the formation of a hydroxyapatite surface layer serves as a distinct indicator of bioactivity. The infusion of antibiotics into the composite bioactive glass specimen was done separately, and then the release kinetics of tetracycline and imipenem were tested in simulated body fluid (SBF). Antimicrobial effectiveness against various bacterial strains have been proven in numerous instances using both melt and sol-gel techniques to create multiple bioactive glass compositions. An elevated concentration of calcium ions within a solution has been observed to cause an increase in the pH level. In aqueous suspensions, bioactive glass particles manifest a significant antimicrobial impact. The composite bioactive glass specimen exhibits a gradual and uninterrupted release, which is highly desirable for a drug delivery system over a span of 72 hours. The reduction in absorption, which signals the loss of a portion of the antibiotic during the loading process from the initial phosphate-buffered saline solution, indicates the successful bonding of the two antibiotics to the surfaces of the bioactive glass samples. The sample denoted as BG/10SnO2/10NiO exhibits a higher loading of particles compared to the sample designated as BG/20SnO2 in the context of bioactive glass. The enriched sample demonstrates a heightened bactericidal impact on the bacteria under investigation while concurrently preserving its antibacterial characteristics. Tailored bioactive glass that incorporates hydroxyapatite, with a regulated and efficient release of drugs targeting bacterial infections, holds promise as a potential framework for bone implant scaffolds following rigorous clinical evaluation, thereby establishing potential future biomedical uses. During the modification process, the introduction of metal oxides into bioactive glass resulted in improved antibacterial characteristics, particularly in the composite bioactive glass sample that displayed the highest level of efficiency.

Keywords: antibacterial, bioactive glasses, implant infections, multi drug resistant

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Authors: Marta Fernández Olmos, Ana Gargallo Castel, Alice Salami

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The literature has shown the importance of studying the issue of business survival in highly competitive environments. In particular, the wine sector has certain characteristics that make it interesting to study factors that increase the possibility of wineries' survival, such as individual productivity, winery size, age, innovation efforts or the maturity of the industry itself, among others. Due to the importance of these factors, this research aims to analyze whether the possibility of wineries' survival increases if they are family businesses or if there is gender diversity in senior management. To this end, a nationwide survey was carried out. The sample was made up of wineries from all the Spanish appellations of origin, using this sample to analyze the survival of the diverse types of wineries according to the factors to be studied. The main results indicate that family wineries survive longer, suggesting that this may be due to the fact that the main objective of family wineries is the continuity of the business in the long term. Regarding gender diversity, wineries that have a female presence in top roles in management, adding gender diversity, survive more than those with a predominantly male presence. Based on these results, it is advisable to consider the importance of family businesses, especially in this type of sector. In addition, support should be provided for the inclusion of a female labor force to improve the possibility of survival.

Keywords: gender, family business, wine industry, survival

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Authors: Yanxue Shang, Jingbin Zeng

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Chlorobenzene homologues (CBHs) are a category of environmental pollutants that can not be ignored. They can stay in the environment for a long period and are potentially carcinogenic. The traditional degradation method of CBHs is dechlorination followed by sample preparation and analysis. This is not only time-consuming and laborious, but the detection and analysis processes are used in conjunction with large-scale instruments. Therefore, this can not achieve rapid and low-cost detection. Compared with traditional sensing methods, colorimetric sensing is simpler and more convenient. In recent years, chromaticity sensors based on fluorescence have attracted more and more attention. Compared with sensing methods based on changes in fluorescence intensity, changes in color gradients are easier to recognize by the naked eye. Accordingly, this work proposes to use single drop microextraction (SDME) technology to solve the above problems. After the dechlorination reaction was completed, the organic droplet extracts Cl⁻ and realizes fluorescence colorimetric sensing at the same time. This method was integrated sample processing and visual in-situ detection, simplifying the detection process. As a fluorescence colorimetric sensor material, CsPbBr₃ was encapsulated in MOF-5 to construct CsPbBr₃@MOF-5 fluorescence colorimetric composite. Then the fluorescence colorimetric sensor was constructed by dispersing the composite in SDME organic droplets. When the Br⁻ in CsPbBr₃ exchanges with Cl⁻ produced by the dechlorination reactions, it is converted into CsPbCl₃. The fluorescence color of the single droplet of SDME will change from green to blue emission, thereby realizing visual observation. Therein, SDME can enhance the concentration and enrichment of Cl⁻ and instead of sample pretreatment. The fluorescence color change of CsPbBr₃@MOF-5 can replace the detection process of large-scale instruments to achieve real-time rapid detection. Due to the absorption ability of MOF-5, it can not only improve the stability of CsPbBr₃, but induce the adsorption of Cl⁻. Simultaneously, accelerate the exchange of Br- and Cl⁻ in CsPbBr₃ and the detection process of Cl⁻. The absorption process was verified by density functional theory (DFT) calculations. This method exhibits exceptional linearity for Cl⁻ in the range of 10⁻² - 10⁻⁶ M (10000 μM - 1 μM) with a limit of detection of 10⁻⁷ M. Whereafter, the dechlorination reactions of different kinds of CBHs were also carried out with this method, and all had satisfactory detection ability. Also verified the accuracy by gas chromatography (GC), and it was found that the SDME we developed in this work had high credibility. In summary, the in-situ visualization method of dechlorination reaction detection was a combination of sample processing and fluorescence colorimetric sensing. Thus, the strategy researched herein represents a promising method for the visual detection of dechlorination reactions and can be extended for applications in environments, chemical industries, and foods.

Keywords: chlorobenzene homologues, colorimetric sensor, metal halide perovskite, metal-organic frameworks, single drop microextraction

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Authors: H. Imad, Y. Cheah, O. Aamera

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The aims of this research are to study the mitochondrial non-coding region by using the Sanger sequencing technique and establish the degree of variation characteristics of a fragment. FTA® Technology (FTA™ paper DNA extraction) utilized to extract DNA. A portion of a non-coding region encompassing positions 37 to 340 amplified in accordance with the Anderson reference sequence. PCR products purified by EZ-10 spin column then sequenced and detected by using the ABI 3730xL DNA Analyzer. New polymorphic positions 57, 63, and 101 are described may in future be suitable sources for identification purpose. The data obtained can be used to identify variable nucleotide positions characterized by frequent occurrence most promising for identification variants.

Keywords: encompassing nucleotide positions 37 to 340, HVII, Iraq, mitochondrial DNA, polymorphism, frequency

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Authors: Mehmood Ali, Attaullah Khan, Md. Abul Kalam

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Petroleum crude oil reserves are going to deplete in future due to the consumption of fossil fuels in transportation and energy generating sector. Thus, increasing the fossil fuel prices and also causing environmental degradation issues such as climate change and global warming due to air pollution. Therefore, to tackle these issues the environmentally friendly fuels are the potential substitute with lower emissions of toxic gases. A non-edible vegetable oilseed crop, Jatropha curcas, from different origins such as Malaysia, Thailand and India were cultivated in Pakistan. The harvested seeds physical, chemical and mechanical properties were measured, having an influence on the post-harvesting machines design parameters for dehulling, storing bins, drying, oil extraction from seeds with a screw expeller and in-situ transesterification reaction to produce biodiesel fuel. The seed variety from Thailand was found better in comparison of its properties with other varieties from Malaysia and India. The seed yield from these three varieties i.e. Malaysia, Thailand and India were 829, 943 and 735 kg/ acre/ year respectively. While the oil extraction yield from Thailand variety seed was found higher (i.e. 32.61 % by wt.) as compared to other two varieties from Malaysia and India were 27.96 and 24.96 % by wt respectively. The physical properties investigated showed the geometric mean diameter of seeds from three varieties Malaysia, Thailand and India were 11.350, 10.505 and 11.324 mm, while the sphericity of seeds were found 0.656, 0.664 and 0.655. The bulk densities of the powdered seeds from three varieties Malaysia, Thailand and India, were found as 0.9697, 0.9932 and 0.9601 g/cm³ and % passing was obtained with sieve test were 78.7, 87.1 and 79.3 respectively. The densities of the extracted oil from three varieties Malaysia, Thailand and India were found 0.902, 0.898 and 0.902 g/ mL with corresponding kinematic viscosities 54.50, 49.18 and 48.16 mm2/sec respectively. The higher heating values (HHV) of extracted oil from Malaysia, Thailand and India seed varieties were measured as 40.29, 36.41 and 34.27 MJ/ kg, while the HHV of de-oiled cake from these varieties were 21.23, 20.78 and 17.31 MJ/kg respectively. The de-oiled cake can be used as compost with nutrients and carbon content to enhance soil fertility to grow future Jatropha curcas oil seed crops and also can be used as a fuel for heating and cooking purpose. Moreover, the mechanical parameter micro Vickers hardness of Malaysia seed was found lowest 16.30 HV measured with seed in a horizontal position to the loading in comparison to other two varieties as 25.2 and 18.7 HV from Thailand and India respectively. The fatty acid composition of three varieties of seed oil showed the presence of C8-C22, required to produce good quality biodiesel fuel. In terms of physicochemical properties of seeds and its extracted oil, the variety from Thailand was found better as compared to the other two varieties.

Keywords: biodiesel, Jatropha curcas, mechanical property, physico-chemical properties

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Authors: M. Umar Hafeez, Furqan Khursheed Hashmi, Nadeem Irfan Bukhari, Shahzad Ali, Muzammil Ali

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The trend of self-medication is increasing due to various factors and is associated with a large number of complications. A cross-sectional study was aimed to investigate self-medication trend in an urban community and its correlates such as level of education, gender and behavior of using psychoactive medicines. A validated questionnaire was used to collect the data from different locations of Lahore, provincial capital of Punjab, Pakistan. The trend of self-medication was noted in reference to difference in educational level and in gender. This study showed that total 110 respondents, all literate,were found to be self-medicating, and their educational status was as 73.13% primary, 63.15% secondary, 61.12% higher secondary and 62.15% university going. In this sample 74.99% were males and 48.00%were females. Twenty nine (26.36%) of the total sample were found to be using psychoactive agents without consulting the physician. The trend of self-medication was 10% higher in individuals having primary level education, whereas there was not much difference of self-medication trend in other levels of education. The main reasons involved in self-medication trend were socio-economic status, medicine accessibility, religious and cultural beliefs, lack of awareness about risks associated with medicine, non-prescription sale of medicines and previous medication experience. The trend of self-medication of psychotropic agents is quite significant.

Keywords: self-medication, educated community, psychotropic drugs, education levels

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Authors: Jovana Nikolov, Natasa Todorovic, Ivana Stojkovic

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Monitoring of 222Rn in drinking or surface waters, as well as in groundwater has been performed in connection with geological, hydrogeological and hydrological surveys and health hazard studies. Liquid scintillation counting (LSC) is often preferred analytical method for 222Rn measurements in waters because it allows multiple-sample automatic analysis. LSC method implies mixing of water samples with organic scintillation cocktail, which triggers radon diffusion from the aqueous into organic phase for which it has a much greater affinity, eliminating possibility of radon emanation in that manner. Two direct LSC methods that assume different sample composition have been presented, optimized and evaluated in this study. One-phase method assumed direct mixing of 10 ml sample with 10 ml of emulsifying cocktail (Ultima Gold AB scintillation cocktail is used). Two-phase method involved usage of water-immiscible cocktails (in this study High Efficiency Mineral Oil Scintillator, Opti-Fluor O and Ultima Gold F are used). Calibration samples were prepared with aqueous 226Ra standard in glass 20 ml vials and counted on ultra-low background spectrometer Quantulus 1220TM equipped with PSA (Pulse Shape Analysis) circuit which discriminates alpha/beta spectra. Since calibration procedure is carried out with 226Ra standard, which has both alpha and beta progenies, it is clear that PSA discriminator has vital importance in order to provide reliable and precise spectra separation. Consequentially, calibration procedure was done through investigation of PSA discriminator level influence on 222Rn efficiency detection, using 226Ra calibration standard in wide range of activity concentrations. Evaluation of presented methods was based on obtained efficiency detections and achieved Minimal Detectable Activity (MDA). Comparison of presented methods, accuracy and precision as well as different scintillation cocktail’s performance was considered from results of measurements of 226Ra spiked water samples with known activity and environmental samples.

Keywords: 222Rn in water, Quantulus1220TM, scintillation cocktail, PSA parameter

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Authors: Stella Sten, Peter Hedström, Joakim Odqvist, Susanne Norgren

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Two functionally graded cemented carbide samples have been produced by local addition of Titanium carbide (TiC) to a pressed Tungsten carbide and Cobalt, WC-10 wt% Co, green body prior to sintering, with the aim of creating a gradient in both composition and grain size in the as-sintered component. The two samples differ only by the in-going WC particle size, where one sub-micron and one coarse WC particle size have been chosen for comparison. The produced sintered samples had a gradient, thus a non-homogenous structure. The Titanium (Ti), Cobalt (Co), and Carbon (C) concentration profiles have been investigated using SEM-EDS and WDS; in addition, the Vickers hardness profile has been measured. Moreover, the Ti concentration profile has been simulated using DICTRA software and compared with experimental results. The concentration and hardness profiles show a similar trend for both samples. Ti and C levels decrease, as expected from the area of TiC application, whereas Co increases towards the edge of the samples. The non-homogenous composition affects the number of stable phases and WC grain size evolution. The sample with finer in-going WC grain size shows a shorter gamma (γ) phase zone and a larger difference in WC grain size compared to the coarse-grained sample. Both samples show, independent of the composition, the presence of abnormally large grains.

Keywords: cemented carbide, functional gradient material, grain growth, sintering

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Authors: Sozan H. Omar, Lina L. Al-Rewaili

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The current study aimed to measure the fifth Grade student skills of reading illustrates in physical and chemical chapter included in science textbook, as well as identity the tasks the dispersants related to designing these illustrates which obstruct the students to read them properly. The researcher applied the test instrument of open discuss questions to measure the skill of: recognizing, description, interpretation and assessment for a sample of this research consisted of (269) students who read three illustrates, and conduct an interview with sample of them (27) students to recognize the dispersants related to designing of these illustrates. The study results showed that there are poor levels in illustrated drawing reading skills: description, interpretation, and assessment. The most important dispersants which obstruct the students to read theses illustrates properly representing: Art impacts of these illustrates, there are some elements which don’t serve these illustrates. In the light of the above results, the researcher provided some recommendations such as training the students on using the images and illustrates properly in science textbooks, as well as create simple designs of illustrates and they should be free of crowded elements and impacts which don’t serve the illustrates.

Keywords: reading illustrated drawings skills, fifth grade science, physical and chemical changes

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Authors: Da-Ming Huang, Ya-Ting Tsai, Shyh-Hau Wang

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Ultrasound signals backscattered from the soft tissues are mainly depending on the size, density, distribution, and other elastic properties of scatterers in the interrogated sample volume. The quantitative analysis of ultrasonic backscattering is frequently implemented using the statistical approach due to that of backscattering signals tends to be with the nature of the random variable. Thus, the statistical analysis, such as Nakagami statistics, has been applied to characterize the density and distribution of scatterers of a sample. Yet, the accuracy of statistical analysis could be readily affected by the receiving signals associated with the nature of incident ultrasound wave and acoustical properties of samples. Thus, in the present study, efforts were made to explore such effects as the ultrasound operational modes and attenuation of biological tissue on the estimation of corresponding Nakagami statistical parameter (m parameter). In vitro measurements were performed from healthy and pathological fibrosis porcine livers using different single-element ultrasound transducers and duty cycles of incident tone burst ranging respectively from 3.5 to 7.5 MHz and 10 to 50%. Results demonstrated that the estimated m parameter tends to be sensitively affected by the use of ultrasound operational modes as well as the tissue attenuation. The healthy and pathological tissues may be characterized quantitatively by m parameter under fixed measurement conditions and proper calibration.

Keywords: ultrasound backscattering, statistical analysis, operational mode, attenuation

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Authors: Sakeena Naikwadi, K. Jagaluraiah Sannapapamma

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Vetiveria zizanioides is an aromatic grass and traditionally been used in aromatherapy and ayurvedic medicine. Vetiver root is multi-functional biopolymer and has highly aromatic, antimicrobial, UV blocking, antioxidant properties suitable for textile finishing. The vetiver root (Gulabi) powder of different concentration (2, 4, 6,8 percent) were extracted by aqueous and solvent methods subjected to bioassay for antimicrobial efficiency and GCMS spectral analysis. The organic cotton fabric was finished with vetiver root extract (8 percent) by exhaust and pad dry cure methods. The finished fabric was assessed for functional properties viz., UV protective factor, antimicrobial efficiency and aroma intensity. The results revealed that Ethanol extraction showed a greater zone of inhibition compared to aqueous extract in root powder. Among the concentrations, 8 percent root extract in ethanol showed a greater zone of inhibition against gram-positive organism S. aureus and gram-negative organism E. coli. The major compounds present in vetiver root extracts were diethyl pathalate with greater percentage (87.73 %) followed by 7- Isopropyl dimethyl carboxylic acid (4.05 %), 2-butanone 4-trimethyle cyclohexen (1.21 %), phenanthrene carboxylic acid (1.03 %), naphthalene pentanoic acid (0.99 %), 1-phenanthrene carboxylic acid and 1 cyclohexenone 2-methyl oxobuty (0.89 %). The sample finished by pad dry cure method exhibited better UV protection even after 10th wash as compared to exhaust method. Vetiver extract treated samples exhibited maximum zone of inhibition against S. aureus than the E. coli organism. The vetiver root extract treated organic cotton fabric through pad dry cure method possessed good antimicrobial activity against S. aureus and E. coli even after 20th washes compared to vetiver root extract treated by exhaust method. The olfactory analysis was carried out by 30 panels of members and opined that vetiver root extract treated fabric has very good and pleasant aroma with better tactile properties that provide cooling, soothing effect and enhances the mood of the wearer. Vetiver root extract finished organic cotton fabric possessed aroma, antimicrobial and UV properties which are aptly suitable for medical and healthcare textiles viz., wound dressing, bandage gauze, surgical cloths, baby diapers and sanitary napkins. It can be used as after finishing agent for variegated garments and made-ups and can be replaced with commercial after finishing agents.

Keywords: antimicrobial, olfactory analysis, UV protection factor, vetiver root extract

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Authors: J. Y. Heo, H. G. Sung

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Numerical simulations have been performed for assessment of compressibility correction of two-equation turbulence models suitable for large scale separation flows perturbed by pintle strokes. In order to take into account pintle movement, a sliding mesh method was applied. The chamber pressure, mass flow rate, and thrust have been analyzed, and the response lag and sensitivity at the chamber and nozzle were estimated for a movable pintle. The nozzle performance for pintle reciprocating as its insertion and extraction processes, were analyzed to better understand the dynamic performance of the pintle nozzle.

Keywords: pintle, sliding mesh, turbulent model, compressibility correction

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Authors: Yina F. Muñoz, Alexander Paz, Hanns De La Fuente-Mella, Joaquin V. Fariña, Guilherme M. Sales

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The primary approach for estimating bridge deterioration uses Markov-chain models and regression analysis. Traditional Markov models have problems in estimating the required transition probabilities when a small sample size is used. Often, reliable bridge data have not been taken over large periods, thus large data sets may not be available. This study presents an important change to the traditional approach by using the Small Data Method to estimate transition probabilities. The results illustrate that the Small Data Method and traditional approach both provide similar estimates; however, the former method provides results that are more conservative. That is, Small Data Method provided slightly lower than expected bridge condition ratings compared with the traditional approach. Considering that bridges are critical infrastructures, the Small Data Method, which uses more information and provides more conservative estimates, may be more appropriate when the available sample size is small. In addition, regression analysis was used to calculate bridge deterioration. Condition ratings were determined for bridge groups, and the best regression model was selected for each group. The results obtained were very similar to those obtained when using Markov chains; however, it is desirable to use more data for better results.

Keywords: concrete bridges, deterioration, Markov chains, probability matrix

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Authors: Munawar Malik, Muntaha Ahmad, Khalil Ullah Khan

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Linguistic abilities in students with hearing impairment yet remain a concern for educationists. The emerging technological support and provisions in recent era vows to have addressed the situation and claims significant contribution in terms of linguistic repertoire. Being a descriptive and quantitative paradigm of study, the purpose of this research set forth was to assess linguistic competencies of students with hearing impairment in English language. The goals were further broken down to identify level of reading abilities in the subject population. The population involved students with HI studying at higher secondary level in Lahore. Simple random sampling technique was used to choose a sample of fifty students. A purposive curriculum-based assessment was designed in line with accelerated learning program by Punjab Government, to assess Linguistic competence among the sample. Further to it, an Informal Reading Inventory (IRI) corresponding to reading levels was also developed by researchers duly validated and piloted before the final use. Descriptive and inferential statistics were utilized to reach to the findings. Spearman’s correlation was used to find out relationship between degree of hearing loss, grade level, gender and type of amplification device. Independent sample t-test was used to compare means among groups. Major findings of the study revealed that students with hearing impairment exhibit significant deviation from the mean scores when compared in terms of grades, severity and amplification device. The study divulged that respective students with HI have yet failed to qualify an independent level of reading according to their grades as majority falls at frustration level of word recognition and passage comprehension. The poorer performance can be attributed to lower linguistic competence as it shows in the frustration levels of reading, writing and comprehension. The correlation analysis did reflect an improved performance grade wise, however scores could only correspond to frustration level and independent levels was never achieved. Reported achievements at instructional level of subject population may further to linguistic skills if practiced purposively.

Keywords: linguistic competence, hearing impairment, reading levels, educationist

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Authors: Kiran P. Chadayamuri, Saransh Bagdi

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Increasing imbalance between energy supply and demand has made nations and companies involved in the energy sector to boost up their research and find suitable solutions. With the high rates at which conventional oil and gas resources are depleting, efficient exploration and exploitation of heavy oil could just be the answer. Heavy oil may be defined as crude oil having API gravity value of less than 20⁰. They are highly viscous, have low hydrogen to carbon ratios and are known to produce high carbon residues. They have high contents of asphaltenes, heavy metals, sulphur and nitrogen in them. Due to these properties extraction, transportation and refining of crude oil have its share of challenges. Lack of suitable technology has hindered its production in the past, but now things are going in a more positive direction. The aim of this paper is to study the various advantages of heavy oil, associated limitations and its feasibility as a fuel of the future.

Keywords: energy, heavy oil, fuel, future

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Authors: Mustafa Alhamdi

Abstract:

Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Devesh Motwani, Amey Kashyap

Abstract:

Interest in cost effective drilling has increased substantially in the past years. Economics associated with drilling fluids is needed to be considered seriously for lesser cost per foot in planning and drilling of a wellbore and the various environmental concerns imposed by international communities related with the constituents of the drilling fluid. Viscofier such as Guar Gum is a high molecular weight polysaccharide from Guar plants, is used to increase viscosity in water-based and brine-based drilling fluids thus enabling more efficient cleaning of the bore. Other applications of this Viscofier are to reduce fluid loss by giving a better colloidal solution, decrease fluid friction and so minimising power requirements and used in hydraulic fracturing to increase the recovery of oil and gas. Guar gum is also used as a surfactant, synthetic polymer and defoamer. This paper presents experimental results to verifying the properties of guar gum as a viscofier and filtrate retainer as well as observing the impact of different quantities of guar gum and Carboxymethyl cellulose (CMC) in a standard sample of water based bentonite mud solution. This is in attempt to make a drilling fluid which contains half of the quantity of drilling mud used and yet is equally viscous to the standardised mud sample. Thus we can see that mud economics will be greatly affected by this approach. However guar gum is thermally stable till 60-65°C thus limited to be used in drilling shallow wells and for a wider thermal range, suitable chrome free additives are required.

Keywords: economics, guargum, viscofier, CMC, thermal stability

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Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

Abstract:

Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

Procedia PDF Downloads 596

Authors: Zhang Shuqi, Liu Dan

Abstract:

For the problems in intelligent network anomaly traffic detection models, such as low detection accuracy caused by the lack of training samples, poor effect with small sample attack detection, a classification model enhancement method, F-ACGAN(Flow Auxiliary Classifier Generative Adversarial Network) which introduces generative adversarial network and adversarial training, is proposed to solve these problems. Generating adversarial data with category labels could enhance the training effect and improve classification accuracy and model robustness. FACGAN consists of three steps: feature preprocess, which includes data type conversion, dimensionality reduction and normalization, etc.; A generative adversarial network model with feature learning ability is designed, and the sample generation effect of the model is improved through adversarial iterations between generator and discriminator. The adversarial disturbance factor of the gradient direction of the classification model is added to improve the diversity and antagonism of generated data and to promote the model to learn from adversarial classification features. The experiment of constructing a classification model with the UNSW-NB15 dataset shows that with the enhancement of FACGAN on the basic model, the classification accuracy has improved by 8.09%, and the score of F1 has improved by 6.94%.

Keywords: data imbalance, GAN, ACGAN, anomaly detection, adversarial training, data augmentation

Procedia PDF Downloads 105

Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

Abstract:

The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

Procedia PDF Downloads 418

Authors: Songul Cinaroglu

Abstract:

Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

Procedia PDF Downloads 395

Authors: Samuel McLennan, Tane Moleta, Andre Brown, Marc Aurel Schnabel

Abstract:

The development of Ecclesiastical buildings within New Zealand has produced some unique design characteristics that take influence from both international styles and local building methods. What this research looks at is how procedural modelling can be used to define such common characteristics and understand how they are shared and developed within different examples of a similar architectural style. This will be achieved through the creation of procedural digital reconstructions of the various timber Gothic Churches built during the 19th century in the city of Wellington, New Zealand. ‘Procedural modelling’ is a digital modelling technique that has been growing in popularity, particularly within the game and film industry, as well as other fields such as industrial design and architecture. Such a design method entails the creation of a parametric ‘ruleset’ that can be easily adjusted to produce many variations of geometry, rather than a single geometry as is typically found in traditional CAD software. Key precedents within this area of digital heritage includes work by Haegler, Müller, and Gool, Nicholas Webb and Andre Brown, and most notably Mark Burry. What these precedents all share is how the forms of the reconstructed architecture have been generated using computational rules and an understanding of the architects’ geometric reasoning. This is also true within this research as Gothic architecture makes use of only a select range of forms (such as the pointed arch) that can be accurately replicated using the same standard geometric techniques originally used by the architect. The methodology of this research involves firstly establishing a sample group of similar buildings, documenting the existing samples, researching any lost samples to find evidence such as architectural plans, photos, and written descriptions, and then culminating all the findings into a single 3D procedural asset within the software ‘Houdini’. The end result will be an adjustable digital model that contains all the architectural components of the sample group, such as the various naves, buttresses, and windows. These components can then be selected and arranged to create visualisations of the sample group. Because timber gothic churches in New Zealand share many details between designs, the created collection of architectural components can also be used to approximate similar designs not included in the sample group, such as designs found beyond the Wellington Region. This creates an initial library of architectural components that can be further expanded on to encapsulate as wide of a sample size as desired. Such a methodology greatly improves upon the efficiency and adjustability of digital modelling compared to current practices found in digital heritage reconstruction. It also gives greater accuracy to speculative design, as a lack of evidence for lost structures can be approximated using components from still existing or better-documented examples. This research will also bring attention to the cultural significance these types of buildings have within the local area, addressing the public’s general unawareness of architectural history that is identified in the Wellington based research ‘Moving Images in Digital Heritage’ by Serdar Aydin et al.

Keywords: digital forensics, digital heritage, gothic architecture, Houdini, procedural modelling

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Authors: Kobus-Cisowska Joanna, Flaczyk Ewa, Gramza-Michalowska Anna, Kmiecik Dominik, Przeor Monika, Marcinkowska Agata, Korczak Józef

Abstract:

The object of this study was to develop recipes and technology of production of functional bread with morus alba fruit addition. There were prepared four samples of functional breads and the control sample also. Bread recipe was designed for supporting the treatment of anemia, diabetes, obesity and cardiovascular diseases. Samples of bread were baked with mixes directly after preparation and after three months' storage, each time preparing the water and methanol extracts. The sensory analysis and nutritional value were estimated. The antioxidant activity were estimated used tests such as the ability to scavenge free radical DPPH, the ability to scavenge the ABTS cation, chelating properties and the total content of polyphenols. The study results showed that the prepared sample of functional breads were characterized by a high nutritional value with high concentration of biologically active compounds which showed antioxidant activity. In addition, the profile sensory of bread samples was highly rated. However, to determine whether they can be considered as a new product preset pro-health properties require additional nutritional studies - clinical trials.

Keywords: functional food, breads, white mulberry, bioactive components

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Authors: Honggang Qu, Rongmei Liu, Bin Wang, Yong Xu, Zhenji Gao

Abstract:

There is a big gap in the ability and level of the informatization technology innovation of cores and samples compared with developed countries. Under the current background of promoting the technology innovation, how to strengthen the informatization technology innovation of cores and samples for National Cores and Samples Archives, which is a national innovation research center, is an important research topic. The paper summarizes the development status of cores and samples informatization technology, and finds the gaps and deficiencies, and proposes the innovation research directions and content, including data extraction, recognition, processing, integration, application and so on, so as to provide some reference and guidance for the future innovation research of the archives and support better the geological technology innovation in China.

Keywords: cores and samples;, informatization technology;, innovation;, suggestion

Procedia PDF Downloads 126

Authors: Fatima Mokeddem

Abstract:

The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs.

Keywords: phonocardiogram signal, filtering, Envelope, Detection, murmurs, heart sounds

Procedia PDF Downloads 140