Search results for: variable clustering

Authors: Om Prakash Bharti, Aanchal Verma, R. K. Saket

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The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods.

Keywords: doubly-fed induction generator, wind turbine, wind energy conversion system, induction generator, transfer function, proportional, integral, derivatives

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Authors: Lina Najafian, Hamidreza Vakilifard

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The present study focused on the relationship between the quality of accruals and non-systematic risk. The independent study variables included the ability of accruals, the information content of accruals, and amount of discretionary accruals considered as accruals quality measures. The dependent variable was non-systematic risk based on the Fama and French Three Factor model (FFTFM) and the capital asset pricing model (CAPM). The control variables were firm size, financial leverage, stock return, cash flow fluctuations, and book-to-market ratio. The data collection method was based on library research and document mining including financial statements. Multiple regression analysis was used to analyze the data. The study results showed that there is a significant direct relationship between financial leverage and discretionary accruals and non-systematic risk based on FFTFM and CAPM. There is also a significant direct relationship between the ability of accruals, information content of accruals, firm size, and stock return and non-systematic based on both models. It was also found that there is no relationship between book-to-market ratio and cash flow fluctuations and non-systematic risk.

Keywords: accruals quality, non-systematic risk, CAPM, FFTFM

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Authors: Perminderjit Singh, Randeep Singh

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The performance, emission and combustion characteristics of a single cylinder four stroke variable compression ratio multifuel engine when fueled with different blends of rice bran oil methyl ester and ethanol are investigated and compared with the results of standard diesel. Biodiesel produced from rice bran oil by transesterification process has been used in this study. The experiment has been conducted at a fixed engine speed of 1500 rpm, 50% load and at compression ratios of 16.5:1, 17:1, 17.5:1 and 18:1. The impact of compression ratio on fuel consumption, brake thermal efficiency and exhaust gas emissions has been investigated and presented. Optimum compression ratio which gives the best performance has been identified. The results indicate longer ignition delay, the maximum rate of pressure rise, lower heat release rate and higher mass fraction burnt at higher compression ratio for waste cooking oil methyl ester when compared to that of diesel. The brake thermal efficiency at 50% load for rice bran oil methyl ester blends and diesel has been calculated and the blend B40 is found to give maximum thermal efficiency. The blends when used as fuel results in the reduction of carbon monoxide, hydrocarbon and increase in nitrogen oxides emissions.

Keywords: biodiesel, rice bran oil, transesterification, ethanol, compression ratio

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Authors: Ahmed Bahieldin, Ahmed Atef, Jamal S. M. Sabir, Nour O. Gadalla, Sherif Edris, Ahmed M. Alzohairy, Nezar A. Radhwan, Mohammed N. Baeshen, Ahmed M. Ramadan, Hala F. Eissa, Sabah M. Hassan, Nabih A. Baeshen, Osama Abuzinadah, Magdy A. Al-Kordy, Fotouh M. El-Domyati, Robert K. Jansen

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Wild salt-tolerant barley (Hordeum spontaneum) is the ancestor of cultivated barley (Hordeum vulgare or H. vulgare). Although the cultivated barley genome is well studied, little is known about genome structure and function of its wild ancestor. In the present study, RNA-Seq analysis was performed on young leaves of wild barley treated with salt (500 mM NaCl) at four different time intervals. Transcriptome sequencing yielded 103 to 115 million reads for all replicates of each treatment, corresponding to over 10 billion nucleotides per sample. Of the total reads, between 74.8 and 80.3% could be mapped and 77.4 to 81.7% of the transcripts were found in the H. vulgare unigene database (unigene-mapped). The unmapped wild barley reads for all treatments and replicates were assembled de novo and the resulting contigs were used as a new reference genome. This resultedin94.3 to 95.3%oftheunmapped reads mapping to the new reference. The number of differentially expressed transcripts was 9277, 3861 of which were uni gene-mapped. The annotated unigene- and de novo-mapped transcripts (5100) were utilized to generate expression clusters across time of salt stress treatment. Two-dimensional hierarchical clustering classified differential expression profiles into nine expression clusters, four of which were selected for further analysis. Differentially expressed transcripts were assigned to the main functional categories. The most important groups were ‘response to external stimulus’ and ‘electron-carrier activity’. Highly expressed transcripts are involved in several biological processes, including electron transport and exchanger mechanisms, flavonoid biosynthesis, reactive oxygen species (ROS) scavenging, ethylene production, signaling network and protein refolding. The comparisons demonstrated that mRNA-Seq is an efficient method for the analysis of differentially expressed genes and biological processes under salt stress.

Keywords: electron transport, flavonoid biosynthesis, reactive oxygen species, rnaseq

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Authors: Sumanta Kumar Saha, Jie Qin

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This study analyzes the impact of financial inclusion on gender inequality in 126 countries belonging to different income groups during the 2005–2019 period. Due to its positive influence on poverty alleviation, economic growth, women empowerment, and income inequality reduction, financial inclusion may help reduce gender equality. This study constructs a novel composite financial inclusion index and applies both fixed-effect panel estimation and instrumental variable approach to examine the impact of financial inclusion on gender inequality. The results indicate that financial inclusion can reduce gender inequality in developing and low- and lower-middle-income countries, but not in higher-income countries. The impact is not always immediate. Past financial inclusion initiatives have a significant influence on future gender inequality. Financial inclusion is also significant if the poverty level is high and women's access to financial services is low compared to men. When the poverty level is low, or women have equal access to financial services, financial inclusion does not significantly affect gender inequality. The study finds that compulsory education and improvement in institutional quality promote gender equality in developing countries apart from financial inclusion. The study proposes that lower-income countries use financial inclusion initiatives to improve gender equality. Other countries need to focus on other aspects such as promoting educational support and institutional quality improvements to achieve gender equality.

Keywords: financial inclusion, gender inequality, institutional quality, women empowerment

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Authors: Anyeres N. Atehortua Jimenez, J. David Lambraño, Juan Carlos Muñoz

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Navier-Stokes equations (NSE), which describe the dynamics of a fluid, have an important application on modeling waves used for data inversion techniques as full waveform inversion (FWI). In this work a linearized version of NSE and its variables, neglecting deviatoric terms of stress tensor, is presented. In order to get a theoretical modeling of pressure p(x,t) and wave velocity profile c(x,t), a wave equation of visco-acoustic medium (VAE) is written. A change of variables p(x,t)=q(x,t)h(ρ), is made on the equation for the VAE leading to a well known Klein-Gordon equation (KGE) describing waves propagating in variable density medium (ρ) with dispersive term α^2(x). KGE is reduced to a Poisson equation and solved by proposing a specific function for α^2(x) accounting for the energy dissipation and dispersion. Finally, an integral form solution is derived for p(x,t), c(x,t) and kinematics variables like particle velocity v(x,t), displacement u(x,t) and bulk modulus function k_b(x,t). Further, it is compared this visco-acoustic formulation with another form broadly used in the geophysics; it is argued that this formalism is more general and, given its integral form, it may offer several advantages from the modern parallel computing point of view. Applications to minimize the errors in modeling for FWI applied to oils resources in geophysics are discussed.

Keywords: Navier-Stokes equations, modeling, visco-acoustic, inversion FWI

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Authors: Nima Mahmoudi, Hamzeh Khazaei

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Serving machine learning inference workloads on the cloud is still a challenging task at the production level. The optimal configuration of the inference workload to meet SLA requirements while optimizing the infrastructure costs is highly complicated due to the complex interaction between batch configuration, resource configurations, and variable arrival process. Serverless computing has emerged in recent years to automate most infrastructure management tasks. Workload batching has revealed the potential to improve the response time and cost-effectiveness of machine learning serving workloads. However, it has not yet been supported out of the box by serverless computing platforms. Our experiments have shown that for various machine learning workloads, batching can hugely improve the system’s efficiency by reducing the processing overhead per request. In this work, we present MLProxy, an adaptive reverse proxy to support efficient machine learning serving workloads on serverless computing systems. MLProxy supports adaptive batching to ensure SLA compliance while optimizing serverless costs. We performed rigorous experiments on Knative to demonstrate the effectiveness of MLProxy. We showed that MLProxy could reduce the cost of serverless deployment by up to 92% while reducing SLA violations by up to 99% that can be generalized across state-of-the-art model serving frameworks.

Keywords: serverless computing, machine learning, inference serving, Knative, google cloud run, optimization

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Authors: Adnan F. Sheikh, Fayaz A. Mir

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After the recent devastating flood in Kashmir in 2014, dredging of the local water bodies, especially Jhelum River has become a priority for the government. Local government under the project name of 'Comprehensive Flood Management Programme' plans to undertake an increase in discharge of existing flood channels by removal of encroachments and acquisition of additional land, dredging and other works of the water bodies. The total quantity of soil to be dredged will be 16.15 lac cumecs. Dredged soil is a major component that would result from the project which requires disposal/utilization. This study analyses the effect of cement and sand on the engineering properties of soil. The tests were conducted with variable additions of sand (10%, 20% and 30%), whereas cement was added at 12%. Samples with following compositions: soil-cement (12%) and soil-sand (30%) were tested as well. Laboratory experiments were conducted to determine the engineering characteristics of soil, i.e., compaction, strength, and CBR characteristics. The strength characteristics of the soil were determined by unconfined compressive strength test and direct shear test. Unconfined compressive strength of the soil was tested immediately and for a curing period of seven days. CBR test was performed for unsoaked, soaked (worst condition- 4 days) and cured (4 days) samples.

Keywords: comprehensive flood management programme, dredge soil, strength characteristics, flood

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Authors: Mustafa Abu Ghalia, Yaser Dahman

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A new class of polyurethane (PU) reinforced with green bacterial cellulose nanofibers (BC) were prepared using a solvent casting method, with the goal of fabricating green nanocomposites. Four series classes of BC (1, 2.5, 5, and 10 wt%) were reinforced into PU matrices via BC surface modification and subsequently BC-grafted into PU throughout silane coupling agent to improve BC dispersion and its interfacial interaction. The experiment results from the tensile tester were evaluated according to the response surface method (RSM) for optimizing the impacts of variable parameters, pore size, porosity, and BC contents on the mechanical properties. The compressive strength for PU-5 BC wt% was about 9.8 MPa, and decrease when being generated prosperity to recorded at 4.9 MPa. Nielson model was applied to investigate the BC stress concentration on the PU matrices. Likewise, krenche and Hapli-Tasi model were employed to evaluate the BC nanofiber reinforcement potential and BC orientation into PU matrices. The analysis of variance (ANOVA) demonstrated that only BC loading has a significant effect in increases tensile strength, young’s modulus, and a flexural modulus of the PU-BC nanocomposites. The optimal factors of the variables experiment confirmed to be 5 wt% for BC, 230 for pore size, and 80 % for porosity. Scanning electron microscopy (SEM) micrographs showed that the uniform distribution of nanofibers in the PU matrices with the addition of BC 5 wt %. Hydrolytic degradation revealed that the weight loss in PU-BC scaffold is higher than PU-BC wt %.

Keywords: polyurethane scaffold, mechanical properties, tissue engineering, polyurethane

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Authors: Hasan Yalcin, Tugba Dursun Capar

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Deep-fat frying causes desirable as well as undesirable changes in oil and potato, and changes the quality of the oil by hydrolysis, oxidation, and polymerization. The main objective of the present study was to investigate the pre-drying effects on the quality of both frying oil and potatoes. Prior to frying, potato slices (10 mm x10 mm x 30 mm) were air- dried at 60°C for 15, 30, 45, 60, 90, and 120 mins., respectively. Potato slices without the pre-drying treatment were considered as the control variable. Potato slices were fried in sunflower oil at 180°C for 5, 10, and 13 mins. The deep-frying experiments were repeated five times using the new potato slices in the same oil without oil replenishment. Samples of the fresh oil, together with those sampled at the end of successive frying operations (1th, 3th and 5th) were removed and analysed. Moisture content, colour and oil intake of the potato and colour, peroxide value (PV), free fatty acid (FFA), fatty acid composition and viscosity of the used oil were evaluated. The effect of frying time was also examined. Results show that pre-drying treatment had a significant effect on physicochemical properties and colour parameters of potato slices and frying oil. Pre-drying considerably decreased the oil absorption. The lowest oil absorption was found for the treatment that was pre-dried for 120, and fried for 5 min. The FFA levels decreased permanently for each pre-treatment throughout the frying period. All the pre-drying treatments had reached their maximum levels of FFA by the end of the frying procedures. The PV of the control and 60 min pre-dried sample decreased after the third frying. However, the PV of other samples increased constantly throughout the frying periods. Lastly, pre-drying did not affect the fatty acid composition of frying oil considerably when compared against previously unused oil.

Keywords: air-drying, deep-fat frying, moisture content oil uptake, quality

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Authors: Tamer Mesallam, Medhat Yousef, Ayna Almasaad

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BACKGROUND: Cochlear implantation (CI) in children with additional disabilities can be a fundamental and supportive intervention. Although, there may be some positive impacts of CI on children with multiple disabilities such as better outcomes of communication skills, development, and quality of life, the families of those children complain from the post-implant habilitation efforts that considered as a burden. OBJECTIVE: To investigate the outcomes of CI children with different co-disabilities through using the Meaningful Auditory Integration Scale (MAIS) and the Meaningful Use of Speech Scale (MUSS) as outcome measurement tools. METHODS: The study sample comprised 25 hearing-impaired children with co-disability who received cochlear implantation. Age and gender-matched control group of 25 cochlear-implanted children without any other disability has been also included. The participants' auditory skills and speech outcomes were assessed using MAIS and MUSS tests. RESULTS: There was a statistically significant difference in the different outcomes measure between the two groups. However, the outcomes of some multiple disabilities subgroups were comparable to the control group. Around 40% of the participants with co-disabilities experienced advancement in their methods of communication from behavior to oral mode. CONCLUSION: Cochlear-implanted children with multiple disabilities showed variable degrees of auditory and speech outcomes. The degree of benefits depends on the type of the co-disability. Long-term follow-up is recommended for those children.

Keywords: children with disabilities, Cochlear implants, hearing impairment, language development

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Authors: Krasimir Ivanov, Elitsa Kolentsova, Dimitar Dimitrov, Petya Petrova, Tatyana Tabakova

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This work studies the effect of chemical composition on the activity and selectivity of γ–alumina supported CuO/ MnO2/Cr2O3 catalysts toward deep oxidation of CO, dimethyl ether (DME) and methanol. The catalysts were prepared by impregnation of the support with an aqueous solution of copper nitrate, manganese nitrate and CrO3 under different conditions. Thermal, XRD and TPR analysis were performed. The catalytic measurements of single compounds oxidation were carried out on continuous flow equipment with a four-channel isothermal stainless steel reactor. Flow-line equipment with an adiabatic reactor for simultaneous oxidation of all compounds under the conditions that mimic closely the industrial ones was used. The reactant and product gases were analyzed by means of on-line gas chromatographs. On the basis of XRD analysis it can be concluded that the active component of the mixed Cu-Mn-Cr/γ–alumina catalysts consists of at least six compounds – CuO, Cr2O3, MnO2, Cu1.5Mn1.5O4, Cu1.5Cr1.5O4 and CuCr2O4, depending on the Cu/Mn/Cr molar ratio. Chemical composition strongly influences catalytic properties, this influence being quite variable with regards to the different processes. The rate of CO oxidation rapidly decrease with increasing of chromium content in the active component while for the DME was observed the reverse trend. It was concluded that the best compromise are the catalysts with Cu/(Mn + Cr) molar ratio 1:5 and Mn/Cr molar ratio from 1:3 to 1:4.

Keywords: Cu-Mn-Cr oxide catalysts, volatile organic compounds, deep oxidation, dimethyl ether (DME)

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Authors: Parisa Mansour

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The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

Procedia PDF Downloads 39

Authors: Elżbieta Antczak

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Cities offer important opportunities for economic development and for expanding access to basic services, including health care and education, for large numbers of people. Moreover, green areas (as an integral part of sustainable urban development) present a major opportunity for improving urban environments, quality of lives and livelihoods. This paper examines, using spatial concentration and spatial taxonomic measures, regional diversification of greenery in the cities of Poland. The analysis includes location quotients, Lorenz curve, Locational Gini Index, and the synthetic index of greenery and spatial statistics tools: (1) To verify the occurrence of strong concentration or dispersion of the phenomenon in time and space depending on the variable category, and, (2) To study if the level of greenery depends on the spatial autocorrelation. The data includes the greatest Polish cities, categories of the urban greenery (parks, lawns, street greenery, and green areas on housing estates, cemeteries, and forests) and the time span 2004-2015. According to the obtained estimations, most of cites in Poland are already taking measures to become greener. However, in the country there are still many barriers to well-balanced urban greenery development (e.g. uncontrolled urban sprawl, poor management as well as lack of spatial urban planning systems).

Keywords: greenery, urban areas, regional spatial diversification and concentration, spatial taxonomic measure

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Authors: Tayyaba Ghani, Mazhar Mehmood, Mohammad Mujahid

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TiO₂ nanotubes are receiving immense attraction in the field of dye-sensitized solar cells due to their well-defined nanostructures, efficient electron transport and large surface area as compared to other one dimensional structures. In the present work, we have investigated the influence of temperature on the morphology of anodically produced self-organized Titanium oxide nanotubes (TiNTs). TiNTs are synthesized by two-step anodization method in an ethylene glycol based electrolytes containing ammonium fluoride. Experiments are performed at constant anodization voltage for two hours. An investigation by the SEM images reveals that if the temperature is kept constant during the anodizing experiment, variation in the average tube diameter is significantly reduced. However, if the temperature is not controlled then due to the exothermic nature of reactions for the formation of TiNTs, the temperature of electrolyte keep on increasing. This variation in electrolyte bath temperature introduced strong variations in tube diameter (20 nm to 160 nm) along the length of tubes. Current profiles, recorded during the anodization experiment, predict the effect of constant and varying experimental temperatures as well. In both cases, XRD results show the complete anatase crystal structure of nanotube upon annealing at 450 °C. Present work highlights the importance of constant temperature during the anodization experiments in order to develop an ordered array of nanotubes with a uniform tube diameter.

Keywords: anodization, ordering, temperature, TiO₂ nanotubes

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Authors: Susan Lewis

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The assessment of learning outcomes at the program level has attracted much international interest from the perspectives of quality assurance and ongoing curricular redesign and renewal. This paper examines program-level learning outcomes in the field of music and technology, an area of study that has seen an explosion in program development over the past fifteen years. The Audio Engineering Society (AES) maintains an online directory of educational institutions worldwide, yielding the most comprehensive inventory of programs and courses in music and technology. The inventory includes courses, programs, and degrees in music and technology, music and computer science, music production, and the music industry. This paper focuses on published student learning outcomes for undergraduate degrees in music and technology and analyses commonalities at institutions in North America, the United Kingdom, and Europe. The results of a survey of student learning outcomes at twenty institutions indicates a focus on three distinct student learning outcomes: (1) cross-disciplinary knowledge in the fields of music and technology; (2) the practical application of training through the professional industry; and (3) the acquisition of skills in communication and collaboration. The paper then analyses assessment mechanisms for tracking student learning and achievement of learning outcomes at these institutions. The results indicate highly variable assessment practices. Conclusions offer recommendations for enhancing assessment techniques and better communicating learning outcomes to students.

Keywords: quality assurance, student learning; learning outcomes, music and technology

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Authors: Stephen Vera, Tabitha Black, Charalambos Cleanthous, Ryan Sain

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A gender comparison of USA commercial pilots’ demographics and views of CRM, social desirability and locus of control were surveyed. The Aviation safety locus of control (ASLOC) was used to measure external (ASLOC-E) or internal (ASLOC-I) aviation safety locus of control. The gender differences were explored using the ASLOC scores as a categorical variable. A differential comparison of crew resource management (CRM), based on the Federal Aviation Administration’s (FAA) guidelines was conducted. The results indicated that the proportion of female to male respondents matches the current ratio of USA commercial pilots. Moreover, there were no significant differences regarding overall education and the total number of communication classes one took. Regarding CRM issues, there were no significant differences on their views regarding the roles of the PIC, stress, time management, and managing a flight team. The females scored significantly lower on aeronautical decision making (ADM) and communications. There were no significant differences on either the Balanced Inventory of Desirable Responding (BIDR) impression management (IM) or self-deceptive enhancement (SDE). Although there were no overall significant differences on the ASLOC, the females did score higher on the internal subscale than did the males. An additional comparison of socially desirable responding indicates that all scores may be invalid, especially from the female respondents.

Keywords: social desirability, safety locus of control, crew resource management, commercial pilots

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Authors: Vanessa Kummer, Maik Meusel

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Real estate demand estimates are typically derived from transaction data. However, in regions with excess demand, transactions are driven by supply and therefore do not indicate what people are actually looking for. To estimate the demand for housing in Switzerland, search subscriptions from all important Swiss real estate platforms are used. These data do, however, suffer from missing information—for example, many users do not specify how many rooms they would like or what price they would be willing to pay. In economic analyses, it is often the case that only complete data is used. Usually, however, the proportion of complete data is rather small which leads to most information being neglected. Also, the data might have a strong distortion if it is complete. In addition, the reason that data is missing might itself also contain information, which is however ignored with that approach. An interesting issue is, therefore, if for economic analyses such as the one at hand, there is an added value by using the whole data set with the imputed missing values compared to using the usually small percentage of complete data (baseline). Also, it is interesting to see how different algorithms affect that result. The imputation of the missing data is done using unsupervised learning. Out of the numerous unsupervised learning approaches, the most common ones, such as clustering, principal component analysis, or neural networks techniques are applied. By training the model iteratively on the imputed data and, thereby, including the information of all data into the model, the distortion of the first training set—the complete data—vanishes. In a next step, the performances of the algorithms are measured. This is done by randomly creating missing values in subsets of the data, estimating those values with the relevant algorithms and several parameter combinations, and comparing the estimates to the actual data. After having found the optimal parameter set for each algorithm, the missing values are being imputed. Using the resulting data sets, the next step is to estimate the willingness to pay for real estate. This is done by fitting price distributions for real estate properties with certain characteristics, such as the region or the number of rooms. Based on these distributions, survival functions are computed to obtain the functional relationship between characteristics and selling probabilities. Comparing the survival functions shows that estimates which are based on imputed data sets do not differ significantly from each other; however, the demand estimate that is derived from the baseline data does. This indicates that the baseline data set does not include all available information and is therefore not representative for the entire sample. Also, demand estimates derived from the whole data set are much more accurate than the baseline estimation. Thus, in order to obtain optimal results, it is important to make use of all available data, even though it involves additional procedures such as data imputation.

Keywords: demand estimate, missing-data imputation, real estate, unsupervised learning

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Authors: Mojebullah Wahidy, Murat Olgun

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In this study, four different types of cement are used to investigate the permeability of DMC (Deep Mixing Column) in the clay. The clay used in this research is in the kaolin group, and the types of cement are; CEM I 42.5.R. normal portland cement, CEM II/A-M (P-L) pozzolan doped cement, CEM III/A 42.5 N blast furnace slag cement and DMFC-800 fine-grained portland cement. Firstly, some rheological tests are done on every cement, and a 0.9 water/cement ratio is selected as the appropriate ratio. This ratio is used to prepare the small-scale DMCs for all types of cement with %6, %9, %12, and %15, which are determined as the dry weight of the clay. For all the types of cement, three samples were prepared in every percentage and were kept on curing for 7, 14, and 28 days for permeability tests. As a result of the small-scale DMCs, permeability tests, a %12 selected for big-scale DMCs. A total of five big scales DMC were prepared by using a %12-cement and were kept for 28 days curing for permeability tests. The results of the permeability tests show that by increasing the cement percentage and curing time of all DMCs, the permeability coefficient (k) is decreased. Despite variable results in different cement ratios and curing time in general, samples treated by DMFC-800 fine-grained cement have the lowest permeability coefficient. Samples treated with CEM II and CEM I cement types were the second and third lowest permeable samples. The highest permeability coefficient belongs to the samples that were treated with CEM III cement type.

Keywords: deep mixing column, rheological test, DMFC-800, permeability test

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Authors: Hemad Zareiforoush, Saeed Minaei, Ahmad Banakar, Mohammad Reza Alizadeh

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The quality inspection of rice (Oryza sativa L.) during its various processing stages is very important. In this research, an artificial intelligence-based model coupled with computer vision techniques was developed as a decision support system for qualitative grading of rice grains. For conducting the experiments, first, 25 samples of rice grains with different levels of percentage of broken kernels (PBK) and degree of milling (DOM) were prepared and their qualitative grade was assessed by experienced experts. Then, the quality parameters of the same samples examined by experts were determined using a machine vision system. A grading model was developed based on fuzzy logic theory in MATLAB software for making a relationship between the qualitative characteristics of the product and its quality. Totally, 25 rules were used for qualitative grading based on AND operator and Mamdani inference system. The fuzzy inference system was consisted of two input linguistic variables namely, DOM and PBK, which were obtained by the machine vision system, and one output variable (quality of the product). The model output was finally defuzzified using Center of Maximum (COM) method. In order to evaluate the developed model, the output of the fuzzy system was compared with experts’ assessments. It was revealed that the developed model can estimate the qualitative grade of the product with an accuracy of 95.74%.

Keywords: machine vision, fuzzy logic, rice, quality

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Authors: Bidyadhar Dehury, Sanjay Kumar Mohanty

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According to the Right to Education Act of India, education is the fundamental right of all children of age group 6-14 year irrespective of their status. Using the unit level data from India Human Development Survey (IHDS), we tried to understand the inter-relationship between the level of poverty and the academic performance of the children aged 8-11 years. The level of multidimensional poverty is measured using five dimensions and 10 indicators using Alkire-Foster approach. The weighted deprivation score was obtained by giving equal weight to each dimension and indicators within the dimension. The weighted deprivation score varies from 0 to 1 and grouped into four categories as non-poor, vulnerable, multidimensional poor and sever multidimensional poor. The academic performance index was measured using three variables reading skills, math skills and writing skills using PCA. The bivariate and multivariate analysis was used in the analysis. The outcome variable was ordinal. So the predicted probabilities were calculated using the ordinal logistic regression. The predicted probabilities of good academic performance index was 0.202 if the child was sever multidimensional poor, 0.235 if the child was multidimensional poor, 0.264 if the child was vulnerable, and 0.316 if the child was non-poor. Hence, if the level of poverty among the children decreases from sever multidimensional poor to non-poor, the probability of good academic performance increases.

Keywords: multidimensional poverty, academic performance index, reading skills, math skills, writing skills, India

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Authors: Monika Szymańska-Czerwińsk, Kinga Zaręba-Marchewka, Krzysztof Niemczuk

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Chlamydiaceae are Gram-negative bacteria distributed worldwide in animals and humans. One of them is Chlamydia gallinacea recently discovered. Available data show that C. gallinacea is dominant chlamydial agent found in poultry in European and Asian countries. The aim of the studies was screening of poultry flocks in order to evaluate frequency of C. gallinacea shedding and genetic diversity. Sampling was conducted in different regions of Poland in 2019-2020. Overall, 1466 cloacal/oral swabs were collected in duplicate from 146 apparently healthy poultry flocks including chickens, turkeys, ducks, geese and quails. Dry swabs were used for DNA extraction. DNA extracts were screened using a Chlamydiaceae 23S rRNA real-time PCR assay. To identify Chlamydia species, specific real-time PCR assays were performed. Furthermore, selected samples were used for sequencing based on ompA gene fragments and variable domains (VD1-2, VD3-4). In total, 10.3% of the tested flocks were Chlamydiaceae-positive (15/146 farms). The presence of Chlamydiaceae was confirmed mainly in chickens (13/92 farms) but also in turkey (1/19 farms) and goose (1/26 farms) flocks. Eleven flocks were identified as C. gallinacea-positive while four flocks remained unclassified. Phylogenetic analysis revealed at least 16 genetic variants of C. gallinacea. Research showed that Chlamydiaceae occur in a poultry flock in Poland. The strains of C. gallinacea as dominant species show genetic variability.

Keywords: C. gallinacea, emerging agent, poultry, real-time PCR

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Authors: Mahnoosh Aliahmadi, Akbar Esmaeili

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This study synthesized new modified imaging nanocapsules (NCs) of gallium@deferoxamine/folic acid/chitosan/polyaniline/polyvinyl alcohol (Ga@DFA/FA/CS/PANI/PVA) containing Morus nigra extract by selenium nanoparticles prepared from Lactobacillus acidophilus. Se nanoparticles were then deposited on (Ga@DFA/FA/CS/PANI/PVA) using the impregnation method. The modified contrast agents were mixed with M. nigra extract, and their antibacterial activities were investigated by applying them to L929 cell lines. The influence of variable factors including surfactant, solvent, aqueous phase, pH, buffer, minimum Inhibitory concentration (MIC), minimum bactericidal concentration (MBC), cytotoxicity on cancer cells, antibiotic, antibiogram, release and loading, stirring effect, the concentration of nanoparticle, olive oil, and thermotical methods was investigated. The structure and morphology of the synthesized contrast agents were characterized by zeta potential sizer analysis (ZPS), X-Ray diffraction (XRD), Fourier-transform infrared (FT-IR), and energy-dispersive X-ray (EDX), ultraviolet-visible (UV-Vis) spectra, and scanning electron microscope (SEM). The experimental section was conducted and monitored by response surface methods (RSM) and MTT conversion assay. Antibiogram testing of NCs on Pseudomonas aeruginosa bacteria was successful, and the MIC=2 factor was obtained with a less harmful effect.

Keywords: imaging contrast agent, nanoparticles, response surface method, Lactobacillus acidophilus, selenium

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Authors: Ibtisam Mahmoud Mohammed Sultan

Abstract:

The present research aimed to identify the level of both emotional and emotional competence among students in Tikrit University aimed to know the assumptions in statistical significance for both variables as gender variables (m-f) and specialty (scientific-humanistic), as research to learn what Relationship between emotional safety and efficiency alanfaalet Tikrit University students. The researcher built emotional security measure (54) as built measure emotional competence (46), as the researcher extract full alsaykomtrih characteristics of both scales. The research sample consisted of (600) students selected by the random way and applying the scales on a basic search sample and processed statistical data using a variety of methods, including statistical test (test T.) and Pearson correlation coefficient, the researcher found a set of results. The following: 1. that the Tikrit University students possess a high level of emotional security. 2. to safely enjoy passionate males more than females. 3. that there is no difference between students of scientific and humanitarian specialization in variable emotional security. 4. that the Tikrit University students enjoy a high level of emotional competence. 5. the female-male outperforming in emotional competence level. 6. the humanitarian specialization students Excel in emotional competence for those of specialty. 7. the existence of a positive correlation between variables. Through search results, the researcher has developed a set of conclusions, proposals, and recommendations.

Keywords: relation, emotional security, students, efficiency

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Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

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Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

Procedia PDF Downloads 53

Authors: Kina Kim

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Background: There are two types of interferon-gamma release assays (IGRAs) in use for the detection of latent tuberculosis infection (LTBI), QuantiFERON-TB Gold In-tube (QFT-GIT) and T-SPOT.TB. There are some reports that IGRA results are affected by the patient's age. This study aims to compare the results of both IGRA tests according to age groups. Methods: We reviewed 54,882 samples referred to an independent reference laboratory (Seegene Medical Foundation, Seoul, Korea) for the diagnosis of LTBI from January 1, 2021, to December 31, 2021. This retrospective study enrolled 955 patients tested using QFT-GIT and 53,927 patients tested using T-SPOT.TB. The results of both IGRAs were divided in three age groups (0-9, 10-17, and ≥18-year old). The positive rates and the indeterminate rates between QFT-GIT and T-SPOT.TB were compared. We also evaluated the differences in positive and indeterminate rates by age-group. Results: The positive rate of QFT-GIT was 20.1% (192/955) and that of T-SPOT.TB was 8.7% (4704/53927) in overall patients. The positive rates of QFT-GIT in individuals aged 0-9, 10-17, and over 18-year old were 15.4%, 13.3%, and 22.0%, respectively. The positive rates of T-SPOT.TB were 8.9%, 2.0% and 8.8%,in each agegroup, respectively.The overall prevalence of indeterminate results was 2.1% (20/955) of QFT-GIT and 0.5% (270/53927) of T-SPOT.TB. The indeterminate rates of QFT-GIT in individuals aged 0-9, 10-17, and over 18 years were 0.4%, 6.7%, and 2.6%, respectively. The indeterminate rate of T-SPOT.TB were 0.5%, 0.7% and 0.5%,in each age group, respectively. Conclusion: Our findings suggest that T-SPOT.TB has a lower rate of positive results in overall patients and a lower rate of indeterminate results than those of QFT-GIT. The highest positive rate was found in the over 18 years group for QFT-GIT, but the positive rates of T-SPOT.TB was not significantly different among groups by age. QFT-GIT showed variable and higher indeterminate rates according to age group, but T-SPOT.TB showed lower rates in all age groups(<1%).

Keywords: LTBI, IGRA, QFT-GIT, T-SPOT. TB

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Authors: Heba Ahmed Abdelaziz, Doaa Tawfik Mohamed Ibrahim

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Background: COVID-19 pandemic is the major health problem facing the world recently, causing variable effects on mental health and eating behavior. Aim of the study: Identifying changes in eating patterns and other health behaviors in relation to the anxiety caused by the COVID-19 pandemic lockdown in adult females in Alexandria, Egypt. Method: 344 adult females (20+ years old), were included in online self-administered questionnaire. Results: Severe anxiety symptoms was among 34.6% of the studied females especially; those aged 25-40 years, married, non-working or student females, females who had change in their work routine (half or full time from home). Homemade pastries and bakery product then beverages followed by fresh fruits and vegetables were frequently consumed by the studied females than before lockdown while fast foods were decreased during lockdown. Overweight and obesity were high among most of the participants with different grades of anxiety symptoms. Females with moderate and severe anxiety symptoms reported increase in appetite and body weight with irregular sleeping during lockdown. Conclusion: the current study concluded that stressful situations like lockdown due to COVID-19 pandemic is associated with anxiety (severe, moderate, mild then minimal, respectively) along with changes in eating habits, physical activity, sleeping pattern and smoking.

Keywords: COVID-19, lockdown, females, anxiety, eating, stress, lifestyle

Procedia PDF Downloads 171

Authors: Dai-Ling Li, Jung-Fa Cheng, Min-Lang Huang, Yun-Yao Chi

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The hedonic pricing model has been popularly applied to describe the economic value of environmental amenities in urban housing, but the results for cultural heritage variables remain relatively ambiguous. In this paper, integrated variables extending by GIS-based data and an existing typology of communities used to examine how cultural heritage and environmental amenities and disamenities affect housing prices across urban communities in Tainan, Taiwan. The developed models suggest that, although a sophisticated variable for central services is selected, the centrality of location is not fully controlled in the price models and thus picked up by correlated peripheral and central amenities such as cultural heritage, open space or parks. Analysis of these correlations permits us to qualify results and present a revised set of relatively reliable estimates. Positive effects on housing prices are identified for views, various types of recreational infrastructure and vicinity of nationally cultural sites and significant landscapes. Negative effects are found for several disamenities including wasteyards, refuse incinerators, petrol stations and industries. The results suggest that systematic hypothesis testing and reporting of correlations may contribute to consistent explanatory patterns in hedonic pricing estimates for cultural heritage and landscape amenities in urban.

Keywords: hedonic pricing model, cultural heritage, landscape amenities, housing

Procedia PDF Downloads 325

Authors: Nelson Bii, Christopher Ouma, John Odhiambo

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Non-response is a potential source of errors in sample surveys. It introduces bias and large variance in the estimation of finite population parameters. Regression models have been recognized as one of the techniques of reducing bias and variance due to random non-response using auxiliary data. In this study, it is assumed that random non-response occurs in the survey variable in the second stage of cluster sampling, assuming full auxiliary information is available throughout. Auxiliary information is used at the estimation stage via a regression model to address the problem of random non-response. In particular, the auxiliary information is used via an improved Nadaraya-Watson kernel regression technique to compensate for random non-response. The asymptotic bias and mean squared error of the estimator proposed are derived. Besides, a simulation study conducted indicates that the proposed estimator has smaller values of the bias and smaller mean squared error values compared to existing estimators of finite population mean. The proposed estimator is also shown to have tighter confidence interval lengths at a 95% coverage rate. The results obtained in this study are useful, for instance, in choosing efficient estimators of the finite population mean in demographic sample surveys.

Keywords: mean squared error, random non-response, two-stage cluster sampling, confidence interval lengths

Procedia PDF Downloads 121

Authors: Y. T. Gee, I. N. Umar

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Students’ achievement and motivation in learning English in Malaysia is a worrying trend as it is lagging behind several other countries in Asia. Thus, necessary actions have to be taken by the parties concerned to overcome this problem. The purpose of this research was to study the effects of drill and practice courseware on students’ achievement and motivation in learning English language. A multimedia courseware was developed for this purpose. The independent variable was the drill and practice courseware while the dependent variables were the students’ achievement and motivation. Their achievement was measured using pre-test and post-test scores, while motivation was measured using a questionnaire adapted from Keller’s (1979) Instructional Materials Motivation Scale. A total of 60 students from three vernacular primary schools in a northern state in Malaysia were randomly selected in this study. The findings indicate: (1) a significant difference between the students’ pre-test and post-test scores after using the courseware, (2) no significant difference in the achievement score between male and female students after using the courseware, (3) a significant difference in motivation score between the female and the male students, and (4) while the female students scored significantly higher than the male students in the aspects of relevance, confidence and satisfaction, no significant difference in terms of attention was observed between them. Overall, the findings clearly indicate that although the female students are significantly more motivated than their male students, they are equally good in terms of achievement after learning from the courseware. Through this study, the drill and practice courseware is proven to influence the students’ learning and motivation.

Keywords: courseware, drill and practice, English learning, motivation

Procedia PDF Downloads 291