Search results for: hybrid block methods
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17546

Search results for: hybrid block methods

15056 Towards a Standardization in Scheduling Models: Assessing the Variety of Homonyms

Authors: Marcel Rojahn, Edzard Weber, Norbert Gronau

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Terminology is a critical instrument for each researcher. Different terminologies for the same research object may arise in different research communities. By this inconsistency, many synergistic effects get lost. Theories and models will be more understandable and reusable if a common terminology is applied. This paper examines the terminological (in) consistency for the research field of job-shop scheduling through a literature review. There is an enormous variety in the choice of terms and mathematical notation for the same concept. The comparability, reusability, and combinability of scheduling methods are unnecessarily hampered by the arbitrary use of homonyms and synonyms. The acceptance in the community of used variables and notation forms is shown by means of a compliance quotient. This is proven by the evaluation of 240 scientific publications on planning methods.

Keywords: job-shop scheduling, terminology, notation, standardization

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15055 FT-NIR Method to Determine Moisture in Gluten Free Rice-Based Pasta during Drying

Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

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Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

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15054 Computer Aided Analysis of Breast Based Diagnostic Problems from Mammograms Using Image Processing and Deep Learning Methods

Authors: Ali Berkan Ural

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This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

Procedia PDF Downloads 96
15053 Advances in Artificial intelligence Using Speech Recognition

Authors: Khaled M. Alhawiti

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This research study aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition has become one of the widely used technologies, as it offers great opportunity to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitates its users and helps them to perform their daily routine tasks, in a more convenient and effective manner. This research intends to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches have revealed the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to overcome these issues, different statistical models were developed by the researchers. Some of the most prominent statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). The research will help in understanding all of these statistical models of speech recognition. Researchers have also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods include pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable methods, which are being used in speech recognition.

Keywords: speech recognition, acoustic phonetic, artificial intelligence, hidden markov models (HMM), statistical models of speech recognition, human machine performance

Procedia PDF Downloads 478
15052 Study of Flow-Induced Noise Control Effects on Flat Plate through Biomimetic Mucus Injection

Authors: Chen Niu, Xuesong Zhang, Dejiang Shang, Yongwei Liu

Abstract:

Fishes can secrete high molecular weight fluid on their body skin to enable their rapid movement in the water. In this work, we employ a hybrid method that combines Computational Fluid Dynamics (CFD) and Finite Element Method (FEM) to investigate the effects of different mucus viscosities and injection velocities on fluctuation pressure in the boundary layer and flow-induced structural vibration noise of a flat plate model. To accurately capture the transient flow distribution on the plate surface, we use Large Eddy Simulation (LES) while the mucus inlet is positioned at a sufficient distance from the model to ensure effective coverage. Mucus injection is modeled using the Volume of Fluid (VOF) method for multiphase flow calculations. The results demonstrate that mucus control of pulsating pressure effectively reduces flow-induced structural vibration noise, providing an approach for controlling flow-induced noise in underwater vehicles.

Keywords: mucus, flow control, noise control, flow-induced noise

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15051 Diagnosis of Avian Pathology in the East of Algeria

Authors: Khenenou Tarek, Benzaoui Hassina, Melizi Mohamed

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The diagnosis requires a background of current knowledge in the field and also complementary means in which the laboratory occupies the central place for a better investigation. A correct diagnosis allows to establish the most appropriate treatment as soon as possible and avoids both the economic losses associated with mortality and growth retardation often observed in poultry furthermore it may reduce the high cost of treatment. Epedemiologic survey, hematologic and histopathologic study’s are three aspects of diagnosis heavily used in both human and veterinary pathology and the advanced researches in human medicine would be exploited to be applied in veterinary medicine with given modification .Whereas, the diagnostic methods in the east of Algeria are limited to the clinical signs and necropsy finding. Therefore, the diagnosis is based simply on the success or the failure of the therapeutic methods (therapeutic diagnosis).

Keywords: chicken, diagnosis, hematology, histopathology

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15050 Heterothic Effect of Some Quantitative Traits in F1 Diallel Hybrids of Various Tobacco Types

Authors: Jane Aleksoski

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The mode of inheritance and heterotic effect were studied in ten F1 crosses obtained by one-way diallel crossing between five parental genotypes: MV-1, P 76/86, Adiyaman, Basma-Djebel, and P 66 9 7. The following quantitative traits were studied: the number of leaves per stalk, length of leaves from the middle belt of the stalk, and yield of green leaf mass per stalk and per hectare. The trial was set up in the experimental field of Scientific Tobacco Institute - Prilep, using a randomized block design with four replications in the period 2018-2019. Traditional cultural practices were applied during the growing season of tobacco in the field. The aim of this work was to study the mode of inheritance of the quantitative traits, to detect heterosis in the F1 generation, and to assess its economic viability. Analysis of variance determined statistically significant differences in traits between parents and their hybrids in the two-year investigation. The most common way of trait inheritance is partial-dominant, then intermediate. The negative heterotic effect on the number of leaves per stalk has P 76/86 x P 66 9 7. The hybrids MV-1 x Adiyaman, P 76/86 x Basma-Djebel, P 76/86 x P 66 9 7, and Basma-Djebel x P 66 9 7 have a positive heterotic effect on the length of the leaves. Oriental hybrids, where one of the parents is variety P 66 9 7, have positive heterosis in the yield of green leaf mass per stalk. The investigation provides very useful guidance for future successive selection activities.

Keywords: dominance, heterosis, inheritance, tobacco.

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15049 Seismic Response of Large-Scale Rectangular Steel-Plate Concrete Composite Shear Walls

Authors: Siamak Epackachi, Andrew S. Whittaker, Amit H. Varma

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An experimental program on steel-plate concrete (SC) composite shear walls was executed in the NEES laboratory at the University at Buffalo. Four large-size specimens were tested under displacement-controlled cyclic loading. The design variables considered in the testing program included wall thickness, reinforcement ratio, and faceplate slenderness ratio. The aspect ratio (height-to-length) of the four walls was 1.0. Each SC wall was installed on top of a re-usable foundation block. A bolted baseplate to RC foundation connection was used for all four walls. The walls were identified to be flexure-critical. This paper presents the damage to SC walls at different drift ratios, the cyclic force-displacement relationships, energy dissipation and equivalent viscous damping ratios, the strain and stress fields in the steel faceplates and the contribution of the steel faceplates to the total shear load, the variation of vertical strain in the steel faceplates along the length of the wall, near the base, at different drift ratios, the contributions of shear, flexure, and base rotation to the total lateral displacement, the displacement ductility of the SC walls, and the cyclic secant stiffness of the four SC walls.

Keywords: steel-plate composite shear wall, safety-related nuclear structure, flexure-critical wall, cyclic loading

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15048 Synthesizing an Artificial Loess for Geotechnical Investigations of Collapsible Soil Behavior

Authors: Hamed Sadeghi, Pouya A. Panahi, Hamed Nasiri, Mohammad Sadeghi

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Collapsible soils like loess comprise an important category of problematic soils for construction purposes and sustainable development. As a result, research on both geological and geotechnical aspects of this type of soil have been in progress for decades. However, considerable natural variability in physical properties of in-situ loess strata even in a single block sample challenges the fundamental laboratory investigations. The reason behind this is that it is somehow impossible to remove the effect of a specific factor like void ratio from fair comparisons to come with a reliable conclusion. In order to cope with this limitation, two types of artificially made dispersive and calcareous loess are introduced which can be easily reproduced in any soil mechanics laboratory provided that all its compositions are known and controlled. The collapse potential is explored for a variety of soil water salinity and lime content and comparisons are made against the natural soil behavior. Trends are reported for the influence of pore water salinity on collapse potential under different osmotic flow conditions. The most important advantage of artificial loess is the ease of controlling cementing agent content like calcite or dispersive potential for studying their influence on mechanical soil behavior.

Keywords: artificial loess, unsaturated soils, collapse potential, dispersive clays, laboratory tests

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15047 Monte Carlo Methods and Statistical Inference of Multitype Branching Processes

Authors: Ana Staneva, Vessela Stoimenova

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A parametric estimation of the MBP with Power Series offspring distribution family is considered in this paper. The MLE for the parameters is obtained in the case when the observable data are incomplete and consist only with the generation sizes of the family tree of MBP. The parameter estimation is calculated by using the Monte Carlo EM algorithm. The estimation for the posterior distribution and for the offspring distribution parameters are calculated by using the Bayesian approach and the Gibbs sampler. The article proposes various examples with bivariate branching processes together with computational results, simulation and an implementation using R.

Keywords: Bayesian, branching processes, EM algorithm, Gibbs sampler, Monte Carlo methods, statistical estimation

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15046 Influence of Cucurbitacin-Containing Phytonematicides on Growth of Rough Lemon (Citrus jambhiri)

Authors: Raisibe V. Mathabatha, Phatu W. Mashela, Nehemiah M. Mokgalong

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Occasional incidence of phytotoxicity in Nemarioc-BL and Nemafric-AL phytonematicides to crops raises credibility challenges that could negate their registration as commercial products. Responses of plants to phytonematicides are characterized by the existence of stimulation, neutral and inhibition phases, with the mid-point of the former being referred to as the Mean Concentration Stimulation Point (MSCP = Dm + Rh/2). The objective of this study was to determine the MCSP and the overall sensitivity (∑k) of Nemarioc-AL and Nemafric-BL phytonematicides to rough lemon seedling rootstocks using the Curve-fitting Allelochemical Response Dosage (CARD) computer-based model. Two parallel greenhouse experiments were initiated, with seven dilutions of each phytonematicide arranged in a randomised complete block design, replicated nine times. Six-month-old rough lemon seedlings were transplanted into 20-cm-diameter plastic pots, filled with steam-pasteurised river sand (300°C for 3 h) and Hygromix-T growing mixture. Treatments at 0, 2, 4, 8, 16, 32 and 164% dilutions were applied weekly at 300 ml/plant. At 84 days after the treatments, analysis of variance-significant plant variables was subjected to the CARD model to generate appropriate biological indices. Computed MCSP values for Nemarioc-AL and Nemafric-BL phytonematicides on rough lemon were 29 and 38%, respectively, whereas ∑k values were 1 and 0, respectively. At the applied concentrations, rough lemon seedlings were highly sensitive to Nemarioc-AL and Nemafric-BL phytonematicides.

Keywords: crude extracts, cucurbitacins, effective microbes, fruit extracts

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15045 Effect of Distance Education Students Motivation with the Turkish Language and Literature Course

Authors: Meva Apaydin, Fatih Apaydin

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Role of education in the development of society is great. Teaching and training started with the beginning of the history and different methods and techniques which have been applied as the time passed and changed everything with the aim of raising the level of learning. In addition to the traditional teaching methods, technology has been used in recent years. With the beginning of the use of internet in education, some problems which could not be soluted till that time has been dealt and it is inferred that it is possible to educate the learners by using contemporary methods as well as traditional methods. As an advantage of technological developments, distance education is a system which paves the way for the students to be educated individually wherever and whenever they like without the needs of physical school environment. Distance education has become prevalent because of the physical inadequacies in education institutions, as a result; disadvantageous circumstances such as social complexities, individual differences and especially geographical distance disappear. What’s more, the high-speed of the feedbacks between teachers and learners, improvement in student motivation because there is no limitation of time, low-cost, the objective measuring and evaluation are on foreground. In spite of the fact that there is teaching beneficences in distance education, there are also limitations. Some of the most important problems are that : Some problems which are highly possible to come across may not be solved in time, lack of eye-contact between the teacher and the learner, so trust-worthy feedback cannot be got or the problems stemming from the inadequate technological background are merely some of them. Courses are conducted via distance education in many departments of the universities in our country. In recent years, giving lectures such as Turkish Language, English, and History in the first grades of the academic departments in the universities is an application which is constantly becoming prevalent. In this study, the application of Turkish Language course via distance education system by analyzing advantages and disadvantages of the distance education system which is based on internet.

Keywords: distance education, Turkish language, motivation, benefits

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15044 Highly Selective Conversion of CO2 to CO on Cu Nanoparticles

Authors: Rauf Razzaq, Kaiwu Dong, Muhammad Sharif, Ralf Jackstell, Matthias Beller

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Carbon dioxide (CO2), a key greenhouse gas produced from both anthropogenic and natural sources, has been recently considered to be an important C1 building-block for the synthesis of many industrial fuels and chemicals. Catalytic hydrogenation of CO2 using a heterogeneous system is regarded as an efficient process for CO2 valorization. In this regard CO2 reduction to CO via the reverse water gas shift reaction (RWGSR) has attracted much attention as a viable process for large scale commercial CO2 utilization. This process can generate syn-gas (CO+H2) which can provide an alternative route to direct CO2 conversion to methanol and/or liquid HCs from FT reaction. Herein, we report a highly active and selective silica supported copper catalyst with efficient CO2 reduction to CO in a slurry-bed batch autoclave reactor. The reactions were carried out at 200°C and 60 bar initial pressure with CO2/H2 ratio of 1:3 with varying temperature, pressure and fed-gas ratio. The gaseous phase products were analyzed using FID while the liquid products were analyzed by using FID detectors. It was found that Cu/SiO2 catalyst prepared using novel ammonia precipitation-urea gelation method achieved 26% CO2 conversion with a CO and methanol selectivity of 98 and 2% respectively. The high catalytic activity could be attributed to its strong metal-support interaction with highly dispersed and stabilized Cu+ species active for RWGSR. So, it can be concluded that reduction of CO2 to CO via RWGSR could address the problem of using CO2 gas in C1 chemistry.

Keywords: CO2 reduction, methanol, slurry reactor, synthesis gas

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15043 TDApplied: An R Package for Machine Learning and Inference with Persistence Diagrams

Authors: Shael Brown, Reza Farivar

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Persistence diagrams capture valuable topological features of datasets that other methods cannot uncover. Still, their adoption in data pipelines has been limited due to the lack of publicly available tools in R (and python) for analyzing groups of them with machine learning and statistical inference. In an easy-to-use and scalable R package called TDApplied, we implement several applied analysis methods tailored to groups of persistence diagrams. The two main contributions of our package are comprehensiveness (most functions do not have implementations elsewhere) and speed (shown through benchmarking against other R packages). We demonstrate applications of the tools on simulated data to illustrate how easily practical analyses of any dataset can be enhanced with topological information.

Keywords: machine learning, persistence diagrams, R, statistical inference

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15042 Coagulase Negative Staphylococci: Phenotypic Characterization and Antimicrobial Susceptibility Pattern

Authors: Lok Bahadur Shrestha, Narayan Raj Bhattarai, Basudha Khanal

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Introduction: Coagulase-negative staphylococci (CoNS) are the normal commensal of human skin and mucous membranes. The study was carried out to study the prevalence of CoNS among clinical isolates, to characterize them up to species level and to compare the three conventional methods for detection of biofilm formation. Objectives: to characterize the clinically significant coagulase-negative staphylococci up to species level, to compare the three phenotypic methods for the detection of biofilm formation and to study the antimicrobial susceptibility pattern of the isolates. Methods: CoNS isolates were obtained from various clinical samples during the period of 1 year. Characterization up to species level was done using biochemical test and study of biofilm formation was done by tube adherence, congo red agar, and tissue culture plate method. Results: Among 71 CoNS isolates, seven species were identified. S. epidermidis was the most common species followed by S. saprophyticus, S. haemolyticus. Antimicrobial susceptibility pattern of CoNS documented resistance of 90% to ampicillin. Resistance to cefoxitin and ceftriaxone was observed in 55% of the isolates. We detected biofilm formation in 71.8% of isolates. The sensitivity of tube adherence method was 82% while that of congo red agar method was 78%. Conclusion: Among 71 CoNS isolated, S. epidermidis was the most common isolates followed by S. saprophyticus and S. haemolyticus. Biofilm formation was detected in 71.8% of the isolates. All of the methods were effective at detecting biofilm-producing CoNS strains. Biofilm former strains are more resistant to antibiotics as compared to biofilm non-formers.

Keywords: CoNS, congo red agar, bloodstream infections, foreign body-related infections, tissue culture plate

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15041 Comparing Community Detection Algorithms in Bipartite Networks

Authors: Ehsan Khademi, Mahdi Jalili

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Despite the special features of bipartite networks, they are common in many systems. Real-world bipartite networks may show community structure, similar to what one can find in one-mode networks. However, the interpretation of the community structure in bipartite networks is different as compared to one-mode networks. In this manuscript, we compare a number of available methods that are frequently used to discover community structure of bipartite networks. These networks are categorized into two broad classes. One class is the methods that, first, transfer the network into a one-mode network, and then apply community detection algorithms. The other class is the algorithms that have been developed specifically for bipartite networks. These algorithms are applied on a model network with prescribed community structure.

Keywords: community detection, bipartite networks, co-clustering, modularity, network projection, complex networks

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15040 Multichannel Surface Electromyography Trajectories for Hand Movement Recognition Using Intrasubject and Intersubject Evaluations

Authors: Christina Adly, Meena Abdelmeseeh, Tamer Basha

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This paper proposes a system for hand movement recognition using multichannel surface EMG(sEMG) signals obtained from 40 subjects using 40 different exercises, which are available on the Ninapro(Non-Invasive Adaptive Prosthetics) database. First, we applied processing methods to the raw sEMG signals to convert them to their amplitudes. Second, we used deep learning methods to solve our problem by passing the preprocessed signals to Fully connected neural networks(FCNN) and recurrent neural networks(RNN) with Long Short Term Memory(LSTM). Using intrasubject evaluation, The accuracy using the FCNN is 72%, with a processing time for training around 76 minutes, and for RNN's accuracy is 79.9%, with 8 minutes and 22 seconds processing time. Third, we applied some postprocessing methods to improve the accuracy, like majority voting(MV) and Movement Error Rate(MER). The accuracy after applying MV is 75% and 86% for FCNN and RNN, respectively. The MER value has an inverse relationship with the prediction delay while varying the window length for measuring the MV. The different part uses the RNN with the intersubject evaluation. The experimental results showed that to get a good accuracy for testing with reasonable processing time, we should use around 20 subjects.

Keywords: hand movement recognition, recurrent neural network, movement error rate, intrasubject evaluation, intersubject evaluation

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15039 Utilization of Long Acting Reversible Contraceptive Methods, and Associated Factors among Female College Students in Gondar Town, Northwest Ethiopia, 2018

Authors: Woledegebrieal Aregay

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Introduction: Family planning is defined as the ability of individuals and couples to anticipate and attain their desired number of children and the spacing and timing of their births. It is part of a strategy to reduce poverty, maternal, infant and child mortality; empowers women by lightening the burden of excessive childbearing. Family planning is achieved through the use of different contraceptive methods among which the most effective method is modern family planning methods like Long-Acting Reversible Contraceptive (LARCs) which are IUCD and Implant and these methods have multiple advantages over other reversible methods. Most importantly, once in place, they do not require maintenance and their duration of action is long, ranging from 3 to10 years. Methods: An institutional-based cross-sectional study was conducted in Gondar town among female college students from April-May. A simple random sampling technique was employed to recruit a total of 1166 study subjects. Descriptive variables were computed for all predictors & dependent variables. The presence of an association between covariates & LARC use was observed by two tables’ findings using the chi-square test. Bivariate logistic regression was conducted to identify all possible factors affecting LARC utilization & its crude Odds Ratio, 95% Confidence Interval (CI) & P-value was observed. A multivariable logistic regression model was developed to control possible confounding variables. Adjusted Odds Ratio (AOR) with 95% Confidence Interval (CI) &P-values will be computed to identify significantly associated factors (P < 0.05) with LARC utilization. Result: Utilization of LARCs was 20.4%, the most common is Implant 86(96.5%), and followed by Intra-Uterine Contraceptive Device (IUCD) 3(3.5%). The result of the multivariate analysis revealed that the significant association of marital status of the respondent on utilization of LARC [AOR 3.965(2.051-7.665)], discussion of the respondent about LARC utilization with the husband/boyfriend [AOR 2.198(1.191-4.058)], and attitude of the respondent on implant was found to be associated [AOR 0.365(0.143-0.933)].Conclusion: The level of knowledge and attitude in this study was not satisfactory, the utilization of long-acting reversible contraceptives among college students was relatively satisfactory but if the knowledge and attitude of the participant has improved the prevalence of LARC were increased.

Keywords: utilization, long-acting reversible contraceptive, Ethiopia, Gondar

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15038 Nitrogen Uptake of Different Safflower (Carthamus tinctorius L.) Genotypes at Different Growth Stages in Semi-Arid Conditions

Authors: Zehra Aytac, Nurdilek Gulmezoglu

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Safflower has been grown for centuries for many purposes worldwide. Especially it is important for the orange-red dye from its petal and for its high-quality oil obtained from the seeds. The crop is high adaptable to areas with insufficient rainfall and poor soil conditions. The plant has a deep taproot that can draw moisture and plant nutrients from deep to the subsoil. The research was carried out to study the nitrogen (N) uptake of different safflower cultivars and lines at different stages of growth and different plant parts in the experimental field of Faculty of Agriculture, Eskişehir Osmangazi University under semi-arid conditions. Different safflower cultivars and lines of varied origins were used as the material. The cultivars and lines were planted in a Randomized Complete Block Design with three replications. Two different growth stages (flowering and harvest) and three different plant parts (head, stem+leaf and seed) were determined. The nitrogen concentration of different plant parts was determined by the Kjeldahl method. Statistical analysis were performed by analysis of variance for each growth stage and plant parts taking a level of p < 0.05 and p < 0.01 as significant according to the LSD test. As a result, N concentration showed significant differences among different plant parts and different growth stages for different safflower genotypes of varied origins.

Keywords: Carthamus tinctorius L., growth stages, head N, leaf N, N uptake, seed N, Safflower

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15037 An Inviscid Compressible Flow Solver Based on Unstructured OpenFOAM Mesh Format

Authors: Utkan Caliskan

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Two types of numerical codes based on finite volume method are developed in order to solve compressible Euler equations to simulate the flow through forward facing step channel. Both algorithms have AUSM+- up (Advection Upstream Splitting Method) scheme for flux splitting and two-stage Runge-Kutta scheme for time stepping. In this study, the flux calculations differentiate between the algorithm based on OpenFOAM mesh format which is called 'face-based' algorithm and the basic algorithm which is called 'element-based' algorithm. The face-based algorithm avoids redundant flux computations and also is more flexible with hybrid grids. Moreover, some of OpenFOAM’s preprocessing utilities can be used on the mesh. Parallelization of the face based algorithm for which atomic operations are needed due to the shared memory model, is also presented. For several mesh sizes, 2.13x speed up is obtained with face-based approach over the element-based approach.

Keywords: cell centered finite volume method, compressible Euler equations, OpenFOAM mesh format, OpenMP

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15036 Ultrasonic Treatment of Baker’s Yeast Effluent

Authors: Emine Yılmaz, Serap Fındık

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Baker’s yeast industry uses molasses as a raw material. Molasses is end product of sugar industry. Wastewater from molasses processing presents large amount of coloured substances that give dark brown color and high organic load to the effluents. The main coloured compounds are known as melanoidins. Melanoidins are product of Maillard reaction between amino acid and carbonyl groups in molasses. Dark colour prevents sunlight penetration and reduces photosynthetic activity and dissolved oxygen level of surface waters. Various methods like biological processes (aerobic and anaerobic), ozonation, wet air oxidation, coagulation/flocculation are used to treatment of baker’s yeast effluent. Before effluent is discharged adequate treatment is imperative. In addition to this, increasingly stringent environmental regulations are forcing distilleries to improve existing treatment and also to find alternative methods of effluent management or combination of treatment methods. Sonochemical oxidation is one of the alternative methods. Sonochemical oxidation employs ultrasound resulting in cavitation phenomena. In this study, decolorization of baker’s yeast effluent was investigated by using ultrasound. Baker’s yeast effluent was supplied from a factory which is located in the north of Turkey. An ultrasonic homogenizator used for this study. Its operating frequency is 20 kHz. TiO2-ZnO catalyst has been used as sonocatalyst. The effects of molar proportion of TiO2-ZnO, calcination temperature and time, catalyst amount were investigated on the decolorization of baker’s yeast effluent. The results showed that prepared composite TiO2-ZnO with 4:1 molar proportion treated at 700°C for 90 min provides better result. Initial decolorization rate at 15 min is 3% without catalyst, 14,5% with catalyst treated at 700°C for 90 min respectively.

Keywords: baker’s yeast effluent, decolorization, sonocatalyst, ultrasound

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15035 Research and Innovation Centre

Authors: Krasimir Ivanov, Tonyo Tonev, Nguyen Nguyen, Alexander Peltekov, Anyo Mitkov

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Maize is among the most economically important crops and at the same time one of the most sensitive to soil deficiency in zinc. In this paper, the impact of the foliar zinc application in the form of zinc hydroxy nitrate suspension on the micro and macro elements partitioning in maize leaves and grain was studied during spring maize season, 2017. The impact of the foliar zinc fertilization on the grain yield and quality was estimated too. The experiment was performed by the randomized block design with 8 variants in 3 replications. Seven suspension solutions whit different Zn concentration were used, including ZnO suspension and zinc hydroxyl nitrate alone or nixed with other nutrients. Fertilization and irrigation were the same for all variants. The Zn content and the content of selected micro (Cu, Fe) and macro (Ca, Mg, P and K) elements in maize leaves were determined two weeks after the first spraying (5-6 sheets), two weeks after the second spraying (9-10 sheets) and after harvesting. It was concluded that the synthesized zinc hydroxy nitrate demonstrates potential as the long-term foliar fertilizer. A significant (p < 0.05) effect of zinc accumulation in maize leaves by foliar zinc application during the first growth stage was found, followed by its reutilization to other plants organs during the second growth stage. Significant export of Cu, P, and K from lower and middle leaves was observed. The content of Ca and Mg remains constant in the whole longevity period, while the content of Fe decreases sharply.

Keywords: foliar fertilization, zinc hydroxy nitrate, maize, zinc

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15034 Stock Movement Prediction Using Price Factor and Deep Learning

Authors: Hy Dang, Bo Mei

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The development of machine learning methods and techniques has opened doors for investigation in many areas such as medicines, economics, finance, etc. One active research area involving machine learning is stock market prediction. This research paper tries to consider multiple techniques and methods for stock movement prediction using historical price or price factors. The paper explores the effectiveness of some deep learning frameworks for forecasting stock. Moreover, an architecture (TimeStock) is proposed which takes the representation of time into account apart from the price information itself. Our model achieves a promising result that shows a potential approach for the stock movement prediction problem.

Keywords: classification, machine learning, time representation, stock prediction

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15033 Physicochemical Characterization of Low Sulfonated Polyether Ether Ketone/ Layered Double Hydroxide/Sepiolite Hybrid to Improve the Performance of Sulfonated Poly Ether Ether Ketone Composite Membranes for Proton Exchange Membrane Fuel Cells

Authors: Zakaria Ahmed, Khaled Charradi, Sherif M. A. S. Keshk, Radhouane Chtourou

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Sulfonated poly ether ether ketone (SPEEK) with a low sulfonation degree was blended using nanofiller Layered Double Hydroxide (LDH, Mg2AlCl) /sepiolite nanostructured material as additive to use as an electrolyte membrane for fuel cell application. Characterization assessments, i.e., mechanical stability, thermal gravimetric analysis, ion exchange capability, swelling properties, water uptake capacities, electrochemical impedance spectroscopy analysis, and Fourier transform infrared spectroscopy (FTIR) of the composite membranes were conducted. The presence of LDH/sepiolite nanoarchitecture material within SPEEK was found to have the highest water retention and proton conductivity value at high temperature rather than LDH/SPEEK and pristine SPEEK membranes.

Keywords: SPEEK, sepiolite clay, LDH clay, proton exchange membrane

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15032 CompPSA: A Component-Based Pairwise RNA Secondary Structure Alignment Algorithm

Authors: Ghada Badr, Arwa Alturki

Abstract:

The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.

Keywords: alignment, RNA secondary structure, pairwise, component-based, data mining

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15031 Frequent Itemset Mining Using Rough-Sets

Authors: Usman Qamar, Younus Javed

Abstract:

Frequent pattern mining is the process of finding a pattern (a set of items, subsequences, substructures, etc.) that occurs frequently in a data set. It was proposed in the context of frequent itemsets and association rule mining. Frequent pattern mining is used to find inherent regularities in data. What products were often purchased together? Its applications include basket data analysis, cross-marketing, catalog design, sale campaign analysis, Web log (click stream) analysis, and DNA sequence analysis. However, one of the bottlenecks of frequent itemset mining is that as the data increase the amount of time and resources required to mining the data increases at an exponential rate. In this investigation a new algorithm is proposed which can be uses as a pre-processor for frequent itemset mining. FASTER (FeAture SelecTion using Entropy and Rough sets) is a hybrid pre-processor algorithm which utilizes entropy and rough-sets to carry out record reduction and feature (attribute) selection respectively. FASTER for frequent itemset mining can produce a speed up of 3.1 times when compared to original algorithm while maintaining an accuracy of 71%.

Keywords: rough-sets, classification, feature selection, entropy, outliers, frequent itemset mining

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15030 Comparison of Transparent Nickel Doped Cobalt Sulfide and Platinum Counter Electrodes Used in Quasi-Solid State Dye Sensitized Solar Cells

Authors: Dimitra Sygkridou, Dimitrios Karageorgopoulos, Elias Stathatos, Evangelos Vitoratos

Abstract:

Transparent nickel doped cobalt sulfide was fabricated on a SnO2:F electrode and tested as an efficient electrocatalyst and as an alternative to the expensive platinum counter electrode. In order to investigate how this electrode could affect the electrical characteristics of a dye-sensitized solar cell, we manufactured cells with the same TiO2 photoanode sensitized with dye (N719) and employing the same quasi-solid electrolyte, altering only the counter electrode used. The cells were electrically and electrochemically characterized and it was observed that the ones with the Ni doped CoS2 outperformed the efficiency of the cells with the Pt counter electrode (3.76% and 3.44% respectively). Particularly, the higher efficiency of the cells with the Ni doped CoS2 counter electrode (CE) is mainly because of the enhanced photocurrent density which is attributed to the enhanced electrocatalytic ability of the CE and the low charge transfer resistance at the CE/electrolyte interface.

Keywords: nickel doped cobalt sulfide, counter electrodes, dye-sensitized solar cells, quasi-solid state electrolyte, hybrid organic-inorganic materials

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15029 Previously Undescribed Cardiac Abnormalities in Two Unrelated Autistic Males with Causative Variants in CHD8

Authors: Mariia A. Parfenenko, Ilya S. Dantsev, Sergei V. Bochenkov, Natalia V. Vinogradova, Olga S. Groznova, Victoria Yu. Voinova

Abstract:

Introduction: Autism is the most common neurodevelopmental disorder. Autism is characterized by difficulties in social interaction and adherence to stereotypic behavioral patterns and frequently co-occurs with epilepsy, intellectual disabilities, connective tissue disorders, and other conditions. CHD8 codes for chromodomain-helicase-DNA-binding protein 8 - a chromatin remodeler that regulates cellular proliferation and neurodevelopment in embryogenesis. CHD8 is one of the genes most frequently involved in autism. Patients and methods: 2 unrelated male patients, P3 and P12, aged 3 and 12 years old, underwent whole genome sequencing, which determined that they both had different likely pathogenic variants, both previously undescribed in literature. Sanger sequencing later determined that P12 inherited the variant from his affected mother. Results: P3 and P12 presented with autism, a developmental delay, ataxia, sleep disorders, overgrowth, and macrocephaly, as well as other clinical features typically present in patients with causative variants in CHD8. The mother of P12 also has autistic traits, as well as ataxia, hypotonia, sleep disorders, and other symptoms. However, P3 and P12 also have different cardiac abnormalities. P3 had signs of a repolarization disorder: a flattened T wave in the III and aVF derivations and a negative T wave in the V1-V2 derivations. He also had structural valve anomalies with associated regurgitation, local contractility impairment of the left ventricular, and diastolic dysfunction of the right ventricle. Meanwhile, P12 had Wolff-Parkinson-White syndrome and underwent radiofrequency ablation at the age of 2 years. At the time of observation, P12 had mild sinus arrhythmia and an incomplete right bundle branch block, as well as arterial hypertension. Discussion: Cardiac abnormalities were not previously reported in patients with causative variants in CHD8. The underlying mechanism for the formation of those abnormalities is currently unknown. However, the two hypotheses are either a disordered interaction with CHD7 – another chromodomain remodeler known to be directly involved in the cardiophenotype of CHARGE syndrome – a rare condition characterized by coloboma, heart defects and growth abnormalities, or the disrupted functioning of CHD8 as an A-Kinase Anchoring Protein, which are known to modulate cardiac function. Conclusion: We observed 2 unrelated autistic males with likely pathogenic variants in CHD8 that presented with typical symptoms of CHD8-related neurodevelopmental disorder, as well as cardiac abnormalities. Cardiac abnormalities have, until now, been considered uncharacteristic for patients with causative variants in CHD8. Further accumulation of data, including experimental evidence of the involvement of CHD8 in heart formation, will elucidate the mechanism underlying the cardiophenotype of those patients. Acknowledgements: Molecular genetic testing of the patients was made possible by the Charity Fund for medical and social genetic aid projects «Life Genome.»

Keywords: autism spectrum disorders, chromodomain-helicase-DNA-binding protein 8, neurodevelopmental disorder, cardio phenotype

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15028 Detection the Ice Formation Processes Using Multiple High Order Ultrasonic Guided Wave Modes

Authors: Regina Rekuviene, Vykintas Samaitis, Liudas Mažeika, Audrius Jankauskas, Virginija Jankauskaitė, Laura Gegeckienė, Abdolali Sadaghiani, Shaghayegh Saeidiharzand

Abstract:

Icing brings significant damage to aviation and renewable energy installations. Air-conditioning, refrigeration, wind turbine blades, airplane and helicopter blades often suffer from icing phenomena, which cause severe energy losses and impair aerodynamic performance. The icing process is a complex phenomenon with many different causes and types. Icing mechanisms, distributions, and patterns are still relevant to research topics. The adhesion strength between ice and surfaces differs in different icing environments. This makes the task of anti-icing very challenging. The techniques for various icing environments must satisfy different demands and requirements (e.g., efficient, lightweight, low power consumption, low maintenance and manufacturing costs, reliable operation). It is noticeable that most methods are oriented toward a particular sector and adapting them to or suggesting them for other areas is quite problematic. These methods often use various technologies and have different specifications, sometimes with no clear indication of their efficiency. There are two major groups of anti-icing methods: passive and active. Active techniques have high efficiency but, at the same time, quite high energy consumption and require intervention in the structure’s design. It’s noticeable that vast majority of these methods require specific knowledge and personnel skills. The main effect of passive methods (ice-phobic, superhydrophobic surfaces) is to delay ice formation and growth or reduce the adhesion strength between the ice and the surface. These methods are time-consuming and depend on forecasting. They can be applied on small surfaces only for specific targets, and most are non-biodegradable (except for anti-freezing proteins). There is some quite promising information on ultrasonic ice mitigation methods that employ UGW (Ultrasonic Guided Wave). These methods are have the characteristics of low energy consumption, low cost, lightweight, and easy replacement and maintenance. However, fundamental knowledge of ultrasonic de-icing methodology is still limited. The objective of this work was to identify the ice formation processes and its progress by employing ultrasonic guided wave technique. Throughout this research, the universal set-up for acoustic measurement of ice formation in a real condition (temperature range from +240 C to -230 C) was developed. Ultrasonic measurements were performed by using high frequency 5 MHz transducers in a pitch-catch configuration. The selection of wave modes suitable for detection of ice formation phenomenon on copper metal surface was performed. Interaction between the selected wave modes and ice formation processes was investigated. It was found that selected wave modes are sensitive to temperature changes. It was demonstrated that proposed ultrasonic technique could be successfully used for the detection of ice layer formation on a metal surface.

Keywords: ice formation processes, ultrasonic GW, detection of ice formation, ultrasonic testing

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15027 The Development of the Geological Structure of the Bengkulu Fore Arc Basin, Western Edge of Sundaland, Sumatra, and Its Relationship to Hydrocarbon Trapping Mechanism

Authors: Lauti Dwita Santy, Hermes Panggabean, Syahrir Andi Mangga

Abstract:

The Bengkulu Basin is part of the Sunda Arc system, which is a classic convergent type margin that occur around the southern rim of the Eurasian continental (Sundaland) plate. The basin is located between deep sea trench (Mentawai Outer Arc high) and the volvanic/ magmatic Arc of the Barisan Mountains Range. To the northwest it is bounded by Padang High, to the northest by Barisan Mountains (Sumatra Fault Zone) to the southwest by Mentawai Fault Zone and to the southeast by Semangko High/ Sunda Strait. The stratigraphic succession and tectonic development can be broadly divided into four stage/ periods, i.e Late Jurassic- Early Cretaceous, Late Eocene-Early Oligocene, Late Oligocene-Early Miocene, Middle Miocene-Late Miocene and Pliocene-Plistocene, which are mainly controlled by the development of subduction activities. The Pre Tertiary Basement consist of sedimentary and shallow water limestone, calcareous mudstone, cherts and tholeiitic volcanic rocks, with Late Jurassic to Early Cretaceous in age. The sedimentation in this basin is depend on the relief of the Pre Tertiary Basement (Woyla Terrane) and occured into two stages, i.e. transgressive stage during the Latest Oligocene-Early Middle Miocene Seblat Formation, and the regressive stage during the Latest Middle Miocene-Pleistocene (Lemau, Simpangaur and Bintunan Formations). The Pre-Tertiary Faults were more intensive than the overlying cover, The Tertiary Rocks. There are two main fault trends can be distinguished, Northwest–Southwest Faults and Northeast-Southwest Faults. The NW-SE fault (Ketaun) are commonly laterally persistent, are interpreted to the part of Sumatran Fault Systems. They commonly form the boundaries to the Pre Tertiary basement highs and therefore are one of the faults elements controlling the geometry and development of the Tertiary sedimentary basins.The Northeast-Southwest faults was formed a conjugate set to the Northwest–Southeast Faults. In the earliest Tertiary and reactivated during the Plio-Pleistocene in a compressive mode with subsequent dextral displacement. The Block Faulting accross these two sets of faults related to approximate North–South compression in Paleogene time and produced a series of elongate basins separated by basement highs in the backarc and forearc region. The Bengkulu basin is interpreted having evolved from pull apart feature in the area southwest of the main Sumatra Fault System related to NW-SE trending in dextral shear.Based on Pyrolysis Yield (PY) vs Total Organic Carbon (TOC) diagram show that Seblat and Lemau Formation belongs to oil and Gas Prone with the quality of the source rocks includes into excellent and good (Lemau Formation), Fair and Poor (Seblat Formation). The fine-grained carbonaceous sediment of the Seblat dan Lemau Formations as source rocks, the coarse grained and carbonate sediments of the Seblat and Lemau Formations as reservoir rocks, claystone bed in Seblat and Lemau Formation as caprock. The source rocks maturation are late immature to early mature, with kerogen type II and III (Seblat Formation), and late immature to post mature with kerogen type I and III (Lemau Formation). The burial history show to 2500 m in depthh with paleo temperature reached 80oC. Trapping mechanism occur during Oligo–Miocene and Middle Miocene, mainly in block faulting system.

Keywords: fore arc, bengkulu, sumatra, sundaland, hydrocarbon, trapping mechanism

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