Search results for: petroleum play fairway analysis

Authors: Reza Siyami, Bahram Mirshekari

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Seed and oil yield of rapeseed is considerably affected by weeds interference including mustard (Sinapis arvensis L.), lambsquarters (Chenopodium album L.) and redroot pigweed (Amaranthus retroflexus L.) throughout the East Azerbaijan province in Iran. To formulate the relationship between four independent growth variables measured in our experiment with a dependent variable, multiple regression analysis was carried out for the weed leaves number per plant (X1), green cover percentage (X2), LAI (X3) and leaf area per plant (X4) as independent variables and rapeseed oil yield as a dependent variable. The multiple regression equation is shown as follows: Seed essential oil yield (kg/ha) = 0.156 + 0.0325 (X1) + 0.0489 (X2) + 0.0415 (X3) + 0.133 (X4). Furthermore, the stepwise regression analysis was also carried out for the data obtained to test the significance of the independent variables affecting the oil yield as a dependent variable. The resulted stepwise regression equation is shown as follows: Oil yield = 4.42 + 0.0841 (X2) + 0.0801 (X3); R2 = 81.5. The stepwise regression analysis verified that the green cover percentage and LAI of weed had a marked increasing effect on the oil yield of rapeseed.

Keywords: green cover percentage, independent variable, interference, regression

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Authors: Anung Style Bukhori, Ani Dijah Rahajoe

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Poverty poses a significant challenge in Indonesia, requiring an effective analytical approach to understand and address this issue. In this research, we applied the Naïve Bayes classification method to examine and classify poverty data in Indonesia. The main focus is on classifying data using RapidMiner, a powerful data analysis platform. The analysis process involves data splitting to train and test the classification model. First, we collected and prepared a poverty dataset that includes various factors such as education, employment, and health..The experimental results indicate that the Naïve Bayes classification model can provide accurate predictions regarding the risk of poverty. The use of RapidMiner in the analysis process offers flexibility and efficiency in evaluating the model's performance. The classification produces several values to serve as the standard for classifying poverty data in Indonesia using Naive Bayes. The accuracy result obtained is 40.26%, with a moderate recall result of 35.94%, a high recall result of 63.16%, and a low recall result of 38.03%. The precision for the moderate class is 58.97%, for the high class is 17.39%, and for the low class is 58.70%. These results can be seen from the graph below.

Keywords: poverty, classification, naïve bayes, Indonesia

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Authors: Ksenija Taški-Ajdukovic, Nevena Nagl, Živko Ćurčić, Dario Danojević

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Information about genetic diversity of sugar beet parental populations is of a great importance for hybrid breeding programs. The aim of this research was to evaluate genetic diversity among and within populations and lines of diploid sugar beet pollinators, by using SSR markers. As plant material were used eight pollinators originating from three USDA-ARS breeding programs and four pollinators from Institute of Field and Vegetable Crops, Novi Sad. Depending on the presence of self-fertility gene, the pollinators were divided into three groups: autofertile (inbred lines), autosterile (open-pollinating populations), and group with partial presence of autofertility gene. A total of 40 SSR primers were screened, out of which 34 were selected for the analysis of genetic diversity. A total of 129 different alleles were obtained with mean value 3.2 alleles per SSR primer. According to the results of genetic variability assessment the number and percentage of polymorphic loci was the maximal in pollinators NS1 and tester cms2 while effective number of alleles, expected heterozygosis and Shannon’s index was highest in pollinator EL0204. Analysis of molecular variance (AMOVA) showed that 77.34% of the total genetic variation was attributed to intra-varietal variance. Correspondence analysis results were very similar to grouping by neighbor-joining algorithm. Number of groups was smaller by one, because correspondence analysis merged IFVCNS pollinators with CZ25 into one group. Pollinators FC220, FC221 and C 51 were in the next group, while self-fertile pollinators CR10 and C930-35 from USDA-Salinas were separated. On another branch were self-sterile pollinators ЕL0204 and ЕL53 from USDA-East Lansing. Sterile testers cms1 and cms2 formed separate group. The presented results confirmed that SSR analysis can be successfully used in estimation of genetic diversity within and among sugar beet populations. Since the tested pollinator differed considering the presence of self-fertility gene, their heterozygosity differed as well. It was lower in genotypes with fixed self-fertility genes. Since the most of tested populations were open-pollinated, which rarely self-pollinate, high variability within the populations was expected. Cluster analysis grouped populations according to their origin.

Keywords: auto fertility, genetic diversity, pollinator, SSR, sugar beet

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Authors: M. Hadji, N. Chiker, Y. Hadji, A. Haddad

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In this paper, we report for the first time on the synthesis and characterization of novel MAX phases (Ti3SiC2, Ti2AlC) reinforced Ni-matrix and Ti2AlC reinforced Al-matrix. The stability of MAX phases in Al-matrix and Ni-matrix at a temperature of 985°C has been investigated. All the composites were cold pressed and sintered at a temperature of 985°C for 20min in H2 environment, except (Ni/Ti3SiC2) who was sintered at 1100°C for 1h.Microstructure analysis by scanning electron microscopy and phase analysis by X-Ray diffraction confirmed that there was minimal interfacial reaction between MAX particles and Ni, thus Al/MAX samples shown that MAX phases was totally decomposed at 985°C.The Addition of MAX enhanced the Al-matrix and Ni-matrix.

Keywords: MAX phase, microstructures, composites, hardness, SEM

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Authors: Hailekiros Tadesse Tekle, Yemane Tsehaye, Fetien Abay

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Barley (Hordeum vulgare L.) is one of the most important cereal crops in the world, grown for the poor farmers in Tigray with low yield production. The purpose of this research was to estimate the performance of 166 barley genotypes against the quantitative traits with detailed analysis of the variance component, heritability, genetic advance, and genetic usefulness parameters. The finding of ANOVA was highly significant variation (p ≤ 0:01) for all the genotypes. We found significant differences in coefficient of variance (CV of 15%) for 5 traits out of the 12 quantitative traits. The topmost broad sense heritability (H2) was recorded for seeds per spike (98.8%), followed by thousand seed weight (96.5%) with 79.16% and 56.25%, respectively, of GAM. The traits with H2 ≥ 60% and GA/GAM ≥ 20% suggested the least influenced by the environment, governed by the additive genes and direct selection for improvement of such beneficial traits for the studied genotypes. Hence, the 20 outstanding recombinant inbred lines (RIL) barley genotypes performing early maturity, high yield, and 1000 seed weight traits simultaneously were the top ranked group barley genotypes out of the 166 genotypes. These are; G5, G25, G33, G118, G36, G123, G28, G34, G14, G10, G3, G13, G11, G32, G8, G39, G23, G30, G37, and G26. They were early in maturity, high TSW and GYP (TSW ≥ 55 g, GYP ≥ 15.22 g/plant, and DTM below 106 days). In general, the 166 genotypes were classified as high (group 1), medium (group 2), and low yield production (group 3) genotypes in terms of yield and yield component trait analysis by clustering; and genotype parameter analysis such as the heritability, genetic advance, and genetic usefulness traits in this investigation.

Keywords: barley, clustering, genetic advance, heritability, usefulness, variability, yield

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Authors: Sara Rute Monteiro Silva Sousa

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Since the second half of the 20th century, environmental problems began to generate deep concern around the world. The harmful effects of human's irresponsible actions are increasingly evident, profoundly affecting biodiversity and even human health. Given the seriousness of this human footprint, governments, organizations, and civil society must all be more proactive and adopt more effective measures to solve environmental problems and promote sustainable development. This can be achieved through different tools, namely through a more efficient education that enables current and future generations to meet their needs in an integrated approach to the economic, social, and environmental dimensions of sustainable development. In this context, schools play a key role, being responsible for educating today's students and tomorrow's leaders, decision makers, intellectuals, managers, politicians, employers, and parents. Aware of this crucial role of education and schools, the Foundation for Environmental Education created the Eco-Schools program in 1992, ensuring that schools develop a whole-school approach to environmental and sus-tainable education. This research aims to increase knowledge and information about the efficiency of the Eco-Schools program as a promoter of more sustainable schools and communities. This research study analyses a specific case of a Portuguese higher education institution in the area of management, accounting, and administration. A description, reflection, and discussion are made on some of the main measures implemented in the last academic year of 2021/22 within the scope of the Eco-Schools program, concluding that, despite some implementation difficulties, the program was successfully developed, involving the participation of students, teachers, staff, and outside school community members, being awarded with the Green Flag as a recognition of its key contribution to a more sustainable society.

Keywords: sustainable development, environmental education, eco-schools program, higher education institutions, portugal

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Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

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This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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Authors: Seyong Jeong, Jinmo Park, Jinhyoun Park, Boram Kim, Kyoungsoo Ahn

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Energy management in the maritime industry is being required by economics and in conformity with new legislative actions taken by the International Maritime Organization (IMO) and the European Union (EU). In response, the various performance monitoring methodologies and data collection practices have been examined by different stakeholders. While many assorted advancements in operation and technology are applicable, their adoption in the shipping industry stays small. This slow uptake can be considered due to many different barriers such as data analysis problems, misreported data, and feedback problems, etc. This study presents a conceptual design of an energy management system (EMS) and proposes the methodology to resolve the limitations (e.g., data normalization using naval architectural evaluation, management of misrepresented data, and feedback from shore to ship through management of performance analysis history). We expect this system to make even short-term charterers assess the ship performance properly and implement sustainable fleet control.

Keywords: data normalization, energy management system, naval architectural evaluation, ship performance analysis

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Authors: Thedy Yogasara, Fredy Agus

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In designing a product, it is currently crucial to focus not only on the product’s usability based on performance measures, but also on user experience (UX) that includes pragmatic and hedonic aspects of product use. These aspects play a significant role in fulfillment of user needs, both functionally and psychologically. Pragmatic quality refers to as product’s perceived ability to support the fulfillment of behavioral goals. It is closely linked to functionality and usability of the product. In contrast, hedonic quality is product’s perceived ability to support the fulfillment of psychological needs. Hedonic quality relates to the pleasure of ownership and use of the product, including stimulation for personal development and communication of user’s identity to others through the product. This study evaluates the pragmatic and hedonic aspects of gaming mice G600 and Razer Krait using AttrakDiff tool to create an improved design that is able to generate positive UX. AttrakDiff is a method that measures pragmatic and hedonic scores of a product with a scale between -3 to +3 through four attributes (i.e. Pragmatic Quality, Hedonic Quality-Identification, Hedonic Quality-Stimulation, and Attractiveness), represented by 28 pairs of opposite words. Based on data gathered from 15 participants, it is identified that gaming mouse G600 needs to be redesigned because of its low grades (pragmatic score: -0.838, hedonic score: 1, attractiveness score: 0.771). The redesign process focuses on the attributes with poor scores and takes into account improvement suggestions collected from interview with the participants. The redesigned mouse G600 is evaluated using the previous method. The result shows higher scores in pragmatic quality (1.929), hedonic quality (1.703), and attractiveness (1.667), indicating that the redesigned mouse is more capable of creating pleasurable experience of product use.

Keywords: AttrakDiff, hedonic aspect, pragmatic aspect, product design, user experience

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Authors: Luke Galvani

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The cultural representations of people with disabilities are frequently biased which can lead to a general misunderstanding of disability. Representations of disabled deviance are especially problematic given that they typify or generally abstract disability as being abnormal, which then begin to take root in the cultural mind. This study utilizes critical discourse analysis to investigate how discourses of disabled sexual deviance are promoted within two major films that portray disabled sexual subjects. The findings indicate that perceptions of disabled sexual deviance are heightened by cinematic representations of sex and disability, which characterize disabled sexual expression as being undesirable due to the ephemeral and abnormal qualities ascribed to it.

Keywords: deviance, disability, discourse analysis, sexuality

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Authors: H. Hruschka

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This paper presents the first comparison of the performance of the restricted Boltzmann machine and the deep belief net on binary market basket data relative to binary factor analysis and the two best-known topic models, namely Dirichlet allocation and the correlated topic model. This comparison shows that the restricted Boltzmann machine and the deep belief net are superior to both binary factor analysis and topic models. Managerial implications that differ between the investigated models are treated as well. The restricted Boltzmann machine is defined as joint Boltzmann distribution of hidden variables and observed variables (purchases). It comprises one layer of observed variables and one layer of hidden variables. Note that variables of the same layer are not connected. The comparison also includes deep belief nets with three layers. The first layer is a restricted Boltzmann machine based on category purchases. Hidden variables of the first layer are used as input variables by the second-layer restricted Boltzmann machine which then generates second-layer hidden variables. Finally, in the third layer hidden variables are related to purchases. A public data set is analyzed which contains one month of real-world point-of-sale transactions in a typical local grocery outlet. It consists of 9,835 market baskets referring to 169 product categories. This data set is randomly split into two halves. One half is used for estimation, the other serves as holdout data. Each model is evaluated by the log likelihood for the holdout data. Performance of the topic models is disappointing as the holdout log likelihood of the correlated topic model – which is better than Dirichlet allocation - is lower by more than 25,000 compared to the best binary factor analysis model. On the other hand, binary factor analysis on its own is clearly surpassed by both the restricted Boltzmann machine and the deep belief net whose holdout log likelihoods are higher by more than 23,000. Overall, the deep belief net performs best. We also interpret hidden variables discovered by binary factor analysis, the restricted Boltzmann machine and the deep belief net. Hidden variables characterized by the product categories to which they are related differ strongly between these three models. To derive managerial implications we assess the effect of promoting each category on total basket size, i.e., the number of purchased product categories, due to each category's interdependence with all the other categories. The investigated models lead to very different implications as they disagree about which categories are associated with higher basket size increases due to a promotion. Of course, recommendations based on better performing models should be preferred. The impressive performance advantages of the restricted Boltzmann machine and the deep belief net suggest continuing research by appropriate extensions. To include predictors, especially marketing variables such as price, seems to be an obvious next step. It might also be feasible to take a more detailed perspective by considering purchases of brands instead of purchases of product categories.

Keywords: binary factor analysis, deep belief net, market basket analysis, restricted Boltzmann machine, topic models

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Authors: Reza Zakerinejad

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Gully erosion is a serious problem that threading the sustainability of agricultural area and rangeland and water in a large part of Iran. This type of water erosion is the main source of sedimentation in many catchment areas in the north of Iran. Since in many national assessment approaches just qualitative models were applied the aim of this study is to predict the spatial distribution of gully erosion processes by means of detail terrain analysis and GIS -based logistic regression in the loess deposition in a case study in the Golestan Province. This study the DEM with 25 meter result ion from ASTER data has been used. The Landsat ETM data have been used to mapping of land use. The TreeNet model as a stochastic modeling was applied to prediction the susceptible area for gully erosion. In this model ROC we have set 20 % of data as learning and 20 % as learning data. Therefore, applying the GIS and satellite image analysis techniques has been used to derive the input information for these stochastic models. The result of this study showed a high accurate map of potential for gully erosion.

Keywords: TreeNet model, terrain analysis, Golestan Province, Iran

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Authors: A.Cifarelli, L. Boggioni, F. Bertini, L. Magon, M. Pitalieri, S. Losio

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Nowadays, the growing environmental awareness and the dwindling of fossil resources stimulate the polyurethane (PU) industry towards renewable polymers with low carbon footprint to replace the feed stocks from petroleum sources. The main challenge in this field consists in replacing high-performance products from fossil-fuel with novel synthetic polymers derived from 'green monomers'. The bio-polyols from plant oils have attracted significant industrial interest and major attention in scientific research due to their availability and biodegradability. Triglycerides rich in unsaturated fatty acids, such as soybean oil (SBO) and linseed oil (ELO), are particularly interesting because their structures and functionalities are tunable by chemical modification in order to obtain polymeric materials with expected final properties. Unfortunately, their use is still limited for processing or performance problems because a high functionality, as well as OH number of the polyols will result in an increase in cross-linking densities of the resulting PUs. The main aim of this study is to evaluate soy and linseed-based polyols as precursors to prepare prepolymers for the production of polyurethane foams (PUFs) or waterborne-polyurethanes (WPU) used as coatings. An effective reaction route is employed for its simplicity and economic impact. Indeed, bio-polyols were synthesized by a two-step method: epoxidation of the double bonds in vegetable oils and solvent-free ring-opening reaction of the oxirane with organic acids. No organic solvents have been used. Acids with different moieties (aliphatic or aromatics) and different length of hydrocarbon backbones can be used to customize polyols with different functionalities. The ring-opening reaction requires a fine tuning of the experimental conditions (time, temperature, molar ratio of carboxylic acid and epoxy group) to control the acidity value of end-product as well as the amount of residual starting materials. Besides, a Lewis base catalyst is used to favor the ring opening reaction of internal epoxy groups of the epoxidized oil and minimize the formation of cross-linked structures in order to achieve less viscous and more processable polyols with narrower polydispersity indices (molecular weight lower than 2000 g/mol⁻¹). The functionality of optimized polyols is tuned from 2 to 4 per molecule. The obtained polyols are characterized by means of GPC, NMR (¹H, ¹³C) and FT-IR spectroscopy to evaluate molecular masses, molecular mass distributions, microstructures and linkage pathways. Several polyurethane foams have been prepared by prepolymer method blending conventional synthetic polyols with new bio-polyols from soybean and linseed oils without using organic solvents. The compatibility of such bio-polyols with commercial polyols and diisocyanates is demonstrated. The influence of the bio-polyols on the foam morphology (cellular structure, interconnectivity), density, mechanical and thermal properties has been studied. Moreover, bio-based WPUs have been synthesized by well-established processing technology. In this synthesis, a portion of commercial polyols is substituted by the new bio-polyols and the properties of the coatings on leather substrates have been evaluated to determine coating hardness, abrasion resistance, impact resistance, gloss, chemical resistance, flammability, durability, and adhesive strength.

Keywords: bio-polyols, polyurethane foams, solvent free synthesis, waterborne-polyurethanes

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Authors: H. G. C. P. Dinesh, G. Tharshini, M. P. B. Ekanayake, G. M. R. I. Godaliyadda

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This paper presents a new spatial feature extraction method based on principle component analysis (PCA) and Fisher Discernment Analysis (FDA) for facial expression recognition. It not only extracts reliable features for classification, but also reduces the feature space dimensions of pattern samples. In this method, first each gray scale image is considered in its entirety as the measurement matrix. Then, principle components (PCs) of row vectors of this matrix and variance of these row vectors along PCs are estimated. Therefore, this method would ensure the preservation of spatial information of the facial image. Afterwards, by incorporating the spectral information of the eigen-filters derived from the PCs, a feature vector was constructed, for a given image. Finally, FDA was used to define a set of basis in a reduced dimension subspace such that the optimal clustering is achieved. The method of FDA defines an inter-class scatter matrix and intra-class scatter matrix to enhance the compactness of each cluster while maximizing the distance between cluster marginal points. In order to matching the test image with the training set, a cosine similarity based Bayesian classification was used. The proposed method was tested on the Cohn-Kanade database and JAFFE database. It was observed that the proposed method which incorporates spatial information to construct an optimal feature space outperforms the standard PCA and FDA based methods.

Keywords: facial expression recognition, principle component analysis (PCA), fisher discernment analysis (FDA), eigen-filter, cosine similarity, bayesian classifier, f-measure

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Authors: Afy Syahidan Achmad

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Tangkuban Perahu is located in West Java, Indonesia. It is active stratovolcano type and still showing hidrothermal activity. The main purpose of this study is to find correlation between subsurface structure and hidrothermal activity on the surface. Using topographic map, SRTM images, and field observation, geological condition and alteration area was mapped. Alteration sample analyzed trough petrographic analysis and X-Ray Diffraction (XRD) analysis. Altered rock in study area showing white-yellowish white colour, and texture changing variation from softening to hardening because of alteration by sillica and sulphur. Alteration mineral which can be observed in petrographic analysis and XRD analysis consist of crystobalite, anatase, alunite, and pyrite. This mineral assemblage showing advanced argillic alteration type with West-East alteration area orientation. Alteration area have correlation with manifestation occurance such as steam vents, solfatara, and warm to hot pools. Most of manifestation occured in main crater like Ratu Crater and Upas crater, and parasitic crater like Domas Crater and Jarian Crater. This manifestation indicates permeability in subsurface which can be created trough structural process with same orientation. For further study geophysics method such as Magneto Telluric (MT) and resistivity can be required to find permeability zone pattern in Tangkuban Perahu subsurface.

Keywords: alteration, advanced argillic, Tangkuban Perahu, XRD, crystobalite, anatase, alunite, pyrite

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Authors: Shravani Itkelwar, Deepak Tewari, Bhaskar Natarajan

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The energy consumption data plays a vital role in energy efficiency policy design, implementation, and impact assessment. Any demand-side energy management intervention's success relies on the availability of accurate, comprehensive, granular, and up-to-date data on energy consumption. The Building sector, including residential and commercial, is one of the largest consumers of energy in India after the Industrial sector. With economic growth and increasing urbanization, the building sector is projected to grow at an unprecedented rate, resulting in a 5.6 times escalation in energy consumption till 2047 compared to 2017. Therefore, energy efficiency interventions will play a vital role in decoupling the floor area growth and associated energy demand, thereby increasing the need for robust data. In India, multiple institutions are involved in the collection and dissemination of data. This paper focuses on energy consumption data management in the building sector in India for both residential and commercial segments. It evaluates the robustness of data available through administrative and survey routes to estimate the key performance indicators and identify critical data gaps for making informed decisions. The paper explores several issues in the data, such as lack of comprehensiveness, non-availability of disaggregated data, the discrepancy in different data sources, inconsistent building categorization, and others. The identified data gaps are justified with appropriate examples. Moreover, the paper prioritizes required data in order of relevance to policymaking and groups it into "available," "easy to get," and "hard to get" categories. The paper concludes with recommendations to address the data gaps by leveraging digital initiatives, strengthening institutional capacity, institutionalizing exclusive building energy surveys, and standardization of building categorization, among others, to strengthen the management of building sector energy consumption data.

Keywords: energy data, energy policy, energy efficiency, buildings

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Stephanie Ho

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This project utilizes principles derived from the Surrealist movement to prioritize creative and critical thinking in secondary English Language Arts (ELA). The implementation of Surrealist-style pedagogies within an ELA classroom will be rooted in critical, radical pedagogy, which addresses the injustices caused by economic-oriented educational systems. The use of critical pedagogy will enable the subversive artistic and political aims of Surrealism to be transmitted to a classroom context. Through aesthetic reading strategies, appreciative questioning and dialogue, students will actively critique the power dynamics which structure (and often restrict) their lives. Within the ELA domain, cost-effective approaches often replace the actual “arts” of ELA. This research will therefore explore how Surrealist-oriented pedagogies could restore imaginative freedom and deconstruct conceptual barriers (normative standards, curricular constraints, and status quo power relations) in secondary ELA. This research will also examine how Surrealism can be used as a political and pedagogical model to treat societal problems mirrored in ELA classrooms. The stakeholders are teachers, as they experience constant pressure within their practices. Similarly, students encounter rigorous, results-based pressures. These dynamics contribute to feelings of powerlessness, thus reinforcing a formulaic model of ELA. The ELA curriculum has potential to create laboratories for critical discussion and active movement towards social change. This proposed research strategy of Surrealist-oriented pedagogies could enable students to experiment with social issues and develop senses of agency and voice that reflect awareness of contemporary society while simultaneously building their ELA skills.

Keywords: arts-informed pedagogies, language arts, literature, surrealism

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Authors: Emine Tuğba Akyüz

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In this study, the analysis of Hadamard matrices, which is a special type of matrix, was made under three headings: norms, singular values, condition number. Six norm types was applied to Hadamard matrices and the relationship between the results and the size of the matrix has been studied. As a result of the investigation when 2-norm was used on the problem Hx =f, the equation ‖x‖_2= ‖f‖_2/√n was shown (H is n-dimensional Hadamard matrix). Related with this, the relationship between the the singular value of H and 2-norm and eigenvalues was shown. Then, the evaluation of condition number for Hx =f was made.

Keywords: condition number, Hadamard matrix, norm, singular value

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Authors: Shally Pais

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Film music holds a special relationship with the narrative systems and dramaturgical operations in animation. Though the roles of cartoon music closely resemble those fulfilled by traditional film scores, which have been extensively studied, there is a large knowledge gap regarding non-mainstream or non-Hollywood animation music. This paper is an investigation of the understudied compositional materials and narrative contexts in three distinct films by exploring the main narrative and dramaturgical effects of music in The Skeleton Dance, Fox and The Whale, and La Vieille Dame et les Pigeons. The study uses a Neoformalist approach towards qualitative analysis of the music in these films to document ways in which music can be made to function differently depending on the individual films’ contexts and the desired effects to be had on the audience. Consequently, the paper highlights these factors’ influence on the films’ narratives and aims to widen the discourse on composition for animation film scores, suggesting the further study of non-mainstream film music.

Keywords: animation film music, film score analysis, Fox and The Whale, La Vieille Dame et les Pigeons, Neoformalist analysis, The Skeleton Dance

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Authors: Xi Yu, Lili Gu, Huizhu Wang, Xiao Wei, Dandan Sheng, Xiaoyan Jiang, Min Hong

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Introduction: Hypersensitivity disease is difficult to cure completely because of its recurrence, yupingfengsan (YPFS) is used to treat the diseases with the advantage of reducing the recurrence,but the precise mechanism is not clear. Previous studies of our laboratory have shown that the extract of YPFS can inhibit Th2-type allergic contact dermatitis(ACD) induced by FITC.Besides, thymic stromal lymphopoietin(TSLP) have been proved to be a master switch for allergic inflammation. Based on these studies, we want to establish a mouse model of TSLP production based on Th2 cell-mediated allergic inflammation to explore the regulating mechanisms of YPFS on TSLP in Th2 cell-mediated allergic inflammation. Methods: Th2-type ACD mouse model: The mice were topically sensitized on the abdomens (induction phase) and elicited on its ears skin 6 day later (excitation phase) with FITC solution, and the ear swelling was measured to evaluate the allergic inflammation；A mouse model of TSLP production based on Th2 cell-mediated allergic inflammation (TSLP production model): the skin of the ear was sensitized on two consecutive days with FITC solution causing the production of TSLP；Mice were treated with YPFS extract，ELISA、Real-time PCR and Western-blotting were using to examine the mRNA and protein levels of TSLP\TSLPR and TLRs ect. Results: YPFS extract can attenuates Th2-type allergic inflammatory in mice；in TSLP production model, YPFS can inhibit the expression of TSLP、 TSLPR、TLRs and MyD88, So we deduce the possible mechanisms of YPFS to play a role of intervention is through TLRs- MyD88 dependent and independent pathway to reduce TSLP production.

Keywords: YPFS, TSLP, TLRs, Th2-type allergic contact dermatitis

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Authors: Nassima Behidj-Benyounes, Thoraya Dahmene, Khaled Benyounes Nadjiba Chebouti1and F/Zohra Bissaad

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Essential oils have a significant antimicrobial activity. These oils can successfully replace the antibiotics. So, the microorganisms show their inefficiencies resistant for the antibiotics. For this reason, we study the physicochemical analysis and antimicrobial activity of the essential oil of Daucus carota. The extraction is done by steam distillation of water which brought us a very significant return of 4.65%. The analysis of the essential oil is performed by GC/MS and has allowed us to identify 32 compounds in the oil of D. carota flowering tops of Bouira. Three of which are in the majority are the α-pinene (22.3%), the carotol (21.7%) and the limonene (15.8%).

Keywords: Daucus carota, essential oil, α-pinene, carotol, limonene

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Authors: Roohallah Fallah-Moshkani, Mohammad Ali Mohsenpour, Reza Ghiasvand, Hossein Khosravi-Boroujeni, Seyed Mehdi Ahmadi, Paula Brauer, Amin Salehi-Abargouei

Abstract:

Purpose: Several investigations have proposed the protective association between dietary approaches to stop hypertension (DASH) style diet and risk of cancers; however, they have led to inconsistent results. The present study aimed to systematically review the prospective cohort studies conducted in this regard and, if possible, to quantify the overall effect of using meta-analysis. Methods: PubMed, EMBASE, Scopus, and Google Scholar were searched for cohort studies published up to December 2017. Relative risks (RRs) which were reported for fully adjusted models and their confidence intervals were extracted for meta-analysis. Random effects model was incorporated to combine the RRs. Results: Sixteen studies were eligible to be included in the systematic review from which 8 reports were conducted on the effect of DASH on the risk of mortality from all cancer types, four on the risk of colorectal cancer, and three on the risk of colon and rectal cancer. Four studies examined the association with other cancers (breast, hepatic, endometrial, and lung cancer). Meta-analysis showed that high concordance with DASH significantly decreases the risk of all cancer types (RR=0.83, 95% confidence interval (95%CI):0.80-0.85); furthermore participants who highly adhered to the DASH had lower risk of developing colorectal (RR=0.79, 95%CI: 0.75-0.83), colon (RR=0.81, 95%CI: 0.74-0.87) and rectal (RR=0.79, 95%CI: 0.63-0.98) cancer compared to those with the lowest adherence. Conclusions: DASH-style diet should be suggested as a healthy approach to protect from cancer in the community. Prospective studies exploring the effect on other cancer types and from regions other than the United States are highly recommended.

Keywords: cancer, DASH-style diet, dietary patterns, meta-analysis, systematic review

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Authors: Mohammad Beyki, Justus Pawlak, Robert Patzke, Franz Renz

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In the context of planetary exploration, the MIMOS II (miniaturized Mössbauer spectrometer) serves as a proven and reliable measuring instrument. The transmission behaviour of the electronics in the Mössbauer spectroscopy is newly developed and optimized. For this purpose, the overall electronics is split into three parts. This elaboration deals exclusively with the first part of the signal chain for the evaluation of photons in experiments with gamma radiation. Parallel to the analysis of the electronics, a new method for the stability consideration of linear and non-linear systems is presented: The extended method of Lyapunov’s stability criteria. The design helps to weigh advantages and disadvantages against other simulated circuits in order to optimize the MIMOS II for the terestric and extraterestric measurment. Finally, after stability analysis, the controller design according to Ackermann is performed, achieving the best possible optimization of the output variable through a skillful pole assignment.

Keywords: Mössbauer spectroscopy, electronic signal amplifier, light processing technology, photocurrent, trans-impedance amplifier, extended Lyapunov method

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Authors: Ogunrinde Roseline Bosede

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This paper presents the development, analysis and implementation of an inverse polynomial numerical method which is well suitable for solving initial value problems in first order ordinary differential equations with applications to sample problems. We also present some basic concepts and fundamental theories which are vital to the analysis of the scheme. We analyzed the consistency, convergence, and stability properties of the scheme. Numerical experiments were carried out and the results compared with the theoretical or exact solution and the algorithm was later coded using MATLAB programming language.

Keywords: differential equations, numerical, polynomial, initial value problem, differential equation

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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The present study deals with the selection of the most suitable quantitative structure-retention relationship (QSRR) models which should be used in prediction of the retention behavior of basic, neutral, acidic and phenolic pesticides which belong to different classes: fungicides, herbicides, metabolites, insecticides and plant growth regulators. Sum of ranking differences (SRD) approach can give a different point of view on selection of the most consistent QSRR model. SRD approach can be applied not only for ranking of the QSRR models, but also for detection of similarity or dissimilarity among them. Applying the SRD analysis, the most similar models can be found easily. In this study, selection of the best model was carried out on the basis of the reference ranking (“golden standard”) which was defined as the row average values of logarithm of retention time (logtr) defined by high performance liquid chromatography (HPLC). Also, SRD analysis based on experimental logtr values as reference ranking revealed similar grouping of the established QSRR models already obtained by hierarchical cluster analysis (HCA).

Keywords: chemometrics, chromatography, pesticides, sum of ranking differences

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Authors: Maryam Torabi, Habibi, Abdolahi, Mohammadi, Hassanzadeh, Darban Maghami, Baghi

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Sheeppox Virus (SPPV) and goatpox virus (GTPV) are considerable diseases of sheep, and goats, caused by viruses of the Capripoxvirus (CaPV) genus. They are responsible for economic losses. Animal mortality, morbidity, cost of vaccinations, and restrictions in animal products’ trade are the reasons of economic losses. Control and eradication of CaPV depend on early detection of outbreaks so that molecular detection and genetic analysis could be effective to this aim. This study was undertaken to molecularly characterize SPPV and GTPV strains that have been circulating in Iran. 120 skin papules and nodule biopsies were collected from different regions of Iran and were examined for SPPV, GTPV viruses using TaqMan Real -Time PCR. Some of these amplified genes were sequenced, and phylogenetic trees were constructed. Out of the 120 samples analysed, 98 were positive for CaPV by Real- Time PCR (81.6%), and most of them wereSPPV. then 10 positive samples were sequenced and characterized by amplifying the ORF 103CaPV gene. sequencing and phylogenetic analysis for these positive samples revealed a high percentage of identity with SPPV isolated from different countries in Middle East. In conclusions, molecular characterization revealed nearly complete identity with all recent SPPVs strains in local countries that requires further studies to monitor the virus evolution and transmission pathways to better understand the virus pathobiology that will help for SPPV control.

Keywords: molecular epidemiology, Real-Time PCR, phylogenetic analysis, capripoxviruses

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Authors: Iannick Gagnon, Alain April

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The performance of a metaheuristic on a given problem class depends on the class itself and the choice of parameters. Parameter tuning is the most time-consuming phase of the optimization process after the main calculations and it often nullifies the speed advantage of metaheuristics over traditional optimization algorithms. Several off-the-shelf parameter tuning algorithms are available, but when the objective function is expensive to evaluate, these can be prohibitively expensive to use. This paper presents a surrogate-like method for finding adequate parameters using fitness landscape analysis on simple benchmark functions and real-world objective functions. The result is a simple compound similarity metric based on the empirical correlation coefficient and a measure of convexity. It is then used to find the best benchmark functions to serve as surrogates. The near-optimal parameter set is then found using fractional factorial design. The real-world problem of NACA airfoil lift coefficient maximization is used as a preliminary proof of concept. The overall aim of this research is to reduce the computational overhead of metaheuristics parameterization.

Keywords: metaheuristics, stochastic optimization, particle swarm optimization, exploratory landscape analysis

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Authors: Rupak Kumar Sarma, Ratul Saikia

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Macrophytes encompass major functional group in eutrophic wetland ecosystems. As a key functional element of freshwater lakes, they play a crucial role in regulating various wetland biogeochemical cycles, as well as maintain the biodiversity at the ecosystem level. The high carbon-rich underground biomass of macrophyte populations may harbour diverse microbial community having significant potential in maintaining different biogeochemical cycles. The present investigation was designed to study the macrophyte-microbe interaction in coupled nitrification and denitrification, considering Deepor Beel Lake (a Ramsar conservation site) of North East India as a model eutrophic system. Highly eutrophic sites of Deepor Beel were selected based on sediment oxygen demand and inorganic phosphorus and nitrogen (P&N) concentration. Sediment redox potential and depth of the lake was chosen as the benchmark for collecting the plant and sediment samples. The average highest depth in winter (January 2016) and summer (July 2016) were recorded as 20ft (6.096m) and 35ft (10.668m) respectively. Both sampling depth and sampling seasons had the distinct effect on variation in macrophyte community composition. Overall, the dominant macrophytic populations in the lake were Nymphaea alba, Hydrilla verticillata, Utricularia flexuosa, Vallisneria spiralis, Najas indica, Monochoria hastaefolia, Trapa bispinosa, Ipomea fistulosa, Hygrorhiza aristata, Polygonum hydropiper, Eichhornia crassipes and Euryale ferox. There was a distinct correlation in the variation of major sediment physicochemical parameters with change in macrophyte community compositions. Quantitative estimation revealed an almost even accumulation of nitrate and nitrite in the sediment samples dominated by the plant species Eichhornia crassipes, Nymphaea alba, Hydrilla verticillata, Vallisneria spiralis, Euryale ferox and Monochoria hastaefolia, which might have signified a stable nitrification and denitrification process in the sites dominated by the selected aquatic plants. This was further examined by a systematic analysis of microbial populations through culture dependent and independent approach. Culture-dependent bacterial community study revealed the higher population of nitrifiers and denitrifiers in the sediment samples dominated by the six macrophyte species. However, culture-independent study with bacterial 16S rDNA V3-V4 metagenome sequencing revealed the overall similar type of bacterial phylum in all the sediment samples collected during the study. Thus, there might be the possibility of uneven distribution of nitrifying and denitrifying molecular markers among the sediment samples collected during the investigation. The diversity and abundance of the nitrifying and denitrifying molecular markers in the sediment samples are under investigation. Thus, the role of different aquatic plant functional types in microorganism mediated nitrogen cycle coupling could be screened out further from the present initial investigation.

Keywords: denitrification, macrophyte, metagenome, microorganism, nitrification

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Authors: Bhavesh N. Bhatt, Zozimus D. Labana

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This work is mainly focused on the analysis of heat transfer of blade by using internal cooling method. By using conjugate heat transfer technology we can effectively compute the cooling and heat transfer analysis of blade. Here blade temperature is limited by materials melting temperature. By using CFD code, we will analyze the blade cooling with the help of CHT method. There are two types of CHT methods. In the first method, we apply coupled CHT method in which all three domains modeled at once, and in the second method, we will first model external domain and then, internal domain of cooling channel. Ten circular cooling channels are used as a cooling method with different mass flow rate and temperature value. This numerical simulation is applied on NASA C3X turbine blade, and results are computed. Here results are showing good agreement with experimental results. Temperature and pressure are high at the leading edge of the blade on stagnation point due to its first faces the flow. On pressure side, shock wave is formed which also make a sudden change in HTC and other parameters. After applying internal cooling, we are succeeded in reducing the metal temperature of blade by some extends.

Keywords: gas turbine, conjugate heat transfer, NASA C3X Blade, circular film cooling channel

Procedia PDF Downloads 335