Search results for: fuzzy modeling and rule extraction

Authors: Dawd Ahmed, Venkatesh Uddameri

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Agriculture in Ethiopia is the main economic sector influenced by agricultural drought. A simultaneous assessment of drought trends using multiple drought indicators is useful for drought planning and management. Intra-season and seasonal drought trends in Ethiopia were studied using a suite of drought indicators. Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI), Palmer Drought Severity Index (PDSI), and Z-index for long-rainy, dry, and short-rainy seasons are used to identify drought-causing mechanisms. The Statistical software package R version 3.5.2 was used for data extraction and data analyses. Trend analysis indicated shifts in late-season long-rainy season precipitation into dry in the southwest and south-central portions of Ethiopia. Droughts during the dry season (October–January) were largely temperature controlled. Short-term temperature-controlled hydrologic processes exacerbated rainfall deficits during the short rainy season (February–May) and highlight the importance of temperature- and hydrology-induced soil dryness on the production of short-season crops such as tef. Droughts during the long-rainy season (June–September) were largely driven by precipitation declines arising from the narrowing of the intertropical convergence zone (ITCZ). Increased dryness during long-rainy season had severe consequences on the production of corn and sorghum. PDSI was an aggressive indicator of seasonal droughts suggesting the low natural resilience to combat the effects of slow-acting, moisture-depleting hydrologic processes. The lack of irrigation systems in the nation limits the ability to combat droughts and improve agricultural resilience. There is an urgent need to monitor soil moisture (a key agro-hydrologic variable) to better quantify the impacts of meteorological droughts on agricultural systems in Ethiopia.

Keywords: autocorrelation, climate change, droughts, Ethiopia, food security, palmer z-index, PDSI, SPEI, SPI, trend analysis

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Authors: Joseph Amponsah

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This research proposes an equation to predict and determine the momentum source equation term after factoring in the radial friction between the fluid and the blades and the impeller's propulsive power. This research aims to look at how CFD software can be used to predict the effect of flows in nuclear reactor stirred tanks through a momentum source equation and the concentration distribution of tracers that have been introduced in reactor tanks. The estimated findings, including the dimensionless concentration curves, power, and pumping numbers, dimensionless velocity profiles, and mixing times 4, were contrasted with results from tests in stirred containers. The investigation was carried out in Part I for vessels that were agitated by one impeller on a central shaft. The two types of impellers employed were an ordinary Rushton turbine and a 6-bladed 45° pitched blade turbine. The simulations made use of numerous reference frame techniques and the common k-e turbulence model. The impact of the grid type was also examined; unstructured, structured, and unique user-defined grids were looked at. The CFD model was used to simulate the flow field within the Rushton turbine nuclear reactor stirred tank. This method was validated using experimental data that were available close to the impeller tip and in the bulk area. Additionally, analyses of the computational efficiency and time using MRF and SM were done.

Keywords: Ansys fluent, momentum equation, CFD, prediction

Procedia PDF Downloads 75

Authors: Cheng-Kuang Hsu, Chih-Hsiang Chang, Chi-Chih Wang

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Black soybeans contain high amount of antioxidants including polyphenols, anthocyanins and flavones. The protective function of black soybean against CCl4 (a strong oxidant) induced acute and chronic liver damage was investigated in vivo using SD rats or ICR mouse. The evaluation of CCl4 induced oxidative stress in the liver tissues included the measurements of the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), the concentration of thiobarbituric acid reactive substances (TBARS), the activities of antioxidant enzymes (superoxide dismutase SOD, catalase, and glutathione peroxidase GPx), as well as the level of histological lesion in the liver tissues. For chronic experiment, a decoction at the concentration of 100 or 1000 mg/kg of body weight, produced by baking black soybean at 130°C for 5 min and followed by immerging in 100°C hot water for 20 min, showed the inhibitory effect against CCl4 induced liver damage in SD rats. Hot-water extract (80 °C for 30 min) from un-preheated black soybean at the concentration of 200 mg/kg of body weight could not reduce ALT and AST levels in CCl4 treated SD rats, but the hot-water extract from preheated black soybean did enhance antioxidant enzymes activities, decline ALT and AST levels. Specially, the hot-water extract from the seed cost of black soybean had the highest liver protective function since it can reduce vacuolization and necrosis in the liver tissues. For acute experiment, the hot-water extracts from black soybean and the seed coat, as well as pure cyanidin-3-glucoside (C3G) could reduce ALT and AST levels of CCl4 induced ICR mouse. The decoction and hot-water extract from the seed coat of black soybean had higher total polyphenols, anthocyanins and flavones contents than those extracts from whole black soybean. Such results agreed with high liver protective function in the decoction and hot-water from the seed coat of black soybean. Black soybean showed protective function only after preheating process (baking at 130°C for 5 to 10 min) because preheating treatment damaged the cell wall and made the extraction of the antioxidants more effectively.

Keywords: black soybean, liver protective function, antioxidant, antioxidative stress

Procedia PDF Downloads 475

Authors: Adriano Trono, Federico Pinto, Diego Turello, Marcelo A. Ceballos

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Numerical modeling of dynamic soil-structure interaction problems requires an adequate representation of the unbounded characteristics of the ground, material non-linearity of soils, and geometrical non-linearities such as large displacements due to rocking of the structure. In order to account for these effects simultaneously, it is often required that the equations of motion are solved in the time domain. However, boundary conditions in conventional finite element codes generally present shortcomings in fully absorbing the energy of outgoing waves. In this sense, the Perfectly Matched Layers (PML) technique allows a satisfactory absorption of inclined body waves, as well as surface waves. However, the PML domain is inherently unstable, meaning that it its instability does not depend upon the discretization considered. One way to stabilize the PML domain is to use multiaxial stretching functions. This development is questionable because some Jacobian terms of the coordinate transformation are not accounted for. For this reason, the resulting absorbing layer element is often referred to as "uncorrected M-PML” in the literature. In this work, the strong formulation of the "corrected M-PML” absorbing layer is proposed using multiaxial stretching functions that incorporate all terms of the coordinate transformation. The results of the stable model are compared with reference solutions obtained from extended domain models.

Keywords: mixed finite elements, multiaxial stretching functions, perfectly matched layer, soil-structure interaction

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Authors: Olivier Mesly

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This research presents a conceptual framework termed “Consumer Financial Spinning” (CFS) to analyze consumer behavior in the financial/economic markets. This phenomenon occurs when consumers of high-stakes financial products accumulate unsustainable debt, leading them to detach from their initial financial hierarchy of needs, wealth-related goals, and preferences regarding their household portfolio of assets. The daring actions of these consumers, forming a dark financial triangle, are characterized by three behaviors: overconfidence, the use of rationed rationality, and deceitfulness. We show that we can incorporate CFS into the traditional CAPM and Markovitz’ portfolio optimization models to create a framework that explains such market phenomena as the global financial crisis, highlighting the antecedents and consequences of ill-conceived speculation. Because this is a conceptual paper, there is no methodology with respect to ground studies. However, we apply modeling principles derived from the data percolation methodology, which contains tenets explicating how to structure concepts. A simulation test of the proposed framework is conducted; it demonstrates the conditions under which the relationship between expected returns and risk may deviate from linearity. The analysis and conceptual findings are particularly relevant both theoretically and pragmatically as they shed light on the psychological conditions that drive intense speculation, which can lead to market turmoil. Armed with such understanding, regulators are better equipped to propose solutions before the economic problems become out of control.

Keywords: consumer financial spinning, rationality, deceitfulness, overconfidence, CAPM

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Authors: Natalia Limones, Javier Marzo, Marcus Wijnen, Aleix Serrat-Capdevila

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In this research we developed a structured approach for the detection of areas under the highest levels of drought risk that is suitable for data-scarce environments. The methodology is based on recent scientific outcomes and methods and can be easily adapted to different contexts in successive exercises. The research reviews the history of drought in the south of Angola and characterizes the experienced hazard in the episode from 2012, focusing on the meteorological and the hydrological drought types. Only global open data information coming from modeling or remote sensing was used for the description of the hydroclimatological variables since there is almost no ground data in this part of the country. Also, the study intends to portray the socioeconomic vulnerabilities and the exposure to the phenomenon in the region to fully understand the risk. As a result, a map of the areas under the highest risk in the south of the country is produced, which is one of the main outputs of this work. It was also possible to confirm that the set of indicators used revealed different drought vulnerability profiles in the South of Angola and, as a result, several varieties of priority areas prone to distinctive impacts were recognized. The results demonstrated that most of the region experienced a severe multi-year meteorological drought that triggered an unprecedent exhaustion of the surface water resources, and that the majority of their socioeconomic impacts started soon after the identified onset of these processes.

Keywords: drought risk, exposure, hazard, vulnerability

Procedia PDF Downloads 188

Authors: Laura Mejias, Sandra Monteagudo, Oscar Martinez-Avila, Sergio Ponsa

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Bioplastics are gaining attention as potential substitutes of conventional fossil-derived plastics and new components of specialized applications in different industries. Besides, these constitute a sustainable alternative since they are biodegradable and can be obtained starting from renewable sources. Thus, agro-industrial wastes appear as potential substrates for bioplastics production using microorganisms, considering they are a suitable source for nutrients, low-cost, and available worldwide. Therefore, this approach contributes to the biorefinery and circular economy paradigm. The present study assesses the solid-state fermentation (SSF) technology for the co-synthesis of exopolysaccharides (EPS) and polyhydroxyalkanoates (PHA), two attractive biodegradable bioplastics, using the leftover of the brewery industry brewer's spent grain (BSG). After an initial screening of diverse PHA-producer bacteria, it was found that Burkholderia cepacia presented the highest EPS and PHA production potential via SSF of BSG. Thus, B. cepacia served to identify the most relevant aspects affecting the EPS+PHA co-synthesis at a lab-scale (100g). Since these are growth-dependent processes, they were monitored online through oxygen consumption using a dynamic respirometric system, but also quantifying the biomass production (gravimetric) and the obtained products (EtOH precipitation for EPS and solid-liquid extraction coupled with GC-FID for PHA). Results showed that B. cepacia has grown up to 81 mg per gram of dry BSG (gDM) at 30°C after 96 h, representing up to 618 times higher than the other tested strains' findings. Hence, the crude EPS production was 53 mg g-1DM (2% carbohydrates), but purity reached 98% after a dialysis purification step. Simultaneously, B. cepacia accumulated up to 36% (dry basis) of the produced biomass as PHA, mainly composed of polyhydroxybutyrate (P3HB). The maximum PHA production was reached after 48 h with 12.1 mg g⁻¹DM, representing threefold the levels previously reported using SSF. Moisture content and aeration strategy resulted in the most significant variables affecting the simultaneous production. Results show the potential of co-synthesis via SSF as an attractive alternative to enhance bioprocess feasibility for obtaining these bioplastics in residue-based systems.

Keywords: bioplastics, brewer’s spent grain, circular economy, solid-state fermentation, waste to product

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Authors: Majid Alizadeh, Sina Nematizadeh, Hassan Esmailpour

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The mutual effects of hospitality and the environment are undeniable, so that the tourism industry has major harmful effects on the environment. Hotels, as one of the most important pillars of the hospitality industry, have significant effects on the environment. Green marketing is a promising strategy in response to the growing concerns about the environment. A green hotel marketing model was proposed using a grounded theory approach in the hotel industry. The study was carried out as a mixed method study. Data gathering in the qualitative phase was done through literature review and In-depth, semi-structured interviews with 10 experts in green marketing using snowball technique. Following primary analysis, open, axial, and selective coding was done on the data, which yielded 69 concepts, 18 categories and six dimensions. Green hotel (green product) was adopted as the core phenomenon. In the quantitative phase, data were gleaned using 384 questionnaires filled-out by hotel guests and descriptive statistics and Structural equation modeling (SEM) were used for data analysis. The results indicated that the mediating role of behavioral response between the ecological literacy, trust, marketing mix and performance was significant. The green marketing mix, as a strategy, had a significant and positive effect on guests’ behavioral response, corporate green image, and financial and environmental performance of hotels.

Keywords: green marketing, sustainable development, hospitality, grounded theory, structural equations model

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Authors: S. Alyami, S. Mohammad

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These Risk management practices have a significant impact on construction SMEs. The effective utilisation of these practices depends on culture change in order to optimise decision making for critical activities within construction projects. Thus, successful implementation of empowerment strategies would enhance operational employees to participate in effective decision making. However, there remain many barriers to individuals and organisations within empowerment strategies that require empirical investigation before the industry can benefit from their implementation. Gaps in understanding the relationship between employee empowerment and risk management practices still exist. This research paper aims to examine the impact of the structural empowerment on risk management practices in construction SMEs. The questionnaire has been distributed to participants (162 employees) that involve projects and civil engineers within a case study from Saudi construction SMEs. Partial least squares based structural equation modeling (PLS-SEM) was utilised to perform analysis. The results reveal a positive relationship between empowerment and risk management practices. The study shows how structural empowerment contributes to operational employees in risk management practices through involving activities such as decision making, self-efficiency, and autonomy. The findings of this study will contribute to close the current gaps in the construction SMEs context.

Keywords: construction SMEs, culture, decision making, empowerment, risk management

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Authors: Azeez Shaik, Amit Salvi, B. P. Gautham

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Fiber reinforced polymer resin composite materials are finding wide variety of applications in automotive and aerospace industry because of their high specific stiffness and specific strengths when compared to metals. New class of 2D and 3D textile and woven fabric composites offer excellent fracture toughens as they bridge the cracks formed during fracture. Due to complexity of their fiber architectures and its resulting composite microstructures, optimized design and analysis of these structures is very complicated. A traditional homogenization approach is typically used to analyze structures made up of these materials. This approach usually fails to predict damage initiation as well as damage propagation and ultimate failure of structure made up of woven and textile composites. This study demonstrates a methodology to analyze woven and textile composites by using the multi-level multi-scale modelling approach. In this approach, a geometric repetitive unit cell (RUC) is developed with all its constituents to develop a representative volume element (RVE) with all its constituents and their interaction modeled correctly. The structure is modeled based on the RUC/RVE and analyzed at different length scales with desired levels of fidelity incorporating the damage and failure. The results are passed across (up and down) the scales qualitatively as well as quantitatively from the perspective of material, configuration and architecture.

Keywords: cohesive zone, multi-scale modeling, rate dependency, RUC, woven textiles

Procedia PDF Downloads 358

Authors: Yunseok Noh, Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park

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Scripts are one of the basic text resources to understand broadcasting contents. Since broadcast media wields lots of influence over the public, tools for understanding broadcasting contents are more required. Topic modeling is the method to get the summary of the broadcasting contents from its scripts. Generally, scripts represent contents descriptively with directions and speeches. Scripts also provide scene segments that can be seen as semantic units. Therefore, a script can be topic modeled by treating a scene segment as a document. Because scripts consist of speeches mainly, however, relatively small co-occurrences among words in the scene segments are observed. This causes inevitably the bad quality of topics based on statistical learning method. To tackle this problem, we propose a method of learning with additional word co-occurrence information obtained using scene similarities. The main idea of improving topic quality is that the information that two or more texts are topically related can be useful to learn high quality of topics. In addition, by using high quality of topics, we can get information more accurate whether two texts are related or not. In this paper, we regard two scene segments are related if their topical similarity is high enough. We also consider that words are co-occurred if they are in topically related scene segments together. In the experiments, we showed the proposed method generates a higher quality of topics from Korean drama scripts than the baselines.

Keywords: broadcasting contents, scripts, text similarity, topic model

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Authors: Qiang Wang, Hongyang Yu

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Multi-human 3D pose estimation is a challenging task in computer vision, which aims to recover the 3D joint locations of multiple people from multi-view images. In contrast to traditional methods, which typically only use color (RGB) images as input, our approach utilizes both color and depth (D) information contained in RGB-D images. We also employ a transformer-based model as the backbone of our approach, which is able to capture long-range dependencies and has been shown to perform well on various sequence modeling tasks. Our method is trained and tested on the Carnegie Mellon University (CMU) Panoptic dataset, which contains a diverse set of indoor and outdoor scenes with multiple people in varying poses and clothing. We evaluate the performance of our model on the standard 3D pose estimation metrics of mean per-joint position error (MPJPE). Our results show that the transformer-based approach outperforms traditional methods and achieves competitive results on the CMU Panoptic dataset. We also perform an ablation study to understand the impact of different design choices on the overall performance of the model. In summary, our work demonstrates the effectiveness of using a transformer-based approach with RGB-D images for multi-human 3D pose estimation and has potential applications in real-world scenarios such as human-computer interaction, robotics, and augmented reality.

Keywords: multi-human 3D pose estimation, RGB-D images, transformer, 3D joint locations

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Authors: Md Abdullah Al Faruque, Ram Balachandar

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Sudden change of bed condition is frequent in open channel flow. Change of bed condition affects the turbulence characteristics in both streamwise and wall-normal direction. Understanding the turbulence intensity in open channel flow is of vital importance to the modeling of sediment transport and resuspension, bed formation, entrainment, and the exchange of energy and momentum. A comprehensive study was carried out to understand the extent of the effect of Reynolds number and bed roughness on different turbulence characteristics in an open channel flow. Four different bed conditions (impervious smooth bed, impervious continuous rough bed, pervious rough sand bed, and impervious distributed roughness) and two different Reynolds numbers were adopted for this cause. The effect of bed roughness on different turbulence characteristics is seen to be prevalent for most of the flow depth. Effect of Reynolds number on different turbulence characteristics is also evident for flow over different bed, but the extent varies on bed condition. Although the same sand grain is used to create the different rough bed conditions, the difference in turbulence characteristics is an indication that specific geometry of the roughness has an influence on turbulence characteristics. Roughness increases the contribution of the extreme turbulent events which produces very large instantaneous Reynolds shear stress and can potentially influence the sediment transport, resuspension of pollutant from bed and alter the nutrient composition, which eventually affect the sustainability of benthic organisms.

Keywords: open channel flow, Reynolds Number, roughness, turbulence

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Authors: Carmen Cantuarias-Villessuzanne, Jeffrey Blain, Radmila Pineau

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Our research project aims at analyzing the sensitiveness of French households to urban biodiversity and urban ecosystem services (UES). Opinion surveys show that the French population is sensitive to biodiversity and ecosystem services loss, but the value given to these issues within urban fabric and real estate market lacks evidence. Using GIS data and economic evaluation, by hedonic price methods, weassess the isolated contribution of the explanatory variables of biodiversityand UES on the price of residential real estate. We analyze the variation of the valuefor three urban ecosystem services - flood control, proximity to green spaces, and refreshment - on the price of real estate whena property changes ownership. Our modeling and mapping focus on the price at theIRIS scale (statistical information unit) from 2014 to 2019. The main variables are internal characteristics of housing (area, kind of housing, heating), external characteristics(accessibility and infrastructure, economic, social, and physical environmentsuch as air pollution, noise), and biodiversity indicators and urban ecosystemservices for the Ile-de-France region. Moreover, we compare environmental values on the enhancement of greenspaces and their impact on residential choices. These studies are very useful for real estate developers because they enable them to promote green spaces, and municipalities to become more attractive.

Keywords: urban ecosystem services, sustainable real estate, urban biodiversity perception, hedonic price, environmental values

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Authors: Ali Bahkali, Rayan Yousef Booq, Mohammad Khiyami

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Soil samples were collected from five different regions in the Kingdom of Saudi Arabia. Microbiological methods included dilution methods and pour plates to isolate and purify bacteria soil. The ability of isolates to develop biopolymer was investigated on petri dishes containing elements and substance concentrations stimulating developing biopolymer. Fluorescent stains, Nile red and Nile blue were used to stain the bacterial cells developing biopolymers. In addition, Sudan black was used to detect biopolymers in bacterial cells. The isolates which developed biopolymers were identified based on their gene sequence of 1 6sRNA and their ability to grow and synthesize PHAs on mineral medium supplemented with 1% dates molasses as the only carbon source under nitrogen limitation. During the study 293 bacterial isolates were isolated and detected. Through the initial survey on the petri dishes, 84 isolates showed the ability to develop biopolymers. These bacterial colonies developed a pink color due to accumulation of the biopolymers in the cells. Twenty-three isolates were able to grow on dates molasses, three strains of which showed the ability to accumulate biopolymers. These strains included Bacillus sp., Ralstonia sp. and Microbacterium sp. They were detected by Nile blue A stain with fluorescence microscopy (OLYMPUS IX 51). Among the isolated strains Ralstonia sp. was selected after its ability to grow on molasses dates in the presence of a limited nitrogen source was detected. The optimum conditions for formation of biopolymers by isolated strains were investigated. Conditions studied included, best incubation duration (2 days), temperature (30°C) and pH (7-8). The maximum PHB production was raised by 1% (v1v) when using concentrations of dates molasses 1, 2, 3, 4 and 5% in MSM. The best inoculated with 1% old inoculum (1= OD). The ideal extraction method of PHA and PHB proved to be 0.4% sodium hypochlorite solution, producing a quantity of polymer 98.79% of the cell's dry weight. The maximum PHB production was 1.79 g/L recorded by Ralstonia sp. after 48 h, while it was 1.40 g/L produced by R.eutropha ATCC 17697 after 48 h.

Keywords: bacteria forming polyhydroxyalkanoate, detection, molecular, Saudi Arabia

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Authors: Roupa Agbadede, Biweri Kainga, Mafel Obhuo

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With the growing environmental concerns and regulations associated with fossil fuel usage, the quest for a more favorable, environmentally friendly fuel becomes imperative. Recently, researchers and Original Equipment manufacturers (OEMs) have started exploring means of burning hydrogen in gas turbines because of its potential environmentally friendly nature and performance benefits. However, there are concerns, such as technical and economic challenges, which need to be addressed for its implementation to be feasible. This study presents the investigation of the economic viability of using hydrogen as an alternative to fossil fuels in gas turbines for power generation applications. GasTurb details 5.1 was employed to model the hydrogen-enriched natural gas fuel, while GasTurb 11 was used to model and simulate the performance of the intercooled combined cycle gas turbine engine fired with different fuels. When the heat rate of the engine fired separately with natural gas and hydrogen were compared, the results show that the engine fired with natural gas produced a heat rate of 7180kJ/kWh while hydrogen fuel generated 7134kJ/kWh. Also, when the economic analysis of the engine operated separately with natural gas and hydrogen was compared for the entire life cycle (20years) of the power plant, it was observed that the net present value for the engine fired with natural gas is £736,271,747 as against -£981,795,830.2 for hydrogen.

Keywords: economic analysis, fuel modeling, engine performance analysis, hydrogen, net present value, internal rate of return

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Authors: Tania Bose, Minto Rattan, Neeraj Chamoli

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In this paper, an attempt has been made to study the effect of thermal gradation on the steady-state creep behavior of rotating isotropic disc made of functionally graded material using threshold stress based Sherby’s creep law. The composite discs made of aluminum matrix reinforced with silicon carbide particulate have been taken for analysis. The stress and strain rate distributions have been calculated for the discs rotating at elevated temperatures having thermal gradation. The material parameters of creep vary radially and have been estimated by regression fit of the available experimental data. Investigations for discs made up of linearly increasing particle content operating under linearly decreasing temperature from inner to outer radii have been done using von Mises’ yield criterion. The results are displayed and compared graphically in designer friendly format for the above said disc profile with the disc made of particle reinforced composite operating under uniform temperature profile. It is observed that radial and tangential stresses show minor variation and the strain rates vary significantly in the presence of thermal gradation as compared to disc having uniform temperature.

Keywords: creep, isotropic, steady-state, thermal gradation

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Authors: Ayman Abd-Elhamed, Sayed Mahmoud

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The present research work investigates the seismic response of reinforced concrete (RC) frame building considering the effect of modeling masonry infill (MI) walls. The seismic behavior of a residential 6-storey RC frame building, considering and ignoring the effect of masonry, is numerically investigated using response spectrum (RS) analysis. The considered herein building is designed as a moment resisting frame (MRF) system following the Egyptian code (EC) requirements. Two developed models in terms of bare frame and infill walls frame are used in the study. Equivalent diagonal strut methodology is used to represent the behavior of infill walls, whilst the well-known software package ETABS is used for implementing all frame models and performing the analysis. The results of the numerical simulations such as base shear, displacements, and internal forces for the bare frame as well as the infill wall frame are presented in a comparative way. The results of the study indicate that the interaction between infill walls and frames significantly change the responses of buildings during earthquakes compared to the results of bare frame building model. Specifically, the seismic analysis of RC bare frame structure leads to underestimation of base shear and consequently damage or even collapse of buildings may occur under strong shaking. On the other hand, considering infill walls significantly decrease the peak floor displacements and drifts in both X and Y-directions.

Keywords: masonry infill, bare frame, response spectrum, seismic response

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Authors: M. Mirmohammadi, S. Taghdisi, F. Anali

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Gossypol is a yellow anti-nutritional compound found in the cotton plant. This substance exists in the cottonseed and other parts of the cotton plant, such as bark, leaves, and stems. Chemically, gossypol is a very active polyphenolic aldehyde compound, and due to this polyphenolic structure, it has antioxidant and therapeutic properties. On the other hand, this compound, especially in free form, has many toxic effects, that its excessive consumption can be very dangerous for humans and animals. In this study, gossypol was extracted as a derivative compound of gossypol acetic acid from cottonseed using the n-hexane solvent with an efficiency of 0.84 ± 0.04, which compared to the Gossypol extracted from cottonseed oil with the same method (cold press) showed a significant difference with its efficiency of 1.14 ± 0.06. Therefore, it can be suggested to use cottonseed oil to extract this valuable compound. In the other part of this research, cottonseed extracts and cotton bolls extracts were obtained by two methods of soaking and Soxhlet with hydroalcoholic solvent taken with a ratio of (25:75), then by using extracts and corn starch powder, four herbal medicine code was created and after receiving the code of ethics (IR.SSU.REC.1398.136) the therapeutic effect of each one on the Cutaneous leishmaniasis resistant to drugs (caused by the leishmaniasis parasite) was investigated in real patients and its results was compared with the common drug glucantime (local ampoule) (n = 36). Statistical studies showed that the use of herbal medicines prepared with cottonseed extract and cotton bolls extract has a significant positive effect on the treatment of the disease’s wounds (p-value > 0.05) compared to the control group (only ethanol). Also, by comparing the average diameter of the wounds after a two-month treatment period, no significant difference was found between the use of ointment containing extracts and local glucantime ampoules (p-value < 0.05). Bolls extract extracted with the Soxhlet method showed the best therapeutic effects, although there was no significant difference between them (p-value < 0.05). Therefore, there is acceptable reliability to recommend this medicine for the treatment of Cutaneous leishmaniasis resistant to drugs without the side effects of the chemical drug glucantime and the pain of injecting the ampoule.

Keywords: cottonseed oil, gossypol, cotton boll, cutaneous leishmaniasis

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Authors: Himanshu Sharma, Karthik Kumar, Harish Kumar

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The major problem in crop cultivation is the occurrence of multiple crop diseases. During the growth stage, timely identification of crop diseases is paramount to ensure the high yield of crops, lower production costs, and minimize pesticide usage. In most cases, crop diseases produce observable characteristics and symptoms. The Surveyors usually diagnose crop diseases when they walk through the fields. However, surveyor inspections tend to be biased and error-prone due to the nature of the monotonous task and the subjectivity of individuals. In addition, visual inspection of each leaf or plant is costly, time-consuming, and labour-intensive. Furthermore, the plant pathologists and experts who can often identify the disease within the plant according to their symptoms in early stages are not readily available in remote regions. Therefore, this study specifically addressed early detection of leaf scald, red rot, and eyespot types of diseases within sugarcane plants. The study proposes a computer vision-based approach using a convolutional neural network (CNN) for automatic identification of crop diseases. To facilitate this, firstly, images of sugarcane diseases were taken from google without modifying the scene, background, or controlling the illumination to build the training dataset. Then, the testing dataset was developed based on the real-time collected images from the sugarcane field from India. Then, the image dataset is pre-processed for feature extraction and selection. Finally, the CNN-based Visual Geometry Group (VGG) model was deployed on the training and testing dataset to classify the images into diseased and healthy sugarcane plants and measure the model's performance using various parameters, i.e., accuracy, sensitivity, specificity, and F1-score. The promising result of the proposed model lays the groundwork for the automatic early detection of sugarcane disease. The proposed research directly sustains an increase in crop yield.

Keywords: automatic classification, computer vision, convolutional neural network, image processing, sugarcane disease, visual geometry group

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Authors: Karen C. Olufokunbi, Odetunji A. Odejobi

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The discourse of this paper is the examination of the generation, accumulation and growth of e-waste in a developing country. Images and other data about computer e-waste were collected using a digital camera, 290 copies of questionnaire and three structured interviews using Obafemi Awolowo University (OAU), Ile-Ife, Nigeria environment as a case study. The numerical data were analysed using R data analysis and process tool. Automata-based techniques and Petri net modeling tool were used to design and simulate a computational model for the recovery of saleable materials from e-waste. The R analysis showed that at a 95 percent confidence level, the computer equipment that will be disposed by 2020 will be 417 units. Compared to the 800 units in circulation in 2014, 50 percent of personal computer components will become e-waste. This indicates that personal computer components were in high demand due to their low costs and will be disposed more rapidly when replaced by new computer equipment Also, 57 percent of the respondents discarded their computer e-waste by throwing it into the garbage bin or by dumping it. The simulated model using Coloured Petri net modelling tool for the process showed that the e-waste dynamics is a forward sequential process in the form of a pipeline meaning that an e-waste recovery of saleable materials process occurs in identifiable discrete stages indicating that e-waste will continue to accumulate and grow in volume with time.

Keywords: Coloured Petri net, computational modelling, electronic waste, electronic waste process dynamics

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Authors: Asmae Tafraouti, Yasmina Layouni, Pascal Kleimann

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The growing market for Microsystems (MST) and Micro-Electromechanical Systems (MEMS) is driving the research for alternative manufacturing techniques to microelectronics-based technologies, which are generally expensive and time-consuming. Hot-embossing and micro-injection modeling of thermoplastics appear to be industrially viable processes. However, both require the use of master models, usually made in hard materials such as steel. These master models cannot be fabricated using standard microelectronics processes. Thus, other micromachining processes are used, such as laser machining or micro-electrical discharge machining (µEDM). In this work, µEDM has been used. The principle of µEDM is based on the use of a thin cylindrical micro-tool that erodes the workpiece surface. The two electrodes are immersed in a dielectric with a distance of a few micrometers (gap). When an electrical voltage is applied between the two electrodes, electrical discharges are generated, which cause material machining. In order to produce master models with high resolution and smooth surfaces, it is necessary to well control the discharge mechanism. However, several problems are encountered, such as a random electrical discharge process, the fluctuation of the discharge energy, the electrodes' polarity inversion, and the wear of the micro-tool. The effect of different parameters, such as the applied voltage, the working capacitor, the micro-tool diameter, and the initial gap, has been studied. This analysis helps to improve the machining performances, such as the workpiece surface condition and the lateral crater's gap.

Keywords: craters, electrical discharges, micro-electrical discharge machining, microsystems

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Authors: A. Armin, R. Fotouhi, W. Szyszkowski

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This paper is part of a study to develop robots for farming. As such power requirement to operate equipment attach to such robots become an important factor. Soil-tool interaction play major role in power consumption, thus predicting accurately the forces which act on the blade during the farming is prime importance for optimal designing of farm equipment. In this paper a finite element investigation for tillage tools and soil interaction is described by using an inelastic constitutive material law for agriculture application. A 3-dimentional (3D) nonlinear finite element analysis (FEA) is developed to examine behavior of a blade with different rake angles moving in a block of soil, and to estimate the blade force. The soil model considered is an elastic-plastic with non-associated Drucker-Prager material model. Special use of contact elements are employed to consider connection between soil-blade and soil-soil surfaces. The FEA results are compared with experiment ones, which show good agreement in accurately predicting draft forces developed on the blade when it moves through the soil. Also, a very good correlation was obtained between FEA results and analytical results from classical soil mechanics theories for straight blades. These comparisons verified the FEA model developed. For analyzing complicated soil-tool interactions and for optimum design of blades, this method will be useful.

Keywords: finite element analysis, soil-blade contact modeling, blade force, mechanical engineering

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Authors: M. Etezadi, A. Fahimifar

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In many geotechnical designs in rocks and rock masses, tensile strength of rock and rock mass is needed. The difficulties associated with performing a direct uniaxial tensile test on a rock specimen have led to a number of indirect methods for assessing the tensile strength that in the meantime the Brazilian test is more popular. Brazilian test is widely applied in rock engineering because specimens are easy to prepare, the test is easy to conduct and uniaxial compression test machines are quite common. This study compares experimental results of direct and Brazilian tensile tests carried out on two rock types and three concrete types using 39 cylindrical and 28 disc specimens. The tests are performed using Servo-Control device. The relationship between direct and indirect tensile strength of specimens is extracted using linear regression. In the following, tensile strength of direct and indirect test is evaluated using finite element analysis. The results are analyzed and effective factors on results are studied. According to the experimental results Brazilian test is shown higher tensile strength than direct test. Because of decreasing the contact surface of grains and increasing the uniformity in concrete specimens with fine aggregate (largest grain size= 6mm), higher tensile strength in direct test is shown. The experimental and numerical results of tensile strength are compared and empirical relationship witch is obtained from experimental tests is validated.

Keywords: tensile strength, brittle materials, direct and indirect tensile test, numerical modeling

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Authors: Surendra Choudhary, Sapan Tiwari

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The driver has two fundamental duties i) controlling the position of the vehicle along the longitudinal and lateral direction of movement ii) roadway width. Both of these duties are interdependent and are concurrently referred to as two-dimensional driver behavior. One of the main problems facing driver behavior modeling is to identify the parameters for describing the exemplary driving conduct and car maneuver under distinct traffic circumstances. Still, to date, there is no well-accepted theory that can comprehensively model the 2-D driver conduct (longitudinal and lateral). The primary objective of this research is to explore the vehicle's lateral longitudinal behavior in the heterogeneous condition of traffic on horizontal curves as well as the effect of road geometry on dynamic traffic parameters, i.e., car velocity and lateral placement. In this research, with their interrelationship, a thorough assessment of dynamic car parameters, i.e., speed, lateral acceleration, and turn radius. Also, horizontal curve road parameters, i.e., curvature radius, pavement friction, are performed. The dynamic parameters of the various types of car drivers are gathered using a VBOX GPS-based tool with high precision. The connection between dynamic car parameters and curve geometry is created after the removal of noise from the GPS trajectories. The major findings of the research are that car maneuvers with higher than the design limits of speed, acceleration, and lateral deviation on the studied curves of the highway. It can become lethal if the weather changes from dry to wet.

Keywords: geometry, maneuverability, terrain, trajectory, VBOX

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Authors: Bassim Shaheen Bachy, Jörg Franke

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In this study, a three dimensional numerical heat transfer model has been used to simulate the laser structuring of polymer substrate material in the Three-Dimensional Molded Interconnect Device (3D MID) which is used in the advanced multi-functional applications. A finite element method (FEM) transient thermal analysis is performed using APDL (ANSYS Parametric Design Language) provided by ANSYS. In this model, the effect of surface heat source was modeled with Gaussian distribution, also the effect of the mixed boundary conditions which consist of convection and radiation heat transfers have been considered in this analysis. The model provides a full description of the temperature distribution, as well as calculates the depth and the width of the groove upon material removal at different set of laser parameters such as laser power and laser speed. This study also includes the experimental procedure to study the effect of laser parameters on the depth and width of the removal groove metal as verification to the modeled results. Good agreement between the experimental and the model results is achieved for a wide range of laser powers. It is found that the quality of the laser structure process is affected by the laser scan speed and laser power. For a high laser structured quality, it is suggested to use laser with high speed and moderate to high laser power.

Keywords: laser structuring, simulation, finite element analysis, thermal modeling

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Authors: Chokri Slim

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The relative failure of simultaneous equation models in the seventies has led researchers to turn to other approaches that take into account the dynamics of economic and financial systems. In this paper, we use an approach based on vector autoregressive model that is widely used in recent years. Their popularity is due to their flexible nature and ease of use to produce models with useful descriptive characteristics. It is also easy to use them to test economic hypotheses. The standard econometric techniques assume that the series studied are stable over time (stationary hypothesis). Most economic series do not verify this hypothesis, which assumes, when one wishes to study the relationships that bind them to implement specific techniques. This is cointegration which characterizes non-stationary series (integrated) with a linear combination is stationary, will also be presented in this paper. Since the work of Johansen, this approach is generally presented as part of a multivariate analysis and to specify long-term stable relationships while at the same time analyzing the short-term dynamics of the variables considered. In the empirical part, we have applied these concepts to study the dynamics of of the exchange rate in Tunisia, which is one of the most important economic policy of a country open to the outside. According to the results of the empirical study by the cointegration method, there is a cointegration relationship between the exchange rate and its determinants. This relationship shows that the variables have a significant influence in determining the exchange rate in Tunisia.

Keywords: stationarity, cointegration, dynamic models, causality, VECM models

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Authors: Igor Jerkovic

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Owing to the attractive sensory properties and low odour thresholds, norisoprenoids (degraded carotenoid-like structures with 3,5,5-trimethylcyclohex-2-enoic unit) have been identified as aroma contributors in a number of different matrices. C₁₃-Norisoprenoids have been found among volatile organic compounds of various honey types as well as C₉//C₁₀-norisoprenoids or C₁₄/C₁₅-norisoprenoids. Besides degradation of abscisic acid (which produces, e.g., dehydrovomifoliol, vomifoliol, others), the cleavage of the C(9)=C(10) bond of other carotenoid precursors directly generates nonspecific C₁₃-norisoprenoids such as trans-β-damascenone, 3-hydroxy-trans-β-damascone, 3-oxo-α-ionol, 3-oxo-α-ionone, β-ionone found in various honey types. β-Damascenone and β-ionone smelling like honey, exhibit the lowest odour threshold values of all C₁₃-norisoprenoids. The presentation is targeted on two uncommon C₁₃-norisoprenoids in the honey flavor that could be used as specific or nonspecific chemical markers of the botanical origin. Namely, after screening of different honey types, the focus was directed on Centaruea cyanus L. and Allium ursinum L. honey. The samples were extracted by headspace solid-phase microextraction (HS-SPME) and ultrasonic solvent extraction (USE) and the extracts were analysed by gas chromatography and mass spectrometry (GC-MS). SPME fiber with divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) coating was applied for the research of C. cyanus honey headspace and predominant identified compound was 3,4-dihydro-3-oxoedulan (2,5,5,8a-tetramethyl-2,3,5,6,8,8a-hexahydro-7H-chromen-7-one also known as 2,3,5,6,8,8a-hexahydro-2,5,5,8a-tetramethyl-7H-1-benzo-pyran-7-one). The oxoedulan structure contains epoxide and it is more volatile in comparison with its hydroxylated precursors. This compound has not been found in other honey types and can be considered specific for C. cyanus honey. The dichloromethane extract of A. ursinum honey contained abundant (E)-4-(r-1',t-2',c-4'-trihydroxy-3',6',6'-trimethylcyclohexyl)-but-3-en-2-one that was previously isolated as dominant substance from the ether extracts of New Zealand thyme honey. Although a wide variety of degraded carotenoid-like substances have been identified from different honey types, this appears to be rare situation where 3,4-dihydro-3-oxoedulan and (E)-4-(r-1',t-2',c-4'-trihydroxy-3',6',6'-trimethylcyclohexyl)-but-3-en-2-one have been found that is of great importance for chemical fingerprinting and identification of the chemical biomarkers that can complement the pollen analysis as the major method for the honey classification.

Keywords: 3, 4-dihydro-3-oxoedulan, (E)-4-(r-1', t-2', c-4'-trihydroxy-3', 6', 6'-trimethylcyclohexyl)-but-3-en-2-one, honey flavour, C₁₃-norisoprenoids

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Authors: Olaf Visker, Arnout De Vries, Lambert Schomaker

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Predictive policing refers to the usage of analytical techniques to identify potential criminal activity. It has been widely implemented by various police departments. Being a relatively new area of research, there are, to the author’s knowledge, no absolute tried, and true methods and they still exhibit a variety of potential problems. One of those problems is closely related to the lack of understanding of how acting on these prediction influence crime itself. The goal of law enforcement is ultimately crime reduction. As such, a policy needs to be established that best facilitates this goal. This research aims to find such a policy by using adversarial agent-based modeling in combination with modern reinforcement learning techniques. It is presented here that a baseline model for both law enforcement and criminal agents and compare their performance to their respective reinforcement models. The experiments show that our smart law enforcement model is capable of reducing crime by making more deliberate choices regarding the locations of potential criminal activity. Furthermore, it is shown that the smart criminal model presents behavior consistent with popular crime theories and outperforms the baseline model in terms of crimes committed and time to capture. It does, however, still suffer from the difficulties of capturing long term rewards and learning how to handle multiple opposing goals.

Keywords: adversarial, agent based modelling, predictive policing, reinforcement learning

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Authors: Tran Duong Nguyen, Marwan Shagar, Qinghao Zeng, Aras Maqsoodi, Pardis Pishdad, Eunhwa Yang

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Construction supply chain management (CSCM) involves the collaboration of many disciplines and actors, which generates vast amounts of data. However, inefficient, fragmented, and non-standardized data storage often hinders this data exchange. The industry has adopted building information modeling (BIM) -a digital representation of a facility's physical and functional characteristics to improve collaboration, enhance transmission security, and provide a common data exchange platform. Still, the volume and complexity of data require tailored information categorization, aligning with stakeholders' preferences and demands. To address this, artificial intelligence (AI) can be integrated to handle this data’s magnitude and complexities. This research aims to develop an integrated and efficient approach for data exchange in CSCM by utilizing AI. The paper covers five main objectives: (1) Investigate existing framework and BIM adoption; (2) Identify challenges in data exchange; (3) Propose an integrated framework; (4) Enhance data transmission security; and (5) Develop data exchange in CSCM. The proposed framework demonstrates how integrating BIM and other technologies, such as cloud computing, blockchain, and AI applications, can significantly improve the efficiency and accuracy of data exchange in CSCM.

Keywords: construction supply chain management, BIM, data exchange, artificial intelligence

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