Search results for: production and transport scheduling problem

Authors: Swapna Guntupalli, Leela Madhuri Chalasani, Kshatri Jyothi, C. V. Rao, Bondili J. S.

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The study hypothesizes that enhanced biodegradation of Polycyclic Aromatic Hydrocarbons (PAHs) is achievable with an assemblage of microorganisms that are capable of producing biofilm and biosurfactants. Accordingly, PAHs degrading microorganism’s (bacteria, fungi, actinomycetes and yeast) were screened and grouped into different consortia based on their capabilities to produce biofilm and biosurfactants. Among these, Consortium BTSN09 consisting of bacterial fungal cocultures showed highest degradation due to the synergistic action between them. Degradation effiencies were evaluated using HPLC and GC-MS. Within 7days, BTSN09 showed 51% and 50.7% degradation of Phenanthrene (PHE) and Pyrene (PYR) with 200mg/L and 100 mg/L concentrations respectively in a liquid medium. In addition, several degradative enzymes like laccases, 1hydroxy-2-naphthoicacid dioxygenase, 2-carboxybenzaldehyde dehydrogenase, catechol1,2 dioxygenase and catechol2,3 dioxygenase activity was observed during degradation. Degradation metabolites were identified using GC-MS analysis and from the results it was confirmed that the metabolism of degradation proceeds via pthalic acid pathway for both PAHs. Besides, Microbial consortia also demonstrated good biosurfactant production capacity, achieving maximum oil displacement area and emulsification activity of 19.62 cm2, 65.5% in presence of PAHs as sole carbon source. Scanning Electron Microscopy analysis revealed exopolysaccharides (EPS) production, micro and macrocolonies formation with different stages of biofim development in presence of PAHs during degradation.

Keywords: PAHs, biosurfactant, biofilm, biodegradation

Procedia PDF Downloads 577

Authors: N. Boussouf, M. F. Mosbah, M.Hamel, S. Menassel

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SiO2 particles were inserted (added) into Bi2Sr2CaCu2O8+d precursor powders in various weight fractions. The influence of Si addition to the Bi2212 system on its phase formation, microstructure and transport properties is investigated. Samples are characterized by means of X ray diffraction analysis (XRD), scanning electron microscopy (SEM/EDX), magnetic AC susceptibility and resistivity measurements. For 1% of added Si, the results showed an increase of the apparent superconducting volume fraction. All the samples doped with Si contained a majority fraction of the high TC superconducting Bi2212 phase. SEM observation showed that the average grain size of the Si added samples increased more than that of the sample without Si. From resistivity measurement the Tconset was found to be increased by 7 K for 1% and 5% of added Si compared to the pure sample.

Keywords: superconductors, Bi2212, doping, SiO2 particles

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Michael Graz, Andrew Shearer, Gareth Evans

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Manipulation of rumen bacteria is receiving increasing attention as a way of controlling greenhouse gas (GHG) emissions that are generated by the agricultural sector. Feed supplementation in particular is one of the ways in which this drive is being addressed, in particular with reference to livestock-generated GHG emissions. A blend of naturally occurring chemical extracts obtained from garlic and bitter orange extracts has been identified as a natural, sustainable and non-antibiotic based way of reducing methane production by ruminant livestock. In the current study, the acceptability and impact of this blend of natural extracts on feed rations of beef cattle was trialed in vivo on a commercial farm in Europe. Initial findings have demonstrated acceptable palatability, with all animals accepting the feed supplement into their ration both when it was mixed into the total daily ration and when used as a part of their high energy rations. Measurement of the impact of this feed supplement on productivity weight gain and milk quality is ongoing. In conclusion, this field study confirmed the palatability of the combination of garlic and citrus extracts and hence pointed to possibility of the extract blend to improve digestion, enhance body energy retention and limit CH4 formation in relation to feed intake.

Keywords: citrus, garlic, methane reduction, palatability, ruminants

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Authors: Natarajan Vijayarangan, Viswanath Kumar Ganesan, G. Kumudhavalli

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This abstract figures out an uncertainty problem pertaining to evaluating business proposals or concept notes in an organisation. Let us consider business proposal evaluation process (BPEP) for execution of corporate research cum business projects in the organisation. Assume that two concept notes X and Y of BPEP are approved: one of them is a full-fledged type (100% financial approval given by the organisation) - X and other one is a conditional type (a partial financial approval given by the organisation) - Y. Then a penalty criteria has been introduced during the process. At the end of annual appraisal, if both of them complete as per the goals and objectives committed or figured out at the time of concept note submission, then both will get an incentive of $N from the organisation. If one of them doesn't fulfill the goals and objectives at the year-end appraisal, then d% reduction or cut will be levied on the project budget for the next year. If X fulfills the goals and objectives and Y doesn't , then X gets a gain of d% on Y's previous year budget and Y gets a loss of d% from the previous year budget for the next year. And vice-versa. Further, an incentive of $N will be given to those who gains. This process is a part of Necktie paradox and inherits an uncertainty principle on X or Y getting more than $N even if X or Y performs well.Solving the above problem and generalizing on finitely many concept notes will be a challenging task.

Keywords: concept notes, necktie paradox, annual appraisal, project budget and gain or loss

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Authors: Mozhdeh Khalili Kordabadi

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. By adopting these strategies, the textile industry can contribute to a more sustainable and environmentally friendly future. Introduction: Textiles, particularly clothing, are essential to human existence. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion: The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension.

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Authors: Juan Sebastian Huertas Piedrahita, Jaime Arturo Lopez Duque, Eduardo Luis Perez Londoño, Julián S. Rodríguez

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The process of generating computer vision is called artificial vision. The artificial vision is a branch of artificial intelligence that allows the obtaining, processing, and analysis of any type of information especially the ones obtained through digital images. Actually the artificial vision is used in manufacturing areas for quality control and production, as these processes can be realized through counting algorithms, positioning, and recognition of objects that can be measured by a single camera (or more). On the other hand, the companies use assembly lines formed by conveyor systems with actuators on them for moving pieces from one location to another in their production. These devices must be previously programmed for their good performance and must have a programmed logic routine. Nowadays the production is the main target of every industry, quality, and the fast elaboration of the different stages and processes in the chain of production of any product or service being offered. The principal base of this project is to program a computer that recognizes geometric figures (circle, square, and triangle) through a camera, each one with a different color and link it with a group of conveyor systems to organize the mentioned figures in cubicles, which differ from one another also by having different colors. This project bases on artificial vision, therefore the methodology needed to develop this project must be strict, this one is detailed below: 1. Methodology: 1.1 The software used in this project is QT Creator which is linked with Open CV libraries. Together, these tools perform to realize the respective program to identify colors and forms directly from the camera to the computer. 1.2 Imagery acquisition: To start using the libraries of Open CV is necessary to acquire images, which can be captured by a computer’s web camera or a different specialized camera. 1.3 The recognition of RGB colors is realized by code, crossing the matrices of the captured images and comparing pixels, identifying the primary colors which are red, green, and blue. 1.4 To detect forms it is necessary to realize the segmentation of the images, so the first step is converting the image from RGB to grayscale, to work with the dark tones of the image, then the image is binarized which means having the figure of the image in a white tone with a black background. Finally, we find the contours of the figure in the image to detect the quantity of edges to identify which figure it is. 1.5 After the color and figure have been identified, the program links with the conveyor systems, which through the actuators will classify the figures in their respective cubicles. Conclusions: The Open CV library is a useful tool for projects in which an interface between a computer and the environment is required since the camera obtains external characteristics and realizes any process. With the program for this project any type of assembly line can be optimized because images from the environment can be obtained and the process would be more accurate.

Keywords: artificial intelligence, artificial vision, binarized, grayscale, images, RGB

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Authors: Muhammad Younis Laghari

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Microbial communities play the most important role in aquatic ecosystems. These microbes have a great role in fish growth and aquaculture production. Unfortunately, the farmers are unaware of these useful creatures. Nowadays, the trend of fish farming is developed to re-circulatory aquaculture system (RAS) to increase production and reduce the investment/management cost to increase the profit. However, sometimes, it has been observed that even the growth of fish is decreased in RAS without apparent changes in water quality. There is a great importance of microorganisms in aquaculture, where they occur naturally. However, they can be added artificially by applying different roles. Even these microbes play an important role in the degradation of organic matter and recycling nutrients, along with nutritional support to fish. Even some microorganisms may protect fish and larvae against diseases. But if not managed/utilized properly, they may cause to infect or kill the fish and their larvae. However, manipulating the microbes and monitoring them in aquaculture systems hold great potential to assess and improve the water quality as well as to control the development of microbial infections. While there is an utmost need for research to determine the microbiomes of healthy aquaculture systems, we also need to develop authentic methods for the successful manipulation of microbes as well as engineer these microbiomes. Hence, we should develop a plan to utilize and get full advantage from these microbial interactions for the successful management of aquaculture through advanced research and technology.

Keywords: aquaculture, ecology system, degradation, microbes, nutrient recycling, water quality

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Authors: Sumit Kumar Vishawakarma, Tapas Ranjan Panihari

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The article investigates the propagation behavior of SV-wave, SH-wave, and P-wave in a continuously inhomogeneous cross-anisotropic material, where the material properties such as Young's moduli, shear modulus, and density vary as an arbitrary continuous function of depth. In the considered model, Hook's law, strain-displacement relations along with equilibrium equations have been used to derive the governing equation. The mathematical formulation of this physical problem gives rise to an eigenvalue problem with displacement components as fundamental variables. This leads to achieving the closed-form expressions for quasi-wave velocities of SV-wave, SH-wave, and P-wave in the considered framework. These characteristics of wave propagation along with the above-stated variation have been scrutinized based on their numerical results. This parametric study reveals that wave velocity remarkably fluctuates as the magnitude of inhomogeneity parameters increases and decreases. The prominent effect has been shown depicting the dependence of wave velocity on the degree of material anisotropy. The influence of phase angle and depth of the medium has been remarkably established. The present study may facilitate the theoretical foundation and practical application in the field of earthquake source mechanisms.

Keywords: cross-anisotropic, inhomogeneity, P-wave, SH-wave, SV-wave, shear modulus, Young’s modulus

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Authors: Reinhard Haas, Amela Ajanovic

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In recent years especially electricity generation from intermittent sources like wind and solar has increased remarkably. To balance electricity supply over time calls for storages has been launched. Because intermittency also exists over longer periods – months, years, especially the need for long-term electricity storages is discussed. The major conclusions of our analysis are: (i) Despite many calls for a prophylactic construction of new storage capacities with respect to all centralized long-term storage technologies the future perspectives will be much less promising than currently indicated in several papers and discussions; (ii) new long term hydro storages will not become economically attractive in general in the next decades; however, daily storages will remain the cheapest option and the most likely to be competitive; (iii) For PtG-technologies it will also become very hard to compete in the electricity markets despite a high technological learning potential. Yet, for hydrogen and methane there are prospects for use in the transport sector.

Keywords: storages, electricity markets, power-to-gas, hydro pump storages, economics

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Authors: Jaroslav Masek, Juraj Camaj, Eva Nedeliakova

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The aim of optimization of store management is not only designing the situation of store management itself including its equipment, technology and operation. In optimization of store management we need to consider also synchronizing of technological, transport, store and service operations throughout the whole process of logistic chain in such a way that a natural flow of material from provider to consumer will be achieved the shortest possible way, in the shortest possible time in requested quality and quantity and with minimum costs. The paper deals with the application of the queuing theory for optimization of warehouse processes. The first part refers to common information about the problematic of warehousing and using mathematical methods for logistics chains optimization. The second part refers to preparing a model of a warehouse within queuing theory. The conclusion of the paper includes two examples of using queuing theory in praxis.

Keywords: queuing theory, logistics system, mathematical methods, warehouse optimization

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Authors: Orhun Aydin, Mark V. Janikas, Rodrigo Alves, Renato Assuncao

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In this paper, a tree-based perturbation methodology for regionalization inference is presented. Regionalization is a constrained optimization problem that aims to create groups with similar attributes while satisfying spatial contiguity constraints. Similar to any constrained optimization problem, the spatial constraint may hinder convergence to some global minima, resulting in spatially contiguous members of a group with dissimilar attributes. This paper presents a general methodology for rigorously perturbing spatial constraints through the use of random spanning trees. The general framework presented can be used to quantify the effect of the spatial constraints in the overall regionalization result. We compare several types of stochastic spanning trees used in inference problems such as fuzzy regionalization and determining the number of regions. Performance of stochastic spanning trees is juxtaposed against the traditional permutation-based hypothesis testing frequently used in spatial statistics. Inference results for fuzzy regionalization and determining the number of regions is presented on the Local Area Personal Incomes for Texas Counties provided by the Bureau of Economic Analysis.

Keywords: regionalization, constrained clustering, probabilistic inference, fuzzy clustering

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Authors: Gökhan Polat, Dicle Kocaoğlu Yılmazer, Muhlis Nezihi Sarıdede

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Iron oxides are the main input to produce iron in integrated iron and steel plants. During production of iron from iron oxides, some wastes with high iron content occur. These main wastes can be classified as basic oxygen furnace (BOF) sludge, flue dust and rolling scale. Recycling of these wastes has a great importance for both environmental effects and reduction of production costs. In this study, recycling experiments were performed on basic oxygen furnace sludge, flue dust and rolling scale which contain 53.8%, 54.3% and 70.2% iron respectively. These wastes were mixed together with coke as reducer and these mixtures are pressed to obtain cylindrical briquettes. These briquettes were pressed under various compacting forces from 1 ton to 6 tons. Also, both stoichiometric and twice the stoichiometric cokes were added to investigate effect of coke amount on reduction properties of the waste mixtures. Then, these briquettes were reduced at 1000°C and 1100°C during 30, 60, 90, 120 and 150 min in a muffle furnace. According to the results of reduction experiments, the effect of compacting force, temperature and time on reduction ratio of the wastes were determined. It is found that 1 ton compacting force, 150 min reduction time and 1100°C are the optimum conditions to obtain reduction ratio higher than 75%.

Keywords: Coke, iron oxide wastes, recycling, reduction

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Authors: Soni T. L.

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Sustainable environmental stress is a major concern which needs immediate attention. This paper is an attempt to present participatory action research for sustainable agriculture. Being first and best culture, agriculture protects and improves the natural environment, the social and economic conditions of people, and safeguards the health and welfare of all groups. During course of time agriculture turned to agribusiness, then the values are not safeguarded. Moreover, in today’s busy life many are not taking efforts to take part in agriculture production. Then children are not getting the opportunity to understand agriculture and farming practices. So student initiatives are vital to make them aware. Here the programmes structured by the researcher come under the auspicious of National Service Scheme, a student-centered educational programme, organized by Ministry of Youth Affairs, Government of India. The twin objectives of the study are to examine the role of student initiatives for sustainable agriculture and the role of participatory action research in student initiatives. SWOT analysis is made to study strengths, weaknesses, threats and opportunities. The Methodology adopted is Participatory Action Research. The method is participatory in a sense there is collaboration through participation. The method is action, there is lab land experiences which is real. The method is research that there is documented lessons and creation of new knowledge. Plan of action cover measures adopted and strategies taken i.e., bhavana – kalpana – yojana – sadhana. Through the team effort, the team was successful in converting more than 10 hectares of barren land into cultivable land within and outside the campus. Team efforts of students saved a huge amount of labour cost and produced a huge quantity of organic output and the team was also successful in creating 1000 rain pits in the premises of College for rainwater harvesting. The findings include conveyance of the Message: Food Production is superior to Food donation. Moreover, the study fostered good work ethic and social responsibility among students. Students undertake innovative programmes underlying social and environmental issues and participants got increased opportunities to interact with local and less privileged and acquired increased awareness about real-life experiences which make them confident to interact with people and it resulted in the strengthening of social capital- cooperation, team spirit, social commitment among students. Participants promoted sustainable domestic efforts and ultimately environmental protection is ensured. Finally, there is recognition to the team, institution and the researcher at the university level, state level and at the national level. The learned lessons are, if the approach is good, the response is good and success generates success. Participatory action research is empowering experience for practitioners, focusing the combined time, energy and creativity of a committed group we should lead so many programmes which makes the institution centre of excellence. Authorities should take necessary steps for the Inclusion of community development activities in the curriculum. Action research is problem, client and action centered. So, we must adapt and adopt, coordinates and correlates measures which preserve and conserve the environment.

Keywords: participatory action research, student initiatives, sustainable development, sustainability

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Authors: Marcin Zielinski, Marcin Debowski, Paulina Rusanowska, Magda Dudek

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As a result of sonification, the destruction of complex biomass structures results in an increase in the biogas yield from the conditioned material. First, the amount of organic matter released into the solution due to disintegration was determined. This parameter was determined by changes in the carbon content in liquid phase of the conditioned substrate. The amount of carbon in the liquid phase increased with the prolongation of the sonication time to 16 min. Further increase in the duration of sonication did not cause a statistically significant increase in the amount of organic carbon in the liquid phase. The disintegrated material was then used for respirometric measurements for determination of the impact of the conditioning process used on methane fermentation effectiveness. The relationship between the amount of energy introduced into the lignocellulosic substrate and the amount of biogas produced has been demonstrated. Statistically significant increase in the amount of biogas was observed until sonication of 16 min. Further increase in energy in the conditioning process did not significantly increase the production of biogas from the treated substrate. The biogas production from the conditioned substrate was 17% higher than from the reference biomass at that time. The ultrasonic disintegration method did not significantly affect the observed biogas composition. In all series, the methane content in the produced biogas from the conditioned substrate was similar to that obtained with the raw substrate sample (51.1%). Another method of substrate conditioning was hydrothermal depolymerization. This method consists in application of increased temperature and pressure to substrate. These phenomena destroy the structure of the processed material, the release of organic compounds to the solution, which should lead to increase the amount of produced biogas from such treated biomass. The hydrothermal depolymerization was conducted using an innovative microwave heating method. Control measurements were performed using conventional heating. The obtained results indicate the relationship between depolymerization temperature and the amount of biogas. Statistically significant value of the biogas production coefficients increased as the depolymerization temperature increased to 150°C. Further raising the depolymerization temperature to 180°C did not significantly increase the amount of produced biogas in the respirometric tests. As a result of the hydrothermal depolymerization obtained using microwave at 150°C for 20 min, the rate of biogas production from the Sida silage was 780 L/kg VS, which accounted for nearly 50% increase compared to 370 L/kg VS obtained from the same silage but not depolymerised. The study showed that by microwave heating it is possible to effectively depolymerized substrate. Significant differences occurred especially in the temperature range of 130-150ºC. The pre-treatment of Sida hermaphrodita silage (biogas substrate) did not significantly affect the quality of the biogas produced. The methane concentration was about 51.5% on average. The study was carried out in the framework of the project under program BIOSTRATEG funded by the National Centre for Research and Development No. 1/270745/2/NCBR/2015 'Dietary, power, and economic potential of Sida hermaphrodita cultivation on fallow land'.

Keywords: disintegration, biogas, methane fermentation, Virginia fanpetals, biomass

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Authors: O. R. Obalowu, F. B. Akande, T. P Abegunrin

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Maize (Zea may) is mostly grown and consumed by Nigeria farmers using different tillage practices which have a great effect on its growth and yield. In order to maximize output, there is need to recommend a suitable tillage practice for crop production which will increase the growth and yield of maize. This study investigated the effect of tillage practices and planting pattern on the growth and yield of maize. The experiment was arranged in a 4x3x3 Randomized Complete Block Design (RCBD) layout, with four tillage practices consisting of no-tillage (NT), disc ploughing only (Ponly), disc ploughing followed by harrowing (PH), and disc ploughing, harrowing then ridging (PHR). Three planting patterns which include; 65 x 75, 75 x 75 and 85 x 75 cm spacing within and between the rows respectively, were randomly applied on the plots. All treatments were replicated three times. Data which consist of plant height, stem girth, leaf area and weight of maize per plots were taken and recorded. Data gathered were analyzed using Analysis of Variance (ANOVA) in the Minitab Software Package. The result shows that PHR under the third planting pattern has the highest growth rate (216.50 cm) while NT under the first planting pattern has the lowest mean value of growth rate (115.60 cm). Also, Ponly under the first planting pattern gives a better maize yield (19.45 kg) when compared with other tillage practices while NT under first planting pattern recorded the least yield of maize (9.40 kg). In conclusion, considering soil and weather conditions of the research area, plough only under the first planting pattern (65 x 75 cm) is the best alternative for the production of the Swan maize variety.

Keywords: tillage practice, planting pattern, disc ploughing, harrowing, ridging

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Authors: Muhammad Azmain Abdullah, Ar Rashedul, Mohammad Ali

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This paper scrutinizes the influences of turbulence on heat transport rate, Nusselt number. The subject matter of this investigation also deals with the improvement of heat transfer efficiency of the swirl flow obtained by rotating a twisted tape in a circular pipe. The conditions to be fulfilled to observe the impact of Reynolds number and rotational speed of twisted tape are: a uniform temperature on the outer surface of the pipe, the magnitude of velocity of water varying from 0.1 m/s to 0.7 m/s in order to alter Reynolds number and a rotational speed of 200 rpm to 600 rpm. The gyration of twisted tape increase by 17%. It is also observed that heat transfer is exactly proportional to inlet gauge pressure and reciprocally proportional to increase of twist ratio.

Keywords: swirl flow, twisted tape, twist ratio, heat transfer

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Authors: Daneal Rorke, Gueguim Kana

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The shift towards renewable energy sources for biofuel production has received increasing attention. However, the use and pre-treatment of lignocellulosic material are inundated with the generation of fermentation inhibitors which severely impact the feasibility of bioprocesses. This study reports the profiling of all volatile compounds generated during microwave assisted chemical pre-treatment of sorghum leaves. Furthermore, the optimization of reducing sugar (RS) from microwave assisted acid pre-treatment of sorghum leaves was assessed and gave a coefficient of determination (R2) of 0.76, producing an optimal RS yield of 2.74 g FS/g substrate. The development of an intelligent model to predict volatile compound fractions gave R2 values of up to 0.93 for 21 volatile compounds. Sensitivity analysis revealed that furfural and phenol exhibited high sensitivity to acid concentration, alkali concentration and S:L ratio, while phenol showed high sensitivity to microwave duration and intensity as well. These findings illustrate the potential of using an intelligent model to predict the volatile compound fraction profile of compounds generated during pre-treatment of sorghum leaves in order to establish a more robust and efficient pre-treatment regime for biofuel production.

Keywords: artificial neural networks, fermentation inhibitors, lignocellulosic pre-treatment, sorghum leaves

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Authors: Rashid S. Mohammad, Shicheng Zhang, Sun Lu, Syed Jamal-Ud-Din, Xinzhe Zhao

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A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO₂ injection process in unconventional tight reservoir. Cyclic CO₂ injection is an enhanced oil recovery process consisting of injection, shut-in, and production. The study of cyclic CO₂ injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid, and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO₂ injection process to distinguish the parameters with maximum effect on the oil recovery and to comprehend the behavior of cyclic CO₂ injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issues in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, solubility of CO₂ in the aquifer is one of the safest and permanent trapping techniques when considering CO₂ storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO₂ enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters which dominate the process. The main objective of this study is to improve techniques for designing cyclic CO₂ injection process while considering the effects of asphaltene deposition and solubility of CO₂ in the brine in order to prevent asphaltene precipitation, minimize CO₂ emission, optimize cyclic CO₂ injection, and maximize oil production.

Keywords: tight reservoirs, cyclic O₂ injection, asphaltene, solubility, reservoir simulation

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Aderemi, Moses Aderibigbe

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The supply chain of a manufacturing company can be classified into three categories, namely: 1) supplier chain, these are a network of suppliers of raw materials, machinery, and other requirements for daily operations for the company; 2) internal chain, which are departmental or functional relationships within the organization like production, finance, marketing, logistic and quality control departments all interacting together to achieve the goals and objective of the company; and 3) customer chain; these are networks used for products distribution to the final consumer which includes the product distributors and retailers in the marketplace as may be applicable. In a developing country like Nigeria, where government infrastructures are poor or, in some cases, none in existence, the survival of a small-scale manufacturing company often depends on how effectively its supply chain is managed. In Nigeria, suppliers of machinery and raw materials to most manufacturing companies are from low-cost but high-tech countries like China or India. The problem with the supply chain from these countries apart from the language barrier between these countries and Nigeria, is also that of product quality and after-sales support services. The internal chain also requires funding to employ an experienced and trained workforce to deliver the company’s goals and objectives effectively and efficiently, which is always a challenge for small-scale manufacturers, including product marketing. In Nigeria, the management of the supply chain by small-scale manufacturers is further complicated by unfavourable government policies. This empirical research is a review and analysis of the supply chain management of a small-scale manufacturing company located in Lagos, Nigeria. The company's performance for the past five years has been on the decline and company management thinks there is a need for a review of its supply chain management for business survival. The company’s supply chain is analyzed and compared with best global practices in this research, and recommendations are made to the company management. The research outcome justifies the company’s need for a strategic change in its supply chain management for business sustainability and provides a learning point to small-scale manufacturing companies from developing countries in Africa

Keywords: management, small scale, supply chain, companies, leaders

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Authors: Zhanna Dedovets

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Fostering a mathematical style of thinking is crucial for cultivating intellectual personalities capable of thriving in modern society. Intuitive thinking stands as a cornerstone among the components of mathematical cognition, playing a pivotal role in grasping mathematical truths across various disciplines. This article delves into the exploration of leveraging search activities rooted in students' intuitive thinking, particularly when tackling geometric problems. Emphasizing both student engagement with the task and their active involvement in the search process, the study underscores the importance of heuristic procedures and the freedom for students to chart their own problem-solving paths. Spanning several years (2019-2023) at the Physics and Mathematics Lyceum of Dushanbe, the research engaged 17 teachers and 78 high school students. After assessing the initial levels of intuitive thinking in both control and experimental groups, the experimental group underwent training following the authors' methodology. Subsequent analysis revealed a significant advancement in thinking levels among the experimental group students. The methodological approaches and teaching materials developed through this process offer valuable resources for mathematics educators seeking to enhance their students' learning experiences effectively.

Keywords: teaching of mathematics, intuitive thinking, heuristic procedures, geometric problem, students.

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Authors: Sajjad Ahmed

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Since September 2001, the Federally Administered Tribal Areas (FATA) have become a hotbed of Talibanization. The eruption of Talibanization has caused a catastrophic human and socio-economic cost on Pakistan ever since. The vast majority of extant studies have tended to focus on assessing the current disparaging and destructive condition of FATA as a product of the notorious 'Global War on Terrorism' and its consequences in the form of the Afghan war and the rising socio-political unrest in the region. This, however, is not the case. This study argues that the Talibanization has not happened overnight, the magma of current militant volcanic outburst has been stockpiled since the inception of Pakistan in 1947. The study claims that the Talibanization is the expression of the conflict between the privileged and the underprivileged. The prevailing situation in FATA warrants an in-depth analysis of the problem. By using a qualitative and quantitative research principle, this paper attempts to critically examine 'How is Talibanization in Pakistan connected with the political, social, and economic conditions in FATA?' The critical analyses of this study would assist to policymakers in order to formulate all-encompassing anti-radicalization policies to effectively root out Talibanization in FATA. This research intends to explore the undiscovered root causes of the problem and to suggest remedial measures.

Keywords: exclusion, FATA (Federally Administrated Tribal Areas), inequalities, marginalization, Pakistan, socio-economic, talibanization

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Authors: W. S. Li, S. T. Yang, H. C. Cheng

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The power conversion efficiency (PCE) of the perovskite solar cells has been achieved by inserting vertically-aligned ZnO nanowires (NWs) between the cathode and the active layer and shows better solar cells performance. Perovskite solar cells have drawn significant attention due to the superb efficiency and low-cost fabrication process. In this experiment, ZnO nanowires are used as the electron transport layer (ETL) due to its low temperature process. The main idea of this thesis is utilizing the 3D structures of the hydrothermally-grown ZnO nanowires to increase the junction area to improve the photovoltaic performance of the perovskite solar cells. The infiltration and the surface coverage of the perovskite precursor solution changed as tuning the length of the ZnO nanowires. It is revealed that the devices with ZnO nanowires of 150 nm demonstrated the best PCE of 8.46 % under the AM 1.5G illumination (100 mW/cm2).

Keywords: hydrothermally-grown ZnO nanowires, perovskite solar cells, low temperature process, pinholes

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Authors: Michal Urzynicok, Krzysztof Kwiecinski

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The development of materials used in the power generation industry for the production of boilers and their parts is characterized by high steam parameters, which present new challenges. Implementation of new combinations of alloying elements that lead to the best possible mechanical properties, including creep resistance, greatly affects new steels' weldability. All new grades have to undergo many different examinations, in regards to bending and welding, in order to enable the development of fabrication technologies, ensuring failure-free production and assembly of boiler components. 12% Cr martensitic steels like THOR™ 115 or VM-12 SHC are characterized by high oxidation resistance in high-temperature environments. At the moment, VM-12 SHC can be found in many boilers where both headers and superheater coils were produced. As this material is very difficult to obtain, a search for a proper replacement has begun. A new creep strength-enhanced ferritic steel for service in supercritical and ultra-supercritical boiler applications was developed by Tenaris in Italy and it is designated as Thor™115 (Tenaris High Oxidation Resistance). As high demand in power plants occurred to replace some parts of existing installations fabricated from VM12-SHC with other alternatives, a new development of welding procedures has begun to prepare fabricators for the challenges of joining old components with new THOR™ 115 material. This paper covers the first research of welding of dissimilar joints made out of VM12-SHC and THOR™ 115.

Keywords: thor, vm12, dissimilar welding, weldability

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Authors: Moin Uddin, M. Masroor A. Khan, Faisal Rasheed, Tariq Ahmad Dar, Akbar Ali, Lalit Varshney

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Oligomers, obtained by exposing the natural polysaccharides (alginate, carrageenan, chitosan, etc.) to cobalt-60 generated gamma radiation may prove as potent plant growth promoters when applied as foliar sprays to the plants. They function as endogenous growth elicitors, triggering the synthesis of different enzymes and modulating various plant responses by exploiting the gene expression. Exogenous application of Jasmonic acid or of its methyl ester, methyl jasmonate (MeJ) has been reported to increase the secondary metabolites production in medicinal and aromatic plants. Keeping this in mind, three pot experiments were conducted to test whether the foliar application of irradiated-chitosan (IC) and MeJ, applied alone or in combination, could augment the active constituents as well as growth, physiological and yield attributes of Catharanthus roseus, which carries anticancer alkaloids, viz. vincristine and vinblastine, in its leaves in addition to various other useful alkaloids. Totally, 5 spray treatments, comprising various aqueous solutions of IC [20, 40, 80 and 160 mg L-1 (Experiment 1)], MeJ (10, 20, 30 and 40 mg L-1 (Experiment 2)] and those of IC+MeJ [40+20, 40+30, 80+20, 80+30, 160+20 and 160+30 mg L-1 (Experiment 3)], were applied at seven days interval. Total leaf-alkaloids content as well as growth, physiological and yield parameters, evaluated at 120 days after sowing, were significantly enhanced by IC application. IC application could not increase the leaf-content of vincristine and vinblastine; nonetheless, it significantly augmented the yield of these alkaloids owing to enhancing the dry mass of leaves per plant. MeJ application, particularly at 30 mg L-1, increased both content (17%) and yield (48%) of total leaf-alkaloids as well as the content and yield of vincristine ( 29 and 63%, respectively) and vinblastine (14 and 44%, respectively) alkaloids, though it significantly decreased most other parameters studied, particularly at higher concentrations (30 and 40 mg L-1 of MeJ). As compared to the control (water-spray treatment), collective application of IC (80 mg L-1) and MeJ (20 mg L-1) resulted in the highest values of most of the parameters studied. However, 80 mg L-1 of IC applied with 30 mg L-1 of MeJ gave the best results for the content and yield of total as well as anticancer leaf-alkaloids (vincristine and vinblastine). Comparing the control, it increased the content and yield of total leaf-alkaloids (37 and 118%, respectively) and those of vincristine (65 and 163%, respectively) and vinblastine (31 and 107%, respectively). Conclusively, the applied technique significantly enhanced the production of total as well as anticancer alkaloids of Catharanthus roseus.

Keywords: anticancer alkaloids (vincristine and vinblastine), catharanthus roseus, irradiated chitosan, methyl jasmonate

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Authors: Raja Asad Zaheer, Aisha Tanveer, Hafza Mehreen Fatima

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Global Software Development (GSD) is becoming a common norm in software industry, despite of the fact that global distribution of the teams presents special issues for effective communication and coordination of the teams. Now trends are changing and project management for distributed teams is no longer in a limbo. GSD can be effectively established using agile and project managers can use different agile techniques/tools for solving the problems associated with distributed teams. Agile methodologies like scrum and XP have been successfully used with distributed teams. We have employed exploratory research method to analyze different recent studies related to challenges of GSD and their proposed solutions. In our study, we had deep insight in six commonly faced challenges: communication and coordination, temporal differences, cultural differences, knowledge sharing/group awareness, speed and communication tools. We have established that each of these challenges cannot be neglected for distributed teams of any kind. They are interlinked and as an aggregated whole can cause the failure of projects. In this paper we have focused on creating a scalable framework for detecting and overcoming these commonly faced challenges. In the proposed solution, our objective is to suggest agile techniques/tools relevant to a particular problem faced by the organizations related to the management of distributed teams. We focused mainly on scrum and XP techniques/tools because they are widely accepted and used in the industry. Our solution identifies the problem and suggests an appropriate technique/tool to help solve the problem based on globally shared knowledgebase. We can establish a cause and effect relationship using a fishbone diagram based on the inputs provided for issues commonly faced by organizations. Based on the identified cause, suitable tool is suggested, our framework suggests a suitable tool. Hence, a scalable, extensible, self-learning, intelligent framework proposed will help implement and assess GSD to achieve maximum out of it. Globally shared knowledgebase will help new organizations to easily adapt best practices set forth by the practicing organizations.

Keywords: agile project management, agile tools/techniques, distributed teams, global software development

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Authors: Min-Woo Kim, Ok-Kyun Na, Jun-Ho Byun, Jong-Hwan Park, Seung-Hwa Yang, Joon-Hong Park, Young-Chul Park

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This study is focused on the comparative analysis and improvement to grasp the flow characteristic of the Anti-Splash Device located under the P/V Valve and new concept design models using the CFD analysis and Artificial Neural Network. The P/V valve located upper deck to solve the pressure rising and vacuum condition of inner tank of the liquid cargo ships occurred oil outflow accident by transverse and longitudinal sloshing force. Anti-Splash Device is fitted to improve and prevent this problem in the shipbuilding industry. But the oil outflow accidents are still reported by ship owners. Thus, four types of new design model are presented by study. Then, comparative analysis is conducted with new models and existing model. Mostly the key criterion of this problem is flux in the outlet of the Anti-Splash Device. Therefore, the flow and velocity are grasped by transient analysis. And then it decided optimum model and design parameters to develop model. Later, it needs to develop an Anti-Splash Device by Flow Test to get certification and verification using experiment equipment.

Keywords: anti-splash device, P/V valve, sloshing, artificial neural network

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Authors: Diana Fajardo, Sebastián Ortiz, Oscar Herrera, Angélica Santis

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Currently, in Colombia is arising a problem related to collecting used lubricant oils which are generated by the increment of the vehicle fleet. This situation does not allow a proper disposal of this type of waste, which in turn results in a negative impact on the environment. Therefore, through the comparative analysis of various heuristics, the best solution to the VRP (Vehicle Routing Problem) was selected by comparing costs and times for the collection of used lubricant oils in the city of Pereira, Colombia; since there is no presence of management companies engaged in the direct administration of the collection of this pollutant. To achieve this aim, six proposals of through methods of solution of two phases were discussed. First, the assignment of the group of generator points of the residue was made (previously identified). Proposals one and four of through methods are based on the closeness of points. The proposals two and five are using the scanning method and the proposals three and six are considering the restriction of the capacity of collection vehicle. Subsequently, the routes were developed - in the first three proposals by the Clarke and Wright's savings algorithm and in the following proposals by the Traveling Salesman optimization mathematical model. After applying techniques, a comparative analysis of the results was performed and it was determined which of the proposals presented the most optimal values in terms of the distance, cost and travel time.

Keywords: Heuristics, optimization Model, savings algorithm, used vehicular oil, V.R.P.

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Authors: N. Boutra, N. Ravot, J. Benoit, O. Picon

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Submarine power cables used for offshore wind farms electric energy distribution and transmission are subject to numerous threats. Some of the risks are associated with transport, installation and operating in harsh marine environment. This paper describes the feasibility of an electromagnetic low frequency sensing technique for submarine power cable failure prediction. The impact of a structural damage shape and material variability on the induced electric field is evaluated. The analysis is performed by modeling the cable using the finite element method, we use sensitivity analysis in order to identify the main damage characteristics affecting electric field variation. Lastly, we discuss the results obtained.

Keywords: electromagnetism, finite element method, sensitivity analysis, submarine power cables

Procedia PDF Downloads 350