Search results for: energy modeling

Authors: Susanna Vanhamäki, Gabor Schneider, Kati Manskinen

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‘Bioeconomy’ is a complex concept that cuts across many sectors and covers several policy areas. To achieve an overall understanding and support a successful bioeconomy, a cross-sectorial approach is necessary. In practice, due to the concept’s wide scope and varying international approaches, fully understanding bioeconomy is challenging on policy level. This paper provides a background of the topic through an analysis of bioeconomy strategies in the Baltic Sea region. Expert interviews and a small survey were conducted to discover the current and intended focuses of these countries’ bioeconomy sectors. The research shows that supporting sustainability is one of the keys in developing the future bioeconomy. The results highlighted that the bioeconomy has to be sustainable and based on circular economy principles. Currently, traditional bioeconomy sectors like food, wood, fish & waters as well as fuel & energy, which are in the core of national bioeconomy strategies, are best known and are considered more relevant than other bioeconomy industries. However, there is increasing potential for novel sectors, such as textiles and pharmaceuticals. The present research indicates that the opportunities presented by these bioeconomy sectors should be recognised and promoted. Education, research and innovation can play key roles in developing transformative and sustainable improvements in primary production and renewable resources. Furthermore, cooperation between businesses and educators is important.

Keywords: bioeconomy, circular economy, policy, strategy

Procedia PDF Downloads 155

Authors: Usha N. Murthy, H. B. Rekha, Mahaveer Devoor

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The introduction of more stringent pollution regulations, in relation to financial and social pressures for sustainable development, has pressed toward limiting the volumes of industrial and domestic effluents discharged into the environment-as well as to increase the efforts within research and development of new or more efficient wastewater treatment technologies. Considering both discharge volume and effluent composition, wastewater generated by the textile industry is rated as the most polluting among all industrial sectors. The pollution load is mainly due to spent dye baths, which are composed of unreacted dyes, dispersing agents, surfactants, salts and organics. In the present investigation, the textile dye wastewater was characterized by high colour, chemical oxygen demand (COD), total dissolved solids (TDS) and pH. Electrochemical oxidation process for four plate electrodes was carried out at five different current intensities, out of which 0.14A has achieved maximum percentage removal of COD with 75% and 83% of colour. The COD removal rate in kg COD/h/m2 decreases with increase in the current intensity. The energy consumption increases with increase in the current intensity. Hence, textile dye wastewater can be effectively pre-treated by electrochemical oxidation method where the process limits objectionable colour while leaving the COD associated with organics left for natural degradation thus causing a sustainable reduction in pollution load.

Keywords: electrochemical treatment, COD, colour, environmental engineering

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Authors: Thammanoon Charmjuree, Yuosre F. Badir, Umar Safdar

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There is a consensus among innovation scholars that knowledge is a vital antecedent for firm’s innovation; e.g., process innovation. Recently, there has been an increasing amount of attention to more open approaches to innovation. This open model emphasizes the use of purposive flows of knowledge across the organization boundaries. Firms adopt open innovation strategy to improve their innovation performance by bringing knowledge into the organization (inbound open innovation) to accelerate internal innovation or transferring knowledge outside (outbound open innovation) to expand the markets for external use of innovation. Reviewing open innovation research reveals the following. First, the majority of existing studies have focused on inbound open innovation and less on outbound open innovation. Second, limited research has considered the possible interaction between both and how this interaction may impact the firm’s innovation performance. Third, scholars have focused mainly on the impact of open innovation strategy on product innovation and less on process innovation. Therefore, our knowledge of the relationship between firms’ inbound and outbound open innovation and how these two impact process innovation is still limited. This study focuses on the firm’s external technology acquisition (ETA) and external technology exploitation (ETE) and the firm’s process innovation performance. The ETA represents inbound openness in which firms rely on the acquisition and absorption of external technologies to complement their technology portfolios. The ETE, on the other hand, refers to commercializing technology assets exclusively or in addition to their internal application. This study hypothesized that both ETA and ETE have a positive relationship with process innovation performance and that ETE fully mediates the relationship between ETA and process innovation performance, i.e., ETA has a positive impact on ETE, and turn, ETE has a positive impact on process innovation performance. This study empirically explored these hypotheses in software development firms in Thailand. These firms were randomly selected from a list of Software firms registered with the Department of Business Development, Ministry of Commerce of Thailand. The questionnaires were sent to 1689 firms. After follow-ups and periodic reminders, we obtained 329 (19.48%) completed usable questionnaires. The structure question modeling (SEM) has been used to analyze the data. An analysis of the outcome of 329 firms provides support for our three hypotheses: First, the firm’s ETA has a positive impact on its process innovation performance. Second, the firm’s ETA has a positive impact its ETE. Third, the firm’s ETE fully mediates the relationship between the firm’s ETA and its process innovation performance. This study fills up the gap in open innovation literature by examining the relationship between inbound (ETA) and outbound (ETE) open innovation and suggest that in order to benefits from the promises of openness, firms must engage in both. The study went one step further by explaining the mechanism through which ETA influence process innovation performance.

Keywords: process innovation performance, external technology acquisition, external technology exploitation, open innovation

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Authors: Nicolas Giraudo, Peter Thissen

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In this paper we bring up new aspects of the metal proton exchange reaction (MPER, also called early stage hydration): (1) its dependence of the number of protons consumed by the preferential exchanged cations on the pH value applied at the water/wollastonite interface and (2) strong anisotropic characteristics detected in atomic force microscopy (AFM) and low energy ion scattering spectroscopy measurements (LEIS). First we apply density functional theory (DFT) calculations to compare the kinetics of the reaction on different wollastonite surfaces, and combine it with ab initio thermodynamics to set up a model describing (1) the release of Ca in exchange with H coming from the water/wollastonite interface, (2) the dependence of the MPER on the chemical potential of protons. In the second part of the paper we carried out in-situ AFM and inductive coupled plasma atomic emission spectroscopy (ICP-OES) measurements in order to evaluate the predicted values. While a good agreement is found in the basic and neutral regime (pH values from 14-4), an increasing mismatch appears in the acidic regime (pH value lower 4). This is finally explained by non-equilibrium etching, dominating over the MPER in the very acidic regime.

Keywords: anisotropy, calcium silicate, cement, density functional theory, hydration

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Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

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In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

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Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

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Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

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Authors: Shruti Sakarkar, Jega Jegatheesan, Srinivasan Madapusi

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Photocatalytic membranes have shown great potential for the removal of an organic and inorganic pollutant from wastewater as it combines the degradation and antibacterial properties from photocatalysis and physical separation by the membrane in a single unit. Incorporation of the semiconductor in membrane structure results in enhancing the performance and the properties of the membrane. In this study porous ultrafiltration polyvinylidene fluoride (PVDF) membranes with entrapped TiO₂ nanoparticle were prepared by phase inversion method and further used for the degradation of reactive orange 16 (RO16). Prepared photocatalytic membranes were characterized by the scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), contact angle, and atomic force microscope (AFM). The addition of TiO₂ nanopartparticles improves the strength and thermal stability of the membrane. In particular hydrophilicity and permeability increases with the increase of TiO₂ nanoparticles into the membrane. The photocatalytic membrane achieves 80-85% degrdation of RO16. The impact of different parameters such as pH, concentration of photocatalyst, dye concentration and effect of H₂O₂ were analysed. The best conditions for dye degradation were an initial dye concentration of 50 mg/L, with a membrane containing TiO₂ loading of 2wt%. It was observed that in the presence of H₂O₂, degradation increases with increasing H₂O₂ concentration and reached up to 95-98%. The high quality permeates obtained from the photocatalytic membrane can be reused.

Keywords: photocatalytic membrane, TiO₂, PVDF, nanoparticles

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Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharrazi

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When we teach, we have two critical elements at our disposal to help students: learning styles as well as testing styles. There are many different ways in which educators can effectively teach their students; verbal learning and experience-based learning. Lecture as a form of verbal learning style is a traditional arrangement in which teachers are more active and share information verbally with students. In experienced-based learning as the process of through, students learn actively through hands-on learning materials and observing teachers or others. Meanwhile, standard testing or assessment is the way to determine progress toward proficiency. Teachers and instructors mainly use essay (requires written responses), multiple choice questions (includes the correct answer and several incorrect answers as distractors), or open-ended questions (respondents answers it with own words). The current study focused on exploring an effective teaching style and testing methods as the function of age over school ages. In the present study, totally 410 participants were selected randomly from four grades (2ⁿᵈ, 4ᵗʰ, 6ᵗʰ, and 8ᵗʰ). Each subject was tested individually in one session lasting around 50 minutes. In learning tasks, the participants were presented three different instructions for learning materials (learning by doing, learning by observing, and learning by listening). Then, they were tested via different standard assessments as free recall, cued recall, and recognition tasks. The results revealed that generally students remember more of what they do and what they observe than what they hear. The age effect was more pronounced in learning by doing than in learning by observing, and learning by listening, becoming progressively stronger in the free-recall, cued-recall, and recognition tasks. The findings of this study indicated that learning by doing and free recall task is more age sensitive, suggesting that both of them are more strategic and more affected by developmental differences. Pedagogically, these results denoted that learning by modeling and engagement in program activities have the special role for learning. Moreover, the findings indicated that the multiple-choice questions can produce the best performance for school-aged children but is less age-sensitive. By contrast, the essay as essay can produce the lowest performance but is more age-sensitive. It will be very helpful for educators to know that what types of learning styles and test methods are most effective for students in each school grade.

Keywords: experience-based learning, learning style, school-aged children, testing methods, verbal learning

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Authors: Hakan Gungunes, Ismail A. Auwal, Abdulhadi Baykal, Sagar E. Shirsath

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Barium hexaferrite, BaFe₁₂O₁₉, substituted by Bi³⁺ and La³⁺ (BaBiₓLaₓFe₁₂₋₂ₓO₁₉ where 0.0 ≤ x ≤ 0.5) were prepared by solid state synthesis route. The effect of substituted Bi³⁺ and La³⁺ ions on the structure, morphology, magnetic and cation distributions of barium hexaferrite were investigated by X-ray powder diffractometry (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), Fourier transform infrared spectroscopy (FT-IR) and Mössbauer spectroscopy. XRD powder patterns were refined by the Rietveld analysis method which confirmed the formation of single phase magneto-plumbite structure and the substitution of La³⁺ and Bi³⁺ ions into the lattice of barium ferrite. These results show that both La³⁺ and Bi³⁺ ions completely enter into barium hexaferrite lattice without disturbing the hexagonal ferrite structure. The EDX spectra confirmed the presence of all the constituents in expected elemental percentage. From 57Fe Mössbauer spectroscopy data, the variation in line width, isomer shift, quadrupole splitting and hyperfine magnetic field values on Bi and La substitutions have been determined. Cation distribution in the presently investigated hexaferrite system was estimated using the relative area of Mössbauer spectroscopy.

Keywords: hexaferrite, mössbauer, cation distribution, solid state synthesis

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Authors: Dipti Yadav, Latha Rangan, Pinakeswar Mahanta

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Recent fuel-development strategies to reduce oil dependency, mitigate greenhouse gas emissions, and utilize domestic resources have generated interest in the search for alternative sources of fuel supplies. Bioenergy production from lignocellulosic biomass has a great potential. Cellulose, hemicellulose and Lignin are main constituent of woods or agrowaste. In all the industries there are always left over or waste products mainly lignin, due to the heterogeneous nature of wood and pulp fibers and the heterogeneity that exists between individual fibers, no method is currently available for the quantitative isolation of native or residual lignin without the risk of structural changes during the isolation. The potential benefits from finding alternative uses of lignin are extensive, and with a double effect. Lignin can be used to replace fossil-based raw materials in a wide range of products, from plastics to individual chemical products, activated carbon, motor fuels and carbon fibers. Furthermore, if there is a market for lignin for such value-added products, the mills will also have an additional economic incentive to take measures for higher energy efficiency. In this study residual lignin were isolated from areca nut shells by acid hydrolysis and were analyzed and characterized by Fourier Transform Infrared (FTIR), LCMS and complexity of its structure investigated by NMR.

Keywords: Areca nut, Lignin, wood, bioenergy

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Authors: Wang Haining, Zhang Hong

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In China, rapid urbanization needs more and more buildings constructed for the growing population in cities. With the help of the methodology which contains investigation, contrastive analysis, design based on component with BIM and experiment before real construction, this research based on mobile light structure system, trying to the sustainable problems partly in present China by systematic study. The system cannot replace the permanent heavy structure completely. So the goal is the improvement of the whole building system by the addition of light structure. This house system uses modularized envelopes and standardized connections, which are pre-fabricated and assembled in factories and transported like containers. Aluminum is used as the structural material in this system, and inorganic thermal insulation material used in the envelope, which have high fireproof properties. The relationship between manufactory and construction of the system is progressive hierarchy. They exist as First Industrial, Second Industrial, Third Industrial and Site Assembly Stage. It could maximize the land usage capacity by fully exploit the area where normal permanent architecture can't take advantage of. Not only the building system itself especially the thermal isolated materials used and active solar photovoltaic system equipped can save energy, but also the way of product development is sustainable.

Keywords: aluminum house, light Structure, rapid assembly, repeat construction

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Authors: Daniel Y. Abebe, Jaehyouk Choi

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Link-to-column connection in eccentrically braced frames (EBF) has been a critical problem since the link flange connected to the column fractured prior to the required link rotation. Even though the problem in link-to-column connection still exist, the use of an eccentrically braced frame (EBF) is increasing day by day as EBF have high elastic stiffness, stable inelastic response under repeated lateral loading, and excellent ductility and energy dissipation capacity. In order to address this problem, a reduced web and flange link section is proposed and evaluated in this study. Reducing the web with holes makes the link to control the failure at the edge of holes introduced. Reducing the flange allows the link to control the location at which the plastic hinge is formed. Thus, the failure supposed to occur in the link flange connected at the connection move to the web and to the reduced link flange. Nonlinear FE analysis and experimental investigations have been done on the developed links, and the result shows that the link satisfies the plastic rotation limit recommended in AICS-360-10. Design equations that define the behavior of the proposed link have been recommended, and the equations were verified through the experimental and FE analysis results.

Keywords: EBFs, earthquake disaster, link-to-column connection, reduced link section

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Authors: Wizna, Helmi Muis, Hafil Abbas

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An experiment was conducted to improve the nutrient value of sago pith (Metroxylon sago Rottb) supplemented with Zn, Sulfur and urea through fermentation by using cellulolytic bacteria (Bacillus amyloliquefaciens) as inoculums. The experiment was determination of the optimum dose combination (dosage of Zn, S and urea) for sago pith fermentation based on nutrient quality and quantity of these fermented products. The study was conducted in experimental method, using the completely randomized design in factorial with 3 treatments consist of: factor A (Dose of urea: A1 = 2.0%, A2 = 3.0%), factor B (Dose of S: B1 = 0.2%, B2 = 0.4%) and factor C (Dose of Zn: C1 = 0.0025%, C2 = 0.005%). Results of study showed that optimum condition for fermentation process of sago pith with B. amyloliquefaciens caused a change of nutrient content was obtained at urea (3%), S (0,2%), and Zn (0,0025%). This fermentation process was able to increase amino acid average, reduce crude fiber content by 67% and increase crude protein by 433%, which made the nutritional value of the product based on dry matter was 18.22% crude protein, 12.42% crude fiber, 2525 Kcal/kg metabolic energy and 65.73% nitrogen retention.

Keywords: fermentation, sago pith, sulfur, Zn, urea, Bacillus amyloliquefaciens

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Authors: M. R. Gholizadeh, N. Bhuiyan, M. Salari

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In the near future, companies will be increasingly forced to shift their activities along a new road in order to decrease the harmful effects of their design, production and after-life on our environment. Products must meet environmental standards to not only prevent penalties but to consider the sustainability for future generations. However, the most important factor that companies will face is selecting a reasonable strategy to maximize their profit. Thus, companies need to have precise forecast from their profit after design stage through Trade-off analysis. This paper is an attempt to introduce a mathematical model that considers effective factors that impact the total profit when products are designed for resource and energy efficiency or recyclability. The modification is according to different strategies based on a Cost-Volume-Profit model. Here, the cost structure consists of Recycling cost, Development cost, Ramp-up cost, Production cost, and Pollution cost. Also, the model shows the effect of implementation of design for recyclable on revenue structure through revenue of used parts and revenue of recycled materials. A numerical example is used to evaluate the proposed model. Results show that fulfillment of Green Product Development not only can reduce the environmental impact of products but also it will increase profit of company in long term.

Keywords: green product, design for environment, C-V-P model, trade-off analysis

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Authors: Abdelbary Prince, Said Moussa, Hyungkyu Kim, Eman Gouda, Jin Han

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We compared the dynamic alterations of mitochondrial proteome of control, ischemia-reperfusion (IR) and ischemic preconditioned (IPC) rabbit hearts. Using 2-DE, we identified 29 mitochondrial proteins that were differentially expressed in the IR heart compared with the control and IPC hearts. For two of the spots, the expression patterns were confirmed by Western blotting analysis. These proteins included succinate dehydrogenase complex, Acyl-CoA dehydrogenase, carnitine acetyltransferase, dihydrolipoamide dehydrogenase, Atpase, ATP synthase, dihydrolipoamide succinyltransferase, ubiquinol-cytochrome c reductase, translation elongation factor, acyl-CoA dehydrogenase, actin alpha, succinyl-CoA Ligase, dihydrolipoamide S-succinyltransferase, citrate synthase, acetyl-Coenzyme A dehydrogenase, creatine kinase, isocitrate dehydrogenase, pyruvate dehydrogenase, prohibitin, NADH dehydrogenase (ubiquinone) Fe-S protein, enoyl Coenzyme A hydratase, superoxide dismutase [Mn], and 24-kDa subunit of complex I. Interestingly, most of these proteins are associated with the mitochondrial respiratory chain, antioxidant enzyme system, and energy metabolism. The results provide clues as to the cardioprotective mechanism of ischemic preconditioning at the protein level and may serve as potential biomarkers for detection of ischemia-induced cardiac injury.

Keywords: ischemic preconditioning, mitochondria, proteome, cardioprotection

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Authors: Manju Lata Sharma

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Damage to cells caused by free radicals is believed to play a central role in the ageing process and in disease progression. Withania somnifera is widely used in ayurvedic medicine, and it is one of the ingredients in many formulations to increase energy, improve overall health and longevity and prevent disease. Withania somnifera possesses antioxidative properties. The antioxdant activity of Withania somnifera consisting of an equimolar concentration of active principles of sitoindoside VII-X and withaferin A. The antioxidant effect of Withania somnifera extract was investigated on lipid peroxidation (LPO), superoxide dismutase (SOD) and catalase (CAT) activity in mice. Aim: To study the antioxidant activity of an extract of Withania somnifera leaf against a mice model of chronic stress. Healthy swiss albino mice (3-4 months old) selected from an inbred colony were divided in to 6 groups. Biochemical estimation revealed that stress induced a significant change in SOD, LPO, CAT AND GPX. These stress induced perturbations were attenuated Withania somnifera (50 and 100 mg/kg BW). Result: Withania somnifera tended to normalize the augmented SOD and LPO activities and enhanced the activities of CAT and GPX. The result indicates that treatment with an alcoholic extract of Withania somnifera produced a significant decrease in LPO ,and an increase in both SOD and CAT in brain mice. This indicates that Withania somnifera extract possesses free radical scavenging activity .

Keywords: Withania somnifera, antioxidant, lipid peroxidation, brain

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Authors: Alexey Abilov

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The article highlights the experience of training master's and doctoral students at Satbayev University by preparing their course works for disciplines "Principles of Sustainable Architecture", "Energy Efficiency in Urban planning", "Urban planning analysis, "Social foundations of Architecture". The purpose of these works is the acquisition by students of practical skills necessary in their future professional activities, which are achieved through comprehensive assessment of individual sections of the Almaty urban environment. The methodology of student’s researches carried out under the guidance of the author of this publication is based on an expert assessment of the territory through its full-scale survey, analysis of project documents and statistical data, as well as on a social assessment of the territory based on the results of a questionnaire survey of residents. A comprehensive qualitative and quantitative assessment of the selected sites according to the criteria of the quality of the living environment also allows to formulate specific recommendations for designers who carry out a pre-project analysis of the city territory in the process of preparing draft master plans and detailed planning projects.

Keywords: urban environment, expert/social assessment of the territory, questionnaire survey, comprehensive approach

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Authors: Samvel H. Sargsyan

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Together with the study of electron-optical properties of nanostructures and proceeding from experiment-based data, the study of the mechanical properties of nanostructures has become quite actual. For the study of the mechanical properties of fullerene, carbon nanotubes, graphene and other nanostructures one of the crucial issues is the construction of their adequate mathematical models. Among all mathematical models of graphene or carbon nano-tubes, this so-called discrete-continuous model is specifically important. It substitutes the interactions between atoms by elastic beams or springs. The present paper demonstrates the construction of the discrete-continual beam model for carbon nanotubes or graphene, where the micropolar beam model based on the theory of moment elasticity is accepted. With the account of the energy balance principle, the elastic moment constants for the beam model, expressed by the physical and geometrical parameters of carbon nanotube or graphene, are determined. By switching from discrete-continual beam model to the continual, the models of micropolar elastic cylindrical shell and micropolar elastic plate are confirmed as continual models for carbon nanotube and graphene respectively.

Keywords: carbon nanotube, discrete-continual, elastic, graphene, micropolar, plate, shell

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Authors: Renata Martins Pacheco, João Claro

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Wildfires are becoming an increasing concern worldwide, causing substantial social, economic, and environmental disruptions. This situation is especially relevant in Mediterranean-climate regions, present in all the five continents of the world, in which fire is not only a natural component of the environment but also perhaps one of the most important evolutionary forces. The rise in wildfire occurrences and their associated impacts suggests the need for identifying knowledge gaps and enhancing the basis of scientific evidence on how managers and policymakers may act effectively to address them. Considering that the main goal of a systematic map is to collate and catalog a body of evidence to describe the state of knowledge for a specific topic, it is a suitable approach to be used for this purpose. In this context, the aim of this study is to systematically map the research trends in wildfire management practices in Mediterranean-climate regions. A total of 201 wildfire management studies were analyzed and systematically mapped in terms of their: Year of publication; Place of study; Scientific outlet; Research area (Web of Science) or Research field (Scopus); Wildfire phase; Central research topic; Main objective of the study; Research methods; and Main conclusions or contributions. The results indicate that there is an increasing number of studies being developed on the topic (most from the last 10 years), but more than half of them are conducted in few Mediterranean countries (60% of the analyzed studies were conducted in Spain, Portugal, Greece, Italy or France), and more than 50% are focused on pre-fire issues, such as prevention and fuel management. In contrast, only 12% of the studies focused on “Economic modeling” or “Human factors and issues,” which suggests that the triple bottom line of the sustainability argument (social, environmental, and economic) is not being fully addressed by fire management research. More than one-fourth of the studies had their objective related to testing new approaches in fire or forest management, suggesting that new knowledge is being produced on the field. Nevertheless, the results indicate that most studies (about 84%) employed quantitative research methods, and only 3% of the studies used research methods that tackled social issues or addressed expert and practitioner’s knowledge. Perhaps this lack of multidisciplinary studies is one of the factors hindering more progress from being made in terms of reducing wildfire occurrences and their impacts.

Keywords: wildfire, Mediterranean-climate regions, management, policy

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Authors: Tanushree Jaitly, Shailendra Gupta, Leila Taher, Gerold Schuler, Julio Vera

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Genomics-based personalized medicine is a promising approach to fight aggressive tumors based on patient's specific tumor mutation and expression profiles. A remarkable case is, dendritic cell-based immunotherapy, in which tumor epitopes targeting patient's specific mutations are used to design a vaccine that helps in stimulating cytotoxic T cell mediated anticancer immunity. Here we present a computational pipeline for epitope-based personalized cancer vaccines using patient-specific haplotype and cancer mutation profiles. In the workflow proposed, we analyze Whole Exome Sequencing and RNA Sequencing patient data to detect patient-specific mutations and their expression level. Epitopes including the tumor mutations are computationally predicted using patient's haplotype and filtered based on their expression level, binding affinity, and immunogenicity. We calculate binding energy for each filtered major histocompatibility complex (MHC)-peptide complex using docking studies, and use this feature to select good epitope candidates further.

Keywords: cancer immunotherapy, epitope prediction, NGS data, personalized medicine

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Authors: Sudha T., Naveen C.

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Dengue is a serious public health issue that causes significant annual economic and welfare burdens on nations. However, enhanced optimization techniques and quantitative modeling approaches can predict the incidence of dengue. By advocating for a data-driven approach, public health officials can make informed decisions, thereby improving the overall effectiveness of sudden disease outbreak control efforts. The National Oceanic and Atmospheric Administration and the Centers for Disease Control and Prevention are two of the U.S. Federal Government agencies from which this study uses environmental data. Based on environmental data that describe changes in temperature, precipitation, vegetation, and other factors known to affect dengue incidence, many predictive models are constructed that use different machine learning methods to estimate weekly dengue cases. The first step involves preparing the data, which includes handling outliers and missing values to make sure the data is prepared for subsequent processing and the creation of an accurate forecasting model. In the second phase, multiple feature selection procedures are applied using various machine learning models and optimization techniques. During the third phase of the research, machine learning models like the Huber Regressor, Support Vector Machine, Gradient Boosting Regressor (GBR), and Support Vector Regressor (SVR) are compared with several optimization techniques for feature selection, such as Harmony Search and Genetic Algorithm. In the fourth stage, the model's performance is evaluated using Mean Square Error (MSE), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) as assistance. Selecting an optimization strategy with the least number of errors, lowest price, biggest productivity, or maximum potential results is the goal. In a variety of industries, including engineering, science, management, mathematics, finance, and medicine, optimization is widely employed. An effective optimization method based on harmony search and an integrated genetic algorithm is introduced for input feature selection, and it shows an important improvement in the model's predictive accuracy. The predictive models with Huber Regressor as the foundation perform the best for optimization and also prediction.

Keywords: deep learning model, dengue fever, prediction, optimization

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Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

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This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

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Authors: Imine Zakaria, Meftah Sidi Mohamed El Amine

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One of the most vital aerodynamic organs of a flying machine is the wing, which allows it to fly in the air efficiently. The flow around the wing is very sensitive to changes in the angle of attack. Beyond a value, there is a phenomenon of the boundary layer separation on the upper surface, which causes instability and total degradation of aerodynamic performance called a stall. However, controlling flow around an airfoil has become a researcher concern in the aeronautics field. There are two techniques for controlling flow around a wing to improve its aerodynamic performance: passive and active controls. Blowing and suction are among the active techniques that control the boundary layer separation around an airfoil. Their objective is to give energy to the air particles in the boundary layer separation zones and to create vortex structures that will homogenize the velocity near the wall and allow control. Blowing and suction have long been used as flow control actuators around obstacles. In 1904 Prandtl applied a permanent blowing to a cylinder to delay the boundary layer separation. In the present study, several numerical investigations have been developed to predict a turbulent flow around an aerodynamic profile. CFD code was used for several angles of attack in order to validate the present work with that of the literature in the case of a clean profile. The variation of the lift coefficient CL with the momentum coefficient

Keywords: CFD, control flow, lift, slot

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Authors: Vikas Chawla, Buta Singh Sidhu, Amita Rani, Amit Handa

Abstract:

The main objective of the present work is microstructural and mechanical characterization of the conventional and nanostructured TiAlN and AlCrN coatings deposited on T-11 boiler steel. In case of conventional coatings, Al-Cr and Ti-Al metallic powders were deposited using plasma spray process followed by gas nitriding of the surface which was done in the lab with optimized parameters after conducting several trials on plasma-sprayed coated specimens. The physical vapor deposition process (PAPVD) was employed for depositing nanostructured TiAlN and AlCrN coatings. The field emission scanning electron microscopy (FE-SEM) with energy dispersive X-ray analysis (EDAX) attachment, X-ray diffraction (XRD) analysis, atomic force microscopy (AFM) analysis and the X-Ray mapping analysis techniques have been used to study surface and cross-sectional morphology of the coatings. The surface roughness and micro-hardness were also measured. A good adhesion of the conventional thick TiAlN and AlCrN coatings was found. The coatings under study are recommended for the applications to super-heater and re-heater tubes of the boilers based upon the outcomes of the research work.

Keywords: nanostructure, physical vapour deposition, oxides, thin films, electron microscopy

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Authors: Bashir Abubakar Abdulkadir, Anita Ramli, Lim Jun Wei, Yoshimitsu Uemura

Abstract:

In this study, the ZnO/MCM-22 catalyst with different ZnO loading were prepared using conventional wet impregnation process and the catalyst activity was tested for biodiesel production from Jatropha oil. The effects of reaction parameters with regards to catalyst activity were investigated. The synthesized catalysts samples were then characterized by X-ray diffraction (XRD) for crystal phase, Brunauer–Emmett–Teller (BET) for surface area, pore volume and pore size, Field Emission Scanning electron microscope attached to energy dispersive x-ray (FESEM/EDX) for morphology and elemental composition and TPD (NH3 and CO2) for basic and acidic properties of the catalyst. The XRD spectra couple with the EDX result shows the presence of ZnO in the catalyst confirming the positive intercalation of the metal oxide into the mesoporous MCM-22. The synthesized catalyst was confirmed to be mesoporous according to BET findings. Also, the catalysts can be considered as a bifunctional catalyst based on TPD outcomes. Transesterification results showed that the synthesized catalyst was highly efficient and effective to be used for biodiesel production from low grade oil such as Jatropha oil and other industrial application where the high fatty acid methyl ester (FAMEs) yield was achieved at moderate reaction conditions. It was also discovered that the catalyst can be used more than five (5) runs with little deactivation confirming the catalyst to be highly active and stable to the heat of reaction.

Keywords: MCM-22, synthesis, transesterification, ZnO

Procedia PDF Downloads 180

Authors: Wasi Khan, Suboohi Shervani, Swaleha Naseem, Mohd. Shoeb, J. A. Khan, B. R. Singh, A. H. Naqvi

Abstract:

We have successfully synthesized ZnO/TiO2 nanocomposite using a two-step solochemical synthesis method. The influence of annealing temperature on microstructural, optical, anticandidal, photocatalytic activities and dielectric properties were investigated. X-ray diffraction (XRD) and scanning electron microscopy (SEM) show the formation of nanocomposite and uniform surface morphology of all samples. The UV-Vis spectra indicate decrease in band gap energy with increase in annealing temperature. The anticandidal activity of ZnO/TiO2 nanocomposite was evaluated against MDR C. albicans 077. The in-vitro killing assay revealed that the ZnO/TiO2 nanocomposite efficiently inhibit the growth of the C. albicans 077. The nanocomposite also exhibited the photocatalytic activity for the degradation of methyl orange as a function of time at 465 nm wavelength. The electrical behaviour of composite has been studied over a wide range of frequencies at room temperature using complex impedance spectroscopy. The dielectric constants, dielectric loss and ac conductivity (σac) were studied as the function of frequency, which have been explained by ‘Maxwell Wagner Model’. The data reveals that the dielectric constant and loss (tanδ) exhibit the normal dielectric behavior and decreases with the increase in frequency.

Keywords: ZnO/TiO2 nanocomposites, SEM, photocatalytic activity, dielectric properties

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Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

Abstract:

In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

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Authors: C. Iraklis, G. Evmiridis, A. Iraklis

Abstract:

Renewable energy sources and distributed power generation units already have an important role in electrical power generation. A mixture of different technologies penetrating the electrical grid, adds complexity in the management of distribution networks. High penetration of distributed power generation units creates node over-voltages, huge power losses, unreliable power management, reverse power flow and congestion. This paper presents an optimization algorithm capable of reducing congestion and power losses, both described as a function of weighted sum. Two factors that describe congestion are being proposed. An upgraded selective particle swarm optimization algorithm (SPSO) is used as a solution tool focusing on the technique of network reconfiguration. The upgraded SPSO algorithm is achieved with the addition of a heuristic algorithm specializing in reduction of power losses, with several scenarios being tested. Results show significant improvement in minimization of losses and congestion while achieving very small calculation times.

Keywords: congestion, distribution networks, loss reduction, particle swarm optimization, smart grid

Procedia PDF Downloads 415

Authors: Soon Young Choi, Chan Hwan Kim, Chan Hong Park, Hyung Rae Kim, Myoung Hoon Lee, Hyeon-Yeong Park

Abstract:

We performed the marine magnetic, bathymetry and seismic survey at the TA22 seamount (in the Lau basin, SW Pacific) for finding the submarine hydrothermal deposits in October 2009. We acquired magnetic and bathymetry data sets by suing Overhouser Proton Magnetometer SeaSPY (Marine Magnetics Co.), Multi-beam Echo Sounder EM120 (Kongsberg Co.). We conducted the data processing to obtain detailed seabed topography, magnetic anomaly, reduction to the pole (RTP) and magnetization. Based on the magnetic properties result, we analyzed submarine geology structure of TA22 seamount with post-processed seismic profile. The detailed bathymetry of the TA22 seamount showed the left and right crest parts that have caldera features in each crest central part. The magnetic anomaly distribution of the TA22 seamount regionally displayed high magnetic anomalies in northern part and the low magnetic anomalies in southern part around the caldera features. The RTP magnetic anomaly distribution of the TA22 seamount presented commonly high magnetic anomalies in the each caldera central part. Also, it represented strong anomalies at the inside of caldera rather than outside flank of the caldera. The magnetization distribution of the TA22 seamount showed the low magnetization zone in the center of each caldera, high magnetization zone in the southern and northern east part. From analyzed the seismic profile map, The TA22 seamount area is showed for the inferred small mounds inside each caldera central part and it assumes to make possibility of sills by the magma in cases of the right caldera. Taking into account all results of this study (bathymetry, magnetic anomaly, RTP, magnetization, seismic profile) with rock samples at the left caldera area in 2009 survey, we suppose the possibility of hydrothermal deposits at mounds in each caldera central part and at outside flank of the caldera representing the low magnetization zone. We expect to have the better results by combined modeling from this study data with the other geological data (ex. detailed gravity, 3D seismic, petrologic study results and etc).

Keywords: detailed bathymetry, magnetic anomaly, seamounts, seismic profile, SW Pacific

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Authors: B. Gopal, Pannala Krishna Murthy, G. N. Sreenivas

Abstract:

The increasing demand of electric power is giving an emphasis on the need for the maximum utilization of renewable energy sources. On the other hand maintaining power quality to satisfaction of utility is an essential requirement. In this paper the design aspects of a Unified Power Quality Conditioner integrated with photovoltaic system in a distributed generation is presented. The proposed system consist of series inverter, shunt inverter are connected back to back on the dc side and share a common dc-link capacitor with Distributed Generation through a boost converter. The primary task of UPQC is to minimize grid voltage and load current disturbances along with reactive and harmonic power compensation. In addition to primary tasks of UPQC, other functionalities such as compensation of voltage interruption and active power transfer to the load and grid in both islanding and interconnected mode have been addressed. The simulation model is design in MATLAB/ Simulation environment and the results are in good agreement with the published work.

Keywords: distributed generation (DG), interconnected mode, islanding mode, maximum power point tracking (mppt), power quality (PQ), unified power quality conditioner (UPQC), photovoltaic array (PV)

Procedia PDF Downloads 483