Search results for: optimal porosity

Authors: Giriprasath Ramanathan, Sivakumar Singaravelu, M. D. Raja, Uma Tirichurapalli Sivagnanam

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Collagen is the abundant protein found in the skin of the animal body that has been designed to provide adequate structural support for the adhesion of cells. The dressing material widely used for tissue engineering and biomedical application has to posses good swelling and biological property for the absorption of exudates and cell proliferation. Acid solubilised collagen from the fish skin of the Arothron stellatus was extracted. The collagen with hydroxypropyl and carboxy methyl cellulose has the better biological property to enhance the healing efficiency. The inter property of collagen with interesting perspectives in the tissue engineering process leads to the development of biomaterial with natural polymer with biologically derived collagen. Keeping this as an objective, the composite biomaterial was fabricated to improve the wound healing and biological properties. In this study the collagen from Arothron stellatus fish skin (ACO) was uniformly blended separately with hydroxypropyl methyl cellulose (HPMC) and carboxyl methyl cellulose (CMC) as biosheets. The casted biosheets were impregnated with mupirocin to get rid of infection from the microbes. Further, the results obtained from differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), tensile studies and biocompatibility of the biosheets were assessed. The swelling, porosity and degradation of the casted biosheets were studied to make the biosheets as a suitable wound dressing material. ACO-HPMC and ACO-CMC biosheets both showed good results, but ACO-HPMC biosheet showed better results than ACO-CMC and hence it can be used as a potential dermal substitute in skin tissue engineering.

Keywords: arothron stellatus, biocompatibility, collagen, tensile strenght

Procedia PDF Downloads 322

Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

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In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

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Authors: Hamidreza Fallah Lajimi, Elham Karami, Alireza Arab, Fatemeh Alinasab

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Being responsive is an increasingly important skill for firms in today’s global economy; thus firms must be agile. Naturally, it follows that an organization’s agility depends on its supply chain being agile. However, achieving supply chain agility is a function of other abilities within the organization. This paper analyses results from a survey of 71 Iran manufacturing companies in order to identify some of the factors for agile organizations in managing their supply chains. Then we classification this company in four cluster with fuzzy c-mean technique and with Four validations functional determine automatically the optimal number of clusters.

Keywords: agile supply chain, clustering, fuzzy clustering, business engineering

Procedia PDF Downloads 715

Authors: Anelise Leal Vieira Cubas, Marina de Medeiros Machado, Marília de Medeiros Machado

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The volatile organic compounds - BTEX (Benzene, Toluene, Ethylbenzene, and Xylene) petroleum derivatives, have high rates of toxicity, which may carry consequences for human health, biota and environment. In this direction, this paper proposes a method of treatment of these compounds by using corona discharge plasma technology. The efficiency of the method was tested by analyzing samples of BTEX after going through a plasma reactor by gas chromatography method. The results show that the optimal residence time of the sample in the reactor was 8 minutes.

Keywords: BTEX, degradation, cold plasma, ecological sciences

Procedia PDF Downloads 318

Authors: A. Hidalgo, A. Desportes, E. Bonin, A. Kadaoui, T. Bouaricha

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Present paper is concerned with portfolio management with Black-Litterman (B-L) model. Considered stocks are exclusively limited to large companies stocks on US market. Results obtained by application of the model are presented. From analysis of collected Dow Jones stock data, remarkable explicit analytical expression of optimal B-L parameter τ, which scales dispersion of normal distribution of assets mean return, is proposed in terms of standard deviation of covariance matrix. Implementation has been developed in Matlab environment to split optimization in Markovitz sense from specific elements related to B-L representation.

Keywords: Black-Litterman, Markowitz, market data, portfolio manager opinion

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Authors: Mailin Misson, Bo Jin, Sheng Dai, Hu Zhang

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Advances in biotechnology have witnessed a growing interest in enzyme applications for the development of green and sustainable bio processes. While known as powerful bio catalysts, enzymes are no longer of economic value when extended to large commercialization. Alternatively, immobilization technology allows enzyme recovery and continuous reuse which subsequently compensates high operating costs. Employment of enzymes on nano structured materials has been recognized as a promising approach to enhance enzyme catalytic performances. High porosity, inter connectivity and self-assembling behaviors endow nano fibers as exciting candidate for enzyme carrier in bio reactor systems. In this study, nano fibers were successfully fabricated via electro spinning system by optimizing the polymer concentration (10-30 %, w/v), applied voltage (10-30 kV) and discharge distance (11-26 cm). Microscopic images have confirmed the quality as homogeneous and good fiber alignment. The nano fibers surface was modified using strong oxidizing agent to facilitate bio molecule binding. Bovine serum albumin and β-galactosidase enzyme were employed as model bio catalysts and immobilized onto the oxidized surfaces through covalent binding. Maximum enzyme adsorption capacity of the modified nano fibers was 3000 mg/g, 3-fold higher than the unmodified counterpart (1000 mg/g). The highest immobilization yield was 80% and reached the saturation point at 2 mg/ml of enzyme concentration. The results indicate a significant increase of activity retention by the enzyme-bound modified nano fibers (80%) as compared to the nascent one (60%), signifying excellent enzyme-nano carrier bio compatibility. The immobilized enzyme was further used for the bio conversion of dairy wastes into value-added products. This study demonstrates great potential of acid-modified electrospun polystyrene nano fibers as enzyme carriers.

Keywords: immobilization, enzyme, nanocarrier, nanofibers

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Authors: Alia Alghosoun, Nabil El Moçayd, Mohammed Seaid

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Modeling dam-break flows over non-flat beds requires an accurate representation of the topography which is the main source of uncertainty in the model. Therefore, developing robust and accurate techniques for reconstructing topography in this class of problems would reduce the uncertainty in the flow system. In many hydraulic applications, experimental techniques have been widely used to measure the bed topography. In practice, experimental work in hydraulics may be very demanding in both time and cost. Meanwhile, computational hydraulics have served as an alternative for laboratory and field experiments. Unlike the forward problem, the inverse problem is used to identify the bed parameters from the given experimental data. In this case, the shallow water equations used for modeling the hydraulics need to be rearranged in a way that the model parameters can be evaluated from measured data. However, this approach is not always possible and it suffers from stability restrictions. In the present work, we propose an adaptive optimal control technique to numerically identify the underlying bed topography from a given set of free-surface observation data. In this approach, a minimization function is defined to iteratively determine the model parameters. The proposed technique can be interpreted as a fractional-stage scheme. In the first stage, the forward problem is solved to determine the measurable parameters from known data. In the second stage, the adaptive control Ensemble Kalman Filter is implemented to combine the optimality of observation data in order to obtain the accurate estimation of the topography. The main features of this method are on one hand, the ability to solve for different complex geometries with no need for any rearrangements in the original model to rewrite it in an explicit form. On the other hand, its achievement of strong stability for simulations of flows in different regimes containing shocks or discontinuities over any geometry. Numerical results are presented for a dam-break flow problem over non-flat bed using different solvers for the shallow water equations. The robustness of the proposed method is investigated using different numbers of loops, sensitivity parameters, initial samples and location of observations. The obtained results demonstrate high reliability and accuracy of the proposed techniques.

Keywords: erodible beds, finite element method, finite volume method, nonlinear elasticity, shallow water equations, stresses in soil

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Authors: Valeriya Tyo, Serikbolat Yessengabulov

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Regions with extreme climate conditions such as Astana city require energy saving measures to increase the energy performance of buildings which are responsible for more than 40% of total energy consumption. Identification of optimal building geometry is one of the key factors to be considered. The architectural form of a building has the impact on space heating and cooling energy use, however, the interrelationship between the geometry and resultant energy use is not always readily apparent. This paper presents a comparative case study of two prototypical buildings with compact building shape to assess its impact on energy performance.

Keywords: building geometry, energy efficiency, heat gain, heat loss

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Authors: Jiuyao Jiang, Jiahao Liu, Jichao Li, Kewei Yang, Minghao Li, Bingfeng Ge

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Modern warfare has transitioned from the paradigm of isolated combat forces to system-to-system confrontations due to advancements in combat technologies and application concepts. A combat system-of-systems (CSoS) is a combat network composed of independently operating entities that interact with one another to provide overall operational capabilities. Enhancing the resilience of CSoS is garnering increasing attention due to its significant practical value in optimizing network architectures, improving network security and refining operational planning. Accordingly, a unified framework called CSoS space-time resilience enhancement (CSoS-STRE) has been proposed, which enhances the resilience of CSoS by incorporating spatial features. Firstly, a multilayer spatial combat network model has been constructed, which incorporates an information layer depicting the interrelations among combat entities based on the OODA loop, along with a spatial layer that considers the spatial characteristics of equipment entities, thereby accurately reflecting the actual combat process. Secondly, building upon the combat network model, a spatiotemporal resilience optimization model is proposed, which reformulates the resilience optimization problem as a classical linear optimization model with spatial features. Furthermore, the model is extended from scenarios without obstacles to those with obstacles, thereby further emphasizing the importance of spatial characteristics. Thirdly, a resilience-oriented recovery optimization method based on improved non dominated sorting genetic algorithm II (R-INSGA) is proposed to determine the optimal recovery sequence for the damaged entities. This method not only considers spatial features but also provides the optimal travel path for multiple recovery teams. Finally, the feasibility, effectiveness, and superiority of the CSoS-STRE are demonstrated through a case study. Simultaneously, under deliberate attack conditions based on degree centrality and maximum operational loop performance, the proposed CSoS-STRE method is compared with six baseline recovery strategies, which are based on performance, time, degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. The comparison demonstrates that CSoS-STRE achieves faster convergence and superior performance.

Keywords: space-time resilience enhancement, resilience optimization model, combat system-of-systems, recovery optimization method, no-obstacles and obstacles

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Authors: Saâd Oukkass, Abderrahim Bouftou, Rachid Ouchn, L. Lebrun, Miloudi Hlaibi

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We invariably exist in a world steeped in colors, whether in our clothing, food, cosmetics, or even medications. However, most of the dyes we use pose significant problems, being both harmful to the environment and resistant to degradation. Among these dyes, methylene blue and acid yellow 61 stand out, commonly used to dye various materials such as cotton, wood, and silk. Fortunately, various methods have been developed to treat and remove these polluting dyes, among which membrane processes play a prominent role. These methods are praised for their low energy consumption, ease of operation, and their ability to achieve effective separation of components. Adsorption on activated carbon is also a widely employed technique, complementing the basic processes. It proves particularly effective in capturing and removing organic compounds from water due to its substantial specific surface area while retaining its properties unchanged. In the context of our study, we examined two crucial aspects. Firstly, we explored the possibility of selectively extracting methylene blue from a mixture containing another dye, acid yellow 61, using a polymer inclusion membrane (PIM) made of PVA. After characterizing the morphology and porosity of the membrane, we applied kinetic and thermodynamic models to determine the values of permeability (P), initial flux (J0), association constant (Kass), and apparent diffusion coefficient (D*). Subsequently, we measured activation parameters (activation energy (Ea), enthalpy (ΔH#ass), entropy (ΔS#)). Finally, we studied the effect of activated carbon on the processes carried out through the membrane, demonstrating a clear improvement. These results make the membrane developed in this study a potentially pivotal player in the field of membrane separation.

Keywords: dyes, methylene blue, membrane, activated carbon

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Authors: Mahnaz Hosseinzadeh, Aliyeh Kazemi

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In this paper, a method is proposed for solving Fuzzy Multi-Objective Linear Programming problems (FMOLPP) with fuzzy right hand side and fuzzy decision variables. To illustrate the proposed method, it is applied to the problem of selecting suppliers for an automotive parts producer company in Iran in order to find the number of optimal orders allocated to each supplier considering the conflicting objectives. Finally, the obtained results are discussed.

Keywords: fuzzy multi-objective linear programming problems, triangular fuzzy numbers, fuzzy ranking, supplier selection problem

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Authors: Chakib Jerry, Mounir Jerry

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In this paper, a mathematical model of infested honey bees colonies is formulated in order to investigate Colony Collapse Disorder in a honeybee colony. CCD, as it is known, is a major problem on honeybee farms because of the massive decline in colony numbers. We introduce to the model a control variable which represents forager protection. We study the controlled model to derive conditions under which the bee colony can fight off epidemic. Secondly we study the problem of minimizing prevention cost under model’s dynamics constraints.

Keywords: honey bee, disease transmission model, disease control honeybees, optimal control

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Authors: Amir Mahdavi

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In this paper a highly linear CMOS low noise amplifier (LNA) for ultra-wideband (UWB) applications is proposed. The proposed LNA uses a linearization technique to improve second and third-order intercept points (IIP3). The linearity is cured by repealing the common-mode section of all intermodulation components from the cascade topology current with optimization of biasing current use symmetrical and asymmetrical circuits for biasing. Simulation results show that maximum gain and noise figure are 6.9dB and 3.03-4.1dB over a 3.1–10.6 GHz, respectively. Power consumption of the LNA core and IIP3 are 2.64 mW and +4.9dBm respectively. The wideband input impedance matching of LNA is obtained by employing a degenerating inductor (|S11|<-9.1 dB). The circuit proposed UWB LNA is implemented using 0.18 μm based CMOS technology.

Keywords: highly linear LNA, low-power LNA, optimal bias techniques

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Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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The aim of this study was to develop an Artificial Neural Network0 s recommendation model for an online process using the complexity of load, performance, and average servicing time of the resources. Here, the proposed model investigates the resource performance using stochastic gradient decent method for learning ranking function. A probabilistic cost function is implemented to identify the optimal θ values (load) on each resource. Based on this result the recommendation of resource suitable for performing the currently executing task is made. The test result of CoSeLoG project is presented with an accuracy of 72.856%.

Keywords: ADALINE, neural network, gradient decent, process mining, resource behaviour, polynomial regression model

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Authors: M. A. Bayona, E. M. Cordoba, V. R. Guiza

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Highly porous carbon-based foams are used in a wide range of industrial applications, which include absorption, catalyst supports, thermal insulation, and biomaterials, among others. Particularly, silicon carbide (SiC) based foams have shown exceptional potential for catalyst support applications, due to their chemical inertness, large frontal area, low resistance to flow, low-pressure drop, as well as high resistance to temperature and corrosion. These properties allow the use of SiC foams in harsh environments with high durability. Commonly, SiC foams are fabricated from polysiloxane, SiC powders and phenolic resins, which can be costly or highly toxic to the environment. In this work, we propose a low-cost method for the fabrication of highly porous, three-dimensional SiC foams via template replica, using recycled polymeric sponges as sacrificial templates. A sucrose-based resin combined with a Si-containing pre-ceramic polymer was used as the precursor. Polymeric templates were impregnated with the precursor solution, followed by thermal treatment at 1500 °C under an inert atmosphere. Several synthesis parameters, such as viscosity and composition of the precursor solution (Si: Sucrose molar ratio), and the porosity of the template, were evaluated in terms of their effect on the morphology, composition and mechanical resistance of the resulting SiC foams. The synthesized composite foams exhibited a highly porous (50-90%) and interconnected structure, containing 30-90% SiC with a mechanical compressive strength between 0.01-0.1 MPa. The methodology employed here allowed the fabrication of foams with a varied concentration of SiC and with morphological and mechanical properties that contribute to the development of materials of high relevance in the industry, while using low-cost, renewable sources such as table sugar, and providing a recycling alternative for polymeric sponges.

Keywords: catalyst support, polymer replica technique, reticulated porous ceramics, silicon carbide

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Authors: Benhamouda Sara, Guezouli Larbi

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Nowadays, the dissemination of information touches the distributed world, where selecting the relevant servers to a user request is an important problem in distributed information retrieval. During the last decade, several research studies on this issue have been launched to find optimal solutions and many approaches of collection selection have been proposed. In this paper, we propose a new collection selection approach that takes into consideration the number of documents in a collection that contains terms of the query and the weights of those terms in these documents. We tested our method and our studies show that this technique can compete with other state-of-the-art algorithms that we choose to test the performance of our approach.

Keywords: distributed information retrieval, relevance, server selection, collection selection

Procedia PDF Downloads 315

Authors: Sung-Hee Nam, Kwang-Gill Lee, You-Young Jo, HaeYong Kweon

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Entomopathogenic fungi is a Cordyceps species that is isolated from dead silkworm and cicada. Fungi on cicadas were described in old Chinese medicinal books and From ancient times, vegetable wasps and plant worms were widely known to have active substance and have been studied for pharmacological use. Among many fungi belonging to the genus Cordyceps, Cordyceps sinensis have been demonstrated to yield natural products possessing various biological activities and many bioactive components. Generally, It is commonly used to replenish the kidney and soothe the lung, and for the treatment of fatigue. Due to their commercial and economic importance, the demand for Cordyceps has been rapidly increased. However, a supply of Cordyceps specimen could not meet the increasing demand because of their sole dependence on field collection and habitat destruction. Because it is difficult to obtain many insect hosts in nature and the edibility of host insect needs to be verified in a pharmacological aspect. Recently, this setback was overcome that P. tenuipes was able to be cultivated in a large scale using silkworm as host. Pharmacological effects of P. tenuipes cultured on silkworm such as strengthening immune function, anti-fatigue, anti-tumor activity and controlling liver etc have been proved. They are widely commercialized. In this study, we attempted to establish a method for stable growth inhibition of P. tenuipes on silkworm hosts and an optimal condition for synnemata formation. To determine optimum culturing conditions, temperature and light conditions were varied. The length and number of synnemata was highest at 25℃ temperature and 100~300 lux illumination. On an average, the synnemata of wild P. tenuipes measures 70 ㎜ in length and 20 in number; those of the cultured strain were relatively shorter and more in number. The number of synnemata may have increased as a result of inoculating the host with highly concentrated conidia, while the length may have decreased due to limited nutrition per individual. It is not able that changes in light illumination cause morphological variations in the synnemata. However, regulation of only light and temperature could not produce stromata like perithecia, asci, and ascospores. Yamanaka reported that although a complete fruiting body can be produced under optimal culture conditions, it should be regarded as synnemata because it does not develop into an ascoma bearing ascospores.

Keywords: paecilomyces tenuipes, entomopathogenic fungi, silkworm larva, bombyx mori

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Authors: Shilpa Sondkar, Maithili Patil, Atharva Potnis

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The current health care landscape desires efficiency and patient satisfaction for optimal performance. Medical appointment booking apps have increased the overall efficiency of clinics, hospitals, and e-health marketplaces while simplifying processes. These apps allow patients to connect with doctors online. Not only are mobile doctor appointment apps a reliable and efficient solution, but they are also the future of clinical progression and a distinct new stage in the patient-doctor relationship. Compared to the usual queuing method, the web-based appointment system could significantly increase patients' satisfaction with registration and reduce total waiting time effectively.

Keywords: appointment, patient, scheduling, design and development, Figma

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Authors: Zouhair Issa Ahmed, Ahmed Abdulrasool Ahmed, Falah Hassan Abdulsada

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This paper presents a layout of a factory using Pro-Model simulation by choosing the best layout that gives the highest productivity and least work in process. The general problem is to find the best sequence in which jobs pass between the machines which are compatible with the technological constraints and optimal with respect to some performance criteria. The best simulation with Pro-Model program increased productivity and reduced work in process by balancing lines of production compared with the current layout of factory when productivity increased from 45 products to 180 products through 720 hours.

Keywords: scheduling, Pro-Model, simulation, balancing lines of production, layout planning, WIP

Procedia PDF Downloads 638

Authors: Yi-Cheng Tian, Miin-Shen Yang

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The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm.

Keywords: clustering, EM algorithm, Gaussian mixture model, mixture regression model

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Authors: R. M. Rizk-Allah

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This paper presents co-evolutionary fruit fly optimization algorithm based on firefly algorithm (CFOA-FA) for solving unconstrained optimization problems. The proposed algorithm integrates the merits of fruit fly optimization algorithm (FOA), firefly algorithm (FA) and elite strategy to refine the performance of classical FOA. Moreover, co-evolutionary mechanism is performed by applying FA procedures to ensure the diversity of the swarm. Finally, the proposed algorithm CFOA- FA is tested on several benchmark problems from the usual literature and the numerical results have demonstrated the superiority of the proposed algorithm for finding the global optimal solution.

Keywords: firefly algorithm, fruit fly optimization algorithm, unconstrained optimization problems

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Authors: É. Vincze

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Demand on plant oils has increased to an enormous extent that is due to the change of human nutrition habits on the one hand, while on the other hand to the increase of raw material demand of some industrial sectors, just as to the increase of biofuel production. Besides the determining importance of sunflower in Hungary the production area, just as in part the average yield amount of rapeseed has increased among the produced oil crops. The variety/hybrid palette has changed significantly during the past decade. The available varieties’/hybrids’ palette has been extended to a significant extent. It is agreed that rapeseed production demands professionalism and local experience. Technological elements are successive; high yield amounts cannot be produced without system-based approach. The aim of the present work was to execute the complex study of one of the most critical production technology element of rapeseed production, that was sowing technology. Several sowing technology elements are studied in this research project that are the following: biological basis (the hybrid Arkaso is studied in this regard), sowing time (sowing time treatments were set so that they represent the wide period used in industrial practice: early, optimal and late sowing time) plant density (in this regard reaction of rare, optimal and too dense populations) were modelled. The multifactorial experimental system enables the single and complex evaluation of rapeseed sowing technology elements, just as their modelling using experimental result data. Yield quality and quantity have been determined as well in the present experiment, just as the interactions between these factors. The experiment was set up in four replications at the Látókép Plant Production Research Site of the University of Debrecen. Two different sowing times were sown in the first experimental year (2014), while three in the second (2015). Three different plant densities were set in both years: 200, 350 and 500 thousand plants ha-1. Uniform nutrient supply and a row spacing of 45 cm were applied. Winter wheat was used as pre-crop. Plant physiological measurements were executed in the populations of the Arkaso rapeseed hybrid that were: relative chlorophyll content analysis (SPAD) and leaf area index (LAI) measurement. Relative chlorophyll content (SPAD) and leaf area index (LAI) were monitored in 7 different measurement times.

Keywords: inner quality, plant density, rapeseed, sowing time

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Authors: Elif Cakir, Görkem Özülkü, Hatice Bekiroğlu, Muhammet Arici, Osman Sağdic

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It is important to be able to formulate cakes with a wide consumption mass with gluten-free and high nutritional value ingredients to increase the consumption possibilities of people with limited nutrition opportunities. Although people do not prefer Prunus spinosa (PS)because of its sour taste and its use in the food industry is limited on a local scale, the potential of using PS, which is a naturally rich source of many micronutrients and bioactive compounds, in glutenfree cake production has been investigated. In this study, the potential of using PS, a natural wild fruit, in the production of functional gluten-free cakes was investigated. It was aimed to evaluate the effects of freeze-dried and powdered PS-enriched rice flour cakes on tech functionality, nutrition and eating quality. In terms of physicochemical properties, PS raises increased the ash, protein, and moisture values of the cakes. PS with high phenolic content, phenolic component content, and radical reducing power made by ABTS, FRAP, and DPPH techniques were higher in all samples than control, and the highest 4% PS was determined in cakes. In terms of the glycemic index (GI), which is an important feature of diet products, it was determined that the GI in cakes decreased by 86.30±1.04.75.05±1.16 and 69.38±1.21, respectively, with the increase in PS ratio. Except for the 1%, PS added sample, the increase in PS caused a decrease in specific volume, % porosity and increase in hardness, including 4 days of storage. PS increase decreased the L* and b* values and increased a* value and redness of the cake. Sensory liking of the cake samples containing PS was scored significantly (p<0.05) higher of control.

Keywords: Prunus spinosa, gluten-free cake, antioxidant, phenolic, glycemic index

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Authors: Vinai K. Singh

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For reducing impulsive noise without degrading image contours, median filtering is a powerful tool. In multiband images as for example colour images or vector fields obtained by optic flow computation, a vector median filter can be used. Vector median filters are defined on the basis of a suitable distance, the best performing distance being the Euclidean. Euclidean distance is evaluated by using the Euclidean norms which is quite demanding from the point of view of computation given that a square root is required. In this paper an optimal piece-wise linear approximation of the Euclidean norm is presented which is applied to vector median filtering.

Keywords: euclidean norm, quasi euclidean norm, vector median filtering, applied mathematics

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Authors: H. K. Esfahani, B. Datta

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Groundwater is one of the most important natural resources in many parts of the world; however it is widely polluted due to human activities. Currently, effective and reliable groundwater management and remediation strategies are obtained using characterization of groundwater pollution sources, where the measured data in monitoring locations are utilized to estimate the unknown pollutant source location and magnitude. However, accurately identifying characteristics of contaminant sources is a challenging task due to uncertainties in terms of predicting source flux injection, hydro-geological and geo-chemical parameters, and the concentration field measurement. Reactive transport of chemical species in contaminated groundwater systems, especially with multiple species, is a complex and highly non-linear geochemical process. Although sufficient concentration measurement data is essential to accurately identify sources characteristics, available data are often sparse and limited in quantity. Therefore, this inverse problem-solving method for characterizing unknown groundwater pollution sources is often considered ill-posed, complex and non- unique. Different methods have been utilized to identify pollution sources; however, the linked simulation-optimization approach is one effective method to obtain acceptable results under uncertainties in complex real life scenarios. With this approach, the numerical flow and contaminant transport simulation models are externally linked to an optimization algorithm, with the objective of minimizing the difference between measured concentration and estimated pollutant concentration at observation locations. Concentration measurement data are very important to accurately estimate pollution source properties; therefore, optimal design of the monitoring network is essential to gather adequate measured data at desired times and locations. Due to budget and physical restrictions, an efficient and effective approach for groundwater pollutant source characterization is to design an optimal monitoring network, especially when only inadequate and arbitrary concentration measurement data are initially available. In this approach, preliminary concentration observation data are utilized for preliminary source location, magnitude and duration of source activity identification, and these results are utilized for monitoring network design. Further, feedback information from the monitoring network is used as inputs for sequential monitoring network design, to improve the identification of unknown source characteristics. To design an effective monitoring network of observation wells, optimization and interpolation techniques are used. A simulation model should be utilized to accurately describe the aquifer properties in terms of hydro-geochemical parameters and boundary conditions. However, the simulation of the transport processes becomes complex when the pollutants are chemically reactive. Three dimensional transient flow and reactive contaminant transport process is considered. The proposed methodology uses HYDROGEOCHEM 5.0 (HGCH) as the simulation model for flow and transport processes with chemically multiple reactive species. Adaptive Simulated Annealing (ASA) is used as optimization algorithm in linked simulation-optimization methodology to identify the unknown source characteristics. Therefore, the aim of the present study is to develop a methodology to optimally design an effective monitoring network for pollution source characterization with reactive species in polluted aquifers. The performance of the developed methodology will be evaluated for an illustrative polluted aquifer sites, for example an abandoned mine site in Queensland, Australia.

Keywords: monitoring network design, source characterization, chemical reactive transport process, contaminated mine site

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Authors: Ali Akbar, Seungho Shin, Sukkee Um

Abstract:

The composition of catalyst layers (CLs) plays an important role in the overall performance and cost of the proton exchange membrane fuel cells (PEMFCs). Low platinum loading, high utilization, and more durable catalyst still remain as critical challenges for PEMFCs. In this study, a three-dimensional material network model is developed to visualize the nanostructure of carbon supported platinum Pt/C and Pt/VACNT catalysts in pursuance of maximizing the catalyst utilization. The quadruple-phase randomly generated CLs domain is formulated using quasi-random stochastic Monte Carlo-based method. This unique statistical approach of four-phase (i.e., pore, ionomer, carbon, and platinum) model is closely mimic of manufacturing process of CLs. Various CLs compositions are simulated to elucidate the effect of electrons, ions, and mass transport paths on the catalyst utilization factor. Based on simulation results, the effect of key factors such as porosity, ionomer contents and Pt weight percentage in Pt/C catalyst have been investigated at the represented elementary volume (REV) scale. The results show that the relationship between ionomer content and Pt utilization is in good agreement with existing experimental calculations. Furthermore, this model is implemented on the state-of-the-art Pt/VACNT CLs. The simulation results on Pt/VACNT based CLs show exceptionally high catalyst utilization as compared to Pt/C with different composition ratios. More importantly, this study reveals that the maximum catalyst utilization depends on the distance spacing between the carbon nanotubes for Pt/VACNT. The current simulation results are expected to be utilized in the optimization of nano-structural construction and composition of Pt/C and Pt/VACNT CLs.

Keywords: catalyst layer, platinum utilization, proton exchange membrane fuel cell, stochastic modeling

Procedia PDF Downloads 121

Authors: M. Pramila Devi, N. V. N. Indra Kiran

Abstract:

Control charts, predominantly in the form of X-bar chart, are important tools in statistical process control (SPC). They are useful in determining whether a process is behaving as intended or there are some unnatural causes of variation. A process is out of control if a point falls outside the control limits or a series of point’s exhibit an unnatural pattern. In this paper, a study is carried out on four training algorithms for CCPs recognition. For those algorithms optimal structure is identified and then they are studied for type I and type II errors for generalization without early stopping and with early stopping and the best one is proposed.

Keywords: control chart pattern recognition, neural network, backpropagation, generalization, early stopping

Procedia PDF Downloads 373

Authors: Shih-Huang Pan, Tsuyoshi Miyazaki, Minoru Otani, Santhanamoorthi Nachimuthu, Jyh-Chiang Jiang

Abstract:

Ammonia (NH₃) is crucial in renewable energy and agriculture, yet its traditional production via the Haber-Bosch process faces challenges due to the inherent inertness of nitrogen (N₂) and the need for high temperatures and pressures. The electrocatalytic nitrogen reduction (ENRR) presents a more sustainable option, functioning at ambient conditions. However, its advancement is limited by selectivity and efficiency challenges due to the competing hydrogen evolution reaction (HER). The critical roles of protonation of N-species and HER highlight the necessity of selecting optimal catalysts and solvents to enhance ENRR performance. Notably, transition metal oxides, with their adjustable electronic states and excellent chemical and thermal stability, have shown promising ENRR characteristics. In this study, we use density functional theory (DFT) methods to investigate the ENRR mechanisms on IrO₂ (110), a material known for its tunable electronic properties and exceptional chemical and thermal stability. Employing the constant electrode potential (CEP) model, where the electrode - electrolyte interface is treated as a polarizable continuum with implicit solvation, and adjusting electron counts to equalize work functions in the grand canonical ensemble, we further incorporate the advanced 3D Reference Interaction Site Model (3D-RISM) to accurately determine the ENRR limiting potential across various solvents and pH conditions. Our findings reveal that the limiting potential for ENRR on IrO₂ (110) is significantly more favorable than for HER, highlighting the efficiency of the IrO₂ catalyst for converting N₂ to NH₃. This is supported by the optimal *NH₃ desorption energy on IrO₂, which enhances the overall reaction efficiency. Microkinetic simulations further predict a promising NH₃ production rate, even at the solution's boiling point¸ reinforcing the catalytic viability of IrO₂ (110). This comprehensive approach provides an atomic-level understanding of the electrode-electrolyte interface in ENRR, demonstrating the practical application of IrO₂ in electrochemical catalysis. The findings provide a foundation for developing more efficient and selective catalytic strategies, potentially revolutionizing industrial NH₃ production.

Keywords: density functional theory, electrocatalyst, nitrogen reduction reaction, electrochemistry

Procedia PDF Downloads 24

Authors: Jose Gois

Abstract:

The paper presents the development of a porous porcelain frappe with thermochromic visualization for port wines, having as a partner the Institute of Vinhos do Douro and Porto. This ceramic frappe is intended to promote the cooling and maintenance of the temperature of port wines through porous ceramic materials, consisting of a porcelain composite with sawdust addition, so as to contain, on the one hand, the similar cooling properties of the terracotta and, on the other, the resistance of materials such as porcelain. The application of the thermochromic element makes it possible to see if the wine is at optimal service temperatures, allowing users to drink the wine in the ideal conditions and contributing to more efficient maintenance of the service.

Keywords: design, frappe, porcelain, porous, thermochromic

Procedia PDF Downloads 135

Authors: Navid Zarif Karimi, Giangiacomo Minak, Parnian Kianfar

Abstract:

Drilling is one of the most frequently used machining process for glass fiber reinforced polymer composites due to the need for structural joining. In drilling of composite laminates, interlaminar cracking, or delamination, has a detrimental effect on the compressive strength of these materials. The delamination can be controlled by adopting proper drilling condition. In this paper, the effect of feed rate, cutting speed and drill point angle on delamination and residual compressive strength of drilled GFRPs is studied. The objective is to find optimal conditions for maximum residual compressive strength.

Keywords: composite material, delamination, drilling, residual compressive strength

Procedia PDF Downloads 458