Search results for: bacterial foraging optimization

Authors: Ibrahim Aydogdu, Alper Akin

Abstract:

In this study, the development of minimizing the cost and the CO2 emission of the RC retaining wall design has been performed by Biogeography Based Optimization (BBO) algorithm. This has been achieved by developing computer programs utilizing BBO algorithm which minimize the cost and the CO2 emission of the RC retaining walls. Objective functions of the optimization problem are defined as the minimized cost, the CO2 emission and weighted aggregate of the cost and the CO2 functions of the RC retaining walls. In the formulation of the optimum design problem, the height and thickness of the stem, the length of the toe projection, the thickness of the stem at base level, the length and thickness of the base, the depth and thickness of the key, the distance from the toe to the key, the number and diameter of the reinforcement bars are treated as design variables. In the formulation of the optimization problem, flexural and shear strength constraints and minimum/maximum limitations for the reinforcement bar areas are derived from American Concrete Institute (ACI 318-14) design code. Moreover, the development length conditions for suitable detailing of reinforcement are treated as a constraint. The obtained optimum designs must satisfy the factor of safety for failure modes (overturning, sliding and bearing), strength, serviceability and other required limitations to attain practically acceptable shapes. To demonstrate the efficiency and robustness of the presented BBO algorithm, the optimum design example for retaining walls is presented and the results are compared to the previously obtained results available in the literature.

Keywords: bio geography, meta-heuristic search, optimization, retaining wall

Procedia PDF Downloads 382

Authors: Dario Barsi, Marina Ubaldi, Pietro Zunino, Robert Fink

Abstract:

A design and optimization procedure is proposed and developed to provide the geometry of a high efficiency compact hydraulic propeller turbine for low head. For the preliminary design of the machine, classic design criteria, based on the use of statistical correlations for the definition of the fundamental geometric parameters and the blade shapes are used. These relationships are based on the fundamental design parameters (i.e., specific speed, flow coefficient, work coefficient) in order to provide a simple yet reliable procedure. Particular attention is paid, since from the initial steps, on the correct conformation of the meridional channel and on the correct arrangement of the blade rows. The preliminary geometry thus obtained is used as a starting point for the hydrodynamic optimization procedure, carried out using a CFD calculation software coupled with a genetic algorithm that generates and updates a large database of turbine geometries. The optimization process is performed using a commercial approach that solves the turbulent Navier Stokes equations (RANS) by exploiting the axial-symmetric geometry of the machine. The geometries generated within the database are therefore calculated in order to determine the corresponding overall performance. In order to speed up the optimization calculation, an artificial neural network (ANN) based on the use of an objective function is employed. The procedure was applied for the specific case of a propeller turbine with an innovative design of a modular type, specific for applications characterized by very low heads. The procedure is tested in order to verify its validity and the ability to automatically obtain the targeted net head and the maximum for the total to total internal efficiency.

Keywords: renewable energy conversion, hydraulic turbines, low head hydraulic energy, optimization design

Procedia PDF Downloads 136

Authors: Gianmaria Califano, Júlio Augusto Lucena Maciel, Olfa Zarrouk, Miguel Damasio, Jose Silvestre, Ana Margarida Fortes

Abstract:

Global warming, with rapid and sudden changes in meteorological conditions, is one of the major constraints to ensuring agricultural and crop resilience in the Mediterranean regions. Several strategies are being adopted to reduce the pressure of drought stress on grapevines at regional and local scales: improvements in the irrigation systems, adoption of interline cover crops, and adaptation of pruning techniques. However, still, more can be achieved if also microbial compartments associated with plants are considered in crop management. It is known that the microbial community change according to several factors such as latitude, plant variety, age, rootstock, soil composition and agricultural management system. Considering the increasing pressure of the biotic and abiotic stresses, it is of utmost necessity to also evaluate the effects of drought on the microbiome associated with the grapevine, which is a commercially important crop worldwide. In this study, we characterize the diversity and the structure of the microbial community under three long-term irrigation levels (100% ETc, 50% ETc and rain-fed) in a drought-tolerant grapevine cultivar present worldwide, Syrah. To avoid the limitations of culture-dependent methods, amplicon sequencing with target primers for bacteria and fungi was applied to the same soil samples. The use of the DNeasy PowerSoil (Qiagen) extraction kit required further optimization with the use of lytic enzymes and heating steps to improve DNA yield and quality systematically across biological treatments. Target regions (16S rRNA and ITS genes) of our samples are being sequenced with Illumina technology. With bioinformatic pipelines, it will be possible to obtain a characterization of the bacterial and fungal diversity, structure and composition. Further, the microbial communities will be assessed for their functional activity, which remains an important metric considering the strong inter-kingdom interactions existing between plants and their associated microbiome. The results of this study will lay the basis for biotechnological applications: in combination with the establishment of a bacterial library, it will be possible to explore the possibility of testing synthetic microbial communities to support plant resistance to water scarcity.

Keywords: microbiome, metabarcoding, soil, vinegrape, syrah, global warming, crop sustainability

Procedia PDF Downloads 100

Authors: Shahab Azimi, Siamak Arzanpour, Anahita Sayyar

Abstract:

Asthma and Chronic obstructive pulmonary disease (COPD) are common lung diseases that have a significant global impact. Pressurized metered dose inhalers (pMDIs) are widely used for treatment, but they can have limitations such as high medication release speed resulting in drug deposition in the mouth or oral cavity and difficulty achieving proper synchronization with inhalation by users. Spacers are add-on devices that improve the efficiency of pMDIs by reducing the release speed and providing space for aerosol particle breakup to have finer and medically effective medication. The aim of this study is to optimize the size and cylindrical shape of spacers to enhance their drug delivery performance. The study was based on fluid dynamics theory and employed Ansys software for simulation and optimization. Results showed that optimization of the spacer's geometry greatly influenced its performance and improved drug delivery. This study provides a foundation for future research on enhancing the efficiency of inhalation therapy for lung diseases.

Keywords: asthma, COPD, pressurized metered dose inhalers, spacers, CFD, shape optimization

Procedia PDF Downloads 68

Authors: Deepa T., Inchara S. R., Venkatesh S. V., Seema Tharannum

Abstract:

Concrete is the most widely used structural material. It is usually made using locally available materials. However, concrete has low tensile strength and may crack in the early days with exothermic hydration, for which water is essential. To address the increased construction water demand, treated greywater may be used. Bacillus subtilis bacteria that form endospores is the biological agent considered in this study for biomineralization or Microbially Induced Calcite Precipitation (MICP) technique to heal cracks. Treated grey water which is obtained from STP of PES University, opted in place of Potable water, which had qualities within the standard range as per codal provisions. In this work, M30 grade conventional concrete is designed using OPC 53-grade cement, manufactured sand, natural coarse aggregates, and potable water. Conventional concrete (CC), bacterial concrete with potable water (BS), and treated grey water concrete (TGWBS) are the three different concrete specimens cast. Experimental studies such as the strength test and the surface hardness test are performed on conventional and bacterial concrete samples after 7, 28, and 56 days of curing. Concrete cubes are subjected to a temperature of 50° C to investigate the effect of higher temperature. Cracked cube specimens are observed for self-healing -as well as microstructure analysis with Scanning Electron Microscope (SEM), Energy Dispersive X-Ray Analysis (EDAX), and X-Ray Diffraction Analysis (XRD). Noticeable calcium salt deposition is observed on the surface of the BS and TGWBS cracked specimen. Surface hardness and the EDAX test gave promising results on the advantage of using spore-forming bacteria in concrete. This is followed by the strength gained in compression and flexure. Results also indicate that treated grey water can be a substitute for potable water in concrete.

Keywords: Bacillus subtilis concrete, microstructure, temperature, treated greywater

Procedia PDF Downloads 79

Authors: Mitchell Gohnert, Ryan Bradley

Abstract:

This paper reviews some fundamental concepts of structural optimization, which are based on the type of materials used in construction and the shape of the structure. The first step in structural optimization is to break down all internal forces in a structure into fundamental stresses, which are tensions and compressions. Knowing the stress patterns directs our selection of structural shapes and the most appropriate type of construction material. In our selection of materials, it is essential to understand all construction materials have flaws, or micro-cracks, which reduce the capacity of the material, especially when subjected to tensions. Because of material defects, many construction materials perform significantly better when subjected to compressive forces. Structures are also more efficient if bending moments are eliminated. Bending stresses produce high peak stresses at each face of the member, and therefore, substantially more material is required to resist bending. The shape of the structure also has a profound effect on stress levels. Stress may be reduced dramatically by simply changing the shape. Catenary, triangular and linear shapes are the fundamental structural forms to achieve optimal stress flow. If the natural flow of stress matches the shape of the structures, the most optimal shape is determined.

Keywords: arches, economy of stresses, material strength, optimization, shells

Procedia PDF Downloads 96

Authors: Sudha T., Naveen C.

Abstract:

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

Procedia PDF Downloads 38

Authors: K. Petrosyan, R. Piwowarczyk, K. Ruraż, S. Thijs, J. Vangronsveld, W. Kaca

Abstract:

Holoparasitic plants are flowering heterotrophic angiosperms which with the help of an absorbing organ - haustorium, attach to another plant, the so-called the host. Due to the different hosts, unusual lifestyle, lack of roots, chlorophylls and photosynthesis, these plants are interesting and unique study objects for global biodiversity. The seeds germination of the parasitic plants also is unique: they germinate only in response to germination stimulants, namely strigolactones produced by the root of an appropriate host. Resistance of the seeds on different environmental conditions allow them to stay viable in the soil for more than 20 years. Among the wide range of plant protection mechanisms the endophytic communities have a specific role. In this way, they have the potential to mitigate the impacts of adverse conditions such as soil salinization. The major objective of our study was to compare the bacterial endo-microbiomes from seeds of two holoparasitic plants from Orobanchaceae family, Cistanche – C. armena (Armenia) and C. phelypaea (Portugal) – from saline habitats different in soil water status. The research aimed to perform how environmental conditions influence on the diversity of the bacterial communities of C. armena and C. phelypaea seeds. This was achieved by comparison of the endophytic microbiomes of two species and isolation of culturable bacteria. A combination of culture-dependent and molecular techniques was employed for the identification of the seed endomicrobiome (culturable and unculturable). Using the V3-V4 hypervariable region of the 16S rRNA gene, four main taxa were identified: Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes, but the relative proportion of the taxa was different in each type of seed. Generally, sixteen phyla, 323 genera and 710 bacterial species were identified, mainly Gram negative, halotolerant bacteria with an environmental origin. However, also some unclassified and unexplored taxonomic groups were found in the seeds of both plants. 16S rRNA gene sequencing analysis from both species identified the gram positive, endospore forming, halotolerant and alkaliphile Bacillus spp. which suggests that the endophytic bacteria of examined seeds possess traits that are correlated with the natural habitat of their hosts. The cultivable seed endophytes from C. armena and C. phelypaea were rather similar, notwithstanding the big distances between their growth habitats - Armenia and Portugal. Although the seed endophytic microbiomes of C. armena and C. phelypaea contain a high number of common bacterial taxa, also remarkable differences exist. We demonstrated that the environmental conditions or abiotic stresses influence on diversity of the bacterial communities of holoparasiotic seeds. To the best of our knowledge the research is the first report of endophytes from seeds of holoparasitic Cistanche armena and C. phelypaea plants.

Keywords: microbiome, parasitic plant, salinity, seeds

Procedia PDF Downloads 56

Authors: Mohamed Ahmed Kenawi Abdallah

Abstract:

Chemical composition, cooking loss, shrinkage value, texture coefficient indices, Feder value, microbial examination, and sensory evaluation were done in order to examine the effect of adding 15% germinated quinoa seeds flour as extender to chicken wings meat to produce low fat chicken burger, packaged in two different packing materials and stored frozen for nine months. The data indicated reduction in the moisture content, crude either extract, and increase in the ash content, pH value, and total acidity for the samples extended by quinoa flour compared with the control one. The data showed that the extended samples with quinoa flour had the lowest values of TBA, cooking loss, and shrinkage value compared with the control ones. The data also revealed that, the sample contained quinoa flour had total bacterial count and psychrophilic bacterial count lower than the control sample. In addition, it has higher evaluation values for overall acceptability than the control one.

Keywords: chicken wings, low fat chicken burger, quinoa flour, vacuum packaging.

Procedia PDF Downloads 89

Authors: Iryna P. Dzieciuch, Michael D. Putman

Abstract:

Humidity is known to degrade Navy ship electronic equipment, especially in hot moist environments. If left untreated, it can cause significant and permanent damage. Even rigorous inspection and frequent clean-up would not prevent further equipment contamination and degradation because of the constant presence of favorable growth conditions for many microorganisms. Generally, relative humidity levels of less than 60% will inhibit corrosion in electronic equipment, but because NAVY electronics often operate in hot and humid environments, prevention via dehumidification is not always possible. Currently, there is no defined research that fully describes key mechanisms which cause electronics and its coating degradation. The corrosive action of most bacteria is mainly developed through (i) mycelium adherence to the metal plates, (ii) facilitation the formation of pitting areas, (iii) production of organic acids such as citric, iso-citric, cis-aconitic, alpha-ketoglutaric, which are corrosive to electronic equipment and its components. Our approach studies corrosive action in electronic equipment: circuit-board, wires and connections that are exposed in the humid environment that gets worse during condensation. In our new approach the technical task is built on work with the bacterial communities in public areas, bacterial genetics, bioinformatics, biostatistics and Scanning Electron Microscopy (SEM) of corroded circuit boards. Based on these methods, we collect and examine environmental samples from biofilms of the corroded and non-corroded sites, where bacterial contamination of electronic equipment, such as machine racks and shore boats, is an ongoing concern. Sample collection and sample analysis is focused on addressing the key questions identified above through the following tasks: laboratory sample processing and evaluation under scanning electron microscopy, initial sequencing and data evaluation; bioinformatics and data analysis. Preliminary results from scanning electron microscopy (SEM) have revealed that metal particulates and alloys in corroded samples consists mostly of Tin ( < 40%), Silicon ( < 4%), Sulfur ( < 1%), Aluminum ( < 2%), Magnesium ( < 2%), Copper ( < 1%), Bromine ( < 2%), Barium ( <1%) and Iron ( < 2%) elements. We have also performed X 12000 magnification of the same sites and that proved existence of undisrupted biofilm organelles and crystal structures. Non-corrosion sites have revealed high presence of copper ( < 47%); other metals remain at the comparable level as on the samples with corrosion. We have performed X 1000 magnification on the non-corroded at the sites and have documented formation of copper crystals. The next step of this study, is to perform metagenomics sequencing at all sites and to compare bacterial composition present in the environment. While copper is nontoxic to the living organisms, the process of bacterial adhesion creates acidic environment by releasing citric, iso-citric, cis-aconitic, alpha-ketoglutaric acidics, which in turn release copper ions Cu++, which that are highly toxic to the bacteria and higher order living organisms. This phenomenon, might explain natural “antibiotic” properties that are lacking in elements such as tin. To prove or deny this hypothesis we will use next - generation sequencing (NGS) methods to investigate types and growth cycles of bacteria that from bacterial biofilm the on corrosive and non-corrosive samples.

Keywords: bacteria, biofilm, circuit board, copper, corrosion, electronic equipment, organic acids, tin

Procedia PDF Downloads 140

Authors: Lana Dalawr Jalal

Abstract:

This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex three-dimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.

Keywords: obstacle avoidance, particle swarm optimization, three-dimensional path planning unmanned aerial vehicles

Procedia PDF Downloads 387

Authors: D. Hammad, D. P. Tonge

Abstract:

Rheumatoid arthritis (RA) is a disabling and common autoimmune disease during which the body's immune system attacks healthy tissues. This results in complicated and long-lasting actions being carried out by the immune system, which typically only occurs when the immune system encounters a foreign object. In the case of RA, the disease affects millions of people and causes joint inflammation, ultimately leading to the destruction of cartilage and bone. Interestingly, the disease mechanism still remains unclear. It is likely that RA occurs as a result of a complex interplay of genetic and environmental factors including an imbalance in the microorganism population inside our body. The human microbiome or microbiota is an extensive community of microorganisms in and on the bodies of animals, which comprises bacteria, fungi, viruses, and protozoa. Recently, the development of molecular techniques to characterize entire bacterial communities has renewed interest in the involvement of the microbiome in the development and progression of RA. We believe that an imbalance in some of the specific bacterial species in the gut, mouth and other sites may lead to atopobiosis; the translocation of these organisms into the blood, and that this may lead to changes in immune system status. The aim of this study was, therefore, to characterize the microbiome of RA serum samples in comparison to healthy control subjects using 16S rRNA gene amplification and sequencing. Serum samples were obtained from healthy control volunteers and from patients with RA both prior to, and following treatment. The bacterial community present in each sample was identified utilizing V4 region 16S rRNA amplification and sequencing. Bacterial identification, to the lowest taxonomic rank, was performed using a range of bioinformatics tools. Significantly, the proportions of the Lachnospiraceae, Ruminococcaceae, and Halmonadaceae families were significantly increased in the serum of RA patients compared with healthy control serum. Furthermore, the abundance of Bacteroides and Lachnospiraceae nk4a136_group, Lachnospiraceae_UGC-001, RuminococcaceaeUCG-014, Rumnococcus-1, and Shewanella was also raised in the serum of RA patients relative to healthy control serum. These data support the notion of a blood microbiome and reveal RA-associated changes that may have significant implications for biomarker development and may present much-needed opportunities for novel therapeutic development.

Keywords: blood microbiome, gut and oral bacteria, Rheumatoid arthritis, 16S rRNA gene sequencing

Procedia PDF Downloads 109

Authors: Zhang Jianrun, He Tangling

Abstract:

Superposition wave form automotive exhaust bellows is a new type of bellows, which has the characteristics of large compensation, good vibration isolation performance and long life. It has been paid more and more attention and applications in automotive exhaust pipe system. Aiming at the lack of current design methods of superposition wave form automotive exhaust bellows, this paper proposes a response surface parameter optimization method where the fatigue life and vibration transmissibility of the bellows are set as objectives. The parametric modeling of bellow structure is also adopted to achieve the high efficiency in the design. The approach proposed in this paper provides a new way for the design of superposition wave form automotive exhaust bellows. It embodies good engineering application value.

Keywords: superposition wave form, exhaust bellows, optimization, vibration, fatigue life

Procedia PDF Downloads 76

Authors: Suganya Chandrababu, Dhundy Bastola

Abstract:

Like in the gut, the subgingival microbiota plays a crucial role in oral hygiene, health, and cariogenic diseases. Human activities like diet, antibiotics, and periodontal treatments alter the bacterial communities, metabolism, and functions in the oral cavity, leading to a dysbiotic state and changes in the plaques of orthodontic patients. Fixed periodontal appliances hinder oral hygiene and cause changes in the dental plaques influencing the subgingival microbiota. However, the microbial species’ diversity and complexity pose a great challenge in understanding the taxa’s community distribution patterns and their role in oral health. In this research, we analyze the subgingival microbial samples from individuals with fixed dental appliances (metal/clear) using an in silico approach. We employ exploratory hypothesis-driven multivariate and regression analysis to shed light on the microbial community and its functional fluctuations due to dental appliances used and identify risks associated with complex disease phenotypes. Our findings confirm the changes in oral microbiota composition due to the presence and type of fixed orthodontal devices. We identified seven main periodontic pathogens, including Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacteria, and Firmicutes, whose abundances were significantly altered due to the presence and type of fixed appliances used. In the case of metal braces, the abundances of Bacteroidetes, Proteobacteria, Fusobacteria, Candidatus saccharibacteria, and Spirochaetes significantly increased, while the abundance of Firmicutes and Actinobacteria decreased. However, in individuals With clear braces, the abundance of Bacteroidetes and Candidatus saccharibacteria increased. The highest abundance value (P-value=0.004 < 0.05) was observed with Bacteroidetes in individuals with the metal appliance, which is associated with gingivitis, periodontitis, endodontic infections, and odontogenic abscesses. Overall, the bacterial abundances decrease with clear type and increase with metal type of braces. Regression analysis further validated the multivariate analysis of variance (MANOVA) results, supporting the hypothesis that the presence and type of the fixed oral appliances significantly alter the bacterial abundance and composition.

Keywords: oral microbiota, statistical analysis, fixed or-thodontal appliances, bacterial abundance, multivariate analysis, regression analysis

Procedia PDF Downloads 176

Authors: Mamidi Ramakrishna Rao

Abstract:

Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: direct search, DFIG, equivalent circuit parameters, optimization

Procedia PDF Downloads 238

Authors: Ilknur Tuncer, Nihayet Bizsel

Abstract:

The studies in bacterial diversity and antimicrobial resistance in coastal areas are important to understand the variability in the community structures and metabolic activities. In the present study, antimicrobial susceptibility and phylogenetic analysis of bacteria isolated from stations with different depths and influenced by terrestrial and marine fluxes in eastern Aegean Sea were illustrated. 51% of the isolates were found as resistant and 14% showed high MAR index indicating the high-risk sources of contamination in the environment. The resistance and the intermediate levels and high MAR index of the study area were 38–60%, 11–38% and 0–40%, respectively. According to 16S rRNA gene analysis, it was found that the isolates belonged to two phyla Firmicutes and Gammaproteobacteria with the genera Bacillus, Halomonas, Oceanobacillus, Photobacterium, Pseudoalteromonas, Psychrobacter, and Vibrio. 47% of Bacillus strains which were dominant among all isolates were resistant. In addition to phylogenetically diverse bacteria, the variability in resistance, intermediate and high MAR index levels of the study area indicated the effect of geographical differences.

Keywords: bacterial diversity, multiple antibiotic resistance, 16S rRNA genes, Aegean Sea

Procedia PDF Downloads 395

Authors: Fatih Özogul, Esmeray Kuley Boga, Ferhat Kuley, Yesim Özogul

Abstract:

The impact of diethyl ether extract of spices (sumac, cumin, black pepper and red pepper) on growth of Staphylococcus aureus, Salmonella Paratyphi A, Klebsiella pneumoniae, Enterococcus faecalis, Camplylobacter jejuni, Aeromonas hydrophila, Pseudomonas aeruginosa and Yersinia enterocolitica and their biogenic amine production were investigated in tyrosine decarboxylase broth. Sumac extract generally had the highest activity to inhibit bacterial growth compared to other extracts, although antimicrobial effect of extracts used varied depending on bacterial strains. Sumac extract resulted in 3.34 and 2.54 log reduction for Y. enterocolitica and Camp. jejuni growth, whilst red pepper extract induced 0.65, 0.41 and 0.34 log reduction for growth of Y. enterocolitica, S. Paratyphi A and Staph. aureus, respectively. Spice extracts significantly inhibited ammonia production by bacteria (P < 0.05). Eleven and nine fold reduction on ammonia production by S. Paratyphi A and Staph. aureus were observed in the presence of sumac extract. Dopamine, agmatine, tyramine, serotonin and TMA were main amines produced by bacteria. Tyramine production by food-borne-pathogens was more than 10 mg/L, whereas histamine accumulated below 52 mg/L. The effect of spice extracts on biogenic amine production varied depending on amino acid decarboxylase broth, spice type, bacterial strains and specific amine, although cumin extract generally increased biogenic amine production by bacteria.

Keywords: antimicrobials, biogenic amines, food-borne pathogens, spice extracts

Procedia PDF Downloads 297

Authors: Haider M. Alsaeq

Abstract:

The present research is an attempt to figure out the best configuration of composite cylindrical shells of the sandwich type, i.e. the lightest design of such shells required to sustain a certain load over a certain area. The optimization is based on elastic-plastic geometrically nonlinear incremental-iterative finite element analysis. The nine-node degenerated curved shell element is used in which five degrees of freedom are specified at each nodal point, with a layered model. The formulation of the geometrical nonlinearity problem is carried out using the well-known total Lagrangian principle. For the structural optimization problem, which is dealt with as a constrained nonlinear optimization, the so-called Modified Hooke and Jeeves method is employed by considering the weight of the shell as the objective function with stress and geometrical constraints. It was concluded that the optimum design of composite sandwich cylindrical shell that have a rigid polyurethane foam core and steel facing occurs when the area covered by the shell becomes almost square with a ratio of core thickness to facing thickness lies between 45 and 49, while the optimum height to length ration varies from 0.03 to 0.08 depending on the aspect ratio of the shell and its boundary conditions.

Keywords: composite structure, cylindrical shell, optimization, non-linear analysis, finite element

Procedia PDF Downloads 380

Authors: Richardson Ciguene, Bertrand Marron, Nicolas Habert

Abstract:

Today, more and more consumers are purchasing their products and services online. At the same time, the penetration rate of very small and medium-sized businesses on marketplaces continues to increase, which has the direct impact of intensifying competition between sellers. Thus, only the best-optimized deals are ranked well by algorithms and are visible to consumers. However, it is almost impossible to know all the Brand Content rules and criteria established by marketplaces, which is essential to optimizing their product sheets, especially since these rules change constantly. In this paper, we propose to detail this question of Brand Content optimization by taking into account the case of Amazon in order to capture the scientific dimension behind such a subject. In a second step, we will present the genesis of our research project, DEEPERFECT, which aims to set up original methods and effective tools in order to help sellers present on marketplaces in the optimization of their branded content.

Keywords: e-commerce, scoring, marketplace, Amazon, brand content, product sheets

Procedia PDF Downloads 107

Authors: Waseem Shahzad, Ayesha Tahir Khan, Hamid Hussain Awan

Abstract:

Ant-Miner algorithm that lies under ACO algorithms is used to extract knowledge from data in the form of rules. A variant of Ant-Miner algorithm named as cAnt-MinerPB is used to generate list of rules using pittsburgh approach in order to maintain the rule interaction among the rules that are generated. In this paper, we propose a parallel Ant MinerPB in which Ant colony optimization algorithm runs parallel. In this technique, a data set is divided vertically (i-e attributes) into different subsets. These subsets are created based on the correlation among attributes using Mutual Information (MI). It generates rules in a parallel manner and then merged to form a final list of rules. The results have shown that the proposed technique achieved higher accuracy when compared with original cAnt-MinerPB and also the execution time has also reduced.

Keywords: ant colony optimization, parallel Ant-MinerPB, vertical partitioning, classification rule discovery

Procedia PDF Downloads 276

Authors: M. C. Lin, C. W. Su

Abstract:

The paper investigates the optimization analysis to the heat exchanger design, mainly with response surface method and genetic algorithm to explore the relationship between optimal fluid flow velocity and temperature of the heat exchanger using field synergy principle. First, finite volume method is proposed to calculate the flow temperature and flow rate distribution for numerical analysis. We identify the most suitable simulation equations by response surface methodology. Furthermore, a genetic algorithm approach is applied to optimize the relationship between fluid flow velocity and flow temperature of the heat exchanger. The results show that the field synergy angle plays vital role in the performance of a true heat exchanger.

Keywords: optimization analysis, field synergy, heat exchanger, genetic algorithm

Procedia PDF Downloads 286

Authors: Jumazulhisham Abdul Shukor, Mohd. Sazali Said, Roshanizah Harun, Shuib Husin, Ahmad Razlee Ab Kadir

Abstract:

This paper applies Taguchi Optimization Method in determining the best machining parameters for pocket milling process on Polypropylene (PP) using CNC milling machine where the surface roughness is considered and the Carbide inserts cutting tool are used. Three machining parameters; speed, feed rate and depth of cut are investigated along three levels; low, medium and high of each parameter (Taguchi Orthogonal Arrays). The setting of machining parameters were determined by using Taguchi Method and the Signal-to-Noise (S/N) ratio are assessed to define the optimal levels and to predict the effect of surface roughness with assigned parameters based on L9. The final experimental outcomes are presented to prove the optimization parameters recommended by manufacturer are accurate.

Keywords: inserts, milling process, signal-to-noise (S/N) ratio, surface roughness, Taguchi Optimization Method

Procedia PDF Downloads 610

Authors: Linh Nguyen Tung, Anh Truong Viet, Nghien Nguyen Ba, Chuong Trinh Trong

Abstract:

This paper proposes a reconfiguration methodology based on a continuous genetic algorithm (CGA) and particle swarm optimization (PSO) for minimizing active power loss and minimizing voltage deviation. Both algorithms are adapted using graph theory to generate feasible individuals, and the modified crossover is used for continuous variable of CGA. To demonstrate the performance and effectiveness of the proposed methods, a comparative analysis of CGA with PSO for network reconfiguration, on 33-node and 119-bus radial distribution system is presented. The simulation results have shown that both CGA and PSO can be used in the distribution network reconfiguration and CGA outperformed PSO with significant success rate in finding optimal distribution network configuration.

Keywords: distribution network reconfiguration, particle swarm optimization, continuous genetic algorithm, power loss reduction, voltage deviation

Procedia PDF Downloads 166

Authors: Mitchell Gohnert

Abstract:

This paper reviews some fundamental concepts of structural optimization, which is based on the type of materials used in construction and the shape of the structure. The first step in structural optimization is to break down all internal forces in a structure into fundamental stresses, which are tensions and compressions. Knowing the stress patterns directs our selection of structural shapes, and the most appropriate type of construction material. In our selection of materials, it is essential to understand all construction materials have flaws, or micro-cracks, which reduce the capacity of the material, especially when subjected to tensions. Because of material defects, many construction materials perform significantly better when subjected to compressive forces. Structures are also more efficient if bending moments are eliminated. Bending stresses produce high peak stresses at each face of the member, and therefore substantially more material is required to resist bending. The shape of the structure also has a profound effect on stress levels. Stress may be reduced dramatically by simply changing the shape. Catenary, triangular and linear shapes are the fundamental structural forms to achieve optimal stress flow. If the natural flow of stress matches the shape of the structures, the most optimal shape is determined.

Keywords: Shell structures, structural optimization, Stress flow, Construction materials, catenary shapes

Procedia PDF Downloads 15

Authors: Xiaoping Qiu, Binci You, Yue Hu

Abstract:

The executive time of the workflow network has an important effect on the efficiency of the business process. In this paper, the activity executive time is divided into the service time and the waiting time, then the lead time can be extracted from the waiting time. The executive time formulas of the three basic structures in the workflow network are deduced based on the activity lead time. Taken the process of e-commerce logistics as an example, insert appropriate lead time for key activities by using Petri net, and the executive time optimization model is built to minimize the waiting time with the time-cost constraints. Then the solution program-using VC++6.0 is compiled to get the optimal solution, which reduces the waiting time of key activities in the workflow, and verifies the role of lead time in the timeliness of e-commerce logistics.

Keywords: electronic business, execution time, lead time, optimization model, petri net, time workflow network

Procedia PDF Downloads 156

Authors: Christoph Ramsauer, Jaydeep Karandikar, Tony Schmitz, Friedrich Bleicher

Abstract:

Machining stability is an important limitation to discrete part machining. In this work, a networked implementation of milling stability optimization with Bayesian learning is presented. The milling process was monitored with a wireless sensory tool holder instrumented with an accelerometer at the Vienna University of Technology, Vienna, Austria. The recorded data from a milling test cut is used to classify the cut as stable or unstable based on the frequency analysis. The test cut result is fed to a Bayesian stability learning algorithm at the University of Tennessee, Knoxville, Tennessee, USA. The algorithm calculates the probability of stability as a function of axial depth of cut and spindle speed and recommends the parameters for the next test cut. The iterative process between two transatlantic locations repeats until convergence to a stable optimal process parameter set is achieved.

Keywords: machining stability, machine learning, sensor, optimization

Procedia PDF Downloads 189

Authors: Luis Guilherme Resende Santos, Ido Nevat, Leslie Norford

Abstract:

The Urban Heat Island (UHI) is characterized by increased air temperatures in urban areas compared to undeveloped rural surrounding environments. With urbanization and densification, the intensity of UHI increases, bringing negative impacts on livability, health and economy. In order to reduce those effects, it is required to take into consideration design factors when planning future developments. Given design constraints such as population size and availability of area for development, non-trivial decisions regarding the buildings’ dimensions and their spatial distribution are required. We develop a framework for optimization of urban design in order to jointly minimize UHI intensity and buildings’ energy consumption. First, the design constraints are defined according to spatial and population limits in order to establish realistic boundaries that would be applicable in real life decisions. Second, the tools Urban Weather Generator (UWG) and EnergyPlus are used to generate outputs of UHI intensity and total buildings’ energy consumption, respectively. Those outputs are changed based on a set of variable inputs related to urban morphology aspects, such as building height, urban canyon width and population density. Lastly, an optimization problem is cast where the utility function quantifies the performance of each design candidate (e.g. minimizing a linear combination of UHI and energy consumption), and a set of constraints to be met is set. Solving this optimization problem is difficult, since there is no simple analytic form which represents the UWG and EnergyPlus models. We therefore cannot use any direct optimization techniques, but instead, develop an indirect “black box” optimization algorithm. To this end we develop a solution that is based on stochastic optimization method, known as the Cross Entropy method (CEM). The CEM translates the deterministic optimization problem into an associated stochastic optimization problem which is simple to solve analytically. We illustrate our model on a typical residential area in Singapore. Due to fast growth in population and built area and land availability generated by land reclamation, urban planning decisions are of the most importance for the country. Furthermore, the hot and humid climate in the country raises the concern for the impact of UHI. The problem presented is highly relevant to early urban design stages and the objective of such framework is to guide decision makers and assist them to include and evaluate urban microclimate and energy aspects in the process of urban planning.

Keywords: building energy consumption, stochastic optimization, urban design, urban heat island, urban weather generator

Procedia PDF Downloads 113

Authors: M. R. Al-Rashidi, K. M. El-Naggar, M. F. Al-Hajri

Abstract:

The fuel cost function describes the electric power generation-cost relationship in thermal plants, hence, it sheds light on economical aspects of power industry. Different models have been proposed to describe this relationship with the quadratic function model being the most popular one. Parameters of second order fuel cost function are estimated in this paper using cuckoo search algorithm. It is a new population based meta-heuristic optimization technique that has been used in this study primarily as an accurate estimation tool. Its main features are flexibility, simplicity, and effectiveness when compared to other estimation techniques. The parameter estimation problem is formulated as an optimization one with the goal being minimizing the error associated with the estimated parameters. A case study is considered in this paper to illustrate cuckoo search promising potential as a valuable estimation and optimization technique.

Keywords: cuckoo search, parameters estimation, fuel cost function, economic dispatch

Procedia PDF Downloads 561

Authors: Shonak Bansal, Prince Jain, Arun Kumar Singh, Neena Gupta

Abstract:

Recently nature–inspired algorithms have widespread use throughout the tough and time consuming multi–objective scientific and engineering design optimization problems. In this paper, we present extended forms of firefly algorithm to find optimal Golomb ruler (OGR) sequences. The OGRs have their one of the major application as unequally spaced channel–allocation algorithm in optical wavelength division multiplexing (WDM) systems in order to minimize the adverse four–wave mixing (FWM) crosstalk effect. The simulation results conclude that the proposed optimization algorithm has superior performance compared to the existing conventional computing and nature–inspired optimization algorithms to find OGRs in terms of ruler length, total optical channel bandwidth and computation time.

Keywords: channel allocation, conventional computing, four–wave mixing, nature–inspired algorithm, optimal Golomb ruler, lévy flight distribution, optimization, improved multi–objective firefly algorithms, Pareto optimal

Procedia PDF Downloads 303

Authors: Ahmed Ishtiaq, Maeeda Khalid, Umair Sajjad

Abstract:

In the fast-moving world, information is the key to success. If information is easily available, then it makes work easy. The Internet is the biggest collection and source of information nowadays, and with every single day, the data on internet increases, and it becomes difficult to find required data. Everyone wants to make his/her website at the top of search results. This can be possible when you have applied some techniques of SEO inside your application or outside your application, which are two types of SEO, onsite and offsite SEO. SEO is an abbreviation of Search Engine Optimization, and it is a set of techniques, methods to increase users of a website on World Wide Web or to rank up your website in search engine indexing. In this paper, we have compared different techniques of Onpage and Offpage SEO, and we have suggested many things that should be changed inside webpage, outside web page and mentioned some most powerful and search engine considerable elements and techniques in both types of SEO in order to gain high ranking on Search Engine.

Keywords: auto-suggestion, search engine optimization, SEO, query, web mining, web crawler

Procedia PDF Downloads 124