947 resultados para Bacterial foraging algorithm


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Microbiological studies on the incidence, behaviour, activity and ecological implications of marine micro~organisms, particularly microbial pathogens in coastal waters and estuaries exhibit the increasing concern and awareness of environmental impacts on health and wealth. Marine microbiologists have been active in investigating on the distribution, kinds of organisms and their activity in the environment. However, informations on the effect of environment on the ecology or on the distribution (spatial/temporal) of microbial comunity and competition among groups inhabiting the ecosystem are sparE§L Estuarine environment are complex with respect to diversity of habitats, variation in physicochemical parameters and contamination by terrestrial bacterial species. Being the organisms of‘public health significance, ecological studies on total coliforms, faecal coliforms, faecal streptococci, §. ggli and X. parahaemolyticus have great relevance as studies of these types would provide a wealth of information to environmentalists and to fishery industry. In order to evalé%e the status, role and significance of potentially hazardous bacterial species in natural environment it is necessary to monitor the ecology of such organisms systematically in relation to physico-chemical parameters

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Assembly job shop scheduling problem (AJSP) is one of the most complicated combinatorial optimization problem that involves simultaneously scheduling the processing and assembly operations of complex structured products. The problem becomes even more complicated if a combination of two or more optimization criteria is considered. This thesis addresses an assembly job shop scheduling problem with multiple objectives. The objectives considered are to simultaneously minimizing makespan and total tardiness. In this thesis, two approaches viz., weighted approach and Pareto approach are used for solving the problem. However, it is quite difficult to achieve an optimal solution to this problem with traditional optimization approaches owing to the high computational complexity. Two metaheuristic techniques namely, genetic algorithm and tabu search are investigated in this thesis for solving the multiobjective assembly job shop scheduling problems. Three algorithms based on the two metaheuristic techniques for weighted approach and Pareto approach are proposed for the multi-objective assembly job shop scheduling problem (MOAJSP). A new pairing mechanism is developed for crossover operation in genetic algorithm which leads to improved solutions and faster convergence. The performances of the proposed algorithms are evaluated through a set of test problems and the results are reported. The results reveal that the proposed algorithms based on weighted approach are feasible and effective for solving MOAJSP instances according to the weight assigned to each objective criterion and the proposed algorithms based on Pareto approach are capable of producing a number of good Pareto optimal scheduling plans for MOAJSP instances.

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Decimal multiplication is an integral part of financial, commercial, and internet-based computations. A novel design for single digit decimal multiplication that reduces the critical path delay and area for an iterative multiplier is proposed in this research. The partial products are generated using single digit multipliers, and are accumulated based on a novel RPS algorithm. This design uses n single digit multipliers for an n × n multiplication. The latency for the multiplication of two n-digit Binary Coded Decimal (BCD) operands is (n + 1) cycles and a new multiplication can begin every n cycle. The accumulation of final partial products and the first iteration of partial product generation for next set of inputs are done simultaneously. This iterative decimal multiplier offers low latency and high throughput, and can be extended for decimal floating-point multiplication.

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Considering the extent of warming in the artic region and the resultant changes in the dynamic marine enviornments there is a need to monitor the bacterial diversity in the fjord enviornments especially in terms of cultivable bacteria. The present study reports the diversity of cultivable hetrotrophic bacteria from the water and sediment samples of kongsfjord their growth responses to important enviornmental variables and ability to produce industrially important hydrolytic enzymes.

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In natural systems phytoplankton interact with planktonic (free living) and attached epiphytic bacteria both synergistically and antagonistically. The specificity of the association with micro algae and bacteria differs in terms of adhesion mechanisms and metabolic cooperation. Present research was carried out to study the effect of bacterial isolates namely Bacillus sp. and Pseudomonas sp. from algal culture systems on the growth of micro algae such as Chaetoceros calcitrans and Nannochloropsis oculata. C. calcitrans (F= 15.34; P<0.05) and N. oculata (F=12.52; P<0.05) showed significantly higher growth, in treatments with Bacillus sp. and Pseudomonas sp when compared to control.

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Shrimp grow out systems under zero water exchange mode demand constant remediation of total ammonia nitrogen (TAN) andNO2 −–Nto protect the crop. To address this issue, aninexpensive and user-friendly technology using immobilized nitrifying bacterial consortia (NBC) as bioaugmentors has been developed and proposed for adoption in shrimp culture systems. Indigenous NBC stored at 4 °C were activated at room temperature (28 °C) and cultured in a 2 L bench top fermentor. The consortia, after enumeration by epifluorescence microscopy,were immobilized on delignifiedwood particles of a soft wood tree Ailantus altissima (300–1500 μm) having a surface area of 1.87m2 g−1. Selection of wood particle as substratumwas based on adsorption of NBC on to the particles, biofilm formation, and their subsequent nitrification potential. The immobilization could be achievedwithin 72 h with an initial cell density of 1×105 cells mL−1. On experimenting with the lowest dosage of 0.2 g (wet weight) immobilized NBC in 20 L seawater, a TAN removal rate of 2.4 mg L−1 within three days was observed. An NBC immobilization device could be developed for on site generation of the bioaugmentor preparation as per requirement. The product of immobilization never exhibited lag phase when transferred to fresh medium. The extent of nitrification in a simulated systemwas two times the rate observed in the control systems suggesting the efficacy in real life situations. The products of nitrification in all experiments were undetectable due to denitrifying potency, whichmade the NBC an ideal option for biological nitrogen removal. The immobilized NBC thus generated has been named TANOX (Total Ammonia Nitrogen Oxidizer)

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This study shows that the disease resistance and survival rate of Penaeus monodon in a larval rearing systems can be enhanced by supplementing with antagonistic or non-antagonistic probiotics. The antagonistic mode of action of Pseudomonas MCCB 102 and MCCB 103 against vibrios was demonstrated in larval mesocosm with cultures having su⁄cient concentration of antagonistic compounds in their culture supernatant. Investigations on the antagonistic properties of Bacillus MCCB 101, Pseudomonas MCCB 102 and MCCB 103 and Arthrobacter MCCB 104 against Vibrio harveyi MCCB111under in vitro conditions revealed that Pseudomonas MCCB 102 and MCCB 103 were inhibitory to the pathogen.These inhibitory propertieswere further con¢rmed in the larval rearing systems of P. monodon. All these four probionts signi¢cantly improved larval survival in long-term treatments as well as when challengedwith a pathogenic strain ofV. harveyiMCCB111. We could demonstrate that Pseudomonas MCCB 102 andMCCB103 accorded disease resistance and a higher survival rate in P. monodon larval rearing systems throughactive antagonism of vibrios,whereas Bacillus MCCB 101 and Arthrobacter MCCB 104 functioned as probiotics through immunostimulatory and digestive enzyme-supporting modes of action.

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Two distinct nitrifying bacterial consortia, namely an ammonia oxidizing non-penaeid culture (AMO NPCU-1) and an ammonia oxidizing penaeid culture (AMOPCU-1), have been mass produced in a nitrifying bacterial consortia production unit (NBCPU). The consortia, maintained at 4 C were activated and cultured in a 2 l fermentor initially. At this stage the net biomass (0.105 and 0.112 g/l), maximum specific growth rate (0.112 and 0.105/h) and yield coefficients (1.315 and 2.08) were calculated respectively, for AMONPCU-1 and AMOPCU-1 on attaining stationary growth phase. Subsequently on mass production in a 200 l NBCPU under optimized culture conditions, the total amounts of NH4 ?–N removed by AMONPCU-1 and AMOPCU-1 were 1.948 and 1.242 g/l within 160 and 270 days, respectively. Total alkalinity reduction of 11.7–14.4 and 7.5–9.1 g/l were observed which led to the consumption of 78 and 62 g Na2CO3. The yield coefficient and biomass of AMONPCU-1 were 0.67 and 125.3 g/l and those of AMOPCU-1 were 1.23 and 165 g/l. The higher yield coefficient and growth rate of AMOPCU-1 suggest better energy conversion efficiency and higher CO2 fixation potential. Both of the consortia were dominated by Nitrosomonas-like organisms. The consortia may find application in the establishment of nitrification within marine and brackish water culture systems.

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Two ammonia oxidizing (AMOPCU-1 and AMONPCU-1) and two nitrite oxidizing (NIOPCU-1 and NIONPCU-1) consortia for activating nitrifying bioreactors and thereby establishing nitrification in penaeid and non-penaeid hatchery systems were developed by enrichment. For further amplification of the consortia a simple medium having seawater (either salinity 30 ‰ or 15 ‰) as base, supplemented with NH4+-N/NO2--N and PO4- and pH adjusted to 8 was identified. During the amplification in a fermentor the consortia exhibited excessive wall growth and diminished their yield coefficient posing difficulty in harvesting the cells completely. The consortia consisted of both Gram negative and Gram-positive bacterial cells embedded in a mucilaginous matrix of glycocalyx - like material presumably composed of polysaccharides. The consortia besides being useful in activating nitrifying bioreactors developed for shrimp/prawn hatchery systems can also be used as bioaugmentors in the bioremediation of ammonia and nitrite toxicity in aquaculture systems.

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The addition of commercial nitrifying bacterial products has resulted in significant improvement of nitrification efficiency in recirculating aquaculture systems (RAS). We developed two nitrifying bacterial consortia (NBC) from marine and brackish water as start up cultures for immobilizing commercialized nitrifying bioreactors for RAS. In the present study, the community compositions of the NBC were analyzed by universal 16S rRNA gene and bacterial amoA gene sequencing and fluorescence in situ hybridization (FISH). This study demonstrated that both the consortia involved autotrophic nitrifiers, denitrifiers as well as heterotrophs. Abundant taxa of the brackish water heterotrophic bacterial isolates were Paenibacillus and Beijerinckia spp. whereas in the marine consortia they were Flavobacterium, Cytophaga and Gramella species. The bacterial amoA clones were clustered together with high similarity to Nitrosomonas sp. and uncultured beta Proteobacteria. FISH analysis detected ammonia oxidizers belonging to b subclass of proteobacteria and Nitrosospira sp. in both the consortia, and Nitrosococcus mobilis lineage only in the brackish water consortium and the halophilic Nitrosomonas sp. only in the marine consortium. However, nitrite oxidizers, Nitrobacter sp. and phylum Nitrospira were detected in both the consortia. The metabolites from nitrifiers might have been used by heterotrophs as carbon and energy sources making the consortia a stable biofilm.

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The composition and variability of heterotrophic bacteria along the shelf sediments of south west coast of India and its relationship with the sediment biogeochemistry was investigated. The bacterial abundance ranged from 1.12 x 103 – 1.88 x 106 CFU g-1 dry wt. of sediment. The population showed significant positive correlation with silt (r = 0.529, p< 0.05), organic carbon (OC) (r = 0.679, p< 0.05), total nitrogen (TN) (r = 0.638, p< 0.05), total protein (TPRT) (r = 0.615, p< 0.05) and total carbohydrate (TCHO) (r = 0.675, p< 0.05) and significant negative correlation with sand (r = -0.488, p< 0.05). Community was mainly composed of Bacillus, Alteromonas, Vibrio, Coryneforms, Micrococcus, Planococcus, Staphylococcus, Moraxella, Alcaligenes, Enterobacteriaceae, Pseudomonas, Acinetobacter, Flavobacterium and Aeromonas. BIOENV analysis explained the best possible environmental parameters i.e., carbohydrate, total nitrogen, temperature, pH and sand at 50m depth and organic matter, BPC, protein, lipid and temperature at 200m depth controlling the distribution pattern of heterotrophic bacterial population in shelf sediments. The Principal Component Analysis (PCA) of the environmental variables showed that the first and second principal component accounted for 65% and 30.6% of the data variance respectively. Canonical Correspondence Analysis (CCA) revealed a strong correspondence between bacterial distribution and environmental variables in the study area. Moreover, non-metric MDS (Multidimensional Scaling) analysis demarcated the northern and southern latitudes of the study area based on the bioavailable organic matter

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Decision trees are very powerful tools for classification in data mining tasks that involves different types of attributes. When coming to handling numeric data sets, usually they are converted first to categorical types and then classified using information gain concepts. Information gain is a very popular and useful concept which tells you, whether any benefit occurs after splitting with a given attribute as far as information content is concerned. But this process is computationally intensive for large data sets. Also popular decision tree algorithms like ID3 cannot handle numeric data sets. This paper proposes statistical variance as an alternative to information gain as well as statistical mean to split attributes in completely numerical data sets. The new algorithm has been proved to be competent with respect to its information gain counterpart C4.5 and competent with many existing decision tree algorithms against the standard UCI benchmarking datasets using the ANOVA test in statistics. The specific advantages of this proposed new algorithm are that it avoids the computational overhead of information gain computation for large data sets with many attributes, as well as it avoids the conversion to categorical data from huge numeric data sets which also is a time consuming task. So as a summary, huge numeric datasets can be directly submitted to this algorithm without any attribute mappings or information gain computations. It also blends the two closely related fields statistics and data mining

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This work proposes a parallel genetic algorithm for compressing scanned document images. A fitness function is designed with Hausdorff distance which determines the terminating condition. The algorithm helps to locate the text lines. A greater compression ratio has achieved with lesser distortion

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Prodigiosin is known for its immunomodulatory, antibacterial, antimycotic, antimalarial, algicidal and anticancer activities. Here, we reported the evaluation of prodigiosin pigment as a dyeing agent in rubber latex, paper and polymethyl methacrylate (PMMA) so that it can be considered as an alternative to synthetic pigments. Maximum color shade was obtained in rubber sheet prepared with 0.5 parts per hundred gram of rubber (phr) pigment and PMMA sheet incorporated with 0.08 μg pigment. Results indicate scope for utilization of prodigiosin as dye for PMMA and rubber and also prodigiosin dyed paper as a pH indicator. Further, being a natural and water insoluble pigment, it is ecofriendly

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Reinforcement Learning (RL) refers to a class of learning algorithms in which learning system learns which action to take in different situations by using a scalar evaluation received from the environment on performing an action. RL has been successfully applied to many multi stage decision making problem (MDP) where in each stage the learning systems decides which action has to be taken. Economic Dispatch (ED) problem is an important scheduling problem in power systems, which decides the amount of generation to be allocated to each generating unit so that the total cost of generation is minimized without violating system constraints. In this paper we formulate economic dispatch problem as a multi stage decision making problem. In this paper, we also develop RL based algorithm to solve the ED problem. The performance of our algorithm is compared with other recent methods. The main advantage of our method is it can learn the schedule for all possible demands simultaneously.