Search results for: Fed batch bioprocess

Authors: Mihai Caramihai, Irina Severin

Abstract:

Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate.

Keywords: Fed batch bioprocess, mass-balance model, fuzzy control

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Authors: Mihai Caramihai Ana A Chirvase, Irina Severin

Abstract:

Bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying, in particular, when they are operating in fed batch mode. The research objective of this study was to develop an appropriate control method for a complex bioprocess and to implement it on a laboratory plant. Hence, an intelligent control structure has been designed in order to produce biomass and to maximize the specific growth rate.

Keywords: Fed batch bioprocess, mass-balance model, fuzzy control.

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Authors: Mihai Caramihai, Irina Severin, Ana Aurelia Chirvase, Adrian Onu, Cristina Tanase, Camelia Ungureanu

Abstract:

An immunomodulator bioproduct is prepared in a batch bioprocess with a modified bacterium Pseudomonas aeruginosa. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The optimal bioprocess parameters were determined: temperature – 37 0C, agitation speed - 300 rpm, aeration rate – 40 L/min, pressure – 0.5 bar, Dow Corning Antifoam M-max. 4 % of the medium volume, duration - 6 hours. This kind of bioprocesses are appreciated as difficult to control because their dynamic behavior is highly nonlinear and time varying. The aim of the paper is to present (by comparison) different models based on experimental data. The analysis criteria were modeling error and convergence rate. The estimated values and the modeling analysis were done by using the Table Curve 2D. The preliminary conclusions indicate Andrews-s model with a maximum specific growth rate of the bacterium in the range of 0.8 h-1.

Keywords: bioprocess modeling, Pseudomonas aeruginosa, kinetic models,

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Authors: M. Caramihai, Irina Severin

Abstract:

This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: Bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques.

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Authors: Nagmani Lnu

Abstract:

Often, quality engineering refers to testing the applications that either have a User Interface (UI) or an Application Programming Interface (API). We often find mature test practices, standards, and automation regarding UI or API testing. However, another kind is present in almost all types of industries that deal with data in bulk and often get handled through something called a batch application. This is primarily an offline application companies develop to process large data sets that often deal with multiple business rules. The challenge gets more prominent when we try to automate batch testing. This paper describes the approaches taken to test a batch application from a financial industry to test the payment settlement process (a critical use case in all kinds of FinTech companies), resulting in 100% test automation in test creation and test execution. One can follow this approach for any other batch use cases to achieve a higher efficiency in their testing process.

Keywords: Batch testing, batch test automation, batch test strategy, payments testing, payments settlement testing.

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte

Abstract:

This paper proposes a bioprocess optimization procedure based on Relevance Vector Regression models and evolutionary programming technique. Relevance Vector Regression scheme allows developing a compact and stable data-based process model avoiding time-consuming modeling expenses. The model building and process optimization procedure could be done in a half-automated way and repeated after every new cultivation run. The proposed technique was tested in a simulated mammalian cell cultivation process. The obtained results are promising and could be attractive for optimization of industrial bioprocesses.

Keywords: Bioprocess optimization, Evolutionary programming, Relevance Vector Regression.

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Authors: Vitalice K. Oduol, C. Ardil

Abstract:

The transient analysis of a queuing system with fixed-size batch Poisson arrivals and a single server with exponential service times is presented. The focus of the paper is on the use of the functions that arise in the analysis of the transient behaviour of the queuing system. These functions are shown to be a generalization of the modified Bessel functions of the first kind, with the batch size B as the generalizing parameter. Results for the case of single-packet arrivals are obtained first. The similarities between the two families of functions are then used to obtain results for the general case of batch arrival queue with a batch size larger than one.

Keywords: batch arrivals, generalized Bessel functions, queuetransient analysis, time-varying probabilities.

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Authors: Nikhil, Ari Visa, Chin-Chao Chen, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja

Abstract:

A predictive clustering hybrid regression (pCHR) approach was developed and evaluated using dataset from H2- producing sucrose-based bioreactor operated for 15 months. The aim was to model and predict the H2-production rate using information available about envirome and metabolome of the bioprocess. Selforganizing maps (SOM) and Sammon map were used to visualize the dataset and to identify main metabolic patterns and clusters in bioprocess data. Three metabolic clusters: acetate coupled with other metabolites, butyrate only, and transition phases were detected. The developed pCHR model combines principles of k-means clustering, kNN classification and regression techniques. The model performed well in modeling and predicting the H2-production rate with mean square error values of 0.0014 and 0.0032, respectively.

Keywords: Biohydrogen, bioprocess modeling, clusteringhybrid regression.

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Authors: Jožef Ritonja

Abstract:

The biochemical industry is one of the most important modern industries. Biochemical reactors are crucial devices of the biochemical industry. The essential bioprocess carried out in bioreactors is the fermentation process. A thorough insight into the fermentation process and the knowledge how to control it are essential for effective use of bioreactors to produce high quality and quantitatively enough products. The development of the control system starts with the determination of a mathematical model that describes the steady state and dynamic properties of the controlled plant satisfactorily, and is suitable for the development of the control system. The paper analyses the fermentation process in bioreactors thoroughly, using existing mathematical models. Most existing mathematical models do not allow the design of a control system for controlling the fermentation process in batch bioreactors. Due to this, a mathematical model was developed and presented that allows the development of a control system for batch bioreactors. Based on the developed mathematical model, a control system was designed to ensure optimal response of the biochemical quantities in the fermentation process. Due to the time-varying and non-linear nature of the controlled plant, the conventional control system with a proportional-integral-differential controller with constant parameters does not provide the desired transient response. The improved adaptive control system was proposed to improve the dynamics of the fermentation. The use of the adaptive control is suggested because the parameters’ variations of the fermentation process are very slow. The developed control system was tested to produce dairy products in the laboratory bioreactor. A carbon dioxide concentration was chosen as the controlled variable. The carbon dioxide concentration correlates well with the other, for the quality of the fermentation process in significant quantities. The level of the carbon dioxide concentration gives important information about the fermentation process. The obtained results showed that the designed control system provides minimum error between reference and actual values of carbon dioxide concentration during a transient response and in a steady state. The recommended control system makes reference signal tracking much more efficient than the currently used conventional control systems which are based on linear control theory. The proposed control system represents a very effective solution for the improvement of the milk fermentation process.

Keywords: Bioprocess engineering, biochemical reactor, fermentation process, modeling, adaptive control.

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Authors: Seyed Ali Jafari, Mohammad Ghomi Avili, Emad Benhelal

Abstract:

In this study, a mathematical model was proposed and the accuracy of this model was assessed to predict the growth of Pseudomonas aeruginosa and rhamnolipid production under nitrogen limiting (sodium nitrate) fed-batch fermentation. All of the parameters used in this model were achieved individually without using any data from the literature. The overall growth kinetic of the strain was evaluated using a dual-parallel substrate Monod equation which was described by several batch experimental data. Fed-batch data under different glycerol (as the sole carbon source, C/N=10) concentrations and feed flow rates were used to describe the proposed fed-batch model and other parameters. In order to verify the accuracy of the proposed model several verification experiments were performed in a vast range of initial glycerol concentrations. While the results showed an acceptable prediction for rhamnolipid production (less than 10% error), in case of biomass prediction the errors were less than 23%. It was also found that the rhamnolipid production by P. aeruginosa was more sensitive at low glycerol concentrations. Based on the findings of this work, it was concluded that the proposed model could effectively be employed for rhamnolipid production by this strain under fed-batch fermentation on up to 80 g l- 1 glycerol.

Keywords: Fed-batch culture, glycerol, kinetic parameters, modelling, Pseudomonas aeruginosa, rhamnolipid.

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Authors: Shan Gao

Abstract:

This paper treats a discrete-time finite buffer batch arrival queue with a single working vacation and partial batch rejection in which the inter-arrival and service times are, respectively, arbitrary and geometrically distributed. The queue is analyzed by using the supplementary variable and the imbedded Markov-chain techniques. We obtain steady-state system length distributions at prearrival, arbitrary and outside observer-s observation epochs. We also present probability generation function (p.g.f.) of actual waiting-time distribution in the system and some performance measures.

Keywords: Discrete-time, finite buffer, single working vacation, batch arrival, partial rejection.

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Authors: M.V.R.K Sarma, Krishna Saharan, Lalit Kumar, Ashwani Gautam, Avhijeet Kapoor, Nishant Srivastava, Vikram Sahai, V.S Bisaria

Abstract:

The fluorescent pseudomonad strain R81 is a root colonizing rhizobacteria which promotes the growth of many plants by various mechanisms. Its broth containing siderophore (ironchelating compound) and 2,4- diacetyl phloroglucinol (DAPG) is used for preparing bioinoculant formulations for agronomical applications. Glycerol was found to be the best carbon source for improved biomass production. Splitting of nitrogen source to NH4Cl and urea had a stabilizing effect on pH during batch cultivation. Ltryptophan at 0.5 % in the medium increased the siderophore production to 850 mg/l. During batch cultivation of the strain in a bioreactor, a maximum of 4 g/l of dry cell mass, 1.8 g/l of siderophore and 20 mg/l of DAPG was achieved when glycerol was 15 g/l and C/N ratio was maintained at 12.5. In case of intermittent feeding of fresh medium during fed-batch cultivation, the dry cell mass was increased to 25 g/l with improved production of DAPG to 70 mg/l.

Keywords: Batch cultivation, Fed-batch cultivation, fluorescent pseudomonad, Metabolites

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Authors: R. Khaniki, M.B. Menhaj, H. Eliasi

Abstract:

This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.

Keywords: Generalized Predictive Control (GPC), TemperatureControl, Global Linearizing Control (GLC), Batch Reactor.

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Authors: R. Khaniki, M.B. Menhaj, H. Eliasi

Abstract:

This paper describes the application of a model predictive controller to the problem of batch reactor temperature control. Although a great deal of work has been done to improve reactor throughput using batch sequence control, the control of the actual reactor temperature remains a difficult problem for many operators of these processes. Temperature control is important as many chemical reactions are sensitive to temperature for formation of desired products. This controller consist of two part (1) a nonlinear control method GLC (Global Linearizing Control) to create a linear model of system and (2) a Model predictive controller used to obtain optimal input control sequence. The temperature of reactor is tuned to track a predetermined temperature trajectory that applied to the batch reactor. To do so two input signals, electrical powers and the flow of coolant in the coil are used. Simulation results show that the proposed controller has a remarkable performance for tracking reference trajectory while at the same time it is robust against noise imposed to system output.

Keywords: Generalized Predictive Control (GPC), TemperatureControl, Global Linearizing Control (GLC), Batch Reactor.

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Authors: María D. Groppa, Andrea Trentini, Myriam Zawoznik, Roxana Bigi, Carlos Nadra, Patricia L. Marconi

Abstract:

In the present work, a remediation bioprocess based on the use of a local isolate of the microalgae Chlorella vulgaris immobilized in alginate beads is proposed. This process was shown to be effective for the reduction of several chemical and microbial contaminants present in Cildáñez stream, a water course that is part of the Matanza-Riachuelo Basin (Buenos Aires, Argentina). The bioprocess, involving the culture of the microalga in autotrophic conditions in a stirred-tank bioreactor supplied with a marine propeller for 6 days, allowed a significant reduction of Escherichia coli and total coliform numbers (over 95%), as well as of ammoniacal nitrogen (96%), nitrates (86%), nitrites (98%), and total phosphorus (53%) contents. Pb content was also significantly diminished after the bioprocess (95%). Standardized cytotoxicity tests using Allium cepa seeds and Cildáñez water pre- and post-remediation were also performed. Germination rate and mitotic index of onion seeds imbibed in Cildáñez water subjected to the bioprocess was similar to that observed in seeds imbibed in distilled water and significantly superior to that registered when untreated Cildáñez water was used for imbibition. Our results demonstrate the potential of this simple and cost-effective technology to remove urban-water contaminants, offering as an additional advantage the possibility of an easy biomass recovery, which may become a source of alternative energy.

Keywords: Bioreactor, bioremediation, Chlorella vulgaris, Matanza-Riachuelo basin, microalgae.

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Authors: Gorazd Karer, Igor Skrjanc, Borut Zupancic

Abstract:

The complex hybrid and nonlinear nature of many processes that are met in practice causes problems with both structure modelling and parameter identification; therefore, obtaining a model that is suitable for MPC is often a difficult task. The basic idea of this paper is to present an identification method for a piecewise affine (PWA) model based on a fuzzy clustering algorithm. First we introduce the PWA model. Next, we tackle the identification method. We treat the fuzzy clustering algorithm, deal with the projections of the fuzzy clusters into the input space of the PWA model and explain the estimation of the parameters of the PWA model by means of a modified least-squares method. Furthermore, we verify the usability of the proposed identification approach on a hybrid nonlinear batch reactor example. The result suggest that the batch reactor can be efficiently identified and thus formulated as a PWA model, which can eventually be used for model predictive control purposes.

Keywords: Batch reactor, fuzzy clustering, hybrid systems, identification, nonlinear systems, PWA systems.

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Authors: Farouq Twaiq, Ishaq Al-Anbari, Mustafa Nasser

Abstract:

The kinetics of palm oil catalytic cracking over aluminum containing mesoporous silica Al-MCM-41 (5% Al) was investigated in a batch autoclave reactor at the temperatures range of 573 – 673 K. The catalyst was prepared by using sol-gel technique and has been characterized by nitrogen adsorption and x-ray diffraction methods. Surface area of 1276 m2/g with average pore diameter of 2.54 nm and pore volume of 0.811 cm3/g was obtained. The experimental catalytic cracking runs were conducted using 50 g of oil and 1 g of catalyst. The reaction pressure was recorded at different time intervals and the data were analyzed using Levenberg- Marquardt (LM) algorithm using polymath software. The results show that the reaction order was found to be -1.5 and activation energy of 3200 J/gmol.

Keywords: Batch Reactor, Catalytic Cracking, Kinetics, Palm Oil.

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Authors: Hyun-Woo Cho

Abstract:

The early diagnostic decision making in industrial processes is absolutely necessary to produce high quality final products. It helps to provide early warning for a special event in a process, and finding its assignable cause can be obtained. This work presents a hybrid diagnostic schmes for batch processes. Nonlinear representation of raw process data is combined with classification tree techniques. The nonlinear kernel-based dimension reduction is executed for nonlinear classification decision boundaries for fault classes. In order to enhance diagnosis performance for batch processes, filtering of the data is performed to get rid of the irrelevant information of the process data. For the diagnosis performance of several representation, filtering, and future observation estimation methods, four diagnostic schemes are evaluated. In this work, the performance of the presented diagnosis schemes is demonstrated using batch process data.

Keywords: Diagnostics, batch process, nonlinear representation, data filtering, multivariate statistical approach

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Authors: Ali W. Alattabi, Khalid S. Hashim, Hassnen M. Jafer, Ali Alzeyadi

Abstract:

This study was performed to optimise the react time (RT) and study its effects on the removal rates of nitrogen compounds in a sequencing batch reactor (SBR) treating synthetic industrial wastewater. The results showed that increasing the RT from 4 h to 10, 16 and 22 h significantly improved the nitrogen compounds’ removal efficiency, it was increased from 69.5% to 95%, 75.7 to 97% and from 54.2 to 80.1% for NH₃-N, NO₃-N and NO₂-N respectively. The results obtained from this study showed that the RT of 22 h was the optimum for nitrogen compounds removal efficiency.

Keywords: Ammonia-nitrogen, retention time, nitrate, nitrite, sequencing batch reactor, sludge characteristics.

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Authors: A. Djafer, S. Kouadri Moustefai, A. Idou, M. Douani

Abstract:

The removal of chromium by living yeast biomass immobilized onto pozzolana was studied. The results obtained in batch experiments indicate that the immobilized yeast on to pozzolana is a excellent biosorbent of Cr(V) with a good removal rates of 85–90%. The initial concentration solution and agitation speed affected Cr(V) removal. The batch studies data were described using the Freundlich and Langmuir models, but the best fit was obtained with Langmuir model. The breakthrough curve from the continuous flow studies shows that immobilized yeast in the fixed-bed column is capable of decreasing Cr(VI) concentration from 15mg/l to a adequate level. 

Keywords: Biosorption, yeast, chromium, kinetic biosorption, fixed biomass

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Authors: Vitalice K. Oduol, C. Ardil

Abstract:

The paper shows that in the analysis of a queuing system with fixed-size batch arrivals, there emerges a set of polynomials which are a generalization of Chebyshev polynomials of the second kind. The paper uses these polynomials in assessing the transient behaviour of the overflow (equivalently call blocking) probability in the system. A key figure to note is the proportion of the overflow (or blocking) probability resident in the transient component, which is shown in the results to be more significant at the beginning of the transient and naturally decays to zero in the limit of large t. The results also show that the significance of transients is more pronounced in cases of lighter loads, but lasts longer for heavier loads.

Keywords: batch arrivals, blocking probability, generalizedChebyshev polynomials, overflow probability, queue transientanalysis

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Authors: Rakmi Abd.-Rahman, Nurina Anuar

Abstract:

Removal of PCP by a system combining biodegradation by biofilm and adsorption was investigated here. Three studies were conducted employing batch tests, sequencing batch reactor (SBR) and continuous biofilm activated carbon column reactor (BACCOR). The combination of biofilm-GAC batch process removed about 30% more PCP than GAC adsorption alone. For the SBR processes, both the suspended and attached biomass could remove more than 90% of the PCP after acclimatisation. BACCOR was able to remove more than 98% of PCP-Na at concentrations ranging from 10 to 100 mg/L, at empty bed contact time (EBCT) ranging from 0.75 to 4 hours. Pure and mixed cultures from BACCOR were tested for use of PCP as sole carbon and energy source under aerobic conditions. The isolates were able to degrade up to 42% of PCP under aerobic conditions in pure cultures. However, mixed cultures were found able to degrade more than 99% PCP indicating interdependence of species.

Keywords: Adsorption, biodegradation, identification, isolated bacteria, pentachlorophenol.

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Authors: Amin Mojiri, Akiyoshi Ohashi, Tomonori Kindaichi

Abstract:

Synthetic domestic wastewater was treated via combining treatment methods, including electrochemical oxidation, adsorption, and sequencing batch reactor (SBR). In the upper part of the reactor, an anode and a cathode (Ti/RuO₂-IrO₂) were organized in parallel for the electrochemical oxidation procedure. Sodium sulfate (Na₂SO₄) with a concentration of 2.5 g/L was applied as the electrolyte. The voltage and current were fixed on 7.50 V and 0.40 A, respectively. Then, 15% working value of the reactor was filled by activated sludge, and 85% working value of the reactor was added with synthetic wastewater. Powdered cockleshell, 1.5 g/L, was added in the reactor to do ion-exchange. Response surface methodology was employed for statistical analysis. Reaction time (h) and pH were considered as independent factors. A total of 97.0% biochemical oxygen demand, 99.9% phosphorous and 88.6% cadmium were eliminated at the optimum reaction time (80.0 min) and pH (6.4).

Keywords: Adsorption, electrochemical oxidation, metals, sequencing batch reactor.

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Authors: Weeraya Samnuknit, Apichat Boontawan

Abstract:

A vacuum fractionation technique was introduced to remove ethanol from fermentation broth. The effect of initial glucose and ethanol concentrations were investigated for specific productivity. The inhibitory ethanol concentration was observed at 100 g/L. In order to increase the fermentation performance, the ethanol product was removed as soon as it is produced. The broth was boiled at 35^oC by reducing the pressure to 65 mBar. The ethanol/water vapor was fractionated for up to 90 wt% before leaving the column. Ethanol concentration in the broth was kept lower than 25 g/L, thus minimized the product inhibition effect to the yeast cells. For batch extractive fermentation, a high substrate utilization rate was obtained at 26.6 g/L.h and most of glucose was consumed within 21 h. For repeated-batch extractive fermentation, addition of glucose was carried out up to 9 times and ethanol was produced more than 8-fold higher than batch fermentation.

Keywords: Ethanol, Extractive fermentation, Product inhibition, Vacuum fractionation.

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Authors: Vitalice K. Oduol

Abstract:

The paper considers a single-server queue with fixedsize batch Poisson arrivals and exponential service times, a model that is useful for a buffer that accepts messages arriving as fixed size batches of packets and releases them one packet at time. Transient performance measures for queues have long been recognized as being complementary to the steady-state analysis. The focus of the paper is on the use of the functions that arise in the analysis of the transient behaviour of the queuing system. The paper exploits practical modelling to obtain a solution to the integral equation encountered in the analysis. Results obtained indicate that under heavy load conditions, there is significant disparity in the statistics between the transient and steady state values.

Keywords: batch arrivals, modelling, single-server queue, time-varying probabilities, transient analysis.

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Authors: Ghazy M.R. Assassa, Mona F. M. Mursi, Hatim A. Aboalsamh

Abstract:

Traditional principal components analysis (PCA) techniques for face recognition are based on batch-mode training using a pre-available image set. Real world applications require that the training set be dynamic of evolving nature where within the framework of continuous learning, new training images are continuously added to the original set; this would trigger a costly continuous re-computation of the eigen space representation via repeating an entire batch-based training that includes the old and new images. Incremental PCA methods allow adding new images and updating the PCA representation. In this paper, two incremental PCA approaches, CCIPCA and IPCA, are examined and compared. Besides, different learning and testing strategies are proposed and applied to the two algorithms. The results suggest that batch PCA is inferior to both incremental approaches, and that all CCIPCAs are practically equivalent.

Keywords: Candid covariance-free incremental principal components analysis (CCIPCA), face recognition, incremental principal components analysis (IPCA).

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Authors: Subrata Hait, Debabrata Mazumder

Abstract:

A shaft-type activated sludge reactor has been developed in order to study the feasibility of high-rate wastewater treatment. The reactor having volume of about 14.5 L was operated with the acclimated mixed activated sludge under batch and continuous mode using a synthetic wastewater as feed. The batch study was performed with varying chemical oxygen demand (COD) concentrations of 1000–3500 mg·L-1 for a batch period up to 9 h. The kinetic coefficients: Ks, k, Y and kd were obtained as 2040.2 mg·L-1 and 0.105 h-1, 0.878 and 0.0025 h-1 respectively from Monod-s approach. The continuous study showed a stable and steady state operation for a hydraulic retention time (HRT) of 8 h and influent COD of about 1000 mg·L-1. A maximum COD removal efficiency of about 80% was attained at a COD loading rate and food-tomicroorganism (F/M) ratio (COD basis) of 3.42 kg·m-3d-1 and 1.0 kg·kg-1d-1 respectively under a HRT of 8 h. The reactor was also found to handle COD loading rate and F/M ratio of 10.8 kg·m-3d-1 and 2.20 kg·kg-1d-1 respectively showing a COD removal efficiency of about 46%.

Keywords: Activated sludge process, shaft-type reactor, highrate treatment, carbonaceous wastewater.

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Authors: Ashish Pathak, Dong-Jin Kim, S. Singh, H. Srichandan, Byoung-Gon Kim

Abstract:

The desulfurization of coal using biological methods is an emerging technology. The biodesulfurization process uses the catalytic activity of chemolithotrophic acidpohiles in removing sulfur and pyrite from the coal. The present study was undertaken to examine the potential of Acidithiobacillus ferrooxidans in removing the pyritic sulfur and iron from high iron and sulfur containing US coal. The experiment was undertaken in 10 L batch stirred tank reactor having 10% pulp density of coal. The reactor was operated under mesophilic conditions and aerobic conditions were maintained by sparging the air into the reactor. After 35 days of experiment, about 64% of pyrite and 21% of pyritic sulfur was removed from the coal. The findings of the present study indicate that the biodesulfurization process does have potential in treating the high pyrite and sulfur containing coal. A good mass balance was also obtained with net loss of about 5% showing its feasibility for large scale application.

Keywords: At.ferrroxidans, Batch reactor, Coal desulfurization, Pyrite.

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Authors: L. N. Corîci, A. E. Frissen, D -J. Van Zoelen, I. F. Eggen, F. Peter, C. M. Davidescu, C. G. Boeriu

Abstract:

Two commercial proteases from Bacillus licheniformis (Alcalase 2.4 L FG and Alcalase 2.5 L, Type DX) were screened for the production of Z-Ala-Phe-NH2 in batch reaction. Alcalase 2.4 L FG was the most efficient enzyme for the C-terminal amidation of Z-Ala-Phe-OMe using ammonium carbamate as ammonium source. Immobilization of protease has been achieved by the sol-gel method, using dimethyldimethoxysilane (DMDMOS) and tetramethoxysilane (TMOS) as precursors (unpublished results). In batch production, about 95% of Z-Ala-Phe-NH2 was obtained at 30°C after 24 hours of incubation. Reproducibility of different batches of commercial Alcalase 2.4 L FG preparations was also investigated by evaluating the amidation activity and the entrapment yields in the case of immobilization. A packed-bed reactor (0.68 cm ID, 15.0 cm long) was operated successfully for the continuous synthesis of peptide amides. The immobilized enzyme retained the initial activity over 10 cycles of repeated use in continuous reactor at ambient temperature. At 0.75 mL/min flow rate of the substrate mixture, the total conversion of Z-Ala-Phe-OMe was achieved after 5 hours of substrate recycling. The product contained about 90% peptide amide and 10% hydrolysis byproduct.

Keywords: packed-bed reactor, peptide amide, protease, sol-gel immobilization.

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Authors: Siew-Teng

Abstract:

Durian husk (DH), a fruit waste, was studied for its ability to remove Basic blue 3 (BB3) from aqueous solutions. Batch kinetic studies were carried out to study the sorption characteristics under various experimental conditions. The optimum pH for the dye removal occurred in the pH range of 3-10. Sorption was found to be concentration and agitation dependent. The kinetics of dye sorption fitted a pseudo-second order rate expression. Both Langmuir and Freundlich models appeared to provide reasonable fittings for the sorption data of BB3 on durian husk. Maximum sorption capacity calculated from the Langmuir model is 49.50 mg g-1.

Keywords: Durian husk, Batch study, Sorption, Basic Blue 3

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