59 resultados para Adaptive Modelling, Entropy Evolution, Sustainable Design
Resumo:
Superheater corrosion causes vast annual losses for the power companies. With a reliable corrosion prediction method, the plants can be designed accordingly, and knowledge of fuel selection and determination of process conditions may be utilized to minimize superheater corrosion. Growing interest to use recycled fuels creates additional demands for the prediction of corrosion potential. Models depending on corrosion theories will fail, if relations between the inputs and the output are poorly known. A prediction model based on fuzzy logic and an artificial neural network is able to improve its performance as the amount of data increases. The corrosion rate of a superheater material can most reliably be detected with a test done in a test combustor or in a commercial boiler. The steel samples can be located in a special, temperature-controlled probe, and exposed to the corrosive environment for a desired time. These tests give information about the average corrosion potential in that environment. Samples may also be cut from superheaters during shutdowns. The analysis ofsamples taken from probes or superheaters after exposure to corrosive environment is a demanding task: if the corrosive contaminants can be reliably analyzed, the corrosion chemistry can be determined, and an estimate of the material lifetime can be given. In cases where the reason for corrosion is not clear, the determination of the corrosion chemistry and the lifetime estimation is more demanding. In order to provide a laboratory tool for the analysis and prediction, a newapproach was chosen. During this study, the following tools were generated: · Amodel for the prediction of superheater fireside corrosion, based on fuzzy logic and an artificial neural network, build upon a corrosion database developed offuel and bed material analyses, and measured corrosion data. The developed model predicts superheater corrosion with high accuracy at the early stages of a project. · An adaptive corrosion analysis tool based on image analysis, constructedas an expert system. This system utilizes implementation of user-defined algorithms, which allows the development of an artificially intelligent system for thetask. According to the results of the analyses, several new rules were developed for the determination of the degree and type of corrosion. By combining these two tools, a user-friendly expert system for the prediction and analyses of superheater fireside corrosion was developed. This tool may also be used for the minimization of corrosion risks by the design of fluidized bed boilers.
Resumo:
Key management has a fundamental role in secure communications. Designing and testing of key management protocols is tricky. These protocols must work flawlessly despite of any abuse. The main objective of this work was to design and implement a tool that helps to specify the protocol and makes it possible to test the protocol while it is still under development. This tool generates compile-ready java code from a key management protocol model. A modelling method for these protocols, which uses Unified Modeling Language (UML) was also developed. The protocol is modelled, exported as an XMI and read by the code generator tool. The code generator generates java code that is immediately executable with a test software after compilation.
Resumo:
Tässä työssä tutkitaan ohjelmistoarkkitehtuurisuunnitteluominaisuuksien vaikutusta erään client-server –arkkitehtuuriin perustuvan mobiilipalvelusovelluksen suunnittelu- ja toteutusaikaan. Kyseinen tutkimus perustuu reaalielämän projektiin, jonka kvalitatiivinen analyysi paljasti arkkitehtuurikompponenttien välisten kytkentöjen merkittävästi vaikuttavan projektin työmäärään. Työn päätavoite oli kvantitatiivisesti tutkia yllä mainitun havainnon oikeellisuus. Tavoitteen saavuttamiseksi suunniteltiin ohjelmistoarkkitehtuurisuunnittelun mittaristo kuvaamaan kyseisen järjestelmän alijärjestelmien arkkitehtuuria ja luotiin kaksi suunniteltua mittaristoa käyttävää, työmäärää (komponentin suunnittelu-, toteutus- ja testausaikojen summa) arvioivaa mallia, joista toinen on lineaarinen ja toinen epälineaarinen. Näiden mallien kertoimet sovitettiin optimoimalla niiden arvot epälineaarista gloobaalioptimointimenetelmää, differentiaalievoluutioalgoritmia, käyttäen, niin että mallien antamat arvot vastasivat parhaiten mitattua työmäärää sekä kaikilla ominaisuuksilla eli attribuuteilla että vain osalla niistä (yksi jätettiin vuorotellen pois). Kun arkkitehtuurikompenttien väliset kytkennät jätettiin malleista pois, mitattujen ja arvoitujen työmäärien välinen ero (ilmaistuna virheenä) kasvoi eräässä tapauksessa 367 % entisestä tarkoittaen sitä, että näin muodostettu malli vastasi toteutusaikoja huonosti annetulla ainestolla. Tämä oli suurin havaitu virhe kaikkien poisjätettyjen ominaisuuksien kesken. Saadun tuloksen perusteella päätettiin, että kyseisen järjestelmän toteutusajat ovat vahvasti riippuvaisia kytkentöjen määrästä, ja näin ollen kytkentöjen määrä oli mitä todennäköisemmin kaikista tärkein työmäärään vaikuttava tekijä tutkitun järjestelmän arkkitehtuurisuunnittelussa.
Resumo:
Työn tavoitteena oli mallintaa uuden tuoteominaisuuden aiheuttamat lisäkustannukset ja suunnitella päätöksenteon työkalu Timberjack Oy:n kuormatraktorivalmistuksen johtoryhmälle. Tarkoituksena oli luoda karkean tason malli, joka sopisi eri tyyppisten tuoteominaisuuksien kustannuksien selvittämiseen. Uuden tuoteominaisuuden vaikutusta yrityksen eri toimintoihin selvitettiin haastatteluin. Haastattelukierroksen tukena käytettiin kysymyslomaketta. Haastattelujen tavoitteena oli selvittää prosessit, toiminnot ja resurssit, jotka ovat välttämättömiä uuden tuoteominaisuuden tuotantoon saattamisessa ja tuotannossa. Malli suunniteltiin haastattelujen ja tietojärjestelmästä hankitun tiedon pohjalta. Mallin rungon muodostivat ne prosessit ja toiminnot, joihin uudella tuoteominaisuudella on vaikutusta. Huomioon otettiin sellaiset resurssit, joita uusi tuoteominaisuus kuluttaa joko välittömästi, tai välillisesti. Tarkasteluun sisällytettiin ainoastaan lisäkustannukset. Uuden tuoteominaisuuden toteuttamisesta riippumattomat, joka tapauksessa toteutuvat yleiskustannukset jätettiin huomioimatta. Malli on yleistys uuden tuoteominaisuuden aiheuttamista lisäkustannuksista, koska tarkoituksena on, että se sopii eri tyyppisten tuoteominaisuuksien aiheuttamien kustannusten selvittämiseen. Lisäksi malli soveltuu muiden pienehköjen tuotemuutosten kustannusten kartoittamiseen.
Resumo:
Tämä diplomityökuuluu tietoliikenneverkkojen suunnittelun tutkimukseen ja pohjimmiltaan kohdistuu verkon mallintamiseen. Tietoliikenneverkkojen suunnittelu on monimutkainen ja vaativa ongelma, joka sisältää mutkikkaita ja aikaa vieviä tehtäviä. Tämä diplomityö esittelee ”monikerroksisen verkkomallin”, jonka tarkoitus on auttaa verkon suunnittelijoita selviytymään ongelmien monimutkaisuudesta ja vähentää verkkojen suunnitteluun kuluvaa aikaa. Monikerroksinen verkkomalli perustuu yleisille objekteille, jotka ovat yhteisiä kaikille tietoliikenneverkoille. Tämä tekee mallista soveltuvan mielivaltaisille verkoille, välittämättä verkkokohtaisista ominaisuuksista tai verkon toteutuksessa käytetyistä teknologioista. Malli määrittelee tarkan terminologian ja käyttää kolmea käsitettä: verkon jakaminen tasoihin (plane separation), kerrosten muodostaminen (layering) ja osittaminen (partitioning). Nämä käsitteet kuvataan yksityiskohtaisesti tässä työssä. Monikerroksisen verkkomallin sisäinen rakenne ja toiminnallisuus ovat määritelty käyttäen Unified Modelling Language (UML) -notaatiota. Tämä työ esittelee mallin use case- , paketti- ja luokkakaaviot. Diplomityö esittelee myös tulokset, jotka on saatu vertailemalla monikerroksista verkkomallia muihin verkkomalleihin. Tulokset osoittavat, että monikerroksisella verkkomallilla on etuja muihin malleihin verrattuna.
Resumo:
Oral mucosa is a frequent site of primary herpes simplex virus type 1 (HSV-1) infection, whereas intraoral recurrent disease is very rare. Instead, reactivation from latency predominantly results in asymptomatic HSV shedding to saliva or recurrent labial herpes (RLH) with highly individual frequency. The current study aimed to elucidate the role of human oral innate and acquired immune mechanisms in modulation of HSV infection in orolabial region. Saliva was found to neutralize HSV-1, and to protect cells from infection independently of salivary antibodies. Neutralization capacity was higher in saliva from asymptomatic HSV-seropositive individuals compared to subjects with history of RLH or seronegative controls. Neutralization was at least partially associated with salivary lactoferrin content. Further, lactoferrin and peroxidase-generated hypothiocyanite were found to either neutralize HSV-1 or interfere with HSV-1 replication, whereas lysozyme displayed no anti-HSV-1 activity. Lactoferrin was also shown to modulate HSV-1 infection by inhibiting keratinocyte proliferation. RLH susceptibility was further found to be associated with Th2 biased cytokine responses against HSV, and a higher level of anti- HSV-IgG with Th2 polarization, indicating lack of efficiency of humoral response in the control of HSV disease. In a three-dimensional cell culture, keratinocytes were found to support both lytic and nonproductive infection, suggesting HSV persistence in epithelial cells, and further emphasizing the importance of peripheral immune control of HSV. These results suggest that certain innate salivary antimicrobial compounds and Th1 type cellular responses are critically important in protecting the host against HSV disease, implying possible applications in drug, vaccine and gene therapy design.
Resumo:
Several possible methods of increasing the efficiency and power of hydro power plants by improving the flow passages are investigated in this stydy. The theoretical background of diffuser design and its application to the optimisation of hydraulic turbine draft tubes is presented in the first part of this study. Several draft tube modernisation projects that have been carried out recently are discussed. Also, a method of increasing the efficiency of the draft tube by injecting a high velocity jet into the boundary layer is presented. Methods of increasing the head of a hydro power plant by using an ejector or a jet pump are discussed in the second part of this work. The theoretical principles of various ejector and jet pump types are presented and four different methods of calculating them are examined in more detail. A self-made computer code is used to calculate the gain in the head for two example power plants. Suitable ejector installations for the example plants are also discussed. The efficiency of the ejector power was found to be in the range 6 - 15 % for conventional head increasers, and 30 % for the jet pump at its optimum operating point. In practice, it is impossible to install an optimised jet pump with a 30 % efficiency into the draft tube as this would considerabely reduce the efficiency of the draft tube at normal operating conditions. This demonstrates, however, the potential for improvement which lies in conventional head increaser technology. This study is based on previous publications and on published test results. No actual laboratory measurements were made for this study. Certain aspects of modelling the flow in the draft tube using computational fluid dynamics are discussed in the final part of this work. The draft tube inlet velocity field is a vital boundary condition for such a calculation. Several previously measured velocity fields that have successfully been utilised in such flow calculations are presented herein.
Resumo:
Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.
Resumo:
This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.
Resumo:
Nowadays the Finnish-Russian electric energy interaction is carried out through the back-to-back DC Vyborg substation and several power plants working synchronously with Finnish power system. Constant amount of energy flows in one direction — from Russia to Finland. But the process of electricity market development in Russian energy system makes the new possibilities of electrical cooperation available. The goal of master's thesis is to analyze the current state and possible evolution trends of North-West Russian system in relation with future possible change in power flow between Russia and Finland. The research is done by modelling the market of North-West Russia and examination of technical grid restrictions. The operational market models of North-West region of Russia for the years 2008 and 2015 were created during the research process. The description of prepared market models together with modelling results and their analysis are shown in the work. The description of power flow study process and results are also presented.
Resumo:
The present thesis in focused on the minimization of experimental efforts for the prediction of pollutant propagation in rivers by mathematical modelling and knowledge re-use. Mathematical modelling is based on the well known advection-dispersion equation, while the knowledge re-use approach employs the methods of case based reasoning, graphical analysis and text mining. The thesis contribution to the pollutant transport research field consists of: (1) analytical and numerical models for pollutant transport prediction; (2) two novel techniques which enable the use of variable parameters along rivers in analytical models; (3) models for the estimation of pollutant transport characteristic parameters (velocity, dispersion coefficient and nutrient transformation rates) as functions of water flow, channel characteristics and/or seasonality; (4) the graphical analysis method to be used for the identification of pollution sources along rivers; (5) a case based reasoning tool for the identification of crucial information related to the pollutant transport modelling; (6) and the application of a software tool for the reuse of information during pollutants transport modelling research. These support tools are applicable in the water quality research field and in practice as well, as they can be involved in multiple activities. The models are capable of predicting pollutant propagation along rivers in case of both ordinary pollution and accidents. They can also be applied for other similar rivers in modelling of pollutant transport in rivers with low availability of experimental data concerning concentration. This is because models for parameter estimation developed in the present thesis enable the calculation of transport characteristic parameters as functions of river hydraulic parameters and/or seasonality. The similarity between rivers is assessed using case based reasoning tools, and additional necessary information can be identified by using the software for the information reuse. Such systems represent support for users and open up possibilities for new modelling methods, monitoring facilities and for better river water quality management tools. They are useful also for the estimation of environmental impact of possible technological changes and can be applied in the pre-design stage or/and in the practical use of processes as well.
Resumo:
The mobile networks of earlier and current generations, or 2G and 3G networks, provide users voice and packet services with higher transmission rates and good quality over the same core network. When developing the next generation of mobile networks the current quality of services needs to be maintained. This thesis concentrates on the next generation mobile network, especially on the evolution of the packet network part. The new mobile network has requirements for the common packet backbone network, Mobile Packet Backbone Network, which is additionally discussed in this study. The next generation mobile network, called LTE/SAE, is currently under testing. The test system is called Container Trial System. It is a mini sized LTE/SAE site. The LTE/SAE is studied in this thesis concentrating on the evolved packet core, the SAE part of the composition. The empirical part of the study compares the LTE/SAE Container Trial System and commercial network designs and additionally produces documentation for internal personnel and customers. The research is performed by comparing the documentations and specifications of both the Container Trial System and commercial network. Since the LTE commercial network is not yet constructed, the comparison is done theoretically. The purpose is furthermore to find out if there are any design issues that could be done differently in the next version of the Container Trial System.
Resumo:
Genetic diversity is one of the levels of biodiversity that the World Conservation Union (IUCN) has recognized as being important to preserve. This is because genetic diversity is fundamental to the future evolution and to the adaptive flexibility of a species to respond to the inherently dynamic nature of the natural world. Therefore, the key to maintaining biodiversity and healthy ecosystems is to identify, monitor and maintain locally-adapted populations, along with their unique gene pools, upon which future adaptation depends. Thus, conservation genetics deals with the genetic factors that affect extinction risk and the genetic management regimes required to minimize the risk. The conservation of exploited species, such as salmonid fishes, is particularly challenging due to the conflicts between different interest groups. In this thesis, I conduct a series of conservation genetic studies on primarily Finnish populations of two salmonid fish species (European grayling, Thymallus thymallus, and lake-run brown trout, Salmo trutta) which are popular recreational game fishes in Finland. The general aim of these studies was to apply and develop population genetic approaches to assist conservation and sustainable harvest of these populations. The approaches applied included: i) the characterization of population genetic structure at national and local scales; ii) the identification of management units and the prioritization of populations for conservation based on evolutionary forces shaping indigenous gene pools; iii) the detection of population declines and the testing of the assumptions underlying these tests; and iv) the evaluation of the contribution of natural populations to a mixed stock fishery. Based on microsatellite analyses, clear genetic structuring of exploited Finnish grayling and brown trout populations was detected at both national and local scales. Finnish grayling were clustered into three genetically distinct groups, corresponding to northern, Baltic and south-eastern geographic areas of Finland. The genetic differentiation among and within population groups of grayling ranged from moderate to high levels. Such strong genetic structuring combined with low genetic diversity strongly indicates that genetic drift plays a major role in the evolution of grayling populations. Further analyses of European grayling covering the majority of the species’ distribution range indicated a strong global footprint of population decline. Using a coalescent approach the beginning of population reduction was dated back to 1 000-10 000 years ago (ca. 200-2 000 generations). Forward simulations demonstrated that the bottleneck footprints measured using the M ratio can persist within small populations much longer than previously anticipated in the face of low levels of gene flow. In contrast to the M ratio, two alternative methods for genetic bottleneck detection identified recent bottlenecks in six grayling populations that warrant future monitoring. Consistent with the predominant role of random genetic drift, the effective population size (Ne) estimates of all grayling populations were very low with the majority of Ne estimates below 50. Taken together, highly structured local populations, limited gene flow and the small Ne of grayling populations indicates that grayling populations are vulnerable to overexploitation and, hence, monitoring and careful management using the precautionary principles is required not only in Finland but throughout Europe. Population genetic analyses of lake-run brown trout populations in the Inari basin (northernmost Finland) revealed hierarchical population structure where individual populations were clustered into three population groups largely corresponding to different geographic regions of the basin. Similar to my earlier work with European grayling, the genetic differentiation among and within population groups of lake-run brown trout was relatively high. Such strong differentiation indicated that the power to determine the relative contribution of populations in mixed fisheries should be relatively high. Consistent with these expectations, high accuracy and precision in mixed stock analysis (MSA) simulations were observed. Application of MSA to indigenous fish caught in the Inari basin identified altogether twelve populations that contributed significantly to mixed stock fisheries with the Ivalojoki river system being the major contributor (70%) to the total catch. When the contribution of wild trout populations to the fisheries was evaluated regionally, geographically nearby populations were the main contributors to the local catches. MSA also revealed a clear separation between the lower and upper reaches of Ivalojoki river system – in contrast to lower reaches of the Ivalojoki river that contributed considerably to the catch, populations from the upper reaches of the Ivalojoki river system (>140 km from the river mouth) did not contribute significantly to the fishery. This could be related to the available habitat size but also associated with a resident type life history and increased cost of migration. The studies in my thesis highlight the importance of dense sampling and wide population coverage at the scale being studied and also demonstrate the importance of critical evaluation of the underlying assumptions of the population genetic models and methods used. These results have important implications for conservation and sustainable fisheries management of Finnish populations of European grayling and brown trout in the Inari basin.
Resumo:
Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.
Resumo:
Antibodies are natural binding proteins produced in vertebrates as a response to invading pathogens and foreign substances. Because of their capability for tight and specific binding, antibodies have found use as binding reagents in research and diagnostics. Properties of cloned recombinant antibodies can be further improved by means of in vitro evolution, combining mutagenesis with subsequent phage display selection. It is also possible to isolate entirely new antibodies from vast naïve or synthetic antibody libraries by phage display. In this study, library techniques and phage display selection were applied in order to optimise binding scaffolds and antigen recognition of antibodies, and to evolve new and improved bioaffinity reagents. Antibody libraries were generated by random and targeted mutagenesis. Expression and stability were mainly optimised by the random methods whereas targeted randomisation of the binding site residues was used for optimising the binding properties. Trinucleotide mutagenesis allowed design of defined randomisation patterns for a synthetic antibody library. Improved clones were selected by phage display. Capture by a specific anti- DHPS antibody was exploited in the selection of improved phage display of DHPS. Efficient selection for stability was established by combining phage display selection with denaturation under reducing conditions. Broad-specific binding of a generic anti-sulfonamide antibody was improved by selection with one of the weakest binding sulfonamides. In addition, p9 based phage display was studied in affinity selection from the synthetic library. A TIM barrel protein DHPS was engineered for efficient phage display by combining cysteinereplacement with random mutagenesis. The resulting clone allows use of phage display in further engineering of DHPS and possibly use as an alternative-binding scaffold. An anti-TSH scFv fragment, cloned from a monoclonal antibody, was engineered for improved stability to better suite an immunoassay. The improved scFv tolerates 8 – 9 °C higher temperature than the parental scFv and should have sufficient stability to be used in an immunoanalyser with incubation at 36 °C. The anti-TSH scFv fragment was compared with the corresponding Fab fragment and the parental monoclonal antibody as a capturing reagent in a rapid 5-min immunoassay for TSH. The scFv fragment provided some benefits over the conventionally used Mab in anayte-binding capacity and assay kinetics. However, the recombinant Fab fragment, which had similar kinetics to the scFv, provided a more sensitive and reliable assay than the scFv. Another cloned scFv fragment was engineered in order to improve broad-specific recognition of sulfonamides. The improved antibody detects different sulfonamides at concentrations below the maximum residue limit (100 μg/kg in EU and USA) and allows simultaneous screening of different sulfonamide drug residues. Finally, a synthetic antibody library was constructed and new antibodies were generated and affinity matured entirely in vitro. These results illuminate the possibilities of phage display and antibody engineering for generation and optimisation of binding reagents in vitro and indicate the potential of recombinant antibodies as affinity reagents in immunoassays.