Design, development and testing of a CAD integrated design for environment software tool.

The research described in this thesis was developed as part o f the Information Management for Green Design (IMA GREE) Project. The 1MAGREE Project was founded by Enterprise Ireland under a Strategic Research Grant Scheme as a partnership project between Galway Mayo Institute o f Technology and C1MRU University College Galway. The project aimed to develop a CAD integrated software tool to support environmental information management for design, particularly for the electronics-manufacturing sector in Ireland.

Evaluation of three automated systems for susceptibility testing of enterobacteria containing qnrB, qnrS, and/or aac(6')-Ib-cr.

The accuracy of the MicroScan WalkAway, BD Phoenix, and Vitek-2 systems for susceptibility testing of quinolones and aminoglycosides against 68 enterobacteria containing qnrB, qnrS, and/or aac(6 ')-Ib-cr was evaluated using reference microdilution. Overall, one very major error (0.09%), 6 major errors (0.52%), and 45 minor errors (3.89%) were noted.

New TTCN interfaces for WCDMA base station testing

WCDMA tukiasema (Node B) on osa UMTS-järjestelmän radioverkkoa. Node B on tärkeä verkkoelementti, jonka tarkoituksena on yhdistää mobiilikäyttäjät verkkoon. Telecom –ohjelmisto (TCOM SW) on vastuussa suuresta osasta Node B:n toiminnallisuutta. TCOM SW:n testaukseen käytetään paljon resursseja, jotta ohjelmiston oikeasta toiminnasta ja laadusta voidaan varmistua. System component testing on testausvaihe, jossa järjestelmän (Node B) osa (system component, tässä diplomityössä TCOM SW) testataan ennen sen integroimista muuhun järjestelmään. Tähän tarvitaan testityökalu ja testitapausten toteutus. Node B TTCN Tester (testeri) on työkalu, jota käytetään Node B:n ohjelmiston testauksessa. Testitapaukset toteutetaan TTCN-testinotaatiota käyttäen ja testataan testerin avulla. TCOM SW:n system component –testausvaihetta varten testeriin lisättiin uudet rajapinnat, joiden avulla voidaan simuloita Node B:n ATM-ohjelmistoa sekä WPA- ja WTR-yksiköitä. Tässä diplomityössä toteuttiin TTCN testitapaukset uusille rajapinnoille. Testitapaukset tekivät TCOM SW system component –testausvaiheen riippumattomaksi Node B:n ATM-ohjelmistosta sekä WPA- ja WTR-yksiköistä. Lisäksi TCOM SW:n toiminnan testaus näissä rajapinnoissa voidaan tästä lähtien tehdä automaattisesti. Testitapauksien toiminta varmistettiin testeriä käyttäen. Tulokset olivat hyviä, uudet testitapaukset ja TTCN rajapinnat toimivat oikein lisäten testauksen tehokkuutta.

Software Security Design and Testing

Elektroninen kaupankäynti ja pankkipalvelut ovat herättäneet toiminnan jatkuvuuden kannalta erittäin kriittisen kysymyksen siitä, kuinka näitä palveluja pystytään suojaamaan järjestäytynyttä rikollisuutta ja erilaisia hyväksikäyttöjä vastaan.

Comparison of Inoculation with the InoqulA and WASP Automated Systems with Manual Inoculation.

The quality of sample inoculation is critical for achieving an optimal yield of discrete colonies in both monomicrobial and polymicrobial samples to perform identification and antibiotic susceptibility testing. Consequently, we compared the performance between the InoqulA (BD Kiestra), the WASP (Copan), and manual inoculation methods. Defined mono- and polymicrobial samples of 4 bacterial species and cloudy urine specimens were inoculated on chromogenic agar by the InoqulA, the WASP, and manual methods. Images taken with ImagA (BD Kiestra) were analyzed with the VisionLab version 3.43 image analysis software to assess the quality of growth and to prevent subjective interpretation of the data. A 3- to 10-fold higher yield of discrete colonies was observed following automated inoculation with both the InoqulA and WASP systems than that with manual inoculation. The difference in performance between automated and manual inoculation was mainly observed at concentrations of >10(6) bacteria/ml. Inoculation with the InoqulA system allowed us to obtain significantly more discrete colonies than the WASP system at concentrations of >10(7) bacteria/ml. However, the level of difference observed was bacterial species dependent. Discrete colonies of bacteria present in 100- to 1,000-fold lower concentrations than the most concentrated populations in defined polymicrobial samples were not reproducibly recovered, even with the automated systems. The analysis of cloudy urine specimens showed that InoqulA inoculation provided a statistically significantly higher number of discrete colonies than that with WASP and manual inoculation. Consequently, the automated InoqulA inoculation greatly decreased the requirement for bacterial subculture and thus resulted in a significant reduction in the time to results, laboratory workload, and laboratory costs.

Software Development: Testing

This presentation discusses the role and purpose of testing in the systems/Software Development Life Cycle. We examine the consequences of the 'cost curve' on defect removal and how agile methods can reduce its effects. We concentrate on Black Box Testing and use Equivalence Partitioning and Boundary Value Analysis to construct the smallest number of test cases, test scenarios necessary for a test plan.

Validation of an automated algorithm for auditory brainstem response testing

This paper discusses the auditory brainstem response (ABR) testing for infants.

Final report on research project PS2010, proof of concept of automated mapping of weeds in arable fields

Many weeds occur in patches but farmers frequently spray whole fields to control the weeds in these patches. Given a geo-referenced weed map, technology exists to confine spraying to these patches. Adoption of patch spraying by arable farmers has, however, been negligible partly due to the difficulty of constructing weed maps. Building on previous DEFRA and HGCA projects, this proposal aims to develop and evaluate a machine vision system to automate the weed mapping process. The project thereby addresses the principal technical stumbling block to widespread adoption of site specific weed management (SSWM). The accuracy of weed identification by machine vision based on a single field survey may be inadequate to create herbicide application maps. We therefore propose to test the hypothesis that sufficiently accurate weed maps can be constructed by integrating information from geo-referenced images captured automatically at different times of the year during normal field activities. Accuracy of identification will also be increased by utilising a priori knowledge of weeds present in fields. To prove this concept, images will be captured from arable fields on two farms and processed offline to identify and map the weeds, focussing especially on black-grass, wild oats, barren brome, couch grass and cleavers. As advocated by Lutman et al. (2002), the approach uncouples the weed mapping and treatment processes and builds on the observation that patches of these weeds are quite stable in arable fields. There are three main aspects to the project. 1) Machine vision hardware. Hardware component parts of the system are one or more cameras connected to a single board computer (Concurrent Solutions LLC) and interfaced with an accurate Global Positioning System (GPS) supplied by Patchwork Technology. The camera(s) will take separate measurements for each of the three primary colours of visible light (red, green and blue) in each pixel. The basic proof of concept can be achieved in principle using a single camera system, but in practice systems with more than one camera may need to be installed so that larger fractions of each field can be photographed. Hardware will be reviewed regularly during the project in response to feedback from other work packages and updated as required. 2) Image capture and weed identification software. The machine vision system will be attached to toolbars of farm machinery so that images can be collected during different field operations. Images will be captured at different ground speeds, in different directions and at different crop growth stages as well as in different crop backgrounds. Having captured geo-referenced images in the field, image analysis software will be developed to identify weed species by Murray State and Reading Universities with advice from The Arable Group. A wide range of pattern recognition and in particular Bayesian Networks will be used to advance the state of the art in machine vision-based weed identification and mapping. Weed identification algorithms used by others are inadequate for this project as we intend to collect and correlate images collected at different growth stages. Plants grown for this purpose by Herbiseed will be used in the first instance. In addition, our image capture and analysis system will include plant characteristics such as leaf shape, size, vein structure, colour and textural pattern, some of which are not detectable by other machine vision systems or are omitted by their algorithms. Using such a list of features observable using our machine vision system, we will determine those that can be used to distinguish weed species of interest. 3) Weed mapping. Geo-referenced maps of weeds in arable fields (Reading University and Syngenta) will be produced with advice from The Arable Group and Patchwork Technology. Natural infestations will be mapped in the fields but we will also introduce specimen plants in pots to facilitate more rigorous system evaluation and testing. Manual weed maps of the same fields will be generated by Reading University, Syngenta and Peter Lutman so that the accuracy of automated mapping can be assessed. The principal hypothesis and concept to be tested is that by combining maps from several surveys, a weed map with acceptable accuracy for endusers can be produced. If the concept is proved and can be commercialised, systems could be retrofitted at low cost onto existing farm machinery. The outputs of the weed mapping software would then link with the precision farming options already built into many commercial sprayers, allowing their use for targeted, site-specific herbicide applications. Immediate economic benefits would, therefore, arise directly from reducing herbicide costs. SSWM will also reduce the overall pesticide load on the crop and so may reduce pesticide residues in food and drinking water, and reduce adverse impacts of pesticides on non-target species and beneficials. Farmers may even choose to leave unsprayed some non-injurious, environmentally-beneficial, low density weed infestations. These benefits fit very well with the anticipated legislation emerging in the new EU Thematic Strategy for Pesticides which will encourage more targeted use of pesticides and greater uptake of Integrated Crop (Pest) Management approaches, and also with the requirements of the Water Framework Directive to reduce levels of pesticides in water bodies. The greater precision of weed management offered by SSWM is therefore a key element in preparing arable farming systems for the future, where policy makers and consumers want to minimise pesticide use and the carbon footprint of farming while maintaining food production and security. The mapping technology could also be used on organic farms to identify areas of fields needing mechanical weed control thereby reducing both carbon footprints and also damage to crops by, for example, spring tines. Objective i. To develop a prototype machine vision system for automated image capture during agricultural field operations; ii. To prove the concept that images captured by the machine vision system over a series of field operations can be processed to identify and geo-reference specific weeds in the field; iii. To generate weed maps from the geo-referenced, weed plants/patches identified in objective (ii).

Evolutionary Testing of Autonomous Software Agents

A system built in terms of autonomous agents may require even greater correctness assurance than one which is merely reacting to the immediate control of its users. Agents make substantial decisions for themselves, so thorough testing is an important consideration. However, autonomy also makes testing harder; by their nature, autonomous agents may react in different ways to the same inputs over time, because, for instance they have changeable goals and knowledge. For this reason, we argue that testing of autonomous agents requires a procedure that caters for a wide range of test case contexts, and that can search for the most demanding of these test cases, even when they are not apparent to the agents’ developers. In this paper, we address this problem, introducing and evaluating an approach to testing autonomous agents that uses evolutionary optimization to generate demanding test cases.

Parentage testing in alpacas (Vicugna pacos) using semi-automated fluorescent multiplex PCRs with 10 microsatellite markers

The aim of this study was to assess and apply a microsatellite multiplex system for parentage determination in alpacas. An approach for parentage testing based on 10 microsatellites was evaluated in a population of 329 unrelated alpacas from different geographical zones in Peru. All microsatellite markers, which amplified in two multiplex reactions, were highly polymorphic with a mean of 14.5 alleles per locus (six to 28 alleles per locus) and an average expected heterozygosity (H-E) of 0.8185 (range of 0.698-0.946). The total parentage exclusion probability was 0.999456 for excluding a candidate parent from parentage of an arbitrary offspring, given only the genotype of the offspring, and 0.999991 for excluding a candidate parent from parentage of an arbitrary offspring, given the genotype of the offspring and the other parent. In a case test of parentage assignment, the microsatellite panel assigned 38 (from 45 cases) offspring parentage to 10 sires with LOD scores ranging from 2.19 x 10(+13) to 1.34 x 10(+15) and Delta values ranging from 2.80 x 10(+12) to 1.34 x 10(+15) with an estimated pedigree error rate of 15.5%. The performance of this multiplex panel of markers suggests that it will be useful in parentage testing of alpacas.

A reference model as automated process for software adaptation at runtime

The development of self-adaptive software (SaS) has specific characteristics compared to traditional one, since it allows that changes to be incorporated at runtime. Automated processes have been used as a feasible solution to conduct the software adaptation at runtime. In parallel, reference model has been used to aggregate knowledge and architectural artifacts, since capture the systems essence of specific domains. However, there is currently no reference model based on reflection for the development of SaS. Thus, the main contribution of this paper is to present a reference model based on reflection for development of SaS that have a need to adapt at runtime. To present the applicability of this model, a case study was conducted and good perspective to efficiently contribute to the area of SaS has been obtained.