Custom Integrated Circuits

Contains reports on twelve research projects.Analog Devices, Inc.International Business Machines, Inc.Joint Services Electronics Program (Contract DAAL03-86-K-0002)Joint Services Electronics Program (Contract DAAL03-89-C-0001)U.S. Air Force - Office of Scientific Research (Grant AFOSR 86-0164)Rockwell International CorporationOKI Semiconductor, Inc.U.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)Charles Stark Draper LaboratoryNational Science Foundation (Grant MIP 84-07285)National Science Foundation (Grant MIP 87-14969)Battelle LaboratoriesNational Science Foundation (Grant MIP 88-14612)DuPont CorporationDefense Advanced Research Projects Agency/U.S. Navy - Office of Naval Research (Contract N00014-87-K-0825)American Telephone and TelegraphDigital Equipment CorporationNational Science Foundation (Grant MIP-88-58764

Evolutionary algorithms for synthesis and optimisation of sequential logic circuits

Considerable progress has been made recently 1n the understanding of combinational logic optimization. Consequently a large number of university and industrial Electric Computing Aided Design (ECAD) programs are now available for optimal logic synthesis of combinational circuits. The progress with sequential logic synthesis and optimization, on the other hand, is considerably less mature. In recent years, evolutionary algorithms have been found to be remarkably effective way of using computers for solving difficult problems. This thesis is, in large part, a concentrated effort to apply this philosophy to the synthesis and optimization of sequential circuits. A state assignment based on the use of a Genetic Algorithm (GA) for the optimal synthesis of sequential circuits is presented. The state assignment determines the structure of the sequential circuit realizing the state machine and therefore its area and performances. The synthesis based on the GA approach produced designs with the smallest area to date. Test results on standard fmite state machine (FS:M) benchmarks show that the GA could generate state assignments, which required on average 15.44% fewer gates and 13.47% fewer literals compared with alternative techniques. Hardware evolution is performed through a succeSSlOn of changes/reconfigurations of elementary components, inter-connectivity and selection of the fittest configurations until the target functionality is reached. The thesis presents new approaches, which combine both genetic algorithm for state assignment and extrinsic Evolvable Hardware (EHW) to design sequential logic circuits. The implemented evolutionary algorithms are able to design logic circuits with size and complexity, which have not been demonstrated in published work. There are still plenty of opportunities to develop this new line of research for the synthesis, optimization and test of novel digital, analogue and mixed circuits. This should lead to a new generation of Electronic Design Automation tools.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Evolutionary algorithms for synthesis and optimisation of sequential logic circuits.

Considerable progress has been made recently 1n the understanding ofcombinational logic optimization. Consequently a large number of universityand industrial Electric Computing Aided Design (ECAD) programs are nowavailable for optimal logic synthesis of combinational circuits. The progresswith sequential logic synthesis and optimization, on the other hand, isconsiderably less mature.In recent years, evolutionary algorithms have been found to be remarkablyeffective way of using computers for solving difficult problems. This thesis is,in large part, a concentrated effort to apply this philosophy to the synthesisand optimization of sequential circuits.A state assignment based on the use of a Genetic Algorithm (GA) for theoptimal synthesis of sequential circuits is presented. The state assignmentdetermines the structure of the sequential circuit realizing the state machineand therefore its area and performances. The synthesis based on the GAapproach produced designs with the smallest area to date. Test results onstandard fmite state machine (FS:M) benchmarks show that the GA couldgenerate state assignments, which required on average 15.44% fewer gatesand 13.47% fewer literals compared with alternative techniques.Hardware evolution is performed through a succeSSlOn ofchanges/reconfigurations of elementary components, inter-connectivity andselection of the fittest configurations until the target functionality is reached.The thesis presents new approaches, which combine both genetic algorithmfor state assignment and extrinsic Evolvable Hardware (EHW) to designsequential logic circuits. The implemented evolutionary algorithms are able todesign logic circuits with size and complexity, which have not beendemonstrated in published work.There are still plenty of opportunities to develop this new line of research forthe synthesis, optimization and test of novel digital, analogue and mixedcircuits. This should lead to a new generation of Electronic DesignAutomation tools

Embedded System Design

A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues

The Good Behaviour Game intervention to improve behavioural and other outcomes for children aged 7–8 years: a cluster RCT

BackgroundUniversal, school-based behaviour management interventions can produce meaningful improvements in children’s behaviour and other outcomes. However, the UK evidence base for these remains limited.ObjectiveThe objective of this trial was to investigate the impact, value for money and longer-term outcomes of the Good Behaviour Game. Study hypotheses centred on immediate impact (hypothesis 1); subgroup effects (at-risk boys, hypothesis 2); implementation effects (dosage, hypothesis 3); maintenance/sleeper effects (12- and 24-month post-intervention follow-ups, hypothesis 4); the temporal association between mental health and academic attainment (hypothesis 5); and the health economic impact of the Good Behaviour Game (hypothesis 6).DesignThis was a two-group, parallel, cluster-randomised controlled trial. Primary schools (n = 77) were randomly assigned to implement the Good Behaviour Game for 2 years or continue their usual practice, after which there was a 2-year follow-up period.SettingThe trial was set in primary schools across 23 local authorities in England.ParticipantsParticipants were children (n = 3084) aged 7–8 years attending participating schools.InterventionThe Good Behaviour Game is a universal behaviour management intervention. Its core components are classroom rules, team membership, monitoring behaviour and positive reinforcement. It is played alongside a normal classroom activity for a set time, during which children work in teams to win the game to access the agreed rewards. The Good Behaviour Game is a manualised intervention delivered by teachers who receive initial training and ongoing coaching.Main outcome measuresThe measures were conduct problems (primary outcome; teacher-rated Strengths and Difficulties Questionnaire scores); emotional symptoms (teacher-rated Strengths and Difficulties Questionnaire scores); psychological well-being, peer and social support, bullying (i.e. social acceptance) and school environment (self-report Kidscreen survey results); and school absence and exclusion from school (measured using National Pupil Database records). Measures of academic attainment (reading, standardised tests), disruptive behaviour, concentration problems and prosocial behaviour (Teacher Observation of Child Adaptation Checklist scores) were also collected during the 2-year follow-up period.ResultsThere was no evidence that the Good Behaviour Game improved any outcomes (hypothesis 1). The only significant subgroup moderator effect identified was contrary to expectations: at-risk boys in Good Behaviour Game schools reported higher rates of bullying (hypothesis 2). The moderating effect of the amount of time spent playing the Good Behaviour Game was unclear; in the context of both moderate (≥ 1030 minutes over 2 years) and high (≥ 1348 minutes over 2 years) intervention compliance, there were significant reductions in children’s psychological well-being, but also significant reductions in their school absence (hypothesis 3). The only medium-term intervention effect was for peer and social support at 24 months, but this was in a negative direction (hypothesis 4). After disaggregating within- and between-individual effects, we found no temporal within-individual associations between children’s mental health and their academic attainment (hypothesis 5). Last, our cost–consequences analysis indicated that the Good Behaviour Game does not provide value for money (hypothesis 6).LimitationsLimitations included the post-test-only design for several secondary outcomes; suboptimal implementation dosage (mitigated by complier-average causal effect estimation); and moderate child-level attrition (18.5% for the primary outcome analysis), particularly in the post-trial follow-up period (mitigated by the use of full information maximum likelihood procedures).Future workQuestions remain regarding programme differentiation (e.g. how distinct is the Good Behaviour Game from existing behaviour management practices, and does this makes a difference in terms of its impact?) and if the Good Behaviour Game is impactful when combined with a complementary preventative intervention (as has been the case in several earlier trials).ConclusionThe Good Behaviour Game cannot be recommended based on the findings reported here

Aplicaciones de la teoría de la información y la inteligencia artificial al testing de software

Tesis inédita de la Universidad Complutense de Madrid, Facultad de Informática, Departamento de Ingeniería de Sistemas lnformáticos y de Computación, leída el 4-05-2022Software Testing is a critical field for the software industry, as it has the main tools used to ensure the reliability of the produced software. Currently, mor then 50% of the time and resources for creating a software product are diverted to testing tasks, from unit testing to system testing. Moreover, there is a huge interest into automatising this field, as software gets bigger and the amount of required testing increases. however, software Testing is not only an industry oriented field; it is also a really interesting field with a noble goal (improving the reliability of software systems) that at the same tieme is full of problems to solve....Es Testing Software es un campo crítico para la industria del software, ya que éste contienen las principales herramientas que se usan para asegurar la fiabilidad del software producido. Hoy en día, más del 50% del tiempo y recursos necesarios para crear un producto software son dirigidos a tareas de testing, desde el testing unitario al testing a nivel de sistema. Más aún, hay un gran interés en automatizar este campo, ya que el software cada vez es más grande y la cantidad de testing requerido crece. Sin embargo, el Testing de Software no es solo un campo orientado a la industria; también es un campo muy interesante con un objetivo noble (mejorar la fiabilidad de los sistemas software) que al mismo tiempo está lleno de problemas por resolver...Fac. de InformáticaTRUEunpu

Embedded System Design

A unique feature of this open access textbook is to provide a comprehensive introduction to the fundamental knowledge in embedded systems, with applications in cyber-physical systems and the Internet of things. It starts with an introduction to the field and a survey of specification models and languages for embedded and cyber-physical systems. It provides a brief overview of hardware devices used for such systems and presents the essentials of system software for embedded systems, including real-time operating systems. The author also discusses evaluation and validation techniques for embedded systems and provides an overview of techniques for mapping applications to execution platforms, including multi-core platforms. Embedded systems have to operate under tight constraints and, hence, the book also contains a selected set of optimization techniques, including software optimization techniques. The book closes with a brief survey on testing. This fourth edition has been updated and revised to reflect new trends and technologies, such as the importance of cyber-physical systems (CPS) and the Internet of things (IoT), the evolution of single-core processors to multi-core processors, and the increased importance of energy efficiency and thermal issues