Vision-based neural network classifiers and their applications

A thesis submitted for the degree of Doctor of Philosophy of University of LutonVisual inspection of defects is an important part of quality assurance in many fields of production. It plays a very useful role in industrial applications in order to relieve human inspectors and improve the inspection accuracy and hence increasing productivity. Research has previously been done in defect classification of wood veneers using techniques such as neural networks, and a certain degree of success has been achieved. However, to improve results in tenus of both classification accuracy and running time are necessary if the techniques are to be widely adopted in industry, which has motivated this research. This research presents a method using rough sets based neural network with fuzzy input (RNNFI). Variable precision rough set (VPRS) method is proposed to remove redundant features utilising the characteristics of VPRS for data analysis and processing. The reduced data is fuzzified to represent the feature data in a more suitable foml for input to an improved BP neural network classifier. The improved BP neural network classifier is improved in three aspects: additional momentum, self-adaptive learning rates and dynamic error segmenting. Finally, to further consummate the classifier, a uniform design CUD) approach is introduced to optimise the key parameters because UD can generate a minimal set of uniform and representative design points scattered within the experiment domain. Optimal factor settings are achieved using a response surface (RSM) model and the nonlinear quadratic programming algorithm (NLPQL). Experiments have shown that the hybrid method is capable of classifying the defects of wood veneers with a fast convergence speed and high classification accuracy, comparing with other methods such as a neural network with fuzzy input and a rough sets based neural network. The research has demonstrated a methodology for visual inspection of defects, especially for situations where there is a large amount of data and a fast running speed is required. It is expected that this method can be applied to automatic visual inspection for production lines of other products such as ceramic tiles and strip steel

Teacher efficacy, teacher burnout, and attitudes toward students with autism.

Students with autism require a variety of supports to be successful in classrooms. Because of this, special education teachers need additional training to address these needs along with balancing the demands of the rest of their caseload. This daunting task can often lead to lower levels of efficacy (general teaching and personal teacher) and increased levels of burnout. The Teacher Efficacy Scale-Short Form (Hoy & Woolfolk 1993), Teacher Burnout Scale (Seidman & Zager, 1987), and Autism Attitude Scale for Teachers (Olley et al., 1981) were chosen for this study. The Olley et al. work was modified to reflect current trends in language, remove efficacy-based questions, and add several new questions; the scale was renamed the Teachers\u27 Attitudes about Autism Scale. The final questionnaire, Autism Education Survey (AES), consisted of the three scales plus environmental factors. The central research question reflects the purpose of this study: What is the effect of teacher efficacy and teacher burnout on educators\u27 attitudes towards students with autism? After human subjects approval, the survey was administered to the 684 teachers who fit the profile, those special education teachers in a large urban district in a south central state who held LBD and moderate/severe disability certificates; 267 (39%) responded. Descriptive statistics; psychometric work (factor analysis, Cronbach\u27s alpha, and interscale correlations), and multiple regression were conducted. The results for Research Question 1 demonstrated that the environmental factors are essentially independent of attitudes towards autism with the exception of hours spent in an autism workshop. Analysis for Research Questions 2 and 3 revealed that for special education teachers dealing with autism, both general teaching efficacy and personal teacher efficacy were significant for Autism-Inclusion and Autism-Supports. For Teacher Burnout, the Attitudes Towards Students and Coping with Stress were the most significant of the four subscales. In Research Question 3, the hierarchical regressions produced essentially the same results as RQ2, except that the environmental factors (entered first) were basically rendered non-significant when the professional characteristics were added, demonstrating that Teacher Efficacy and Teacher Burnout are the stronger predictors of teachers\u27 attitudes about autism. The implications of the results are discussed

IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing

Formation control of autonomous vehicles with emotion assessment

Autonomous driving is a major state-of-the-art step that has the potential to transform the mobility of individuals and goods fundamentally. Most developed autonomous ground vehicles (AGVs) aim to sense the surroundings and control the vehicle autonomously with limited or no driver intervention. However, humans are a vital part of such vehicle operations. Therefore, an approach to understanding human emotions and creating trust between humans and machines is necessary. This thesis proposes a novel approach for multiple AGVs, consisting of a formation controller and human emotion assessment for autonomous driving and collaboration. As the interaction between multiple AGVs is essential, the performance of two multi-robot control algorithms is analysed, and a platoon formation controller is proposed. On the other hand, as the interaction between AGVs and humans is equally essential to create trust between humans and AGVs, the human emotion assessment method is proposed and used as feedback to make autonomous decisions for AGVs. A novel simulation platform is developed for navigating multiple AGVs and testing controllers to realise this concept. Further to this simulation tool, a method is proposed to assess human emotion using the affective dimension model and physiological signals such as an electrocardiogram (ECG) and photoplethysmography (PPG). The experiments are carried out to verify that humans' felt arousal and valence levels could be measured and translated to different emotions for autonomous driving operations. A per-subject-based classification accuracy is statistically significant and validates the proposed emotion assessment method. Also, a simulation is conducted to verify AGVs' velocity control effect of different emotions on driving tasks

Experimental investigation and modelling of the heating value and elemental composition of biomass through artificial intelligence

Abstract: Knowledge advancement in artificial intelligence and blockchain technologies provides new potential predictive reliability for biomass energy value chain. However, for the prediction approach against experimental methodology, the prediction accuracy is expected to be high in order to develop a high fidelity and robust software which can serve as a tool in the decision making process. The global standards related to classification methods and energetic properties of biomass are still evolving given different observation and results which have been reported in the literature. Apart from these, there is a need for a holistic understanding of the effect of particle sizes and geospatial factors on the physicochemical properties of biomass to increase the uptake of bioenergy. Therefore, this research carried out an experimental investigation of some selected bioresources and also develops high-fidelity models built on artificial intelligence capability to accurately classify the biomass feedstocks, predict the main elemental composition (Carbon, Hydrogen, and Oxygen) on dry basis and the Heating value in (MJ/kg) of biomass...Ph.D. (Mechanical Engineering Science

Conflict Style is not a Label: The Relationship of Age, Education Level, Work Level, Reason for Assessment, and Time Between Assessments to Conflict Style Change

Organizations and research that are only measuring conflict style one time, are treating conflict style as a trait or label. However, conflict style can change over time, and with context. Even the circumstances around the conflict itself may impact how individuals handle conflict. This means that individuals may demonstrate different conflict styles in different circumstances. There is little research that explores the implications of individual conflict style change if measured at different times and in different circumstances. Nor is there much research that explores what factors may have an influence on conflict style change. This study explores whether conflict style significantly changes for individuals who completed the Thomas-Kilmann Conflict MODE Instrument (TKI) assessment two times. The research examined data from 11,821 participants and found a statistically significant relationship between conflict style change and age of participants, the highest level of participant education, and the duration of time between taking the first and second assessment. The results of this study suggested that it may be more appropriate to assess conflict style multiple times if conflict style metrics are contributing to research outcomes or organization training determination and planning. Because conflict style can change for individuals, it may be inappropriate to consider conflict style a trait, or use it as a label. Instead, conflict style may be better suited for the evaluation of organizational conflict learning objectives, and situationally specific individual conflict style state observation

Constructions of higher ability in two maintained and two independent schools

This research is an exploration of constructions of ability, especially `greater ability' within four Maintained and Independent case study schools in Scotland, from a variety of group perspectives. It seeks to illuminate the commonalties and differences between and within schools in individuals' implicit theories of ability and explores the possible implications of such constructs. An analysis of policy and political debate provided the starting point for this research. This led into the empirical work in four case study schools. Data were gathered from semi structured interviews with headteachers, principal teachers of English, Maths, Art and music, class teachers, parents and pupils. In addition, non-participant observation took place for each subject area and class. Multiple perspectives helped to create meaningful layers of perceptions of ability while also making it possible to analyse the complexity of values and beliefs within each class and school. The research found that there were distinctions to be made between schools in both sectors which reflected contrasting viewpoints, echoing `communitarian concerns' and the `culture of self interest' (Ball, 1997). However, the experiences, judgements and choices of individuals presented a more complex pattern in which contradictory beliefs could lead to experiences of dissonance in maintained schools and highlighted the importance of the negotiated ability constructs being brought to bear by individuals within institutions

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

Advanced Automation for Space Missions

The feasibility of using machine intelligence, including automation and robotics, in future space missions was studied