Development of neural units with higher-order synaptic operations and their applications to logic circuits and control problems

Neural networks play an important role in the execution of goal-oriented paradigms. They offer flexibility, adaptability and versatility, so that a variety of approaches may be used to meet a specific goal, depending upon the circumstances and the requirements of the design specifications. Development of higher-order neural units with higher-order synaptic operations will open a new window for some complex problems such as control of aerospace vehicles, pattern recognition, and image processing. The neural models described in this thesis consider the behavior of a single neuron as the basic computing unit in neural information processing operations. Each computing unit in the network is based on the concept of an idealized neuron in the central nervous system (CNS). Most recent mathematical models and their architectures for neuro-control systems have generated many theoretical and industrial interests. Recent advances in static and dynamic neural networks have created a profound impact in the field of neuro-control. Neural networks consisting of several layers of neurons, with linear synaptic operation, have been extensively used in different applications such as pattern recognition, system identification and control of complex systems such as flexible structures, and intelligent robotic systems. The conventional linear neural models are highly simplified models of the biological neuron. Using this model, many neural morphologies, usually referred to as multilayer feedforward neural networks (MFNNs), have been reported in the literature. The performance of the neurons is greatly affected when a layer of neurons are implemented for system identification, pattern recognition and control problems. Through simulation studies of the XOR logic it was concluded that the neurons with linear synaptic operation are limited to only linearly separable forms of pattern distribution. However, they perform a variety of complex mathematical operations when they are implemented in the form of a network structure. These networks suffer from various limitations such as computational efficiency and learning capabilities and moreover, these models ignore many salient features of the biological neurons such as time delays, cross and self correlations, and feedback paths which are otherwise very important in the neural activity. In this thesis an effort is made to develop new mathematical models of neurons that belong to the class of higher-order neural units (HONUs) with higher-order synaptic operations such as quadratic and cubic synaptic operations. The advantage of using this type of neural unit is associated with performance of the neurons but the performance comes at the cost of exponential increase in parameters that hinders the speed of the training process. In this context, a novel method of representation of weight parameters without sacrificing the neural performance has been introduced. A generalised representation of the higher-order synaptic operation for these neural structures was proposed. It was shown that many existing neural structures can be derived from this generalized representation of the higher-order synaptic operation. In the late 1960’s, McCulloch and Pitts modeled the stimulation-response of the primitive neuron using the threshold logic. Since then, it has become a practice to implement the logic circuits using neural structures. In this research, realization of the logic circuits such as OR, AND, and XOR were implemented using the proposed neural structures. These neural structures were also implemented as neuro-controllers for the control problems such as satellite attitude control and model reference adaptive control. A comparative study of the performance of these neural structures compared to that of the conventional linear controllers has been presented. The simulation results obtained in this research were applicable only for the simplified model presented in the simulation studies

U-model based adaptive internal model control for tracking of nonlinear dynamic plants

We present a technique to infer lower bounds on the worst-case runtime complexity of integer programs, where in contrast to earlier work, our approach is not restricted to tail-recursion. Our technique constructs symbolic representations of program executions using a framework for iterative, under-approximating program simplification. The core of this simplification is a method for (under-approximating) program acceleration based on recurrence solving and a variation of ranking functions. Afterwards, we deduce asymptotic lower bounds from the resulting simplified programs using a special-purpose calculus and an SMT encoding. We implemented our technique in our tool LoAT and show that it infers non-trivial lower bounds for a large class of examples

Dynamical Systems

Complex systems are pervasive in many areas of science integrated in our daily lives. Examples include financial markets, highway transportation networks, telecommunication networks, world and country economies, social networks, immunological systems, living organisms, computational systems and electrical and mechanical structures. Complex systems are often composed of a large number of interconnected and interacting entities, exhibiting much richer global scale dynamics than the properties and behavior of individual entities. Complex systems are studied in many areas of natural sciences, social sciences, engineering and mathematical sciences. This special issue therefore intends to contribute towards the dissemination of the multifaceted concepts in accepted use by the scientific community. We hope readers enjoy this pertinent selection of papers which represents relevant examples of the state of the art in present day research. [...

Robots learn to behave: improving human-robot collaboration in flexible manufacturing applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Safe navigation and human-robot interaction in assistant robotic applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

The management of people at work: strategy, HRM, discourse

This thesis critically examines the concept of strategic human resource management (HRM). Existing 'critical' approaches identify prescriptive HRNI literature as 'rhetoric' that does not match 'reality'. Such an approach understands management initiatives as separate, individual, discrete, and ad hoc. However, this thesis develops an alternative perspcctivc, informed by a Foucauldian approach to 'discourse', that understands 'HRM' and 'strategy' as cultural constructs that are used by actors as they 'make sense' of discursively constructed organizational 'realities'. This perspective is then utilized to demonstrate that the existing 'critical' approaches are engaged in particular practices that define strategic HRM in a way that constructs the 'gap' between 'rhetoric' and 'reality' as HRM is simultaneously created as an academic subject. This alternative perspective provides a means of understanding and analysing prescriptive management literature and texts generated from interviews with managers in terms of two different discursively constructed 'rationalities'. Both 'rationalities' establish causal relationships between concepts of environment, organization and individual as organizational 'reality' is constructed. This perspective is utilized in the identification of the connections that are established between the managerial initiatives that are thought of as separate, individual, discrete, and ad hoc by the 'critical' literature. There are two parts to this thesis. The first part describes the development of HM4, outlines a Foucauldian conceptualization of 'discourse, and re-examines prescriptive and 'critical' HRM literature. The second part analyses texts generated from interviews with HRIpersonnel managers in a range of public and private sector organizations. This analysis demonstrates that, while there is great variety in the descriptions of organizational 'reality', connections between concepts of environment, organization and individual arc established as two key 'rationalities' are discursively constructed. It is argued that these 'rationalities' position people and practices within organizational 'reality'

Leadership, emotions and school outcomes in Romania

Personal and collective emotions play an important role in our private and social lives. Educational research suggests that emotions are powerful motivational forces that can impact upon leadership practices as well as on teaching and learning at individual and classroom level. However, less is known about the role of emotional experiences and displays in relation to leadership practices and school outcomes at organisational level. In order to develop more substantial knowledge, this mixed method study aims to explore the relationship between leadership styles, emotions and school outcomes from an organisational perspective in several urban schools from Timisoara, Romania. A sample of 408 teaching and non-teaching staff from 18 schools took part in a survey and 14 participants from two selected case study schools took part in semi-structured interviews. A widely used model of leadership is proposed by Bass & Avolio (1994) who identify transformational, transactional and laissez-faire practices. In this study, the quantitative data analysis using the Multifactorial Leadership Questionnaire developed by Bass and Avolio (ibid) suggests that a hybrid leadership that combines transformational and transactional elements such as contingent reward, individual consideration and charismatic behaviours is positively associated with positive emotions such as joy, enthusiasm and hope and with better outcomes such as perceived school success. The survey findings identify more variation and subtlety of negative emotions compared to positive emotions and also examine the role of self-other rapport in experiencing and displaying emotion at work. Secondly, the qualitative data reveal various contextualized meanings of leadership, emotions and school success, provides an integrated perspective of findings and allows for comparison of the overall results with previously published literature. Furthermore, the thesis presents emergent theoretical models for the study of leadership, emotions and school development and performance. Finally, the implications of the overall findings for policy and practice are discussed by taking into consideration the Romanian cultural and educational context

Pittsburgh\u27s Response to Deindustrialization: Renaissance, Renewal and Recovery, 1946-1999

Pittsburgh was able to gradually ease its transition into a post-industrial economy in the second half of the twentieth century because of an elite-driven planning movement known as the Pittsburgh Renaissance. The Renaissance first addressed the physical failings of the city and sought state legislation that would support further urban redevelopment immediately following World War II. While the physical improvements were underway, Renaissance organizers began working with the University of Pittsburgh to upgrade Pitt\u27s educational and recreational facilities so that it would become an engine for the city\u27s future economic growth. City support for improved facilities, especially those pertaining to the growing medical center and scientific research programs, laid the foundation for the city\u27s post-industrial economy. Evolving plans for a new municipal amphitheater also began in the mid-1940s, but merged with the federal urban renewal program in the mid-1950s. The intention was to turn Pittsburgh into a business tourism destination that would highlight the city\u27s cultural assets with an adjacent Center for the Arts, but the finished facility failed to meet the expectations planners set for it and constituted a transformative experience for the Renaissance movement. When Renaissance planning resumed in the late 1970s, it returned without centralized control, but it shared the goals of promoting Downtown Pittsburgh as a business center, diversifying the city\u27s economy away from steel, and emphasizing the city\u27s cultural institutions. As Renaissance continued through the next two decades, these core values continued to motivate projects and link it to past accomplishments solidifying the importance of planning to the city\u27s operations. By responding to the threat of capital flight in the 1940s, the Renaissance created a movement that could outlast any individual participants, suspend and resume operations as needed, and adapt to meet different crises that emerged over time