Printing Process Parameters Identification System

The paper presents the research aimed at setting up and developing a software system for the printing process parameters identification based on modern computer and software systems, algorithmic principles, principles of expert systems construction and advanced learning. Thus, the possibilities of application of contemporary software tools were investigated, which facilitates the process and forms the program structure of the model that uses programming languages based on the expert systems construction principles and tools for the development of system model based on the principles of modern learning. For complex model development, concepts of process knowledge bases with influential process parameters of printing technique have been developed through modelling and construction based on the logic of expert systems with the presentation, use and involvement of experts knowledge in decision making with the evaluation of the impact of individual parameters. In addition to this approach, a module was developed using modern software tools based on an algorithmic principle and a module for identifying printing process parameters using modern platforms based on advanced learning. Sophisticated software model has been made through the research and developed with databases of process parameter identification systems based on modern software tools. This tool enables a significant expedition of the solution resolving, thus improving the graphical production process and the processes of acquiring and expanding knowledge. The model is based on integrative modules: a printing process parameters identification system based on algorithmic program structure systems, a printing process parameters identification system based on expert system building principles, and a printing process parameter identification system based on modern learning systems

Randomly Evolving Idiotypic Networks: Structural Properties and Architecture

We consider a minimalistic dynamic model of the idiotypic network of B-lymphocytes. A network node represents a population of B-lymphocytes of the same specificity (idiotype), which is encoded by a bitstring. The links of the network connect nodes with complementary and nearly complementary bitstrings, allowing for a few mismatches. A node is occupied if a lymphocyte clone of the corresponding idiotype exists, otherwise it is empty. There is a continuous influx of new B-lymphocytes of random idiotype from the bone marrow. B-lymphocytes are stimulated by cross-linking their receptors with complementary structures. If there are too many complementary structures, steric hindrance prevents cross-linking. Stimulated cells proliferate and secrete antibodies of the same idiotype as their receptors, unstimulated lymphocytes die. Depending on few parameters, the autonomous system evolves randomly towards patterns of highly organized architecture, where the nodes can be classified into groups according to their statistical properties. We observe and describe analytically the building principles of these patterns, which allow to calculate number and size of the node groups and the number of links between them. The architecture of all patterns observed so far in simulations can be explained this way. A tool for real-time pattern identification is proposed.Comment: 19 pages, 15 figures, 4 table

Capacity building for flood management in developing countries under climate change

Department Head: Luis A. Garcia.2010 Summer.Includes bibliographical references.Climate change will bring new flood threats, especially in developing countries. In addition, the contexts surrounding flood management have been shifting globally. If developing countries are to address serious flood risks caused by insufficient infrastructure and lack of legislation and enforcement programs, they must improve institutional, organizational, and individual capacities for flood management systems. The research for this dissertation explored how to alleviate flood damage and achieve sound economic growth in developing countries in the context of a global paradigm shift in flood management under climate change with a focus on capacity building. The research established a conceptual model to clarify the relationships between flood risks, elements of flood management systems, and the influence of institutional, organizational, and individual capacities on the system elements. The research also offered a tool to evaluate how capacity affects the systems and to identify the needs for capacity building. Additionally, the research established and tested capacity building methodologies for flood management in developing countries under climate change, including both principles and the procedures to implement them. Case studies in Jakarta, Indonesia and the Tokai region, Japan were analyzed to identify capacity building needs and constraints in developing countries as well as factors determining effectiveness of flood management systems. They showed that while institutional arrangements are essential for effective flood management, their effectiveness depends on the capacity to implement them. While infrastructure may mitigate flood damage, the limitations of infrastructure must be recognized and should not induce complacency. Awareness of flood threats and management by the local community is a key issue and data accessibility is fundamental to the flood management process. The conceptual model used here identified capacity-related flood management problems and their interrelationships clarified the needs for capacity building at institutional, organizational, and individual levels throughout the flood management processes. Case studies in Manila, the Philippines and the Nyando river basin, Kenya led to the following principles of capacity building for flood management in developing countries under climate change: 1. Capacity to implement both structural and non-structural measures needs to be developed, 2. All institutional, organizational, and individual capacity is crucial, 3. Leadership and decision-making capacity are more necessary under increased flood risks, and 4. Capacity to secure the 'three Es' (effectiveness, efficiency, and equity) is the key to increasing feasibility of flood management means. Then, capacity building procedures to implement the principles were formulated, which consisted of the processes of capacity assessments; integration of resources including formulation and prioritization of alternatives and implementation of priority measures; and human resources development to make the most use of the resources. The case studies also suggested that complexity of problems and levels of self-sufficiency differed between urban and rural areas regardless of the shared necessity of comprehensive capacity building. Following the recent paradigm shift on public policy and the increasing complexity and uncertainty under climate change, the requirements to identify and solve problems in a comprehensive and integrated manner are even more important. Considering that problems in developing countries are more complex and intertwined than those in developed countries, the trade-offs between the requirements for flood management and the need to cope with flood risks in developing countries take on greater urgency. Given these concerns, the research offered the tools to assess and improve flood management systems. Institutional, organizational, and individual capacity building based on appropriate problem identification and needs clarification is time-consuming yet ultimately, it is the fastest and the most inevitable road for effective flood management under climate change

Perceived Self-in-Group Prototypicality and Psychological Well-being

Recent work examining health and well-being has identified people’s group memberships as important contributors to positive life outcomes. Social identification with these groups, in particular, has been identified as a powerful positive predictor of psychological well-being. In the current thesis I present five studies, two correlational, two experimental and one overarching study which combined the data from the preceding studies. Each of these studies expands upon this earlier work from within the social identity approach to understanding psychological well-being by examining not only people’s relative levels of social identification with their groups, but their perceptions of their own relative in-group prototypicality within these groups. Building explicitly upon self-categorization theory principles, the results of these five studies demonstrate that: (1) perceived self-in-group prototypicality can be measured separately from social identification with a group, and that (2) these two combine multiplicatively, so that people who have both high social identification and high perceptions of self-in-group prototypicality also have the highest level of psychological well-being on several psychological well-being outcome measures. This latter effect occurs even after controlling for known factors related to these outcomes, including age, gender and major life stressors. Overall, this thesis provides evidence for the first time that perceived self-in-group prototypicality contributes to predicting whether a social group may be beneficial to an individual’s psychological well-being. The theoretical and clinical implications of the findings of this thesis are then discussed in relation to the social factors in the biopsychosocial model of psychological well-being

Developing a building sustainability assessment model for the South African built environment : searching for new appoaches to improve the effectiveness of building assessment

The fundamental premise of research presented in this thesis is the search for conceptual approaches and practical measures to enhance the practice of building assessment in fostering sustainable construction. Hence, this thesis advances the theory for the practice of building assessment that incorporates the principles of sustainable development. The research findings are communicated via a functional specification for a building sustainability assessment model, suitable to the South African context. The research focuses primarily on process-related aspects of building assessment. Important insights for the development of the model's specification are gained from the review of the practice and experience of Environmental Assessment (EA) in addressing sustainability at a project level. Lessons are also drawn from the Process Protocol (PP), which provides a means of describing the building project process in a way that is transparent and accessible to building stakeholders. The most relevant insights sourced from these two fields of expertise are grouped into three key themes. These include integration (i.e. integration of sustainability principles, stakeholder values and perspectives), transparency and accessibility (i.e. open participation and communication competence) and collaborative learning (i.e. active involvement and transfer of knowledge). It is proposed that these themes form key outcomes of building assessment and be viewed as crucial functionalities of the model. The model is presented as a generic method that can be customised to suit the context of its application. The potential use scenarios of the model, identified in this thesis, include the formulation of a building project proposal, a building project sustainability appraisal and a building performance audit. The use of process maps produced through this research facilitates the identification of interfaces between the model and the building process in terms of decision-points and associated information needs in each use scenario. The model's user personas are also discussed (i.e. building stakeholders) with regard to the potential benefits and challenges of their participation in the building assessment process. The theory for building assessment advanced in this thesis was validated during a workshop with South African academics and built environment practitioners, held at the University of Cape Town. The thesis concludes that building assessment methods can do more than assess the sustainability of a building. More importantly, they provide a means of introducing the principles of sustainable development into the processes that produce the built end-product. This suggests a need to move beyond the terminology of building assessment and instead talk of enhancement models that would facilitate a shift in the practice of building assessment from measuring to one of proactive improvement

BIM adoption and implementation for architectural practices

Severe issues about data acquisition and management arise during the design creation and development due to complexity, uncertainty and ambiguity. BIM (Building Information Modelling) is a tool for a team based lean design approach towards improved architectural practice across the supply chain. However, moving from a CAD (Computer Aided Design) approach to BIM (Building Information Modelling) represents a fundamental change for individual disciplines and the construction industry as a whole. Although BIM has been implemented by large practices, it is not widely used by SMEs (Small and Medium Sized Enterprises). Purpose: This paper aims to present a systematic approach for BIM implementation for Architectural SMEs at the organizational level Design/Methodology/Approach: The research is undertaken through a KTP (Knowledge transfer Partnership) project between the University of Salford and John McCall Architects (JMA) a SME based in Liverpool. The overall aim of the KTP is to develop lean design practice through BIM adoption. The BIM implementation approach uses a socio-technical view which does not only consider the implementation of technology but also considers the socio-cultural environment that provides the context for its implementation. The action research oriented qualitative and quantitative research is used for discovery, comparison, and experimentation as it provides �learning by doing�. Findings: The strategic approach to BIM adoption incorporated people, process and technology equally and led to capacity building through the improvements in process, technological infrastructure and upskilling of JMA staff to attain efficiency gains and competitive advantages. Originality/Value: This paper introduces a systematic approach for BIM adoption based on the action research philosophy and demonstrates a roadmap for BIM adoption at the operational level for SME companie

Simultaneous Learning of Contact and Continuous Dynamics

Robotic manipulation can greatly benefit from the data efficiency, robustness, and predictability of model-based methods if robots can quickly generate models of novel objects they encounter. This is especially difficult when effects like complex joint friction lack clear first-principles models and are usually ignored by physics simulators. Further, numerically-stiff contact dynamics can make common model-building approaches struggle. We propose a method to simultaneously learn contact and continuous dynamics of a novel, possibly multi-link object by observing its motion through contact-rich trajectories. We formulate a system identification process with a loss that infers unmeasured contact forces, penalizing their violation of physical constraints and laws of motion given current model parameters. Our loss is unlike prediction-based losses used in differentiable simulation. Using a new dataset of real articulated object trajectories and an existing cube toss dataset, our method outperforms differentiable simulation and end-to-end alternatives with more data efficiency. See our project page for code, datasets, and media: https://sites.google.com/view/continuous-contact-nets/homeComment: 13 pages, 5 figures. Accepted to Conference on Robot Learning (CoRL) 2023. Project webpage with code, datasets, media, and OpenReview link at https://sites.google.com/view/continuous-contact-nets/hom

Development of a Novel Methodology for the Identification of VOC Emission Sources in Indoor Environments based on the Material Emission Signatures and Air Samples measured by PTR-MS

One of the recent important challenges in the research field of indoor air quality is the identification of indoor Volatile Organic Compound (VOC) emission sources to clearly pinpoint the sources of concern in a field condition. This study represents the first attempt in developing a new technique to find the sources that may be invisible or hidden based on the inspection even of experts when a building with problems of indoor air quality is suspected. The objectives of this study were 1) to determine VOC emission signatures specific to nine typical building materials by using an on-line analytical monitoring device, Proton Transfer Reaction - Mass Spectrometry (PTR-MS), 2) to explore the correlation between the PTR-MS measurements and the measurements of acceptability by human subjects, 3) to develop and evaluate a methodology to identify individual sources of VOC emissions based on the measurements of mixed air samples and the PTR-MS material emission signatures, 4) to determine the long-term variation of VOC emission signatures over time, and 5) to develop a method to account for the long-term variation of emission signatures in the application of the emission source identification method. Samples of nine building materials were tested individually and in combination, including carpet, ceiling material, gypsum board, linoleum, two paints, polyolefine, PVC and wood. VOC emissions from each material were measured in a 50-liter small-scale chamber. Chamber air was sampled by PTR-MS to establish a database of emission signatures unique to each individual material. Sorbent tube sampling and TD-GC/MS analysis were also performed to identify the major VOCs emitted and to compare the resulting data with the PTR-MS emission signatures. The data on the acceptability of air quality assessed by human subjects were obtained from a previous experimental study in which the emissions from the same batch of materials were determined under the same area-specific ventilation rates as in the case of the current measurements with PTR-MS. The same task was performed to measure combined emissions from material mixtures for the application and validation of a signal separation methodology and its source identification enhancement by the consideration of long-term emissions. The methodology was developed based on signal processing principles by employing the method of multiple regression least squares (MRLS) and a normalization technique. Source models were employed to track the change of individual material emission signatures by PTR-MS over a long period of time. It is concluded that: 1) PTR-MS can be an effective tool for establishing VOC emission signatures of material types, and there were sufficient correlations (i.e. Correlation coefficient r \u3c -0.92 ) between the PTR-MS measurements and the acceptability of air quality for the nine materials tested when the sum of selected major individual VOC odor indices was used to represent the emission level measured by PTR-MS; 2) the proposed method for source identification could identify the individual sources at high success rates under laboratory conditions with two, three, five and seven materials present; and 3) the long-term (over nine months) variation of emission factors of the tested materials could be well represented by an empirical power-law model or a mechanistic diffusion based model, and the model coefficients could be estimated based on relatively a short-term set of emission measurements (i.e. within 28 days). The source models could also be used to predict the variation of material emission signatures, which could in turn be used for source identification. Further experiments and investigation are needed to apply the presented source identification method under real field conditions