Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

A prevalent and pervasive view of designing is that it can be modeled using variables and decisions made about what values should be taken by these variables. The activity of designing is carried out with the expectation that the designed artifact will operate in the natural world and the social world. These worlds impose constraints on the variables and their values; so, design could be described as a goal-oriented, constrained, decision- making activity. However, design distinguish- es itself from other similarly described activities not only by its domain but also by additional necessary features. Designing involves exploration, exploring what variables might be appropriate. The process of explo- ration involves both goal variables and deci- sion variables. In addition, designing involves learning: Part of the exploration activity is learning about emerging features as a design proceeds. Finally, design activity occurs within two contexts: the context within which the designer operates and the context produced by the developing design itself. The designer’s perception of what the context is affects the implication of the context on the design. The context shifts as the designer’s perceptions change. Design activity can be now characterized as a goal-oriented, con- strained, decision-making, exploration, and learning activity that operates within a con- text that depends on the designer’s percep- tion of the context.

Design Prototypes: A Knowledge Representation Schema for Design

/pdf/online-communities-designing-usability-supporting-1rx78h3t04.pdf

Online communities – Designing Usability, Supporting Sociability

Culture and Consumption: New Approaches to the Symbolic Character of Consumer Goods and Activities

International Joint Conference on Neural Networks

Anomaly detection is the problem of finding patterns in data that do not conform to an a priori expected behavior. This is related to the problem in which some samples are distant, in terms of a given metric, from the rest of the dataset, where these anomalous samples are indicated as outliers. Anomaly detection has recently attracted the attention of the research community, because of its relevance in real-world applications, like intrusion detection, fraud detection, fault detection and system health monitoring, among many others. Anomalies themselves can have a positive or negative nature, depending on their context and interpretation. However, in either case, it is important for decision makers to be able to detect them in order to take appropriate actions. The petroleum industry is one of the application contexts where these problems are present. The correct detection of such types of unusual information empowers the decision maker with the capacity to act on the system in order to correctly avoid, correct or react to the situations associated with them. In that application context, heavy extraction machines for pumping and generation operations, like turbomachines, are intensively monitored by hundreds of sensors each that send measurements with a high frequency for damage prevention. In this paper, we propose a combination of yet another segmentation algorithm (YASA), a novel fast and high quality segmentation algorithm, with a one-class support vector machine approach for efficient anomaly detection in turbomachines. The proposal is meant for dealing with the aforementioned task and to cope with the lack of labeled training data. As a result, we perform a series of empirical studies comparing our approach to other methods applied to benchmark problems and a real-life application related to oil platform turbomachinery anomaly detection.

Anomaly detection based on sensor data in petroleum industry applications.

Electronic government allows a broad range of citizens to access governamental information and services, as well as to participate in the government decision-making process On the other hand, it imposes a higher challenge on a web designer to avoid digital exclusion Before proposing guidelines to design e-gov sites, it is important to have objective methods to evaluate their quality Traditional inspection methods do not cover the specificities of e-gov sites This work proposes an extension of Nielsen's heuristic evaluating method, applied to the information, services and citizens' participation categories Broad accessibility, interoperability, security and privacy, information truth and precision, service agility, and transparency are added The g-Quality method was instrumental as an objective evaluation form It was applied to 127 Brazilian e-gov sites The extended method found more problems, resulting in more negative ratings than the Nielsen's original method The Brazilian public sites quality level was determined by using the g-Quality method, producing positive results

/pdf/a-quality-inspection-method-to-evaluate-e-government-sites-1s6t2h97um.pdf

A quality inspection method to evaluate e-government sites

https://www.addlabs.uff.br/papers/No%207%20-%202004%20-%20Building%20project%20ontology%20with%20extreme%20collaboration%20and%20virtual%20design%20and%20construction.pdf

Building a project ontology with extreme collaboration and virtual design and construction

Currently design documentation rarely records the designer's decision process or the reasons behind those decisions This paper describes an effort to improve design documentation by having the computer act as an intelligent apprentice to the designer to capture the rationale during the design process The apprentice learns about the features that make a specific case different from the standard Whenever the designer proposes a design action that differs from the apprentice's expectations, the interface will ask for the designer for justifications to explain the differences Later queries for design rationale are answered using a combination of the apprentice's domain knowledge and the designer-supplied justifications The apprentice model is being implemented in a prototype system called ADD (Augmenting Design Documentation) The initial focus of the work is on HVAC (Heating, Ventilation, and Air Conditioning) design Our starting point for implementing the apprentice model is observing how people develop HVAC system designs and then explain those designs

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0890060400002948

Ana Cristina Bicharra Garcia

Papers

Anomaly detection based on sensor data in petroleum industry applications.

A quality inspection method to evaluate e-government sites

Building a project ontology with extreme collaboration and virtual design and construction

Acquiring design knowledge through design decision justification

High-speed idea filtering with the bag of lemons