Heat losses from occupant body by means of convection, radiation, vapor, and sweat are essential data for indoor climate and energy simulations. Heat losses depend on the metabolic activity and body surface area. Higher variations of body surface area of occupants are observed in day care centers, kinder gardens and schools compared to other building categories (Tables 2 and 3) and these variations need to be accounted, otherwise in these building categories heat gains, CO2 and humidity generation are overestimated. Indoor temperature, humidity level, air velocity, and clothing insulation have significant influences on dry and total heat losses from occupant body leading to typical values for summer and winter. The data presented in this article are related to the research article entitled Occupancy schedules for energy simulation in new prEN16798-1 and ISO/FDIS 17772-1 standards (Ahmed et al., 2017) [1].

Abstract. Virtual 3D cities are becoming increasingly important as a means of visually communicating diverse urban-related information. To get a deeper understanding of a human’s cognitive experience of virtual 3D cities, this paper presents a user study on the human ability to perceive building categories (e.g. residential home, office building, building with shops etc.) from geometric 3D building representations. The study reveals various dependencies between geometric properties of the 3D representations and the perceptibility of the building categories. Knowledge about which geometries are relevant, helpful or obstructive for perceiving a specific building category is derived. The importance and usability of such knowledge is demonstrated based on a perception-guided 3D building abstraction process.

Virtual 3D cities are becoming increasingly important as a means of visually communicating diverse urban-related information. To get a deeper understanding of a human’s cognitive experience of virtual 3D cities, this paper presents a user study on the human ability to perceive building categories (e.g. residential home, office building, building with shops etc.) from geometric 3D building representations. The study reveals various dependencies between geometric properties of the 3D representations and the perceptibility of the building categories. Knowledge about which geometries are relevant, helpful or obstructive for perceiving a specific building category is derived. The importance and usability of such knowledge is demonstrated based on a perception-guided 3D building abstraction process.

This book addresses the topic of linguistic categorization from a novel perspective. While most of the early research has focused on how linguistic systems reflect some pre-existing ways of categorizing experience, the contributions included in this volume seek to understand how linguistic resources of various nature (prosodic cues, affixes, constructions, discourse markers, …) can be ‘put to work’ in order to actively build categories in discourse and in interaction, to achieve social goals. This question is addressed in different ways by researchers from different subfields of linguistics, including psycholinguistics, conversation analysis, linguistic typology and discourse pragmatics, and a major point of innovation is represented in fact by the interdisciplinary nature of the volume and in the systematic search for converging evidence.

The PercEVAL model is intended to learn concepts through pseudo-visual observations. PercEVAL is a connectionist sub-system of MoHA, an hybrid model designed for knowledge learning in order to understand natural language. The purpose of PercEVAL is to provide an account for categories emergence through perception and understanding of many visual experiences. Categories emergence depends on motivation and language, together with economic constraints of representation. Visual knowledge is represented according to the model of shape diffusion, which grants a stylish way to drop useless details of experiences. >

Erasmus was a monk, and although he left the monastery and took up the life of “a roving international man of letters” (MacCulloch 2003: 99), he retained his disdain for the sensuous props of spirituality that so engaged his contemporaries. Speaking of the Apostles, in his witty critique, In Praise of Folly, he notes with sarcasm that “it does not appear to have been revealed to them that one should worship a charcoal picture on the wall as if it were Christ himself.” Eamon Duffy’s recent books on pre-Reformation religious life have made clear just how out of step with the religion of his day was the great Dutch precursor of reform. Ignoring for the nonce the standard Protestant attacks on the materially rich religious culture of medieval Christianity in England, this chapter aims to suggest some of the things we can say about how that world came to be embodied, that is, about how individual brains and bodies learned to know their God. By embedding a discussion of some of the artifacts of that life within a cognitive description of learning and envisioning, we can begin to see how different the world of the intellectual churchman was from that of uneducated Christians, and even from the materially rich world of many clergymen (Buick 1997). We can perhaps, thus, appreciate what might have been their losses after the royal visitors had radically changed the furnishings of churches.

The article uses a categorical approach to the study of the Latin name of the adjective, which is based on the definition of the adjective as part of speech that is related to grammatical categories. Morphological and derivational categories of the adjective are analyzed. Disclosed are the semantic and formal differences between them, a discrepancy in their quantitative measurement is revealed. The grammatical means of their expression are illuminated. Characterized suffixes and prefixes, highlighting the corresponding word-formative categories of the adjective.

The electric vehicle (EV) can be utilized as a dynamically configurable dispersed energy storage in the vehicle-to-grid (V2G) and vehicle-to-building (V2B) operation mode to balance the energy demand between buildings and EVs. This paper proposes a mixed integer linear programming based collaborative decision model to study the energy sharing between a building and an EV charging station (CS). The building has its distributed generator, and electric and thermal energy storage, and the CS has its own renewable energy source. To model the V2G/V2B integration, we introduce three sets of decision variables to represent the energy exchange among building, CS and power grid. A set of parameters are introduced to model the driver behaviors, such as initial and desired state of charge level of EV battery, and available hours of EV, and sixteen different building categories (e.g., office, restaurant, hotel, warehouse, etc.) are studied. The impacts of driver behaviors and building categories on the economic performance of V2G/V2B integration are characterized and analyzed. The results from this research can recommend best V2G/V2B integration considering various driver behaviors and building categories which can provide valuable insight for smart community design.