Hedonic and Transcendent Conceptions of Value

In this paper we introduce a conceptual distinction between a hedonic and transcendent conception of value. We posit three linguistic earmarks by which one can distinguish these conceptions of value. We seek validation for the conceptual distinctions by examining the language contained in reviews of cars and reviews of paintings. In undertaking the empirical examination, we draw on the work of M.A.K. Halliday to identify clauses as fundamental units of meaning and to specify process types that can be mapped onto theoretical distinctions between the two conceptions of value. Extensions of this research are discussed

State-of-the-art on research and applications of machine learning in the building life cycle

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of building life cycle. By conducting a literature search on the Web of Knowledge platform, we found 9579 papers in this field and selected 153 papers for an in-depth review. The number of published papers is increasing year by year, with a focus on building design, operation, and control. However, no study was found using machine learning in building commissioning. There are successful pilot studies on fault detection and diagnosis of HVAC equipment and systems, load prediction, energy baseline estimate, load shape clustering, occupancy prediction, and learning occupant behaviors and energy use patterns. None of the existing studies were adopted broadly by the building industry, due to common challenges including (1) lack of large scale labeled data to train and validate the model, (2) lack of model transferability, which limits a model trained with one data-rich building to be used in another building with limited data, (3) lack of strong justification of costs and benefits of deploying machine learning, and (4) the performance might not be reliable and robust for the stated goals, as the method might work for some buildings but could not be generalized to others. Findings from the study can inform future machine learning research to improve occupant comfort, energy efficiency, demand flexibility, and resilience of buildings, as well as to inspire young researchers in the field to explore multidisciplinary approaches that integrate building science, computing science, data science, and social science

"Hegelian Buddhist Hypertextual Media Inhabitation, or, Criticism in the Age of Electronic Immersion"

What can it mean to criticize when you are inside the work itself? In a immersive electronic or digital environment critic is not distanced on a platform based on firm principles. Yet criticism self-awareness and commentary remain possible. This essay examines various techniques for dealing with immersive environments critically

Visual Feature Attribution using Wasserstein GANs

Attributing the pixels of an input image to a certain category is an important and well-studied problem in computer vision, with applications ranging from weakly supervised localisation to understanding hidden effects in the data. In recent years, approaches based on interpreting a previously trained neural network classifier have become the de facto state-of-the-art and are commonly used on medical as well as natural image datasets. In this paper, we discuss a limitation of these approaches which may lead to only a subset of the category specific features being detected. To address this problem we develop a novel feature attribution technique based on Wasserstein Generative Adversarial Networks (WGAN), which does not suffer from this limitation. We show that our proposed method performs substantially better than the state-of-the-art for visual attribution on a synthetic dataset and on real 3D neuroimaging data from patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). For AD patients the method produces compellingly realistic disease effect maps which are very close to the observed effects.Comment: Accepted to CVPR 201

TRINITIES IN DISCOVERING MEANINGS ON LITERATURE INSTRUCTIONAL SCHEME ON LITERARY STUDIES

This paper’s title is Trinities in Discovering Meaning on Literature aiming to discuss Instructional Scheme on Literary Studies. Methods of the study consist of qualitative design in explaining discourse, library research in collecting data, and problem-based approach in answering the problem statements, the three-substances of which are significant to English teaching on literary studies. Literary studies are the humanistic studies of literature and literary research is the final project for the students who are going to complete their study at notably English Literature Study Programs. Their final project must compose scientific written report. It is in the form of writing literary analysis. The most significant point to emphasize is that literary analysis is an argument about a literary work and that whatever recommendations are made throughout the interpretation from the need to write persuasively about a clear, scientific, and debatable thesis. The writing on literary analysis is getting branched out being up to date in any academic atmosphere, of course, in line with the development of theory, history, and criticism on literature. This article is an alternative way for instructional manuscript blending theoretical or conceptual ideas with practical ideas about an alternative pedagogy in the area of English literary studies teaching and research. It is designed to help teachers specialized in literature introducing the writing literary analysis to their students. I deliver this article because I am sure that the trinities in the science of literature must be comprehended by the teachers before they transmit it in the classroom activities in teaching English Literary Studies. The term “Trinities†above is going to be explained in a discussion.Keywords: trinities, literature, instructional scheme, literary studie