Smart homes and their users:a systematic analysis and key challenges

Published research on smart homes and their users is growing exponentially, yet a clear understanding of who these users are and how they might use smart home technologies is missing from a field being overwhelmingly pushed by technology developers. Through a systematic analysis of peer-reviewed literature on smart homes and their users, this paper takes stock of the dominant research themes and the linkages and disconnects between them. Key findings within each of nine themes are analysed, grouped into three: (1) views of the smart home-functional, instrumental, socio-technical; (2) users and the use of the smart home-prospective users, interactions and decisions, using technologies in the home; and (3) challenges for realising the smart home-hardware and software, design, domestication. These themes are integrated into an organising framework for future research that identifies the presence or absence of cross-cutting relationships between different understandings of smart homes and their users. The usefulness of the organising framework is illustrated in relation to two major concerns-privacy and control-that have been narrowly interpreted to date, precluding deeper insights and potential solutions. Future research on smart homes and their users can benefit by exploring and developing cross-cutting relationships between the research themes identified

Kama muta: conceptualizing and measuring the experience of being moved across 19 nations and 15 languages

English-speakers sometimes say that they feel moved to tears, emotionally touched, stirred, or that something warmed their heart; other languages use similar passive contact metaphors to refer to an affective state. We propose and measure the concept of kama muta to understand experiences often given these and other labels. Do the same experiences evoke the same kama muta emotion across nations and languages? We conducted studies in 19 different countries, five continents, 15 languages, with a total of 3542 participants. We tested the construct while validating a comprehensive scale to measure the appraisals, valence, bodily sensations, motivation, and lexical labels posited to characterize kama muta. Our results are congruent with theory and previous findings showing that kama muta is a distinct positive social relational emotion that is evoked by experiencing or observing a sudden intensification of communal sharing. It is commonly accompanied by a warm feeling in the chest, moist eyes or tears, chills or piloerection, feeling choked up or having a lump in the throat, buoyancy and exhilaration. It motivates affective devotion and moral commitment to communal sharing. While we observed some variations across cultures, these five facets of kama muta are highly correlated in every sample, supporting the validity of the construct and the measure.info:eu-repo/semantics/acceptedVersio

Analysis of protein carbonylation - pitfalls and promise in commonly used methods

Abstract Oxidation of proteins has received a lot of attention in the last decades due to the fact that they have been shown to accumulate and to be implicated in the progression and the patho-physiology of several diseases such as Alzheimer, coronary heart diseases, etc. This has also resulted in the fact that research scientist became more eager to be able to measure accurately the level of oxidized protein in biological materials, and to determine the precise site of the oxidative attack on the protein, in order to get insights into the molecular mechanisms involved in the progression of diseases. Several methods for measuring protein carbonylation have been implemented in different laboratories around the world. However, to date no methods prevail as the most accurate, reliable and robust. The present paper aims at giving an overview of the common methods used to determine protein carbonylation in biological material as well as to highlight the limitations and the potential. The ultimate goal is to give quick tips for a rapid decision making when a method has to be selected and taking into consideration the advantage and drawback of the methods

How weeping influences the perception of facial expressions:The signal value of tears

Emotional tears have been proposed to serve as a signal of distress, appeasement, and helplessness, which promotes prosocial responses in observers. They may also facilitate the perception of sadness. A still unanswered question is what information tears convey about emotional states when they are combined with different muscular facial expressions. The current study evaluated three hypotheses: Tears facilitate inferences about (a) emotion intensity in general (b) sadness in particular, or (c) helplessness-related appraisal and behavioral intentions. In the first experiment, participants viewed pictures of (non)tearful real and artificial faces displaying anger, disgust, fear, happiness, sadness, surprise, and neutral state. They had to report which of the seven expressions they recognized, and to rate its intensity, sincerity, and felt empathy. Tears appeared to facilitate the perception of sadness, but also of anger and fear, while they decreased the perception of disgust and surprise. The ratings of the intensity, the perceived sincerity, and the experienced empathy followed a similar pattern. In the second experiment, participants had to indicate if briefly (50 ms) presented (non)tearful faces showed a particular expression, and we measured their accuracy and reaction times. The results of the first experiment were not corroborated. Overall, the findings lend most support to the appraisal/behavioral intentions hypothesis and less support for the intensity and the sadness enhancement hypotheses

Vision Transformers for Brain Tumor Classification

With the increasing amount of data gathered by healthcare providers, interest has been growing in Machine Learning, and more specifically in Deep Learning. Medical applications of machine learning range from the prediction of medical events, to computer-aided detection, diagnosis, and classification. This paper will investigate the application of State-of-the-Art (SoA) Deep Neural Networks in classifying brain tumors. We distinguish between several types of brain tumors, which are typically diagnosed and classified by experts using Magnetic Resonance Imaging (MRI). The most common benign tumors are gliomas and meningiomas, however there exist many more which vary in size and location. Convolutional Neural Networks (CNN) are the SoA deep learning technique for image processing tasks such as image segmentation and classification. However, a recently developed architecture for image classification, namely Vision Transformers, have been shown to outperform classical CNNs in efficiency. while requiring fewer computational resources. This work introduces using only Transformer networks in brain tumor classification for the first time, and compares their performance with CNNs. A significant difference between the two models, tested in this manner, is the lack of translational equivariance in Transformers, which the CNNs already have. Experiments for brain tumor classification on benchmark real-world datasets show they can achieve comparable or better performance, despite using limited training data

Control architectures for autonomous underwater vehicles

utonomous Underwater Vehicles (AUVs) share common A control problems with other air, land, and water unmanned vehicles. In addition to requiring high-dimensional and computationally intensive sensory data for real-time mission execution, power and communication limitations in an underwater environment make it more difficult to develop a control architecture for an AUV. In this article, the four types of control architectures being used for AUVs (hierarchical, heterarchical, subsumption, and hybrid architecture) are reviewed. A summary of 25 existing AUVs and a review of 11 AUV control architecture systems present a flavor of the state of the art in AUV technology. A new sensor-based embedded AUV control system architecture is also described and its implementation is discussed

Ubiquitous web services for e-government social services

[No abstract available