Predicting how consumers perceive the naturalness of snacks: The usefulness of a simple index

For many consumers, it is important that food products be natural. Naturalness is a perceived property of food, but in the present study, we demonstrate that an objectively defined Food Naturalness Index (FNI) predicts perceived naturalness with a high degree of accuracy. A sample of 179 participants ranked 28 snacks, ranging from least natural to the most natural. Correlations on aggregated and individual levels suggest that perceived naturalness is strongly associated with the FNI. The food industry could therefore use the FNI to predict perceived naturalness during the product development phase of snacks, and it might also be a promising tool for regulating the use of naturalness claims in food marketing.     

Creative conservation, landscapes and loss

Conservation practice has recently begun to be transformed by the rhetoric of creative ecology and the possibility of creating (or re-creating) desired ecological conditions. This paper explores the potential conflict between these new developments and the conservation movement's long-standing dependence on a widely-shared (and widely disseminated) sense of 'the naturalness' of habitats and landscapes, and fear of their destruction. Conservation has long been driven by fear of loss of habitat, familiar features of landscapes, and of specific places. The paper discusses the potential for creative conservation to be carried out in such a way that its potential gains can be realized without cutting off the cultural engine of concern that drives conservation forwards.     

Gold, jade, and emeruby: The value of naturalness for theories of concepts and categories.

Researchers studying the psychology of concepts frequently draw distinctions between artificial and natural concepts. Unfortunately, there is a lack of consensus regarding the foundations and implications of the distinction. This paper provides a review and evaluation of the different ways researchers have approached the question of conceptual naturalness. Accounts may be divided into 2 approaches described as psychologically or externally based. These characterizations motivate distinctive sets of research questions. In addition to the particular implications, the author also considers the general significance of a distinction between natural and artificial concepts. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Restorative wildscapes at work: an investigation of the wellbeing benefits of greenspace at urban fringe business sites using ‘go-along’ interviews

Abstract

The potential well-being benefits associated with the use of privately owned greenspaces in working environments have received little research attention. Given the growing evidence on the restorative benefits of urban greenspace, and the fact that many people spend most of their daily hours at the workplace, the question of whether physical access to green environments from workplaces can promote well-being is a pertinent one. Person–environment relationships in peri-urban business sites were investigated in a series of semi-structured ‘go-along’ interviews with employees at Scottish science parks. Workers described a range of well-being benefits from outdoor breaks and associated these with qualities of the environment. Semi-natural and informally landscaped areas were most strongly associated with restoration during the working day. The implications of the findings for the planning and design of business sites at the urban fringe are explored.     

后置滤波器参数自适应的语音合成改进算法

针对HMM语音合成算法,固定参数的后置滤波器无法适应不同失真程度的频谱导致合成语音自然度下降,提出了一种基于后置滤波器参数自适应的语音合成改进算法。该方法根据语音谱的平坦度自适应选择最优的短时滤波参数来对合成语音频谱的共振峰区域增强;使用长时后置滤波器优化合成语音的基频谐波结构来减轻合成语音基频的不连续性。仿真实验结果表明,该方法能够有效地减轻语音的频谱过平滑,主观测试结果表明,合成语音的自然度得以提高。     

基于代码自然性的切片粒度缺陷预测方法

软件缺陷预测是软件质量保障领域的一个活跃话题,它可以帮助开发人员发现潜在的缺陷并更好地利用资源.如何为预测系统设计更具判别力的度量元,并兼顾性能与可解释性,一直是人们致力于研究的方向.针对这一挑战,提出了一种基于代码自然性特征的缺陷预测方法——CNDePor.该方法通过正逆双向度量代码并利用质量信息对样本加权的方式改进...     

Robotics Applications in Manufacturing

Changes in national and international competition, coupled with the mass application of new technologies, are revolutionizing production. Consumers are demanding quality, and manufacturers are being forced to provide it. Companies that wish to remain competitive and maintain their market share are turning to such advanced technologies as computer-aided industrial robots. This article discusses the benefits and justification of the industrial robot and provides managers in manufacturing firms with an overview of its potential applications.     

Reconstituting Beta Graphs into an Efficacious System

Logicians have strongly preferred first-order natural deductive systems over Peirce's Beta Graphs even though both are equivalent to each other. One of the main reasons for this preference, I claim, is that inference rules for Beta Graphs are hard to understand, and, therefore, hard to apply for deductions. This paper reformulates the Beta rules to show more fine-grained symmetries built around visual features of the Beta system, which makes the rules more natural and easier to use and understand. Noting that the rules of a natural deductive system are natural in a different sense, this case study shows that the naturalness and the intuitiveness of rules depends on the type of representation system to which they belong. In a diagrammatic system, when visual features are discovered and fully used, we have a more efficacious deductive system. I will also show that this project not only helps us to apply these rules more easily but to understand the validity of the system at a more intuitive level.     

An experimental evaluation of comprehensibility aspects of knowledge structures derived through induction techniques: A case study of industrial fault diagnosis

Machine induction has been extensively used in order to develop knowledge bases for decision support systems and predictive systems. The extent to which developers and domain experts can comprehend these knowledge structures and gain useful insights into the basis of decision making has become a challenging research issue. This article examines the knowledge structures generated by the C4.5 induction technique in a fault diagnostic task and proposes to use a model of human learning in order to guide the process of making comprehensive the results of machine induction. The model of learning is used to generate hierarchical representations of diagnostic knowledge by adjusting the level of abstraction and varying the goal structures between 'shallow' and 'deep' ones. Comprehensibility is assessed in a global way in an experimental comparison where subjects are required to acquire the knowledge structures and transfer to new tasks. This method of addressing the issue of comprehensibility appears promising especially for machine induction techniques that are rather inflexible with regard to the number and sorts of interventions allowed to system developers.     

Color reproduction and the naturalness constraint

This article aims to determine the process underlying the subjective impression about the fidelity of reproduced object colors. To this end, we present the concept of the naturalness constraint and a framework for specification of naturalness judgments. We consider several research questions that are essential for this framework and discuss plausible answers supported by experiments. In general, naturalness assessment of reproduced object colors can be (1) defined as similarity to prototypical object colors, and (2) characterized by a probability density function (e.g., Gaussian). Experiments show that (3) there is a considerable amount of consistency in naturalness judgments of locally and globally processed images (although observers are slightly more tolerant of global image processing), and (4) naturalness judgments vary for different object categories; e.g., subjects are more consistent in naturalness judgments of skin, grass, and sky reproductions than shirt reproduction. We suggest that (5) naturalness of a whole picture is determined by the naturalness of the most critical object in that picture. Finally, we introduce a naturalness index predicting perceived naturalness of color reproduction of real‐life scenes. © 1999 John Wiley & Sons, Inc. Col Res Appl, 24, 52–67, 1999