Physics‐based spectral sharpening through filter‐chart calibration

The spectral overlap of color‐sampling filters increases errors when using a diagonal matrix transform, for color correction and reduces color distinction. Spectral sharpening is a transformation of colors that was introduced to reduce color‐constancy errors when the colors are collected through spectrally overlapping filters. The earlier color‐constancy methods improved color precision when the illuminant color is changed, but they overlooked the color distinction. In this article, we introduce a new spectral sharpening technique that has a good compromise of color precision and distinction, based on real physical constraints. The spectral overlap is measured through observing a gray reference chart with a set of real and spectrally disjoint filters selected by the user. The new sharpening method enables to sharpen colors obtained by a sensor without knowing the camera response functions. Experiments with real images showed that the colors sharpened by the new method have good levels of color precision and distinction as well. The color‐constancy performance is compared with the data‐based sharpening method in terms of both precision and distinction. © 2014 Wiley Periodicals, Inc. Col Res Appl, 40, 564–576, 2015     

An approach for evaluating collaboration attributes in cluster-based companies

This paper presents an approach for evaluating collaboration attributes in companies operating in industrial clusters. From the literature review, we identified governance, geographic proximity, and trust as the main collaboration attributes in industrial clusters. For each of them, there is a set of related sub-attributes that composed the evaluation model. For developing the model, we used the graph theoretic approach (GTA), a methodology for multi-attribute assessment that considers interdependencies among elements of a system to provide an overall evaluation. We applied the model to five companies of a furniture cluster. The results showed the model allows for systematizing relationship management because it highlights the collaboration attributes that need to be improved. Furthermore, the application of the model may contribute to encouraging companies to develop collaborative practices.     

Influence of photovoltaic generation model and time resolution on the reliability evaluation of distribution systems

This paper aims to investigate the influence of photovoltaic (PV) generation on reliability evaluation of distribution systems. Two PV generation models are used to predict the output power injected into the grid, taking into account the main relevant environmental variables, the irradiance and ambient temperature. Issues that directly affect the output power, such as the spatial smoothing effect due to the plant size and the influence of the irradiance and temperature measurement interval are taken into consideration. Using measurement time series of irradiance and local temperature, the models are used to generate power series in 4‐minute and hourly resolutions. The generated power series are used in a reliability assessment model, with the objective of evaluating the impact of solar resource variability on the reliability indices of the system. Case studies on the IEEE RBTS‐Bus 2 and on the real distribution system of Fernando de Noronha in Brazil are presented and discussed, for power plants of different capacities, considering the effect of the PV generation models, the temporal resolution of the time series and the spatial smoothing of the power output fluctuations. The results show that the power time series in hourly resolution significantly underestimates the frequency of interruptions. For the real system, this index is underestimated at the system level (up to 43%) and at the load points (up to 72%). On the other hand, for the interruption duration index, the temporal aggregation results in a small underestimation (just 4%). The results also indicates that the smoothing effect is irrelevant for typical PV system sizes of distribution systems with discretization equal to or above 4 minutes.     

Multi-modal approach to evaluate adaptive visual stimuli of remote operation system using gaze behavior

A multi-modal approach is proposed to evaluate the usability of Adaptive Visual Stimuli for User Interface (AVS4UI) of remote operation systems. This study focuses on the evaluation of AVS4UI for forklift work because the operation complexity includes driving and cargo handling, which typically requires multiple salient attention. Presenting this amount of information simultaneously on a User Interface (UI) tends to cause confusions to operators and reduces operation efficiency. AVS4UI can therefore be one of the promising solutions where the optimal visual stimuli are autonomously presented for different work conditions. However, evaluation of AVS4UI is challenging because operators may be disoriented by adaptive information and worked without safety considerations. Therefore, novel gaze metrics are proposed to evaluate responses of forklift operators to AVS4UI so that undesired behavior can be evaluated. The proposed metrics implicitly represent gaze pattern in terms of transition and distribution between UI elements, operation safety, and familiarity with the adaptive system. The ideal AVS4UI is expected to minimize the proposed gaze metrics and outperform the non-adaptive UI. More importantly, the results of these metrics are consistent with those of perceived workload defined by NASA-Task Load Index. We also propose a correlation model using stepwise linear regression that provides reasonable estimation of perceived workload. Such novel metrics and correlation model enable objective and online evaluation to minimize biases of subjective response. Therefore, online work support system can be developed to support workers.     

基于改进雷达图的配电系统电能质量评估方法

本文针对配电系统电能质量综合评估存在的评估指标权重分配过于主观或客观的问题,提出一种基于改进雷达图法的配电系统电能质量评估方法。该方法利用最小偏差组合权重法计算各评估指标的最优组合权重。并在传统雷达图的基础上对各指标轴间夹角值的确定和特征向量的选取两方面做了进一步的改进。首先采用扇形区域取代原始的三角形区域,并利用最小偏差组合权重法计算各指标轴间夹角值。其次选择新的特征向量构造评估函数对配电系统电能质量进行综合评估。最后通过对某钢铁厂棒材变电站10kV配电系统电能质量进行综合评估,验证了该方法的可行性和合理性。较传统雷达图而言,改进雷达图法解决了传统雷达图法中各指标间信息共用以及评估结果不唯一的问题,使评估结果更加准确合理。     

支持规避设计的海量专利质量评价模型

专利规避设计需从现有专利中遴选具有核心竞争力的目标专利，以提升技术起点。针对设计领域的海量专利信息，提出了专利质量多指标主客观综合评价模型。分析专利书目信息与专利质量存在的正相关关系，甄选存活期、权利项数、同族专利数、引证数和被引证数等书目信息指标，构建了专利质量多指标综合评价指标体系，提升了评价方法的科学性和可操作性；提出将德尔菲法、层次分析法和均方差决策法相结合的主客观赋权法，确定专利质量评价指标权重，既保证了评价的权威性，又减小了个人偏见与从众妥协等因素的影响；建立了基于质量评价模型遴选目标专利的过程模型，并通过应用实例验证了该模型对遴选具有核心竞争力专利的有效性。     

Cloud based cyber-physical systems: Network evaluation study

In recent years, the Industry 4.0 concept brings new demands and trends in different areas; one of them is distributing computational power to the cloud. This concept also introduced the Reference Architectural Model for Industry 4.0 (RAMI 4.0). The efficiency of data communications within the RAMI 4.0 model is a critical issue. Aiming to evaluate the efficiency of data communication in the Cloud Based Cyber-Physical Systems (CB-CPS), this study analyzes the periods and data amount required to communicate with individual hierarchy levels of the RAMI 4.0 model. The evaluation of the network properties of the communication protocols eligible for CB-CPS is presented. The network properties to different cloud providers and data centers’ locations have been measured and interpreted. To test the findings, an architecture for cloud control of laboratory model was proposed. It was found that the time of the day; the day of the week; and data center utilization have a negligible impact on latency. The most significant impact lies in the data center distance and the speed of the communication channel. Moreover, the communication protocol also has impact on the latency. The feasibility of controlling each level of RAMI 4.0 through cloud services was investigated. Experimental results showed that control is possible in many solutions, but these solutions mostly cannot depend just on cloud services. The intelligence on the edge of the network will play a significant role. The main contribution is a thorough evaluation of different cloud providers, locations, and communication protocols to provide recommendations sufficient for different levels of the RAMI 4.0 architecture.     

A complex network approach to environmental impact assessment

This article proposes a complex network methodology for the process of Environmental Impact Assessment (EIA) that limits subjectivity and reduces uncertainty by incorporating elements of complex systems theory in the stages of identification and assessment of the significance of environmental impacts. The proposed methodology reduces the sources of uncertainty, which emerge from the use of simplified models that analyse the environment-activity interactions in a unidirectional fashion. This proposal determines the significance of environmental impacts through multidirectional or complex causal relationships. Likewise, it limits the subjectivity of the evaluator by using these causality relationships instead of criteria based on the impacts’ attributes. The application of the proposed methodology demonstrates the advantages of (i) prioritizing the impacts according to their capacity to interact with other impacts, and (ii) the possibility to redirect the environmental management plans towards the prevention of impacts of higher complexity and to reduce the importance of derived impacts.

The application of the proposed methodology reveals that the percentage of irrelevant and moderate impacts is reduced, whereas the percentage of severe and critical impacts increase, in comparison to the conventional methodologies.     

Quantifying co-creative writing experiences

Collaboration with artificial intelligence (AI) is a growing trend even in the field of creativity. This paper examines which quantitative metrics can be used to comparatively analyse human-computer co-creativity with children. To study this question, 24 schoolchildren of age 10–11 wrote a poem with three co-creative poetry writing processes: a human-computer, a human-human, and a human-human-computer process. The computational participant in the processes was an AI-based application called the Poetry Machine. The children were asked to evaluate their user experience with a 5-point Likert-type questionnaire after each writing process and a comparative questionnaire after finishing all processes. The metrics used in the evaluation were immediate fun, long-term enjoyment, creativity, self-expression, outcome satisfaction, ease of starting and finishing writing, quality of ideas and support from others, and ownership.

Significant differences were found in fun, long-term enjoyment, quality of ideas, support, and ownership. The high number of statistically relevant results was enabled by exposing all participants to all writing processes, and the comparative questionnaire. The human-human-computer process was evaluated the best in long-term enjoyment and the human-computer process the weakest in support and idea quality. Creativity and ease of finishing writing turned out to be outlining metrics for the co-creative processes.