Catalytic feasibility of Ce-doped LaCoO3 systems for chlorobenzene oxidation: An analysis of synthesis method

A family of Ce-doped LaCoO₃ perovskites are presented as possible catalysts for Cl–VOCs elimination. These materials with different contents of Ce were obtained through the citrate and the reactive grinding methods. The insertion of Ce in the original perovskite structure favours the presence of Co²⁺/Co³⁺ and Ce³⁺/Ce⁴⁺ redox pairs and a higher content of oxygen vacancies that enhances the catalytic performance in chlorobenzene combustion based on differential kinetics studies. The family obtained by the grinding method presents a performance as high as that synthesized by citrate method. Thus, the reactive grinding is a feasible green chemistry alternative to obtain a catalyst with the same performance as that obtained from traditional methods. Finally, the stability of samples was evaluated under total combustion reaction conditions showing an excellent activity during 45 h time on stream.     

Asynchronous decentralized event-triggered control

In this paper we propose an approach to the implementation of controllers with decentralized strategies triggering controller updates. We consider set-ups with a central node in charge of the computation of the control commands, and a set of not co-located sensors providing measurements to the controller node. The solution we propose does not require measurements from the sensors to be synchronized in time. The sensors in our proposal provide measurements in an aperiodic way triggered by local conditions. Furthermore, in the proposed implementation (most of) the communication between nodes requires only the exchange of one bit of information (per controller update), which could aid in reducing transmission delays and as a secondary effect result in fewer transmissions being triggered.     

Utility of stereoscopic displays for indirect-vision driving and robot teleoperation

The effectiveness of an active shutter-glasses stereoscopic display (SD) and a passive polarised SD was evaluated in a live robot-teleoperation task and a simulated indirect-vision driving task in various terrains. Overall, participants completed their tasks significantly faster with the SDs in three-dimensional (3D) mode than with the SDs in the baseline 2D mode. They also navigated more accurately with the SDs in 3D mode. When the effectiveness of the two types of SDs was examined separately, results showed that the active shutter-glasses SD resulted in faster responses and task completion times than the passive polarised SD, though most of the differences failed to reach statistical significance. Perceived workload when interacting with the two SD systems did not differ significantly between the active versus passive display types or between the 3D and 2D modes of operation; however, participants reported more severe discomfort after interacting with the passive polarised SD.     

A 3D analysis of the joint torques developed during driver's ingress–egress motion

Providing an easy ingress–egress (I/E) movement remains a challenge for car designers. I/E has been largely studied in kinematics, but not in dynamics. This study proposes: (1) to evaluate and describe the motor torques developed in the lower limbs and lumbar joints during I/E motions and (2) to analyse the influence of the car geometry and subject anthropometry. An experiment was performed to observe 15 subjects of three anthropometrical groups getting in and out of a car mock-up simulating three different vehicle configurations. Motor torques were extracted using an inverse dynamics analysis. Both ingress and egress motions were primarily characterised by large torques. Overall, the taller a subject and the lower the seat of the vehicle were, the larger the peak torques were. Moreover, peak torques were higher for egress than ingress. These results are discussed in regard to the current knowledge on I/E ergonomics.     

Validation of a task demand measure for predicting mental workloads of physical therapists

The purpose of this study is to validate an analytical method in assessing demanded mental workloads for physical therapists, and to discuss its possible ergonomics implications on the design of healthcare working systems in which physical therapists are considered as the users. A task analysis was first used to understand the operation steps of three identified physical therapies. Then, the McCracken–Aldrich technique was applied to assign ratings of mental workload demanded for performing each step of the therapies. Finally, the assigned ratings were validated by the analysis of correlation with the answers of the NASA-TLX questionnaire collected from seventeen physical therapists in the rehabilitation center of a university-affiliated hospital. Results showed that the proposed McCracken–Aldrich technique was suitable as an analysis tool for predicting metal workloads of physical therapists. Some possible implications about the information provision and user interface design for reducing therapists' mental workloads on current therapy operations were discussed.Relevance to industryResults of this paper are expected to contribute the research and development in healthcare industry on its system design and workflow analysis.     

Interactive fuzzy stochastic multi-level 0–1 programming using tabu search and probability maximization

In this paper, we consider interactive fuzzy programming for multi-level 0–1 programming problems involving random variable coefficients both in objective functions and constraints. Following the probability maximization model together with the concept of chance constraints, the formulated stochastic multi-level 0–1 programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. For solving the transformed deterministic problems efficiently, we also introduce novel tabu search for general 0–1 programming problems. A numerical example for a three-level 0–1 programming problem is provided to illustrate the proposed method.     

Determination of temporal information granules to improve forecasting in fuzzy time series

Partitioning the universe of discourse and determining intervals containing useful temporal information and coming with better interpretability are critical for forecasting in fuzzy time series. In the existing literature, researchers seldom consider the effect of time variable when they partition the universe of discourse. As a result, and there is a lack of interpretability of the resulting temporal intervals. In this paper, we take the temporal information into account to partition the universe of discourse into intervals with unequal length. As a result, the performance improves forecasting quality. First, time variable is involved in partitioning the universe through Gath–Geva clustering-based time series segmentation and obtain the prototypes of data, then determine suitable intervals according to the prototypes by means of information granules. An effective method of partitioning and determining intervals is proposed. We show that these intervals carry well-defined semantics. To verify the effectiveness of the approach, we apply the proposed method to forecast enrollment of students of Alabama University and the Taiwan Stock Exchange Capitalization Weighted Stock Index. The experimental results show that the partitioning with temporal information can greatly improve accuracy of forecasting. Furthermore, the proposed method is not sensitive to its parameters.     

Beauty is more than screen deep: Improving the web survey respondent experience through socially-present and aesthetically-pleasing user interfaces

Web surveys are rapidly becoming standard issue in many researchers’ toolkits; however, measurement error has been shown to affect web surveys to a greater extent than paper-and-pencil surveys (Couper, 2000, Manfreda and Vehovar, 2002). Principles of aesthetic design and social presence have been applied to web surveys to reduce the prevalence of such error with promising results, which were further investigated in this research. A sample of 181 first-year psychology undergraduate students participated in this study. Participants were randomly allocated to view one of eight web survey interfaces, which varied by aesthetic quality and social presence. Exploratory structural equation modeling using the partial least squares method revealed that classical aesthetic quality and social presence were both positively related to perceived ease of use of the web survey interface and positive state affect; social presence and perceived ease of use were positively related to trust in the web survey researcher; classical aesthetic quality was negatively related to negative state affect; and, expressive aesthetic quality was negatively related to perceived ease of use and positively related to positive state affect. Interestingly, expressive aesthetic quality was also positively related to negative state affect. These relationships between aesthetic quality and social presence should inform best practice web survey design recommendations, and future empirical work should extend and test the generalizability of these findings.     

Level of interest sensing in spoken dialog using decision-level fusion of acoustic and lexical evidence

Automatic detection of a user's interest in spoken dialog plays an important role in many applications, such as tutoring systems and customer service systems. In this study, we propose a decision-level fusion approach using acoustic and lexical information to accurately sense a user's interest at the utterance level. Our system consists of three parts: acoustic/prosodic model, lexical model, and a model that combines their decisions for the final output. We use two different regression algorithms to complement each other for the acoustic model. For lexical information, in addition to the bag-of-words model, we propose new features including a level-of-interest value for each word, length information using the number of words, estimated speaking rate, silence in the utterance, and similarity with other utterances. We also investigate the effectiveness of using more automatic speech recognition (ASR) hypotheses (n-best lists) to extract lexical features. The outputs from the acoustic and lexical models are combined at the decision level. Our experiments show that combining acoustic evidence with lexical information improves level-of-interest detection performance, even when lexical features are extracted from ASR output with high word error rate.