Simulation of humidity control and greenhouse temperature tracking in a growth chamber using a passive air conditioning unit

In this paper, we define a dynamic discrete model of a passive air conditioning unit, without the more typical compression or absorption-refrigeration cycle. The unit is composed of heat exchangers, a positioning system and humid corrugated pads. The aim of the study was to follow the temperature in a greenhouse and to replicate it with a desired and stable relative humidity in a ventilated growth chamber. A control law, based on a quadratic criterion and dynamic programming, taking output error and energy consumption minimisation into account, was used to control the behaviour of the unit in spite of air intake disturbances. The results of the simulation indicate that the air conditioning unit can produce a variable climate in the growth chamber, with a wide range of relative humidity setpoints.     

Electrochemical characteristics of heme proteins in hydroxyethylcellulose film

A stable film made from hydroxyethylcellulose (HEC) on pyrolytic graphite (PG) electrode was employed for incorporating hemoglobin (Hb), myoglobin (Mb) and horseradish peroxidase (HRP), and the electrochemical characteristics of the proteins were studied correspondingly. Experimental results revealed that HEC film could greatly accelerate electron transfer between the proteins and electrode, and the proteins showed a thin layer electrochemical behavior in the film. Moreover, all the proteins in the film exhibited good catalytic activity towards the reduction of hydrogen peroxide (H₂O₂) in the low H₂O₂ concentration range. In the high concentration range, H₂O₂ would exhibit toxicity effect on the proteins. The electrochemical properties and electrocatalytic abilities of the three heme proteins in HEC film have been compared, and the optimal conditions for H₂O₂ biosensor fabrication have been obtained.     

Sensor fault tolerant control using sliding mode observers

Previous work has considered the use of sliding mode observers for fault detection and isolation (FDI) in uncertain linear systems whereby the unknown faults are reconstructed by appropriate processing of the so-called equivalent output error injection. The paper builds on this work and considers such a scheme within the broader context of fault tolerant control. Specifically, by correcting the faulty measurement by an estimate of the fault obtained from the sliding mode FDI scheme, good closed-loop performance is still maintained. An example of such a scheme, which has been implemented in real-time on a laboratory dc motor rig, is described.     

The ability of eye-tracking metrics to classify and predict the perceived driving workload

Traffic safety is directly related to the mental and physical condition of the driver. Performing regular secondary tasks while driving is an additional activity that dissipates attention and adds to the drivers' workload. Identifying driver fatigue and workload based on gaze behavior is one way to ensure a safe driving experience. The purpose of this paper is to classify and predict driving perceived workload using a set of eye-tracking metrics (gaze fixation, duration, pointing, and pupil diameter). The ability of eye-tracking metrics to predict driving workload has been investigated. As a result, frustration, performance, and temporal load showed a correlation with gaze metrics. Gaze point, duration, fixation, and pupil diameter significantly influence driving workload.Relevance to industry: Results will supply the specialists in eye-tracking/sensor technologies and traffic safety with new knowledge to improve the design of the driving performance and safety monitoring systems and efficiency of the driving process.     

Accurate positioning of a drilling and riveting cell for aircraft assembly

Modern aircraft assembly demands assembly cells or machines with higher machining efficiency and accuracy. Thus, a dual-machine drilling and riveting cell is developed in this paper. We firstly discuss its physical design, as well as the automatic drilling and riveting process. With the automatic drilling and riveting cell, drilling and riveting production line of aircraft panels can be expected. The frame chain of the drilling and riveting cell is constructed to link the assembly cell to its task space, which is the kinematics base. System calibrations, including task space calibration, the sensor calibration of an orientation alignment unit, the floating calibration of the implicit hand-eye relationship, are explored. For high positioning accuracy, a multi-sensor servoing method is proposed for cell positioning. An orientation-based laser servoing strategy, which uses the feedback of the orientation errors measured by laser displacement sensors, is used to align drilling direction and camera shooting direction. Besides, A single-camera-based visual servoing is applied to align the tool center point (TCP) to reference holes, to obtain their coordinates for drilling position modification. Experiments of multi-sensor servoing for cell positioning are performed on an automatic drilling and riveting machine developed for the panel assembly of an aircraft in China. With the cell positioning method, the automatic drilling and riveting cell can approximately achieve an accuracy of 0.05 mm, which can adequately fulfill the requirement for the assembly of the aircraft.     

An SVD-based image watermarking in wavelet domain using SVR and PSO

The paper presents a novel blind watermarking scheme for image copyright protection, which is developed in the discrete wavelet transform (DWT) and is based on the singular value decomposition (SVD) and the support vector regression (SVR). Its embedding algorithm hides a watermark bit in the low–low (LL) subband of a target non-overlap block of the host image by modifying a coefficient of U component on SVD version of the block. A blind watermark-extraction is designed using a trained SVR to estimate original coefficients. Subsequently, the watermark bit can be computed using the watermarked coefficient and its corresponding estimate coefficient. Additionally, the particle swarm optimization (PSO) is further utilized to optimize the proposed scheme. Experimental results show the proposed scheme possesses significant improvements in both transparency and robustness, and is superior to existing methods under consideration here.     

Adaptive receding horizon control for constrained MIMO systems

An adaptive control algorithm for open-loop stable, constrained, linear, multiple input multiple output systems is presented. The proposed approach can deal with both input and output constraints, as well as measurement noise and output disturbances. The adaptive controller consists of an iterative set membership identification algorithm, that provides a set of candidate plant models at each time step, and a model predictive controller, that enforces input and output constraints for all the plants inside the model set. The algorithm relies only on the solution of standard convex optimization problems that are guaranteed to be recursively feasible. The experimental results obtained by applying the proposed controller to a quad-tank testbed are presented.     

Greedy-search-based multi-objective genetic algorithm for emergency logistics scheduling

To enable the immediate and efficient dispatch of relief to victims of disaster, this study proposes a greedy-search-based, multi-objective, genetic algorithm capable of regulating the distribution of available resources and automatically generating a variety of feasible emergency logistics schedules for decision-makers. The proposed algorithm dynamically adjusts distribution schedules from various supply points according to the requirements at demand points in order to minimize unsatisfied demand for resources, time to delivery, and transportation costs. The proposed algorithm was applied to the case of the Chi–Chi earthquake in Taiwan to verify its performance. Simulation results demonstrate that under conditions of a limited/unlimited number of available vehicles, the proposed algorithm outperforms the MOGA and standard greedy algorithm in ‘time to delivery’ by an average of 63.57% and 46.15%, respectively, based on 10,000 iterations.     

Aligning principal and agent’s incentives: A principal–agent perspective of social networking sites

The viability of networked communities depends on the creation and disclosure of user-generated content and the frequency of user visitation (Facebook 10-K Annual Report, 2012). However, little is known about how to align the interests of user and social networking sites. In this study, we draw upon the principal-agent perspective to extend Pavlou et al.’s uncertainty mitigation model of online exchange relationships (2007) and propose an empirically tested model for aligning the incentives of the principal (user) and the agent (service provider). As suggested by Pavlou et al., we incorporated a multi-dimensional measure of trust: trust of provider and trust of members. The proposed model is empirically tested with survey data from 305 adults aged 20-55. The results support our model, delineating how real individuals with bounded rationality actually make decision about information disclosure under uncertainty in the social networking site context. There is show little to no relationship between online privacy concerns and information disclosure on online social network sites. Perceived benefits provide the linkage between the incentives of principal (user) and agent (provider) while usage intensity demonstrated the most significant impact on information disclosure. We argue that the phenomenon may be explained through Communication Privacy Management Theory. The present study enhances our understanding of agency theory and human judgment theory in the context of social media. Practical implications for understanding and facilitating online social exchange relationships are also discussed.