Complexity and performance of an Augmented Lagrangian algorithm

Algencan is a well established safeguarded Augmented Lagrangian algorithm introduced in [R. Andreani, E. G. Birgin, J. M. Martínez, and M. L. Schuverdt, On Augmented Lagrangian methods with general lower-level constraints, SIAM J. Optim. 18 (2008), pp. 1286–1309]. Complexity results that report its worst-case behaviour in terms of iterations and evaluations of functions and derivatives that are necessary to obtain suitable stopping criteria are presented in this work. In addition, its computational performance considering all problems from the CUTEst collection is presented, which shows that it is a useful tool for solving large-scale constrained optimization problems.     

Multiplane displays based on liquid crystals for AR applications

Multiplane displays are capable of displaying 3D scenes with correct focus cues by creating multilayer 2D images in the display volume. Hence, such a 3D display technique could effectively address the accommodation‐vergence conflict (AVC) problem, which is prevalent in augmented reality (AR) displays. In this paper, we review the recent progress on multiplane AR displays based on liquid crystals (LCs) for AR applications. The working principle of multiplane AR displays is illustrated, the electro‐optical properties of the tunable LC devices are investigated and display prototypes are demonstrated. Finally, we discuss the prospects and challenges of multiplane AR displays based on LCs.     

Differences between oculomotor and perceptual artifacts for temporally limited head mounted displays

We used perceptual and oculomotor measures to understand the negative impacts of low (phantom array) and high (motion blur) duty cycles with a high‐speed, AR‐likehead‐mounted display prototype. We observed large intersubject variability for the detection of phantom array artifacts but a highly consistent and systematic effect on saccadic eye movement targeting during low duty cycle presentations. This adverse effect on saccade endpoints was also related to an increased error rate in a perceptual discrimination task, showing a direct effect of display duty cycle on the perceptual quality. For high duty cycles, the probability of detecting motion blur increased during head movements, and this effect was elevated at lower refresh rates. We did not find an impact of the temporal display characteristics on compensatory eye movements during head motion (e.g., VOR). Together, our results allow us to quantify the tradeoff of different negative spatiotemporal impacts of user movements and make subsequent recommendations for optimized temporal HMD parameters.     

基于Bootstrap方法的密封寿命可靠性评估

针对高可靠、长寿命密封件在小样本试验下的可靠性寿命评估需求,提出一种基于虚拟增广样本和Bootstrap方法的密封寿命小样本数据可靠性评估方法。并以轴用阶梯圈为例,进行寿命可靠性评估。首先通过虚拟增广法将轴用阶梯圈台架寿命试验数据样本数增广至10个,使得样本数满足Bootstrap方法的适用条件;然后再利用Bootstrap方法得到轴用阶梯圈的寿命可靠性评估结果。     

Supply chain network design under the risk of uncertain disruptions

Facility disruptions in the supply chain often lead to catastrophic consequences, although they occur rarely. The low frequency and non-repeatability of disruptive events also make it impossible to estimate the disruption probability accurately. Therefore, we construct an uncertain programming model to design the three-echelon supply chain network with the disruption risk, in which disruptions are considered as uncertain events. Under the constraint of satisfying customer demands, the model optimises the selection of retailers with uncertain disruptions and the assignment of customers and retailers, in order to minimise the expected total cost of network design. In addition, we simplify the proposed model by analysing its properties and further linearise the simplified model. A Lagrangian relaxation algorithm for the linearised model and a genetic algorithm for the simplified model are developed to solve medium-scale problems and large-scale problems, respectively. Finally, we illustrate the effectiveness of proposed models and algorithms through several numerical examples.     

Emerging Thermal Technology Enabled Augmented Reality

In the past decade, remarkable progress has been made in the domain of augmented reality/virtual reality (AR/VR). The need for realistic and immersive augmentation has propelled the development of haptics interfaces-enabled AR/VR. The haptics interfaces facilitate direct interaction and manipulation with both real and virtual objects, thus augmenting the perception and experiences of the users. The level of augmentation can be significantly improved by thermal stimulation or sensing, which facilitates a higher degree of object identification and discrimination. This review discusses the thermal technology-enabled augmented reality and summarizes the recent progress in the development of different thermal technology such as thermal haptics including thermo-resistive heater and Peltier devices, thermal sensors including resistive, pyroelectric, and thermoelectric sensors, which can be utilized to improve the realism of augmentation. The fundamental mechanism, design strategies, and the rational guidelines for the adoption of these technologies in AR/VR is explicitly discussed. The conclusion provides an outlook on the existing challenges and outlines the future roadmap for the realization of next-generation thermo-haptics enabled augmented reality.     

Augmented reality in language learning: A state-of-the-art review of 2014–2019

This systematic review study synthesizes research findings pertaining to the use of augmented reality (AR) in language learning. Published research from 2014 to 2019 has been explored and specific inclusion and exclusion criteria have been applied resulting in 54 relevant publications. Our findings determined: (a) devices and software employed for mastering AR; languages and contexts in which AR had been applied; theoretical perspectives adopted for guiding the use of AR; the number of participants in AR activities and benefits from using AR as an educational tool in the language classroom; (b) alignment of the affordances of Augmented Reality with the KSAVE (Knowledge, Skills, Attitudes, Values, Ethics) 21st-century skills framework; (c) future directions in AR research and practice. The main findings from this review demonstrate the popularity of mobile-based AR for supporting vocabulary (23.9%), reading (12.7%), speaking (9.9%) writing (8.5%) or generic language skills (9.9%). Our findings also uncovered areas that merit future attention in the application of AR in language learning – for instance learning theories were not often considered in the implementation of AR. The study concludes with suggestions for future research especially in the areas of instructional design and user experience.     

Supply chain planning and scheduling integration using Lagrangian decomposition in a knowledge management environment

The integration of planning and scheduling decisions in rigorous mathematical models usually results in large scale problems. In order to tackle the problem complexity, decomposition techniques based on duality and information flows between a master and a set of subproblems are widely applied. In this sense, ontologies improve information sharing and communication in enterprises and can even represent holistic mathematical models facilitating the use of analytic tools and providing higher flexibility for model building. In this work, we exploit this ontologies’ capability to address the optimal integration of planning and scheduling using a Lagrangian decomposition approach. Scheduling/planning sub-problems are created for each facility/supply chain entity and their dual solution information is shared by means of the ontological framework. Two case studies based on a STN representation of supply chain planning and scheduling models are presented to emphasize the advantages and limitations of the proposed approach.     

Lagrangian relaxation hybrid with evolutionary algorithm for short-term generation scheduling

Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.