Laser-Printed Plasmonic Metasurface Supporting Bound States in the Continuum Enhances and Shapes Infrared Spontaneous Emission of Coupled HgTe Quantum Dots

In order to advance the development of quantum emitter-based devices, it is essential to enhance light-matter interactions through coupling between semiconductor quantum dots with high quality factor resonators. Here, efficient tuning of the emission properties of HgTe quantum dots in the infrared spectral region is demonstrated by coupling them to a plasmonic metasurface that supports bound states in the continuum. The plasmonic metasurface, composed of an array of gold nanobumps, is fabricated using single-step direct laser printing, opening up new opportunities for creating exclusive 3D plasmonic nanostructures and advanced photonic devices in the infrared region. A 12-fold enhancement of the photoluminescence in the 900–1700 nm range is observed under optimal coupling conditions. By tuning the geometry of the plasmonic arrays, controllable shaping of the emission spectra is achieved, selectively enhancing specific wavelength ranges across the emission spectrum. The observed enhancement and shaping of the emission are attributed to the Purcell effect, as corroborated by systematic measurements of radiative lifetimes and optical simulations based on the numerical solution of Maxwell's equations. Moreover, coupling of the HgTe photoluminescence to high quality factor modes of the metasurface improves emission directivity, concentrating output within an ≈20° angle.     

The Electrochemical Response of Single Crystalline Copper Nanowires to Atmospheric Air and Aqueous Solution

In this paper, single crystalline copper nanowires (CuNWs) have been electrochemically grown through anodic aluminum oxide template. The environmental stability of the as‐obtained CuNWs in both 40% relative humidity (RH) atmosphere and 0.1 m NaOH aqueous solution has been subsequently studied. In 40% RH atmosphere, a uniform compact Cu₂O layer is formed as a function of exposure time following the logarithmic law and epitaxially covers the CuNW surfaces. It is also found that the oxide layers on CuNWs are sequentially grown when subjected to the cyclic voltammetry measurement in 0.1 m NaOH solution. An epitaxially homogeneous Cu₂O layer is initially formed over the surface of the CuNW substrates by solid‐state reaction (SSR). Subsequently, the conversion of Cu₂O into epitaxial CuO based on the SSR takes place with the increase of applied potential. This CuO layer is partially dissolved in the solution forming Cu(OH)₂, which then redeposited on the CuNW surfaces (i.e., dissolution‐redeposition (DR) process) giving rise to a mixed polycrystalline CuO/Cu(OH)₂ layer. The further increase of applied potential allows the complete oxidation of Cu₂O into CuO to form a dual‐layer structure (i.e., CuO inner layer and Cu(OH)₂ outer layer) with random orientations through an enhanced DR process.     

An economical piezoelectric phase modulator for fiber optic sensors

A homemade piezoelectric phase modulator for interfero-metric fiber optic sensors was fabricated using piezoelectric buzzers as strain elements. Six piezoelectric elements were embedded between the two halves of a bakelite cylinder split along its axis and secured tightly together again to form a cylinder. Single-mode optical fiber was then wound around the cylinder to complete the unit. Up to a frequency of 500 Hz, the phase shift produced by the modulator is linearly proportional to the amplitude of the applied voltage. The sensitivity of the phase modulator is about 3.6 rad/V and has a dynamic range of 1,000 rad, which is sufficient for most phase modulation purposes.     

A job grouping approach for planning container transfers at automated seaport container terminals

This paper proposes a practical job grouping approach, which aims to enhance the time related performance metrics of container transfers in the Patrick AutoStrad container terminal, located in Brisbane, Australia. It first formulates a mathematical model of the automated container transfers in a relatively complex environment. Apart from the consideration on collision avoidance of a fleet of large vehicles in a confined area, it also deals with many other difficult practical challenges such as the presence of multiple levels of container stacking and sequencing, variable container orientations, and vehicular dynamics that require finite acceleration and deceleration times. The proposed job grouping approach aims to improve the makespan of the schedule for yard jobs, while reducing straddle carrier waiting time by grouping jobs using a guiding function. The performance of the current sequential job allocation method and the proposed job grouping approach are evaluated and compared statistically using a pooled t-test for 30 randomly generated yard configurations. The experimental results show that the job grouping approach can effectively improve the schedule makespan and reduce the total straddle carrier waiting time.     

Towards a web-based progressive handwriting recognition environment for mathematical problem solving

The emergence of pen-based mobile devices such as PDAs and tablet PCs provides a new way to input mathematical expressions to computer by using handwriting which is much more natural and efficient for entering mathematics. This paper proposes a web-based handwriting mathematics system, called WebMath, for supporting mathematical problem solving. The proposed WebMath system is based on client–server architecture. It comprises four major components: a standard web server, handwriting mathematical expression editor, computation engine and web browser with Ajax-based communicator. The handwriting mathematical expression editor adopts a progressive recognition approach for dynamic recognition of handwritten mathematical expressions. The computation engine supports mathematical functions such as algebraic simplification and factorization, and integration and differentiation. The web browser provides a user-friendly interface for accessing the system using advanced Ajax-based communication. In this paper, we describe the different components of the WebMath system and its performance analysis.     

A Visualization Based Approach for Digital Signature Authentication

We propose a visualization based approach for digital signature authentication. Using our method, the speed and pressure aspects of a digital signature process can be clearly and intuitively conveyed to the user for digital signature authentication. Our design takes into account both the expressiveness and aesthetics of the derived visual patterns. With the visual aid provided by our method, digital signatures can be authenticated with better accuracy than using existing methods—even novices can examine the authenticity of a digital signature in most situations using our method. To validate the effectiveness of our method, we conducted a comprehensive user study which confirms positively the advantages of our approach. Our method can be employed as a new security enhancement measure for a range of business and legal applications in reality which involve digital signature authorization and authentication.     

Modeling Default Data Via an Interactive Hidden Markov Model

In this paper, we first introduce the use of an interactive hidden Markov model (IHMM) for modeling and analyzing default data in a sector. Under the IHMM, transitions of the hidden risk states of the sector depend on the observed number of bonds in the sector that default in the current time period. This incorporates the feedback effect of the number of defaults on the transitions of the hidden risk states. This feature seems to be more realistic and does not enjoy by the traditional HMMs. We then develop a “dynamic” version of the binomial expansion technique (BET) modulated by the IHMM for modeling the occurrence of defaults of bonds issued by firms in the same sector. Under the BET modulated by the IHMM, the number of bonds defaulting in each time period follows a Markov-modulated binomial distribution with the probability of defaulting of each bond depending on the states of the IHMM, which represent the hidden risk states of the sector. Efficient method will be presented for estimating the model parameters in the BET modulated by the IHMM. We shall compare the hidden risk state process extracted from the IHMM-modulated BET with that extracted from the BET modulated by HMM in order to illustrate the significance of the feedback effect using real data. We shall also present the estimation results for the BET modulated by the IHMM and compare them with those for the BET modulated by the HMM.     

Immunity-based hybrid evolutionary algorithm for multi-objective optimization in global container repositioning

The development of evolutionary algorithms for optimization has always been a stimulating and growing research area with an increasing demand in using them to solve complex industrial optimization problems. A novel immunity-based hybrid evolutionary algorithm known as Hybrid Artificial Immune Systems (HAIS) for solving both unconstrained and constrained multi-objective optimization problems is developed in this research. The algorithm adopts the clonal selection and immune suppression theories, with a sorting scheme featuring uniform crossover, multi-point mutation, non-dominance and crowding distance sorting to attain the Pareto optimal front in an efficient manner. The proposed algorithm was verified with nine benchmarking functions on its global optimal search ability as well as compared with four optimization algorithms to assess its diversity and spread. Sensitivity analysis was also carried out to investigate the selection of key parameters of the algorithm. It is found that the developed immunity-based hybrid evolutionary algorithm provides a useful means for solving optimization problems and has successfully applied to the problem of global repositioning of containers, which is one of a constrained multi-objective optimization problem. The developed HAIS will assist shipping liners on timely decision making and planning of container repositioning operations in global container transportation business in an optimized and cost effective manner.     

On detecting faults for Boolean expressions

Fault based testing aims at detecting hypothesized faults based on specifications or program source. There are some fault based techniques for testing Boolean expressions which are commonly used to model conditions in specifications as well as logical decisions in program source. The MUMCUT strategy has been proposed to generate test cases from Boolean expressions. Moreover, it detects eight common types of hypothesized faults provided that the original expression is in irredundant disjunctive normal form, IDNF. Software practitioners are more likely to write the conditions and logical decisions in general form rather than IDNF. Hence, it is interesting to investigate the fault detecting capability of the MUMCUT strategy with respect to general form Boolean expressions. In this article, we perform empirical studies to investigate the fault detection capability of the MUMCUT strategy with respect to general form Boolean expressions as well as mutated expressions. A mutated expression can be obtained from the original given Boolean expression by making a syntactic change based on a particular type of fault.

Situation awareness acquired from monitoring process plants – the Process Overview concept and measure

We introduce Process Overview, a situation awareness characterisation of the knowledge derived from monitoring process plants. Process Overview is based on observational studies of process control work in the literature. The characterisation is applied to develop a query-based measure called the Process Overview Measure. The goal of the measure is to improve coupling between situation and awareness according to process plant properties and operator cognitive work. A companion article presents the empirical evaluation of the Process Overview Measure in a realistic process control setting. The Process Overview Measure demonstrated sensitivity and validity by revealing significant effects of experimental manipulations that corroborated with other empirical results. The measure also demonstrated adequate inter-rater reliability and practicality for measuring SA based on data collected by process experts.

Practitioner Summary: The Process Overview Measure is a query-based measure for assessing operator situation awareness from monitoring process plants in representative settings.