A chaotic non-dominated sorting genetic algorithm for the multi-objective automatic test task scheduling problem

Solving a task scheduling problem is a key challenge for automatic test technology to improve throughput, reduce test time, and operate the necessary instruments at their maximum capacity. Therefore, this paper attempts to solve the automatic test task scheduling problem (TTSP) with the objectives of minimizing the maximal test completion time (makespan) and the mean workload of the instruments. In this paper, the formal formulation and the constraints of the TTSP are established to describe this problem. Then, a new encoding method called the integrated encoding scheme (IES) is proposed. This encoding scheme is able to transform a combinatorial optimization problem into a continuous optimization problem, thus improving the encoding efficiency and reducing the complexity of the genetic manipulations. More importantly, because the TTSP has many local optima, a chaotic non-dominated sorting genetic algorithm (CNSGA) is presented to avoid becoming trapped in local optima and to obtain high quality solutions. This approach introduces a chaotic initial population, a crossover operator, and a mutation operator into the non-dominated sorting genetic algorithm II (NSGA-II) to enhance the local searching ability. Both the logistic map and the cat map are used to design the chaotic operators, and their performances are compared. To identify a good approach for hybridizing NSGA-II and chaos, and indicate the effectiveness of IES, several experiments are performed based on the following: (1) a small-scale TTSP and a large-scale TTSP in real-world applications and (2) a TTSP used in other research. Computational simulations and comparisons show that CNSGA improves the local searching ability and is suitable for solving the TTSP.     

A novel artificial bee colony algorithm with Powell's method

Artificial bee colony (ABC) algorithm is a relatively new optimization technique which has been shown to be competitive to other population-based algorithms. However, there is still an insufficiency in ABC regarding its solution search equation, which is good at exploration but poor at exploitation. To address this concerning issue, we first propose a modified search equation which is applied to generate a candidate solution in the onlookers phase to improve the search ability of ABC. Further, we use the Powell's method as a local search tool to enhance the exploitation of the algorithm. The new algorithm is tested on 22 unconstrained benchmark functions and 13 constrained benchmark functions, and are compared with some other ABCs and several state-of-the-art algorithms. The comparisons show that the proposed algorithm offers the highest solution quality, fastest global convergence, and strongest robustness among all the contenders on almost all test functions.     

Efficient bidirectional quantum secure communication with two-photon entanglement

An efficient bidirectional quantum secure communication protocol is proposed with two-photon entanglement. Compared with the previous protocol proposed by Shi et al., our protocol can achieve higher efficiency. Meanwhile, for the same length secret messages, only half of entangled photon pairs need to be prepared in our protocol. And the number of classical bits in public classical communication is also a half of that in the previous protocol. Moreover, the information leakage does not exist in our scheme.     

Input-to-state-stability modular command filtered back-stepping attitude control of a generic reentry vehicle

A command filtered back-stepping attitude controller is exploited and analyzed to design a dynamic state-feedback controller for a generic Reentry Vehicle. A novel back-stepping control that obviates the need to compute analytic derivatives in the traditional back-stepping design is presented by combining command filtered back-stepping method, sliding-mode-based integral filters and inputto-state stability (ISS) analysis. The ISS-modular approach provides a simple and effective way for controlling non-linear Reentry Vehicle satisfying the strict-feedback form, simultaneously solving the problem of “explosion of complexity” in traditional back-stepping approach. The stability analysis of the closed-loop system and the convergence of the aerodynamic angles are verified based on the smallgain theorem. Numerical simulations are included to demonstrate the effectiveness of the proposed control scheme.     

Spindle-shaped microfluidic chamber with uniform perfusion flows

The reaction chamber is important due to its wide applications. Based on the idea of the bionics, a novel spindle-shaped chamber (S-chamber) for microfluidics was designed to provide uniform flow and eliminate stagnant corners for microchannels. The computational fluid dynamics simulation results demonstrate that these S-chambers have a better performance compared to the conventional diamond-shaped chambers. An S-chamber with the optimized shape, which consists of a rectangle reaction region interfaced to the inlet/outlet channel through an expansion region with smooth arc edges, was fabricated by micromolding of polydimethylsiloxane. This S-chamber was fixed into a microreactor and mounted horizontally on a synthesizer for biochemical reactions. Solvent perfusion experiments and synthetic optimization experiments for in situ synthesis of peptide nucleic acids microarray were performed. The experimental results indicate that the newly designed and fabricated S-chamber provides excellent homogeneous perfusion flows. This type of S-chamber is designed for the most convenient fixation in the horizontal direction, without the need to consider the complicated effect caused by other housing directions. It has a wide application for cell culturing, microarray synthesis, gene hybridization, and many other microfluidic system-based techniques requiring uniform flow conditions.     

Multiconsensus of second order multiagent systems with directed topologies

A novel multiconsensus problem is introduced in multiagent systems. The states of multiple agents in each subnetwork asymptotically converge to a consistent value with information exchanges among subnetworks. The multiconsensus problem of second order multiagent systems with directed topologies is studied. Three linear protocols are proposed to solve the multiconsensus problem. Necessary and sufficient conditions are derived based on matrix theory. Simulations are provided to demonstrate the effectiveness of the theoretical results.     

An efficient quantum search engine on unsorted database

We consider the problem of finding one or more desired items out of an unsorted database. Patel has shown that if the database permits quantum queries, then mere digitization is sufficient for efficient search for one desired item. The algorithm, called factorized quantum search algorithm, presented by him can locate the desired item in an unsorted database using O( $log_4N$ ) queries to factorized oracles. But the algorithm requires that all the attribute values must be distinct from each other. In this paper, we discuss how to make a database satisfy the requirements, and present a quantum search engine based on the algorithm. Our goal is achieved by introducing auxiliary files for the attribute values that are not distinct, and converting every complex query request into a sequence of calls to factorized quantum search algorithm. The query complexity of our algorithm is O( $log_4N$ ) for most cases.     

Computational characterization on the thermoacoustic thermophone effects induced by micro/nano-heating elements

A thermoacoustic thermophone is a classical device wherein an alternating current passes through a thin heating element to emit sound. The newly emerging micro- and nanotechnology has not only greatly improved such a device’s performance, but also expended its new potential functions such as serving as directional ultrasound sources, phased arrays, or even in some audible sound applications. So far, most investigations on thermoacoustic thermophones are on experimental parts. Besides, the existing theoretic analysis generally adopted a fundamental equation for characterizing the surrounding gas which unfortunately could only consider the heat conduction effect. However, the transient volume and pressure change in an ideal gas caused by the periodic heating would definitely trigger the flow process, which in fact contributed to most of the phenomena occurring in small scale. Here, to disclose the actual working process of the thermoacoustic thermophone and the mechanisms thus involved, we developed a computational model to systematically describe both the gas flow dynamics and heat transfer behavior for the first time. Some important physical parameter variations initiated by the alternating voltage and the corresponding double frequency heat flux, such as pressure, velocity, temperature, etc., were successfully revealed. Discoveries on such variations paved the way for the identification of critical factors that affected the sound pressure, which as a result would serve as a valuable reference for designing a thermoacoustic thermophone in the near future.     

Development of a nanofluidic preconcentrator with precise sample positioning and multi-channel preconcentration

A nanofluidic preconcentrator with the capability of rapidly preconcentrating and precisely positioning protein bands in multiple microchannels has been developed for highly sensitive detection of biomolecules. A novel electrical resistive network model is developed to guide the design of the nanofluidic preconcentrator which consists of a PDMS slab bonded with a glass slide. In the prototype design, two microchannels (23 mm long, 25–50 μm wide, and 5–15 μm deep), one preconcentration microchannel and one ground microchannel are connected in the middle via 16 nanochannels (25–50 μm long, 25 μm wide, and 50–80 nm deep). With two sets of optimal voltage settings applied on the opposite ends of the nanofluidic chip, the ion depletion region and electrokinetic trapping were generated to carry out the preconcentration. With the optimal voltage settings (30–30 V) predicted by the model, the ionic current of the nanochannel in our optimized preconcentrator was adjusted to be greater than the threshold value (3.9 nA) needed for the occurrence of the preconcentration, and a preconcentration factor >10⁵ was achieved in 5 min. The sample positioning capability of the preconcentrator was demonstrated by adjusting the applied voltages and moving the preconcentrated protein bands to multiple sites by a distance from several micrometers to several millimeters in the preconcentration channel. The multi-channel preconcentration capability was also demonstrated by preconcentrating two protein bands in two separate microchannels. In this work, the resistive network model was developed and validated to optimize nanofluidic preconcentrators for rapid, high throughput and highly sensitive sensing of low abundance analytes.