Computational imaging describes the whole imaging process fromthe perspective of light transport and information transmission, featurestraditional optical computing capabilities, and assists in breakingthrough the limitations of visual information recording. Progressin computational imaging promotes the development of diverse basicand applied disciplines. In this review, we provide an overview ofthe fundamental principles and methods in computational imaging, thehistory of this field, and the important roles that it plays in thedevelopment of science. We review the most recent and promising advancesin computational imaging, from the perspective of different dimensionsof visual signals, including spatial dimension, temporal dimension,angular dimension, spectral dimension, and phase. We also discusssome topics worth studying for future developments in computationalimaging.

The broad applicability of super-resolution microscopy has beenwidely demonstrated in various areas and disciplines. The optimizationand improvement of algorithms used in super-resolution microscopyare of great importance for achieving optimal quality of super-resolutionimaging. In this review, we comprehensively discuss the computationalmethods in different types of super-resolution microscopy, includingdeconvolution microscopy, polarization-based super-resolution microscopy,structured illumination microscopy, image scanning microscopy, super-resolutionoptical fluctuation imaging microscopy, single-molecule localizationmicroscopy, Bayesian super-resolution microscopy, stimulated emissiondepletion microscopy, and translation microscopy. The developmentof novel computational methods would greatly benefit super-resolutionmicroscopy and lead to better resolution, improved accuracy, and fasterimage processing.

Light field imaging is an emerging technology in computationalphotography areas. Based on innovative designs of the imaging modeland the optical path, light field cameras not only record the spatialintensity of threedimensional (3D) objects, but also capture the angularinformation of the physical world, which provides new ways to addressvarious problems in computer vision, such as 3D reconstruction, saliencydetection, and object recognition. In this paper, three key aspectsof light field cameras, i.e., model, calibration, and reconstruction,are reviewed extensively. Furthermore, light field based applicationson informatics, physics, medicine, and biology are exhibited. Finally,open issues in light field imaging and long-term application prospectsin other natural sciences are discussed.

Compared with conventional cameras, spectral imagers providemany more features in the spectral domain. They have been used invarious fields such as material identification, remote sensing, precisionagriculture, and surveillance. Traditional imaging spectrometers usegenerally scanning systems. They cannot meet the demands of dynamicscenarios. This limits the practical applications for spectral imaging.Recently, with the rapid development in computational photographytheory and semiconductor techniques, spectral video acquisition hasbecome feasible. This paper aims to offer a review of the state-of-the-artspectral imaging technologies, especially those capable of capturingspectral videos. Finally, we evaluate the performances of the existingspectral acquisition systems and discuss the trends for future work.

Single-pixel imaging (SPI) technology has garnered great interestwithin the last decade because of its ability to record high-resolutionimages using a single-pixel detector. It has been applied to diversefields, such as magnetic resonance imaging (MRI), aerospace remotesensing, terahertz photography, and hyperspectral imaging. Comparedwith conventional silicon-based cameras, single-pixel cameras (SPCs)can achieve image compression and operate over a much broader spectralrange. However, the imaging speed of SPCs is governed by the responsetime of digital micromirror devices (DMDs) and the amount of compressionof acquired images, leading to low (ms-level) temporal resolution.Consequently, it is particularly challenging for SPCs to investigatefast dynamic phenomena, which is required commonly in microscopy.Recently, a unique approach based on photonic time stretch (PTS) toachieve high-speed SPI has been reported. It achieves a frame ratefar beyond that can be reached with conventional SPCs. In this paper,we first introduce the principles and applications of the PTS technique.Then the basic architecture of the high-speed SPI system is presented,and an imaging flow cytometer with high speed and high throughputis demonstrated experimentally. Finally, the limitations and potentialapplications of high-speed SPI are discussed.

Transient imaging is a technique in photography that recordsthe process of light propagation before it reaches a stationary statesuch that events at the light speed level can be observed. In thisreview we introduce three main models for transient imaging with atime-of-flight (ToF) camera: correlation model, frequency-domain model,and compressive sensing model. Transient imaging applications usuallyinvolve resolving the problem of light transport and separating thelight rays arriving along different paths. We discuss two of the applications:imaging objects inside scattering media and recovering both the shapeand texture of an object around a corner.

Because the phase contains more information about the fieldcompared to the amplitude, measurement of the phase is encounteredin many branches of modern science and engineering. Direct measurementof the phase is difficult in the visible regime of the electromagneticwave. One must employ computational techniques to calculate the phasefrom the captured intensity. In this paper, we provide a review ofour recent work on iterative phase retrieval techniques and theirapplications in optical imaging.

We propose and fabricate a monolithic optical interconnect ona GaN-on-silicon platform using a wafer-level technique. Because theInGaN/GaN multiple-quantum-well diodes (MQWDs) can achieve light emissionand detection simultaneously, the emitter and collector sharing identicalMQW structure are produced using the same process. Suspended waveguidesinterconnect the emitter with the collector to form in-plane lightcoupling. Monolithic optical interconnect chip integrates the emitter,waveguide, base, and collector into a multi-component system witha common base. Output states superposition and 1×2 in-planelight communication are experimentally demonstrated. The proposedmonolithic optical interconnect opens a promising way toward the diverseapplications from in-plane visible light communication to light-inducedartificial synaptic devices, intelligent display, on-chip imaging,and optical sensing.

We propose a method to establish a dynamic model for a waveglider, a wave-propelled sea surface vehicle that can make use ofwave energy to obtain thrust. The vehicle, composed of a surface floatand a submerged glider in sea water, is regarded as a two-particlesystem. Kane’s equations are used to establish the dynamic model.To verify the model, the design of a testing prototypeis proposed and pool trials are conducted. The speeds of the vehicleunder different sea conditions can be computed using the model, whichis verified by pool trials. The optimal structure parameters usefulfor vehicle designs can also be obtained from the model. We illustratehow to build an analytical dynamics model for the wave glider, whichis a crucial basis for the vehicle’s motion control. The dynamicsmodel also provides foundations for an off-line simulation of vehicleperformance and the optimization of its mechanical designs.

We introduce a novel strategy of designing a chaotic coverage path planner for the mobile robot based on the Chebyshev map for achieving special missions. The designed chaotic path planner consists of a two-dimensional Chebyshev map which is constructed by two one-dimensional Chebyshev maps. The performance of the time sequences which are generated by the planner is improved by arcsine transformation to enhance the chaotic characteristics and uniform distribution. Then the coverage rate and randomness for achieving the special missions of the robot are enhanced. The chaotic Chebyshev system is mapped into the feasible region of the robot workplace by affine transformation. Then a universal algorithm of coverage path planning is designed for environments with obstacles. Simulation results show that the constructed chaotic path planner can avoid detection of the obstacles and the workplace boundaries, and runs safely in the feasible areas. The designed strategy is able to satisfy the requirements of randomness, coverage, and high efficiency for special missions.

The component-based business architecture integration of militaryinformation systems is a popular research topic in the field of militaryoperational research. Identifying enterprise-level business componentsis an important issue in business architecture integration. Currentlyused methodologies for business component identification tend to focuson software-level business components, and ignore such enterpriseconcerns in business architectures as organizations and resources.Moreover, approaches to enterprise-level business component identificationhave proven laborious. In this study, we propose a novel approachto enterprise-level business component identification by consideringoverall cohesion, coupling, granularity, maintainability, and reusability.We first define and formulate enterprise-level business componentsbased on the component business model and the Department of DefenseArchitecture Framework (DoDAF) models. To quantify the indices ofbusiness components, we formulate a create, read, update, and delete(CRUD) matrix and use six metrics as criteria. We then formulate businesscomponent identification as a multi-objective optimization problemand solve it by a novel meta-heuristic optimization algorithm calledthe ‘simulated annealing hybrid genetic algorithm (SHGA)’.Case studies showed that our approach is more practical and efficientfor enterprise-level business component identification than prevalentapproaches.

The explosive growth of malware variants poses a major threat to information security. Traditional anti-virus systems based on signatures fail to classify unknown malware into their corresponding families and to detect new kinds of malware programs. Therefore, we propose a machine learning based malware analysis system, which is composed of three modules: data processing, decision making, and new malware detection. The data processing module deals with gray-scale images, Opcode n-gram, and import functions, which are employed to extract the features of the malware. The decision-making module uses the features to classify the malware and to identify suspicious malware. Finally, the detection module uses the shared nearest neighbor (SNN) clustering algorithm to discover new malware families. Our approach is evaluated on more than 20 000 malware instances, which were collected by Kingsoft, ESET NOD32, and Anubis. The results show that our system can effectively classify the unknown malware with a best accuracy of 98.9%, and successfully detects 86.7% of the new malware.

Because of the concise functionality of oblivious transfer (OT)protocols, they have been widely used as building blocks in securemultiparty computation and high-level protocols. The security of OTprotocols built upon classical number theoretic problems, such asthe discrete logarithm and factoring, however, is threatened as aresult of the huge progress in quantum computing. Therefore, post-quantumcryptography is needed for protocols based on classical problems,and several proposals for post-quantum OT protocols exist. However,most post-quantum cryptosystems present their security proof onlyin the context of classical adversaries, not in the quantum setting.In this paper, we close this gap and prove the security of the lattice-basedOT protocol proposed by Peikert et al. (CRYPTO, 2008), which is universally composably secure under theassumption of learning with errors hardness, in the quantum setting.We apply three general quantum security analysis frameworks. First,we apply the quantum lifting theorem proposed by Unruh (EUROCRYPT,2010) to prove that the security of the lattice-based OT protocolcan be lifted into the quantum world. Then, we apply two more securityanalysis frameworks specified for post-quantum cryptographic primitives,i.e., simple hybrid arguments (CRYPTO, 2011) and game-preserving reduction(PQCrypto, 2014).

In modern energy-saving replication storage systems, a primarygroup of disks is always powered up to serve incoming requests whileother disks are often spun down to save energy during slack periods.However, since new writes cannot be immediately synchronized intoall disks, system reliability is degraded. In this paper, we developa high-reliability and energy-efficient replication storage system,named RERAID, based on RAID10. RERAID employs part of the free spacein the primary disk group and uses erasure coding to construct a codecache at the front end to absorb new writes. Since code cache supportsfailure recovery of two or more disks by using erasure coding, RERAIDguarantees a reliability comparable with that of the RAID10 storagesystem. In addition, we develop an algorithm, called erasure codingwrite (ECW), to buffer many small random writes into a few large writes,which are then written to the code cache in a parallel fashion sequentiallyto improve the write performance. Experimental results show that RERAIDsignificantly improves write performance and saves more energy thanexisting solutions.

The introduction of proportional-integral-derivative (PID) controllersinto cooperative collision avoidance systems (CCASs) has been hinderedby difficulties in their optimization and by a lack of study of theireffects on vehicle driving stability, comfort, and fuel economy. Inthis paper, we propose a method to optimize PID controllers usingan improved particle swarm optimization (PSO) algorithm, and to bettermanipulate cooperative collision avoidance with other vehicles. First,we use PRESCAN and MATLAB/Simulink to conduct a united simulation,which constructs a CCAS composed of a PID controller, maneuver strategyjudging modules, and a path planning module. Then we apply the improvedPSO algorithm to optimize the PID controller based on the dynamicvehicle data obtained. Finally, we perform a simulation test of performancebefore and after the optimization of the PID controller, in whichvehicles equipped with a CCAS undertake deceleration driving and steeringunder the two states of low speed (≤50 km/h) and high speed (≥100km/h) cruising. The results show that the PID controller optimizedusing the proposed method can achieve not only the basic functionsof a CCAS, but also improvements in vehicle dynamic stability, ridingcomfort, and fuel economy.

Complementing our previous publications, this paper presentsthe information schema constructs (ISCs) that underpin the programmingof specific system manifestation feature (SMF) orientated informationmanagement and composing system models. First, we briefly present(1) the general process of pre-embodiment design with SMFs, (2) theprocedures of creating genotypes and phenotypes of SMFs, (3) the specificprocedure of instantiation of phenotypes of SMFs, and (4) the procedureof system model management and processing. Then, the chunks of informationneeded for instantiation of phenotypes of SMFs are discussed, andthe ISCs designed for instantiation presented. Afterwards, the informationmanagement aspects of system modeling are addressed. Methodologically,system modeling involves (1) placement of phenotypes of SMF in themodeling space, (2) combining them towards the desired architectureand operation, (3) assigning values to the parameters and checkingthe satisfaction of constraints, and (4) storing the system modelin the SMFs-based warehouse database. The final objective of the reportedresearch is to develop an SMFs-based toolbox to support modeling ofcyber-physical systems (CPSs).

In the field of nanotechnology, quantum dot-cellular automata(QCA) is the promising archetype that can provide an alternative solutionto conventional complementary metal oxide semiconductor (CMOS) circuit.QCA has high device density, high operating speed, and extremely lowpower consumption. Reversible logic has widespread applications inQCA. Researchers have explored several designs of QCA-based reversiblelogic circuits, but still not much work has been reported on QCA-basedreversible binary subtractors. The low power dissipation and highcircuit density of QCA pledge the energy-efficient design of logiccircuit at a nano-scale level. However, the necessity of too manylogic gates and detrimental garbage outputs may limit the functionalityof a QCA-based logic circuit. In this paper we describethe design and implementation of a DG gate in QCA. The universal natureof the DG gate has been established. The QCA building block of theDG gate is used to achieve new reversible binary subtractors. Theproposed reversible subtractors have low quantum cost and garbageoutputs compared to the existing reversible subtractors. The proposedcircuits are designed and simulated using QCA Designer-2.0.3.

Rotating speed is a critical parameter affecting the performanceof rotor gyroscopes. Rotor gyroscopes must operate at the rated rotatingspeed. To shorten the start time of the ball-disk rotor gyroscope,this paper presents a new design of the drive system for a ball-diskrotor gyroscope. The drive system is monitored by a microcontroller.First, the microcontroller generates a sine pulse width modulationsignal to drive the permanent magnet rotor. Second, the position ofthe rotor is detected according to the back electromotive force inthe non-energized coil. Third, a piecewise closed-loop control algorithmis implemented to keep the angular acceleration of the rotor withinthe safe range automatically during the acceleration process and whenrunning at a constant speed. This control algorithm can avoid rotorstalling due to loss of steps. Experimental result shows that withthe help of adaptive quick-start technique, the start time of thedevice can be shortened by up to 36.6%.

We propose a method to suppress deceptive jamming by frequencydiverse array (FDA) in radar electronic countermeasure environments.FDA offers a new range-angle-dependent beam pattern through a smallfrequency increment across elements. Due to the coupling between theangle and range, a mismatch between the test angle and physical angleoccurs when the slant range on which the beam focuses is not equalto the slant range of the real target. In addition, the range of thetarget can be extracted by sum-difference beam except for time-delaytesting, because the beam provides a range resolution in the FDA thatcannot be deceived by traditional deceptive jamming. A strategy ofusing FDA to transmit two pulses with zero and nonzero frequency increments,respectively, is proposed to ensure that the angle of a target canbe obtained by FDA. Moreover, the localization performance is examinedby analyzing the Cramer-Rao lower bound and detection probability.Effectiveness of the proposed method is confirmed by simulation results.