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Many anthropological researches require identification and measurement of craniometric and cephalometric landmarks which provide valuable information about the shape of a head. This information is necessary for morphometric analysis, face approximation, craniafacial identification etc. Traditional techniques use special anthropological tools to perform required measurements, identification of landmarks usually being made by an expert-anthropologist. Modern techniques of optical 3D measurements such as photogrammetry, computer tomography, laser 3D scanning provide new possibilities for acquiring accurate 2D and 3D data of high resolution, thus creating new conditions for anthropological data analysis. Traditional anthropological manual point measurements can be substituted by analysis of accurate textured 3D models, which allow to retrieve more information about studied object and easily to share data for independent analysis. The paper presents the deep learning technique for anthropological landmarks identification and accurate 3D measurements. Photogrammetric methods and their practical implementation in the automatic system for accurate digital 3D reconstruction of anthropological objects are described.

This paper proposes a new hybrid method for automatic detection and recognition of the presence/absence of a protective mask on human's face. It combines visual features extracted using Convolutional Neural Network (CNN) with image histograms that convey information about pixel intensity. Several pre-trained models for building feature extraction systems using a CNN and several types of image histograms are considered in this paper. We test our approach on the Medical Mask Dataset and perform cross-corpus analysis on two other databases named Masked Faces (MAFA) and Real-World Masked Face Dataset (RMFD). We demonstrate that the proposed hybrid method increases the Unweighted Average Recalls (UARs) of recognition of the presence/absence of a protective mask on human's face in comparison with traditional CNNs on the MAFA and RMFD databases by 0.96% and 1.32%, respectively. The proposed method can be generalized and used for other tasks of biometry, computer vision, machine learning and automatic face recognition.

The active development of neural network technologies and optoelectronic systems has led to the introduction of computer vision technologies in various fields of science and technology. Deep learning made it possible to solve complex problems that a person had not been able to solve before. The use of multi-spectral optical systems has significantly expanded the field of application of video systems. Tasks such as image recognition, object re-identification, video surveillance require high accuracy, speed and reliability. These qualities are provided by algorithms based on deep convolutional neural networks. However, they require to have large databases of multi-spectral images of various objects to achieve state-of-the-art results. While large and various databases of color images of different objects are widely available in public domain, then similar databases of thermal images are either not available, or they represent a small number of types of objects. The quality of three-dimensional modeling for the thermal imaging spectral range remains at an insufficient level for solving a number of important tasks, which require high precision and reliability. The realistic synthesis of thermal images is especially important due to the complexity and high cost of obtaining real data. This paper is focused on the development of a method for synthesizing thermal imaging images based on generative adversarial neural networks. We developed an algorithm for a multi-spectral image-to-image translation. We have changed to the original GAN architecture and converted the loss function. We presented a new learning approach. For this, we prepared a special training dataset including about 2000 image tensors. The evaluation of the results obtained showed that the proposed method can be used to expand the available databases of thermal images.

In this paper, a new technique for real-time object detection and tracking is presented. This technique is based on the geometrized histograms method (GHM) for segmenting and describing color images (frames of video sequences) and on the facilities for global image analysis provided by this method. Basic elements of the technique that make it possible to solve image understanding problems almost without using the pixel arrays of images are introduced and discussed.A real-time parallel software implementation of the developed technique is briefly discussed. This technique is applied to solving problems of road scene analysis. The application to finding small contrast objects in images, like traffic signals and signal zones of vehicles is given. The developed technique is applied also to detecting other vehicles in the frame. The results of processing different frame of videos of road scenes are presented and discussed.

Today, possibilities of artificial intelligence allow us to see the emergence of autonomous cars. However, there are still many problems in this area at present. Often, such vehicles are “too slow to think”, are not able to reliably process data from video cameras in the event of reflections, glare, and there are also questions about the safety of such driving in difficult weather conditions or in heavy traffic. At the same time, the human factor plays a major role in accidents of driven vehicles. Many accidents involve driver fatigue, distraction, or even falling asleep. At the same time, it is potentially possible to monitor the state of a person behind the wheel by a video sequence received from a camera installed in the car's interior and registering the driver's face in video sequence. In this paper, the existing databases of images of faces and eyes are considered, and an algorithm is presented that detects the state of closed eyes based on Haar detectors and convolutional neural networks.

Image matting often requires advanced image processing, especially in conditions, when small details such as hair are present in the image. In this article the hybrid method for human image matting based on convolutional neural network and principal curvatures is proposed. The U-Net based neural network is used to predict a rough foreground segmentation mask. Then the obtained foreground mask is refined by principal curvatures method to process the elongated hair-like structures. Test results show that the proposed method can improve the coarse human segmentation.

In the era of data-driven machine learning algorithms, data represents a new oil. The application of machine learning algorithms shows they need large heterogeneous datasets that crucially are correctly labeled. However, data collection and its labeling are time-consuming and labor-intensive processes. A particular task we solve using machine learning is related to the segmentation of medical devices in echocardiographic images during minimally invasive surgery. However, the lack of data motivated us to develop an algorithm generating synthetic samples based on real datasets. The concept of this algorithm is to place a medical device (catheter) in an empty cavity of an anatomical structure, for example, in a heart chamber, and then transform it. To create random transformations of the catheter, the algorithm uses a coordinate system that uniquely identifies each point regardless of the bend and the shape of the object. It is proposed to take a cylindrical coordinate system as a basis, modifying it by replacing the Z-axis with a spline along which the h-coordinate is measured. Having used the proposed algorithm, we generated new images with the catheter inserted into different heart cavities while varying its location and shape. Afterward, we compared the results of deep neural networks trained on the datasets comprised of real and synthetic data. The network trained on both real and synthetic datasets performed more accurate segmentation than the model trained only on real data. For instance, modified U-net trained on combined datasets performed segmentation with the Dice similarity coefficient of 92.6±2.2%, while the same model trained only on real samples achieved the level of 86.5±3.6%. Using a synthetic dataset allowed decreasing the accuracy spread and improving the generalization of the model. It is worth noting that the proposed algorithm allows reducing subjectivity, minimizing the labeling routine, increasing the number of samples, and improving the heterogeneity.

In medical image processing, image fusion is the process of combining complementary information from different (multimodality) images to obtain a fused image, which plays a vital role in further analysis and treatment planning. The main idea of this paper is to improve the image content by fusing computer tomography (CT) and magnetic resonance (MR) images. We propose here the new algorithm based on the probabilistic gamma-normal model with structure-transferring properties. Firstly, we select the areas with the highest pixel intensity on original CT and MR images. In parallel with this, the structures of original images are distinguished using the probabilistic gamma-normal model. The weighted-fusion image can be obtained based on detected objects and structure. Finally, we smooth the weighted-fusion image using the structure-transferring filter and combine the smoothed image with the weighted-fusion image for obtaining the resulting image. The key point here is that we do not need to re-allocate the structure, which leads to the reduction of computation time. The proposed method gives the best result in terms of the spatial frequency metric and lower computation time than other image fusion methods.

Over the past few years closer cooperation can be observed in various aspects of digital techniques in such disciplines as dentistry and anthropology. And in most cases that consists in imaging and image processing which results in obtaining 3D reconstructions. And indeed, they can significantly improve research and practice. Thus, depending on imaging technique and application, they can support CAD/CAM technology or precisely reconstruct morphology of invisible structures. However the currently presented study refers to technical aspects of shade and texture mapping, which is more aimed to obtain more realistic 3D reconstructions of palaeoanthropological material. Colour or shade matching has become an integral part of dental practice. It can be carried in a traditional manner though matching the tooth with conventional shade-guides, or, which is in line with the subjects of our study, by means of spectrophotometry. And the main procedures of shade detection have been performed by SpectroShade (MHT). Necessary attention has been paid to conditions influencing shade detection process with respect to the studied material teeth taken from the Bronze Age findings. Reconstructive techniques have traditionally been a scientific and practical part of palaeoanthropological research which is directed at appearance reconstruction. Though the leading part of this branch has been always aimed at analysis of skull morphology. In our time of rapidly developing digital techniques reconstructions have become to a large extent a matter of improvements of imaging and image processing techniques. Even though this doesnt directly refer to soft tissue reconstruction, it undoubtedly applies to dental reconstructions. And the current study presents improvements in reconstruction through combining imaging with shade and texture mapping on 3D models of teeth.

Visual information plays a key role in automatic speech recognition (ASR) when audio is corrupted by background noise, or even inaccessible. Speech recognition using visual information is called lip-reading. The initial idea of visual speech recognition comes from humans’ experience: we are able to recognize spoken words from the observation of a speaker's face without or with limited access to the sound part of the voice. Based on the conducted experimental evaluations as well as on analysis of the research field we propose a novel task-oriented approach towards practical lip-reading system implementation. Its main purpose is to be some kind of a roadmap for researchers who need to build a reliable visual speech recognition system for their task. In a rough approximation, we can divide the task of lip-reading into two parts, depending on the complexity of the problem. First, if we need to recognize isolated words, numbers or small phrases (e.g. Telephone numbers with a strict grammar or keywords). Or second, if we need to recognize continuous speech (phrases or sentences). All these stages disclosed in detail in this paper. Based on the proposed approach we implemented from scratch automatic visual speech recognition systems of three different architectures: GMM-CHMM, DNN-HMM and purely End-to-end. A description of the methodology, tools, step-by-step development and all necessary parameters are disclosed in detail in current paper. It is worth noting that for the Russian speech recognition, such systems were created for the first time.

Mobile devices provide a huge amount of multimedia information sending to the members of social groups every day. Sometimes it is required to authorize the sending information using the limited computational resources of smartphones, tablets or laptops. The hardest problem is with smartphones, which have the limited daily energy and battery life. There are two scenarios for using mobile watermarking techniques. The first scenario is to implement the embedding and extraction schemes using proxy server. In this case, the watermarking scheme does not differ from conventional techniques, including the advanced ones based on adaptive paradigms, deep learning, multi-level protection, and so on. The main issue is to hide the embedding and extracting information from the proxy server. The second scenario is to provide a pseudo-optimized algorithm respect to robustness, imperceptibility and capacity using limited mobile resources. In this paper, we develop the second approach as a light version of adaptive image and video watermarking schemes. We propose a simple approach for creating a patch-based set for watermark embedding using texture estimates in still images and texture/motion estimates in frames that are highly likely to be I-frames in MPEG notation. We embed one or more watermarks using relevant large-sized patches according to two main criteria: high texturing in still images and high texturing/non-significant motion in videos. The experimental results confirm the robustness of our approach with minimal computational costs.

The presented research considers the problems of studying the cluster structure of multidimensional data volumes. This paper presents the results of numerical experiments on the study of data volumes consisting of frequencies of joint use of words from different parts of speech, for instance “noun + verb” or “adjective + noun”. The volumes of data are obtained from samples from text collections in Russian. The aim of the research is to analyze the cluster structure of the studied volume and semantic proximity of words in clusters and subclusters. The hypothesis was used that words with similar meaning should occur in approximately the same context. In this regard, in the space of features, they will be at a relatively close distance from each other, while differing words will be at a more distant distance from each other. Research is carried out using elastic maps, which are effective tools for visual analysis of multidimensional data. The construction of elastic maps and their extensions in the space of the first three principal components makes it possible to determine the cluster structure of the studied multidimensional data volumes. Such analysis can be useful in the tasks of confronting negative verbal influences such as fake news, hidden propaganda, involvement in sects, verbal manipulation, etc. Also this approach can be applied to text collections having medical origin.

Object Re-Identification (ReID) is the task of matching a given object in the new environment with its image captured in a different environment. The input for a ReID method includes two sets of images. The probe set includes one or more images of the object that must be identified in the new environment. The gallery set includes images that may contain the object from the probe image. The ReID task’s complexity arises from the differences in the object appearance in the probe and gallery sets. Such difference may originate from changes in illumination or viewpoint locations for multiple cameras that capture images in the probe and gallery sets. This paper focuses on developing a deep learning ThermalReID framework for cross-modality object ReID in thermal images. Our framework aims to provide continuous object detection and re-identification while monitoring a region from a UAV. Given an input probe image captured in the visible range, our ThermalReID framework detects objects in a thermal image and performs the ReID. We evaluate our ThermalReID framework and modern baselines using various metrics. We use the IoU and mAP metrics for the object detection task. We use the cumulative matching characteristic (CMC) curves and normalized area-under-curve (nAUC) for the ReID task. The evaluation demonstrated encouraging results and proved that our ThermalReID framework outperforms existing baselines in the ReID accuracy. Furthermore, we demonstrated that the fusion of the semantic data with the input thermal gallery image increases the object detection and localization scores. We developed the ThermalReID framework for cross-modality object re-identification. We evaluated our framework and two modern baselines on the task of object ReID for four object classes. Our framework successfully performs object ReID in the thermal gallery image from the color probe image. The evaluation using real and synthetic data demonstrated that our ThermalReID framework increases the ReID accuracy compared to modern ReID baselines.

A new topology that generates a DC voltage whose value is depending on the phase difference of two input RF signals is presented. It is implemented by the mixer concept. With the use of microwave photonics, the mixer-based phase detector can be operated over a very wide frequency range. It also has the advantages of high phase detection resolution, small phase detection error, and small DC offset and phase offset. The phase detector can be constructed using off-the-shelf components including a single integrated optical modulator and a low-speed balanced detector. Measured results on the phase detector demonstrate a 0° to 180° RF signal phase difference detection range for 3.5 GHz to 18 GHz input RF signal frequencies, less than ±3° phase detection error and 2° phase detection resolution.

Van der Waals (vdW) heterostructures based on transition metal dichalcogenides (TMDs) generally possess a type-II band alignment that facilitates the formation of interlayer excitons between constituent monolayers. Manipulation of the interlayer excitons in TMD vdW heterostructures holds great promise for the development of excitonic integrated circuits that serve as the counterpart of electronic integrated circuits, which allows the photons and excitons to transform into each other and thus bridges optical communication and signal processing at the integrated circuit. As a consequence, numerous studies have been carried out to obtain deep insight into the physical properties of interlayer excitons, including revealing their ultrafast formation, long population recombination lifetimes, and intriguing spin-valley dynamics. These outstanding properties ensure interlayer excitons with good transport characteristics, and may pave the way for their potential applications in efficient excitonic devices based on TMD vdW heterostructures. At present, a systematic and comprehensive overview of interlayer exciton formation, relaxation, transport, and potential applications is still lacking. In this review, we give a comprehensive description and discussion of these frontier topics for interlayer excitons in TMD vdW heterostructures to provide valuable guidance for researchers in this field.

An iterative pairwise maximum likelihood (ML) receiver is proposed for asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) in visible light communications (VLC). With the aid of the pairwise ML detection, half of the received ACO-OFDM samples are forced to zero in time domain. However, when the signal-to-noise ratio (SNR) is low, the pairwise ML detection may cause misjudgment. With the iterative pairwise ML detection, the ACO-OFDM symbols are detected in frequency domain and the SNR gain of 3 dB could be available. Simulation results show that the pairwise ML receiver without iteration provides the SNR improvement of 1.5∼2.7 dB for 7% forward error correction (FEC) limit. The proposed iterative receiver gives a SNR gain of 2.6∼2.9 dB with 7% FEC limit.

The human desire to live in an urban area increases every day. However, citizens’ expectation of urban life is very different compared to the past. It is, thus, essential to satisfy their requirements and ensure their safety within their cities. As a result, there is a huge trend in the implementation of smart cities around the world. A smart city is a solution to improve the quality of life of the citizens, and governing the city in an efficient and systematic. Besides, significant advances have been raised in biometrics technologies, which have made many aspects of urban life easier, more efficient, and more secure. Accordingly, to be compliant with the demands of a smart city in the future, biometrics-based technologies will certainly play a significant role from now on. Thus, it is necessary to list the different biometrics methods that could be used in smart cities and to review the variety of applications for each method. In this article, we have listed the potential biometrics systems that can be employed in smart cities, such as facial recognition, age estimation, gender detection, facial expression detection and sentiment recognition, and gait recognition. We also have listed different applications imagined for each biometrics system such as their application in identification systems and security, smart healthcare, smart advertising, education, and high-risk lifestyle behaviours prevention. We believe that this work can help to better use of these methods, improve their technical quality, and also employing them in the advance and more effective ways.

In order to achieve high-speed, high-sensitivity optical communication over long distances and high attenuation channels, we propose a photon-counting communication system based on the detection of multichannel single-photon avalanche diodes (SPADs). First, the ideal pulse position modulation (PPM) bit error rate (BER) expression for a multichannel detection system is derived, and then the effect of the detector's dead time is taken into account. The BER of the multichannel detection system was analyzed by means of a Monte Carlo simulation, after which we set up a four-channel receiving experimental verification system with a 1 × 4 fiber splitter and four single-photon counting modules (SPCMs). The simulation and experimental results demonstrated that the BER of the multichannel detection system could be greatly reduced and the communication speed substantially improved. Finally, a reliable photon-counting communication system with a rate of 50 Mbps and sensitivity of 4 photons/bit was developed using serially-concatenated pulse position modulation (SCPPM) technology.

The issues of image fusion in a two-position small-size radar on-board operational monitoring system are considered. The aim of present research is to develop a method for fusion of images of the land surface based on data obtained from a multi-sensor spatially distributed on-board location system implemented on the basis of a UAV. The method of combining different-angle location images is implemented iteratively. At each iteration, there is a search for pairs of points of the contour of the isolated areas. Areas are highlighted using two image segmentation methods. The final result is a proposed method for information fusion from a two-position on-board small-sized radar system and an optical location system. The implemented method of fusion makes it possible to increase the information content, quality and reliability of information about the observed underlying surfaces and the physical objects detected on them. The practical significance of the results obtained lies in the formation of integral information in real time in the interests of environmental reconnaissance, monitoring in hard-to-reach and dangerous places for human life, as well as in order to promptly prevent natural and man-made emergencies.

We report the design, fabrication and characterization of a 1.55-μm dual-wavelength Distributed Bragg Reflector (DBR) laser photonic integrated circuit (PIC) chip for continuous-waves (CW) terahertz generation. The PIC chip consists of a pair of parallel DBR lasers with integrated semiconductor optical amplifiers (SOA), and a multimode interference (MMI) coupler for combining the two wavelength channels into a single output waveguide. A room temperature continuous wave THz tuning range of 0.06 THz – 0.71 THz was obtained through optical heterodyne technique.

Electromagnetic metasurface cloaks provide an alternative paradigm toward rendering arbitrarily shaped scatterers invisible. Most transformation-optics (TO) cloaks intrinsically need wavelength-scale volume/thickness, such that the incoming waves could have enough long paths to interact with structured meta-atoms in the cloak region and consequently restore the wavefront. Other challenges of TO cloaks include the polarization-dependent operation to avoid singular parameters of composite cloaking materials and limitations of canonical geometries, e.g., circular, elliptical, trapezoidal, and triangular shapes. Here, we report for the first time a conformal-skin metasurface carpet cloak, enabling to work under arbitrary states of polarization (SOP) at Poincaré sphere for the incident light and arbitrary conformal platform of the object to be cloaked. By exploiting the foundry three-dimensional (3D) printing techniques to fabricate judiciously designed meta-atoms on the external surface of a conformal object, the spatial distributions of intensity and polarization of its scattered lights can be reconstructed exactly the same as if the scattering wavefront were deflected from a flat ground at any SOP, concealing targets under polarization-scanning detections. Two conformal-skin carpet cloaks working for partial- and full-azimuth plane operation are respectively fabricated on trapezoid and pyramid platforms via 3D printing. Experimental results are in good agreement with numerical simulations and both demonstrate the polarization-insensitive cloaking within a desirable bandwidth. Our approach paves a deterministic and robust step forward to the realization of interfacial, free-form, and full-polarization cloaking for a realistic arbitrary-shape target in real-world applications.

We utilize singular spectrum analysis (SSA) for post-processing distance measurement data obtained by a dual-comb femtosecond laser rangefinder. Signal denoising technique based on SSA allows detection of low amplitude vibrations from time series of distance data with limited signal-to-noise ratio (SNR). Various one-dimensional vibrations, including harmonic, amplitude modulated harmonic, and sinc-function vibrations, with micrometer amplitude comparable with measurement uncertainty of laser rangefinder, have been imposed on the target mirror by a piezo positioner. These vibrations have been extracted by SSA and the obtained vibration amplitudes agree with that imposed on the target very well. A commercial interferometer is used to evaluate the accuracy of SSA. Standard deviations of residuals between the SSA extractions and interferometer measurements are smaller than 0.6 $\mu$ m. This technique is promising for complex moving pattern detection in object tracking and remote sensing.

We report the design and fabrication of a high-speed GeSn normal-incidence p-i-n photodetector. To realize high-speed detection in all telecommunication bands, we optimize the Sn content in the absorption layer, the absorption-layer thickness, and the device size. The responsivity of the 18-μm-diameter device at 1550 nm reaches 0.32 A/W with an extended cutoff wavelength of 1700 nm and a 3-dB bandwidth as high as 28 GHz under −3 V bias, clear open eye diagrams are also obtained under zero bias at 1630 nm. All the results indicate that the device has a significant potential for applications in Si-based optical telecommunication in all telecommunication bands.

In this paper, we propose a dynamic key technique based on Cellular Neural Network (CNN) for security improvement in the orthogonal frequency division multiplexing passive optical network (OFDM-PON). To enhance the encryption scheme security, a six-dimensional CNN hyperchaotic system is employed to encrypt the data. And, the keys are divided into the dynamic and static. The dynamic key is randomly extracted from a key set by incorporating the random feature of the input data. Then, the chaotic sequence generated by the dynamic key is served as the synchronous sequence for encryption. Moreover, the chaotic sequences generated by the static keys are used to resist the chosen-plaintext attacks (CPAs) and scramble the phase of QAM symbols on the frequency domain. With these processing techniques, the multi-fold data encryption can create a key space of ∼10315 to protect against the exhaustive trial. The transmission of 10-Gb/s encrypted 16-QAM-based OFDM signal is demonstrated over 20-km single mode fiber (SMF) by experiment. The results show that our proposed scheme can provide excellent confidentiality of data transmission against the CPAs and brute-force attack.

A systematic comparison of fiber-based gas pressure sensors using different types of hollow-core photonic crystal fibers (PCFs) is conducted. The sensor was fabricated by splicing a segment of hollow-core silica capillary between a single mode fiber (SMF) and a hollow-core PCF. A Fabry-Perot (FP) cavity configuration is thus formed with the capillary tube as the sensing cavity, while the PCF acts as gas passage to the external environment. External pressure change would lead to the variation in the refractive index of air in the sensing cavity, resulting in a wavelength shift of the interference dips. The pressure sensitivity is measured to be around 4 nm/MPa, with a high linearity of 99.7% or above, regardless of the type of the PCFs we used as gas inlet. Among the four different PCFs, the large-mode-area (LMA) PCF shows the highest fringe contrast in the reflection spectrum. Modal analysis reveals that this is due to the high reflectivity caused by the solid core of LMA-PCF. Our experimental results also indicate that the length of the sensing cavity, as well as the offset fusion splice will influence the fringe contrast. The sensor has potential application in gas pressure sensing for advantages of high sensitivity, compact size and ease of fabrication.

The research results in the field of computer visualization of the shoulder joint biomechanics are presented. The possibilities of using biomechanical robotic mechanotherapy on the CON-TREX complex in the rehabilitation treatment of patients after arthroscopic shoulder surgery are shown. The possibilities of additional visualization of magnetic resonance imaging (MRI) data using spectral decomposition methods (Shearlet transform and contrasting with color coding) are studied. Experiments with the use of the proposed diagnostic technique are described. The relationship between the MRI data and CON-TREX protocols in planning and implementation of the rehabilitation procedures is demonstrated. The technique which allows to improve the quality and availability of the MRI data in the study of the shoulder joint biomechanics during restorative treatment is described.

We report the effect of the double Rayleigh backscattering (DRB) noise, in which the interference of the signal light with the double Rayleigh backscattered light, on the fiber-optic radio-frequency (RF) transfer system. Here, we theoretically analyze and experimentally demonstrate that the DRB noise within the fiber link will become the dominative noise on the fiber-optic RF transfer system once narrow linewidth lasers are used. The strong DRB noise is experimentally confirmed through the measurement of the effect of the coherent interference term of the signal light and the double Rayleigh backscattered light on the 100 km RF transfer system. Our results provide evidence that the conventional RF transfer technique with the telecommunications-grade lasers, in which the chromatic dispersion effect in the single-mode fiber is compensated by dispersion compensation fibers (DCFs), could be the better choice for high-performance RF transfer.

Fiber loop ring down spectroscopy has been developed into a high-sensitivity technique for sensing many important characteristics of samples, such as refractive index. In contrast to the previous demonstrations by using mode-locked fiber laser, this work is demonstrated to use chaotic laser combined with fiber loop ring down sensor. The formation and performance of fiber tapers was monitored by combining chaotic fiber ring down technology on line and in real time. Two sets of refractive index sensing experiments are performed and further analyzed by using the proposed setup. The results are shown that the detection limit of the chaotic correlation fiber loop ring down system is 3.45 × 10−4 RIU and the sensitivity is 0.0682 ns−1RIU−1 in 6.7 m, respectively. The performance of our system can be drastically improved by increasing the length of the etched fiber tapers to be tens of centimeters using the chaotic correlation fiber loop ring down system with the smaller fiber ring lengths.

The introduction of information technologies into the practice of healthcare significantly changes the methods of diagnosis and treatment, the forms of interaction of doctors with patients and colleagues, the organization of treatment and restoration of health. Modern digital medicine makes it possible to increase the availability, quality and efficiency of medical care.The development of modern three-dimensional modeling and the introduction of a new generation of spiral computed tomographs have significantly expanded the possibilities of using these information technologies in reconstructive surgery. The performed study deals with the problems of forming the personalized digital models of anatomical structures according to patient's tomographic data. The principles of tomographic image segmentation are considered. A review and comparison of the specialized software for obtaining of digital models with the use of tomographic data is given. The evaluation of the functionality, speed and quality of the models is presented. Practical recommendations on the use of the software for creating digital models for medical applications are given. The issues of certification of personalized models and medical products are discussed.

Coded targets are physical optical markers that can be easily identified in an image. Their detection is a critical step in the process of camera calibration. A wide range of coded targets was developed to date. The targets differ in their decoding algorithms. The main limitation of the existing methods is low robustness to new backgrounds and illumination conditions. Modern deep learning recognition-based algorithms demonstrate exciting progress in object detection performance in low-light conditions or new environments. This paper is focused on the development of a new deep convolutional network for automatic detection and recognition of the coded targets and sub-pixel estimation of their centers.

Graphene waveguide plays an important role in modulating optical signal. But it is hard to make a tradeoff between low propagating loss and high field confinement. Here, we propose a bilayer graphene waveguide in a thin topas film and a high refractive index material-germanium cladded with thin metallic film. The influences of structural parameter and chemical potential of graphene are studied to optimize the dimension and working mode. Simulation reveals that our structure can make a balance between high figure of merit (FOM) and low propagation loss, and it reaches a high modulation depth of $\text{2.5 dB}/ \mu\text{m}$ . The design can work with FOM over 200, propagation loss lower than $\text{0.2 dB}/\mu\text{m} $ , and propagation length beyond $\text{30}\;\mu\text{m}$ in a wide band from 6 THz to 18 THz. Compared with previous graphene waveguides, our structure operates from terahertz band to mid-infrared band, and it has longer propagation length due to the existence of bilayer graphene. Besides, benefiting from the thin metallic film, our structure can be integrated on chip.

The paper considers two directions in the use of visual data for information support of purposeful movements of ground vehicles. This is optical odometry and navigation by landmarks in the environment. Optical odometry builds the trajectory of movement of the vehicle based on the determination of displacements based on selective visual data from different fields of view. The choice and indication of landmarks at the described stage of research remains with the operator. The vision system (VS) monitors the specified landmarks and determines the position of the vehicle relative to them. The experiments used such fields of view as monocular forward looking, panoramic (fisheye type) and forward looking stereo system. When combining the data of the visual channel with each other and with the data of other navigation systems, the specificity of visual sensors is taken into account – a significant effect of the reliability and accuracy of the results from the observation conditions. Experimental verification of the VS layout showed the achievability of high accuracy in solving the navigation problem using the visual channel. All the components of the described process of organizing purposeful movements based on the use of the visual channel continue to be improved.

In case of COVID-19 epidemic spread the requirements for protection of medical personnel were increased. This category of specialists has exposure of high risk of COVID-19, due to inevitable numerous contacts with infected persons.Because of this, existing practicable models of medical care are needed to be upgraded (Tavakoli, 2020). The emergency response path was implemented through the opening of new infectious hospitals, re-profiling clinics, as well as increasing workload on medical personnel. This approach is associated with the possible rapid drop-up of qualified medical specialists due to the illness, which is a strong limiting factor to respond to new threats of COVID-19 due to the risks of exhaustion of the human resource. In the worst scenario, a threat of collapse of the emergency and specialized medical care system due to peak load of severe patients under the shortage of doctors and support personnel. To prevent such an emergency, a complex of anti-epidemic events is provided, most of the purpose of interrupting infection contacts, isolation of the most vulnerable contingents, extended population testing for virus or contact with infected persons, this allows you to follow unwanted contacts with the subsequent mobility limitation.Digital monitoring technologies with digitization of incoming data of significant events played the increasing role in all these options. Today they are complemented by robotic supporting. Due to the high risk of the infection in the COVID-19 spread, including the intra-clinic infections, the requirements for reliable disinfection of closed premises intended for patients and medical personnel should be fulfilled. At the same time, the following circumstance should be taken into account. When these work-time activities are imposed on the employee who is forced to stay long in an infected air environment, he is subjected to additional impact of pathogenes. To reduce these threats, robotic support for the work for disinfection of premises with automated air environment control and tracing contacts.

A subwavelength gratings (SWG) assisted directional coupler (DC) is proposed to work as beam splitter (BS) for 850 nm chip-based optical coherence tomography (OCT). The bandwidth of the SWG assisted DC is maximized to 110 nm by selecting appropriate SWG geometries including its duty cycle and period. The axial point spread functions (PSFs) derived from the BS transmittances proves the optimized bandwidth is broad enough to support axial resolution higher than $4 \;\mu m$ . Meanwhile, the SWG period can be manipulated to match the center wavelength between BS and light source so that the wavelength mismatching induced resolution degradation is effectively mitigated. Furthermore, a statistical analysis is performed to demonstrate the SWG assisted DC is a high fabrication-tolerant device in terms of axial resolution, even the SWG geometries suffer from a fabrication jitter in 20 nm variance.

We propose a photonic mixer with image rejection capability using a broadband optical source (BOS) and polarization processing. Intermediate frequency (IF) signals with image rejection are generated from the local oscillator-modulated and the time-delayed radio frequency (RF)-modulated BOS light. The RF operating frequency is flexibly tunable over a wide range by simply adjusting the time delay. In addition, the proposed system is free from dispersion-induced mixing power fading and bias drift problem. Experimental results exhibit an image rejection ratio of more than 44.6 dB for RF signals from 2 to 18 GHz, while the IF signal is fixed at 800 MHz. Image rejection mixing operation at different IF frequencies and signal power is also confirmed.

The applicability of resonant waveguide grating (RWG)-based structures as filters to control the spectral response in an optical communication system is investigated. A new physical model for the structure is established on the basis of the Fabry–Pérot (FP) etalon model and coupled leaky mode theory (CLMT). It is found that the flat-top spectral response of the filter is achieved by the combined effect of the guided-mode resonance of an RWG and its Fabry–Pérot resonance (FPR). The bandwidth-tunable spectral response of the filter can be varied according to the change in the eigenvalues of the RWG by changing the structural parameters such as strip width of the grating and incident angle. The flat-top and bandwidth-tunable RWG-based resonant filter is a promising application for high-performance optical communication systems.

In this paper, we present a novel transmission line architecture in thin-film lithium niobate (TFLN) platforms to improve the velocity match between the microwave and the optical wave. Compared to conventional coplanar waveguide (CPW), the microwave index ($n_m$) of the proposed slotted electrodes can be optimized from 2.1 to 3 while maintaining the high modulation efficiency and 50-$\Omega$ impedance match. Equivalent-circuit model analysis and finite-element simulation are performed. The simulated half-wave voltage (V$_\pi$) of 1.2 V and E-O modulation bandwidth greater than 80 GHz is obtained for a 2-cm-long modulator. By utilizing the slotted slow-wave electrode, TFLN Mach-Zehnder modulators with CMOS-compatible operating voltage and 3-dB modulation bandwidth greater than 100 GHz are potentialized.

In recent years computed tomography of the lungs has been the most common diagnostic procedure aimed at detection of the pathological changes associated with COVID-19. The study is aimed at the use of the developed algorithmic support in combination with texture (geometric) analysis to highlight a number of indicators characterizing the clinical state of the object of interest. Processing is aimed at the solution of a number of diagnostic tasks such as highlighting and contrasting the objects of interest, taking into account the color coding. Further, an assessment is performed according to the appropriate criteria in order to find out the nature of the changes and increase both the visualization of pathological changes and the accuracy of the X-ray diagnostic report. For these purposes, it is proposed to use preprocessing algorithms for a series of images in dynamics. Segmentation of the lungs and areas of possible pathology are performed using wavelet transform and Otsu threshold value. Delta-maps and maps obtained using Shearlet transform with contrasting color coding are used as a means of visualization and selection of features (markers). The analysis of the experimental and clinical material carried out in the work shows the effectiveness of the proposed combination of methods for studying of the variability of the internal geometric features (markers) of the object of interest in the images.

A 365 nm AlxGa1-xN-based ultraviolet light-emitting diodes (LEDs) with double Al composition gradient last quantum barrier and hole supply layer structure has been studied. Experimental results show that the proposed structure enhances the carrier injection efficiency and suppresses the overflow of electrons. The introduction of three-dimensional hole gas further enhances the hole injection efficiency. As a result, the wall plug efficiency and electroluminescence intensity are significantly improved. In addition, the carrier concentration and the radiative recombination rate in the active region of the quantum well increases. Looking at the energy band diagram, one sees that the double Al composition gradient structure leads to higher electron blocking and alleviates the hole blocking effect. Overall, we conclude that the double Al composition gradient structure provides a pathway to achieve high-efficiency ultraviolet LEDs.

We present a comprehensive systematic framework for optimizing adiabaticity in photonic lanterns. The framework considers the effects of both the cross-sectional and longitudinal device parameters on adiabaticity. Photonic lanterns are adiabatic photonic devices and are therefore known to have large device lengths. A Shortcuts-to-adiabaticity (STA) protocol is employed to optimize the adiabatic taper profile in all-fibre photonic lanterns. The method tailors adiabatic propagation of light in the system by appropriately correcting the local slope of the taper profile. A quantifiable measure of adiabaticity is established, based on the adiabaticity criterion. This measure relates inversely to the device length and is a useful parameter in taper optimization. We apply the protocol to reported photonic lantern devices to obtain optimal adiabatic taper profiles having shorter device lengths. The optimized taper profile refers to that taper profile which corresponds to the minimum local inter-modal coupling at every point along the quasi-adiabatic transition for a given device length. While optimizing the adiabatic transition by minimizing inter-modal coupling is the basic aim of this work, length optimization is an extremely useful by-product. This procedure can be used to either reduce the device length or to reduce the mode-coupling losses or both. This study analyses reported three and six-core mode selective photonic lanterns as examples. We also discuss ways to make the optimum profiles practically realizable.

We investigate the monolithicintegration of RF antennas onto a silicon-based integrated microwave photonics (IMWP) chip for short-range millimeter-wave (mmW) communication. The unification of antenna with photonic integrated circuits (PICs) reduces system loss for high data rate communication by eliminating parasitic interconnects. This integration of electronics (antenna) with photonics will be a key milestone leading to increased bandwidth capability and ubiquitous wireless links for emerging applications such as 5G, Internet of Things (IoT), autonomous vehicles, high data rate point-to-point communication, and wireless sensors. Through simulation above 20 GHz, we compare the transmission of three on-chip antenna structures designed in a commercial silicon photonics (SiPh) process and consider them for both inter and intra-chip communication. Results provide insight on the transmission gain variations relative to the antenna orientation from their distinct radiation pattern. The folded monopole structure provides superior gain, smaller footprint with layout flexibility, and good transmission spectrum. The analysis supports the idea of a monolithic mmW transmitter integrated with on-chip antennas on IMWP chip.

This paper proposes a novel refractive index profile design based on few-mode fibers (FMFs) which can support 4 linear polarization (LP) modes. We first present a FMF whose core is dually assisted by a nano-hole (NH) and a high-index-ring (HIR), and then substitute the dual assistance by an innovative graded concave HIR (GC-HIR) assisted structure. Using the finite element method (FEM), the parameters of the NH-HIR and GC-HIR optical fiber are adjusted to investigate their respective minimum effective refractive index difference (minΔneff), which is 2.012 × 10−3 for the former, and 2.532 × 10−3 for the latter. Both optical fibers have a significant improvement on the crosstalk suppression effect, and the GC-HIR optical fiber is even better. The proposed GC-HIR FMF with special refractive index profile has potential application prospects in mode division multiplexing (MDM) optical fiber communication system, and can provide theoretical foundation for the design and analysis of subsequent optical fibers and key components.

In this work, the design and fabrication of a Cu/p-Si/Pt Schottky photodetector with a simple structure is investigated. The mechanism of electron flow is explained using internal photoemission theory, which is further applied to make the fabricated devices reach a high responsivity of 0.542 mA/W at 0–V bias. The investigation revealed that the rapid thermal annealing process could significantly influence the device characteristics. Variations in Schottky barrier height and series resistance of the photodetectors were also analyzed and correlated with the device responsivity. With proper conditions to improve the Pt/Si ohmic contact, the device performance can be enhanced.

Photonics-assisted frequency conversion based on cascaded modulators is an effective way to satisfy the requirements of distributed antenna array applications. A filter-free photonic image-rejection down-converter with immunity to dispersion-induced power fading is proposed and demonstrated. The radio frequency (RF) signal from the distributed antenna unit is injected into a dual-drive Mach–Zehnder modulator (DDMZM) through an electrical 90° hybrid coupler (HC), and a single-sideband (SSB) signal is realized. It is then transmitted to the center office by an optical fiber link. At the center office, the modulated RF signal is injected into a dual-polarization dual-parallel MZM (DP-DPMZM) after a polarization controller (PC). Afterwards, an LO signal remodulates it through the Y-DPMZM, and carrier-suppressed SSB modulation is fulfilled via another electrical 90° HC. After the power splitting, quadrature I and Q IF signals can be obtained by a photonics-based continuously adjustable phase shifter. Through a combination of the I/Q IF signals with a low-frequency electrical 90° HC, a photonics image-rejection down-converter based on phase cancellation is realized. Moreover, no optical filter is required; thus, the image-rejection down-converter can work with a large bandwidth. The proposed filter-free photonic image-rejection down-converter is theoretically analyzed and experimentally verified.

Two new photonics-based microwave frequency translators are presented. They are based on Serrodyne modulation to frequency translate an optical carrier, which beats with a microwave signal sideband at a photodetector to generate a frequency translated microwave signal. The proposed frequency translators have a simple structure, a wide bandwidth and a large spurious signal suppression ratio. Experimental results are presented for the novel structures, which demonstrate the realisation of microwave signal frequency translation with >38 dB spurious signal suppression over a wide microwave signal frequency range of 2 to 18 GHz and with >35 dB spurious signal suppression for a translation rate of 500 Hz to 3 MHz. Frequency translation of an 80 MHz bandwidth frequency modulated continuous wave signal at 5.88 GHz frequency with >34 dB spurious signal suppression is also demonstrated.

The scattering from air–glass interfaces within solid-core polarization-maintaining photonic crystal fiber (PM–PCF) will increase the fiber attenuation coefficient, which may lead to high transmission loss. Therefore, it is necessary to describe scattering properties to guide research into reducing fiber loss. In this paper, the loss resulting from roughness scattering at multi-hole interfaces within PM–PCF was theoretically and experimentally analyzed. A PM–PCF scattering model was established to explore the scattering distribution. On the other hand, a fully automatic testing device was built to enable the measurement of a three-dimensional scattering sphere. Simulations were in good agreement with experimental measurements. Moreover, this new proposed measurement method could apply to other PCFs and it will be a useful tool for further scattering research.

Polarizing beamsplitters have numerous applications in optical systems, such as systems for freeform surface metrology. They are classically manufactured from birefringent materials or with stacks of dielectric coatings. We present a binary subwavelength-structured form-birefringent diffraction grating, which acts as a polarizing beamsplitter for a wide range of incidence angles −30∘…+30∘. We refine the general design method for such hybrid gratings. We furthermore demonstrate the manufacturing steps with Soft-UV-Nanoimprint-Lithography, as well as the experimental verification, that the structure reliably acts as a polarizing beamsplitter. The experimental results show a contrast in efficiency for TE- and TM-polarization of up to 1:18 in the first order, and 34:1 in the zeroth order. The grating potentially enables us to realize integrated compact optical measurement systems, such as common-path interferometers.

Vector beams, non-separable in spatial mode and polarisation, have emerged as enabling tools in many diverse applications, from communication to imaging. This applicability has been achieved by sophisticated laser designs controlling the spin and orbital angular momentum, but so far is restricted to only two-dimensional states. Here we demonstrate the first vectorially structured light created and fully controlled in eight dimensions, a new state-of-the-art. We externally modulate our beam to control, for the first time, the complete set of classical Greenberger–Horne–Zeilinger (GHZ) states in paraxial structured light beams, in analogy with high-dimensional multi-partite quantum entangled states, and introduce a new tomography method to verify their fidelity. Our complete theoretical framework reveals a rich parameter space for further extending the dimensionality and degrees of freedom, opening new pathways for vectorially structured light in the classical and quantum regimes.

Optical tweezers and associated manipulation tools in the far field have had a major impact on scientific and engineering research by offering precise manipulation of small objects. More recently, the possibility of performing manipulation with surface plasmons has opened opportunities not feasible with conventional far-field optical methods. The use of surface plasmon techniques enables excitation of hotspots much smaller than the free-space wavelength; with this confinement, the plasmonic field facilitates trapping of various nanostructures and materials with higher precision. The successful manipulation of small particles has fostered numerous and expanding applications. In this paper, we review the principles of and developments in plasmonic tweezers techniques, including both nanostructure-assisted platforms and structureless systems. Construction methods and evaluation criteria of the techniques are presented, aiming to provide a guide for the design and optimization of the systems. The most common novel applications of plasmonic tweezers, namely, sorting and transport, sensing and imaging, and especially those in a biological context, are critically discussed. Finally, we consider the future of the development and new potential applications of this technique and discuss prospects for its impact on science., Optical manipulation: plasmonic tweezers Plasmonic tweezers exploit sub-wavelength confinement of light to allow trapping and manipulation of small particles with far greater precision than usual. Yuquan Zhang and coworkers from Shenzhen University in China and Delft University of Technology in The Netherlands have now reviewed the principles of operation, benefits and potential applications of such tweezers. They document the popular designs of plasmonic nanostructures that have been used to create tweezers to date and the theories behind the generation of surface plasmon polaritons and the forces that they induce. They also discuss the opportunities for improving performance of the tweezers in the future and their applications in the areas of manipulation, sorting, characterization and sensing of objects, especially biological entities such as viruses, DNA, biomolecules and cells.

Self-homodyne optical orthogonal frequency division multiplexing (OFDM) transmission system is a variant of self-coherent systems with a relaxed laser linewidth requirement as opposed to a full coherent system. The system is designed by transmitting a carrier together with the subcarriers, ensuring a strong phase-correlation between them at a receiver compared to the coherent system where only the subcarriers are transmitted. Despite the strong phase-correlation, the laser phase noise (PN) can still degrade the self-homodyne system performance due to the interaction of the PN with a chromatic dispersion (CD) induces a phase-modulation to intensity-modulation (PM-to-IM) conversion noise which cannot be canceled using a balanced-receiver. This imposes a high noise pedestal underneath each subcarrier, with the highest pedestal's peak imposed beneath the subcarriers that are farthest away from the carrier. This in turn produces a phase-decorrelation between the carrier and subcarriers which degrades the Q-factor between the lowest and highest subcarrier frequencies. In this work, the effect of the PM-to-IM conversion noise is reduced for the transmission of up to 174 Gb/s using a simple delay-line assigned to realign the phase-decorrelation of the subcarriers. With this technique, the subcarriers Q-degradation can be improved and the total transmission length can be tripled with Q-improvements of 5.4, 5.3, and 5-dB for 16-quadrature amplitude modulation (QAM) over 1360 km, 32- QAM over 800 km, and 64-QAM over 480 km, respectively, using 10-MHz LW with a 15-GHz total signal bandwidth. For 29 GHz signal bandwidth, the phase-walk-off of the high frequency subcarrier becomes more severe where the introduced delay can increase the transmission length by 2.5 times than without the delay, which increased the signal tolerance to the conversion noise.