We show that general-form optical cavities are able to perform the temporal differentiation of optical signals. Analytical relationships to account for the scattering losses for such a cavity's characteristics are deduced on the basis of temporal coupled-mode theory. A compact nanocavity-aided differentiator based on a ridge photonic crystal waveguide is designed.

A complex spectral–spatial classification scheme for hyperspectral images is proposed and explored. The key feature of method is using widespread and simple enough algorithms while having high precision. The method combines the results of a pixel wise support vector machine classification and the segmentation map obtained by partitional clustering using majority voting. The k-means++ clusterization algorithm is used for image clustering. Principal component analysis is used to prevent redundant processing of similar data. The proposed method provides improved precision and speed of hyperspectral data classification.

In this paper, we propose and numerically investigate an all-optical temporal integrator based on a photonic crystal cavity. We show that an array of photonic crystal cavities enables high-order temporal integration. The effect of the value of the cavity's free spectral range on the accuracy of the integration is considered. The influence of the coupling coefficients in the resonator array on the integration accuracy is demonstrated. A compact integrator based on a photonic crystal nanobeam cavity is designed, which allows high-precision integration of optical pulses of subpicosecond duration.

Analysis of two streaming frameworks: Apache Storm and IBM InfoSphere Streams was performed in solving a multiple object detection task. The analysis focused on two parameters: throughput and 95th percentile of image processing delay. Faces were chosen as the objects to be detected. Profiling was held under CentOS operating systems running on a five node cluster. Face detection was performed using an OpenCV cascade classifier. First architectures and the experiment description were covered. Final suggestions on the applicability of the two systems were made in the concluding section of the article. Apache Storm demonstrated a scalability advantage over IBM InfoSphere Streams in the experiment conducted. It was confirmed that the system based on Apache Storm was able to operate on FullHD video in real-time, achieving throughput of 24 images per second on the hardware used.

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A two-fold way to increase the sensitivity of the optical sensor is proposed and numerically investigated. The sensor based on the coupled photonic crystal cavities is calculated as an illustration of the proposed approach. The correspondence between analytical and numerical modeling approach is demonstrated.

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