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The derivation of the probability density of irradiance for the received electromagnetic wave propagating through random inhomogeneities has applications in many diverse fields, such as optical wireless communications, radar, and imaging systems, to name few. The conventional approach in this regard is to combine distribution models, with each being found valid under different conditions, in a modulation process, e.g., the extended Rytov theory. However, in these techniques, the nature of the physical processes responsible for the randomness is not considered directly. Moreover, it is not clear how the model parameters are related to the physical environment. Recent research studies found that in random media, such as underwater, the exact physical processes in effect can significantly alter the distribution of the received signal intensity. In this article, a novel intensity distribution model is derived based on Rytov theory of propagation through weak turbulence. The physical parameters of the medium are directly included into the model parameters. Therefore, the resultant model is general enough to describe different physical environments. The utility of the model is validated by studying the effect of the medium parameters on the distribution through simulations. [ABSTRACT FROM AUTHOR]

Summary: Numerous physical mediums can be modelled as turbulent magnetized plasma, for example, the solar corona, and the ionosphere. Scintillation effects on the intensity of electromagnetic beam wave propagating through magnetized plasma necessitate the introduction of a statistical distribution valid over a large range of scintillation conditions, and incorporating the plasma physical properties. Under some simplifying assumptions, such a theoretical model can be derived based on the Rytov solution, the external magnetic field variation, and the space permeating plasma electron density variation. The resultant wave intensity distribution is compared with the Lognormal, Rician, and the Nakagami distributions for different scintillations conditions. The work presented in this paper is applicable to the analysis and design of optical wireless communication links through the ionosphere and deep space plasma. [ABSTRACT FROM AUTHOR]

Departing from the conventional view of the reasons for the behavior of living systems, this research presents a radical and unique view of that behavior, as the observed side effects of a hierarchical set of simple, continuous, and dynamic negative feedback control systems, by way of an experimental model implemented on a real-world autonomous robotic rover. Rather than generating specific output from input, the systems control their perceptual inputs by varying output. The variables controlled do not exist in the environment, but are entirely internal perceptions constructed as a result of the layout and connections of the neural architecture. As the underlying processes are independent of the domain, the architecture is universal and thus has significant implications not only for understanding natural living systems, but also for the development of robotics systems. The central process of perceptual control has the potential to unify the behavioral sciences and is proposed as the missing behavioral principle of Artificial Life. [ABSTRACT FROM AUTHOR]

The objective of this paper is to derive a model for the irradiance distribution of underwater optical waves propagation in the combined presence of turbulence and air bubbles. The proposed distribution is based on modelling the medium index of refraction as a shot noise process and using the Rytov solution to the stochastic wave equation. Since the oceanic turbulence spectrum is different than the atmospheric spectrum, recent studies show that the well-known probability density functions poorly describe optical wave propagation underwater in the combined presence of air bubbles and turbulence, and that a mixture of distributions is generally needed. This conclusion, however, does not follow from theoretical investigations. Moreover, the physical aspects of the phenomena, such as the bubble size distribution, are not included in these models, and as such may limit their applicability. The approach introduced in this paper allows for including the environment physical properties directly in to the medium index of refraction. In this paper, intensity distribution model is derived based on Rytov theory of propagation through weak turbulence. The physical processes in effect are directly included by assuming a shot noise index of refraction model. Using the beam propagation method combined with the random phase screen method, the derived distribution is validated by simulation over a large range of turbulence levels and shows excellent agreement with the simulation data. In particular, the qualitative aspect of two peak distribution is modelled by the proposed distribution. • A proposed approach for the intensity pdf of optical waves through random mediums. • The proposed approach incorporates the physical characteristics of the mediums. • Underwater optical waves in presence of turbulence and air bubbles is considered. • The model is verified through simulation of underwater turbulent environment. [ABSTRACT FROM AUTHOR]

Emerging technologies such as network function virtualization and software-defined networking (SDN) have made a phenomenal breakthrough in network management by introducing softwarization. The provision of assets to each virtualized network functions autonomously as well as efficiently and searching for an optimal pattern for traffic routing challenges are still under consideration. Unfortunately, the traditional methods for estimating the desired performance indicators are insufficient for a self-driven SDN. In the last decade, a combination of machine learning and cognitive techniques construct a knowledge plane (KP) for the Internet which introduces numerous benefits to networking, like automation and recommendation. Furthermore, the inclusion of KP to the conventional three planes SDN architectures recently has added another knowledge defined networking (KDN) architecture to drive an SDN autonomously. In this article, a self-driving system has been proposed based on KDN to achieve the selection of an optimal path for the deployment of service function chaining (SFC) and reactive traffic routing among the edge clouds. Considering the limited resource of edge clouds, the proposed system also maintains a balance among edge cloud resources while orchestrating SFC resources. The graph neural network has been also applied in the proposed system to recognize the composite relationship concerning topology, traffic features, and routing patterns for accurate estimation of key performance indicators. The proposed system improves resource utilization efficiency for SFC deployment by 20%, maximum network throughput by 5%, and CPU load by 13%. [ABSTRACT FROM AUTHOR]

Abstract: A popular approach for detecting moving object regions in video sequences is the application of the background subtraction technique. According to this technique the background (reference) image is subtracted from the current image frame and the moving parts are detected by the selection of a suitable threshold. In this paper we present our work to discriminate the moving pixels of the generated difference images from the relatively stationary pixels through the use of three different threshold selection strategies, namely, (i) ‘3σ edit rule’, (ii) rule utilizing the Hampel identifier, and (iii) rule based on an ad hoc selection of threshold. Further, after segmentation a method of classification, based on a moving shadow search technique, previously developed by the authors, has been applied to segregate the moving shadow region from the actual moving object. The speed-up achieved through the use of the three aforementioned techniques on the core moving shadow search process, compared to that where no such process has been applied, has been documented. The final outcomes of applying the shadow detection technique after segmenting using each of the threshold selection strategies, one at a time, on some indoor video sequences have been demonstrated and comparison of the methods made. [Copyright &y& Elsevier]

Abstract: In the field of optical pattern recognition, there are a large number of filters that possess identification capabilities for certain kinds of input distortions. The resolution of the spectral components plays an important role in the overall processing time of a correlator that may employ such filters. In this paper, two different techniques are discussed: low pass phase filtering and high pass phase filtering. This is achieved by binarizing the amplitude information which then allows certain frequencies to pass and others to be blocked. Their response to different kinds of input distortions is presented and the effect of phase quantisation is considered in detail. [Copyright &y& Elsevier]

Free space diffraction causes the spreading of the received energy at the receiver and thus reduces the signal-to-noise ratio. Bessel–Gauss (BG) beams are considered physically realizable beams, which are robust to free space diffraction over finite propagation distances. Non-diffraction beams have proved useful in many applications, such as optical wireless communications (OWC) and non-linear optics. However, in turbulence BG-beams do suffer from turbulence-induced diffraction. The extended Huygens–Fresnel principle is the main tool of analysis under the effect of strong turbulence. However, the extended Rytov theory (ERT) method provides expressions for the small- and large-scale turbulence-induced signal fluctuations and hence is particularly suitable for statistical channel modeling. In this work, application of the ERT to BG-beams propagating through turbulence is carried out. Closed-form expressions for the induced on-axis small- and large-scale log-irradiance variances are derived. The resultant index of scintillation is analyzed. Then, the error performance of OWC is investigated for BG-beams combined with intensity modulation, M-ary phase shift keying, polarization shift keying, and single-input-multiple-output systems. Significant performance gains are reported compared to Gaussian beams. [ABSTRACT FROM AUTHOR]

The article discusses robotics and artificial intelligence including the need for a perception-based control for the same. It discusses the engineering required in standard robotics such as robot arms and self-driving cars including kinematic computations, parametric knowledge and algorithms. It describes how the perceptual control theory eliminates the need for transfer functions in some robotic systems and overcomes the complexity problem associated with predictive modelling.

Abstract: Objectives: To determine whether texture analysis of non-contrast enhanced computed tomography (CT) images in apparently disease-free areas of the liver is altered by the presence of extra- and intra-hepatic malignancy in colorectal cancer patients. Materials and methods: Hepatic attenuation and texture were assessed from non-contrast enhanced CT in three groups of colorectal cancer patients: (A) 15 controls with no malignancy; (B) nine patients with extra-hepatic malignancy but no liver involvement; (C) eight patients with hepatic metastases. Regions of interest were manually constructed only over apparently normal areas of liver tissue excluding major blood vessels and areas of intra-hepatic fat, which may otherwise alter CT texture irrespective of the presence of malignancy. Texture was analysed on unfiltered images and following band-pass image filtration to highlight image features at different spatial frequencies (fine: 2pixels/1.68mm in width, medium: 6pixels/5.04mm and coarse: 12pixels/10.08mm). The relative contributions made to the image by features at two different spatial frequencies were expressed as filter ratios (fine/medium, fine/coarse and medium/coarse). Texture was quantified as mean grey-level intensity, entropy and uniformity. Results: Texture was not altered on unfiltered images whereas relative texture analysis following image filtration identified differences in fine to medium texture ratios in apparently disease-free areas of the liver in patients with hepatic metastases as compared to patients with no tumour (entropy, p =0.0257) and patients with extra-hepatic disease (uniformity, p =0.0143). Conclusions: Relative texture analysis of unenhanced hepatic CT can reveal changes in apparently disease-free areas of the liver that have previously required more complex perfusion measurements for detection. [Copyright &y& Elsevier]

Abstract: Achieving phase only modulation from a spatial light modulator (SLM) is useful for many optical processing tasks. In this paper, we demonstrate a simple method of decoupling phase and amplitude modulation in a twisted nematic liquid crystal (TNLC) SLM using a double pass technique. A Jones calculus model is developed which matches our experimental data. [Copyright &y& Elsevier]

To solve the problems of occlusion and fast motion of small targets in unmanned aerial vehicle target tracking, an adaptive algorithm that fuses the improved color histogram tracking response and the correlation filter tracking response based on multichannel histogram of oriented gradient features is proposed to realize small target tracking with high accuracy. The state judgment index is used to determine whether the target is in a fast motion or an occlusion state. In the fast motion state, the search area is enlarged, and the color optimal model that suppresses the suspected area is used for rough detection. Then, redetection in the location of multiple peaks in the rough detection response is carried out using the correlation filter to accurately locate the target. In an occlusion state, the model stops updating, the search area is expanded, and the current color model is used for rough detection. Then, redetection in the place of multiple peaks in the rough detection response is carried out using the correlation filter to accurately locate the target. Experimental results show that the proposed method can track small targets accurately. The frame rate of the proposed method is 40.23 frames/s, indicating usable real-time performance. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. [DOI: 10 .1117/1.JEI.27.5.053010] [ABSTRACT FROM AUTHOR]

Several power allocation algorithms for cooperative relay networks are presented in the literature. These contributions assume perfect channel knowledge and capacity achieving codes. However in practice, obtaining the channel state information at a relay or at the destination is an estimation problem and can generally not be error free. The investigation of the power allocation mechanism in a wireless network due to channel imperfections is important because it can severely degrade its performance regarding throughput and bit error rate. In this paper, the impact of imperfect channel state information on the power allocation of an adaptive relay network is investigated. Moreover, a framework including Automatic Repeat reQuest (ARQ) mechanism is provided to make the power allocation mechanism robust against these channel imperfections. For this framework, the end-to-end SNR is calculated considering imperfect channel knowledge using ARQ analytically. The goal is to emphasize the impact of imperfect channel knowledge on the power allocation mechanism. In this paper, the simulation results illustrate the impact of channel uncertainties on the average outage probability, throughput, and consumed sum power for different qualities of channel estimation. It is shown that the presented framework with ARQ is extremely robust against the channel imperfections. [ABSTRACT FROM AUTHOR]

A solution was sought for control of Spodoptera exempta in cereal crops. The proposed solution enhanced a previous scheme since it provided control of the pest eggs and larvae and improved the quality of crop products by replacing pesticides. The scheme consists of a surveillance and monitoring system to activate a measured response to pest invasion. In the control phase naturally beneficial insects (NBIs) were deployed via an unmanned aerial vehicle (UAV) system to control the pest population; parasite egg wasps ( Trichogramma ) were combined with a larval parasite Diptera ( Tachinidae ) to achieve greater control of the life cycle stages of the African Armyworm – Spodoptera exempta . [ABSTRACT FROM AUTHOR]

The image transformation with respect to mammalian retina-based sensor geometry enables us to resolve some major difficulties in object recognition. Logarithmic mapping is a mathematical transform that converts scale and angular variations to image shifts which helps in classifying target objects correctly. The primary issues dealt with in the design of correlation filters include the ability to suppress clutter and noise, easy detection of the correlation peaks and distortion tolerance. The correlation pattern recognition concept is applied for developing filters that provide invariance to distortions by adopting a suitable training mechanism. But, a separate training requirement for each distortion type is a drawback in correlation filters. By joining a recent variant of correlation filters, i.e. the Extended Maximum Average Correlation Height Filter with the strengths of logarithmic translation, we get a supplementary advantage which is useful in most of the recognition applications. The proposed combination yields a design which can manage multiple distortions in a single training instance with pronounced detection results against complex input scenes. [ABSTRACT FROM AUTHOR]

A real-time system for the detection and tracking of moving objects that becomes stationary in a restricted zone. A new pixel classification method based on the segmentation history image is used to identify stationary objects in the scene. These objects are then tracked using a novel adaptive edge orientation-based tracking method. Experimental results have shown that the tracking technique gives more than a 95% detection success rate, even if objects are partially occluded. The tracking results, together with the historic edge maps, are analysed to remove objects that are no longer stationary or are falsely identified as foreground regions because of sudden changes in the illumination conditions. The technique has been tested on over 7 h of video recorded at different locations and time of day, both outdoors and indoors. The results obtained are compared with other available state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Abstract: The Difference of Gaussian (DOG) filter is widely used in optics and image processing as, among other things, an edge detection and correlation filter. It has important biological applications and appears to be part of the mammalian vision system. In this paper we analyse the filter and provide details of the full width half maximum, bandwidth and frequency response in order to aid the full characterisation of its performance. [Copyright &y& Elsevier]

An article discussing the existence and vocalization of diphthongs or gliding vowels in the Sindhi language is presented. The author examines acoustic samples taken from males in the Sindh region of Pakistan, analyzing the vocal samples and noting the formant frequencies of the speakers. Noting the unique phonetic characteristics of sequential vowels in the Sindhi language, the author cites ethnographic and historical influences on the language, such as Islam and the geographic location, as important factors in the development of Sindhi. The methodology of the study, including the analysis of isolated diphthong words and diphthong words within carrier sentences, are also addressed.

Objectives: Three-dimensional (3-D) selective- and relative-scale texture analysis (TA) was applied to structural magnetic resonance (MR) brain images to quantify the presence of grey-matter (GM) and white-matter (WM) textural abnormalities associated with schizophrenia.Materials and Methods: Brain TA comprised volume filtration using the Laplacian of Gaussian filter to highlight fine, medium and coarse textures within GM and WM, followed by texture quantification. Relative TA (e.g. ratio of fine to medium) was also computed. T1-weighted MR whole-brain images from 32 participants with diagnosis of schizophrenia (n = 10) and healthy controls (n = 22) were examined. Five patients possessed marker alleles (SZ8) associated with schizophrenia on chromosome 8 in the pericentriolar material 1 gene while the remaining five had not inherited any of the alleles (SZ0).Results: Filtered fine GM texture (mean grey-level intensity; MGI) most significantly differentiated schizophrenic patients from controls (P = 0.0058; area under the receiver-operating characteristic curve = 0.809, sensitivity = 90%, specificity = 70%). WM measurements did not distinguish the two groups. Filtered GM and WM textures (MGI) correlated with total GM and WM volume respectively. Medium-to-coarse GM entropy distinguished SZ0 from controls (P = 0.0069) while measures from SZ8 were intermediate between the two.Conclusions: 3-D TA of brain MR enables detection of subtle distributed morphological features associated with schizophrenia, determined partly by susceptibility genes. [ABSTRACT FROM AUTHOR]

Two optical lenses are used to compose a surface position measuring system. A measurand is positioned near the front focal point of the first lens. At the output end of the other lens, a beam splitter is used to split the beam into two paths. One photodetector is positioned before the focal point of the lens in one path and another after the focal point in the other so that the intensities falling onto the two detectors can be adjusted to be equal when the first lens is in focus. This device provides a compact and high-accuracy surface sensor. In this paper, the design and experimental study of the sensor system is described. It is shown that such a sensor embodiment can lead to a resolution of 1 μm. [Copyright &y& Elsevier]

Fast Internet Protocol Version 4 (IPv4) lookup is one of the key challenges that have always been faced with growing internet speed. Next generation networks promise hundreds of gigabit communication bandwidths. To support such high data rates, core networking devices require very fast IPv4 lookup for incoming packets to sustain their functionality. Researchers from academia and industry have contributed widely towards this problem, presenting numerous techniques and algorithms to improve lookup times. In this paper, a bit vector-based IP lookup engine is presented that implements parallel units to achieve 4.3 Billion Packets Per Second (BPPS) lookup speeds for 5 fields. Implementations are done using dual port Distributed RAM (DRAM) on state-of-the-art Xilinx Virtex 7 series Field Programmable Gate Arrays (FPGA). Post place and route results for different configurations showed that the proposed design consumes much less memory, facilitating multiple engines on a single chip whilst maintaining a very low overall power profile. [ABSTRACT FROM AUTHOR]