Building shadow detection in satellite images is still considered a significant challenge in smart city urban planning. Shadows cast by tall buildings and other structures frequently obscure critical details, leading to pricey errors when these images are used in smart city urban geographic information systems. In this research, we propose a novel convolution-based algorithm for effective detection and minimization of buildings’ shadows. The proposed approach iteratively applies a set of operations. First, we split the patch into successive sub-patches. Second, we mix every subsequent corrected and uncorrected $N / 2 \times N$ patches together into a new rebuilt patch. This mathematically implements a convolution processing function to the image sub-patches. For instance, an N pixel width filter is applied on the rebuilt patch, in order to simultaneously detect and correct/minimize its specific shading. Once all the patches are iteratively covered/processed, the whole corrected image is reconstructed. The proposed algorithm is applied to satellite images from Google Earth and the obtained results are presented with respect to the translation patch size. The performance is evaluated in terms of quantitative metrics, including Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Method (SSIM), and processing time. Additionally, histogram analysis of the input and output images is performed to assess changes in luminance distribution and to visually confirm the reduction of shadow artifacts. The proposed method demonstrates promising results for improving the quality of satellite imagery used in urban analysis.

The purpose of this study is to propose a deep learning (DL) approach for the analysis of CT images aiming to assist in the diagnosis of Sjogren's syndrome (SS), a chronic autoimmune disease characterized by exocrine gland inflammation. A dataset consisting of 225 CT images obtained from 115 patients diagnosed with Sjögren's syndrome was employed for this study. To enhance the model's generalizability and robustness, the images underwent a preprocessing and augmentation pipeline. Then a DL model was trained, based on a convolutional neural network (CNN) architecture in order to classify the images whether they correspond to SS or healthy patients. The proposed model achieved an overall accuracy of 99.0%, with a sensitivity of 98.57% and a specificity of 99.45%.

Non‐negativity constraints arise naturally in many applications such as medical and astronomical imaging. These constraints have been recently exploited in the optical communication field where a projected parallel interference cancelation detector has been developed within the context of cancelling multi‐access interference in upstream on‐off‐keying optical code division multiple access passive optical networks; the latter possess the property that the transmitted data symbols are non‐negative. The authors build upon these results and propose a new parallel interference cancellation structure with better features and improved performance. This detector is characterised by a multiplicative update equation and it exhibits a number of unique and desirable features such as stability and smooth convergence behaviour even for highly loaded systems. Up to our knowledge, this structure has not been proposed before either in optical or in wireless communication field. Simulation results are promising and further improvements are possible.

Antennas designed with nano scale technologies, at optical frequencies, will be a corner stone in next generation nano communication links and networks. These optical antennas, operating in the THz regime of electromagnetic spectrum, will be applicable to fields including biomedical, environmental, military, and civilian communications. In this paper, authors propose and explore the potential benefits of designing a hexagonal dielectric loaded nantenna (HDLN) at a center frequency of 193.5 THz using CST Microwave Studio. The nantenna consists of Silver `Ag' as partial ground plane, a top and bottom `SiO2' substrate and a `Si' hexagon as dielectric fed by a `Ag' nanostrip transmission line. The simulated nantenna achieves a wide impedance bandwidth of 3.7% from 190.9 THz to 198.1 THz and an end-fire directivity of 8 dBi, covering all the standard optical transmission window at the ITU-T optical communication 1550 nm C-band.

Optical code division multiple access (OCDMA) is a promising candidate for next generation passive optical networks (NG‐PON). OCDMA‐PON can potentially provide all customers with a Gb/s‐class BW upstream with inherent flexibility. Unfortunately OCDMA suffers from multiple access interference (MAI) and various detection noises. In this study, the authors consider developing efficient interference cancellation detection under mixed Poisson–Gaussian noise. The latter is more realistic than considering Gaussian or Poisson noise alone. The authors first start by developing a maximum likelihood framework of the detection process under Gaussian, Poisson and Poisson–Gaussian noises, respectively. Then, the authors develop the proposed interference cancellation detector for the Poisson–Gaussian noise case after deriving the conventional expectation‐maximisation (EM) detector for the Poisson noise case. Finally, the authors simulate the proposed detector and compare it to the projected parallel interference cancellation, EM and other detectors to validate its superiority and enhanced performance.

Optical code division multiple access (OCDMA) is one of the emerging technologies for next generation passive optical networks that can offer customers a Gb/s‐class experience in the upstream. However, OCDMA suffers from multiple access interference (MAI) that significantly reduces the capacity of the system. To mitigate MAI, three novel interference cancellation (IC) techniques have been proposed for incoherent direct sequence OCDMA systems that make use of some prior information to enhance their performance. Some of the IC structures exploit the non‐negativity of the solution, while others exploit in addition to the non‐negativity information the noise variance information. The proposed IC detectors outperform the conventional correlation receiver, the decorrelator detector, the linear parallel/successive interference cancellation detectors and even the linear minimum mean square error detector.

In this paper, a network fault management and protection system for the ring-and-spur long-reach passive optical network (LR-PON) is proposed. We exploit an adapted, enhanced performance, and inexpensive passive optical components in the field and electronic switches in the central office (CO). Our system allows detecting and localizing not only faulty segments but also faulty nodes, hence alleviating the false alarm probability encountered in previous systems. We show that using ring duplication protection in LR-PON can save half the cost compared to full duplication protection with relatively high reliability performance (99.972%). We describe the implementation strategy of our system in several well known metro network topologies including: (1) single ring, (2) double ring and (3) double fiber pair based ring. The architecture of the remote nodes and the central office is described in addition to the appropriate placement of the passive monitoring devices. We derive an expression for the upper bound notification and recovery times. Moreover, we found that our system can recover from a fault in about 0.5ms as an upper bound.

Several centralized algorithms have been proposed for bandwidth-allocation in passive optical networks (PONs); making the optical line terminal (OLT) in the central office the intelligent device that arbitrates time-division access to the shared upstream channel. When the distance between the OLT and optical network units (ONUs) is extended from 20 km to 100 km and beyond, as suggested by next generation long-reach PONs, it becomes difficult for centralized algorithms to maintain their performance and to support service differentiation for real-time applications. This is because these algorithms are based on bandwidth negotiation messages frequently exchanged between the OLT and ONUs, which become seriously delayed, thereby delaying packet transmissions and causing the performance to degrade. Decentralized schemes, on the other hand, are independent of the OLT distance and can perform better with such extended reach. In this paper, we introduce and enhance the performance of a decentralized scheme for the emerging LR-PON. Simulation results show that the proposed scheme can significantly reduce upstream packet delays below those of centralized algorithms by 80% while keeping a high throughput.

A novel ring encoder for passive optical network (PON) is proposed and analyzed in term of SNR and probability of false alarm (PFA). The encoder exploits a fiber ring and one Bragg grating to produce a multi- level periodic code. We obtain an SNR of 10 dB for 256 customers in 10ms measurement time with 20km traditional PON. For 100km long reach PON (LR-PON), we obtain an SNR of 10dB for 64 customers in very high 1.7 minutes measurement time. We also apply Neyman-Pearson testing to the receiver and we investigate how the network size affects the operational expenses of our monitoring system. We illustrate the receiver operating characteristics (ROCs) of the system showing the tradeoff between the detection and false alarm probabilities. We show that 95% detection probability (PD) for 128 traditional PON customers can be achieved with 0.006 false alarm probability (PFA) in 2ms measurement time which is 50 times smaller than PFA when averaging is not used.

We analyze the performance of fiber fault monitoring of a PON using a centralized, passive optical coding (OC) system. We develop an expression for the detected monitoring signal, study its statistics, and contrast our OC monitoring system with standard optical code division multiplexing (OCDM) data communication. We derive a new closed form lower bound expression for the interference probability, and use this to find the signal-to-interference ratio (SIR). A service provider cannot control the physical layout of homes in a coverage area; measuring performance for one network layout would be insufficient to test our proposed monitoring system. Client geographic distribution has a significant impact on the SIR. We consider five different PON geographical distributions and study their effect on OC monitoring performance. Our results show that SIR is sufficient to successfully monitor the network. In addition, we find that the uniform radial (UR) distribution, an analytically tractable distribution, gives good performance estimation and can therefore be a useful tool in characterizing performance in terms of both SIR and signal-to-noise ratio (SNR).

We evaluate the theoretical performance of recently proposed optical coding (OC) technology for fiber fault monitoring of a PON through the signal-to-noise ratio (SNR), the signal-to-noise-plus-interference ratio (SNIR), and the falsealarm probability. First, we develop a mathematical model and expressions for the detected monitoring signals considering a square law detector and using realistic parameters. Second, we address the effect of the transmitted pulse power, network size and light source coherence on the performance of both one-dimensional (1D) and two-dimensional (2D) OC monitoring systems. We show that the transmitted pulse width can be optimized to trade-off the interference and the detection noises. We give simple analytic equations for this optimal pulse width as a function of network parameters. Both 1D and 2D coding schemes are considered. We find that, under perfect dispersion compensation, an incoherent source performs better than lasers for 1D coding. In addition, 2D coding using lasers offer very good performance and supports networks up to 128 customers with SNIR¿10dB; a promising candidate for future high capacity PON. Finally, we apply Neyman-Pearson testing to the receiver of our monitoring system and investigate how coding and network size affect the operational expenses (OPEX) of our monitoring system.

In this paper we investigate both experimentally and via simulation the monitoring of fiber link quality in a PON using optical coding technology. We use a new, simple and cost-effective coding scheme well adapted to the monitoring application, namely periodic coding. We discuss design issues for periodic coding and the optimal detection criteria. We develop a reduced complexity maximum-likelihood sequence estimation (RC-MLSE) algorithm for monitoring. We conduct experiments to validate our detection algorithm using four periodic encoders that we designed and fabricated. These encoders were placed at roughly equal distances (within a meter) to represent a partial return from a very high density (geographically) PON. The measured data were fed into our detection algorithm and the exact location of each subscriber was correctly identified. Using the experimental data for the encoder's impulse responses, we completed Monte-Carlo simulations for more realistic PON geographical distributions with randomly located customers. Error-free detection is achieved. We also highlight the importance of averaging to remedy the power/loss budget limitations in our monitoring system to support higher network sizes.

We propose fast optical frequency-hop code division multiple access (FH-CDMA) for high bandwidth local area networks. Encoding and decoding are achieved by tunable fiber Bragg gratings. Frequency hopping offers many advantages compared to the previously proposed optical CDMA multiple access techniques. The simultaneous utilization of the time and frequency domains offers notable flexibility in the selection of codes, however code families previously developed for radio frequency (RF) communications are not directly applicable to an optical FH-CDMA system. We propose codes to meet the special constraints imposed by our encoding device and present theoretical and simulation results for their performance.

We address the problem of suppression of a digital narrow-band interferer in direct-sequence spread spectrum (DSSS) communications. We focus on the adaptive suppression method proposed by Honig, Madhow and Verdti (see IEEE Trans. Inform. Theory, vol.41, p.944-960, 1995) for wide-band interference, applying it to a narrow-band interferer. We identify the eigenspaces of the system dynamics to analyze the convergence of the adaptive version of the minimum mean square error (MMSE) algorithm for this application. Using this subspace approach we are able to: (1) significantly decrease the convergence times via a new constraint on the step size in adaptation; (2) introduce a simple parameterization of the mean output energy (MOE) and signal-to-interference ratio (SIR) to compare performance of various receivers; and (3) identify modes of operation where the algorithm will cease to effectively cancel interference. We propose a new adaptive receiver that avoids the convergence anomalies identified, while capitalizing on the new step size for faster convergence. Simulation results to support theoretical results are presented.