Double Modulation Research Articles

Simulation of Anti Reflecting Coating for Improving External Quantum Efficiency of Photovoltaic Cell

Due to a dramatic drop in solar module prices/watt peaks, photovoltaic (PV) electricity has become more concentrated over the last decade. Crystallized silicon (c-Si) solar cells have dominated the solar market since their creation, outperforming all other photovoltaic technologies. PV modules are frequently required to work in inclement weather. Outdoor photovoltaic performance is affected by a number of factors, including 1) solar radiation, 2) the shape of the absorbed solar spectrum, 3) ambient temperature, 4) location, 5) wind speed, and 6) aerosols. These parameters, on the other hand, are out of our hands. It does not prevent solar panels from becoming heated on hot days, which has a negative impact on their electrical performance and longevity. To protect the solar cell from various external variables, multiple layers are applied to solar cell modules, including EVA (Ethylene Vinyl Acetate), polyvinyl fluoride sheet (Tedlar), front solar glass, metal frame, and side water seal. One of the main causes of the absorber layer temperature in solar modules rising is this. For single-layer and multi-layer ARC designs, a range of materials are used in the ARC of solar modules. Instead of functioning as a radiative cooler, the ARC can be changed or simple tweaks can be made to improve absorption and lower the temperature of the solar module. Based on light and radiation properties, choose materials for SR-ARC design of solar cells and modules. The chosen material must have very low absorption between 300 and 1200 nm and emit between 8 and 13 m. The annual power generation of a 1kW system in India's complicated environment is determined with the aforesaid efficiency increases and temperature reductions. From a single layer c-Si solar module system, the double layer module of the 1kW system generates 54kWh. Furthermore, the cooling effect was calculated, with the failed component losing 80% of its initial efficiency by the end of 2014, but the two- and three-layer components reached this level by the end of 36. The dual layer SR-ARC coated module system will start producing single layer modules at the end of 26 or 36, with or without replacement.

Investigation of a social group assisted differential evolution for the optimal PV parameter extraction of standard and modified diode models

Parameter estimation of PV cells is essential to develop accurate simulation techniques, optimal control mechanisms, converter design optimization, maximize the efficiency of PV harvesting systems, improve the accuracy of monitoring systems etc. Advanced meta-heuristic algorithms for the optimal parameter estimation through the minimization of the disparity between the measured and estimated I-V data pairs have emerged as a powerful tool in this regard. Despite the efficacy of the meta-heuristics for the standard diode models, the optimization of modified diode models including the higher-order complex modified double and triple diode modules remains largely unexplored. Hence, an advanced hybrid meta-heuristic technique benefitting from the synergy of social group optimization and differential evolution known as social group assisted differential evolution (SGDE) is developed to achieve an enhanced balance of exploration and exploitation for the complex multi-modal landscapes of the modified diode models. Three experiments involving the minimization of the root mean square error for three commercial PV modules (KC200GT, Shell SQ85 and Shell ST40) based on the simulated I-V data followed by four experimental I-V curves of two solar cells (RTC France solar cell and PVM 752 GaAs thin-film cell) and two PV modules (Photowatt-PWP201 and STM6-40/36 PV modules) and the parameter optimization for two commercial modules (JAM72S01-380/PR and SUNCECO SEP300W PV modules) at varying levels of irradiance and temperature are investigated and extensively compared with fourteen other state-of-the-art meta-heuristic techniques. SGDE outperforms the competitor algorithms in terms of optimality, consistency and demonstrated greater robustness to local entrapment for the standard and modified diode models.

Generation of soft annular beams with high uniformity, low ring width increment, and a smooth edge.

In this paper, soft-edge toroidal amplitude filter (STAF) and soft-edge toroidal complex amplitude filter (STCAF) are designed according to the principle that soft-edge structures can eliminate diffraction. Based on the Mach-Zehnder interference principle, a double optical path compound interference modulation method that can generate soft annular beams is proposed by using STAF and STCAF. The 1/e2 radius and peak-to-average ratio (PAR) were used to evaluate the ring width and uniformity of the annular beam. Compared with the annular beams generated by STAF and hard-edge toroidal amplitude filter (HTAF), it can be found that the soft annular beam generated by this proposed method has the advantages of high uniformity, small ring width increment, and smooth edges. By analyzing the influence of the number and height of the sawtooth structures on the annular beam propagation performance, the relationship between the PAR and the structure parameters of the STAF was established. Moreover, three kinds of toroidal filters were designed by lithography processing, and an experimental system was built to generate the soft annular beam. In the experiment, the average value of the ring width increment of the soft annular beam is 0.0125, the PAR is less than 1.5, and the root mean square error of the PAR curve is 0.0865, which indicates that the soft annular beam maintains high uniformity during propagation.

Simulation of Anti Reflecting Coating for Improving External Quantum Efficiency of Photovoltaic Cell

Due to a dramatic drop in solar module prices/watt peaks, photovoltaic (PV) electricity has become more concentrated over the last decade. Crystallized silicon (c-Si) solar cells have dominated the solar market since their creation, outperforming all other photovoltaic technologies. PV modules are frequently required to work in inclement weather. Outdoor photovoltaic performance is affected by a number of factors, including 1) solar radiation, 2) the shape of the absorbed solar spectrum, 3) ambient temperature, 4) location, 5) wind speed, and 6) aerosols. These parameters, on the other hand, are out of our hands. It does not prevent solar panels from becoming heated on hot days, which has a negative impact on their electrical performance and longevity. To protect the solar cell from various external variables, multiple layers are applied to solar cell modules, including EVA (Ethylene Vinyl Acetate), polyvinyl fluoride sheet (Tedlar), front solar glass, metal frame, and side water seal. One of the main causes of the absorber layer temperature in solar modules rising is this. For single-layer and multi-layer ARC designs, a range of materials are used in the ARC of solar modules. Instead of functioning as a radiative cooler, the ARC can be changed or simple tweaks can be made to improve absorption and lower the temperature of the solar module. Based on light and radiation properties, choose materials for SR-ARC design of solar cells and modules. The chosen material must have very low absorption between 300 and 1200 nm and emit between 8 and 13 m. The annual power generation of a 1kW system in India's complicated environment is determined with the aforesaid efficiency increases and temperature reductions. From a single layer c-Si solar module system, the double layer module of the 1kW system generates 54kWh. Furthermore, the cooling effect was calculated, with the failed component losing 80% of its initial efficiency by the end of 2014, but the two- and three-layer components reached this level by the end of 36. The dual layer SR-ARC coated module system will start producing single layer modules at the end of 26 or 36, with or without replacement.

Simulation of Anti Reflecting Coating for Improving External Quantum Efficiency of Photovoltaic Cell

Due to a dramatic drop in solar module prices/watt peaks, photovoltaic (PV) electricity has become more concentrated over the last decade. Crystallized silicon (c-Si) solar cells have dominated the solar market since their creation, outperforming all other photovoltaic technologies. PV modules are frequently required to work in inclement weather. Outdoor photovoltaic performance is affected by a number of factors, including 1) solar radiation, 2) the shape of the absorbed solar spectrum, 3) ambient temperature, 4) location, 5) wind speed, and 6) aerosols. These parameters, on the other hand, are out of our hands. It does not prevent solar panels from becoming heated on hot days, which has a negative impact on their electrical performance and longevity. To protect the solar cell from various external variables, multiple layers are applied to solar cell modules, including EVA (Ethylene Vinyl Acetate), polyvinyl fluoride sheet (Tedlar), front solar glass, metal frame, and side water seal. One of the main causes of the absorber layer temperature in solar modules rising is this. For single-layer and multi-layer ARC designs, a range of materials are used in the ARC of solar modules. Instead of functioning as a radiative cooler, the ARC can be changed or simple tweaks can be made to improve absorption and lower the temperature of the solar module. Based on light and radiation properties, choose materials for SR-ARC design of solar cells and modules. The chosen material must have very low absorption between 300 and 1200 nm and emit between 8 and 13 m. The annual power generation of a 1kW system in India's complicated environment is determined with the aforesaid efficiency increases and temperature reductions. From a single layer c-Si solar module system, the double layer module of the 1kW system generates 54kWh. Furthermore, the cooling effect was calculated, with the failed component losing 80% of its initial efficiency by the end of 2014, but the two- and three-layer components reached this level by the end of 36. The dual layer SR-ARC coated module system will start producing single layer modules at the end of 26 or 36, with or without replacement.

Optimal parameter estimation without consuming raw keys for continuous-variable quantum key distribution

In conventional continuous-variable quantum key distribution using single Gaussian modulation (SGM), it is usually necessary to reveal a portion of the raw keys to estimate the parameters of the quantum channel. In the double Gaussian modulation (DGM) protocol, parameter estimation is performed without consuming raw keys at the cost of having the estimated result be affected by more aggregated noise than the SGM protocol. In this paper, inspired by the idea of performing parameter estimation after error correction, we propose two improved DGM protocols, i.e., the Gaussian dense modulation protocol, and the Gaussian separate modulation protocol, to eliminate this cost. The two DGM protocols perform parameter estimation twice, once before and once after error correction, so that all raw keys can be used for both parameter estimation and key extraction. Therefore, when finite-size effects are considered, the optimal parameter estimation of the protocol is achieved.

Semi-supervised double attention guided assessment approach for remaining useful life of rotating machinery

Many data-driven methods attempt to derive key degradation features from vibration data. However, information consistency and local semantics are not considered when minimizing feature distribution discrepancy in global adaptation learning, resulting in limitations. Meanwhile, the traditional convolution-based feature extractor is difficult to establish the global connection between features. To address the above issues, a semi-supervised double attention guided assessment approach (SDAGA) is proposed to evaluate the remaining useful life of rotating machinery. Specifically, a multi-level deformable convolution module is designed to establish global connections between features and further extract global information. Also, information consistency and multiscale semantics can be maintained by U-shaped sampling and double attention module in a semi-supervised domain adaptation, making it learn more robust invariant degradation features. Extensive experiments are conducted on public and experimental datasets to validate the effectiveness and superiority of SDAGA compared to state-of-the-art methods.

Construction of a Semantic Segmentation Network for the Overhead Catenary System Point Cloud Based on Multi-Scale Feature Fusion

Accurate semantic segmentation results of the overhead catenary system (OCS) are significant for OCS component extraction and geometric parameter detection. Actually, the scenes of OCS are complex, and the density of point cloud data obtained through Light Detection and Ranging (LiDAR) scanning is uneven due to the character difference of OCS components. However, due to the inconsistent component points, it is challenging to complete better semantic segmentation of the OCS point cloud with the existing deep learning methods. Therefore, this paper proposes a point cloud multi-scale feature fusion refinement structure neural network (PMFR-Net) for semantic segmentation of the OCS point cloud. The PMFR-Net includes a prediction module and a refinement module. The innovations of the prediction module include the double efficient channel attention module (DECA) and the serial hybrid domain attention (SHDA) structure. The point cloud refinement module (PCRM) is used as the refinement module of the network. DECA focuses on detail features; SHDA strengthens the connection of contextual semantic information; PCRM further refines the segmentation results of the prediction module. In addition, this paper created and released a new dataset of the OCS point cloud. Based on this dataset, the overall accuracy (OA), F1-score, and mean intersection over union (MIoU) of PMFR-Net reached 95.77%, 93.24%, and 87.62%, respectively. Compared with four state-of-the-art (SOTA) point cloud deep learning methods, the comparative experimental results showed that PMFR-Net achieved the highest accuracy and the shortest training time. At the same time, PMFR-Net segmentation performance on S3DIS public dataset is better than the other four SOTA segmentation methods. In addition, the effectiveness of DECA, SHDA structure, and PCRM was verified in the ablation experiment. The experimental results show that this network could be applied to practical applications.

Multiple target recognition and position identification circuit based on memristor

Traditional target recognition has low precision and the data processing is complicated when recognizing multiple targets. A multiple target recognition and position identification circuit based on memristor is designed in this paper, which can simultaneously realize the recognition for multiple targets with different shapes. The dual recognition is used in the designed recognition circuit, including position identification and size recognition, which will improve the recognition accuracy. Integral holding module and double threshold detection module with variable threshold based on memristor can flexibly construct the circuit according to different requirements, and the application range of the circuit is expanded. The signal processing module is designed in this paper to effectively filter out redundant targets and improve the reliability of the circuit. Different from the existing target recognition technologys, the multiple target recognition circuit based on memristor adopts the method of analog circuit to provide reference for the further development of target recognition.

MP04-12 EN-BLOC ENUCLEATION TECHNIQUE WITH EARLY APICAL RELEASE AND URINARY SPHINCTER PRESERVATION USING PULSE MODULATION (VIRTUAL BASKET) VS EN-BLOC HOLEP

You have accessJournal of UrologyCME1 May 2022MP04-12 EN-BLOC ENUCLEATION TECHNIQUE WITH EARLY APICAL RELEASE AND URINARY SPHINCTER PRESERVATION USING PULSE MODULATION (VIRTUAL BASKET) VS EN-BLOC HOLEP Moises Elias Socarras, Javier Reinoso Elbers, Fabio Esposito, Isabella Greco, Julio Fernandez del Alamo, Vanesa Cuadros Rivera, Diego Carrion Monsalve, Juan Gomez Rivas, Luis Llanes Gonzalez, Luis Llanes Gonzalez, and Fernando Gomez Sancha Moises Elias SocarrasMoises Elias Socarras More articles by this author , Javier Reinoso ElbersJavier Reinoso Elbers More articles by this author , Fabio EspositoFabio Esposito More articles by this author , Isabella GrecoIsabella Greco More articles by this author , Julio Fernandez del AlamoJulio Fernandez del Alamo More articles by this author , Vanesa Cuadros RiveraVanesa Cuadros Rivera More articles by this author , Diego Carrion MonsalveDiego Carrion Monsalve More articles by this author , Juan Gomez RivasJuan Gomez Rivas More articles by this author , Luis Llanes GonzalezLuis Llanes Gonzalez More articles by this author , Luis Llanes GonzalezLuis Llanes Gonzalez More articles by this author , and Fernando Gomez SanchaFernando Gomez Sancha More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002521.12AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Pulse modulation represents one of the important advances in holmium lasers in recent years. We aimed to assess the feasibility, efficacy, safety and outcomes of En-Bloc technique with early apical release using pulse Modulation (Virtual Basket) and compare with En Bloc HoLEP. METHODS: n=261 patients underwent En Bloc enucleation of prostate (n= 126 En Bloc HoLEP using Pulse modulation (Virtual Basket) were compared with n=135 patients in En Bloc HoLEP group. Procedures were performed by a large experienced single surgeon in laser surgery for BPE (>5000 procedures), using the Cyber Ho 150W Holmium laser (Quanta SystemSpA). Setting 2 J/ 50 Hz, with Virtual Basket (VB) activated during enucleation time and 1.2J/40 Hz with Bubble Blast (BB) for hemostasis time. Intra- and post-operative parameters as well as functional results were assessed: prostate volume, Q max, PVR, PSA, IPSS, surgical time, enucleation time, ablation rate, length of hospitalization and complications according to Clavien Dindo. Both (VB & BB) are double pulse modulation effects, Virtual Basket provides excellent cutting, dissection and coagulation balance; while Bubble Blast is useful for coagulation time. RESULTS: Median patient age was 66.5±8.6 and 65.30±7.95, prostate volume 80.57±39.34 and 77.75±39.25, PSA 4.55±0.99 and 4.15±0.75 for En Bloc Holep using Virtual basket and En Bloc HoLEP respectively. Surgical time (37.32±11.9 vs 48.35±19.3), enucleation time (24.97±7.4 vs 32.75±13.08), ablation rate (3.87±1.35 vs 1.65±0.77 gr/min) and haemostasia time (2.36±2.35 vs 8.13±4.39) were significantly better for En Bloc HoLEP using Virtual basket (All p <0.001). Q max, PVR, PSA and IPSS showed significant improvement. No complications Clavien Dindo II – III were observed in En Bloc HoLEP using virtual basket group. CONCLUSIONS: En-Bloc HoLEP with early apical release using pulse modulation is feasible, safe and effective to treat patients affected by BPE. Source of Funding: None © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e62 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Moises Elias Socarras More articles by this author Javier Reinoso Elbers More articles by this author Fabio Esposito More articles by this author Isabella Greco More articles by this author Julio Fernandez del Alamo More articles by this author Vanesa Cuadros Rivera More articles by this author Diego Carrion Monsalve More articles by this author Juan Gomez Rivas More articles by this author Luis Llanes Gonzalez More articles by this author Luis Llanes Gonzalez More articles by this author Fernando Gomez Sancha More articles by this author Expand All Advertisement PDF DownloadLoading ...

The Closed-Loop Sideband Harmonic Suppression for CHB Inverter With Unbalanced Operation

For <i>N</i>-cells cascaded H-bridge (CHB) inverters based on unipolar double frequency phase-shifted pulsewidth modulation (PS-PWM), the output voltage is distorted and its harmonics are difficult to be suppressed under unbalanced conditions (different dc voltages and&#x002F;or modulation indices). This article proposes a closed-loop harmonic suppression scheme based on the PS-PWM, and the scheme is easily implemented in the <i>dq</i> frame to adaptively adjust the displacement angles of the triangular carriers. The harmonic content can be suppressed to its possible minimum value without the limitation of the operational point by the proposed method. The adjustment rules of displacement angles and the harmonic suppression principle are presented in detail. This method can effectively restrain harmonic magnitudes without the limitation of the cells number and does not require complicated trigonometric function calculations or optimization algorithms. Moreover, the principle of symmetrical sideband harmonic suppression is also discussed. The effectiveness of the proposed method is verified by a downscale test platform of the single-phase CHB inverter.

Analysis of condensation and ventilation phenomena for double skin façade units

This paper presents a study of the thermo-hygrometric behaviour of a Double Skin Façade (DSF) unit. The study aims (i) at comparing currently used calculation procedures according to European and American standards (UNI EN ISO 10077, UNI EN ISO 12631:2018, ISO 15099:2003, ANSI/NFRC 100 for the thermal performance and ISO 13788:2012 (2012) for the condensation risk), and (ii) at assessing the 2D hygrothermal performance of a double skin module through a Finite Element Method (FEM)-based model. According to the current standards, a detailed characterization of thermal and fluid dynamic phenomena in closed and ventilated cavities is neglected and a simplified approach is proposed, which tends to overestimate the overall U-value of the curtain wall (UCW) due to an incremental thermal resistance that depends on the thickness of the air gap layer and the level of ventilation. The potential risk of this simplification is that the DSF estimated design performance, whilst complying with regulatory requirements, present inconsistencies respect to the real behaviour, impacting energy, comfort, material degradation, etc. Accurate assessments could be done already during design through detailed FEM multi-physic analyses. Nevertheless, those require a specific knowledge, are cost and time-consuming. As a first step, this study focuses on comparing the normed calculation approach for the design, against a detailed FEM-based multi-physics methodology. Specifically, this couples CFD, hygrothermal and Ray Tracing physics in a tool for the calculation of thermal transmittance, g-value and relative humidity of a DSF with a customizable geometry. As a second step, given a real DSF unit that showed unforeseen phenomena of surface condensation inside the cavity during several hours in spring and autumn, the multi-physic tool has been used to evaluate the condensation risk with the current and modified DSF design, under static and time-dependent boundary conditions.

Improved gradient‐based optimizer for parameters extraction of photovoltaic models

An efficient operation of the solar photovoltaic (PV) system relies on accurate and reliable equivalent models and parameters. For different modular circuit models, the parameter estimation of PV solar cells is a key task that is usually translated into optimization problems solved by metaheuristic algorithms. Gradient-based optimizer (GBO), which was proposed in 2020, is a method with swarm characteristics that was developed from Newton's method. Gradient search rule (GSR) and local escape operator (LEO) is main components of the GBO algorithm. This paper proposes an improved GBO (IGBO) optimization algorithm based on the original algorithm. In IGBO, two strategies, adaptive weights and chaotic behaviour, are introduced to adjust the adaptive parameters. The purpose of adaptive weights is to effectively approach the optimal solution and avoid falling into local optimum in different search phases of the algorithm. Chaotic behaviour aims to replace the randomness of the metaheuristic algorithm and to improve the convergence speed and accuracy of the algorithm. To validate the performance of IGBO, it is applied to the parameter extraction of different PV models. The PV models used in this paper include single diode model (SDM), double diode model (DDM) and PV module model. Finally, comparing with the original algorithm and six well-established algorithms, the experimental data show that the IGBO algorithm is highly competitive, as reflected by the best results obtained in terms of root mean square error values. It can be concluded that IGBO is more competitive in robustness, convergence and accuracy.

Extended convolution model for computing the far-field directivity of an amplitude-modulated parametric loudspeaker

The convolution model of the parametric loudspeaker describes the far-field directivity of the difference-frequency wave by the product directivity of two ultrasonic primary frequencies convolved with Westervelt’s directivity. This can be extended to the case when the primary wave is amplitude-modulated thus resulting in the harmonic distortion of the self-demodulated wave. This paper proposes the extended convolution model with Westervelt’s directivity and Berktay’s directivity respectively. The angle-dependent harmonic distortion of the parametric loudspeaker is thereafter investigated, which is a topic not often mentioned in previous literature but is of significance in practice. The measurement, numerical simulation and model results are compared for the case when the double sideband modulation is adopted and the frequency response of the ultrasonic emitter is a known factor. The comparison validates that the extended convolution model provides accurate predictions that are consistent with the measurement results and the extended convolution model is a simpler way to compute the far-field directivity of an amplitude-modulated parametric loudspeaker as compared to the numerical simulation.

Fine-grained calibrated double-attention convolutional network for left ventricular segmentation

Objective. Left ventricular (LV) segmentation of cardiac magnetic resonance imaging (MRI) is essential for diagnosing and treating the early stage of heart diseases. In convolutional neural networks, the target information of the LV in feature maps may be lost with convolution and max-pooling, particularly at the end of systolic. Fine segmentation of ventricular contour is still a challenge, and it may cause problems with inaccurate calculation of clinical parameters (e.g. ventricular volume). In order to improve the similarity of the neural network output and the target segmentation region, in this paper, a fine-grained calibrated double-attention convolutional network (FCDA-Net) is proposed to finely segment the endocardium and epicardium from ventricular MRI. Approach. FCDA-Net takes the U-net as the backbone network, and the encoder-decoder structure incorporates a double grouped-attention module that is constructed by a fine calibration spatial attention module (fcSAM) and a fine calibration channel attention module (fcCAM). The double grouped-attention mechanism enhances the expression of information in both spatial and channelwise feature maps to achieve fine calibration. Main Results. The proposed approach is evaluated on the public MICCAI 2009 challenge dataset, and ablation experiments are conducted to demonstrate the effect of each grouped-attention module. Compared with other advanced segmentation methods, FCDA-Net can obtain better LV segmentation performance. Significance. The LV segmentation results of MRI can be used to perform more accurate quantitative analysis of many essential clinical parameters and it can play an important role in image-guided clinical surgery.

Comparative Analysis of Double Flux Modulation Permanent Magnet Machines With Different Stator PM Arrangements

In this article, two double flux modulation permanent-magnet machines (DFMPMs) with PMs on both stator and rotor are introduced. The two DFMPMs share a similar operation principle. However, due to the different stator-PM arrangements, the two DFMPMs show different performances. In order to analyze their performance characteristics, their analytical models are built and verified by finite element analysis (FEA). Moreover, to quantitatively compare their electromagnetic performances more accurately, the two DFMPM topologies are optimized, respectively, and compared in terms of back-EMF, cogging torque,rated torque, torque ripple, power factor, and efficiency. Finally, the DFMPM topology with relatively better performances is built and tested. The experimental results match well with the FEA simulations.

SNR Enhancement of up to 9.5 Db Utilizing Four-Wave Mixing for Angle-Modulated Analog Optical Links

Angle modulation, such as phase and frequency modulation (FM/PM), has recently attracted attention for improving the fidelity of analog optical links. This is because angle modulation can enhance the signal-to-noise ratio (SNR) of the original analog message simply by increasing the modulation index or the bandwidth. However, direct generation of a broadband optical angle-modulated signal is not necessarily easy. On the other hand, there is an indirect generation method, where a narrowband angle-modulated signal is first generated and then converted to a broadband signal with the help of nonlinear devices. This method is often used in FM radio systems, but few reports are available on the optical implementation of this indirect method. In this paper, therefore, we propose the optical implementation by using four-wave mixing (FWM) in an optical fiber. Since an optical fiber naturally has a third-order nonlinearity (i.e., the Kerr effect), it should be possible to use fiber nonlinearity for the optical implementation of the indirect method to increase the bandwidth of an optical angle-modulated signal. We propose two types of FWM-based methods. In the first type, an angle-modulated signal is injected into a dispersion-shifted fiber (DSF) with an unmodulated pump wave. Consequently, one of the idlers generated via the FWM has a double modulation index, and the SNR of the original signal can be enhanced by 6 dB. In the second type, the input becomes a conjugate pair of an angle-modulated signal. Consequently, the idler has a threefold modulation index, and therefore, this type enhances the SNR by 9.5 dB. We experimentally confirmed the concept. The results showed that the modulation index can actually be increased almost threefold, and the idler can enhance the SNR of the original signal by approximately 8.8 dB.

SurgiNet: Pyramid Attention Aggregation and Class-wise Self-Distillation for Surgical Instrument Segmentation.

Surgical instrument segmentation plays a promising role in robot-assisted surgery. However, illumination issues often appear in surgical scenes, altering the color and texture of surgical instruments. Changes in visual features make surgical instrument segmentation difficult. To address illumination issues, the SurgiNet is proposed to learn pyramid attention features. The double attention module is designed to capture the semantic dependencies between locations and channels. Based on semantic dependencies, the semantic features in the disturbed area can be inferred for addressing illumination issues. Pyramid attention is aggregated to capture multi-scale features and make predictions more accurate. To perform model compression, class-wise self-distillation is proposed to enhance the representation learning of the network, which performs feature distillation within the class to eliminate interference from other classes. Top-down and multi-stage knowledge distillation is designed to distill class probability maps. By inter-layer supervision, high-level probability maps are applied to calibrate the probability distribution of low-level probability maps. Since class-wise distillation enhances the self-learning of the network, the network can get excellent performance with a lightweight backbone. The proposed network achieves the state-of-the-art performance of 89.14% mIoU on CataIS with only 1.66 GFlops and 2.05 M parameters. It also takes first place on EndoVis 2017 with 66.30% mIoU.

Adaptive linear feature-reuse network for rapid forest fire smoke detection model

Current mainstream smoke detection methods have some problems, such as missing report, large deviation of detection box and slow detection speed. Therefore, we propose an Adaptive Linear Feature-Reuse Network for Rapid Forest Fire Smoke Detection (ALFRNet). Firstly, we designed Double Linear Feature-Reuse Module(DLFR Module) to reduce information loss in the process of the acquisition of smoke images；and Hybrid Attention-Guided Module (HAG Module) was proposed to reduce the interference caused by blurred image and to emphasize the expression of smoke characteristics. At the convolutional layer of the proposed network, a novel Adaptive Depthwise Convolution Module (ADC Module) which can effectively solve the problem of difficulty in recognition caused by too small smoke targets in images was used. Besides, we adopt Cluster NMS (CNMS) in purpose of avoiding large deviation of the detection box. It can adapt to smoke target with fuzzy edge and improve the performance of detection. Finally, we build a smoke detection system based on the Internet of things. The experimental results show that our method achieves 87.26% mAP50 at 43 FPS on NVIDIA TITAN Xp. Compared with other mainstream methods, it has the better performance of quicker speed, higher accuracy and more accurate position of detection box.

Development of a low-resource wearable continuous gesture-to-speech conversion system

Purpose Mild to profound hearing impairment places limits on effective communication and day-to-day interaction. Sign language, being the primary mode of communication for people with hearing loss, lacks communicative efficacy. A wearable assistive device that aims to convert sign language into speech is proposed to facilitate communication between the unimpaired population (untrained in sign language) and the hearing impaired population. However, the wide use of geo-centric sign languages in India has resulted in the lack of standardised sign-language datasets. In the proposed work, a compact, low-resource, motion sensor-based, wireless, single and double hand-gesture recognition module is designed to address this issue. Material and methods The proposed module is designed to perform a two-step process with a Hidden Markov Model (HMM) based gesture-to-text conversion and a bilingual text-to-speech synthesis. Multi-threading based parallel processing is implemented to enable simultaneous working of the two systems to reduce the delay. In the proposed continuous-gesture recognition system, non-gesture hand motions are modelled using ergodic HMMs that are trained by concatenating all the states of gesture models, allowing equiprobable transitions. The proposed system is modelled and tested for American Sign Language (ASL) and user-defined gestures. Results The maximum performance of the proposed system in recognising single-handed and double-handed gestures in terms of F1-score is 98.17% and 84.85%, respectively. Further, the proposed system achieves a maximum F1-score of 98% and 83% in recognising isolated and continuous gestures, respectively. Conclusion The gesture-to-speech conversion system is ported on Raspberry Pi making the proposed system wireless, and highly mobile. Implications for rehabilitation The research work proposes to develop a gesture-to-speech conversion system to enable the deaf-mute population in communication. The major implications of the proposed work are: •A light-weight raspberry pi 3B + module hosts the entire hardware andsoftware, and is sufficient to train and test the gesture-to-speech conversion system, thereby ensuring greater mobility. •The proposed system can be customised to recognise user-defined gestures with just 5 examples of the new gesture. •The proposed system can be expanded to control home appliances (IoT applications) by combining the output of the proposed gesture recognition system with appropriate control interfaces.