Channel Spacing Research Articles

Efficient Blue-Green Light Phased Array Based on High-Contrast Grating as a Demultiplexer

Wavelength division multiplexing (WDM) technology has been proven to effectively increase the capacity of optical communications in the infrared light band. However, to date, the WDM systems in the visible band only support limited quantity of wavelength channels, with coarse channel spacing of over 20 nm. This is because there are no available multi/demultiplexers (MUX/DeMUX) with fine wavelength spacing for visible light. In this work, we use a high-contrast grating (HCG) structure to effectively separate the blue-green wavelengths with fine spacing. An efficient blue-green light phased array based on HCG aperture is demonstrated to work as the DeMUX in a WDM system. The HCG aperture presents more efficient main-lobe radiation than typical one-dimensional waveguide surface grating arrays with fishbone antennas. The measured main-lobe loss of optical phased array (OPA) with HCG is over 15 dB lower than that of OPA with fishbone antennas, because HCG provides maximum scatterings for blue-green light. A wavelength spacing as small as 4 nm is validated in a blue-green WDM system, which is the finest channel spacing for WDM in visible band to the best of our knowledge.

Analysis of Bandwidth Narrowing in Wavelength Selective Switch Enabled DP-64QAM Systems With Transceiver Noise

The impact of filtering impairments resulting from cascaded, wavelength selective switches is investigated for 32 Gbaud dual-polarization 64-ary quadrature amplitude modulation in the presence of transceiver noise. Training-sequence based adaptive equalization and pilot-aided carrier phase estimation are employed to cope with the combined effects of the transceiver-imposed limitation in achievable signal-to-noise ratio and the filtering-induced signal distortion. For a given level of amplified spontaneous emission noise, transceiver noise reduces the total signal-to-noise ratio resulting in an increased dependence of the bit-wise achievable information rate on filtering-induced bandwidth narrowing. The implications of statistical variations in the overall filter frequency response are also assessed by considering randomly selected responses for each of the individual filters in a cascade. Further, the impact of the frequency response of the demultiplexing filter at the receiver is investigated by considering a 3-channel 32 Gbaud wavelength division multiplexed system with a channel spacing of 37.5 GHz.

Addressing multiple salient object detection via dual-space long-range dependencies

Salient object detection plays an important role in many downstream tasks. However, complex real-world scenes with varying scales and numbers of salient objects still pose a challenge. In this paper, we directly address the problem of detecting multiple salient objects across complex scenes. We propose a network architecture incorporating non-local feature information in both the spatial and channel spaces, capturing the long-range dependencies between separate objects. Traditional bottom-up and non-local features are combined with edge features within a feature fusion gate that progressively refines the salient object prediction in the decoder. We show that our approach accurately locates multiple salient regions even in complex scenarios. To demonstrate the efficacy of our approach to the multiple salient objects problem, we curate a new dataset containing only multiple salient objects. Our experiments demonstrate the proposed method presents state-of-the-art results on five widely used datasets without any pre-processing and post-processing. We obtain a further performance improvement against competing techniques on our multi-objects dataset. The dataset and source code are available at: https://github.com/EricDengbowen/DSLRDNet.

Electro-optical tunable interleaver in hybrid silicon and lithium niobate thin films.

The interleaver was one of the key devices in dense wavelength division multiplexing (DWDM) applications. In this study, an interleaver with an asymmetrical Mach-Zehnder interferometer structure was designed, fabricated, and characterized in hybrid silicon and lithium niobate thin films (Si-LNOI). The interleaver based on Si-LNOI could be fabricated by mature processing technology of Si photonic, and it was capable of the electro-optical (E-O) tuning function by using the E-O effect of LN. In the range of 1530-1620 nm, the interleaver achieved a channel spacing of 55 GHz and an extinction ratio of 12-28 dB. Due to the large refractive index of Si, the Si loading strip waveguide based on Si-LNOI had a compact optical mode area, which allowed a small electrode gap to improve the E-O modulation efficiency of the interleaver. For an E-O interaction length of 1 mm, the E-O modulation efficiency was 26 pm/V. The interleaver will have potential applications in DWDM systems, optical switches, and filters.

Transmission distance in the space of quantum channels

Transmission distance in the space of quantum channels

Design and Analysis of a Vertical Electric Ducted Fan for Unmanned Aerial Vehicles

Several types of multirotor unmanned aerial vehicles (UAVs) are widely used in various industrial activities. UAVs with electric ducted fans (EDFs) have been developed to mitigate the risks associated with rotary blades, which are installed on the exterior structure of conventional UAVs and exposed to the ambient environment. Particularly, vertical EDFs have become a focus in the field of UAV design because they require less space for the flow channel compared with horizontal EDFs. In this study, a vertical EDF UAV model was developed. Structural and flow field analysis was performed in Ansys software to determine the optimal design configuration. The results confirmed that the designed model facilitated smooth air flow with favorable inlet and outlet velocity. The vehicle structure required minor adjustment to reduce the frequency of occurrence of vortices. Overall, this study made two research contributions. First, an EDF UAV model was developed to mitigate the risk of rotary blades being exposed to the ambient environment. Second, a vertical EDF system was proposed to reduce the flow channel space and maintain the outlet velocity, thereby improving the takeoff, landing, and thrust performance of UAVs.

Looking at Boundary: Siamese Densely Cooperative Fusion for Salient Object Detection

Though deep learning-based saliency detection methods have achieved gratifying performance recently, the predicted saliency maps still suffer from the boundary challenge. From the perspective of foreground-background separation, this article attempts to extract the edge information of objects by exploiting the difference between different color channels in the RGB color space and establishes a novel multicolor contrast extraction (MCE) mechanism to improve the learning ability of exquisite boundary information of the network. To make full use of the MCE outputs and RGB colors, and well depict and capture the complementary information between them, we devise a novel Siamese densely cooperative fusion (DCF) network (SDFNet) for saliency detection, which consists of two effective components: boundary-directed feature learning (BDFL) and DCF. The BDFL provides joint learning for both MCE and RGB modalities through a Siamese network, while the DCF module is devised for complementary feature discovery, in order to effectively combine the features learned from two modalities. Experiments on five well-known benchmark datasets demonstrate that the proposed method outperforms the state-of-the-art approaches in terms of different evaluation metrics. We provide a detailed analysis of these results and indicate that our joint modeling of MCE and RGB colors helps to better capture the object details, especially in the object boundaries.

Gravity separation of fine itabirite iron ore using the Reflux Classifier – Part I – Investigation of continuous steady state separations across a wide range of parameters

High grade iron ore resources are becoming depleted in Brazil, with relatively low-grade ores requiring more intensive concentration to achieve a premium product. Accordingly, a typical industrial itabirite concentration circuit includes desliming in hydrocyclones and concentration via reverse flotation, product thickening and filtration, with the slimes sent to tailings thickeners, and onto tailings storage facilities. This work examined the potential for applying a vastly simpler approach, a single stage of gravity separation using the Reflux Classifier. Here the classified feed, 90 % finer than 0.150 mm, is sent directly to the Reflux Classifier, leading immediately to a high-grade concentrate at high solids concentration.Part I describes the findings from a comprehensive series of experiments covering the effects of bed density set point, feed pulp density, throughput, fluidisation water rate and lamella channel spacing. The main program, based on an ore with 8 % goethite and 45 % hematite, achieved a feed upgrade from 37 % to 65.6+/−0.4 % iron and iron recovery of 72.9+/−0.4 % at 9 t/m2/h. A second feed with 1 % goethite and 57 % hematite was upgraded from 41 % to 66.3+/−0.4 % iron at an iron recovery of 84.7+/−0.5 % at 10 t/m2/h. (The grade of pure hematite is 69.9 % iron). It was essential to run the Reflux Classifier at a sufficient volumetric rate to achieve shear induced inertial lift of the coarse silica within the closely spaced inclined channels, to reject the gangue minerals from the high-grade product. The results demonstrate the technical feasibility of applying the Reflux Classifier to upgrade itabirite feeds.

On-chip non-uniformly spaced multi-channel microwave photonic signal processor based on an ultrahigh-Q multimode micro-disk resonator.

Multi-channel microwave photonic (MWP) signal processing can simultaneously perform different task operations on multiple signals carried by multiple wavelengths, which holds great potential for ultrafast signal processing and characterization in a wavelength-division-multiplexed (WDM) network. As emerging telecommunication services create more data, an elastic optical network, which has a flexible and non-uniform spectrum channel spacing, is an alternative architecture to meet the ever-increasing data transfer need. Here, for the multi-channel ultra-fast signal processing in the elastic optical network, we propose and demonstrate an on-chip non-uniformly spaced multi-channel microwave photonic signal processor based on an ultrahigh-Q multimode micro-disk resonator (MDR). In the proposed signal processor, an MDR supporting multiple different order whispering-gallery modes (WGMs) with an ultrahigh Q-factor is specifically designed. Benefiting from the large and different free spectral ranges (FSRs) provided by the different order WGMs, a non-uniformly spaced multi-channel microwave photonic signal processor is realized, and various processing functions are experimentally demonstrated including bandpass filtering with a narrow passband of 103 MHz, a rejection ratio of 22.3 dB and a frequency tuning range from 1 to 30 GHz, multiple frequency measurement with a frequency measurement range from 1 to 30 GHz, a frequency resolution better than 200 MHz and a measurement accuracy of 91.3 MHz, and phase shifting with a phase tuning range from -170°∼160°, an operational bandwidth of 26 GHz from 6 GHz to 32 GHz and a small power variation of 0.43 dB. Thanks to the coexistence of different order WGMs supported by the MDR, non-uniformly spaced multi-channel signal processing is enabled with the key advantages including a broad operation bandwidth, an ultra-narrow frequency selectivity, and a large phase tuning range with a small power variation. The proposed signal processor is promising to be widely used in future elastic optical networks with flexible spectrum grids.

A hybrid modelling approach for reverse osmosis processes including fouling

A novel hybrid modelling approach, combining the strengths of a mechanistic reverse osmosis (RO) model and a data-driven fouling model, is developed on a unique long-term dataset from a full-scale RO installation to predict its performance. The mechanistic solution-diffusion model describes well understood phenomena in RO such as concentration polarisation, osmotic pressure and solutes transport throughout the membrane. This solution-diffusion model is combined with a data-driven model to cover the gaps in knowledge related to fouling phenomena. Several fouling models are tested to predict the membrane resistance over time and a thorough analysis of important input features was performed. A non-linear recurrent neural network with long short-term memory (RNN-LSTM) clearly outperformed (RMSE = 1.01e13) a linear autoregressive integrated moving average with exogenous variables (ARIMAX) model (RMSE = 1.97e13) for an 8 month testing period. The best performance was achieved when including membrane cleaning as two separate features representing short and long CIPs. Moreover, recovery setpoint, concentrate flow rate, feed temperature, feed conductivity and feed calcium concentration were shown to be important model input features. Fouling sensitive parameters of the solution-diffusion model (the water permeability, the feed spacer channel height and the solute permeability - determined by a global sensitivity analysis) were made function of the output (membrane resistance) of the RNN-LSTM thus leading to a serial hybrid model. The predictions of the hybrid model showed a clear improvement for all output variables when compared to a solution-diffusion model including temperature correction. The model was developed, calibrated and trained on measurements of standard sensors and can thus be used for real-time applications such as advanced control and predictive scenario analysis in a digital twin context.

Design and implementation of microcirculation cooling device for microelectronic devices based on electrostatic force

This paper presents the design of a cooling device for microelectronic device applications. The proposed device uses parallel plate capacitor electrical bias to generate an electrostatic force that acts on the coolant to enable control of the coolant flow in the radiator. Through a combination of the structural design of the device and the application of an electrical bias on both sides of multiple parallel plate capacitor electrodes, the generation of a radiator coolant eddy current is realized, and the functions of cooling and heat transfer are realized for microelectronic devices placed on the surface of the base platform. Based on this principle, a finite element multi-physical field simulation was used to simulate the flow heat transfer function of the coolant in the device under the action of the electrostatic force and the effects of the channel diameter, channel spacing, voltage, and liquid storage tank depth on the peak coolant velocity were studied. In addition, 3D printing technology was used to fabricate the heat dissipation device. The heat dissipation device was tested by charging, with a basic realization of the function of controlling the cooling liquid flow in the heat dissipation device demonstrated. The device realizes radiator coolant flow rate control through voltage control and has characteristics that include low energy consumption and a convenient and compact structure.

On the Latent Space of mmWave MIMO Channels for NLOS Identification in 5G-Advanced Systems

On the Latent Space of mmWave MIMO Channels for NLOS Identification in 5G-Advanced Systems

Multi-Level Attention-Based Categorical Emotion Recognition Using Modulation-Filtered Cochleagram

Speech emotion recognition is a critical component for achieving natural human–robot interaction. The modulation-filtered cochleagram is a feature based on auditory modulation perception, which contains multi-dimensional spectral–temporal modulation representation. In this study, we propose an emotion recognition framework that utilizes a multi-level attention network to extract high-level emotional feature representations from the modulation-filtered cochleagram. Our approach utilizes channel-level attention and spatial-level attention modules to generate emotional saliency maps of channel and spatial feature representations, capturing significant emotional channel and feature space from the 3D convolution feature maps, respectively. Furthermore, we employ a temporal-level attention module to capture significant emotional regions from the concatenated feature sequence of the emotional saliency maps. Our experiments on the Interactive Emotional Dyadic Motion Capture (IEMOCAP) dataset demonstrate that the modulation-filtered cochleagram significantly improves the prediction performance of categorical emotion compared to other evaluated features. Moreover, our emotion recognition framework achieves comparable unweighted accuracy of 71% in categorical emotion recognition by comparing with several existing approaches. In summary, our study demonstrates the effectiveness of the modulation-filtered cochleagram in speech emotion recognition, and our proposed multi-level attention framework provides a promising direction for future research in this field.

A Multi-Feature Fusion Model Based on Denoising Convolutional Neural Network and Attention Mechanism for Image Classification

Spatial location features extracted by denoising convolutional neural network. At this time, an attention mechanism is introduced into denoising convolutional neural network. The dual attention model of local area is presented from two dimensions of channel and space—channel attention mechanism weights channel and spatial attention mechanism weights location. A variety of machine learning methods are used to classify and train different features. Multi-semantic features and heterogeneous features are fused by adaptive weighted fusion algorithm. Finally, the data sets Cifar-10, STL-10, Cifar-100 and GHIM-1OK are verified on the proposed method. Compared with a single semantic feature, the accuracy is improved by 10%-15%. Compared with several advanced algorithms, the performance has a significant advantage, which proves the complementarity of heterogeneous features and multi-network semantic features and the effectiveness of the adaptive weighted fusion algorithm.

Description and Analytical Modeling for a Solid Block Cross-flow High Temperature Heat Exchanger

In this report, the design specifics, and performance modeling results, for a simple, solid metal block, liquid–liquid cross-flow heat exchanger, intended for high temperature applications, are given. The design consists of a solid block of metal, with cylindrical channels providing the cross-flow passageways for two non-mixing liquids. In this design, all flow channels are separated by a certain minimum thickness of the host solid block material. This particular design is limited by the length of pores that can be machined from a solid block. In this study, a simple heat transfer model, appropriate for such an exchanger, was used to estimate what values of effectiveness might be obtainable while keeping the size of the exchanger as compact as possible. The effects of channel length and spacing, liquid specific heat and viscosity and block material conductivity on exchanger effectiveness are considered and results reported. The model predicts that for a cubic exchanger of side length 8.25 cm with 50 channels per side at a diameter of 3.0 mm each, for a particular high temperature situation using molten salts, with an inlet and outlet temperature difference of around 170 K, an effectiveness of 0.4 can be achieved with a total mass flow rate of 0.5 kg $$\cdot$$ s $$^{-1}$$ along with a Reynolds number of less than 2000.

Integration of Optical and Free Space Optics Network Architecture for High-Speed Communication in Adverse Weather using suitable Optical Bands

Free Space Optics (FSO) is a highly viable solution for high-speed wireless communication and is widely preferred over radio frequency communication systems because of its faster data transmission, no regulatory requirements and highly secure long-range operations. However, the capacity and availability of FSO optical bands are a significant concern in varying atmospheric conditions. Our objective is to enhance network flexibility and expand wireless network coverage in adverse weather conditions by combining optical and FSO links using optical bands C, S, and O. The study analyzed the performance of a hybrid 4 channels FSO-WDM system with a 100GHz or 0.8 nm channel spacing under different conditions, including adverse weather and varying data rates. An attenuation of 0.25 dB/km was fixed, and the system's performance was analyzed up to 3 km. The results showed that as the data rate increased, the system's performance declined, and the O band was the best performer up to 25 Gbit/s. BER values were analyzed at different weather conditions using the Kim model, and the O band consistently outperformed the S and C bands. Eye diagrams were used to evaluate the signal quality, and the O band was shown to perform better than the other two bands, even in adverse weather conditions. Overall, the study suggests that FSO is a viable solution for high-speed wireless communication, particularly when using the O band.

Investigation of suitable cascaded arrangement of conventional optical amplifiers for DQPSK modulated UD-WDM system at a channel spacing of 12.5 GHz

Investigation of suitable cascaded arrangement of conventional optical amplifiers for DQPSK modulated UD-WDM system at a channel spacing of 12.5 GHz

Circuits of space and time quantum channels

Exact solutions in interacting many-body systems are scarce but extremely valuable since they provide insights into the dynamics. Dual-unitary models are examples in one spatial dimension where this is possible. These brick-wall quantum circuits consist of local gates, which remain unitary not only in time, but also when interpreted as evolutions along the spatial directions. However, this setting of unitary dynamics does not directly apply to real-world systems due to their imperfect isolation, and it is thus imperative to consider the impact of noise to dual-unitary dynamics and its exact solvability. In this work we generalise the ideas of dual-unitarity to obtain exact solutions in noisy quantum circuits, where each unitary gate is substituted by a local quantum channel. Exact solutions are obtained by demanding that the noisy gates yield a valid quantum channel not only in time, but also when interpreted as evolutions along one or both of the spatial directions and possibly backwards in time. This gives rise to new families of models that satisfy different combinations of unitality constraints along the space and time directions. We provide exact solutions for the spatio-temporal correlation functions, spatial correlations after a quantum quench, and the structure of steady states for these families of models. We show that noise unbiased around the dual-unitary family leads to exactly solvable models, even if dual-unitarity is strongly violated. We prove that any channel unital in both space and time directions can be written as an affine combination of a particular class of dual-unitary gates. Finally, we extend the definition of solvable initial states to matrix-product density operators. We completely classify them when their tensor admits a local purification.

Distribution pattern of natural fractures in lacustrine shales: a case study of the Fengcheng formation in the Mahu Sag of the Junggar Basin, China

The Lower Permian Fengcheng Formation in the Mahu Sag develops a set of organic-rich alkaline lacustrine shale strata, which is a key area for shale oil exploration and development. As an important storage space and seepage channel for shale reservoirs, natural fractures have an impact on shale oil enrichment, production and development effect. In this study, the types and characteristics of natural fractures were first analyzed using core, thin section and imaging logging data. On this basis, combined with the distribution of fractures in single wells, the vertical distribution law of fractures is discussed. Finally, the planar distribution of fractures is evaluated using different seismic attributes such as coherence, curvature, likelihood, and AVAz. The results showed that three types of fractures are existed, including transformational shear fractures, intraformational open fractures and bed-parallel shear fractures, with intraformational open fractures being the most developed. The development degree of fractures in different layers has obvious differences, mainly controlled by lithology and brittle mineral content. The basalt and tuff are developed in the Feng 1 Member, with low carbonate mineral content, resulting in a relatively low degree of fracture development. The dolomite and argillaceous dolomite are developed in the Feng 2 Member and the Feng 3 Member, with high carbonate mineral content and brittleness, resulting in a high degree of fracture development. Additionally, the closer to the fault, the higher the degree of fracture development. On the plane, the fracture zone develops near the main and secondary faults, with the trend mainly oriented in the E-W direction and approximately parallel to the direction of the faults. The width of the fracture zone is largest in the central and southern part of the study area. These fractures are fault-related and are caused by regional stress fields resulting from the activity of the main-secondary faults.

Investigation of MDRZ and DPSK modulation schemes employed in DWDM systems for smart city 5G access networks

Wavelength division multiplexing (WDM) is one of the emerging technologies for data transmission in 5G access network assembly between the antenna unit (AU) and the distribution unit (DU). Here, in this work, we evaluate and analyze a dense wavelength division multiplexing (DWDM) — passive optical networks (PONs) employing erbium–ytterbium-doped fiber amplifier (EYDFA) [Formula: see text] Raman hybrid optical amplifier (HOA) using two modulation schemes — modified duobinary return to zero (MDRZ) and differential phase shift keying (DPSK) for alternate channels, where the channel count has been varied from 8 to 40. The system has been analyzed over the wavelength span of 1550–1558.8[Formula: see text]nm with a channel spacing, input power and data rate of 25[Formula: see text]GHz, 0[Formula: see text]dB and 40[Formula: see text]Gb/s, respectively. An average gain, gain ripple and optical signal-to-noise ratio (OSNR) of 20.87, 0.95 and 30[Formula: see text]dB, respectively have been observed in the case of HOA along with the achievement of Q-factor of up to 9 at the receiving end of the system. The DPSK-modulated channels result in higher values of gain and OSNR along with lower gain ripple as compared to MDRZ channels making the proposed system a good option for 5G access network applications.