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The photonics-assisted millimeter-wave (MMW) communication technology is attractive to facilitate the MMW application in the upcoming B5G and 6G networks. However, its generated MMW signal by optical heterodyne detection usually suffers from serious laser phase noise, which will severely deteriorate the system performance. In this paper, based on a single dual-drive Mach-Zehnder modulator and a single-end photodetector, we first present a simple and spectrally efficient hybrid fiber-wireless double-sideband transmission by employing an overlapping frequency multiplexing scheme. That is, two independent wireless signals with an identical carrier frequency can be simultaneously transmitted in the hybrid fiber-wireless links. To recover the above two overlapped signals, and cancel the concomitant laser phase noise at the same time, a novel digital signal processing method for carrier extraction and signal recovery is further proposed. A proof-of-concept experiment using two independent 3-GBd quadrature phase shift keying (QPSK) signals at W band (92.5 GHz) is performed. After up to 80-km fiber and 3-m wireless transmission, the two QPSK signals can be successfully demodulated, without using the traditional carrier phase estimation algorithm. The proposed scheme not only can double the spectral efficiency of conventional double sideband transmission scheme, but also is immune to its power fading phenomenon induced by chromatic dispersion and robust to the laser phase noise resulting from two free-running lasers in the photonics-assisted MMW communication link.

SDGSAT-1, the inaugural Earth science satellite commissioned by the Chinese Academy of Sciences, successfully lifted off from China's Taiyuan Satellite Launch Center on 5 November 2021. Cross calibration has emerged as an indispensable methodology, providing an effective means for quality assessment, stability monitoring, and uncertainty analysis. This is achieved through the meticulous selection of an appropriate reference instrument. In our investigation, we conducted a comprehensive evaluation of the absolute radiometric calibration accuracy of the thermal infrared spectrometer (TIS), a pivotal component aboard SDGSAT-1. Our evaluation centered on a meticulous comparative analysis, where we juxtaposed the brightness temperature (BT) values recorded by TIS with the BT values derived from TIRS-2, computed following the spectral alignment with TIS. Our findings reveal that the current absolute BT bias for the B2 channel of TIS is less than 0.52 K. Meanwhile, the B3 channel exhibits a slightly larger fluctuation in absolute BT bias, yet remains within acceptable parameters, registering at less than 1 K. Notably, B3 emerges as the more dependable option for accurately gauging the temperature of the target region. Specifically, when the BT of B3 surpasses 290 K, the BT bias remains consistently below 0.3 K. In light of the approximately 40-min time difference in the water surface data utilized in our study, we conducted simulations to assess the channel BT of TIS under the scenario of a 0.25 °C water temperature variation. Our simulations conclusively demonstrate that the corresponding change in BT does not exceed 0.25 K.

Launched in November 2021, the sustainable development science satellite-1 carries the thermal infrared spectrometer (TIS) as a pivotal payload. Achieving precise radiometric calibration for geophysical parameter accuracy is crucial. Leveraging the frequent cross-calibration capability of the geostationary satellite FY-4A/advanced geostationary radiation imager (AGRI), this study addresses observational geometry challenges. The proposed radiance correction model for FY-4A/AGRI effectively reduces radiance discrepancies caused by differences in satellite zenith angles between TIS and AGRI. After integrating the corrected data into nadir-observed statistics, the long-term brightness temperature (BT) bias of TIS and AGRI was monitored. The results show that the daytime and nighttime BT bias exhibit similar trends, with the B2 band mainly showing negative bias. Overall, the BT bias for the B2 and B3 bands is within 1 K. The standard deviation of the BT bias for approximately 2250 sample points was calculated, revealing the values of 0.22 K and 0.40 K during the daytime, and 0.31 K and 0.57 K at night. The introduced model error remains below 0.31 K. Regarding the uncertainty of the BT bias introduced by spectral matching, when the spectral broadening is 1.15 times the wavelength interval, the uncertainty is less than 0.29 K for B2 and less than 0.38 K for B3. This work enhances our understanding of radiometric calibration challenges, providing insights into satellite-based geophysical parameter accuracy.

The efficiency of industrial knowledge transfer (IKT) directly affects the level of knowledge connection and collaborative innovation in the industry. However, there is a lack of research, particularly from the perspective of network characteristics, to investigate the efficiency of IKT. Therefore, this study proposes a methodology for measuring the efficiency of weighted industrial knowledge transfer network (IKTN) by employing multiple network indicators. Firstly, based on patent data, a weighted IKTN model with node and edge weights is constructed, and the weighted clustering coefficient and path length of the network are defined. Then, considering the indicators of node weights, edge weights, weighted clustering coefficient, and path length, an efficiency measurement model for the weighted IKTN is established. Finally, we take the environmental protection industry (EPI) in the Yangtze River Delta region of China as the practical case to verify the scientific validity and applicability of the proposed method. The results show that the measurement method proposed can effectively evaluate the node efficiency and overall efficiency of IKTN, and provide a scientific basis for relevant policymaking. This study comprehensively considered multiple factors in the IKTN efficiency measurement and used existing data from the patent database in the weight setting, avoiding the problem of excessive reliance on subjective factors in previous studies that may lead to deviations in the authenticity of the evaluation.

Intensity modulation/direct detection (IM/DD) and coherent schemes are two kinds of promising solutions to achieve the evolution for B5G/6G fronthaul networks. IM/DD has more mature commercial deployment applications for short-reach applications with lower costs and simpler configurations compared with coherent solutions. In this article, we experimentally demonstrate a local area network-wavelength division multiplexing (LAN-WDM) IM/DD access system with a record bit rate of 2 Tb/s (250 Gbit/s × 8) probabilistic shaping eight-pulse amplitude modulation (PS-PAM-8) signal with joint equalization techniques to support the evolution of future B5G/6G mobile fronthaul networks. Considering the 20% Soft Decision Forward Error Correction (SD-FEC) threshold with the bit error rate (BER) of 2 × 10−2, we realize a record net bit rate of 1.6 Tb/s over 5 km fiber. This system can potentially support a 12-wavelengths transmission with the total line rate of 3 Tb/s (250 Gbit/s × 12). Moreover, we analyze the challenges of the evolution, usage scenarios, digital signal processing (DSP) implementation, transmission rate and distance, and the tolerance of dispersion with different wavelengths. The LAN-WDM can be considered as a feasible and potential candidate scheme to meet the evolution and deployment of B5G/6G Terabit/s fronthaul networks.

In fiber-wireless integration systems, it is valuable to investigate whether digital subcarrier multiplexing (SCM) signal is effective in improving nonlinear tolerance against photodiode (PD) saturation compared to single-carrier (SC) signal. For a fair comparison, the mitigation of linear impairments especially for IQ mixing effects become significant. In this article, we first analyze the impacts of transmitter IQ mixing effects for SC and digital SCM signals. Then, we employ the real-valued multiple-input multiple-output (MIMO) post-equalizers for the PM (polarization multiplexing)-SC system and PM-SCM system so as to mitigate transmitter IQ mixing effects. Finally, we experimentally compare the nonlinear tolerance of SC, SCM with two subcarriers (SCM-2), and SCM-4 signals using QPSK, 8QAM, and 16QAM in a W-band fiber-wireless system against the pin-photodiode (PIN-PD) saturation considering noise-limited case, optimum case and non-linear case. Subcarriers for SC, SCM-2, and SCM-4 are 25GBaud, 12.5GBaud, and 6.25GBaud respectively, with a total symbol rate of 25GBaud. Maximum line rate is 200 Gb/s with the BER satisfying the 7% HD-FEC threshold when employing the PM-16QAM. The results show that SCM signal has better nonlinear tolerance against the PIN-PD saturation than SC signals when system works in the non-linear case especially when using high-order modulation formats.

The quantization technique with a low-bit resolution can significantly reduce the cost and power consumption of analog-to-digital converter (ADC). It will play an important role in energy conservation and cost reduction for the incoming B5G millimeter-wave (MMW) communication systems. In this paper, we propose and demonstrated experimentally a low-bit Gaussian mixture model (GMM) based non-uniform adaptive vector quantization (AVQ) scheme for the low-cost intensity modulated envelope detection photonics-assisted 28 GHz MMW communication system for the first time. The principles of GMM-based one-dimensional adaptive scalar quantization (ASQ) and multi-dimensional AVQ are first introduced, and then are used to realize the low-bit non-uniform adaptive quantization for reducing the ADC bit resolution of MMW receiver. Furthermore, the performance of traditional uniform quantization, the present K-means and proposed GMM-based non-uniform ASQ/AVQ schemes are evaluated and compared in detail. Utilizing the proposed GMM-based AVQ scheme, the ADC quantization resolution in our MMW receiver can be reduced from 5 bits of the traditional uniform quantization to as low as 2 bits, without noticeable performance penalty. Moreover, as compared with the K-means-based quantization scheme, the MMW receiver enabled by GMM-based ASQ/AVQ scheme can save about half of the quantization time under similar performance. This is mainly because the clustering based on probability converges faster than the Euclidean distance, which significantly reduces the number of iterations required. Therefore, the GMM-based AVQ scheme is a promising solution to realize high performance ADCs with low-bit resolution for future MMW-enabled optical fiber wireless access networks.

Orthogonal Frequency Division Multiplexing Access Passive Optical Networks (OFDMA-PONs), a solution for the next-generation optical access network, allows multiple optical network units (ONUs) to dynamically share subcarriers (SCs) to support efficient bandwidth allocation. In uplink transmission, multiple ONUs can share orthogonal low bit rate SCs to transmit data at different time slots (TSs) during the transmission cycle. In this paper, the dynamic subcarrier allocation (DSA) scheme based on deep reinforcement learning (DRL) is proposed for various ONU bandwidth requests. The novel scheme jointly allocates time slots, subcarriers, and modulation formats in a dynamic and flexible manner. The ONU can save transmit power by using a lower order modulation format while meeting the delay requirement. The simulation part demonstrates how the proposed DRL-based DSA scheme can be adapted to various situations, including 1) variation in the size of ONU bandwidth requests, and 2) variation in the weight of different indicators. The extensive simulation results show that, for the first time, the proposed DRL-based DSA algorithm achieves optimal traffic latency with substantial power saving, compared with the traditional two-dimensional DSA algorithms.

The surging mobile traffic poses serious challenges for mobile operators and the advancement of information and communication technologies (ICT). The cost and energy consumption cannot support affordable mobile services and sustainable growth. As a new architecture, cloud-based radio access network (C-RAN) is proposed to confront these challenges. C-RAN is a deployment paradigm that seeks to isolate baseband unit (BBU) from its remote radio unit (RRU) in base station (BS), consolidating the BBUs into a common place (i.e. BBU pool). In the BBU pool, the computing resources provided by the BBUs can be dynamically assigned to RRUs on demand by the BBU controller. Thus, with the fluctuation of data traffic from RRUs, a part of BBUs can be dynamically turned on or off. As a result, the energy consumption of the BBU pool can be reduced correspondingly. In this paper, we design a Markov chain-based calculation model to formulate the energy-saving operation of the BBU pool with an active/sleep mode under dynamic RRU traffic load. On this basis, we propose two different BBU state transition strategies for the BBU pool, i.e., “Cautious ON, Bold OFF (CO-BF)” strategy and “Bold ON, Cautious OFF (BO-CF)” strategy. We formulate the key performance indicators in terms of the energy saving efficiency (ESE), the consequent packet queuing delay (PQD) and the normalized tradeoff cost as well. In extensive simulations, we investigate the effect of these key parameter indicators on the system performances of the BBU pool. Achieving the minimum normalized cost, an optimal operating strategy for the BBU pool can be determined by adjusting the parameter values of the ( $N$ , $M$ ). The simulation results show when RRU traffic load is light (e.g., $\lambda =0.1$ ), the proposed BO-CF strategy can lead to the minimum normalized cost, which corresponds to ESE of up to 75.4% and PQD of 0.0097ms. For heavier load (e.g., $\lambda =0.4$ ), the minimum normalized cost can be obtained along with ESE of up to 74.1% and PQD of 0.1241ms, when the CO-BF strategy is adopted. Hence, we observe that the BO-CF strategy is slightly better than the CO-BF for the light traffic load of the BBU pool, while the CO-BF strategy would be more suitable for the BBU pool with the heavier traffic load. It proves the efficacy of our proposed Markov chain-based calculation model to pursuit an optimal operating strategy for the delay-aware and energy-efficient BBU pool.

A uniform linear array (ULA) or a multi-element planar array composed of uniform linear arrays is the main applied research array for direction-of-arrival (DOA) estimation in array signal processing. In recent years, the uniform circular array (UCA) is getting more attention because of its consistent azimuthal beam resolution, but the DOA estimation algorithm of a UCA is complex and difficult to implement. To solve this problem, a UCA positioning method based on virtual interpolation and subarray rotation (VISAR) is proposed. This method effectively reduces the computational complexity of DOA estimation for a UCA, and the simulation analysis of the algorithm shows that in terms of positioning performance, the proposed algorithm is better than the existing virtual interpolation algorithms in the case of a low signal-to-noise ratio (SNR).

Deep learning methods can improve the performance of recommender systems over traditional methods, especially when text information is available. To extract information hidden in the text description of an item and fuse it with rating information, it has been proposed that the network be stacked with more layers. However, as the network thus deepens, the problem of the attenuation of the preamble signal can cause the convolutional neural network to break down. The gradient gradually disappears during the back-propagation process, resulting in an inability to adjust the weights. In this paper, a method called eXtreme Residual connected Convolution Collaborative Filtering (xRConvCF) is proposed to predict the rating for each item based on the textual information. It creates data branch lines to form a residual module called the eXtreme residual (xRes) connection to mitigate the problem of the vanishing gradient and enhance feature reuse. The results of experiments on empirically obtained datasets show that the proposed deep learning model significantly outperforms state-of-the-art methods of recommendation.

Microfossils, tiny fossils whose study requires the use of a microscope, have been widely applied in many fields of earth, life, and environmental sciences. The abundance and high diversity of microfossils, as well as the need for rapid identification, call for automated methods to classify microfossils. In this study, we constructed an open dataset of three-dimensional (3D) microfossils and proposed a deep learning-based approach for microfossil classification. The dataset, named `Archives of Digital Morphology' (ADMorph), currently contains more than ten thousand 3D models from five classes of 410 million-year-old fishes. The deep learning-based method includes data preprocessing, feature extraction, and 3D microfossil model classification. To assess the method performance and dataset representability, we performed extensive experiments. Compared with multiview convolutional neural networks (MVCNN) (91.54%), PointNet (64.13%), and VoxNet (78.15%), the method proposed herein had higher accuracy (97.60%) on the experimental dataset. We also verified data preprocessing (92.36%) and feature extraction (97.10%). We combined them to obtain the macroaveraging accuracy of 97.60%, the highest accuracy of 100%, and the lowest accuracy of 88.78%. We suggest that the proposed method can be applied to other 3D fossils and biomorphological research fields. The fast-accumulating 3D fossil models might become a source of information-rich datasets for deep learning.

RNA-binding proteins (RBPs) play crucial roles in gene regulation. The advent of high-throughput experimental methods, has generated a huge volume of experimentally verified binding sites of RNA-binding proteins and greatly advanced the genome-wide studies of RNA-protein interactions. Many computational approaches have been proposed, including deep learning models, which have achieved remarkable performance on the identification of RNA-protein binding affinities and sites. In this review, we discuss machine learning and deep learning approaches, mainly focusing on the prediction of RNA and proteins binding sites on RNAs by deep learning. Furthermore, we discuss the advantages and disadvantages of these approaches. The workflow of deep learning is also revealed. We recommend some promising future directions of deep learning models in the study of RBP-binding sites on RNAs, especially the embedding, generative adversarial net, and attention model. Extraction and visualization methods involving motif are illustrated. Finally, we summarize the previous studies, and then compare the performance on different dataset.

Reducing network energy consumption and offering low-latency service quality have been the pursued goals in broadband passive optical networks (PONs). To realize these goals, energy-efficient dynamic bandwidth allocation (DBA) has been extensively studied. Nevertheless, few of these DBA schemes can effectively support low-latency and low-energy requirements, simultaneously. For these existing DBA schemes, the adopted energy-saving methods by sleeping some network elements would not handle the mismatch between the upstream and downstream bandwidth required by an optical network unit (ONU), which brings in a longer active window for each ONU and thus larger packet latencies. In this paper, an energy-efficient low-latency DBA scheme is proposed based on a novel pairwise combination (PWC) method. The essence of the PWC method is to compact the polling cycle length as much as possible by dynamically paring any two ONUs in complementary ways, which in turn also improves latency performance of data packets (i.e., quality of service (QoS)). Moreover, we introduce a multiple-state energy-saving mode into the proposed DBA scheme to reduce the PON energy consumption, with the consideration of both the upstream (US) and downstream (DS) transmissions. We establish an energy saving model for the proposed PWC-PON compared with the PONs with the existing DBA schemes, and also present a comprehensive M/G/1 queuing analysis with modification for the data latency performance. Extensive theoretical analysis and simulation results show that the proposed PWC-PON can reduce US and DS latency by 50% compared with the existing Gate Service (GS)-based DBA scheme. The energy saving efficiency is up to 3.5% higher than the benchmark when the US traffic load is light. It suggests that our PWC-based DBA scheme cannot only reduce the energy consumption, but also reduce the packet latency for PON system.

Girth plays an important role in the design of low-density parity-check (LDPC) codes. Motivated by the works on the girth of some classes of Tanner quasi-cyclic (QC) LDPC codes, e.g., Tanner (3, 5), (3, 7), (3, 11), and (5, 7) codes, we, in this paper, study the girth of Tanner $(J,L)$ QC-LDPC codes where $J$ and $L$ can be any two positive integers. According to the sufficient and necessary conditions for the existence of cycles of lengths 4, 6, 8, and 10, we propose an algorithm to determine the girth of Tanner $(J,L)$ QC-LDPC codes with finite code lengths. Through the analysis of the obtained girth values, we generalize the laws of the girth distributions of Tanner $(J,L)$ QC-LDPC codes. Furthermore, based on the exponent matrices of Tanner $(J,L)$ QC-LDPC codes with known girths, we employ the column selection method and/or the masking technique to construct binary/nonbinary LDPC codes. The numerical results show that the constructed LDPC codes have good performance under iterative decoding over the additive white Gaussian noise channel.

This paper investigates non-orthogonal multiple access (NOMA) system, where the near NOMA user is able to communicate with a base station (BS) directly while the far NOMA user needs to resort to a full-duplex (FD) relay. Wireless power transfer is applied to our system where the FD relay integrated with power splitting architecture can be powered wirelessly by the ambient radio signals simultaneously. Moreover, we assume that self-interference cancellation at the relay and inter-user interference cancellation at the near NOMA user are imperfect. For the purpose of maximizing the energy efficiency of the NOMA system, the power splitting ratio and transmit beamforming vectors are researched for the BS and relay with the guarantee of QoS requirements for two users. The formulated problem appears to be nonlinear fractional programming, which is highly nonconvex and the global optimality is hard to obtain. By introducing Charnes-Cooper's transformation and inner approximation method, we develop an iterative algorithm to gain the near optimal solution. The simulation results show that the proposed joint optimizing algorithm outperforms the existing scheme in terms of energy efficiency as well as the effect of SI cancellation on performance gain.

The vector approximate message passing (VAMP) soft frequency-domain equalizer (SFDE) has been proposed for turbo equalization. It consists of an inner soft equalizer (ISE) and an inner soft slicer (ISS), which iteratively exchange block-wise extrinsic information to improve the equalization performance, analogous to the outer turbo iteration between a soft equalizer and a soft decoder. However, a comparison of the VAMP-SFDE with other types of self-iterative SFDEs, including the self-iterative block-wise soft interference cancellation (SI-BSIC) SFDE and the generalized approximate message passing (GAMP) SFDE, is lacking. Moreover, comprehensive performance analysis for the VAMP-SFDE is yet to be performed. In this paper, relations among the VAMP-SFDE, the SI-BSIC-SFDE, and the GAMP-SFDE are first revealed. After that, the performance analysis is provided for the VAMP-SFDE and it leads to an improved semi-adaptive damping (SAD) scheme for maintaining the independence between the ISS and ISE. The resulting SAD-VAMP-SFDE shows improved mean square error (MSE) evolution curves compared with the original VAMP-SFDE. The SAD-VAMP-SFDE-based turbo equalization outperforms those using the SI-BSIC-SFDE or GAMP-SFDE and approaches the matched filter bound (MFB) over low signal-to-noise ratio region. To further demonstrate its superiority, the SAD-VAMP-SFDE is employed to enable a near-capacity transceiver design, which adopts the serial concatenation of an irregular convolutional code and a unity-rate code on the transmitter side.

Network virtualization has been widely considered to improve the resource efficiency of network infrastructure by allowing multiple virtual networks to coexist on a shared substrate network. With the exponential growth of Internet traffic, the network energy consumption incurs a considerable increase around the world. In this paper, we consider energy-aware virtual optical network embedding (EA-VONE) issue in flexible-grid elastic optical networks (EONs), while sliceable transponders (TPs) are assumed to be equipped in each node. First, an integer linear programming (ILP) model for the energy-minimized VONE is developed to optimally solve this problem. Due to the non-scalability of the ILP model, we then design two energy-saving policies for data centers (DCs) and TPs in the process of the node mapping and link mapping, respectively. Based on the two policies, two heuristic schemes are also developed: 1) DC-EA scheme, which only considers DC energy-saving in the node mapping procedure and 2) DC&TP-EA scheme, which simultaneously considers the energy-saving for both the DCs in the node mapping and TPs in the link mapping. Moreover, offline and online EA-VONE algorithms are developed. To investigate the benefits of the two energy-saving (i.e., DC-EA and DC&TP-EA) schemes, a benchmark scheme is also realized, which only maintains traffic-balancing (TB) policy without any energy-saving consideration. The simulation results indicate that our proposed DC&TP-EA scheme achieves the maximum power saving efficiency compared with the DC-EA and TB schemes. Also, in the DC-EA and DC&TP-EA schemes, the effect of DC energy saving is very remarkable when the traffic load is smaller. With the increase of traffic load, the DC energy saving may matter less, meanwhile, the TP energy-saving plays a more and more important role. Moreover, both the DC&TP-EA and DC-EA schemes maintain similar blocking performance as that of the TB scheme, which shows the superiority of our proposed schemes.

Temperature rise is an essential factor affecting the safety operation of electric machines. An appropriate solving domain is the first step to consider when calculating the temperature rise. However, the effect of solving domain setting on the calculation results of electric machine temperature rise has not been deeply discussed. In this paper, a 3MW permanent magnet wind generator is taken as an example. Based on the electrical and numerical heat transfer theories, two different solving domain models are established to compare the flow thermal characteristics of the internal and external ventilated paths. The fluid velocity changes in external ventilated path, the central section temperature rise and the velocity trace distribution of the internal ventilated path are compared in detail. Furthermore, the temperature rise of each component is analyzed. It is found that the fluid development in the generator is affected by solving domain selection. The results can provide a reference for accurate calculation of temperature rise of permanent magnet wind generator.

Once the motor stator winding is opened, balanced three-phase windings turn into unbalanced two-phases windings. Unfortunately, by conducting Clarke and Park transformation for open-phase PMSM, complete decoupling of the torque and flux cannot achieve. To maintain the rated torque, the two remained phase currents have to be modified as sinusoidal currents with 60° phase difference (not 120°). As a result, the current controller design becomes complicated. In order to solve this problem, a new fault tolerance method for the open-phase PMSM is proposed in this paper. It is designed based on a novel reference frame transformation. Through proposed frame transformation, the modified sinusoidal time-varying current commands are turned into dc variables in the redefined synchronous rotating frame. Hence, the design of the open-phase PMSM current controller can be simplified. This method can deal with different phase open fault and different current control mode (id = 0 or id =6 0 mode). In addition, considering that the neutral current ripple at usual switching frequencies may be very high, an optimal additional inductance that inserted into the neutral wire is designed. With the designed additional inductance, complete decoupling can be achieved. Experimental results confirm that the reliability and the performance of the PMSM drive can be improved distinctly with the proposed open-phase fault tolerance strategy.

To eliminate the ossification of optical infrastructure and adapt to the high-performance Internet applications, optical network virtualization is an important enabler to offer each application type a dedicated virtual optical network (VON). It can provide resource sharing for multiple VON requests on an optical infrastructure, and promise efficient use of network resources. In the paper, we first introduce a new concept of resource-virtualized elastic optical network (RvEON), which not only realizes link-tier spectrum virtualization in each substrate fiber link (SFL), but also node-tier virtualized transponders (vTPs) within each substrate node (SN). The RvEON can be considered as a very promising optical infrastructure for multiple VON requests. We then propose a novel integrated virtual optical network embedding (iVONE) scheme over RvEONs. For the iVONE, the node mapping and link mapping are performed in an integrated way, which is totally different from all existing two-phased VONE schemes. In the RvEONs, a novel integer linear programming (ILP) model is formulated, which additionally takes into account the subcarrier and modulator resource constraints of the virtualized TPs. Meanwhile, a novel routing, modulator, spectrum and subcarrier assignment (RMS2A) algorithm is designed to establish lightpaths for virtual link mapping in the RvEONs. The simulation results demonstrate that our proposed RMS2A algorithm achieves better performance than the existing benchmark two-phased algorithm. We also investigate the impact of bit-rates of the VON requests and the different configurations of various modulators that each vTP can offer on the network performances, respectively.

Selector is considered as a promising solution to solve sneak-path current for high-density 3-Dimensional (3D) memories. However, bidirectional selector with fast speed and long lifetime is still extremely needed. In this work, 2D material of graphene oxide containing epoxide, hydroxyl and carboxyl (-COOH, -OH, >C=O) is assembled with HfO2 to form a flexible bi-layer selector. Interestingly, the selector exhibits excellent uniformity, fast switching speed (~160 ns) and remarkable endurance of ~5×108 cycles. Moreover, no performance degradation is observed for more than 103 times with the bending radii ranging from 40 mm to 20 mm. The high uniformity and excellent endurance may be attributed to the insulating interface layer at the HfO2/GO interface, which plays a vital role on the connection/disrupt of conductive filament (CF). Thus, the incorporation of GO into HfO2 selector may be a feasible way to achieve a promising HfO2-based selector, which have potential applications in high-density 3D integration for flexible electronics.

With the development of communication technologies, many suspicious communication technologies have also been greatly improved. Therefore, one single monitor may not be able to afford in a monitoring process. In this paper, we propose a wireless communication system using two legitimate monitors for cooperative monitoring program, in which the signals sent by two monitors are respectively designed. One monitor is used as the cooperative relay, which is mainly used to improve the overall information transmission rate. The other monitor, which simultaneously receiving suspicious information and sending jamming signals, is used to ensure the successful eavesdropping process. Our purpose is to obtain the maximum eavesdropping rate by jointly design the transmit beamforming of two monitors. Two cases that the channel state information (CSI) is perfectly and imperfectly known by the monitors are considered. For the perfect CSI, several cases corresponding to the different conditions about the CSI from the suspicious transmitter to two monitors are discussed. In each case, a closed-form solution of the appropriate sending strategy is obtained, in which the physical meaning is also proposed. Then, for the imperfect CSI case, by employing the S-procedure method, we reformulate the robust beamforming design problem and solve it optimally. Finally, in the simulation results, the comparison between the cooperative monitoring scheme and the single monitoring scheme demonstrates that the proposed scheme is better in terms of eavesdropping rate.

This paper presents two types of protograph-based globally-coupled low-density parity-check (GC-LDPC) codes formed by a new edge spreading operation. This operation is called the global edge spreading. The Gaussian approximation (GA) and the protograph-based extrinsic information transfer (P-EXIT) analysis are then generalized over a special type of burst-erasure channels (BuECs). Such channel incorporates both Gaussian noise and burst erasures, and is denoted by the Gaussian channel with burst erasures (BuEC-G). Furthermore, the stability condition for BuECs-G is proved and an edge spreading optimization method is proposed to design the structured GC-LDPC codes by predicting the iterative decoding thresholds of corresponding protographs. Simulation results show that the optimized GC-LDPC codes can achieve better thresholds and error performances than existing well-designed GC-LDPC codes, and provide near-capacity performances over BuECs-G.

The classification in class imbalanced data has drawn significant interest in medical application. Most existing methods are prone to categorize the samples into the majority class, resulting in bias, in particular the insufficient identification of minority class. A kind of novel approach, class weights random forest is introduced to address the problem, by assigning individual weights for each class instead of a single weight. The validation test on UCI data sets demonstrates that for imbalanced medical data, the proposed method enhanced the overall performance of the classifier while producing high accuracy in identifying both majority and minority class.

Computer vision, which is used to detect and track a specific target in image sequences, has drawn great attention in recent years. The process of tracking can be formulated as a dynamic optimization problem that identifies the optimal position of the target in each image. Differential evolution (DE), who owns the advantages of simplicity, parallel computing, and self-adaptive search for global optimization, is envisioned as a promising algorithm to provide effective target tracking. In this paper, several improvements are made in DE for better adaptability in target tracking. Specifically, we introduce two inferior individuals into the mutation stage, which further enriches the diversity of the population and speeds up the offspring's evolution. We also proceed several image preprocessing and build an adaptive Gaussian mixture model of the target to deal with the complex tracking scenarios. Experimental results show that the designed tracking algorithm based on our improved DE demonstrates a higher tracking accuracy and faster tracking speed in several challenging tracking scenarios.

We propose a multiple-voting-based joint detection-decoding algorithm for nonbinary low-density parity-check (LDPC)-coded modulation systems. This algorithm is inspired from the reliability-based JDD algorithm for nonbinary LDPC-coded modulation systems, that has been proposed recently, in which the accumulated reliability of symbols based on one-step majority-logic decoding algorithm and the Chase-like local list decoding algorithm are used. However, the reliability-based JDD algorithm still has a significant performance degradation of at least 1 dB with low column weight (dv≤4). In order to reduce the performance degradation with low column weight, the proposed algorithm allows unfixed number of variable nodes to pass two symbols to the associated check node, in contrast with the reliability-based JDD algorithm, which allows only one variable node to pass two symbols to check node, when updating variable-to-check messages. Moreover, the votes are weighted differently according to the components of the list in the check-sum computation. Simulations show that the proposed algorithm yields better performance with low column weight, while still maintaining the low complexity feature.