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Crowd counting has received increasing attention in the field of video surveillance and urban security system. However, many previous models are prone to poor generalization capability to unknown samples when limited labeled samples are available. To improve or mitigate the above weakness, we develop a novel Pseudo-label Growth Dictionary Pair Learning (PG-DPL) method for crowd counting. To be exact, we treat crowd counting as a task of classification and leverage dictionary learning-based (DL) strategy to target the task. Considering that being short of diverse training samples and imbalanced distribution across different classes in crowd scene inevitably result in large prediction deviation caused by the DL model, we propose to apply pseudo-label growth (PG) and adaptive dictionary size (ADS) to improve the accuracy of crowd counting with limited labeled samples. In the proposed method, PG optimizes the initial prediction via reconstructing the discriminant term to improve the robustness of learned dictionary, while ADS explores the imbalanced distribution among different classes to adapt to the size of class-specific dictionary. Extensive validation experiments on five benchmark databases indicate that the proposed PG-DPL can achieve compelling performance compared to other state-of-the-art methods.

Coherent frequency diverse array (FDA) radar is able to cover all directions with a stable gain by transmitting a single frequency-shifted waveform. However, it is revealed in this work that the range resolution scales linearly with the number of elements, which is limited by the fixed element number. By leveraging the relationship between the beam direction and the signal frequency, we link the sub-bands of the emitted signal to angular sectors. Based on the fact, a novel transmit diversity technique, referred to as two-dimensional (2-D) space-time coding (STC), is proposed to improve the range resolution. For a specific observation direction, the frequency band of each pulse is shifted by STC to synthesize a full bandwidth after the pulse accumulation. Furthermore, the piecewise LFM (linear frequency modulation) waveform design can be combined with the STC technique to synthesize the transmit beampattern flexibly without range resolution degradation for each pulse. Compared with the state-of-the-art technologies, the proposed STC technique has superiorities in range resolution improvement, ultra-low range sidelobe level, interference suppression, and beampattern design capability. In addition, multi-dimensional ambiguity functions are derived to assess the performance in range-angle-Doppler domain, including the range and angle resolutions, the sidelobe level (SLL) and the angular coverage. To satisfy practical demands, the general receive processing procedures are also designed. The proposed method and corresponding theoretical analysis are verified by extensive numerical results.

In this Letter, the authors present a novel graph clustering-based method for crowd counting only using very limited labelled samples. Based on an intuitional observation that the distribution of low-level features of a specific scene containing the same or similar number of pedestrians are close to each other in the feature space, the authors adopt a first neighbour propagation (FNP) based clustering method to divide all unlabelled data into different groups. Next, an active sampling learning strategy that measures representativeness and diversity of the training data is used to obtain a few informative samples for annotation. Finally, the counts of those labelled informative samples are effectively propagated to predict the unlabelled samples in the constructed clusters by FNP-based clustering. The compelling results on two benchmark datasets demonstrate that the proposed method is not only effective to estimate crowd counts with very few labelled samples but also applicable to annotate a large number of unknown video frames for scene-specific crowd counting models.

Coherent frequency diverse array (FDA) can provide the full spatial illumination with a stable transmit gain by employing a single frequency-shifted waveform. However, the authors find that the range resolution is scaled linearly with the number of elements. In this work, the problem is first quantitatively analysed through mathematical derivation. To solve the issue, a subarray-based coherent FDA transmitting pulsed linear frequency modulation signals is proposed. The essence of the subaperture technique is to partition the transmit antenna array into multiple regular or irregular subarrays, wherein an identical carrier frequency is utilised in each subarray. Meanwhile, distinct carrier frequencies are adopted between subarrays. Moreover, the multi-dimensional ambiguity function is studied to assess the properties including the range resolution, spatial coverage and sidelobe level. Simulation results demonstrate that the proposed approach has superiorities in range resolution enhancement and range sidelobe reduction.

By transmitting a single frequency-shifted waveform, coherent frequency diverse array (FDA) can provide a simple way to realize full spatial coverages with stable gains. Owing to the range-angle dependency in coherent FDA, the authors implement a two-dimensional angle-time matched filter to perform equivalent transmit beamforming and matched filtering simultaneously. However, such filter structures merely control main-lobes of equivalent transmit beams towards target directions. It fails to form nulls at interference directions. Moreover, traditional adaptive beamforming by designing adaptive weight vectors are no longer applicable. Additionally, they find that the range resolution scales linearly with the element number. To tackle these issues, a space-time matched filter (STMF) in combination with the hybrid coding technique is proposed. Aiming at mitigating interferences, the STMF is designed with a formulation of quadratically constrained quadratic programing. By relaxation of quadratic constraints, the hard non-convex problem can be turned into the second-order cone programing to obtain optimal filter parameters. Furthermore, the hybrid coding technique is devised to jointly improve the range resolution. Numerical experiments of both two-dimensional range-angle outputs and one-dimensional range profiles via filtering are provided, which demonstrate that the STMF with hybrid coding can effectively suppress sidelobe interferences with a range resolution enhancement.

Background: This study explored the predictive value of postoperative C-reactive protein in children with hypospadias for postoperative complications and the risk factors.Methods: The clinical and follow-up data of 106 children with hypospadias who were treated with operations at Kunming Children's Hospital in 2020 were, respectively, analyzed. According to the occurrence of postoperative complications, the patients were divided into two groups: 25 patients with postoperative complications were the complications group, and 81 without postoperative complications were the control group. The baseline data, clinical characteristics, laboratory test indexes, and outcome of the two groups were collected. Receiver operating characteristic (ROC) was used to calculate the optimal cutoff value of C-reaction protein (CRP). Logistic regression was used to analyze the risk factors of hypospadias after surgery. A probability value (P) < 0.05 was considered statistically significant.Results: According to the result of the ROC curve, the optimal cutoff value of CRP was 11.7 mg/L. Logistic regression showed that the length of urethral defect, the urethral material, the operative produce, and the postoperative CRP level were related to the occurrence of postoperative complications of patients with DCC. The length of the urethral defect and the CRP level were the independent risk factors of the prognosis of hypospadias patients. The CRP level was related to the occurrence of postoperative complications and fistula.Conclusions: Postoperative CRP level can be used as a reliable marker for predicting the prognosis of hypospadias patients.

In transmit beampattern design, it is desirable to maximize the power around locations of interest. Multiple-input multiple-output (MIMO) radar transmits orthogonal waveforms, which is hardly achievable in practical applications. Moreover, the constant modulus constraint and the computational burden limit the system performance. In this paper, we propose an effective piecewise linear frequency modulation (PLFM) waveform for coherent frequency diverse array (FDA) radar to synthesize the desired transmit beampattern. By deriving the relationship between the beam direction and the transmit signal frequency, we find that different sub-band of transmitted signal corresponds to different angular sector. With the relationship between frequency band and mainlobe of beampattern, the beampattern synthesis is transformed into the design of waveform spectrum which is realized by designing the PLFM waveform in this paper. Compared with the state-of-the-art technique, the proposed PLFM waveform in coherent FDA enjoys the advantage of the constant modulus, low sidelobe level and reduced computation complexity. In addition, the multi-dimensional ambiguity function and the transmit beampattern response are derived to examine the properties. Numerical results are presented to validate the effectiveness of the proposed method.

ObjectiveTo analyze and compare the efficacy of contrast-enhanced ultrasound (CEUS) and magnetic resonance (MRI) in the diagnosis of difficult renal tumor with CT. MethodsA total of 136 patients with renal space occupying who received CEUS and MRI in the Second Affiliated Hospital of Kunming Medical University from January 2013 to December 2020 after improved abdominal enhanced CT was difficult to distinguish between benign and malignant patients were retrospectively analyzed. The diagnostic results of the two examination methods were compared with the pathological examination results to analyze the diagnostic efficacy of the two methods.Results61 cases were benign and 75 cases were malignant. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of CEUS, MRI and combined examination for the differential diagnosis of benign and malignant renal tumors difficult to be determined by CT were (CEUS:94.42%, 87.69%, 91.18%, 89.33%, 93.44%;MRI:81.63%, 91.84%, 85.29%, 94.67%, 73.77%;MRI+CEUS:94.67%, 93.44%, 92.65%, 94.67%, 93.44%). Comparison of the sensitivity of single and combined CEUS and MRI in the differential diagnosis of benign and malignant renal tumors that were difficult to be identified by CT: χ2=11.34, P =0.001, there was statistical significance; χ2=0.86, P =0.35, there was no statistical significance; χ2=5.73, P =0.02, between MRI and CEUS +CEUS.CEUS with single and combined MRI examination of CT qualitative differential diagnosis of benign and malignant renal tumors ROC curve shows that applied to the differential diagnosis of benign versus malignant tumor CT is qualitative the MRI + CEUS is better than that of CEUS, CEUS is better than that of MRI, the area under the curve comparison(accurate):MRI compar-ed with CEUC no statistical significance (p = 0.26), magnetic resonance imaging (MRI) and CEUS were compared with MRI + CEUS were statistically significant (p = 0.02, p = 0.01).Conclusion Both CEUS and MRI can be used to distinguish between benign and malignant renal tumors that are difficult to be characterized by CT. However, CEUS alone has more clinical application value in the diagnosis of benign and malignant renal tumors that are difficult to be characterized by CT considering economic effects, indications and side effects.

In a multiple-input multiple-output (MIMO) radar, it is desired to maximize the power radiation in an angular region of interest, which, however, is hardly achievable because a set of orthogonal waveforms is employed at the engineering. Different from traditional colocated MIMO radar, space-time coding array (STCA) transmits an identical waveform with a tiny time delay circulating across array elements. It can provide a simple way to achieve the full angular coverage with a stable gain. In this paper, a new scheme referred to as chirp-STCA is proposed to synthesize the desired beampattern flexibly. With the quantitative relationship between the time delay and the span of beam spreading, the transmit beampattern synthesis issue is converted to the design of time delay value which can be readily realized based on the framework of chirp-STCA. As a result, the desired angular sector coverage of the radiation power can be realized by setting a proper time delay. The proposed chirp-STCA can provide many desired features including low range sidelobe level, low computational complexity, and constant modulus. In addition, the range-angle properties are examined by analyzing the transmit beampattern response and the ambiguity function. Numerical results are presented to demonstrate the effectiveness and simplicity of the chirp-STCA scheme for the transmit beampattern synthesis.

Crowd counting is one of the most paramount tasks for safety and security. Many existing methods mainly focus on the predicted accuracy but ignore the efficiency, which hinders their applications in practice. Moreover, their performance heavily depends on the learning from a large number of labeled scene data, which is cost-expensive for crowd counting. In this paper, we present a novel crowd counting approach called semi-supervised manifold embedding (SSME) to address the above weaknesses. In the newly proposed method, we formulate the crowd counting as a semi-supervised classification problem and learn a linear mapping from the high-dimensional scene feature space to the low-dimension label space by simultaneously imposing the label fitness and the manifold smoothness, where the learned linear mapping facilitates the efficiency of crowd counting. In order to alleviate the issue that most supervised approaches to crowd counting require sufficient labeled data for improving the performance, we exploit the first neighbor propagation to select informative samples in the proposed SSME-based algorithm. Thorough validation experiments on three challenging benchmark datasets indicate that the proposed method is capable of achieving more impressive prediction accuracy on the number of pedestrians in a monitoring scene than other state-of-the-art competitors.

As a special type of coherent collocated Multiple-Input Multiple-Output (MIMO) radar, a circulating space-time coding array (CSTCA) transmits an identical waveform with a tiny time shift. It provides a simple way to achieve a full angular coverage with a stable gain and a low sidelobe level (SLL) in the range domain. In this paper, we address the problem of direction-of-arrival (DOA) estimation in CSTCA. Firstly, we design a novel two-dimensional space-time matched filter on receiver. It jointly performs equivalent transmit beamforming in the angle domain and waveform matching in the fast time domain. Multi-beams can be formed to acquire controllable transmit freedoms. Then, we propose a beamspace multiple signal classification (MUSIC) algorithm applicable in case of small training samples. Next, since targets at the same range cell show characteristics of coherence, we devise a transformation matrix to restore the rotational invariance property (RIP) of the receive array. Afterwards, we perform spatial smoothing in element domain based on the transformation. In addition, the closed-form expression of Cramer-Rao lower bound (CRLB) for angle estimation is derived. Theoretical performance analysis and numerical simulations are presented to demonstrate the effectiveness of proposed approaches.