Automatic Generation of High-Coverage Tests for RTL Designs using Software Techniques and Tools

Register Transfer Level (RTL) design validation is a crucial stage in the hardware design process. We present a new approach to enhancing RTL design validation using available software techniques and tools. Our approach converts the source code of a RTL design into a C++ software program. Then a powerful symbolic execution engine is employed to execute the converted C++ program symbolically to generate test cases. To better generate efficient test cases, we limit the number of cycles to guide symbolic execution. Moreover, we add bit-level symbolic variable support into the symbolic execution engine. Generated test cases are further evaluated by simulating the RTL design to get accurate coverage. We have evaluated the approach on a floating point unit (FPU) design. The preliminary results show that our approach can deliver high-quality tests to achieve high coverage

Performance Analysis of Discrete-Phase-Shifter IRS-aided Amplify-and-Forward Relay Network

As a new technology to reconfigure wireless communication environment by signal reflection controlled by software, intelligent reflecting surface (IRS) has attracted lots of attention in recent years. Compared with conventional relay system, the relay system aided by IRS can effectively reduce the cost and energy consumption, and significantly enhance the system performance. However, the phase quantization error generated by IRS with discrete phase shifter may degrade the receiving performance of the receiver. To analyze the performance loss caused by IRS phase quantization error, based on the law of large numbers and Rayleigh distribution, the closed-form expressions for the signal-to-noise ratio (SNR) performance loss and achievable rate of the IRS-aided amplify-and-forward (AF) relay network, which are related to the number of phase shifter quantization bits, are derived under the line-of-sight (LoS) channels and Rayleigh channels, respectively. Moreover, their approximate performance loss closed-form expressions are also derived based on the Taylor series expansion. Simulation results show that the performance losses of SNR and achievable rate decrease with the number of quantization bits increases gradually. When the number of quantization bits is larger than or equal to 3, the SNR performance loss of the system is smaller than 0.23dB, and the achievable rate loss is less than 0.04bits/s/Hz, regardless of the LoS channels or Rayleigh channels

Three Efficient Beamforming Methods for Hybrid IRS plus AF Relay-aided Metaverse

In this paper, an optimization problem is formulated to maximize signal-to-noise ratio (SNR) by jointly optimizing the beamforming matrix at AF relay and the reflecting coefficient matrices at IRS subject to the constraints of transmit power budgets at the base station (BS)/AF relay/hybrid IRS and that of unit-modulus for passive IRS phase shifts. To achieve high rate performance and extend the coverage range, a high-performance method based on semidefinite relaxation and fractional programming (HP-SDR-FP) algorithm is presented. Due to its extremely high complexity, a low-complexity method based on successive convex approximation and FP (LC-SCA-FP) algorithm is put forward. To further reduce the complexity, a lower-complexity method based on whitening filter, general power iterative and generalized Rayleigh-Ritz (WF-GPI-GRR) is proposed, where different from the above two methods, it is assumed that the amplifying coefficient of each active IRS element is equal, and the corresponding analytical solution of the amplifying coefficient can be obtained according to the transmit powers at AF relay and hybrid IRS. Simulation results show that the proposed three methods can greatly improve the rate performance compared to the existing technology-aided metaverse, such as the passive IRS plus AF relay-aided metaverse and only AF relay-aided metaverse. In particular, a 50.0% rate gain over the existing technology-aided metaverse is approximately achieved in the high power budget region of hybrid IRS. Moreover, it is verified that the proposed three efficient beamforming methods have an increasing order in rate performance: WF-GPI-GRR, LC-SCA-FP and HP-SDR-FP

Robust watermarking algorithm for medical volume data in internet of medical things

The advancement of 5G technology, big data and cloud storage has promoted the rapid development of the Internet of Medical Things (IoMT). Based on the strict security requirements and high level of accuracy required for disease diagnosis and pathological analysis, 3D medical volume data have been created in large numbers. The IoMT facilitates the rapid transfer of medical information and also makes the protection of pathological information and privacy information of patients increasingly prominent. To solve the security problem, a robust zero-watermarking algorithm based on 3D hyperchaos and 3D dual-tree complex wavelet transform is proposed according to the selected feature of medical volume data. The feature combines human visual features with improved perceptual hashing techniques. It is a robust and efficient binary sequence. When implementing the proposed algorithm, the watermark is first scrambled with 3D hyperchaos to enhance security. Then, 3D DTCWT-DCT transformation is applied to medical volume data, and the low-frequency coefficients that can represent the features are selected and binarized to generate the secret key to complete the watermark embedding and extraction. Zero embedding and blind extraction ensure that the original medical volume data is not altered in any form, which meets the special requirements for diagnosis. Simulation results show that the algorithm is robust and can effectively resist common attacks and geometric attacks. It used fewer robust features to effectively bound medical volume data and watermark information, saved bandwidth, and satisfied the security of transmission and storage of medical volume data in the Internet of medical things. In particular, compared with state-of-the-art technology, the proposed algorithm improves the average NC value by 46.67% under geometric attacks

Robust and secure zero-watermarking algorithm for medical images based on Harris-SURF-DCT and chaotic map

To protect the patient information in medical images, this article proposes a robust watermarking algorithm for medical images based on Harris-SURF-DCT. First, the corners of the medical image are extracted using the Harris corner detection algorithm, and then, the previously extracted corners are described using the method of describing feature points in the SURF algorithm to generate the feature descriptor matrix. *en, the feature descriptor matrix is processed through the perceptual hash algorithm to obtain the feature vector of the medical image, which is a binary feature vector with a size of 32 bits. Secondly, to enhance the security of the watermark information, the logistic map algorithm is used to encrypt the watermark before embedding the watermark. Finally, with the help of cryptography knowledge, third party, and zero-watermarking technology, the algorithm can embed the watermark without modifying the medical image. When extracting the watermark, the algorithm can extract the watermark from the test image without the original image. In addition, the algorithm has strong robustness to conventional attacks and geometric attacks. Especially under geometric attacks, the algorithm performs better

Robust zero watermarking algorithm for medical images based on Zernike-DCT

Digital medical system not only facilitates the storage and transmission of medical information but also brings information security problems. Aiming at the security of medical images, a robust zero watermarking algorithm for medical images based on Zernike-DCT is proposed. *e algorithm first uses a chaotic logic sequence to preprocess and encrypt the watermark, then performs edge detection and Zernike moment processing on the original medical image to get the accurate edge points, and then performs discrete cosine transform (DCT) on them to get the feature vector. Finally, it combines perceptual Hash and zero watermark technology to generate the key to complete the watermark embedding and extraction. *e algorithm has good robustness to conventional and geometric attacks, strong antinoise ability, high positioning accuracy, and processing efficiency and is superior to the classical edge detection algorithm in extraction effect. It is a stable and reliable image edge detection algorithm

Development of a prognostic nomogram and risk stratification system for upper thoracic esophageal squamous cell carcinoma

BackgroundThe study aimed to develop a nomogram model to predict overall survival (OS) and construct a risk stratification system of upper thoracic esophageal squamous cell carcinoma (ESCC).MethodsNewly diagnosed 568 patients with upper ESCC at Fujian Medical University Cancer Hospital were taken as a training cohort, and additional 155 patients with upper ESCC from Sichuan Cancer Hospital Institute were used as a validation cohort. A nomogram was established using Cox proportional hazard regression to identify prognostic factors for OS. The predictive power of nomogram model was evaluated by using 4 indices: concordance statistics (C-index), time-dependent ROC (ROCt) curve, net reclassification index (NRI) and integrated discrimination improvement (IDI).ResultsIn this study, multivariate analysis revealed that gender, clinical T stage, clinical N stage and primary gross tumor volume were independent prognostic factors for OS in the training cohort. The nomogram based on these factors presented favorable prognostic efficacy in the both training and validation cohorts, with concordance statistics (C-index) of 0.622, 0.713, and area under the curve (AUC) value of 0.709, 0.739, respectively, which appeared superior to those of the American Joint Committee on Cancer (AJCC) staging system. Additionally, net reclassification index (NRI) and integrated discrimination improvement (IDI) of the nomogram presented better discrimination ability to predict survival than those of AJCC staging. Furthermore, decision curve analysis (DCA) of the nomogram exhibited greater clinical performance than that of AJCC staging. Finally, the nomogram fairly distinguished the OS rates among low, moderate, and high risk groups, whereas the OS curves of clinical stage could not be well separated among clinical AJCC stage.ConclusionWe built an effective nomogram model for predicting OS of upper ESCC, which may improve clinicians’ abilities to predict individualized survival and facilitate to further stratify the management of patients at risk