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To address the issue of suboptimal spectral purity in Direct Digital Frequency Synthesis (DDFS) within resource-constrained environments, this paper proposes an optimized DDFS technique based on cubic Hermite interpolation. Initially, a DDFS hardware architecture is implemented on a Field-Programmable Gate Array (FPGA); subsequently, essential interpolation parameters are extracted by combining the derivative relations of sine and cosine functions with a dual-port Read-Only Memory (ROM) structure using the cubic Hermite interpolation method to reconstruct high-fidelity target waveforms. This approach effectively mitigates spurious issues caused by amplitude quantization during the DDFS digitalization process while reducing data node storage units. Moreover, this paper introduces single-quadrant ROM compression technology to further diminish the required storage space. Experimental results indicate that, compared to traditional DDFS methods, the optimization scheme proposed in this work achieves a ROM resource compression ratio of 1792:1 and a 14-bit output Spurious-Free Dynamic Range (SFDR) of −88.134 dBc, effectively enhancing amplitude quantization precision and significantly lowering spurious levels. This significantly improves amplitude quantization precision and reduces spurious levels. The proposed scheme demonstrates notable advantages in both spectral performance and resource utilization efficiency, making it highly suitable for resource-constrained embedded systems and high-performance applications such as radar and communication systems. [ABSTRACT FROM AUTHOR]

In order to solve the problem of the low end positioning accuracy of large hydraulic rock drilling robotic arms due to machining error and the working environment, this paper proposes an end positioning error compensation method based on an Improved Secretary Bird Optimization Algorithm (ISBOA) optimized Back Propagation (BP) neural network. Firstly, the good point set strategy is used to initialize the secretary bird population position to make the initial population distribution more uniform and accelerate the convergence speed of the algorithm. Then, the ISBOA is used to optimize the initial weights and biases of the BP neural network, which effectively overcomes the defect of the BP neural network falling into a local optimum. Finally, by establishing the mapping relationship between the joint value of the robot arm and the end positioning error, the error compensation is realized to improve the positioning accuracy of the rock drilling robot arm. The experimental results show that the average positioning error of the rock drilling robotic arm is reduced from 187.972 mm to 28.317 mm, and the positioning accuracy is improved by 84.94%, which meets the engineering requirements. [ABSTRACT FROM AUTHOR]

In order to effectively improve the resistance adjustment accuracy and efficiency of the laser resistor trimming machine, a measurement and control system of laser resistance trimming machine was designed. By detecting the change of resistance value in the process of resistance adjustment, the laser action was effectively controlled to realize the etching of the resistance. In this scheme, advanced RISC machine (ARM) was used as the main controller to realize communication with the host computer, resistance data acquisition and calculation, and comparator output. The constant current source circuit, signal conditioning circuit and data acquisition circuit were constructed with the Kelvin resistance method. The rapid switching of the measurement channel was realized by designing an extensible relay array, which effectively guaranteed the rapid resistance adjustment of the laser resistor trimming machine. The hardware circuit directly output the TTL signal to control the laser action, so as to realize the etching of the target resistance and ensure the resistance adjustment accuracy and efficiency. The experimental results show that the measurement accuracy of resistance is up to 0.01%, the adjustment accuracy is up to 0.1%, and the fastest speed of adjustment is 50/s. [ABSTRACT FROM AUTHOR]

In order to reduce the high frequency noise in voltage acquisition signal effectively, the voltage acquisition module with adjustable finite impulse response (FIR) filter parameters was designed. FIR digital filter was applied in this acquisition module to filter out the high frequency noise in the acquisition signal based on the advanced RISC machine (ARM) and field programmable gate array (FPGA) hardware platform. The filter coefficients were calculated and generated by ARM automatically according to the filter parameters such as sampling frequency and cut-off frequency. The improved structure of direct filter was adopted by FPGA. The filter structure was adjusted according to filter parameters. The calculation of filter coefficient and acquired data was completed. The parameter adjustable FIR filter was realized by ARM and FPGA work together. The experimental results show that the voltage acquisition module has high voltage acquisition accuracy and its maximum acquisition relative error absolute value is 0. 22%. The module can automatically complete the calculation of FIR filter coefficient and adjust the filter structure according to the set filter parameters. The high-frequency noise in the signal is filtered out effectively at the same time of signal acquisition. [ABSTRACT FROM AUTHOR]

Background: Many locally advanced rectal cancer (LARC) patients can benefit from neoadjuvant chemotherapy (NACT), with some achieving a pathological complete response (pCR). However, there is limited research reporting on the value of intravoxel incoherent motion (IVIM) in monitoring pCR in patients with LARC.Purpose: To identify whether IVIM parameters derived from whole-tumor volume (WTV) before and after NACT could accurately assess pCR in patients with LARC.Study Type: Prospective patient control study.Population: Fifty-one patients with LARC before and after NACT, prior to surgery.Field Strength/sequence: IVIM-diffusion imaging at 3T.Assessment: Apparent diffusion coefficient (ADC), slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion-related diffusion fraction (f) values were obtained on diffusion-weighted magnetic resonance images (DW-MRI) using WTV methods and calculated using a biexponential model before and after NACT.Statistical Tests: DWI-derived ADC and IVIM-derived parameters and their percentage changes (ΔADC%, ΔD%, ΔD*%, and Δf%) were compared using independent-samples t-test and Mann-Whitney U-test between the pCR and non-pCR groups. The diagnostic performance of IVIM parameters and their percentage changes were evaluated using receiver operating characteristic curves.Results: Compared with the non-pCR group, the pCR group exhibited significantly lower pre-ADCmean (P = 0.003) and pre-D values (P = 0.024), and significantly higher post-f (P = 0.002), ΔADCmean % (P = 0.002), ΔD% (P = 0.001), and Δf% values (P = 0.017). Receiver operating characteristic curves showed that the pre-D value had the best specificity (95.12%) and accuracy (86.27%) in predicting the pCR status, and ΔD% had the highest area under the curve (0.832) in assessing the pCR response to NACT.Data Conclusions: The IVIM-derived D value is a promising tool in predicting the pCR status before therapy. The percentage changes in D values after therapy may help assess the pCR status prior to surgery.Level Of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017. [ABSTRACT FROM AUTHOR]