Direct design of ground-state probabilistic logic using many-body interactions for probabilistic computing.

In this work, an innovative design model aimed at enhancing the efficacy of ground-state probabilistic logic with a binary energy landscape (GSPL-BEL) is presented. This model enables the direct conversion of conventional CMOS-based logic circuits into corresponding probabilistic graphical representations based on a given truth table. Compared to the conventional approach of solving the configuration of Ising model-basic probabilistic gates through linear programming, our model directly provides configuration parameters with embedded many-body interactions. For larger-scale probabilistic logic circuits, the GSPL-BEL model can fully utilize the dimensions of many-body interactions, achieving minimal node overhead while ensuring the simplest binary energy landscape and circumventing additional logic synthesis steps. To validate its effectiveness, hardware implementations of probabilistic logic gates were conducted. Probabilistic bits were introduced as Ising cells, and cascaded conventional XNOR gates along with passive resistor networks were precisely designed to realize many-body interactions. HSPICE circuit simulation results demonstrate that the probabilistic logic circuits designed based on this model can successfully operate in free, forward, and reverse modes, exhibiting the simplest binary probability distributions. For a 2-bit × 2-bit integer factorizer involving many-body interactions, compared to the logic synthesis approach, the GSPL-BEL model significantly reduces the number of consumed nodes, the solution space (in the free-run mode), and the number of energy levels from 12, 4096, and 9-8, 256, and 2, respectively. Our findings demonstrate the significant potential of the GSPL-BEL model in optimizing the structure and performance of probabilistic logic circuits, offering a new robust tool for the design and implementation of future probabilistic computing systems.

Framework for developing cost-effectiveness analysis threshold: the case of Egypt.

BACKGROUND: Cost-effectiveness analyses rarely offer useful insights to policy decisions unless their results are compared against a benchmark threshold. The cost-effectiveness threshold (CET) represents the maximum acceptable monetary value for achieving a unit of health gain. This study aimed to identify CET values on a global scale, provide an overview of using multiple CETs, and propose a country-specific CET framework specifically tailored for Egypt. The proposed framework aims to consider the globally identified CETs, analyze global trends, and consider the local structure of Egypt's healthcare system. METHODS: We conducted a literature review to identify CET values, with a particular focus on understanding the basis of differentiation when multiple thresholds are present. CETs of different countries were reviewed from secondary sources. Additionally, we assembled an expert panel to develop a national CET framework in Egypt and propose an initial design. This was followed by a multistakeholder workshop, bringing together representatives of different governmental bodies to vote on the threshold value and finalize the recommended framework. RESULTS: The average CET, expressed as a percentage of the gross domestic product (GDP) per capita across all countries, was 135%, with a range of 21 to 300%. Interestingly, while the absolute value of CET increased with a country's income level, the average CET/GDP per capita showed an inverse relationship. Some countries applied multiple thresholds based on disease severity or rarity. In the case of Egypt, the consensus workshop recommended a threshold ranging from one to three times the GDP per capita, taking into account the incremental relative quality-adjusted life years (QALY) gain. For orphan medicines, a CET multiplier between 1.5 and 3.0, based on the disease rarity, was recommended. A two-times multiplier was proposed for the private reimbursement threshold compared to the public threshold. CONCLUSION: The CET values in most countries appear to be closely related to the GDP per capita. Higher-income countries tend to use a lower threshold as a percentage of their GDP per capita, contrasted with lower-income countries. In Egypt, experts opted for a multiple CET framework to assess the value of health technologies in terms of reimbursement and pricing.

Efficient Data Transfer and Multi-Bit Multiplier Design in Processing in Memory.

Processing in Memory based on memristors is considered the most effective solution to overcome the Von Neumann bottleneck issue and has become a hot research topic. The execution efficiency of logical computation and in-memory data transmission is crucial for Processing in Memory. This paper presents a design scheme for data transmission and multi-bit multipliers within MAT (a data storage set in MPU) based on the memristive alternating crossbar array structure. Firstly, to improve the data transfer efficiency, we reserve the edge row and column of the array as assistant cells for OR AND (OA) and AND data transmission logic operations to reduce the data transfer steps. Furthermore, we convert the multipliers into multi-bit addition operations via Multiple Input Multiple Output (MIMO) logical operations, which effectively improves the execution efficiency of multipliers. PSpice simulation shows that the proposed data transmission and multi-bit multiplier solution has lower latency and power consumption and higher efficiency and flexibility.

Hard X-ray operation of X-ray gas monitors at the European XFEL.

X-ray gas monitors (XGMs) are operated at the European XFEL for non-invasive single-shot pulse energy measurements and average beam-position monitoring. The underlying measurement principle is the photo-ionization of rare gas atoms at low gas pressures and the detection of the photo-ions and photo-electrons created. These are essential for tuning and sustaining self-amplified spontaneous emission (SASE) operation, machine radiation safety, and sorting single-shot experimental data according to pulse energy. In this paper, the first results from XGM operation at photon energies up to 30 keV are presented, which are far beyond the original specification of this device. Here, the Huge Aperture MultiPlier (HAMP) is used for single-shot pulse energy measurements since the standard X-ray gas monitor detectors (XGMDs) do not provide a sufficient signal-to-noise ratio, even at the highest operating gas pressures. A single-shot correlation coefficient of 0.98 is measured between consecutive XGMs operated with HAMP, which is as good as measuring with the standard XGMD detectors. An intra-train non-linearity of the HAMP signal is discovered, and operation parameters to mitigate this effect are studied. The upper repetition rate limit of HAMP operation at 2.25 MHz is also determined. Finally, the possibilities and limits for future XGM operation at photon energies up to 50 keV are discussed.

Testing conditional quantile independence with functional covariate.

We propose a new non-parametric conditional independence test for a scalar response and a functional covariate over a continuum of quantile levels. We build a Cramer-von Mises type test statistic based on an empirical process indexed by random projections of the functional covariate, effectively avoiding the "curse of dimensionality" under the projected hypothesis, which is almost surely equivalent to the null hypothesis. The asymptotic null distribution of the proposed test statistic is obtained under some mild assumptions. The asymptotic global and local power properties of our test statistic are then investigated. We specifically demonstrate that the statistic is able to detect a broad class of local alternatives converging to the null at the parametric rate. Additionally, we recommend a simple multiplier bootstrap approach for estimating the critical values. The finite-sample performance of our statistic is examined through several Monte Carlo simulation experiments. Finally, an analysis of an EEG data set is used to show the utility and versatility of our proposed test statistic.

Design of efficient binary multiplier architecture using hybrid compressor with FPGA implementation.

In signal processing applications, the multipliers are essential component of arithmetic functional units in many applications, like digital signal processors, image/video processing, Machine Learning, Cryptography and Arithmetic & Logical units (ALU). In recent years, Profuse multipliers are there. In that, Vedic multiplier is one of the high-performance multiplications and it is used to signal/image processing applications. In order to ameliorate the performance of this multiplier further, by proposed a novel multiplier using hybrid compressor. The proposed hybrid compressor-based multiplier is designed and implemented in Field programmable Gate Array (FPGA-spartan 6). The synthesis result shows that the speed of proposed hybrid compressor-based multiplier gets improved as compared to Array multiplier (35.83%), Wallace tree multiplier (34.58%), Vedic Multiplier based on Carry look ahead adder (CLA) (28.49%), Vedic Multiplier based on Ripple carry adder (RCA) (20.65%), Booth Multiplication (21.65%) and Vedic Multiplication based on Han-Carlson Adder (HCA) (20.10%) and Hybrid multiplier using Carry Select Adder (CSELA) (17.81%) and Hybrid Vedic Multiplier (7.15%).

Emission characteristics of pulse CNT cold cathode X-ray source combined with channel electron multiplier.

Carbon nanotube (CNT)-based field emission X-ray source with the advantage of fast start-up response offers the chance to achieve high-frequency X-ray emission. In this study, a high-frequency random pulse X-ray source of CNT cold cathode combined with a channel electron multiplier (CEM) was built, and its direct current (DC) and pulse emission characteristics were tested. The DC measurement results were used for parameter selection for performing pulse experiments. During the DC test, with the conditions of 2.2 kV CEM bias voltage and 25 kV anode voltage, the anode currents are 141, 250, and 300 µA at grid voltages of 290, 387.6, and 432.2 V, respectively; the corresponding grid field values are 1.45, 1.94, and 2.16 V/µm. During the pulse test, the amplitude-frequency response of the X-ray source reaches 3.58 MHz at 3 dB. The developed pulse X-ray source was introduced into the X-ray communication (XCOM), and the experimental communication rate reached 6 Mbps with the bit-error-rate of 1.1 × 10-3. The developed high-frequency pulse CNT-CEM X-ray source has potential applications in XCOM, high-speed X-ray imaging, and other fields.

Extendable high gain low current/high pulse modified quadratic-SEPIC converter for water treatment applications.

Substantial attention has been drawn over the past few years by high step-up dc-dc converters owing to their applications in a wide range. Apart from renewable energy applications, high voltage/ high pulse converters are efficiently used in water treatment applications. The converter suggested a combination of Quadratic and SEPIC converters with a diode-capacitor cell. This topology generates high-voltage repetitive pulses with a single semiconductor switch and reduced component count. The stress across the components is less than the high-gain converters reported in the literature. The topology has an extendable feature by increasing the number of diode-capacitor cells without affecting the stress. The superiority of the high pulse generating topology is validated with a similar converter in the literature. This paper discusses the nL5 simulator results for the proposed rated topology required for water treatment. A scaled-down 50 W prototype is tested for various input voltages to generate high voltage pulse, and the analytical study is validated.

Cooperative Safe Trajectory Planning for Quadrotor Swarms.

In this paper, we propose a novel distributed algorithm based on model predictive control and alternating direction multiplier method (DMPC-ADMM) for cooperative trajectory planning of quadrotor swarms. First, a receding horizon trajectory planning optimization problem is constructed, in which the differential flatness property is used to deal with the nonlinear dynamics of quadrotors while we design a relaxed form of the discrete-time control barrier function (DCBF) constraint to balance feasibility and safety. Then, we decompose the original trajectory planning problem by ADMM and solve it in a fully distributed manner with peer-to-peer communication, which induces the quadrotors within the communication range to reach a consensus on their future trajectories to enhance safety. In addition, an event-triggered mechanism is designed to reduce the communication overhead. The simulation results verify that the trajectories generated by our method are real-time, safe, and smooth. A comprehensive comparison with the centralized strategy and several other distributed strategies in terms of real-time, safety, and feasibility verifies that our method is more suitable for the trajectory planning of large-scale quadrotor swarms.

scIALM: A method for sparse scRNA-seq expression matrix imputation using the Inexact Augmented Lagrange Multiplier with low error.

Single-cell RNA sequencing (scRNA-seq) is a high-throughput sequencing technology that quantifies gene expression profiles of specific cell populations at the single-cell level, providing a foundation for studying cellular heterogeneity and patient pathological characteristics. It is effective for developmental, fertility, and disease studies. However, the cell-gene expression matrix of single-cell sequencing data is often sparse and contains numerous zero values. Some of the zero values derive from noise, where dropout noise has a large impact on downstream analysis. In this paper, we propose a method named scIALM for imputation recovery of sparse single-cell RNA data expression matrices, which employs the Inexact Augmented Lagrange Multiplier method to use sparse but clean (accurate) data to recover unknown entries in the matrix. We perform experimental analysis on four datasets, calling the expression matrix after Quality Control (QC) as the original matrix, and comparing the performance of scIALM with six other methods using mean squared error (MSE), mean absolute error (MAE), Pearson correlation coefficient (PCC), and cosine similarity (CS). Our results demonstrate that scIALM accurately recovers the original data of the matrix with an error of 10e-4, and the mean value of the four metrics reaches 4.5072 (MSE), 0.765 (MAE), 0.8701 (PCC), 0.8896 (CS). In addition, at 10%-50% random masking noise, scIALM is the least sensitive to the masking ratio. For downstream analysis, this study uses adjusted rand index (ARI) and normalized mutual information (NMI) to evaluate the clustering effect, and the results are improved on three datasets containing real cluster labels.

Country-Wide Ecological Health Assessment Methodology for Air Toxics: Bridging Gaps in Ecosystem Impact Understanding and Policy Foundations.

Amid the growing concerns about air toxics from pollution sources, much emphasis has been placed on their impacts on human health. However, there has been limited research conducted to assess the cumulative country-wide impact of air toxics on both terrestrial and aquatic ecosystems, as well as the complex interactions within food webs. Traditional approaches, including those of the United States Environmental Protection Agency (US EPA), lack versatility in addressing diverse emission sources and their distinct ecological repercussions. This study addresses these gaps by introducing the Ecological Health Assessment Methodology (EHAM), a novel approach that transcends traditional methods by enabling both comprehensive country-wide and detailed regional ecological risk assessments across terrestrial and aquatic ecosystems. EHAM also advances the field by developing new food-chain multipliers (magnification factors) for localized ecosystem food web models. Employing traditional ecological multimedia risk assessment of toxics' fate and transport techniques as its foundation, this study extends US EPA methodologies to a broader range of emission sources. The quantification of risk estimation employs the quotient method, which yields an ecological screening quotient (ESQ). Utilizing Kuwait as a case study for the application of this methodology, this study's findings for data from 2017 indicate a substantial ecological risk in Kuwait's coastal zone, with cumulative ESQ values reaching as high as 3.12 × 103 for carnivorous shorebirds, contrasted by negligible risks in the inland and production zones, where ESQ values for all groups are consistently below 1.0. By analyzing the toxicity reference value (TRV) against the expected daily exposure of receptors to air toxics, the proposed methodology provides valuable insights into the potential ecological risks and their subsequent impacts on ecological populations. The present contribution aims to deepen the understanding of the ecological health implications of air toxics and lay the foundation for informed, ecology-driven policymaking, underscoring the need for measures to mitigate these impacts.

Analog Convolutional Operator Circuit for Low-Power Mixed-Signal CNN Processing Chip.

In this paper, we propose a compact and low-power mixed-signal approach to implementing convolutional operators that are often responsible for most of the chip area and power consumption of Convolutional Neural Network (CNN) processing chips. The convolutional operators consist of several multiply-and-accumulate (MAC) units. MAC units are the primary components that process convolutional layers and fully connected layers of CNN models. Analog implementation of MAC units opens a new paradigm for realizing low-power CNN processing chips, benefiting from less power and area consumption. The proposed mixed-signal convolutional operator comprises low-power binary-weighted current steering digital-to-analog conversion (DAC) circuits and accumulation capacitors. Compared with a conventional binary-weighted DAC, the proposed circuit benefits from optimum accuracy, smaller area, and lower power consumption due to its symmetric design. The proposed convolutional operator takes as input a set of 9-bit digital input feature data and weight parameters of the convolutional filter. It then calculates the convolutional filter's result and accumulates the resulting voltage on capacitors. In addition, the convolutional operator employs a novel charge-sharing technique to process negative MAC results. We propose an analog max-pooling circuit that instantly selects the maximum input voltage. To demonstrate the performance of the proposed mixed-signal convolutional operator, we implemented a CNN processing chip consisting of 3 analog convolutional operators, with each operator processing a 3 × 3 kernel. This chip contains 27 MAC circuits, an analog max-pooling, and an analog-to-digital conversion (ADC) circuit. The mixed-signal CNN processing chip is implemented using a CMOS 55 nm process, which occupies a silicon area of 0.0559 mm2 and consumes an average power of 540.6 µW. The proposed mixed-signal CNN processing chip offers an area reduction of 84.21% and an energy reduction of 91.85% compared with a conventional digital CNN processing chip. Moreover, another CNN processing chip is implemented with more analog convolutional operators to demonstrate the operation and structure of an example convolutional layer of a CNN model. Therefore, the proposed analog convolutional operator can be adapted in various CNN models as an alternative to digital counterparts.

A Method of Time Prediction in Epiphysiodesis for Limb Length Discrepancy Based On Multiplier.

Objectives: The most critical step in the calculation of final limb length discrepancy (LLD) is estimating the length of the short limb after skeletal maturity(Sm). Paley's multiplier method is a fast, convenient method for calculating Sm and LLD after skeletal maturity; nonetheless, the calculation of the process of Sm and LLD in acquired type cases is complex in contrast to congenital type in this method. Notwithstanding, the multiplier method uses a variable called "growth inhibition" for the calculation process in acquired type LLD; however, its mathematical proof has not been published yet. The present study aims to find out whether there is an alternative way to estimate the length of Sm and LLD in skeletal maturity without using growth inhibition (GI) and its complex calculation process in acquired type LLD. Methods: We used trigonometric equations to prove the GI concept and conducted proportionality analysis to calculate the length of short limbs and LLD in skeletal maturity without using GI. Results: Based on the results, the following proportionality can estimate the length of the short limb in skeletal maturity. (ΔLm/ΔL = ΔSm/ΔS). Conclusion: The GI concept can be proved trigonometrically; nonetheless, its numerical value is not necessary for estimating the length of the short limb in skeletal maturity. Instead, a simple proportionality analysis serves the purpose of calculation.

Ultrasonic Thickness Measurement Method and System Implementation Based on Sampling Reconstruction and Phase Feature Extraction.

The existing ultrasonic thickness measurement systems require high sampling frequencies for echo signal acquisition, leading to complex circuit designs and high costs. Moreover, extracting the characteristics of ultrasonic echo signals for accurate thickness measurement poses significant challenges. To address these issues, this paper proposes a method that utilizes conventional sampling frequencies to acquire high-frequency ultrasonic echo signals, overcoming the limitations of high-frequency data acquisition imposed by the Nyquist-Shannon sampling theorem. By employing an improved sampling reconstruction technique, the multi-cycle sampling signals are reconstructed and rearranged within a single cycle, effectively increasing the equivalent sampling frequency. Additionally, a combination of coarse estimation using fast Fourier transform (FFT) and precise phase extraction using the moving sine fitting algorithm is proposed for accurate thickness measurement, resolving the limitations of common thickness measurement methods such as peak detection, envelope detection, and Hilbert autocorrelation in terms of low measurement accuracy. Experimental results obtained from thickness measurements on 45 steel ultrasonic test blocks within the range of 3 mm to 20 mm indicate a measurement error of ±0.01 mm, while for thicknesses ranging from 1 mm to 50 mm, the measurement error is ±0.05 mm.

Exploring the impacts of local development initiatives on tourism: A case study analysis.

This study investigates the intricate relationship between local development initiatives and tourism, with a specific focus on their impacts. By utilizing input-output matrices and a survey-based vector of tourist expenditure, we calculate both direct and indirect effects using accounting multipliers. The study assesses the potential return on investment and the generation of future income resulting from a 2.3 million euros investment. Our findings illuminate the predominantly positive impacts of local development initiatives on tourism. We underscore the importance of strategic planning, community engagement, and sustainable practices in optimizing the benefits and addressing potential challenges associated with local development for tourism. While this research primarily emphasizes the positive aspects, it recognizes the need for a nuanced understanding of the multifaceted impacts. This study contributes to the existing literature by providing a comprehensive analysis of the intricate relationship between local development and tourism. The study's practical insights and recommendations are valuable for policymakers, local communities, and tourism stakeholders, guiding them toward adopting sustainable and inclusive development strategies that maximize the positive impacts of tourism.

Derivation of Ultra-High Gain Hybrid Converter Families for HASEL Actuators Used in Soft Mobile Robots.

This work proposes, analyzes, designs, and validates superior topologies of UHGH converters that are capable of supporting extremely large conversion ratios up to ∼2000× and output voltage up to ∼4-12 kV for future mobile soft robots from an input voltage as low as the range of a 1-cell battery pack. Thus, the converter makes soft robots standalone systems that can be untethered and mobile. The extremely large voltage gain is enabled by a unique hybrid combination of a high-gain switched magnetic element (HGSME) and a capacitor-based voltage multiplier rectifier (CVMR) that, together, achieve small overall size, efficient operation, and output voltage regulation and shaping with simple duty-cycle modulation. With superior performance, power density, and compact size, the UHGH converters prove to be a promising candidate for future untethered soft robots.

A Segmental 2D Readout Board Manufactured in Printed Circuit Board Technology for Gas Electron Multiplier Detectors.

The Gas Electron Multiplier (GEM) was introduced by Fabio Sauli in 1997. This technology is broadly used in current and planned High-Energy Physics (HEP) experiments. One of the key components of these detectors is a readout board, which collects charges amplified by GEM foils and transfers them to readout electronics. The commonly used Cartesian XY readout boards are manufactured from the same type of polyamide film used to produce the GEM foils. The manufacturing process utilizes a deep polyimide etching, similar to the Micro Chemical Vias (MCV) etching process, which is protected by patent. The material prepared in this way is glued onto a rigid substrate and mounted in a detector. The production process was developed at CERN, and the technology has been commercialized to a small extent. Consequently, only a few research centers have the ability to make dedicated readout strips readouts. GEM detectors are characterized by a segmented structure that allows the separation of an electron-multiplying structure from a readout. This feature enables the implementation of a new type of charge reading system without the need to interfere with the GEM foil system. A new approach is proposed to simplify production and reduce the costs of GEM detector readout boards. It is based on the concept of segmental readout structures that are manufactured in standard Printed Circuit Board (PCB) technology. The interconnectors and mountings are located on the back of the bottom, so it is possible to place the readout electronics behind the readout plate. The boards are designed in such a way that they can be panelized into a readout with a more extensive active area. The margin between PCBs is minimalized to approximately 200 µm, which is less than 1% of the 70 × 70 mm2 board area, so the active area is as big as possible. Therefore, this solution gives us the ability to further increase the size of a readout by adding additional segments, which reduces the cost of scaling up the detector size. A few research groups have suggested similar solutions that utilize PCB technology, but currently, only detectors with 1D zigzag readouts have been validated and used. The measurement results of other 2D (XY) redouts using PCB technology have not been presented. The measurements shown and discussed in this paper validated the proposed technology. X-ray radiographs were obtained, validating the ability to use this technology to manufacture readout boards for GEM detectors. In opposition to state-of-the-art readouts, the proposed solution can be manufactured by any PCB manufacturer without using MCV-patented technology. This gives the users flexibility in designing and ordering low-cost custom readouts.

Reconfigurable frequency multipliers based on graphene field-effect transistors.

Run-time device-level reconfigurability has the potential to boost the performance and functionality of numerous circuits beyond the limits imposed by the integration density. The key ingredient for the implementation of reconfigurable electronics lies in ambipolarity, which is easily accessible in a substantial number of two-dimensional materials, either by contact engineering or architecture device-level design. In this work, we showcase graphene as an optimal solution to implement high-frequency reconfigurable electronics. We propose and analyze a split-gate graphene field-effect transistor, demonstrating its capability to perform as a dynamically tunable frequency multiplier. The study is based on a physically based numerical simulator validated and tested against experiments. The proposed architecture is evaluated in terms of its performance as a tunable frequency multiplier, able to switch between doubler, tripler or quadrupler operation modes. Different material and device parameters are analyzed, and their impact is assessed in terms of the reconfigurable graphene frequency multiplier performance.

Unravelling the dynamics of human development and economic growth on crude oil production based on ARDL and NARDL models.

This paper estimates and establishes the causality between the Human Development Index (HDI), Gross Domestic Product (GDP), inflation and CO2 emissions on crude oil production (COP) in Cameroon from 1977 to 2019. To do so, the Augmented Dicky-Fuller and Zivot-Andrews stationarity tests, ARDL and NARDL modelling, as well as Toda-Yamamoto causality test are performed. Unlike previous studies on COP, this study incorporates the asymmetric impact (NARDL). The results indicate that CO2 emissions and GDP have a negative impact on COP in the long-run, while HDI and inflation have a positive impact in the short-run. GDP and HDI have a non-linear impact in the short run, while in the long-run inflation and CO2 emissions have a non-linear impact on COP. From these results, it is interesting to note that, in order to allow future generations to benefit from the oil windfall. The diversification of the Cameroonian economy, the control of inflation and the use of less polluting crude oil extraction technologies must be imperative.•A step-by-step procedure of the ARDL, NARDL and causality test is provided.•The multiplier effects of GDP, HDI, inflation and CO2 emissions on COP are simulated.•The impact of GDP and HDI on COP is non-linear.

Fast Trajectory Tracking Control Algorithm for Autonomous Vehicles Based on the Alternating Direction Multiplier Method (ADMM) to the Receding Optimization of Model Predictive Control (MPC).

In order to improve the real-time performance of the trajectory tracking of autonomous vehicles, this paper applies the alternating direction multiplier method (ADMM) to the receding optimization of model predictive control (MPC), which improves the computational speed of the algorithm. Based on the vehicle dynamics model, the output equation of the autonomous vehicle trajectory tracking control system is constructed, and the auxiliary variable and the dual variable are introduced. The quadratic programming problem transformed from the MPC and the vehicle dynamics constraints are rewritten into the solution of the ADMM form, and a decreasing penalty factor is used during the solution process. The simulation verification is carried out through the joint simulation platform of Simulink and Carsim. The results show that, compared with the active set method (ASM) and the interior point method (IPM), the algorithm proposed in this paper can not only improve the accuracy of trajectory tracking, but also exhibits good real-time performance in different prediction time domains and control time domains. When the prediction time domain increases, the calculation time shows no significant difference. This verifies the effectiveness of the ADMM in improving the real-time performance of MPC.