Graphics processing unit accelerating compressed sensing photoacoustic computed tomography with total variation

Photoacoustic computed tomography with compressed sensing (CS-PACT) is a commonly used imaging strategy for sparse-sampling PACT. However, it is very time-consuming because of the iterative process involved in the image reconstruction. In this paper, we present a graphics processing unit (GPU)-based parallel computation framework for total-variation-based CS-PACT and adapted into a custom-made PACT system. Specifically, five compute-intensive operators are extracted from the iteration algorithm and are redesigned for parallel performance on a GPU. We achieved an image reconstruction speed 24–31 times faster than the CPU performance. We performed in vivo experiments on human hands to verify the feasibility of our developed method

A Spatial Sigma-Delta Approach to Mitigation of Power Amplifier Distortions in Massive MIMO Downlink

In massive multiple-input multiple-output (MIMO) downlink systems, the physical implementation of the base stations (BSs) requires the use of cheap and power-efficient power amplifiers (PAs) to avoid high hardware cost and high power consumption. However, such PAs usually have limited linear amplification ranges. Nonlinear distortions arising from operation beyond the linear amplification ranges can significantly degrade system performance. Existing approaches to handle the nonlinear distortions, such as digital predistortion (DPD), typically require accurate knowledge, or acquisition, of the PA transfer function. In this paper, we present a new concept for mitigation of the PA distortions. Assuming a uniform linear array (ULA) at the BS, the idea is to apply a Sigma-Delta ($\Sigma \Delta$) modulator to spatially shape the PA distortions to the high-angle region. By having the system operating in the low-angle region, the received signals are less affected by the PA distortions. To demonstrate the potential of this spatial $\Sigma \Delta$ approach, we study the application of our approach to the multi-user MIMO-orthogonal frequency division modulation (OFDM) downlink scenario. A symbol-level precoding (SLP) scheme and a zero-forcing (ZF) precoding scheme, with the new design requirement by the spatial $\Sigma \Delta$ approach being taken into account, are developed. Numerical simulations are performed to show the effectiveness of the developed $\Sigma \Delta$ precoding schemes

VerilogEval: Evaluating Large Language Models for Verilog Code Generation

The increasing popularity of large language models (LLMs) has paved the way for their application in diverse domains. This paper proposes a benchmarking framework tailored specifically for evaluating LLM performance in the context of Verilog code generation for hardware design and verification. We present a comprehensive evaluation dataset consisting of 156 problems from the Verilog instructional website HDLBits. The evaluation set consists of a diverse set of Verilog code generation tasks, ranging from simple combinational circuits to complex finite state machines. The Verilog code completions can be automatically tested for functional correctness by comparing the transient simulation outputs of the generated design with a golden solution. We also demonstrate that the Verilog code generation capability of pretrained language models could be improved with supervised fine-tuning by bootstrapping with LLM generated synthetic problem-code pairs.Comment: ICCAD 2023 Invited Pape

Three-way Imbalanced Learning based on Fuzzy Twin SVM

Three-way decision (3WD) is a powerful tool for granular computing to deal with uncertain data, commonly used in information systems, decision-making, and medical care. Three-way decision gets much research in traditional rough set models. However, three-way decision is rarely combined with the currently popular field of machine learning to expand its research. In this paper, three-way decision is connected with SVM, a standard binary classification model in machine learning, for solving imbalanced classification problems that SVM needs to improve. A new three-way fuzzy membership function and a new fuzzy twin support vector machine with three-way membership (TWFTSVM) are proposed. The new three-way fuzzy membership function is defined to increase the certainty of uncertain data in both input space and feature space, which assigns higher fuzzy membership to minority samples compared with majority samples. To evaluate the effectiveness of the proposed model, comparative experiments are designed for forty-seven different datasets with varying imbalance ratios. In addition, datasets with different imbalance ratios are derived from the same dataset to further assess the proposed model's performance. The results show that the proposed model significantly outperforms other traditional SVM-based methods

Development of social enterprises in rural island tourism in China = 中国海岛乡村旅游的社会企业发展

This paper discussed the major development stages of social enterprises (SEs) in rural island tourism in China. The authors established a conceptual framework with which to analyze the key factors affecting development under the context of Chinese social and economic institution. Informed by the SE life cycle model, the study adopted a case study approach with the Boxue Eco Village on Hainan Island as the case. Data were collected through in-depth interviews, focus group interviews, and observations. Institutional characteristics at every stage, including entrepreneurial, collectivity, standardization, and refinement, were analyzed. Based on the specificity of SE of rural tourism in this case, the authors summarized the influencing factors that shaped the development process of the enterprises. First-hand data were collected through interviews with entrepreneurs, management staff, villagers, and other stakeholders. The model was modified according to the research results, and provides a more integrated model suitable for SEs in Chinese islands. This study established a conceptual framework with which to analyze the development process of SEs in rural tourism within the institutional context of China. This framework could be applied to understand the substantial development of emerging SEs in China. = 本文讨论了中国海岛的乡村旅游中，社会企业发展的主要阶段。作者构建了一个概念模型，分析在中国社会经济制度条件下，影响社会企业的发展因素。结合社会企业生命周期模型，本研究以海南岛博学生态村为案例，通过深度访谈，焦点小组访和实地观察采集数据，展开分析。分析了包括创业、集体、标准化、精细化每个阶段的制度性特征。根据案例中的乡村旅游社会企业的特殊性，作者归纳了影响社会企业发展进程的影响因素。本研究通过对企业家、管理者、村民和其他利益相关者的访谈采集了一手数据。根据研究结果调整了理论模型并且提出了更加适合中国海岛乡村旅游社会企业的整合模型。本项研究为中国制度环境下的乡村旅游中，社会企业的发展建立了一个概念框架。该框架可以帮助人们理解新兴的中国社会企业的发展本质