基于软件无线电平台的调频终端设计

介绍了基于DSP/FPGA混合架构的小型软件无线电平台,运用模块化设计方法设计了基于该平台的调频终端,详细阐述了调制和解调算法的实现。测试结果表明,基于软件无线电平台的调频终端能实现预期的发射和接收功能,具有便于部署、功能易扩展和易于升级等优势。     

高集成RDS调频收音模块设计

主要介绍基于便携式设备的RDS调频收音模块的设计,着重讲述了有关FM接收、RDS数据接收与音频处理等方面的应用电路。     

基于GATE的油田信息抽取技术研究

针对目前国内油田信息抽取系统中文信息抽取不准确的现状,提出了更为准确的基于油田的中文信息抽取的解决方案。在GA T E框架下,开发中文信息抽取插件,解决了基于油田的中文分词、中文语料词表和中文命名实体识别,并在企业实际中进行了应用,取得了较好的应用效果,并为后续的油田信息抽取技术研究提供了研究基础。     

带式输送机滚筒温度检测装置设计

针对传统带式输送机滚筒温度检测方法存在布线困难、测量误差大等问题,设计了一种基于射频通信的带式输送机滚筒温度检测装置。该装置检测终端采用集成温度检测与射频发射功能的轮胎压力传感器芯片SP370,定时采集温度数据并通过射频通信发送给由射频接收芯片、单片机和CAN收发器组成的接收终端,接收终端将接收到的温度数据发送到CAN总线上。测试结果表明,该装置测量误差为±3.73℃,单个纽扣电池可为检测终端连续供电1.5a以上,满足现场应用要求。     

一种新型射频智能报警器的设计

给出了一种基于射频技术的智能报警器的设计方法:该报警器采用NRF401为发射和接收芯片,配以高速处理芯片P89LPC930和高精度A/D,实现了报警信号采集和处理的智能化,并给出了部分硬件电路和软件设计流程图。该报警器应用范围广,有广阔的应用前景。     

调频连续波SAR数字接收机技术研究

针对调频连续波合成孔径雷达系统误差提取和校正困难的问题,提出了一种基于数字接收机的调频连续波合成孔径雷达系统方案.分析了去调频接收模式下调频连续波合成孔径雷达的回波特性,研究了系统误差对回波信号的影响,推导了在数字时域对回波信号进行正交解调、去调频接收处理以及系统误差提取的实现过程.数字接收处理的方法可以简单有效地提取系统的幅相误差,并进行校正.最后,通过实验仿真证明了该方法的有效性和正确性.     

基于自主加密芯片的智能家居控制系统设计

提出了一种智能家居控制系统，该系统基于自主加密芯片，包括控制单元、加密芯片和连接单元。控制单元用于连接控制终端以接收来自控制终端的指令和数据，连接单元用于连接智能家居设备终端以输出控制指令。加密芯片用于将控制单元接收的来自控制终端的指令及数据加密后发送至连接单元。加密芯片由主控芯片和与之连接的算法协处理单元组成，算法协处理单元采用FPGA芯片，为主控芯片提供加密算法。通过在家居中设置不同类型的密钥对，并根据用户需要选择相应的密钥进行加密，从而保证了密钥的保密性和完整性。该智能家居控制系统采用基于自主加密芯片的技术，实现了更加多样化的加密算法，从而显著提升了系统的安全性。     

应用TEA5767的调频收音电路设计

主要介绍调频广播接收芯片TEA5767在便携式video播放器中的应用．着重讲述了有关的FM接收、音频处理等方面的应用电路。     

基于AN7218的超声波接收电路设计

针对现有超声波接收电路前级放大结构复杂、噪声较大、成本较高的缺点,提出了一种基于调频、调幅中频放大器AN7218的超声波接收电路。通过FM与AM中频放大器对超声传感器的回波信号进行低噪声前置放大,电路适用于各种中频超声波接收电路。实验表明,电路设计简单、性能稳定、价格低廉,具有广阔的应用前景。     

信息名址：“叫好”之后

6月18日，工业和信息化部电信研究院（CATR）与全球顶级域名（．mobi）管理有限公司dotMobi签署了战略合作协议。根据合作内容，双方将可受理全球中文．mobim户的业务申请，覆盖全球华人地区，同时用户还可使用中文信息名址在手机终端上快捷地访问移动互联网。     

Some q-rung orthopair fuzzy maclaurin symmetric mean operators and their applications to potential evaluation of emerging technology commercialization

The Maclaurin symmetric mean (MSM) operator is a classical mean type aggregation operator used in modern information fusion theory, which is suitable to aggregate numerical values. The prominent characteristic of the MSM operator is that it can capture the interrelationship among the multi-input arguments. In this paper, we extend the MSM operator and dual MSM operator to q-rung orthopair fuzzy sets to propose the q-rung orthopair fuzzy MSM operator, q-rung orthopair fuzzy dual MSM operator, q-rung orthopair fuzzy weighted MSM operator, and q-rung orthopair fuzzy weighted dual MSM operator. Then, some desirable properties and special cases of these operators are discussed in detail. Finally, a numerical example is provided to illustrate the feasibility of the proposed methods and deliver the sensitivity analysis and comparative analysis.     

An extended COPRAS method for multiattribute group decision making based on dual hesitant fuzzy Maclaurin symmetric mean

The well-known Maclaurin symmetric mean (MSM) and the dual MSM (DMSM) are introduced as important operators to handle multiattribute group decision making (MAGDM) information. The MSM and the DMSM operators have the prominent characteristic of accurately describing the interdependence of multi-input arguments. Due to their advantage, we extend the MSM and the DMSM into the dual hesitant fuzzy environment to aggregate uncertain information. Particularly, we propose some novel aggregation operators, namely dual hesitant fuzzy MSM, weighted dual hesitant fuzzy MSM, dual hesitant fuzzy dual MSM, and weighted dual hesitant fuzzy dual MSM operators. Moreover, we study some properties and special remarks regarding different values of the parameter. With an extension of the complex proportional assessment method, we formulate a new approach for the dual hesitant fuzzy MAGDM. Finally, we test the applicability and feasibility of our proposed method by solving a mobile payment platform selection problem in Ghana.     

Characterization of a high-resolution solid-state micropump that can be integrated into microfluidic systems

Ni–Mn–Ga is a magnetic shape memory (MSM) alloy that can strain up to 6 % when a magnetic field is applied to it. By applying a localized magnetic field to the MSM element, the strain can be precisely controlled and manipulated. By using Ni–Mn–Ga and a local magnetic field, an MSM micropump that is capable of controlling the flow within a microfluidic system has been developed. A computational fluid dynamics analysis illustrates the flow of the liquid at the outlet of the micropump and will be used to optimize future models of the pump. The performance of the MSM micropump, such as its flow rate and pumping pressure, is measured and presented in this study. Beyond its performance, there are also several advantages intrinsic to the MSM micropump. It is controlled by a magnetic field and is therefore contact-free. Depending upon the magnetic field, the MSM micropump can act as either a valve or a reversible pump. It is self-priming and capable of pumping gases as well as viscous liquids, and it has a simple design which consists primarily of the MSM alloy itself. Coupled with its scalability, it is clear that the MSM micropump is a strong candidate for an integratable flow control solution.     

Some q-rung interval-valued orthopair fuzzy Maclaurin symmetric mean operators and their applications to multiple attribute group decision making

In this paper, according to the Maclaurin symmetric mean (MSM) operator, the dual MSM (DMSM) operator and the q-rung interval-valued orthopair fuzzy set (q-RIVOFS), we develop some novel MSM operators under the q-rung interval-valued orthopair fuzzy environment, such as, the q-rung interval-valued orthopair fuzzy MSM operator, the q-rung interval-valued orthopair fuzzy weighted MSM (q-RIVOFWMSM) operator, the q-rung interval-valued orthopair fuzzy DMSM operator, and the q-rung interval-valued orthopair fuzzy weighted DMSM operator. In addition, some precious properties and numerical examples of these new operators are given in detail. These new operators have the advantages of considering the interrelationship of arguments and can deal with multiple attribute group decision-making problems with q-rung interval-valued orthopair fuzzy information. Finally, a reality example for green suppliers selection in green supply chain management is provided to demonstrate the proposed approach and to verify its rationality and scientific.     

Multi-criteria decision-making method based on single-valued neutrosophic linguistic Maclaurin symmetric mean operators

This paper investigates a wide range of generalized Maclaurin symmetric mean (MSM) aggregation operators, such as the generalized arithmetic MSM and the generalized geometric MSM, whose predominant characteristic is capturing the interrelationships among multi-input arguments. The single-valued neutrosophic linguistic set plays an essential role in decision making, which can serve as an extension of either a linguistic term set or a single-valued neutrosophic set. This study centers on multi-criteria decision-making (MCDM) issues in which criteria are weighed differently and criteria values are expressed as single-valued neutrosophic linguistic numbers. Based on this foundation, we extend a series of MSM aggregation techniques under single-valued neutrosophic linguistic environments and propose procedures for solving MCDM problems. We also explore the influence of parameters on aggregation results. Finally, we provide a practical example and conduct a comparison analysis between the proposed approach and other existing methods in order to verify the proposed approach and demonstrate its validity.

     

Pythagorean Fuzzy Maclaurin Symmetric Mean Operators in Multiple Attribute Decision Making

The Maclaurin symmetric mean (MSM) operator is a classical mean type aggregation operator used in modern information fusion theory, which is suitable to aggregate numerical values. The prominent characteristic of the MSM operator is that it can capture the interrelationship among the multiinput arguments. In this paper, we extend MSM to Pythagorean fuzzy environment to propose the Pythagorean fuzzy Maclaurin symmetric mean and Pythagorean fuzzy weighted Maclaurin symmetric mean operators. Then, some desirable properties and special cases of these operators are discussed in detail. Finally, a numerical example is provided to illustrate the feasibility of the proposed methods and deliver a comparative analysis.     

A support vector machine based MSM model for financial short-term volatility forecasting

Financial time series forecasting has become a challenge because of its long-memory, thick tails and volatility persistence. Multifractal process has recently been proposed as a new formalism for this problem. An iterative Markov-Switching Multifractal (MSM) model was introduced to the literature. It is able to capture many of the important stylized features of the financial time series, including long-memory in volatility, volatility clustering, and return outliers. The model delivers stronger performance both in- and out-of-sample than GARCH-type models in long-term forecasts. To enhance MSM’s short-term prediction accuracy, this paper proposes a support vector machine (SVM) based MSM approach which exploits MSM model to forecast volatility and SVM to model the innovations. To verify the effectiveness of the proposed approach, two stock indexes in the Chinese A-share market are chosen as the forecasting targets. Comparing with some existing state-of-the-art models, the proposed approach gives superior results. It indicates that the proposed model provides a promising alternative to financial short-term volatility prediction.     

Some power Maclaurin symmetric mean aggregation operators based on Pythagorean fuzzy linguistic numbers and their application to group decision making

The power average (PA) operator and Maclaurin symmetric mean (MSM) operator are two important tools to handle the multiple attribute group decision‐making (MAGDM) problems, and the combination of two operators can eliminate the influence of unreasonable information from biased decision makers (DMs) and can capture the interrelationship among any number of arguments. The Pythagorean fuzzy linguistic set (PFLS) is parallel to the intuitionistic linguistic set (ILS), which is more powerful to convey the uncertainty and ambiguity of the DMs than ILS. In this paper, we propose some power MSM aggregation operators for Pythagorean fuzzy linguistic information, such as Pythagorean fuzzy linguistic power MSM operator and Pythagorean fuzzy linguistic power weighted MSM (PFLPWMSM) operator. At the same time, we further discuss the properties and special cases of these operators. Then, we propose a new method to solve the MAGDM problems with Pythagorean fuzzy linguistic information based on the PFLPWMSM operator. Finally, some illustrative examples are utilized to show the effectiveness of the proposed method.     

基于GPU的zk-SNARK中多标量乘法的并行计算方法

针对zk-SNARK（zero-knowledge succinct non-interactive argument of knowledge）中计算最为耗时的多标量乘法（multi-scalar multiplication,MSM）,提出了一种基于GPU的MSM并行计算方案。首先,对MSM进行细粒度任务分解,提升算法本身的计算并行性,以充分利用GPU的大规模并行计算能力。采用共享内存对同一窗口下的子MSM并行规约减少了数据传输开销。其次,提出了一种基于底层计算模块线程级任务负载搜索最佳标量窗口的窗口划分方法,以最小化MSM子任务的计算开销。最后,对标量形式转换所用数据存储结构进行优化,并通过数据重叠传输和通信时间隐藏,解决了大规模标量形式转换过程的时延问题。该MSM并行计算方法基于CUDA在NVIDIA GPU上进行了实现,并构建了完整的零知识证明异构计算系统。实验结果表明：所提出的方法相比目前业界最优的cuZK的MSM计算模块获得了1.38倍的加速比。基于所改进MSM的整体系统比业界流行的Bellman提升了186倍,同时比业界最优的异构版本Bellperson提升了1.96倍,验证了方法的有效性。     

输入缓存Clos网络中分布式正交分路路由算法

提出了一种采用输入缓存MSM结构的Clos网络,该结构适用于高速交换网络。提出了这一结构中的路由算法,该算法采用正交分路的方法来减小网络内部的冲突,引入路由优先级来提高网络内部的链路利用率,使用优先级轮转来均衡网络内部负载。针对这一路由算法,还给出了与之对应的信元调度算法。仿真表明,尽管采用共享缓存的MSM结构内部使用了很高的加速比,但是采用了正交分路的路由算法后,输入缓存MSM结构,可以获得比共享缓存MSM结构更好的时延及吞吐性能,更适合在高速大容量多端口的路由器或交换机中采用。