A novel low power hybrid cache using GC-EDRAM cells

In a typical embedded CPU, large on-chip storage is critical to meet high performance requirements. However, the fast increasing size of the on-chip storage based on traditional SRAM cells makes the area cost and energy consumption unsustainable for future embedded applications. Replacing SRAM with DRAM on the CPU’s chip is generally considered not worthwhile because DRAM is not compatible with the common CMOS logic and requires additional processing steps beyond what is required for CMOS. However a special DRAM technology, Gain-Cell embedded-DRAM (GC-eDRAM)  [1], [2], [3] is logic compatible and retains some of the good properties of DRAM (small and low power). In this paper we evaluate the performance of a novel hybrid cache memory where the data array, generally populated with SRAM cells, is replaced with GC-eDRAM cells while the tag array continues to use SRAM cells. Our evaluation of this cache demonstrates that, compared to the conventional SRAM-based designs, our novel architecture exhibits comparable performance with less energy consumption and smaller silicon area, enabling the sustainable on-chip storage scaling for future embedded CPUs.     

End-to-End Multiview Gesture Recognition for Autonomous Car Parking System

The use of hand gestures can be the most intuitive human-machine interaction medium.The early approaches for hand gesture recognition used device-based methods....     

Estimation of Antenna Correlation Coefficient of N-Port Lossy MIMO Array

This paper proposes a simple yet accurate method for estimating the antenna correlation coefficient (ACC) of a high-order multiple-input multiple-output (MIMO) antenna. The conventional method employed to obtain the ACC from three-dimensional radiation patterns is costly and difficult to measure. An alternate method is to use the S-parameters, which can be easily measured using a network analyzer. However, this method assumes that the antennas are highly efficient, and it is therefore not suitable for lossy MIMO antenna arrays. To overcome this limitation, we define and utilize the non-coupled radiation efficiency in the S-parameter-based ACC formula. The accuracy of the proposed method is verified by the simulation results of a 4-port highly coupled lossy MIMO array. Further, the proposed method can be applied to N-port arrays by expanding the calculation matrix.     

青海五龙沟金矿中金的赋存状态研究

青海五龙沟金矿石贵金属矿物以自然金为主，金品位为2.43 g/t，伴生低品位银，属于微细粒-超微细粒浸染型含碳、砷的极难选冶金矿石。为给该矿石的开发利用提供依据，采用X荧光分析法、化学分析、矿相显微镜、X射线衍射分析及MLA矿物自动定量系统等手段对矿石的化学成分、结构构造、矿物组成及金的赋存状态进行研究。结果表明：①矿石有价元素为金、银，有害杂质砷、碳含量较高，含金矿物主要有自然金及方锑金矿、黑铋金矿、碲金银矿等；②金粒大多数呈显微、超显微分散状态包含于毒砂及斜方砷铁矿中，其次包含于绢云母、绿泥石和石英等脉石矿物中，少数与黄铁矿和磁黄铁矿连生或包裹，显微镜中可见金不多，粒度大多小于1 μm；③金嵌布粒度以微细粒为主，98.45%金粒粒度小于0.04 mm；黄铁矿、毒砂和磁黄铁矿的嵌布粒度以中细粒为主，均处于浮选的适宜范围；④金的选矿回收与硫砷化物的回收密切相关，尤其是要重视毒砂的回收。研究结果可以为该金矿石的合理开发利用提供技术依据。     

FPGA-based architecture to estimate the input glucose in a dark fermenter using a super-twisting observer

This article presents a digital architecture design for a Super-Twisting Observer (STO) implemented in a Field-Programmable Gate Array (FPGA). The STO is robust in the presence of uncertainties, which makes it suitable to estimate unknown inputs present in biological systems and applications based on sensorless control accurately. The proposed STO is used to estimate the glucose concentration in the inflow of a hydrogen production bioreactor (e.g., dark fermenter). The dark fermenter is not generally recognized as a swift process. Therefore, the observer digital architecture design criteria aim to optimize hardware resources and reduce power consumption through an iterative approach to perform internal arithmetic operations efficiently. Besides, an analysis of the errors produced by internal operations, observer discretization, and fixed-point data representation is presented and discussed. Numerical results showed that embedding the super-twisting observer into the FPGA is a reliable, low-power consumption, and efficient alternative to estimate the input glucose in a dark fermenter.     

Emotion recognition at the edge with AI specific low power architectures

Nowadays Deep Learning is applied in almost every research field and helps getting amazing results in a great number of challenging tasks. The main problem is that this kind of learning and consequently Neural Networks that can be defined deep, are resource intensive. They need specialized hardware to perform computation in a reasonable time. Many tasks are mandatory to be as much real-time as possible . It is needed to optimize many components such as code, algorithms, numeric accuracy and hardware, to make them “efficient and usable”. All these optimizations can help us to produce incredibly accurate and fast learning models. The paper reports a study in this direction for the challenging face detection and emotion recognition tasks.     

基于AVR单片机的风电机组自动消防控制系统

野外或海上安装的风电系统如发生火灾将造成严重的损失,急需装备自动消防控制系统。面向风电机舱的消防安全,研制基于AVR单片机嵌入式技术的用于火灾感应和检测以及远程监控的消防控制系统。采用了温度、烟度以及图像等信息感应火灾情况,通过电启动超细干粉灭火装置进行自动灭火。最后利用RS485总线和光纤网络将单片机检测仪和远程控制器连接起来,构成完善的风力发电场消防报警和控制系统。初步试验结果表明该系统达到了设计目标,可用于风电系统的消防安全控制。     

基于ARM&FPGA的玻璃刻花机控制器的设计

在分析玻璃刻花工艺的基础上,研究了以嵌入式微处理器ARM和FPGA为核心架构的玻璃刻花机控制器硬件平台,以及以Linux和Xenomai构建的实时操作系统为软件框架的软件平台。针对玻璃刻花加工对同步控制、误差补偿和加工工艺的要求,研究了相关的功能模块,完成玻璃刻花机控制器的设计开发。     

Qt Embedded环境下柱上开关控制器的人机接口设计

为了解决传统柱上开关智能化程度低的缺点,研发了一种新型智能柱上开关控制器。针对新型智能柱上开关控制器所需人机接口的要求,讨论了基于 Qt Embedded的智能柱上开关控制器人机界面的设计,并提供了一种灵活的按键控制人机界面的方法。可供相关的工程设计参考。     

基于STM32F4的时栅数控分度转台控制系统设计

为了提高时栅位移传感器数控转台的控制定位精度,针对步进电机载物运动时的高频出力不足、低频振动、失步、堵转等现象,提出了一种基于STM32F4的数控分度转台控制系统。系统通过对硬件、软件的设计建立了以STM32F4微处理器为控制核心、时栅角位移传感器为反馈元件的全闭环控制系统,有效的解决了步进电机的精确控制问题。经实验验证,实现了高稳定性、高速度、高精度的时栅数控转台定位,定位精度达到了±2＂。