Modeling and simulation of temperature drift for ISFET-based pH sensor and its compensation through machine learning techniques

The paper presents modeling and simulation of ion-sensitive field-effect transistor (ISFET)-based pH sensor with temperature-dependent behavioral macromodel and proposes to compensate the temperature drift in the sensor using intelligent machine learning (ML) models. The macromodel is built using SPICE by introducing electrochemical parameters in a metal-oxide-semiconductor field-effect transistor (MOSFET) model to simulate ISFET characteristics. We account for the temperature dependence of electrochemical and semiconductor parameters in our macromodel to increase its robustness. The macromodel is then exported as a subcircuit element, which is used to design the readout interface circuit. A simple constant-voltage, constant-current (CVCC) topology is utilized to generate the data for temperature drift in ISFET pH sensor, which is used to train and test state-of-the-art ML-based regression models in order to compensate the drift behavior. The experimental results demonstrate that the random forest (RF) technique achieves the best performance with very high correlation and low error rate. Corresponding curves for output signal using the trained models show highly temperature-independent characteristics when tested for pH 2, 4, 7, 10, and 12, and we obtained a root mean squared error (RMS) variation of ΔpH ≤ 0.024 over a temperature range of 15°C to 55°C in comparison with ΔpH ≤ 1.346 for uncompensated output signal. This work establishes the framework for integration of ML techniques for drift compensation of ISFET chemical sensor to improve its performance.     

Dual‐polarized high gain resonant cavity antenna for radio frequency energy harvesting

A Fabry pérot antenna with a multilayer superstrate having nonuniform unit cells has been investigated as a receiving antenna for radio frequency (RF) energy harvesting applications. Here, the primary radiator is selected as a dual‐polarized aperture coupled microstrip antenna with a double‐layer superstrate. This antenna excites orthogonal polarizations, vertical (V) and horizontal (H) in the frequency band of 6.2 and 5.8 GHz, respectively, due to the presence of two orthogonal H‐shaped slots in its ground plane. The proposed antenna provides a gain enhancement of 9.8 and 10.1 dBi at the respective frequencies. The rectifying circuit is designed for a frequency of 5.8 GHz using a voltage doubler topology. The circuit provides a power conversion efficiency of 41% at 0 dBm input power.     

High Performance Lithium‐Ion Batteries Using Layered 2H‐MoTe2 as Anode

The major challenges faced by candidate electrode materials in lithium‐ion batteries (LIBs) include their low electronic and ionic conductivities. 2D van der Waals materials with good electronic conductivity and weak interlayer interaction have been intensively studied in the electrochemical processes involving ion migrations. In particular, molybdenum ditelluride (MoTe₂) has emerged as a new material for energy storage applications. Though 2H‐MoTe₂ with hexagonal semiconducting phase is expected to facilitate more efficient ion insertion/deinsertion than the monoclinic semi‐metallic phase, its application as an anode in LIB has been elusive. Here, 2H‐MoTe₂, prepared by a solid‐state synthesis route, has been employed as an efficient anode with remarkable Li⁺ storage capacity. The as‐prepared 2H‐MoTe₂ electrodes exhibit an initial specific capacity of 432 mAh g^?1 and retain a high reversible specific capacity of 291 mAh g^?1 after 260 cycles at 1.0 A g^?1. Further, a full‐cell prototype is demonstrated by using 2H‐MoTe₂ anode with lithium cobalt oxide cathode, showing a high energy density of 454 Wh kg^?1 (based on the MoTe₂ mass) and capacity retention of 80% over 100 cycles. Synchrotron‐based in situ X‐ray absorption near‐edge structures have revealed the unique lithium reaction pathway and storage mechanism, which is supported by density functional theory based calculations.     

Reliability of fine-pitch through-vias in glass interposers and packages for high-bandwidth computing and communications

Glass is an ideal substrate material to enable 2.5D and 3D packaging of ICs at low cost and high performance. However, it is a brittle material and is prone to failures during fabrication and operation. Large coefficient of thermal expansion (CTE) mismatch between copper and glass leads to thermomechanical stresses that can lead to glass cracking and delamination from glass interfaces. This paper focuses on modeling and reliability characterization of copper-plated through-package-vias (TPV) in glass packages. Thermomechanical simulations were carried out to obtain design guidelines for reliable TPVs in glass. Test-vehicles with different glass thicknesses and copper TPV fabrication conditions were fabricated for thermal cycling tests, resistance monitoring and failure analysis. The reliability characterization results showed good thermomechanical reliability of TPVs in ultra-thin glass panels.     

EAAM: Energy-aware application management strategy for FPGA-based IoT-Cloud environments

The Journal of Supercomputing - An efficient integration of Internet of Things (IoT) and cloud computing techniques accelerates the evolution of next-generation smart environments (e.g., smart...     

A standard deviation based firefly algorithm for multi-objective optimization of WEDM process during machining of Indian RAFM steel

Non-conventional machining processes always suffer due to their low productivity and high cost. However, a suitable machining process should improve its productivity without compromising product quality. This implies the necessity to use efficient multi-objective optimization algorithm in non-conventional machining processes. In this present paper, an effective standard deviation based multi-objective fire-fly algorithm is proposed to predict various process parameters for maximum productivity (without affecting product quality) during WEDM of Indian RAFM steel. The process parameters of WEDM considered for this study are: pulse current (I), pulse-on time (T _on), pulse-off time (T _off) and wire tension (WT).While, cutting speed (CS) and surface roughness (SR) were considered as machining performance parameters. Mathematical models relating the process and response parameters had been developed by linear regression analysis and standard deviation method was used to convert this multi objective into single objective by unifying the responses. The model was then implemented in firefly algorithm in order to optimize the process parameters. The computational results depict that the proposed method is well capable of giving optimal results in WEDM process and is fairly superior to the two most popular evolutionary algorithms (particle swarm optimization algorithm and differential evolution algorithm) available in the literature.

     

3D Face Recognition Using a Fusion of PCA and ICA Convolution Descriptors

Neural Processing Letters - This paper introduces a hybrid filter bank-based convolutional network to develop a 3D face recognition system in different orientations. The filter banks approach has...     

信号调制系统实现角位移测量（英文）

采用基于定时器LM555的非稳态多谐振荡器和通用频数转换设计了一种变面积式电容传感器信号调制系统用于角位移测量。变面积式电容器连接在基于定时器的非稳态电路内,其角位移的变化引起电容的变化,进而引起定时器电路输出时间周期的变化。定时器电路输出波形的时间周期与电容呈线性关系,因而与角位移也是线性关系。定时器输出经通用频数转换器进一步处理后可用于测量。实验结果显示,时间周期与角位移在0-180°范围内呈线性关系,将不确定度与平均时间周期相关联,即为平均标准差,亦称为标准误差,其值为±0.023μs。该测量系统使用简单,可用于电子和工业仪器中。     

Estimating weak ratiometric signals in imaging data. II. Meta-analysis with multiple, dual-channel datasets

Ratiometric fluorescent indicators are used for making quantitative measurements of a variety of physiological variables. Their utility is often limited by noise. This is the second in a series of papers describing statistical methods for denoising ratiometric data with the aim of obtaining improved quantitative estimates of variables of interest. Here, we outline a statistical optimization method that is designed for the analysis of ratiometric imaging data in which multiple measurements have been taken of systems responding to the same stimulation protocol. This method takes advantage of correlated information across multiple datasets for objectively detecting and estimating ratiometric signals. We demonstrate our method by showing results of its application on multiple, ratiometric calcium imaging experiments.