A model study of teaching method reform of computer laboratory course integrating internet of things technology.

The Internet of Things (IoT) is gradually changing the way teaching and learning take place in on-campus programs. In particular, face capture services improve student concentration to create an efficient classroom atmosphere by using face recognition algorithms that support end devices. However, reducing response latency and executing face analysis services effectively in real-time is still challenging. For this reason, this paper proposed a pedagogical model of face recognition for IoT devices based on edge computing (TFREC). Specifically, this research first proposed an IoT service-based face capture algorithm to optimize the accuracy of face recognition. In addition, the service deployment method based on edge computing is proposed in this paper to obtain the best deployment strategy and reduce the latency of the algorithm. Finally, the comparative experimental results demonstrate that TFREC has 98.3% accuracy in face recognition and 72 milliseconds in terms of service response time. This research is significant for advancing the optimization of teaching methods in school-based courses, meanwhile, providing beneficial insights for the application of face recognition and edge computing in the field of education.

Modeling of Charge-to-Breakdown with an Electron Trapping Model for Analysis of Thermal Gate Oxide Failure Mechanism in SiC Power MOSFETs.

The failure mechanism of thermal gate oxide in silicon carbide (SiC) power metal oxide semiconductor field effect transistors (MOSFETs), whether it is field-driven breakdown or charge-driven breakdown, has always been a controversial topic. Previous studies have demonstrated that the failure time of thermally grown silicon dioxide (SiO2) on SiC stressed with a constant voltage is indicated as charge driven rather than field driven through the observation of Weibull Slope ß. Considering the importance of the accurate failure mechanism for the thermal gate oxide lifetime prediction model of time-dependent dielectric breakdown (TDDB), charge-driven breakdown needs to be further fundamentally justified. In this work, the charge-to-breakdown (QBD) of the thermal gate oxide in a type of commercial planar SiC power MOSFETs, under the constant current stress (CCS), constant voltage stress (CVS), and pulsed voltage stress (PVS) are extracted, respectively. A mathematical electron trapping model in thermal SiO2 grown on single crystal silicon (Si) under CCS, which was proposed by M. Liang et al., is proven to work equally well with thermal SiO2 grown on SiC and used to deduce the QBD model of the device under test (DUT). Compared with the QBD obtained under the three stress conditions, the charge-driven breakdown mechanism is validated in the thermal gate oxide of SiC power MOSFETs.

An Investigation of Body Diode Reliability in Commercial 1.2 kV SiC Power MOSFETs with Planar and Trench Structures.

The body diode degradation in SiC power MOSFETs has been demonstrated to be caused by basal plane dislocation (BPD)-induced stacking faults (SFs) in the drift region. To enhance the reliability of the body diode, many process and structural improvements have been proposed to eliminate BPDs in the drift region, ensuring that commercial SiC wafers for 1.2 kV devices are of high quality. Thus, investigating the body diode reliability in commercial planar and trench SiC power MOSFETs made from SiC wafers with similar quality has attracted attention in the industry. In this work, current stress is applied on the body diodes of 1.2 kV commercial planar and trench SiC power MOSFETs under the off-state. The results show that the body diodes of planar and trench devices with a shallow P+ depth are highly reliable, while those of the trench devices with the deep P+ implantation exhibit significant degradation. In conclusion, the body diode degradation in trench devices is mainly influenced by P+ implantation-induced BPDs. Therefore, a trade-off design by controlling the implantation depth/dose and maximizing the device performance is crucial. Moreover, the deep JFET design is confirmed to further improve the body diode reliability in planar devices.

A New Cell Topology for 4H-SiC Planar Power MOSFETs for High-Frequency Switching.

A new cell topology named the dodecagonal (a polygon with twelve sides, short for Dod) cell is proposed to optimize the gate-to-drain capacitance (Cgd) and reduce the specific ON-resistance (Ron,sp) of 4H-SiC planar power MOSFETs. The Dod and the octagonal (Oct) cells are used in the layout design of the 650 V SiC MOSFETs in this work. The experimental results confirm that the Dod-cell MOSFET achieves a 2.2× lower Ron,sp, 2.1× smaller high-frequency figure of merit (HF-FOM), higher turn on/off dv/dt, and 29% less switching loss than the fabricated Oct-cell MOSFET. The results demonstrate that the Dod cell is an attractive candidate for high-frequency power applications.

Effects of JFET Region Design and Gate Oxide Thickness on the Static and Dynamic Performance of 650 V SiC Planar Power MOSFETs.

650 V SiC planar MOSFETs with various JFET widths, JFET doping concentrations, and gate oxide thicknesses were fabricated by a commercial SiC foundry on two six-inch SiC epitaxial wafers. An orthogonal P+ layout was used for the 650 V SiC MOSFETs to reduce the ON-resistance. The devices were packaged into open-cavity TO-247 packages for evaluation. Trade-off analysis of the static and dynamic performance of the 650 V SiC power MOSFETs was conducted. The measurement results show that a short JFET region with an enhanced JFET doping concentration reduces specific ON-resistance (Ron,sp) and lowers the gate-drain capacitance (Cgd). It was experimentally shown that a thinner gate oxide further reduces Ron,sp, although with a penalty in terms of increased Cgd. A design with 0.5 µm half JFET width, enhanced JFET doping concentration of 5.5×1016 cm-3, and thin gate oxide produces an excellent high-frequency figure of merit (HF-FOM) among recently published studies on 650 V SiC devices.

A Brief Talk on the Design of Biopharmaceutical Separation and Purification Technology Course.

Biological separation and purification technology is the basic technology of modern biotechnology, which is widely used in the pharmaceutical industry, especially the biopharmaceutical industry. In recent years, the biopharmaceutical industry has had a lot of room for development in the development of science and technology in South Korea, and the research on biopharmaceutical equipment and pharmaceutical technology has also achieved good research results. This article proposes a brief discussion on the design of biopharmaceutical separation and purification technology courses. In this study, by analyzing the synthesis potential of the secondary metabolites of the strain, using the α-glucosidase inhibition rate as an inspection indicator, the fermentation medium of the strain was optimized, and batch fermentation was carried out, and then, the metabolites were separated and purified, and the following conclusion was obtained: the α-glucosidase inhibition rate of the crude extract of the strain in the optimized fermentation medium is 35% higher than that of the initial medium.

Research on the Impact of Regional Economy on Industrial Development from the Perspective of Big Data.

In order to study the driving force of China's rapid economic development in the past ten years, the study takes Guizhou, Yunnan, and Guangxi as a case study, focusing on the big data assets exchange (GBDEx) and Beibu Gulf Economic Zone, and discusses the impact of Internet plus economic and government data and the big data system on regional economy. Finally, it is believed that the Internet and big data fully avoid the disadvantages of traffic distance between the western region and the eastern region, make full and efficient cooperation between enterprises and institutions in the central and western regions and Chinese and foreign economic entities, and strengthen the control of economic behavior from the big data level with the support of the service-oriented government. The information entropy output from the Internet big data system has led to a significant entropy reduction process in China's economic environment and a more orderly economic system, which is also an important reason for the rapid development of China's economy.

Simulation of biological ion channels with technology computer-aided design.

Computer simulations of realistic ion channel structures have always been challenging and a subject of rigorous study. Simulations based on continuum electrostatics have proven to be computationally cheap and reasonably accurate in predicting a channel's behavior. In this paper we discuss the use of a device simulator, SILVACO, to build a solid-state model for KcsA channel and study its steady-state response. SILVACO is a well-established program, typically used by electrical engineers to simulate the process flow and electrical characteristics of solid-state devices. By employing this simulation program, we have presented an alternative computing platform for performing ion channel simulations, besides the known methods of writing codes in programming languages. With the ease of varying the different parameters in the channel's vestibule and the ability of incorporating surface charges, we have shown the wide-ranging possibilities of using a device simulator for ion channel simulations. Our simulated results closely agree with the experimental data, validating our model.

Detection of dielectrophoretic driven passage of single cells through micro-apertures in a silicon nitride membrane.

Silicon (Si) microstructures are fabricated comprising a micro-aperture (10-25 microm) in a 1.2 kA silicon nitride membrane connecting two microfluidic compartments. Dielectrophoretic forces are created on-chip, which guide the passage of single CHO cells through the microaperture. When a cell dielectrophoretically traverses the aperture, there is a decrease in the background ionic current. These current fluctuations are recorded under varying cell concentrations, micro-aperture sizes, and applied voltages. This work shows the feasibility of building silicon-based bioparticle detectors with nanoscale apertures for sensing the translocation of cells, proteins, and even single-stranded DNA.

Parameter-extraction of a two-compartment model for whole-cell data analysis.

Neuronal modeling of patch-clamp data is based on approximations which are valid under specific assumptions regarding cell properties and morphology. Certain cells, which show a biexponential capacitance transient decay, can be modeled with a two-compartment model. However, for parameter-extraction in such a model, approximations are required regarding the relative sizes of the various model parameters. These approximations apply to certain cell types or experimental conditions and are not valid in the general case. In this paper, we present a general method for the extraction of the parameters in a two-compartment model without assumptions regarding the relative size of the parameters. All the passive electrical parameters of the two-compartment model are derived in terms of the available experimental data. The experimental data is obtained from a DC measurement (where the command potential is a hyperpolarizing DC voltage) and an AC measurement (where the command potential is a sinusoidal stimulus on a hyperpolarized DC potential) performed on the cell under test. Computer simulations are performed with a circuit simulator, XSPICE, to observe the effects of varying the two-compartment model parameters on the capacitive transients of the current response. Our general solution for the parameter-estimation of a two-compartment model may be used to model any neuron, which has a biexponential capacitive current decay. In addition, our model avoids the need for simplifying and perhaps erroneous approximations. Our equations may be easily implemented in hardware/software compensation schemes to correct the recorded currents for any series resistance or capacitive transient errors. Our general solution reduces to the results of previous researchers under their approximations.